B. Christopher Rinderspacher

Chemical Compound Design Using Nuclear Charge Distributions

Finding optimal solutions to design problems in chemistry is hampered by the combinatorially large search space. We develop a general theoretical framework for finding chemical compounds with prescribed properties using nuclear charge distributions. The key is the reformulation of the design problem into an optimization problem on probability density functions in chemical space. In order to achieve tractability, a constrained search formalism on the nuclear charge distributions, which are non-negative, is used to reduce the dimensionality of the problem. Furthermore, we introduce approximations to the exact functional, as derived, for common design properties and constraints.

Enriched optimization of molecular properties under constraints: an electrochromic example

We present a deterministic optimization procedure of molecular properties that ensures diverse coverage of the given chemical compound search space. Diversity is ensured by enriching the set of computed molecules by candidates which maximize the distance to the given set. Each new such point becomes the starting point for a (constrained) optimization as introduced by J. M. Elward and B. C. Rinderspacher, Phys. Chem. Chem. Phys., 2015, 17, 24322–24335. We demonstrate the capabilities on the design of electrochromic chromophores in a search space of 5184 molecules. The enriched optimizations utilizing a dynamic reordering of the search space found the global optima in all studied problems.