The thermal stability of short alkanethiol CH(3)(CH(2))(7)SH (C(8)) and long C(18) self-assembled monolayers (SAMs) is investigated using grazing angle reflection-absorption infrared spectroscopy, cyclic voltammetry, and molecular dynamics simulation. We track the disordering of SAM by untilting and gauche defect accumulation with increasing temperature in the 300-440 K range, a range of interest to tribology. Molecular dynamics simulation with both fully covered and partially covered C(6), C(8), and C(18) monolayers brings out the morphological changes in the SAM, which may be associated with the observed thermal stability characteristics. The molecular dynamics simulations reveal that short-chain C(6) and C(8) alkanethiols are more defective at lower temperature than the long-chain C(18) alkanethiol. With increasing temperature disorder in the SAM, as reflected in both untilting and gauche defect accumulation, tends to saturate at temperatures below 360 K for short-chain SAMs such that any further increase in temperature, until desorption, does not lead to any significant change in conformational order. In contrast the disorder in the long-chain C(18) SAM increases monotonically with temperature beyond 360 K. Thus, in a practical range of temperature, the ability of a SAM to retain order with increasing thermal perturbations is governed by the state of disorder prior to heat treatment. This deduction derived from molecular dynamics simulation helps to rationalize the significant difference we have observed experimentally between the thermal response of short- and long-chain thiol molecules.

This paper provides a review of the available literature on computational schemes for rational solvent design, with a focus on solvent extraction and crystallization (the two most common unit operations) in pharmaceutical industry. The computer-aided design of solvents is important as a cost-effective tool, especially with the regular development of new pharmaceutical molecules. Also, there is a need to minimize the amount and the number of solvents used with regard to environmental, health, and toxicological concerns. This review covers the properties of interest and the predictive methods for estimation of these properties in solvent design including the group contribution based methods, quantitative structure property prediction methods and molecular modeling methods. In addition, the various optimization approaches for rational solvent design such as outer approximation, branch and bound, simulated annealing, and genetic algorithm are also discussed.

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