We have been working to determine optimal (rapid and accurate) methods for calculating basic physicochemical properties of orphaned/under-characterized compounds using quantum chemical techniques. While we mainly approach the problem of data gaps from an emergency response perspective/framework, the same methods can be applied to gain the basic input parameters for models of environmental fate and transport and toxicity for chemical prioritization schemes. Because of the large time and monetary cost, among other factors, required to fully characterize a chemical species, there are significant gaps in our knowledge of the simple physicochemical properties of many compounds in use. As an example, the January 2014 Elk River, WV Chemical Spill highlighted the large numbers and diversity of compounds in commerce that are poorly characterized. That there are 84,000 compounds alone in the TSCA Inventory illustrates the sheer volume of data that may be needed to support efforts toward prevention, mitigation, and remediation of future spills and in overall chemical risk prioritization. Fast and accurate computational methods can help to fill these knowledge gaps on a timescale that can aid both emergency response efforts, as well as having the potential to turnover estimates for absent property data for large number of databased compounds. There is a real need for universal, rigorous, accurate, and fast methods of property prediction. By leveraging supercomputing infrastructure and modern quantum chemical techniques, accurate estimates of physicochemical properties (such as gas- and aqueous-phase permanent dipole moments, polarizabilities, molar volume, aqueous solubility, partitioning coefficients, vapor pressure, etc.) can be obtained. These in turn can be utilized in higher-order persistence, bioaccumulation, and toxicity (PBT) modeling. Progress in our development of models for accurate and predictive determination of physical properties of orphaned/under-characterized compounds and emerging contaminants will be summarized, and the applicability of the methods in high-throughput computational screening of compound databases for PBT behavior will be discussed.

Rapid and accurate quantum chemical physicochemical property computational estimates for under-characterized compounds

255th National Meeting (2018)

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