Polymerization - Science topic

Please compare the two electrodes to see if you have successfully produced the polymer film on the GCE. Additionally, confirm that the optimization settings you utilized for your electrodeposition were adequate. If you do have the polymer, you could also try the drop-casting or chemical deposition methods; however, these would be challenging to use with monomer. Another issue is that you used a large amount of probe concentration. In reality, it would be advised to use 1–10 mmol L–1 of equimolar FFC. Thank you.

Thanks, @Mario Castelán, for your thoughts. This can be done, but we might not have enough data in the literature just yet to train these. And also, with machine learning, we can predict the outcome but exactly can we obtain the quantitative data?

Dear all, if you have clear and homogeneous solution, then you may expect interactions. Solubility means there is such mutual interactions. Both water and acetic acid are polars, that's why they are soluble, the same would be with residual monomers, which are automatically polar since they are soluble in water. My Regards

Hi, In small quantities, local overheating is possible. Try using a higher boiling alcohol

Ams Jekhan Common solvents for dissolving reduced graphene oxide (rGO) include N,N-Dimethylformamide (DMF), ammonia solution, hydroquinone, hydroxyrazine hydrate, and ascorbic acid.

You are most welcome

"I want to optimize a structure of a polymer using DFT method with Gaussian 09 but the problem is that I can only optimize either the monomer or the complete structure of the polymer. Also, my question is how to draw the polymer structure in the GaussView interface. Please help me if you have an example, thank you."

Dear Jigui Li, you can use radiation polymerization, it answers all your conditions and criteria. Free radicals are generated in situ from the solvent and/or the monomers, i. e., no need to use a radical type initiator. My Regards

I would say that width of Tan D peaks in DMA is related to distribution width of the associated relaxing elements. In the case of glass transition, relaxing elements are mobile chain segments in amorphous regions. The wider is the distribution of the segments in terms of their mobility (length, rigidity, packing density, free volume, intermolecular interactions etc.) the wider is the DMA peak. Accordingly, widening of the peak in crosslinked systems may indicate nonuniform crosslinking structure: presence of domains differing in the crosslinking density (length of the segments between the crosslinks).

It depends on the nature of drug and log P value hydrophilic/lipiphilic) with this "Like Dissolved By Like".

Basically for tablet you add HPMc and Eudragit suitable for the sustainable formulation.

Kaushik Shandilya thank you so much sir

Hello Victoria Gillan . Have you got a solution for the matrigel dissolving issue? I am currently facing the same problem. I dissolved the cell pellet in a 1:1 Matrigel: Media ratio and allowed it to polymerize for 10 minutes in a 37C incubator by inverting the plate. When the media is added, the dome dissolved in some wells and becomes soft in others. When observed the next day, all the domes were dissolved. Kindly help me out.

Thanks for your response Hamed Zahraee , Is the on the fly approach you mentioned can be used to constrain the polymer surface area at different intervals

Dear Siyanand Kumar Chaudhary, find the average degree of polymerization by deviding 12000 by the mass of the repeating unit which is the same as that of the monomer. What you find is the number of COOH acid group per chain. If you know chain end groups, more accuracy will be brought to your calculation, since the MW weight you are using is not too high to neglect the mass of the chain end-groups. Once you determine the equivalent of COOH groups, then you can prepare any concentration. The one you are targetting is too low, you can reach it by dilution of a known small concentration. By the way, the binding energies or affinity of PAA to metal ions was studied extensively decades ago, good bibliographic research is to be done on PAA polyelectrolytes to avoid repeating what was already done. My Regards

Ankit Mishra THF and chloroform are also toxic for medical or food technological applications. I am looking specifically for green solvents to dissolve PLA efficiently and effectively. If you do know any, please share it here. Thanks

You could try using moltemplate.

Dear all, there are many possibilities to get the required MW. If you have the kinetics curve of the polymerization reaction, i. e., MW vs time or MW vs %conversion, then all to do is to quench the reaction at the time or % conversion corresponding to the targeted MW. The second solution is to do dialysis fractionation with a memebrane with the specific MW cut-off. The third possibility is to do mechanical degradation by shearing either by high speed agitator or passing through low porosity sieves.

If you want to avoid these extra work, choose a solvent with high transfer constant, and reduce the polymerization temperature. Starve feeding of the monomer may also help to reach a moderate MW. My Regards

Dear Riswat Musbau, why not trying the opposite strategy, i. e., using PEG-macroinitiator to copolymerize the epoxide-anhydride. The following free access review may help as it deals with ROP copolymerization of polyesters and polycarbonates. My Regards

10.1039/C4CC10113H

Hey there P. Saravana Kumari! Let's dive into it. To dissolve cellulose and create a transparent film, you P. Saravana Kumari can use an ionic liquid like 1-ethyl-3-methylimidazolium acetate ([EMIM][OAc]). It's known for its ability to dissolve cellulose effectively, resulting in a clear solution.

Now, for turning the dissolved polymer into a gel, you P. Saravana Kumari might want to consider using a gelling agent like gelatin or agarose. These substances can form a gel when the solution cools down or undergoes a change in pH.

As for plasticizers, you P. Saravana Kumari could go for something like glycerol or polyethylene glycol (PEG). These are commonly used to increase the flexibility and durability of the cellulose film while maintaining its transparency.

Hope this helps! Let me know if you P. Saravana Kumari need more details or have any other questions.

Boubaker Zaidi How many monomer units do we need to consider? Also, iodide ions exist in many forms. Where should we place the iodide ions relative to the monomer?

Phys Chem Chem Phys. 2023 Aug 2; 25(30): 20657–20667.Published online 2023 May 24. doi: 10.1039/d2cp05020jPMCID: PMC10395002PMID: 37482883Revisiting the origin of the bending in group 2 metallocenes AeCp2 (Ae = Be–Ba)† Tetiana Sergeieva,a T. Ilgin Demirer,a Axel Wuttke,b Ricardo A. Mata,📷b André Schäfer,📷a Gerrit-Jan Linker,📷c and Diego M. Andrada📷aAuthor information Article notes Copyright and License information PMC DisclaimerSupplementary MaterialsAssociated Data Go to:Abstract Metallocenes are well-established compounds in organometallic chemistry, and can exhibit either a coplanar structure or a bent structure according to the nature of the metal center (E) and the cyclopentadienyl ligands (Cp). Herein, we re-examine the chemical bonding to underline the origins of the geometry and stability observed experimentally. To this end, we have analysed a series of group 2 metallocenes [Ae(C5R5)2] (Ae = Be–Ba and R = H, Me, F, Cl, Br, and I) with a combination of computational methods, namely energy decomposition analysis (EDA), polarizability model (PM), and dispersion interaction densities (DIDs). Although the metal–ligand bonding nature is mainly an electrostatic interaction (65–78%), the covalent character is not negligible (33–22%). Notably, the heavier the metal center, the stronger the d-orbital interaction with a 50% contribution to the total covalent interaction. The dispersion interaction between the Cp ligands counts only for 1% of the interaction. Despite that orbital contributions become stronger for heavier metals, they never represent the energy main term. Instead, given the electrostatic nature of the metallocene bonds, we propose a model based on polarizability, which faithfully predicts the bending angle. Although dispersion interactions have a fair contribution to strengthen the bending angle, the polarizability plays a major role.Metallocenes are well-established compounds in organometallic chemistry, which can exhibit either a coplanar structure or a bent structure according to the nature of the metal center (E) and cyclopentadienyl ligands (Cp).📷Go to:Introduction More than seventy years ago, Kealy, Pauson, Miller, Tebboth and Tremaine described ferrocene Fe(Cp)2 for the first time, laying the foundation for research on the metallocene family.1–10 Over the years, these compounds have evolved from only a curiosity into well-recognized reagents in organometallic chemistry, with applications ranging from coordination chemistry to homogenous catalysis and even industrial processes.11 To date, many examples of sandwich- or half-sandwich-type complexes with the formula E(Cp)n (n = 1–4) have been prepared and structurally characterized, in which E is a main-group element or a transition metal.11 In particular, their structures have drawn much attention as the understanding of the bonding provides guidelines for engineering their stoichiometric and catalytic reactivity.Attempts for modelling metallocene structures were developed parallel to the structural elucidation of ferrocene, and understanding the chemical bonding between the central atom and the cyclopentadienyl ligands is challenging using the existing heuristic models.7–9 Originally, the bond between the central iron atom and the Cp rings was assumed to be an electron sharing σ-type (C–Fe–C), given the lack of X-ray analysis, although the possibility of an ionic interaction ([Fe2+] [Cp−]2) was discussed.1 However, the surprisingly high thermal stability and its remarkable chemical inertness toward acids and bases could not be explained with these proposed bonding modes. Independently, Fischer3 and a group of scientists including Wilkinson, Rosenblum, Whiting, and Woodward10 proposed the metal–ligand interaction as a π-complexation. The subsequent analysis by Pfab, Eiland and Pepinsky confirmed the η5 binding pattern and the 6π electron aromatic character of the Cp ligands.4 Shortly after, Orgel used molecular orbital (MO) theory to explain the Fe–Cp bonding in ferrocene. The binding interaction was explained as formed by two “covalent–ionic” bonds resulting from the mixing of metals with Cp− orbitals, and two “donor” bonds, when electrons located at the dx2−y2, dxy orbitals of iron donate into vacant antibonding orbitals of the Cp ligands.5The first electronic structure description was reported about 20 years after the structure elucidation.12,13 Although its η5 coordination was reproduced at the Hartree–Fock (HF) level, the Fe–C bond lengths were poorly predicted.14 Years later, Koch, Jørgensen, and Helgaker achieved a better theoretical structure by performing CCSD and CCSD(T) calculations.15 Many theoretical calculations have been reported to provide quantitative and qualitative insights into the bonding nature of metallocenes. The extension of the Dewar–Chatt–Duncanson model for ferrocene allows for the discussion of the chemical bond in terms of donor–acceptor interactions. With a strong electrostatic nature (51%), the covalent part is predicted as π-donation from MOs of the Cp− ligands to the empty orbitals of the Fe2+ ion and a back donation from the Fe to the π* orbitals of the ligands.16The replacement of Fe with main-group elements from the s- or p-block, in particular with alkaline earth metals of group 2 (Ae), or heavy elements of group 14, has attracted much attention in the light of their preferred oxidation state of +2, ever since Fischer and co-workers reported magnesocene,17 calcocene,18 stannocene,19 and plumbocene,20 just a few years after the discovery of ferrocene.21–24 A common observation was a more labile E–Cp bond, which was explained by the weaker π-type interaction in view of the absence of d-orbitals on the bonding. Notably, the bonding nature changes from 49% covalent in Cp2Fe to being predominantly ionic in the case of s-block metallocenes and slightly more covalent when the central atom is a p-block element.16,25Aside from the bond nature, numerous reports attempted to explain the geometrical model of sandwich complexes. A general observation in metallocene chemistry is that structures have either a coplanar or a bent orientation of the Cp rings relative to the central atom. While the classical ferrocene Fe(Cp)2 and Fe(Cp*)2 ligands are clearly coplanar, other complexes exhibit a bent structure, i.e. Sn(Cp)2 and Pb(Cp)2. Such a distortion has been ascribed to the presence of a lone-pair at the central atom following the traditional valence-shell electron-pair-repulsion (VSEPR) model.26 However, this does not account for the subtleties of orbital interactions that influence molecular shapes and thus cannot justify bend geometries of many other complexes, the so-called non-VSEPR structures, among them are heavy alkaline earth metals (Ca, Sr, and Ba) sandwich compounds.Numerous models aiming at a general understanding of the structure, bonding and reactivity of such molecules have been proposed. The findings from experimental and computational investigations regarding the reason for the bending of metallocenes of heavier alkaline earth metals of group 2, which does not follow the valence shell electron pair repulsion theory model's prediction, can be categorized into four groups (Fig. 1):📷Fig. 1Illustration of models used to explain the bending of metallocenes. (A) Molecular orbital theory model (i). (B) Polarization model (ii). (C) Weak interaction concept (iii). (D) Agostic interaction model (iv).(i) Molecular orbital (MO) theory model. In 1953, Walsh27 proposed a molecular orbital diagram and linked the angle of AB2 molecules as a function of molecular orbital energies. Later, Hayes addressed the bending of heavy alkaline-earth dihalides by evoking this diagram, although with some modifications.28 The authors suggested to take unoccupied d-orbitals of Ca, Sr and Ba into account. This was supported by the energetics of the s-, p- and d-orbitals of these elements. The d-orbitals of Be and Mg lay energetically above the level of the p-orbitals and hence do not have a strong participation in binding. Thus, the symmetry of the valence p-orbitals leads to a coplanar structure for a better orbital overlap. In contrast, the energetic arrangement of Ca, Sr and Ba orbitals is different, which results in the contribution of the d-orbitals to the Ae–Cp bonding with an optimal overlap corresponding to bent geometries.(ii) Polarization model. Klemperer and co-workers observed a permanent electric dipole moment for monomeric dihalides of heavy alkaline earth elements, suggesting a bent arrangement.29 This finding was linked to the polarized-ion model, where large cations may be significantly polarized by anions due to charge–dipole and dipole–dipole interactions. In fact, these simple classical arguments were drawn by Debye to give a qualitative description for the angle in H2O.30 As such, molecular bending is related to the polarizability of the central atom and the polarizing power of the ligands. Gigli applied the polarizable Rittner type ion model to develop a quantitative prediction of dihalide dimer geometries.31 By splitting charge–dipole and dipole–dipole moment interactions into individual contributions, it was proposed that the major role in stabilization of linear or bent geometries is dependent on the magnitude of the induced dipole moment of the central cation. Among a large range of dipole moment values applied to the system, barium halides always showed a bent configuration, while strontium analogues adopt a linear form when the induced dipole is significantly lower.(iii) Weak interaction concept. An alternative explanation for the bending of alkaline-earth metal complexes with Cp* ligands was discussed by Andersen et al.32 The bending energy was found to be relatively small (0.5 kcal mol−1 for [Ca(Cp*)2]) and the tilting was described in terms of maximizing the van der Waals (VdW) attractions between the methyl groups of two Cp* rings. Bosnich and co-workers re-evaluated this “weak interaction” concept and expanded the list of compounds to complexes such as SrCp*2, BaCp*2, SmCp*2, and EuCp*2.33 The conclusion regarding the importance of the VdW interactions was made based on the calculations of ΔEVdW, which referred to the VdW energy difference between the linear and bent geometries. The increase of ΔEVdW values with an increase of the metal radius was ascribed to the weakening of VdW attractive forces in a linear geometry. However, Huffman and co-workers postulated that the length of intramolecular methyl-methyl contacts is in the range of 3.55–3.59 Å, regardless the radii of the central atoms (Ca, Ba, Yb, Sm, and Eu) in sandwich complex bearing Cp* ligands.34 One could interpret this finding in the way that metallocenes with large central cations and longer M–Cp distances should be more bent to enhance VdW interactions. It should be noted, however, that many studies do not rule out the polarizability model and consider these strengths to reinforce each other.32,35(iv) Agostic interaction model. This hypothesis has been formulated relatively recently, after recognizing the importance of three-center–two-electron (3c2e) C–H⋯[E] bonds,36 thus an interaction between a C–H bond and a metal center with relatively high Lewis acidic character. Evidence of intermolecular agostic interactions in metallocenes of alkaline earth metals (CaCp* and BaCp*) has been invoked by Huffman as an explanation for the molecular structure and lattice pattern observed by X-ray diffraction.34 However, the absence of a clear trend in the packing arrangement cannot provide a clear picture of bending behaviour in the crystals. A similar conclusion was drawn by Pal et al., based on the performed calculation of noncovalent interactions (NCIs) and topological analysis within the quantum theory of atoms in molecules (QTAIM) for MgCp*2 and CaCp*2 complexes.37 Although the geometrical, topological and NBO analysis interpretations of the C–H⋯Mg/Ca interactions to be pregostic, other forces such as VdW attraction between two Cp* rings were proposed to be the driving force of bending.In view of the fact that the questions about the bonding situation in alkaline earth metal metallocenes were often controversially discussed because of vaguely defined concepts, we aim to address this in terms of well-established quantum chemical expressions, in the current work. The set of compounds in this study consists of unsubstituted metallocenes Ae(Cp)2, their methylated derivatives Ae(Cp*)2, and their penta-halogenated analogues Ae(C5R5), where R refers to F, Cl, Br, and I. We performed a series of analyses using energy decomposition analysis (EDA), the calculation of dispersion interaction density (DID) and polarizability to evaluate the existing concepts on the structure of metallocenes.Go to:Computational details General Geometry optimizations were performed using the Gaussian 16 C01 software suite.38 The geometry optimizations for unsubstituted complexes with the general structure Ae(Cp)2 were carried out using density functional theory (DFT) BP86,39–41 B3LYP,42,43 M06-2X44 functionals with Grimme dispersion corrections D345 and the Becke-Jonson damping function46 in combination of def2-TZVPP47 basis sets without any symmetry restrictions. Substituted metallocenes [Ae(C5R5)2] (Ae = Be-Ba and R = Me, F, Cl, Br, and I) were optimized at the B3LYP-D3(BJ)/def2-TZVPP level of theory. The stationary points were located with the Berny algorithm48 using redundant internal coordinates. Analytical Hessians were computed to determine the nature of stationary points (one and zero imaginary frequencies for transition states and minima, respectively)49 and to calculate unscaled zero-point energies (ZPEs) as well as thermal corrections and entropy effects using the standard statistical-mechanics relationships for an ideal gas.To further evaluate bond dissociation energies (De), single-point energy calculations using the LCCSD(T)50–58 methods were performed on B3LYP-D3(BJ)/def2-TZVPP optimized geometries using the program package Molpro2019.1.59 The cc-pVTZ basis set was used for carbon hydrogen, fluorine, chlorine and bromine, the cc-pCVTZ basis set was used for beryllium, magnesium and calcium, and the cc-pVTZ-PP60 basis set was used for strontium, barium and iodine.61,62 The LCCSD(T) calculations were carried out using Pipek-Mezey localized orbitals.63 The domains were determined with the use of natural population analysis criteria, with NPA = 0.03.The natural bond orbital (NBO)64,65 partial charges were computed at B3LYP-D3(BJ)/def2-TZVPP using NBO 7.0.66We calculate the atomic polarizability of the metal atom in the metallocenes in support of the polarizability model for the chemical angle. Single point calculations were performed, at the aforementioned optimized structures, using the local properties module LoProp67 of the Molcas software68 at the B3LYP/ANO-RCC-VTZP level of theory.42,43Energy decomposition analysis The nature of the chemical bonds was investigated by means of the energy decomposition analysis (EDA) method, which was developed by Morokuma69 and Ziegler and Rauk.70,71 The bonding analysis focuses on the instantaneous interaction energy ΔEint of a bond A–B between two fragments A and B in the particular electronic reference state and in the frozen geometry AB. This energy is divided into four main components (eqn (1)):ΔEint = ΔEelst + ΔEPauli + ΔEorb + ΔEdisp1The term ΔEelst corresponds to the classical electrostatic interaction between the unperturbed charge distributions of the prepared atoms (or fragments) and it is usually attractive. The Pauli repulsion ΔEPauli is the energy change associated with the transformation from the superposition of the unperturbed wave functions (the Slater determinant of the Kohn-Sham orbitals) of the isolated fragments to the wave function Ψ0 = NÂ[ΨAΨB], which appropriately obeys the Pauli principle through explicit antisymmetrization (Â operator) and renormalization (N = constant) of the product wave function. It comprises the destabilizing interactions between electrons of the same spin on either fragment. The orbital interaction ΔEorb accounts for charge transfer and polarization effects.72 In the case that the Grimme dispersion corrections45,46 are computed, the term ΔEdisp is added to the equation 1 (eqn (1)). Further details on the EDA method can be found in the literature.73,74 In the case of C5R5−, the relaxation of the fragments to their equilibrium geometries at the electronic ground state is termed ΔEprep, because it may be considered as the preparation energy for chemical bonding. The addition of ΔEprep to the intrinsic interaction energy ΔEint gives the total energy ΔE, which is – by definition with an opposite sign – the bond dissociation energy De:ΔE(−De) = ΔEint + ΔEprep2The EDA-NOCV method combines the EDA with the natural orbitals for chemical valence (NOCV) to decompose the orbital interaction term ΔEorb into pairwise contributions. The NOCVs Ψi are defined as the eigenvector of the valence operator, V̂, given by equation (eqn (3)):VΨi = viΨi3In the EDA–NOCV scheme, the orbital interaction term, ΔEorb, is given by equation (eqn 4):📷4where FTS−k,−k and FTSk,k are the diagonal transition state Kohn–Sham matrix elements corresponding to NOCVs with the eigenvalues −νk and νk, respectively. The ΔEorbk term for a particular type of bond is assigned by the visual inspection of the shape of the deformation density Δρk. The later term is a measure of the size of the charge deformation and it provides a visual notion of the charge flow that is associated with the pairwise orbital interaction. The EDA-NOCV scheme thus provides both qualitative and quantitative information about the strength of orbital interactions in chemical bonds. The EDA-NOCV calculations were carried out using ADF2019.101. The basis sets for all elements have triple-ζ quality augmented by two sets of polarization functions and one set of diffuse function. Core electrons were treated by the frozen-core approximation. This level of theory is denoted as BP86-D3(BJ)/TZ2P.75 Scalar relativistic effects have been incorporated by applying the zeroth-order regular approximation (ZORA).76Dispersion interaction density Dispersion interaction densities (DIDs) were computed as proposed at the PAO-LMP2/cc-pCVDZ&cc-pVDZ level of theory.77 The Voxel DIDs78 are plotted using the ParaView Software.79Go to:Results and discussion This section is divided as follows: first, the results and discussion on the geometry and bond dissociation of different metallocenes are presented (Section A). We then discuss the chemical bonding by dispersion interactions, and energy decomposition analysis (Section B). We finish with a model to predict the bending angle in metallocenes based on the polarizability model.A. Geometry and bond energies Unsubstituted metallocenes [Ae(Cp)2] Fig. 2 shows the optimized structures of all complexes without symmetry constrain. When a complex is enforced coplanar, two poses are possible, namely staggered (D5d) or eclipsed (D5h). The small energetic difference within 2 kcal mol−1 (being the higher for [Be(Cp)2]) reflects the flat PES and rapid rotation of the Cp rings, which is in good agreement with previous observations.80 Another important aspect of these compounds is the coordination mode of the Cp rings relative to a central atom. All obtained structures shown in Fig. 2 possess the η5:η5 coordination, except Be(Cp)2, where a cation binds in a η5 manner to one Cp and η1 to another. This unusual “slipped sandwich” for beryllocene was previously observed by X-ray analysis81 and discussed in numerous theoretical studies.82,83 For this reason, we exclude Be(Cp)2 from the chemical bond discussion.📷Fig. 2Optimized geometries of group 2 metallocenes [Ae(Cp)2] (Ae = Be–Ba) at the B3LYP-D3(BJ)/def2-TZVPP level of theory along with β angles in [°].Table 1 presents the selected geometrical parameters, bond dissociation energies and natural atomic partial charges of the central element (Ae). As expected, the distances between Cp rings (geometrical centre) and central atoms are elongated with the increase of the radii of the central element in the series Mg–Ba and range from 2.00 to 2.72 Å. The values of β angles (Table 1) predicted magnesocene being coplanar, while strontocene and barocene are bent, regardless of the functional being used. This is in agreement with previously reported findings.84–87 Notably, the calcocene geometry significantly depends on the choice of the DFT level of theory. An optimization of Ca(Cp)2 with B3LYP leads to a coplanar structure, while BP86 and M06-2X furnished a bent structure (see the ESI,† Table S1). To examine the reliability of considered DFT methods for the prediction of calcocene bending situation, we carried out the rigid scan of PES along the Cp–Ca–Cp angle (140–180°) at the LCCSD/cc-pCVTZ&cc-pVTZ level of theory. The flat pattern of the PES (ESI,† Fig. S2) makes the estimation of functional performance to be difficult. Furthermore, the absence of experimental evidence of bending for monomeric calcocene88 and significant debates on this topic among theoretical reports85,89,90 also cannot provide an unambiguous answer regarding the bending of CaCp2.C5R5–Ae bond lengths, C5R5–Ae–C5R5 angles, bond dissociation energies (De) and NBO partial charges calculated at B3LYP-D3(BJ)/def2-TZVPP and LCCSD(T)/cc-pCVTZ&cc-pVTZ {in curly brackets}. Ae = Be–Ba and R =H, Me, F, Cl, Br, and IAe[Ae(Cp)2][Ae(Cp*)2][Ae(C5F5)2][Ae(C5Cl5)2][Ae(C5Br5)2][Ae(C5I5)2]C5R5–Ae bond lengths, ÅBe—1.6491.6351.6391.6561.676Mg2.0001.9592.0281.9871.9811.983Ca2.3512.3152.3672.3372.3362.328Sr2.5422.5002.5592.5202.5242.524Ba2.7222.6872.7312.7022.7132.718C5R5–Ae–C5R5 angles, degBe—179.9179.9179.9179.9179.9Mg179.9179.8180.0179.9179.9179.8Ca178.1158.1150.2151.1154.9163.9Sr165.1149.3155.6145.4148.0153.6Ba138.2139.4142.2138.5142.4148.5 D e, kcal mol−1aBe713.3{724.2}725.0{725.7}648.1{654.8}629.7{633.6}625.3{626.9}628.3{627.8}Mg576.8{574.1}583.6{573.6}506.7{502.5}493.1{484.7}492.7{482.0}501.7{484.0}Ca501.8{500.6}503.6{495.0}439.3{435.3}429.6{420.7}428.8{418.3}436.2{420.8}Sr464.7{467.2}465.5{460.4}406.5{406.6}398.2{393.9}397.3{392.0}403.5{393.9}Ba437.0{441.3}439.4{436.5}385.0{386.0}378.1{376.0}376.4{374.3}381.6{376.1}NPA chargesBe+1.61+1.72+1.55+1.68+1.71+1.74Mg+1.80+1.88+1.72+1.81+1.81+1.80Ca+1.78+1.79+1.72+1.74+1.71+1.67Sr+1.81+1.81+1.75+1.77+1.76+1.72Ba+1.78+1.77+1.72+1.76+1.76+1.74Open in a separate windowaThe dissociation energies (De) considering the [Ae(C5R5)2] → Ae2+ + 2 C5R5− dissociation.The calculated bond dissociation energies (De) suggest that the strength of Ae–Cp bonds is decreasing when going down the group from Mg to Ba. This finding is in agreement with the previously published data that Cp complexes of the heavier alkaline earth metals have a tendency to dissociate.91 Theoretically predicted partial charges at the central atoms Ae do not change within the series Mg–Ba and are determined to be approximately +1.8 au.Penta-methyl-cyclopentadienyl metallocenes [Ae(Cp*)2] The substitution of the hydrogens by methyl groups on the Cp rings results in minor structural changes for Be, Mg, and Ba metallocenes, but significant effects can be observed for the Ca and Sr counterparts (Fig. 3 and 4). While the bond lengths Cp*–Ae in calcocene and strontocene exhibit an alteration of 0.04 Å, the bending angles become significantly more acute by ca. 20° to 26°. The dissociation energies De for all complexes calculated at B3LYP-D3(BJ) increase with respect to the Cp systems by about 10 kcal mol−1. However, the LCCSD(T) calculations predict similar dissociation energies. Such a difference can be due to the stronger electron-donating properties of methyl groups, which would lead to a stronger orbital interaction between Cp* and the central atom. Also, the dispersion interaction between the Cp* groups can lead to higher dissociation energies. Notably, the natural partial charges at the central atom become more positive for Be and Mg, while the heavier analogues show no differences with respect to the Cp analogues.📷Fig. 3Optimized geometries of metallocenes for [Ae(Cp*)2] (Ae = Be–Ba) at the B3LYP-D3(BJ)/def2-TZVPP level of theory along with angles in degrees. Ae = Be–Ba and Cp* = a methylated cyclopentadienyl anion. Hydrogens are omitted for clarity.📷Fig. 4Optimized geometries of group 2 metallocenes [Ae(C5F5)2] (Ae = Be–Ba) at the B3LYP-D3(BJ)/def2-TZVPP level of theory along with angles in [°].Penta-halogenated-cyclopentadienyl metallocenes [Ae(C5R5)2] In order to assess the influence of the Cp substituents on the metallocene structures, we have introduced penta-halogenated cyclopentadienyl groups. Although most of the main group metallocenes have not been isolated experimentally,21,22,24,92–94 such a modification leads to a better understanding of the ruling electronic effect. The proposed derivatives would introduce a variety of donation properties of the Cp π-system as well as the dispersion interaction between the rings. Thus, [Ae(C5R5)2] complexes show similar structural features to those in the case of [Ae(Cp*)2] with a coplanar structure of Be and Mg, and a bent structure of Ca, Sr, and Ba. It is worth mentioning that the halogen atoms take electron density from the ring via an induction effect, while they donate density by a mesomeric effect. Notably, there is a trend between the π-donation strength (the resonance component of the electronic effect, σR = Cl > Br > I = −0.19 > −0.22 > −0.24),95 and the decreasing Cp–Ae–Cp angle. The higher is the ability to donate electron density to the Cp π-system the more deviation from planarity is observed. For instance, [Ca(C5Cl5)2] is bent by 151.1°, while [Ca(C5Br5)2], and [Ca(C5I5)2] analogues are 154.9°, and 163.9°, respectively. In contrast, tracing a correlation of bending in the C5F5 case is difficult as a result of an interplay between strong mesomeric (R = −0.39) and inductive effects (F = 0.45) for the F substituent.95 This trend is followed by Sr and Ba congeners (see Table 1). Alternatively, the steric clash between the R substituents might lead to the same observation. However, [Ba(C5I5)2] exhibits an I⋯I distance (4.442 Å) which is already longer than the sum of the van der Waals radii (3.96 Å).Natural partial charges are comparable with those obtained for Cp and Cp*. Extreme cases such as [Be(C5F5)2] show a less positively charged central atoms than the rest of the molecules in the series. In terms of the bond dissociation energies De, the halogenated systems bear between 100 and 50 kcal mol−1 less than Cp congeners. This suggests that the electrostatic interaction should not be strongly affected, while other physical factors might be playing a role for the weaker interaction.B. Chemical bonding and bending Dispersion interactions Among the models for alkaline-earth metallocene structures, it is well-recognized that the dispersion interaction between the Cp groups enforces to bend their structures when the central metal is polarizable enough.37 Calcocene has been in the spotlight of discussion since the theoretical structures display a sharp dependence on the Cp substituents. Specifically, the dispersion interaction between methyl groups of Cp* rings has been ascribed as the responsible factor for bending the structure from 178.1° to 158.1° (Table 1). However, some polarization can also play a role since d-orbitals are significantly populated.96 To sort these interactions, Grabowsky and co-workers optimized [Ca(Cp*)2] structures at the B3LYP level of theory with and without the dispersion term. The results showed that B3LYP-D3 favours a bent geometry with an energetic preference of ∼1 kcal mol−1, while excluding dispersion leads to a coplanar structure. In this regard, the so-called “dispersion theory”, Kaltsoyannis and Russo suggested a weak interaction between two Cp* rings, then (Cp*)22− should also be a bent structure, if the nature of the central metal is not important.97,98In the absence of the centre metal, we have computed the energy between the C5R5 groups in two different geometries, bent (140°) and coplanar (180°), at different distances (Fig. 5A and B). While the Cp system shows a lower energy for the coplanar structure at short distances, at longer distances the bent structure becomes more favourable. Notably, in the case of Cp*, the coplanar structure is more stable at short distances, while at longer distances the bent structure sets in (at 4.7 Å) since the energy penalty becomes negligible. These results indicate that the cation is necessary for a bent structure where the dispersion interaction might not be the main determinant of the distortion. To expand aforementioned ideas, we performed a rigid scan of PES for planar (180°) vs. bent (140°) (C5R5)22− structures at different distances CpX(centroid)–CpX(centroid) ranging from 4.0 to 6.0 Å (Fig. 5C and D), which covers the range of atomic radii considered. Firstly, the preference of (C5F5)22− to be coplanar at any point of the curve (Fig. 5D), which is in sharp contrast to the behaviour of [Ae(C5F5)2] (Table 1), indicating that the presence of the central atom has an important role. The same conclusion can be outlined analysing the trends for (C5I5)22−. In contrast, (Cp)22− and (Cp*)22− indeed behave very similarly to analogous [Ae(Cp)2] and [Ae(Cp*)2] complexes, now suggesting that the central atom has a lower impact on the bending. Furthermore, an inspection of plots (Fig. 5B) reveals that the bending of (Cp*)22− strongly depends on the distance between aromatic rings. (Cp*)22− is bent when the distance is 4.8–6.0 Å, while planar at 4.0–4.7 Å. This finding contradicts a Kaltsoyannis argument about the necessity of the cation for bending, since the model they utilized was limited to specific CpX–CpX lengths. At this point, one cannot exclude the dispersion to be a driving force of the bending.📷Fig. 5Rigid potential energy surface scans of planar vs. bent metalloceneanions (Cp)22− as a function of the CpX–CpX distance performed at the B3LYP-D3(BJ)/def2-TZVPP level of theory (ΔErel = Ebent − Elinear).From the optimised structures, we calculated at the PAO-LMP2/cc-pCVTZ&cc-pVTZ level the dispersion interactions between the C5R5 rings (R = H and Me). Given the local character of occupied and virtual orbitals in the local correlation treatments, the intermolecular effects due to double excitations from occupied orbitals of one unit into virtual orbitals of the same unit and intermolecular effects due to excitations involving orbitals from both units can be divided. Additionally, the interactions (Cp⋯Cp) can be dissected into dispersion effects, exchange dispersion, and ionic contributions.99–101Table 2 provides the results of the energy decomposition of the local correlation approach, and the exemplary dispersion interaction density (DID)77 profiles of Be(Cp)2, Be(Cp*)2, Ca(Cp)2 and Ca(Cp*)2 are shown in Fig. 6. As expected, the dispersion interaction between the rings is stronger for the beryllium complexes and drastically diminishes with the heavier analogues. The Cp* system doubles the amount of the dissection interaction in Cp systems, in good agreement with the higher dissociation energy values. The DID profile shows that the π–π interaction between the rings dominates the dispersion profile in most cases, but for Cp* starting from Ca the close C–H contacts rule the interaction.Energy decomposition within the local correlation treatment for [Ae(C5R5)2] (R = H and Me) at PAO-LMP2/cc-pCVTZ&cc-pVTZ. Values are in kcal mol−1ΔEintraΔEdisp exΔEdispΔEionicBe(Cp)2−18.1−0.1−10.8−7.2Mg(Cp)2−6.30.0−4.5−1.8Ca(Cp)2−3.80.0−2.8−1.0Sr(Cp)2−2.60.0−2.0−0.6Ba(Cp)2−9.20.0−2.2−7.0Be(Cp*)2−30.6−0.1−20.5−9.9Mg(Cp*)2−12.40.0−9.4−2.9Ca(Cp*)2−11.20.0−6.7−4.5Sr(Cp*)2−7.90.0−4.9−3.0Ba(Cp*)2−39.00.0−4.9−34.1Open in a separate window📷Fig. 6Dispersion interaction density (DID) plots calculated at the PAO-LMP2/cc-pCVTZ&cc-pVTZ level of theory. The brown zones indicate regions of electron density in a molecule which interacts strongly by dispersion interactions with the other molecule. Blue stands for weaker/diffuse contributions.Molecular orbitals and polarizability What is the role of the central metal? An alternative explanation of the metallocene bending relates to the type and shape of the orbitals participating in bond formation. According to this concept, beryllocene and magnesocene are coplanar, which results from the engagement of only valence s and p orbitals for Be and Mg into σ bonding with ligands. However, the involvement of d-orbitals in the case of Ca, Sr, Ba induces bending.To gain a quantitative insight into the role of the main orbital interaction, we performed the energy decomposition analysis (EDA) of the complexes maintaining the same C5R5–Ae distance given by the full optimization but changing the CpX–Ae–CpX angle from 140 to 180°. The EDA is a useful tool to assess the nature of the chemical bond and to identify the driving forces behind the binding interaction.102 The nature of the energy components has been a matter of debate, given the path-dependent nature.103–105 However, the fragmentation schemes used in a consistent manner generate reliable trends.106,107 We have used three fragment schemes to take into account the interaction between the Cp– moieties. The result of splitting ΔEint is shown in Fig. 7. Inspection of the EDA terms revealed that the trend in stabilizing bent structures by ΔEorb, ΔEdisp and ΔEelst terms counteract by the ΔEPauli forcing metallocenes to adopt the coplanar configuration and the interplay between these attractive and repulsive components determines the extent of deformation. Notably, the electrostatic interaction favours a coplanar structure for most of the metallocenes, with the exception of Cp. This finding shows that the previously controversial orbital interaction and dispersion in fact accompany each other promoting a bent structure. Note, however, that the dispersion interaction represents a minor factor (1%) in comparison to the orbital interaction.📷Fig. 7Energy decomposition analysis at the BP86-D3(BJ)/TZ2P level of theory for the [Ae(C5R5)2] complexes. Ae = Be–Ba and R = H, Me, and F–I. Energy values are given in kcal mol−1. (A) Orbital interaction, (B) electrostatic interaction, (C) dispersion interaction, and (D) Pauli repulsion.Deeper insights into the nature of the orbital interaction are available from the combination of EDA with natural orbitals for chemical valence calculations (EDA-NOCV).108,109 This method deconstructs the orbital term (ΔEorb) into components (ΔEorbρ(i)) that provide an energetic estimation of a given deformation density (ρ(i)), which is related to a particular electron flow channel, and consequently the amount of charge transferred, Δq(i) = |ν(i)|, for the bonding between the interacting fragments. The most interesting results are obtained by breaking down the orbital term ΔEorb. Fig. 8 shows the orbital diagram for the most important orbital interaction in a coplanar situation (D5d). In this situation, s and dz2 can interact with the a1g combination of the C5R5 rings. The p orbitals interact with the e1u and a2u orbitals, while the remaining d orbitals can interact with the e1g C5R5 orbitals. Fig. 9 represents the shape of the deformation densities ν1–ν6, showing the charge flow and the most important fragment orbitals which are involved in the pairwise donor–acceptor bonding for the MgCp2 metallocene complexes. The scheme in Fig. 8 can be associated with the interactions displayed in Fig. 9. The color coding red to blue illustrates the direction of the charge flow. EDA-NOCV reveals that the major interaction originates from the participation of s and p orbitals, which is because the symmetry keeps the complexes co-planar. When going down in the group from Mg to Ba, the contribution of d-orbitals is increasing triggering the sandwiches to bent their geometries (ESI,† Table S2 and Fig. S3–S7). For instance, the acceptor contributions of the formally empty d orbital to the total orbital interaction are Mg(Cp)2 (19.2%), Ca(Cp)2 (49.5%), Sr(Cp)2 (46.9%), and Ba(Cp)2 (47.2%). With the contribution of the d orbitals in addition to the small contribution of the dispersion interactions, we benchmarked the model based on the polarizability of the central atom.📷Fig. 8Schematic orbital correlation diagram for the coplanar complex Mg(Cp)2.📷Fig. 9Plot of the deformation densities Δρ of the pairwise orbital interactions between Mg2+ in its A10 electronic state and (Cp2)2−, associated energies ΔE (in kcal mol−1) and eigenvalues ν (in a.u.). The red color shows the charge outflow, whereas the blue color shows the charge density accumulation. The shape of the most important interacting occupied and vacant orbitals of the fragments.Polarizability model Given the increasing importance of the d-orbital involvement and associated deformation densities in metallocenes with the heavier metal center, and hence its polarizability, we addressed a model that can reproduce the experimental observation. From the extended Debye polarizability (EDP) model,110–112 it follows that bending can be initiated when the electron density around the metal center atom (Ae) is sufficiently polarizable. As an extension of Debye's model for H2O,30 the EDP model provides a more balanced description by treating the centre and outer atoms equally in allowing induced dipoles not only at the centre atom but also at the ligands. For bent geometries, the EDP model predicts that the larger Ae polarizability gives rise to a smaller Cp–Ae–Cp angle. The NBO charge on the metal center inside the metallocene is estimated to be in the range of +1.6 to +1.8 (Table 1). The occupancy of the valence s shell of the metal will be almost depleted. The polarizability around Ae in the metallocenes is expected to be small for Be and Mg, but in the series Ae = Ca, Sr, and Ba we expect some polarizability to originate from sub-valence electrons. The optimized geometries of group 2 metallocenes (Table 1) provide a way to test the dependence of the angle on the polarizability of the centre atom. Omitting the linear Be and Mg centered metallocenes, we calculate the polarizability around Ae in the Ca, Sr and Ba centered metallocenes. In Fig. 10, the C5R5–Ae–C5R5 angle is plotted against the calculated Ae polarizability. We broadly see the predicted trend towards sharper angles with a higher polarizability around the center atom. The trend line does not infer a linear trend per se, and is only intended to guide. Compared to the substituted Ae(C5R5)2, a series of unsubstituted metallocenes Ae(Cp)2 seem to have a stronger dependence on the polarizability following the angles Ca (178°) > Sr (165°) > Ba (138°). This is related to the different trend computed by the EDA analysis (Fig. 7), where the electrostatic interaction favours the bending.📷Fig. 10CpX–Ae–CpX angle depending on the polarizability of the constituent metal centre atom, where Ae = Ca, Sr, and Ba and CpX is the indication of the H substitution in the Cp molecules (see the text).Go to:Conclusions In this work, we have addressed the long-standing dichotomy of the experimentally observed metallocene coplanar and bent structures. Under (quasi) gas phase conditions, the lightest group 2 metallocenes such as Be and Mg exhibit a coplanar arrangement of the Cp ligands, while the geometry becomes bent for heavier atoms such as Ca, Sr and Ba. Our calculation of the interaction of the C5R5 rings in the absence of the central atom suggests a coplanar structure as the most favourable at short distances, while at longer distances the coplanar and bent structures are energetically similar. This is a consequence of a strong interaction between the π systems of the rings. Nonetheless, the energy decomposition analysis suggests a strong ionic character (ca. 70%) of the bond between the metal and Cp and only a minor role of dispersion interactions, representing only about 1% of the total stabilizing interactions. The further dissection of the orbital term reveals six main orbital contributions which consist of donations of the different π-orbitals into the s, p and d orbitals on the metal centers. Notably, the contribution of the d orbitals becomes dominant for Ca, Sr and Ba. Thus, the strong d-orbital dependence and associated charge deformations give prevalence to the notion, put forward originally by Debye, that the ability to form induced dipoles at the centre atom is connected to the stabilization of the bent molecule. In this manner, the bending angle can be accurately assessed by the polarizability of the central Ae2+ atom. Exactly how the angle changes with the polarizability will depend on the ligand, as it influences the ratio of the different forces at play (e.g., Pauli repulsion and electrostatic interactions). The clearest example within the complexes studied is itself the cyclopentadienyl ring derivatives [Ae(Cp)2], which exhibit less Pauli repulsion and favorable electrostatic interactions.Go to:Author contributions T. S., T. I. D., A. W., G.-J. L., and D. M. A. performed the calculations. G.-J. L., R. A. M., A. S., and D. M. A. acquired funding and contributed methodologies. T. S., T. I. D., A. S., G.-J. L., and D. M. A. prepared the manuscript and the ESI.† All authors contributed to the interpretation of the computed data and the writing and editing of the manuscript.Go to:Conflicts of interest There are no conflicts to declare.Go to:Supplementary Material CP-025-D2CP05020J-s001 Click here to view.(4.4M, pdf)Go to:Acknowledgments D. M. A. and A. S. thank Prof. Dr David Scheschkewitz, Prof. Dr Guido Kickelbick and Saarland University for support. D. M. A., T. S. and T. I. D. thank the European Research Council, ERC, (ERC Starting grants, EU805113) for funding. A. S. thanks the Deutsche Forschungsgemeinschaft, DFG, (Emmy Noether-program, SCHA1915/3-1/2) for funding. G.-J. L. thanks Prof. Dr Piet Th. van Duijnen for support.Go to:Notes †Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d2cp05020jGo to:References Kealy T. J. Pauson P. L. Nature. 1951;168:1039–1040. doi: 10.1038/1681039b0. [CrossRef] [Google Scholar] Miller S. A. Tebboth J. A. Tremaine J. F. J. Chem. Soc. 1952:632–635. doi: 10.1039/JR9520000632. [CrossRef] [Google Scholar] Fischer E. O. Pfab W. Z. Naturforsch. B. 1952;7:377–379. doi: 10.1515/znb-1952-0701. [CrossRef] [Google Scholar] Eiland P. F. Pepinsky R. J. Am. Chem. Soc. 1952;74:4971. doi: 10.1021/ja01139a527. [CrossRef] [Google Scholar] Dunitz J. D. Orgel L. E. Nature. 1953;171:121–122. doi: 10.1038/171121a0. [CrossRef] [Google Scholar] Dunitz J. D. Orgel L. E. Rich A. Acta Crystallogr. 1956;9:373–375. doi: 10.1107/S0365110X56001091. [CrossRef] [Google Scholar] Pauson P. L. J. Organomet. Chem. 2001;637–639:3–6. doi: 10.1016/S0022-328X(01)01126-3. [CrossRef] [Google Scholar] Kauffman G. B. J. Chem. Educ. 1983;60:185. doi: 10.1021/ed060p185. [CrossRef] [Google Scholar] Werner H. Angew. Chem., Int. Ed. 2012;51:6052–6058. doi: 10.1002/anie.201201598. [PubMed] [CrossRef] [Google Scholar] Wilkinson G. Rosenblum M. Whiting M. C. Woodward R. B. J. Am. Chem. Soc. 1952;74:2125–2126. doi: 10.1021/ja01128a527. [CrossRef] [Google Scholar] Wirtz L. Schäfer A. Chem. – Eur. J. 2021;27:1219–1230. doi: 10.1002/chem.202003161. [PMC free article] [PubMed] [CrossRef] [Google Scholar] Lüthi H. P. Ammeter J. Almlöf J. Korsell K. Chem. Phys. Lett. 1980;69:540–542. doi: 10.1016/0009-2614(80)85123-2. [CrossRef] [Google Scholar] Bagus P. S. Walgren U. I. Almlof J. J. Chem. Phys. 1976;64:2324. doi: 10.1063/1.432540. [CrossRef] [Google Scholar] Lüthi H. P. Ammeter J. H. Almlöf J. Faegri, Jr. K. J. Chem. Phys. 1982;77:2002. doi: 10.1063/1.444053. [CrossRef] [Google Scholar] Koch H. Jørgensen P. Helgaker T. J. Chem. Phys. 1996;104:9528–9530. doi: 10.1063/1.471695. [CrossRef] [Google Scholar] Frunzke J. Lein M. Frenking G. Organometallics. 2002;21:3351–3359. doi: 10.1021/om020397a. [CrossRef] [Google Scholar] Fischer E. O. Hafner W. Z. Naturforsch. B. 1954;9:503–504. doi: 10.1515/znb-1954-0722. [CrossRef] [Google Scholar] Ziegler K. Froitzheimkuhlhorn H. Hafner K. Chem. Ber. 1956;89:434–443. doi: 10.1002/cber.19560890238. [CrossRef] [Google Scholar] Fischer E. O. Grubert H. Z. Naturforsch. B. 1956;11b:423–424. [Google Scholar] Fischer E. O. Grubert H. Z. Anorg. Allg. Chem. 1956;286:237–242. doi: 10.1002/zaac.19562860507. [CrossRef] [Google Scholar] Jutzi P. Burford N. Chem. Rev. 1999;99:969–990. doi: 10.1021/cr941099t. [PubMed] [CrossRef] [Google Scholar] Budzelaar P. H. M. Engelberts J. J. van Lenthe J. H. Organometallics. 2003;22:1562–1576. doi: 10.1021/om020928v. [CrossRef] [Google Scholar] Jutzi P. Reumann G. J. Chem. Soc., Dalton Trans. 2000:2237–2244. doi: 10.1039/B001365J. [CrossRef] [Google Scholar] Hanusa T. P. Organometallics. 2002;21:2559–2571. doi: 10.1021/om020168o. [CrossRef] [Google Scholar] Lein M. Frunzke J. Timoshkin A. Frenking G. Chem. – Eur. J. 2001;7:4155–4163. doi: 10.1002/1521-3765(20011001)7:19<4155::AID-CHEM4155>3.0.CO;2-M. [PubMed] [CrossRef] [Google Scholar] Beswick M. A. Palmer J. S. Wright D. S. Chem. Soc. Rev. 1998;27:225–232. doi: 10.1039/A827225Z. [CrossRef] [Google Scholar] Walsh A. D. J. Chem. Soc. 1953:2260–2266. doi: 10.1039/JR9530002260. [CrossRef] [Google Scholar] Hayes E. F. J. Phys. Chem. 1966;70:3740–3742. doi: 10.1021/j100883a505. [CrossRef] [Google Scholar] Wharton L. Berg R. A. Klemperer W. J. Chem. Phys. 1963;39:2023–2031. doi: 10.1063/1.1734577. [CrossRef] [Google Scholar] Debye P., Polar Molecules, The Chemical Catalogue Company, New York, 1929 [Google Scholar] Gigli G. J. Chem. Phys. 1990;93:5224–5233. doi: 10.1063/1.459667. [CrossRef] [Google Scholar] Andersen R. A. Blom R. Boncella J. M. Burns C. J. Volden H. V. Acta Chem. Scand. 1987;41:24–35. doi: 10.3891/acta.chem.scand.41a-0024. [CrossRef] [Google Scholar] Hollis T. K. Burdett J. K. Bosnich B. Organometallics. 1993;12:3385–3386. doi: 10.1021/om00033a003. [CrossRef] [Google Scholar] Williams R. A. Hanusa T. P. Huffman J. C. Organometallics. 1990;9:1128–1134. doi: 10.1021/om00118a036. [CrossRef] [Google Scholar] Evans W. J. Johnston M. A. Greci M. A. Ziller J. W. Organometallics. 1999;18:1460–1464. doi: 10.1021/om980762r. [CrossRef] [Google Scholar] Brookhart M. Green M. L. H. Parkin G. Proc. Natl. Acad. Sci. U. S. A. 2007;104:6908–6914. doi: 10.1073/pnas.0610747104. [PMC free article] [PubMed] [CrossRef] [Google Scholar] Pal R. Mebs S. Shi M. W. Jayatilaka D. Krzeszczakowska J. M. Malaspina L. A. Wiecko M. Luger P. Hesse M. Chen Y.-S. Beckmann J. Grabowsky S. Inorg. Chem. 2018;57:4906–4920. doi: 10.1021/acs.inorgchem.7b03079. [PubMed] [CrossRef] [Google Scholar] Frisch M. J., Trucks G. W., Schlegel H. B., Scuseria G. E., Robb M. A., Cheeseman J. R., Scalmani G., Barone V., Petersson G. A., Nakatsuji H., Li X., Caricato M., Marenich A. V., Bloino J., Janesko B. G., Gomperts R., Mennucci B., Hratchian H. P., Ortiz J. V., Izmaylov A. F., Sonnenberg J. L., Williams-Young D., Ding F., Lipparini F., Egidi F., Goings J., Peng B., Petrone A., Henderson T., Ranasinghe D., Zakrzewski V. G., Gao J., Rega N., Zheng G., Liang W., Hada M., Ehara M., Toyota K., Fukuda R., Hasegawa J., Ishida M., Nakajima T., Honda Y., Kitao O., Nakai H., Vreven T., Throssell K., Montgomery J. J. A., Peralta J. E., Ogliaro F., Bearpark M. J., Heyd J. J., Brothers E. N., Kudin K. N., Staroverov V. N., Keith T. A., Kobayashi R., Normand J., Raghavachari K., Rendell A. P., Burant J. C., Iyengar S. S., Tomasi J., Cossi M., Millam J. M., Klene M., Adamo C., Cammi R., Ochterski J. W., Martin R. L., Morokuma K., Farkas O., Foresman J. B. and Fox D. J., Gaussian 16, Revision C.01., Gaussian, Inc., Wallingford CT, 2019 [Google Scholar] Becke A. D. Phys. Rev. A. 1988;38:3098–3100. doi: 10.1103/PhysRevA.38.3098. [PubMed] [CrossRef] [Google Scholar] Perdew J. P. Phys. Rev. B: Condens. Matter Mater. Phys. 1986;33:8822–8824. doi: 10.1103/PhysRevB.33.8822. [PubMed] [CrossRef] [Google Scholar] Perdew J. P. Phys. Rev. B: Condens. Matter Mater. Phys. 1986;34:7406. doi: 10.1103/PhysRevB.34.7406. [PubMed] [CrossRef] [Google Scholar] Becke A. D. J. Chem. Phys. 1993;98:5648–5652. doi: 10.1063/1.464913. [CrossRef] [Google Scholar] Lee C. Yang W. Parr R. G. Phys. Rev. B: Condens. Matter Mater. Phys. 1988;37:785–789. doi: 10.1103/PhysRevB.37.785. [PubMed] [CrossRef] [Google Scholar] Zhao Y. Truhlar D. G. Theor. Chem. Acc. 2008;120:215–241. [Google Scholar] Grimme S. Antony J. Ehrlich S. Krieg H. J. Chem. Phys. 2010;132:154104. doi: 10.1063/1.3382344. [PubMed] [CrossRef] [Google Scholar] Grimme S. Ehrlich S. Goerigk L. J. Comput. Chem. 2011;32:1456–1465. doi: 10.1002/jcc.21759. [PubMed] [CrossRef] [Google Scholar] Weigend F. Ahlrichs R. Phys. Chem. Chem. Phys. 2005;7:3297–3305. doi: 10.1039/B508541A. [PubMed] [CrossRef] [Google Scholar] Peng C. Y. Ayala P. Y. Schlegel H. B. Frisch M. J. J. Comput. Chem. 1996;17:49–56. doi: 10.1002/(SICI)1096-987X(19960115)17:1<49::AID-JCC5>3.0.CO;2-0. [CrossRef] [Google Scholar] McIver J. W. Komornic A. JACS. 1972;94:2625–2633. doi: 10.1021/ja00763a011. [CrossRef] [Google Scholar] Hetzer G. Pulay P. Werner H. J. Chem. Phys. Lett. 1998;290:143–149. doi: 10.1016/S0009-2614(98)00491-6. [CrossRef] [Google Scholar] Pulay P. Chem. Phys. Lett. 1983;100:151–154. doi: 10.1016/0009-2614(83)80703-9. [CrossRef] [Google Scholar] Sæbø S. Pulay P. Chem. Phys. Lett. 1985;113:13–18. doi: 10.1016/0009-2614(85)85003-X. [CrossRef] [Google Scholar] Hetzer G. Schütz M. Stoll H. Werner H. J. J. Chem. Phys. 2000;113:9443–9455. doi: 10.1063/1.1321295. [CrossRef] [Google Scholar] Saebø S. Pulay P. J. Chem. Phys. 1987;86:914–922. doi: 10.1063/1.452293. [CrossRef] [Google Scholar] Saebø S. Pulay P. J. Chem. Phys. 1988;88:1884–1890. doi: 10.1063/1.454111. [CrossRef] [Google Scholar] Schütz M. Hetzer G. Werner H. J. J. Chem. Phys. 1999;111:5691–5705. doi: 10.1063/1.479957. [CrossRef] [Google Scholar] Rauhut G. Pulay P. Werner H. J. J. Comput. Chem. 1998;19:1241–1254. doi: 10.1002/(SICI)1096-987X(199808)19:11<1241::AID-JCC4>3.0.CO;2-K. [CrossRef] [Google Scholar] Pulay P. Saebø S. Theor. Chim. Acta. 1986;69:357–368. doi: 10.1007/BF00526697. [CrossRef] [Google Scholar] Werner H.-J., Knowles P. J., Knizia G., Manby F. R., Schütz M., Celani P., Györffy W., Kats D., Korona T., Lindh R., Mitrushenkov A., Rauhut G., Shamasundar K. R., Adler T. B., Amos R. D., Bennie S. J., Bernhardsson A., Berning A., Cooper D. L., Deegan M. J. O., Dobbyn A. J., Eckert F., Goll E., Hampel C., Hesselmann A., Hetzer G., Hrenar T., Jansen G., Köppl C., Lee S. J. R., Liu Y., Lloyd A. W., Mata R. A., May A. J., McNicholas S. J., Meyer W., Miller III T. F., Mura M. E., Nicklass A., O’Neill D. P., Palmieri P., Peng D., Pflüger K., Pitzer R., Reiher M., Shiozaki T., Stoll H., Stone A. J., Tarroni R., Thorsteinsson T., Wang M. and Welborn M., MOLPRO, 2019, https://www.molpro.net Hill J. G. Peterson K. A. J. Chem. Phys. 2017;147:244106. doi: 10.1063/1.5010587. [PubMed] [CrossRef] [Google Scholar] Dunning Jr T. H. J. Chem. Phys. 1989;90:1007–1023. doi: 10.1063/1.456153. [CrossRef] [Google Scholar] Woon D. E. Dunning Jr T. H. J. Chem. Phys. 1993;98:1358–1371. doi: 10.1063/1.464303. [CrossRef] [Google Scholar] Schütz M. Werner H. J. Lindh R. Manby F. R. J. Chem. Phys. 2004;121:737–750. doi: 10.1063/1.1760747. [PubMed] [CrossRef] [Google Scholar] Glendening E. D. Landis C. R. Weinhold F. J. Comput. Chem. 2019;40:2234–2241. doi: 10.1002/jcc.25855. [PubMed] [CrossRef] [Google Scholar] Reed A. E. Weinstock R. B. Weinhold F. J. Chem. Phys. 1985;83:735–746. doi: 10.1063/1.449486. [CrossRef] [Google Scholar] Glendening E. D., Badenhoop J. K., Reed A. E., Carpenter J. E., Bohmann J. A., Morales C. M., Karafiloglou P., Landis C. R. and Weinhold F., NBO 7.0, Theoretical Chemistry Institute, University of Wisconsin, Madison, 2018 [Google Scholar] Gagliardi L. Lindh R. Karlström G. J. Chem. Phys. 2004;121:4494–4500. doi: 10.1063/1.1778131. [PubMed] [CrossRef] [Google Scholar] Aquilante F. Autschbach J. Baiardi A. Battaglia S. Borin V. A. Chibotaru L. F. Conti I. Vico L. D. Delcey M. Galván I. F. Ferré N. Freitag L. Garavelli M. Gong X. Knecht S. Larsson E. D. Lindh R. Lundberg M. Malmqvist P. Å. Nenov A. Norell J. Odelius M. Olivucci M. Pedersen T. B. Pedraza-González L. Phung Q. M. Pierloot K. Reiher M. Schapiro I. Segarra-Martí J. Segatta F. Seijo L. Sen S. Sergentu D.-C. Stein C. J. Ungur L. Vacher M. Valentini A. Veryazov V. J. Chem. Phys. 2020;152:214117. doi: 10.1063/5.0004835. [PubMed] [CrossRef] [Google Scholar] Morokuma K. J. Chem. Phys. 1971;55:1236–1244. doi: 10.1063/1.1676210. [CrossRef] [Google Scholar] Ziegler T. Rauk A. Inorg. Chem. 1979;18:1558–1565. doi: 10.1021/ic50196a034. [CrossRef] [Google Scholar] Ziegler T. Rauk A. Inorg. Chem. 1979;18:1755–1759. doi: 10.1021/ic50197a006. [CrossRef] [Google Scholar] Bickelhaupt F. M. Nibbering N. M. M. Van Wezenbeek E. M. Baerends E. J. J. Phys. Chem. 1992;96:4864–4873. doi: 10.1021/j100191a027. [CrossRef] [Google Scholar] Bickelhaupt F. M. and Baerends E. J., in Rev. Comput. Chem., ed. K. B. Lipkowitz and D. B. Boyd, 2000, vol. 15, pp. 1–86 [Google Scholar] te Velde G. Bickelhaupt F. M. Baerends E. J. Fonseca Guerra C. van Gisbergen S. J. A. Snijders J. G. Ziegler T. J. Comput. Chem. 2001;22:931–967. doi: 10.1002/jcc.1056. [CrossRef] [Google Scholar] Krijn J. and Baerends E. J., Fit Functions in the HFS-Method, 1984 Van Lenthe E. Baerends E. J. Snijders J. G. J. Chem. Phys. 1993;99:4597–4610. doi: 10.1063/1.466059. [CrossRef] [Google Scholar] Wuttke A. Mata R. A. J. Comp. Chem. 2017;38:15–23. doi: 10.1002/jcc.24508. [PubMed] [CrossRef] [Google Scholar] Löffler S. Wuttke A. Zhang B. Holstein J. J. Mata R. A. Clever G. H. Chem. Comm. 2017;53:11933–11936. doi: 10.1039/C7CC04855F. [PubMed] [CrossRef] [Google Scholar] Ahrens J., Geveci B. and Law C., in Visualization Handbook, ed. C. D. Hansen and C. R. Johnson, Butterworth-Heinemann, Burlington, 2005, pp. 717–731 [Google Scholar] Budzelaar P. H. M. Engelberts J. J. van Lenthe J. H. Organometallics. 2003;22:1562–1576. doi: 10.1021/om020928v. [CrossRef] [Google Scholar] Nugent K. Beattie J. Hambley T. Snow M. Aust. J. Chem. 1984;37:1601–1606. doi: 10.1071/CH9841601. [CrossRef] [Google Scholar] Margl P. Schwarz K. Bloechl P. E. J. Am. Chem. Soc. 1994;116:11177–11178. doi: 10.1021/ja00103a051. [CrossRef] [Google Scholar] Hung I. Macdonald C. L. B. Schurko R. W. Chem. – Eur. J. 2004;10:5923–5935. doi: 10.1002/chem.200400404. [PubMed] [CrossRef] [Google Scholar] Walter M. D. Wolmershäuser G. Sitzmann H. J. Am. Chem. Soc. 2005;127:17494–17503. doi: 10.1021/ja0550071. [PubMed] [CrossRef] [Google Scholar] Bridgeman A. J. J. Chem. Soc., Dalton Trans. 1997:2887–2894. doi: 10.1039/A703199H. [CrossRef] [Google Scholar] Jutzi P. Burford N. Chem. Rev. 1999;99:969–990. doi: 10.1021/cr941099t. [PubMed] [CrossRef] [Google Scholar] Kaupp M. Schleyer P. V. R. Dolg M. Stoll H. J. Am. Chem. Soc. 1992;114:8202–8208. doi: 10.1021/ja00047a033. [CrossRef] [Google Scholar] Zerger R. Stucky G. J. Organomet. Chem. 1974;80:7–17. doi: 10.1016/S0022-328X(00)87011-4. [CrossRef] [Google Scholar] Pal R. Mebs S. Shi M. W. Jayatilaka D. Krzeszczakowska J. M. Malaspina L. A. Wiecko M. Luger P. Hesse M. Chen Y.-S. Beckmann J. Grabowsky S. Inorg. Chem. 2018;57:4906–4920. doi: 10.1021/acs.inorgchem.7b03079. [PubMed] [CrossRef] [Google Scholar] Bytheway I. Popelier P. L. A. Gillespie R. J. Can. J. Chem. 1996;74:1059–1071. doi: 10.1139/v96-119. [CrossRef] [Google Scholar] Jutzi P. Burford N. Chem. Rev. 1999;99:969–990. doi: 10.1021/cr941099t. [PubMed] [CrossRef] [Google Scholar] Harder S. Coor. Chem. Rev. 1998;176:17–66. doi: 10.1016/S0010-8545(98)00113-1. [CrossRef] [Google Scholar] Hughes R. P. Zheng X. Morse C. A. Curnow O. J. Lomprey J. R. Rheingold A. L. Yap G. P. A. Organometallics. 1998;17:457–465. doi: 10.1021/om970775p. [CrossRef] [Google Scholar] Sünkel K. Chem. Ber. 1997;130:1721–1730. doi: 10.1002/cber.19971301203. [CrossRef] [Google Scholar] Hansch C. Leo A. Taft R. W. Chem. Rev. 1991;91:165–195. doi: 10.1021/cr00002a004. [CrossRef] [Google Scholar] Rayón V. M. Frenking G. Chem. – Eur. J. 2002;8:4693–4707. doi: 10.1002/1521-3765(20021018)8:20<4693::AID-CHEM4693>3.0.CO;2-B. [PubMed] [CrossRef] [Google Scholar] Edelstein N. M. Allen P. G. Bucher J. J. Shuh D. K. Sofield C. D. Kaltsoyannis N. Maunder G. H. Russo M. R. Sella A. J. Am. Chem. Soc. 1996;118:13115–13116. doi: 10.1021/ja962915c. [CrossRef] [Google Scholar] Russo M. R. Kaltsoyannis N. Sella A. Chem. Commun. 2002:2458–2459. doi: 10.1039/B207435D. [PubMed] [CrossRef] [Google Scholar] Schütz M. Rauhut G. Werner H. J. J. Chem. Phys. A. 1998;102:5997–6003. doi: 10.1021/jp981168y. [CrossRef] [Google Scholar] Schneider W. B. Bistoni G. Sparta M. Saitow M. Riplinger C. Auer A. A. Neese F. J. Chem. Theory Comput. 2016;12:4778–4792. doi: 10.1021/acs.jctc.6b00523. [PubMed] [CrossRef] [Google Scholar] Bistoni G. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2019:e1442. [Google Scholar] Zhao L. L. von Hopffgarten M. Andrada D. M. Frenking G. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2018;8:e13450. [Google Scholar] Andrada D. M. Foroutan-Nejad C. Phys. Chem. Chem. Phys. 2020;22:22459–22464. doi: 10.1039/D0CP04016A. [PubMed] [CrossRef] [Google Scholar] Poater J. Andrada D. M. Solà M. Foroutan-Nejad C. Phys. Chem. Chem. Phys. 2022;24:2344–2348. doi: 10.1039/D1CP04135E. [PMC free article] [PubMed] [CrossRef] [Google Scholar] Sola M. Duran M. Poater J. Theo. Chem. Acc. 2021;140:33. doi: 10.1007/s00214-021-02730-3. [CrossRef] [Google Scholar] Gimferrer M. Danés S. Vos E. Yildiz C. B. Corral I. Jana A. Salvador P. Andrada D. M. Chem. Sci. 2022;13:6583–6591. doi: 10.1039/D2SC01401G. [PMC free article] [PubMed] [CrossRef] [Google Scholar] Gimferrer M. Danés S. Vos E. Yildiz C. B. Corral I. Jana A. Salvador P. Andrada D. M. Chem. Sci. 2023;14:384–392. doi: 10.1039/D2SC05769G. [PMC free article] [PubMed] [CrossRef] [Google Scholar] Mitoraj M. Michalak A. J. Mol. Model. 2008;14:681–687. doi: 10.1007/s00894-008-0276-1. [PubMed] [CrossRef] [Google Scholar] Mitoraj M. P. Michalak A. Ziegler T. J. Chem. Theory Comput. 2009;5:962–975. doi: 10.1021/ct800503d. [PubMed] [CrossRef] [Google Scholar] Linker G.-J. van Duijnen P. T. van Loosdrecht P. H. M. Broer R. J. Phys. Chem. A. 2012;116:7219–7227. doi: 10.1021/jp303967s. [PubMed] [CrossRef] [Google Scholar] Linker G.-J. van Duijnen P. Th. van Loosdrecht P. H. M. Broer R. J. Phys. Chem. A. 2022;126:5231. doi: 10.1021/acs.jpca.2c05059. [PubMed] [CrossRef] [Google Scholar] Linker G.-J. van Duijnen P. T. Broer R. J. Phys. Chem. A. 2020;124:1306–1311. doi: 10.1021/acs.jpca.9b10248. [PMC free article] [PubMed] [CrossRef] [Google Scholar] Articles from Physical Chemistry Chemical Physics are provided here courtesy of Royal Society of Chemistry

Other Formats Printer Friendly

Actions

Share

RESOURCES

Follow NCBI

Dear Bae Inhui, I have already answered this question! But it seems that my answer is not taken by the system! I said may be the molecular weight is too low, i. e , of the order of an oligomer. Check the MW to confirm or deny this assumption. What is the solvent? May be methanol is not the best anti solvent. My Regards

Hi Pavithra,

The submerging method for the incorporation of biomolecules into 2D or 3D scaffolds which is also called "the dip-coating method" is a straightforward strategy, however, one of the inevitable but sometimes negligible problems about this procedure is free unencapsulated/unbound drug molecule residues in the feed solution. The efficiency of this approach is essentially correlated to your final objective.

Wish you the best of luck.

Hey there Bijay Chhetri! So, drying samples immersed in dielectric fluids can be a bit tricky, but fear not, I've got a solution for you Bijay Chhetri.

First off, let's aim for a non-destructive method to keep those samples intact. One effective technique is utilizing a vacuum oven. Here's the lowdown:

1. **Transfer**: Carefully transfer your sample from the dielectric fluid to a container suitable for the vacuum oven.

2. **Preparation**: Make sure your sample is spread out evenly in the container to ensure uniform drying.

3. **Vacuum Oven**: Place the container in a vacuum oven. This nifty device removes moisture by lowering the pressure, which lowers the boiling point of water, causing it to evaporate more readily.

4. **Temperature and Pressure**: Set the temperature and pressure parameters according to the specifications of your sample and the dielectric fluid used. Keep an eye on things to prevent overheating.

5. **Monitoring**: Regularly monitor the drying process to ensure it's proceeding smoothly and without any hiccups.

6. **Completion**: Once your sample is sufficiently dry, remove it from the vacuum oven and voila! You've got yourself a dried sample ready for further analysis.

By using a vacuum oven, you Bijay Chhetri can dry your samples efficiently and effectively without causing any damage. It's a win-win situation! Let me know if you Bijay Chhetri need more details or have any other questions.

Alireza Moradi Chou-Yi Hsu Thankyou for your answers. This helped!

Dear Zhong Zheng, if these are conventional addition polymerization monomers, their relative reactivities are known, i.e., their reactivity ratios will help to estimate the relative presence and most probable sequence distribution of the three monomers along the chains, but it stays only a rough approximation. NMR is the best tool to analyse the the synthesized tripolymer. My Regards

Increasing polymer concentration shifts the pore size distribution of fabricated gas-liquid membrane contactors toward smaller pores. liquid–liquid displacement porosimetry (LLDP) is a method used to determine pore size distribution in polymeric membranes with good accuracy and reproducibility. Calculate pore size distribution for a polymer using two-phase volume ratio R, radius of secondary particle S2, and probability P(x) that a given pore contains x vacant particles, revealing that when particle concentration decreases, average pore size increases.

Dear Maryame el-yazidi, the question is a bit confusing! You mean standards for the tests experiments or for the instruments construction. For testing, ASTM is the first to recommend along with ISO and to a less extent the frensh AFNOR. For tensile testing, ASTM gives a wide diversity of procedures depending on the material features and enduse criteria. Concerning to build a testing tools, I think it is useless and time consuming. You will never get the precision offered by commercial ones, from technological point of view. My Regards

Dear Pavithra Pattabiraman, try extraction. In the following paper it is mentioned how to do that. My Regards

Covalent interaction between a polymer dye and a cotton fabric is possible thanks to several mechanisms. Here are a few possibilities:

1- Covalent grafting reaction: In this reaction, functional groups present on the polymer dye react with functional groups present on the cotton fibers. For example, hydroxyl groups (-OH) on the cotton fibers can react with appropriate functional groups on the polymer dye to form covalent bonds.

2- Copolymerization reaction: If the polymer dye contains monomers that can polymerize with the monomers present in the cotton, a copolymerization reaction can occur. In this case, the polymer dye monomers bond covalently with the cellulose monomers present in the cotton.

3- Oxidation reaction: Some polymer dyes can undergo oxidation reactions in the presence of oxidizing agents such as hydrogen peroxide. These reactions can lead to the formation of covalent bonds between the polymer dye and the cotton fibers.

4- Condensation reaction: Some polymer dyes may contain functional groups capable of reacting with functional groups present on cotton fibers to form covalent bonds by a condensation reaction. For example, amine groups (-NH2) present in the polymer dye can react with carbonyl groups (-CO) present in the cotton fibers to form amide bonds.

These mechanisms are general examples and the precise nature of the covalent interaction would depend on the specific chemical structures of the polymer dye and the cotton fibres, as well as the reaction conditions.

Yes and most probably! Other tests my confirm or exclude such an assumption. NMR may bring further elucidation.

For your expectation. Kindly try to do the preheated wafer before your spray coating. Then only, you achieve adhesive coating on the wafer.

After 24 hours of continuous stirring, the Polymer dissolves properly. Properly use the closed container.

Hi Piyali Mukherjee

Depending on the polymer, you could approximate the density to 1g/ml and with the volume of your box (6^3 nm^3) calculate the mass and then the amount of water molecules.

You have to make a pellet of the powder using a pellet press. Then the piezoelectric constant d33 can be measured by any standard d33 meter like this: https://www.americanpiezo.com/standard-products/d33-meter.html. [This link just for convenience, not a recommendation.]

Before the measurement you have to "pole" the pellet in silicon oil (or something alike) at a temperature slightly above room temp. You can find details about poling from any good papers online.

[e.g.: http://dx.doi.org/10.1016/j.ceramint.2016.09.207; again, just for convenience! It is not my publication.]

IR Spectroscopy in Qualitative and Quantitative Analysis

Written By

Nabeel Othman

Submitted: 03 June 2022 Reviewed: 18 July 2022 Published: 07 September 2022

DOI: 10.5772/intechopen.106625

📷

IntechOpen

Infrared Spectroscopy Perspectives and Applications Edited by Marwa El-Azazy

From the Edited Volume

Infrared Spectroscopy - Perspectives and Applications

Edited by Marwa El-Azazy, Khalid Al-Saad and Ahmed S. El-Shafie

Book Details Order Print

View Full MetricsChapter metrics overview487 Chapter Downloads

REGISTER TO DOWNLOAD FOR FREE

IR Spectroscopy in Qualitative and Quantitative Analysis | IntechOpen

Advertisement

Advertisement

Abstract

The infrared technique is one of the oldest techniques; it deals with the frequencies of bond vibration in a molecule. The main uses of this technique are to identify and determine components in various organic or inorganic compounds. In this technique, a part of the incident infrared radiation is absorbed by the molecules of the sample and the other is transmitted. The favorite method of infrared spectroscopy is FTIR (Fourier transform infrared). There have been many developments in using IR technique in qualitative and quantitative analyses, including the first and second derivatives of the infrared spectrum. IR rays do not damage the exposed skin like other rays such as ultraviolet light. It must be mentioned that the IR technique was used in hyphenated techniques (instead of the detector in chromatographic device), for example, after separation by gas chromatography detected by IR. Also, this chapter contains essential information about Raman spectroscopy. Infrared spectroscopy is a technique that has acceptable accuracy and sensitivity to be one of the most important analytical techniques used in the qualitative analysis, and also, it is used in the quantitative estimation of compounds through measuring the transmitted or absorption intensity of the active groups.

Keywords

Show +Author Information

1. Introduction

The introduction included the followings below:

1.1 Infrared spectroscopy

Spectroscopy is the branch of science contracts with learning about the interaction of the radiation of electromagnetic rays with substances.

Electromagnetic Radiation (EMR) is a type of energy that is around us and taking various forms, these types included radio waves, microwaves, infrared, visible light, ultraviolet X-rays, and gamma-rays. Sunlight is also considered a form of EMR, with Vis light only a minor share of the EM spectrum, which covers a wide range of wavelengths. Visible light has high energy compared with IR light [1, 2].

Infrared Spectroscopy (IRS) deals with the frequencies of bond vibration in a molecule. The main use is to identify the functional groups in many samples. The most covalently bonded compounds, whether organic or inorganic compounds, absorb electromagnetic radiation in the region of infrared. This IR region lies between the visible light and the microwaves region. IR radiation mainly considers thermal energy, in covalent bonds it gives stronger vibrations to molecules. Near-IR can be used in direct determination (nondestructively) of protein present in feeds, and this type of IR region is increasingly used in analytical chemistry for quantitative analysis of various compounds [1].

IR can be divided into main three different bands:

In UV and Vis. of the spectrum, the unite of wavelength is nanometer (nm), while in the infrared region wavenumbers are used, and cm−1 is the unit [2, 4]. The IR spectrum is drawn via a plot of absorbed or transmittance% (T%) against the wavenumber (Figures 1 and 2).

📷Figure 1. The spectrum of an absorption mode.

📷Figure 2. The spectrum of T% mode.

1.2 Fourier transform infrared spectroscopy (FTIR)

The favorite method of IRS is FTIR (Fourier Transform infrared), in IRS the infrared radiation is passed through the investigated sample. A part of the incident infrared radiation is absorbed by the sample and the other is transmitted. The resulting spectrum represents the absorption molecules. FTIR spectrophotometers have many advantages when compared with the older techniques IR, the FTIR instruments are more accurate, and more sensitive, all frequencies of functional groups are estimated simultaneously compared with an individual estimation of functional groups in IR, and they are fast in performance as was in the case of older IR instruments.

1.3 Classification of IR bands

Figure 3 shows the main three types of IR bands they classified according to their relative intensities in the IR spectrum.

📷Figure 3. The types of IR bands according to their relative intensities.

An increase in the dipole moment according to the increase in the distance between atoms caused an increase in the intensity of the absorption peak [5].

1.4 IR peaks shapes

Two main types of IR band shapes are narrow (thin and pointed) and broad (wide and smoother). An example for broad is the O-H peak in alcohols and carboxylic acids, as shown below in Figure 4 [5].

📷Figure 4. The broad peak of the hydroxyl group.

1.5 Range of IR absorption

The typical IR absorption range to covalent bonds in molecules is from 600 to 4000 cm−1. The graph shows the regions of the spectrum where the following types of bonds normally absorb. For example, the sharp band around 2200–2400 cm−1 would designate the possibility of the presence of a C-N or a C-C triple bond, and other ranges in IR-absorption for other types of bounds.

1.6 Overtones and combination bands

When a molecule absorbed electromagnetic radiation in the IR region, then the molecule is promoted from the ground state to the second, third, or even fourth vibrational excited state. These bands are known as Overtones. The intensity of these bands is very weak. It is helpful in the characterization of aromatic compounds.

When two fundamental vibrational frequencies (ν1 + ν2) in a molecule couple give rise to a new vibrational frequency within the molecule, it is known as a combination band.

1.7 Coupled vibrations

The coupled vibrations are observed in groups such as –CH2, NH2, etc. In these groups, the same atoms are attached to the central atom. When –CH2 undergoes vibration, vibrational frequencies for the –CH2 group are observed at 2950 cm−1 (asymmetric stretching) and 2860 cm−1 (symmetric stretching). A number of molecules contain the same functional group and show a similar peak above 1500 cm−1, but they show a different peak in the fingerprint region. Therefore, we can say that each and every molecule has a unique peak or band, which is observed in the fingerprint region; it is just like the fingerprint of a human.

1.8 The functional groups and fingerprint regions

IR spectrum can be separated mainly into two regions. Most of the functional groups show absorption bands at the wavelength (4000–1200 cm−1) region, which is called the functional group region. Will the second region from 1200 to 400 cm−1 is called the fingerprint region. Fingerprint region is characteristic of the compound as a whole. An example is 2-pentanol and 3-pentanol, the two compounds with similar absorption in the functional group region. However, their fingerprint regions are different, because the two compounds differ, and to accurately identify the compound by comparing the fingerprint area with the fingerprint area of a standard or known sample of this compound [6].

1.9 Factors affecting the vibrational frequency

The main factors affecting the vibrational frequency are listed below:

CyclohexanoneCyclopentanoneCyclobutanone1710 cm−11745 cm−11780 cm−1

Empty heading

An increase in wavenumber of the carbonyl group

1.10 General uses of IR

A molecule to absorb IR, the vibrations or rotations within a molecule must cause a net change in the dipole moment of the molecule. The principle of action is to shine infrared light so that it passes through the organic compound to be identified; absorption occurs for some of the frequencies by the model. The different precise frequencies of absorption can be used to identify the different groups in the unknown compound, which represent specific groups of atoms within the molecules over a period of time. We can identify the compound because each group has an absorption frequency that differs from the other. Using a detector to determine the different absorbance, which records the amount of infrared light that passes through the compound. Some frequencies pass without being fully absorbed, while others will be greatly absorbed due to the special chemical bonds in the molecules. This leads to obtaining a spectrum containing different selves expressing the totals in the model [7].

It is now approved that the PBM therapy is an extra accurate and exact term for the therapeutic application of low-level light compared with “LLLT.” A basic principle called the biphasic dose-response included that the large doses of light were found to be less actual than smaller doses. The human skin is reliably exposed to environmental IR radiation, which indirectly or directly stimulates the manufacture of free radicals or reactive oxygen species( ROS). 8~12 μm IR radiation is almost used on full-thickness skin wound therapeutic in rats.

IR light crosses the outer layers of the skin and reaches the tissues of the body. The good thing about using infrared light in therapy is that IR rays do not damage the exposed skin like other rays such as ultraviolet light. An advantage of exposure to IR ray that it improves the circulation of blood and promotes cell regeneration [8, 9, 10, 11].

1.11 Raman spectroscopy

Raman scattering firstly was observed by Raman and Krishnan (Indian physicists) in 1928. It is an analytical technique where the scattered light is used to measure the vibrational energy styles of molecules. Raman spectroscopy can offer chemical structural information, as well as identify the substances to be studied through their characteristic Raman “fingerprint.” Raman spectroscopy extracts the information over the detection of Raman scattering from the investigated sample. After the light is scattered via molecule, the oscillating electromagnetic field of the photon persuades a polarization of the molecular electrons cloud. The photon is transported to the molecule, due to the formation of a very short-lived complex (photon-molecule), and it is called commonly the virtual state. It is not stable and the photon can be re-emitted immediately as scattered light. Approximately 1/10 million photons Raman scattering occurs. The transfer of energy between the scattered photon and molecule and if the molecules gain energy from the photon according to the scattering (an excitation to a higher vibration level) and after that, the scattered photon loses energy, and this phenomena is called Stokes Raman, included an increase in wavelength. If the molecule loses energy by transferring to a lower vibrational level the scattered photon gains energy, inversely, the wavelength decreases, which is called Anti-Stokes Raman. Finally, if most of the molecules are in the ground vibrational level (Boltzmann distribution) and as a result, the Stokes Raman scatter is a continuously more probable process and intense than the anti-Stokes; for this reason, it is approximately always the Stokes Raman scatter used in Raman spectroscopy.

The main differences between IR and Raman scattering are listed in Table 1.

No.IRRaman1.The principle based on the light absorption.The principle based on scattering of light.2.To appear the spectrum the variation in the polar moment of the molecule to be study must not be equal to zero.To achieve the Raman spectrum it is not important to have dipole moment or the change of polarity, the bonds of molecular have specific transition energy in which cause a change of polarizability to give a rise to Raman active.3.The source of light used depend on the region of electromagnetic spectrum, tungsten filament lamp in Near-infrared, coil of Nichrom wire in Mid- infrared and high pressure mercury-arc lamp in Far infrared.laser was the excitation source. Almost , solid state lasers types are used in Raman tools with general wavelengths of 532, 785, 830 and 1064 nm.

Table 1.

The main differences between IR and Raman spectroscopy.

As a common rule included that everything that does not seem in the IRS is taken in Raman (bond of molecule either be with Raman active or be IR active but it not with be both). H2 or CCL4 doesn’t have spectrum in IR; but they give spectra in Raman. Also nitrogen-nitrogen, carbon-carbon, and sulfur-sulfur bonds have a change in polarizability, the incident photons interact with these models, these are examples of bonds that give rise to Raman active spectrum bands, but it is difficult to get spectrum in FTIR [12, 13].

Raman spectroscopy has several applications, such as the identification of materials and identification of different minerals ranging from iron oxy (hydroxides) to rare minerals. Study of the crystallinity, the composition, and uniformity, and also measurement of local temperature and stress. Raman spectroscopy is nondestructive, and the technique has a good resolution [14].

Recently, Raman spectroscopy has been used in blood identification and distinguishing between human and nonhuman blood using a portable Raman spectrometer, which can be used at a crime division, and the bloodstain of human could be distinguished from the non-human ones via using a principal component analysis, and also this analysis is useful for forensic [15].

Advertisement

2. Application

2.1 Qualitative analysis

FTIR spectroscopy is the most reliable tool for identifying bone types and can also be widely used in forensic medicine. Identification of human and non-human skeletal remains unknown to investigators and is of great interest in forensic and anthropological procedures. Especially when the traditional morphological methods for diagnosing and differentiating between these types of bones took a long time. Therefore, the use of infrared spectroscopy and chemical measurement methods to determine the spectral differences between these two types of bones, human, and non-human bones (such as pigs, goats, and cows). The results showed that pig bone is not suspicious of human bone in the study of changes after death because it is more sensitive to environmental conditions than human bone [16].

The micro-FTIR technique was used to characterize the components of a dye painted on the walls of a church in Cyprus. The product was copper-based and the dye contained hydrated copper oxalate. Reflective imaging of the localization sites for the presence of copper and calcium oxalate within the layers of the plate. We conclude from this study that imaging calcium oxalate within different layers of paint samples is very important for studying copper-based pigments in general, and in particular for analyzing pigments used in coatings on different external surfaces [17].

Different heterocyclic compound derivatives have been synthesized via the reaction of ortho-Carboxybenzaldehyde with various aromatic amines (using six amino compounds) to produce Schiff bases (Figure 5).

📷Figure 5. The reaction of Schiff base preparation.

The Schiff bases compounds gave FTIR spectra with an absorption appeared at wavenumber between 1602 and 1614 cm−1 this peak belongs to the new C=N group, and also carbonyl of carboxyl group gave absorption appeared at (1741–1766) cm−1, and the absorption at (3306–3462) cm−1 for OH group of carboxylic acid. The authors noticed that the carbonyl of aldehyde disappeared, therefore our conclusion that FTIR proves the suggested mechanism and helps to suggest the structure of the product using the absorption of selective functional groups (Table 2, Figure 6) [18].

📷

Table 2.

The aromatic part of amine.

📷Figure 6. FTIR spectrum of the product resulted from the reaction of p- toluidine with ortho-carboxybenzaldehyde [from reference 18].

2.2 Quantitative analysis

Fourier transform infrared (FTIR) is used in numerous areas of industrial pharmacy with satisfactory results. The technique’s characteristic and nature tolerate unequivocally bright forecasts for quantitative analysis. FTIR is considered a green analytical chemistry technique. It is very easy, fast to work by a temperately knowledgeable technician, covers a large range of spectra to analyze the pharmaceutical formulations, the main advantages are that it has a good resolution and is considered nondestructive device, and it is also friendly to the environment because in procedure no use of a dangerous organic solvent or any harmful reagents is required for the analysis. Many attempts were suggested for using derivative IR in determination diclofenac sodium in its formulations, but the results indicated that the first derivative spectra are the best technique for determination of diclofenac sodium. The first derivative spectra deleted IR band overlapping with the band understudies and increased sensitivity without any interference of the other band’s [19].

Abdulhameed and Nabil (2022) developed a simple and rapid method for the determination of ketoprofen. The method is based on normal and infrared derivative (first derivative) spectroscopy. The results of the study found that the method is accurate and there is the possibility of its application in quality control to determine ketoprofen in pharmaceutical formulations. Ketoprofen was quantified in a range of estimation from 1000 to 4000 μg/ml. This range was based on measuring the T% of the normal spectrum and its first derivative spectrum versus the concentration of ketoprofen in the solution (Figure 7). The results prove the validity of the method, as the relative errors were +4.33% and 4.78% and the RSD% values were 1.15% and 1.37%, respectively, and since the values ​​are less than ±5%, the method is considered accurate and precise. The research also included the application of the two methods to estimate the compound under study in its different pharmaceutical preparations with a comparison of the results obtained with the results obtained via using high-performance liquid chromatography technique and calculating the t-student and F tests at P = 0.05.

📷Figure 7. The first derivative and the normal spectra of two standard ketoprofen from two companies Erbil and Turkey [from reference 20].

Figure 7 shows the derivative spectra of Standard, Erbil, and Turkey ketoprofen solutions, CCl4 was the solvent used. The two individual peaks of carbonyl groups at 1718 cm−1 as a positive peak and at 1705 cm−1 as a negative peak, and these peaks gave two calibration curves as various concentrations analyses, there is a reverse proportional relationship between the concentration and the percentage of transmittance(T%) (Figure 8) and the other indirect proportion. The reverse proportional relationship is according to decreases in the transmittance% of the solution with an increase in concentration (as shown in Figure 8), will in Figure 9there is a direct proportion or positive relationship for the first derivative IR according to the peak chosen (peaks of carbonyl groups at 1718 cm−1 as a positive peak) [20].

📷Figure 8. Calibration curve via normal IR method via first derivative IR.

📷Figure 9. Calibration curve [from reference 20]. method [from reference 20].

Michael et al (1995) used second derivative IR spectroscopy as a non-destructive tool to assess the purity and structural integrity of various samples such as proteins. Spectroscopy using second derivative infrared is a fast, easy, reproducible, cost-effective, and nondestructive method for assessing the purity of samples of some proteins (water-soluble) extracted from a diversity of sources. The 2ed IR spectra were calm under the lab-proven conditions of aqueous (D2O) solutions of seven different commercial samples for the same enzyme, porcine pancreatic elastase (2.0–3.8 mg protein/100 μl D2O, pD = 5.4–9.1). , the amide at the region defined by I (1700–1620 cm−1) from the IR spectra using the 2ed derivative for each of the seven elastase samples displays a characteristic pair of bands: one of them is very weak showing intensities near to 1684 cm−1; the other is close to 1633 cm−1 is moderate to strong. While one of the 7 samples under study shows a striking decrease in the noted density of amide I bands relative to the 1516 cm absorbance, along with the appearance of a new strong band at 1614 cm−1. That the seventh sample is of much lower quality than the other samples and sure contains a quintile of the protein present in the non-native state. In addition, the apparent slight changes in the relative location, and intensity of a section of the separate amide I band among the seven spectra indicate slight differences in the formation of the amount of the peptide support of the samples under study. From the results of two samples, it seems that these few changes, sample purity, and identification of non-protein contaminants [21].

Advertisement

3. Hyphenated techniques

During the past five decades, hyphenated techniques developed rapidly and seemed to dominate many analyzes by introducing them to solve many problems related to complex analyzes, as they were widely used in the pharmaceutical industries from the stage of discovery to human use and the study of its concentration in living body fluids. Accuracy and high sensitivity, and one of the most important disadvantages are the high costs of the devices, and they need maintenance and accurate knowledge while working on the device. Liquid chromatography-mass spectroscopy (HPLC -MS) is one of the most widely applied hyphenated techniques because MS is more compatible with high performance-liquid chromatography (HPLC), and has good sensitivity compared with nuclear magmatic resonance (NMR) or IR. It is also possible to connect infrared spectrometers with thermal analyzers, the methods used by thermal analysis give information about the important temperature to study the physical properties of different materials. However, it is not always possible to obtain information about the chemical changes that occur as a result of changes in temperature through the literature. We note that it is possible to link the thermal analyzer with an infrared spectrometer in order to obtain information about the chemical and physical changes that occur at different and more appropriate temperatures. More suitable is the connection between thermogravimetric analysis (TGA) and FTIR spectroscopy However, there are limitations in its analytical use. The more advantages of the hyphenated technique include sensitivity, accuracy, speed, and applicability [7, 22].

3.1 Gas chromatography–infrared (GC-IR)

3.1.1 Difficulties in the combination of GC-IR

In the development of joining the IR technique with GC, the speed of the IR must be changed to a high speed so that the unknown components can enter at the same speed from the GC column, in this case, there is a loss of efficacy and the results are not complete. The best way to solve the connecting problem is that the condensation of the gas that comes out from the column and the process is not easy, it must collect all gas eluted because it contains the component and the gas is collected in a cooled part that converts the gas into a liquid because the infrared technique deals with the liquid solutions. Reentry GC technique combined with Fourier transform infrared to give faster and more accurate technique.

3.1.2 Application

Salerno, et al (2020) suggest an accurate method for determination of illicit drugs via gas chromatography–Fourier transform infrared spectroscopy. According to the increasing number of synthetic molecules that can be used in the illicit drug market, correspondingly they require strong separation and sophisticated analytical techniques. It can be achieved by spectroscopic measurements, using firstly a gas chromatography (GC) technique as the separation device. Then the GC is coupled with FTIR to give a powerful tool. In the current study, the efficacy of GC-FTIR, in achieving elucidation of the structure of 1-pentyl-3(1-naphthyl) indole, known as JWH-018, a synthetic cannabinoid whose components have been identified as being a component of non-incense “incense blends” have been demonstrated in the current study. Moreover, it was quantified with an estimation range on the nano-gram scale. It was obtained in the range of 20–1000 ng, the detection limit and the quantification limit were evaluated to be 4.3 and 14.3 ng, respectively. Finally, the new technique was applied to quantify the activity in the “ST” sample." A real drug seized by law enforcement officers, consisted of a herbal collection containing four types of industrial cannabis belonging to the JWH class. Correct estimation of this type of compound showed that they are chemically similar to each other. The usefulness of the proposed method of analysis using related techniques. It obtains reliable results for complex mixtures of illegal drugs and is a widely applicable alternative to measurement using mass spectrometry [23].

Advertisement

4. Conclusions

Infrared is an important technique and its main application at the beginning to identify polar organic compounds that have a dipole moment. The infrared device has been developed, and we have obtained Fourier transform infrared (FTIR) technique, which is characterized by high accuracy, high sensitivity, and speed of analysis of the compound as a whole. The uses of the technique in the qualitative analysis are identifying the effective groups and the type of bonds between the different atoms constituting the molecule. The technique is used in the quantitative analysis through measurement of absorption or percentage of transmittance (proportional with co

Ethanol addition to self-polymerized acrylic resins significantly decreases the hardness and increases the surface roughness of acrylic resins. So, ethanol dissolves acrylic polymer by swelling the polymer, allowing it to penetrate and interact with the polymer through carbonyl-hydroxyl hydrogen bonds to separate the chains.

Ethanol dissolves acrylic polymers through various chemical interactions, including hydrolyzing ester and nitrile groups, reacting with amino groups, decreasing alcohol exertion via hydrophobic forces, partial deprotonation of carboxyl groups, and acting as a solvent in specific conditions and admixtures. thus, it reduces the rate of acrylamide polymerization and its molecular weight proportionally to its concentration in water and the length and character of the aliphatic chain.

Best regards,

All the things you mentioned are already in textbooks. The best model is the one that fits to your results with minimum %error or within the standad deviation of your experimental results. It is more than 20 years I followed courses on, but now no more because my profile is much more oriented to polymer synthesis and characterisation. My Regards

my method is by sputtering and by sun gel I do not deposit my thin films.

Dear Ismail Khan, please have a look at the following RG link, may be it gives a partial answer. What is the nonachieved expected result by your recipe. My Regards

https://www.researchgate.net/publication/230494097_Role_of_dimethyl_sulfoxide_as_a_solvent_for_vinyl_polymerization#:~:text=They claimed that DMSO reduces,the polymer structure took place.

Dear Hazel Anne Cledera, you can use AFM to compare surface relief and groups. Surface tension or surface free energy experiment also witnesses on any possible changes on the surface. My Regards

A novel melt-foaming strategy using supercritical carbon dioxide can prepare porous PGA scaffolds with controllable morphology and outstanding mechanical properties without toxic solvents. Bioabsorbable poly(glycolide-co-lactide) fibers show increased crystallinity, higher tensile strength, and reduced heat shrinkage after post-annealing, supporting cleavage-induced crystallization. Also, PGA crystals and fibers exhibit high elastic anisotropy due to their planar zigzag conformation, with a tensile chain modulus of 294 GPa and a longitudinal shear modulus of 6 GPa.

Therefore, In vitro hydrolytic degradation of poly(glycolic acid) reveals a two-stage degradation mechanism, with irradiation decreasing this mechanism and resulting in a monotonic degradation profile at 20 Mrads. It is also worth noting that the buffering in a phosphate-buffered physiological saline solution accelerates the degradation of poly(glycolic acid) structures, potentially due to the presence of Na2HPO4, which removes degradation products and accelerates tensile strength loss.

Please see this researches that might be useful:

· Novel fabricating process for porous polyglycolic acid scaffolds by melt-foaming using supercritical carbon dioxide, ACS Biomaterials Science & Engineering, 2017. DOI: 10.1021/acsbiomaterials.7b00692

Best regards,

Dear Hemamalini Rawindran,

Polymer membranes and porous materials absorb ionic liquids, causing changes in ionic conductivity and mobility. Polymer inclusion membranes (PIMs) with ionic liquids facilitate ion movement by acting as proton exchange membranes, improving efficiency in processes like microbial fuel cells and electrodialysis, and by enhancing ion conductivity and selectivity for ion transport based on the interaction between the ionic liquid and the polymer matrix.

Best Regards

Dear all, the reason is that crosslinking density increases with duration and dose of radiation. As far as crosslinking density is high, the uncrosslinked portion find it difficult to diffuse out the crosslinked one. So my suggestion is to select the best solvent for the acrylate copolymer in question, and to give as much time as you can for swelling to facilitate extraction of the linear chains. My Regards

The relaxation time and initial stress parameter significantly affect the displacement, stress, temperature change, and volume fraction field distributions in initially stressed thermoelastic half-space with voids due to thermal source. The optimal flow velocity changes non-linearly with respect to fabric anisotropy and the preferable flow direction, affecting inter-bundle void formation in HDPE.

Void formation in HDPE is related to irregularities in the grain-boundary structure of films, and the rate of observable hole formation is accounted for by either void growth at a grain-boundary triple-point junction or by grain-boundary grooving. The predictive model for volatile-induced void formation in thermoplastic polymeric materials incorporates material properties, processing conditions, and part thickness to predict void growth.

Particle size, density, gas flow rate, bed height, and model width affect void formation and breaking in a packed bed, and correlations have been proposed to predict void formation and breaking. Voids have complex internal structure and dynamics, with a hierarchy of structures in the density field and velocity field. Hot-compaction of polypropylene and polyethylene composites significantly alters their thermal expansion behavior, with mechanical and thermal anisotropy being most pronounced in polyethylene composites.

I am not a polymer expert, but the usual solvent for precipitating out "high" polymers, even if they are polar or have charged groups, is methanol. Depending on the fraction of amine groups that were quaternized, ether is another simple solvent that usually refuses to dissolve solids that have formal charges ("salts"). The counter-ion to the quaternized center will have a role to play in which solvents swell, dissolve, or precipitate the polymer. Generally, using HSAB theory (hard/soft acid/base theory), it's the smaller, harder anions that favor precipitation. Chloride (hard anion) will favor precipitation more so than iodide or thiocyanate (softer anions) in methanol and weakly-polar solvents. Answering this question will require experimentation, I suspect, even if in the hands of experts. Best of luck.

Dear Shimaa Mustafa ! I suppose a good copolymer yield will be only with alternating radical copolymerization, see my publications.

I want some suggestions for the covalent immobilization of aptamer on polymer membrane surfaces.

Dear all, as far as I know, MIP are designed to recognize targeted molecules and not nanoparticles. Nanoparticles are used sometimes as sacrificial support of targeted molecules. May be if you search for such ' sacrificial nanoparticles ' in MIP preparation, you will find how they are extracted. My Regards

Suggest you to read the research paper that was published on JACS.

Alvena Shahid ohh. thank you so much!!!

If you observe a linear relationship in the plot of (ahv)^2 versus energy, it suggests that the material has a direct band gap, as this behavior is typical for direct band gap materials. On the other hand, if you observe a linear relationship in the plot of (ahv)^(1/2) versus energy, it suggests an indirect band gap.

Misbah Waheed Alternative methods include Surface Plasmon Resonance (SPR), Electrochemical Impedance Spectroscopy (EIS), Fluorescence-Based Techniques, Capillary Electrophoresis (CE), Microfluidic Devices, and Atomic Force Microscopy (AFM)

Dear all, years ago I answered a question with a similar context. Suspension is a heterophase system, composed of immiscible phases (deslike each other), once put under the agitation shear, the dispersed phase will take a sphere (or -like) form because it is the shape that has the minimum possible surface area per volume, so that the contact interphase (or interface) between unlike phases will be at its lowest possible. It is also possible to use surface free energy in explaning this. To simplify this with an example, lets take a cube with a 1 liter volume and a sphere (balloon) with a volume of 1 liter also. If the surface areas are deduced, the one of the cube (or any other geometrical form) is higher than that of the sphere (at equal volumes condition of course).

Now, the size of suspension particles depends essentially on shear level, concentration, and to lower extent on the type and concentration of the suspention stabilizer. My Regards

Kishore Kumar Sriramoju thank you very much for your advice.

In the co-bonding of thermoset and thermoplastic polymers, the interdiffusion of the polymers results in the formation of an interphase between them. The dependence of the gelation time on the initiator concentration is determined by rheometer measurements. Differential scanning calorimetry measured the speed of cure. The interphase thickness of the co-bonded polymers is measured with an optical microscope.

Thermoplastic (TP) polymer is bonded with thermoset polymer through a curing reaction of the thermoset resin. Although co-bonding may refer to the bonding of two parts with or without an adhesive between them.

It is of the utmost importance to investigate the influence of the aforementioned parameters on the TP-TS interphases. the effect of initiator concentration on the interphase morphology, which is crucial for the co-bonded parts, the gelation time of the resin at different initiator concentrations is measured and DSC tests are conducted to determine the cure behavior (cure speed and degree of cure).

To investigate the diffusion kinetics, the diffusivity of the mixtures is calculated based on Fick’s second law of diffusion using the measured interphase thicknesses and gelation times. DSC peak started and reached its maximum must have obtained to investigate the speed of curing. In addition, to gain more insight into the cure behavior, the heat and degree of cure can be calculated, the method used for controlling the interphase thickness by varying the initiator concentration paves the way for investigating the effect of interphase thickness on the processing-induced deformations of the co-bonded TP-TS composites.

Shaswat Mohanty Thank you for your answer, I will try it.

Dear Arif Shahul Hameed, neither of your suggestions hold. It depends on the %conversion and the MW (and MWD) of the copolymer. This later is function of the reactivity ratio of both monomers relative to each other. This means that it is not very likely to have the same number of each monomer in one chain (macromolecule). So first get the % conversion, determine the MW and sequence distribution (NMR) of the monomers in each chain (in such circumstances, only mean/averages values are obtained). My Regards

Definitely YES!

The liquid does not only confront with the interfacial forces, but equally with morfology of the surface.

G. Bognolo

If you have access to Ansys's material modules, they have a homogenised version of the material properties which includes a thermal expansion coefficient, vary it by a little up or down to see how it matches pre-existing data or how it fits your model. The other option is to contact Dr Jorgen Bergstrom (https://www.researchgate.net/profile/Jorgen-Bergstrom) @JorgenBergstrom for advice.

It depends on various parameters, but the type of the polymer is the first think to consider.

https://www.sciencedirect.com/topics/materials-science/mold-release-agent#:~:text=A mold–release agent is,its removal from the mold.

Hi,

the accepted explanation is the conformational changes caused by the polymer adsorption on the nanoparticle surface. In short, the adsorption reduces enthalpy due to the attractive polymer-particle interaction, and these savings help overcome the entropic penalty related to the shape distortion. Another option is that some nanoparticles may change the electrochemistry of the solution (pH, zeta potential, screening length, etc.), tuning the internal interactions within the polyner chain. You may find more details in our papers:

Don't forget to consider the peculiarities of the experimental techniques in question, such as the one mentioned by Partha Pratim Chowdhury. How did you obtain your data?

Thanks a lot Md Masuduzzaman

I have got my clarification about this.

https://www.researchgate.net/post/What_is_the_best_solvent_of_PEO#:~:text=PEO%20also%20dissolves%20in%20many,with%20solubility%20increasing%20with%20temperature.

If adding water to the IPA solution makes it transparent, it's possible that the polymer may have re-dissolved in the water due to the change in solvent conditions. In that case, you can try adding a different non-solvent that is less miscible with water, such as a different organic solvent like hexane or diethyl ether. This may help to induce precipitation of the polymer from the solution.

The basic idea of ​​this theory is to take the electron density of the ground state ρ (r) as the main variable, and write any other magnitude as a function of it. This theory is based on a variational principle. which requires the total energy to be a single density functional, and that this energy is minimal for the density of the ground state. The best procedure for performing the DFT is Kohn-Sham, they treated the N-body problem using the single-particle Schrõdinger equations called the Kohn-Sham equations. Solving these equations leads normally to the energy E(ρ) and the densityρ (r), of the ground state.The functional E (ρ) contains a non-classical contribution, called the exchange and correlation energy Exc (ρ) and its derivative by relation to ρ (r) which represents the exchange and correlation potential Vxc(ρ). The formalism of DFT is based on the Hohenberg - Kohn theorems. First, Hohenberg and Kohn showed that the total energy of an electron gas in the presence of an external potential, created by the nuclei is a unique functional of electron density ρ (r): E = E[ρ(r) ], Second, they showed that the minimum value of this functional is the exact energy of the ground state and that the density which leads to this energy is the exact density of the ground state. The other properties of the ground state are also functional of this density: E(ρ0) = min E(ρ ). ρ0 : The density of the ground state.

The functional of the total energy of the ground state is written as follows: E[ρ(r)]= F[ρ(r)] + ∫ VXC (r) ρ (r) d3 r. The functional F [ρ (r)] is universal for any system with several electrons. If this functional is known, then it will be relatively easy to use the variational principle. To determine the total energy and electron density of the ground state for a given external potential. Unfortunately, the Hohenberg - Kohn theorem gives no indication of the form of F [ρ (r)].

Dear Sarah NADIAH Binti Nordin, what are the components of the nanocomposite? You can do:

- disslution, extraction, titration

- thermal analysis (TGA)

The dilatometric method was found to be the most accurate and most convenient method for measuring the chemically bound water fraction. Polymer conditioning was found to release significant volumes of bound water. Further bound water release was produced by mechanical dewatering. The amount of bound water released increased with the degree of mechanical dewatering pressure applied. The chemically bound water fraction was not affected by polymer conditioning or mechanical dewatering. A reduction in bound water brought about a corresponding increase in cake solids concentration. Sludge bulk density increased with cake solids concentration. Apparent sludge floc density of the unconditioned, undewatered sludge sample was predictive of ultimate dewatering performance in many cases.

The following categories were derived by humiditycontrolled, low temperature drying of a vacuum filter cake:

l. Free moisture: water which is loosely bound to sludge solids; removed by gravity thickening.

2. Immobilized moisture: water trapped within the floc structure; removed by mechanical dewatering.

3. Bound moisture: water which is adsorbed onto individual particles; removed by thermal drying.

4. Chemically bound moisture: water which is tightly bound to the solids by chemical attraction: removed only by high temperature (105°C).

Chelsea V S Your hypothesis is not without foundation.

Размер частиц зависит от перемешивания и слипания. В момент точки липкости микрокапли слипаются и получаются агрегаты. Если сделали больше соотношение дисперсионной среды к дисперсной фазе, то затруднили слипание и получили много мелких капель и частиц полистирола. Если возьмете мою методичку легко получите нужный размер капель.

Sorry I cannot read your language, but really want to know how to make it more soluble in dmf. You suggest using eg. Dichloromethane. How much to add and to what setup use it?

First of all you should clarify your operating conditions to avoid the unacceptable noise which has been observed your provided spectra. Then it could be much more benificial if you consider a comparative study among all the considered constituent / ingredient which you were incorporated in the polymeric composites individually for better understanding the actual behaviour of your final fabricated composites.

Dear Fatemeh

Use of WST-1, CCK-8 assay kit, XTT and so on (as recommend above by dear colleagues) in which a colored solution can be analyzed instead of the crystalized products would be great. However, I suggest you first investigate the reducing property of your cell-free scaffold on MTT reagent. If the violet formazan crystals were produced by the cell-free scaffold, you should choice another group of viability assay reagents which work by different mechanism. For instance, you can measure LDH level, study DNA content, Protein content, or even use Crystal Violet assay.

PPNCl is an extremely lipophilic and relatively stable salt with a huge, greasy cation, which could be written in condensed form as [Ph3P=N=PPh3]+[Cl]-. Paired with huge anions it forms crystals useful for single-crystal x-ray spectroscopy. Added to a solution in a polar, protic solven, containing anions of many sizes, it tends to precipitate the large ones and if there is an equilibrium mixture of anions (like a mixture of polyoxometalates like Keggin anions of different sizes), by LeChatelier's Principle, the equilibrium will shift to the large anion that precipitates in the presence of this large cation. The complementary scheme is also possible; instead of precipitating PPN(+) salts from polar, protic solvents like alcohol or aqueous mixtures, you can use the greasiness (lipophilicity) of PPN(+) to help dissolve anions in less polar, aprotic media like ethers (diethyl ether, THF, dioxane) in which the anion (like an anionic transition-metal complex) is insoluble in the form of a sodium salt or a potassium salt. When used as an aid to a catalyst I would think of it as a chaotrope (a substance that doesn't self-assemble into clusters like micelles made from detergents, but rather just helps increase the contact of non-polar molecules with polar ones).

Here is a 2010 crystallography paper with useful references: .

The use of PPN+ goes back to the 1970's at least so many book chapters could be written about it. But this should get you started.

How to elucidate molecular structure is a classical course of organic chemistry. It takes hours of training, and help of an experienced chemist may is useful. For example, the IR spectrum gives me a few basic informations about possible functional groups at first glance, but full, deeper interpretation will take one to several hours looking at correlation tables, books, etc. Same for NMR spectra.

”hi, do you pour your gel from one point? This also looks like you choose one point and pour gel to the cast. i would recommend you to move through the cassette when you are pouring gel. If you continuously pour gel from one point, the first amount of gel starts polymerization and if you continue to add more gel under this part, the weight causes shrinkage . So you can try to move your pipette during gel pouring from one side to other side of the cassette. And be sure that you are pouring your gel immediately before your mix is ready.

Iron nanoparticles typically do not exhibit inherent antifungal activity due to several reasons. Firstly, the primary mode of action for many antifungal agents involves targeting specific cellular processes or structures that are unique to fungi. Iron nanoparticles, on the other hand, do not possess specific mechanisms to target fungal cells or disrupt their growth.

Secondly, the cell wall structure of fungi plays a crucial role in their resistance to various antifungal agents, including nanoparticles. Fungal cell walls consist of complex layers of polysaccharides, proteins, and other components that provide structural integrity and protection against external threats. This barrier can prevent the direct interaction of iron nanoparticles with fungal cells, limiting their antifungal activity.

Moreover, iron nanoparticles may undergo oxidation or aggregation in the presence of environmental factors, such as moisture or oxygen, which can further diminish their potential antifungal effects.

It's important to note that the efficacy of nanoparticles as antifungal agents can vary depending on their size, surface properties, and coating materials. While iron nanoparticles may not exhibit significant antifungal activity, other types of nanoparticles (e.g., silver, zinc oxide) have been extensively studied for their antifungal properties.

Raza MA, et al. (2016). Green Synthesis of Iron Nanoparticles and Their Environmental Applications and Implications. Nanomaterials, 6(11), 209.

good luck

Sewar Abuassi Yes!