Benchmarking the SPARC software program for estimating solubilities of naphthalene and anthracene in organic solvents

The SPARC software program was benchmarked for calculating the solubilities of two representative polyaromatic hydrocarbons (PAHs), naphthalene and anthracene, in a range of organic solvents at various temperatures. Although SPARC was able to reasonably approximate the solubilities of naphthalene in some organic solvents, gross errors were obtained for other solvents. For anthracene, poor prediction performance was observed in all solvents considered. Overall, the results suggest that SPARC is currently not suitable for accurately predicting the solubilities of representative PAHs relevant for the petroleum sector in various organic solvents

Automated Identification and Classification of Stereochemistry: Chirality and Double Bond Stereoisomerism

Stereoisomers have the same molecular formula and the same atom connectivity and their existence can be related to the presence of different three-dimensional arrangements. Stereoisomerism is of great importance in many different fields since the molecular properties and biological effects of the stereoisomers are often significantly different. Most drugs for example, are often composed of a single stereoisomer of a compound, and while one of them may have therapeutic effects on the body, another may be toxic. A challenging task is the automatic detection of stereoisomers using line input specifications such as SMILES or InChI since it requires information about group theory (to distinguish stereoisomers using mathematical information about its symmetry), topology and geometry of the molecule. There are several software packages that include modules to handle stereochemistry, especially the ones to name a chemical structure and/or view, edit and generate chemical structure diagrams. However, there is a lack of software capable of automatically analyzing a molecule represented as a graph and generate a classification of the type of isomerism present in a given atom or bond. Considering the importance of stereoisomerism when comparing chemical structures, this report describes a computer program for analyzing and processing steric information contained in a chemical structure represented as a molecular graph and providing as output a binary classification of the isomer type based on the recommended conventions. Due to the complexity of the underlying issue, specification of stereochemical information is currently limited to explicit stereochemistry and to the two most common types of stereochemistry caused by asymmetry around carbon atoms: chiral atom and double bond. A Webtool to automatically identify and classify stereochemistry is available at http://nams.lasige.di.fc.ul.pt/tools.ph

Machine Learning, Quantum Mechanics, and Chemical Compound Space

We review recent studies dealing with the generation of machine learning models of molecular and solid properties. The models are trained and validated using standard quantum chemistry results obtained for organic molecules and materials selected from chemical space at random

Extended Huckel theory for bandstructure, chemistry, and transport. II. Silicon

In this second paper, we develop transferable semi-empirical parameters for the technologically important material, silicon, using Extended Huckel Theory (EHT) to calculate its electronic structure. The EHT-parameters areoptimized to experimental target values of the band dispersion of bulk-silicon. We obtain a very good quantitative match to the bandstructure characteristics such as bandedges and effective masses, which are competitive with the values obtained within an $sp^3 d^5 s^*$ orthogonal-tight binding model for silicon. The transferability of the parameters is investigated applying them to different physical and chemical environments by calculating the bandstructure of two reconstructed surfaces with different orientations: Si(100) (2x1) and Si(111) (2x1). The reproduced $\pi$- and $\pi^*$-surface bands agree in part quantitatively with DFT-GW calculations and PES/IPES experiments demonstrating their robustness to environmental changes. We further apply the silicon parameters to describe the 1D band dispersion of a unrelaxed rectangular silicon nanowire (SiNW) and demonstrate the EHT-approach of surface passivation using hydrogen. Our EHT-parameters thus provide a quantitative model of bulk-silicon and silicon-based materials such as contacts and surfaces, which are essential ingredients towards a quantitative quantum transport simulation through silicon-based heterostructures.Comment: 9 pages, 9 figure