(660d) Intelligent Algorithms for the Design of Rare-Earth Metal Forcefields

Rare earth elements (REEs) are a common component of many consumer electronics. However, the separation/ purification of these materials from more common metals such as iron, copper, and aluminum remains a difficult process. Additionally, the current state-of-the-art for REE extraction involves a series of hazardous solvent extraction steps that render the process environmentally unfriendly. Several recent investigations on sustainable REE processing have focused on “biomining” which utilizes interaction with various biomolecular species (such as peptides) to drive the separation. Molecular modeling can play an important role in the development of these techniques as the design space for binding peptides can be enormous and insights into the binding mechanisms on a molecular scale could greatly benefit the synthetic biologists capable of building specific peptide molecules for investigation. These insights from simulation are only beneficial if one is able to accurately describe the specific atomic interactions that make up the system. Unfortunately, classical interaction parameters for monoatomic trivalent ions are known to suffer from deficiencies due to their high charge density which leads to local polarization. More accurate descriptions can be achieved via a technique termed electronic continuum correction (ECC) which uses selective charge scaling to soften the electronic interactions to mimic the induced dipoles. We demonstrate an application intelligent algorithms to optimize these parameters against a collection of experimental observables to produce improved models of REEs and allow for accurate property prediction, thereby enabling improved design of sustainable separation technologies.