Organic Crystal Engineering of Thermosetting Cyanate Ester Monomers: Influence of Structure on Melting Point

Abstract

Key principles needed for the rational design of thermosetting monomer crystals, in order to control the melting point, have been elucidated using both theoretical and experimental investigations of cyanate esters. A determination of the thermodynamic properties associated with melting showed that the substitution of silicon for the central quaternary carbon in the di(cyanate ester), 2,2-bis(4-cyanatophenyl)propane, resulted in an increase in the entropy of melting along with a decrease in the enthalpy of melting, leading to a decrease in the melting temperature of 21.8 ± 0.2 K. In contrast, the analogous silicon substitution in the tri(cyanate ester), 1,1,1-tris(4-cyanatophenyl)ethane, resulted in no significant changes to the enthalpy and entropy of melting, accompanied by a small increase of 1.5 ± 0.3 K in the melting point. The crystal structure of 1,1,1-tris(4-cyanatophenyl)ethane was determined via single crystal X-ray diffraction, and the structures of these four di(cyanate esters) and tri(cyanate esters) were examined. Although both the empirical models of Lian and Yalkowsky, as well as Chickos and Acree, provided reasonable estimates of the entropy of melting of 2,2-bis(4-cyanatophenyl)propane, they successfully predicted only certain effects of silicon substitution, and did not capture the difference in behavior between the di(cyanate esters) and the tri(cyanate esters). Semi-empirical molecular modeling, however, helped to validate an explanation of the mechanism for the increase in the entropy of melting of the silicon-containing di(cyanate ester), while providing insight into the reason for the difference in behavior between the di(cyanate esters) and tri(cyanate esters). Taken together, the results assist in understanding how freedom of molecular motions in the liquid state may control the entropy of melting, and can be utilized to guide the development of compounds with optimal melting characteristics for high-performance applications.

Calculation of Five Thermodynamic Molecular Descriptors by Means of a General Computer Algorithm Based on the Group-Additivity Method: Standard Enthalpies of Vaporization, Sublimation and Solvation, and Entropy of Fusion of ordinary Organic Molecules and Total Phase-Change Entropy of Liquid Crystals

“…In order to answer this question more than 1200 experimental values have been inserted into the database, originating from Acree's compendium publication [8], complemented by recent values for crown ethers [29], fluorinated alcohols [33], adamantanes [53], 2-chloro-3-(trifluoromethyl)pyridine [61], cyanatophenyl derivatives [62], diphenylamines [63], fatty acids [64], pyridinecarbothioamides [65], isoniazid [66] and phenylthiazole-thione [67]. Figure 5 shows the correlation of the experimental with the predicted values, calculated by means of Formula 2.…”

“…The main source for these values was found in the comprehensive collection of Chickos, Acree and Liebman [21] and in its update [60]. More recent entropy-of-fusion data were found for long-chain fluorinated alcohols [33], halogenated fluorenes [35], di-and tri(cyanatophenyl)alkanes and -silanes [62], 2-cyano-4′-methylbiphenyl [83], diphenyl cyclohexyl-phosphoramidate [84] and 3,4-dinitrofurazanfuroxan [85]. The complete set of compounds with experimental entropy-of-fusion values amounted to a total of 2809 used for the evaluation of the atom-group parameters, yielding 188 valid atom groups.…”

RM1 Semiempirical Model: Chemistry, Pharmaceutical Research, Molecular Biology and Materials Science

“…Structures of several organic molecules obtained by X-ray crystallography 65,78,82,84,91 have been compared with RM1 predicted geometries, these include thiazolylhydrazone, 84 1 -c y a n o a c e t y l -5 -t r i f l u o r o m e t h y l -5 -h y d r o x y -4,5-dihydro-1H-pyrazoles, 82 2,5-dimethyl-3,4-dihydro-2H-pyran-2-carboxylic acid, 78 4-butyloxyphenyl 4'-decyloxybenzoate, 65 and 2,2-bis(4-cyanatophenyl) propane. 91 As Havlík et al 88 describes for some compounds that are not easy to obtain in the form of a single crystal, computational methods, such as RM1, constitute a very important tool. RM1 can also be used instead of higher level ab initio calculations because of the low computational cost and competitive accuracy, such as in the case of Callipeltin A.…”

“…In some of these studies, the authors made comparisons among several semiempirical, as well as high-level methods. 91,245,258,260, In addition, the authors performed these comparisons both on small sets of molecules of particular classes of compounds, as well as on larger sets of molecules. These comparisons range from applications of computational chemistry for molecules and systems, up to hybrid calculations of molecular dynamics.…”

“…345 RM1 was also used in many studies to predict physicochemical and optical properties, such as activity coefficients, 346 reaction energies, 310,343 energy profiles of reactions, 317,329 and cysteine-histidine proton transfer reactions in different environments. 91,309,316,318,323,344 In most of these studies, RM1 was used to obtain the ground state geometries and other molecular properties, either in gas phase, or in solution (using any solvation model). In the following studies, RM1 displayed good performance: (i) in reproducing circular dichroism (CD) spectra for (M)-hexahelicene and in giving experimentally consistent results for reduced rotational strengths of cyclohexanones, 324 (ii) in being consistent with experimental data for aqueous pK a of 48 sulfhydrol compounds (thiols) by using SM5.4 and SM8 solvent models 322 and (iii) in giving low overal mean absolute error (MAE) for Δ r H (enthalpy of reaction) of 34 isomerization reactions of 4.2 kcal mol -1 and ∆ f H of 1356 molecules, radicals, ions, and complexes (MAE of 5.0 kcal mol -1 ).…”