Scalable Enrichment of 48Ca at the Solid/liquid Interface by Chemical and Electrochemical Methods

Enrichment of 48Ca at the gram to kilogram level is critical for advancing scientific frontier, such as creating new heavy elements, and Neutrinoless Double Beta Decay experiments to examine the Standard Model. However, the natural abundance of 48Ca in the earth crust is only 0.187%. This proposal aims to develop chemical and electrochemical methods to enrich 48Ca at ambient conditions and low cost. In chemical separation, a solid phase containing Ca2+ ions and a liquid solution of Ca2+ are in contact and exchange ions. In electrochemical separation, Ca2+ ions are driven by electrical potential to be reduced to either Ca or inserted to an electrode matrix, and the nature of such electrochemical reaction is also a chemical reaction. Both strategies can be operated at mild conditions such as room temperature and ambient pressure, and there is no toxic materials involved. This proposal will screen and identify suitable materials with high separation factor and high ion exchange rate for efficient and low-cost separation of 48Ca. Modeling based on solid-state physics and physical chemistry first unveil design rules for screening suitable materials. In both chemical and electrochemical separations, the solid phase should have high strong bonding between Ca2+ and the environment, and a high Debye temperature (TD). The liquid phase should have a low coordination number of Ca2+ and weak ion-solvent interaction. Moreover, to enhance ion exchange rate, nanostructures of the solid phase will be made. Based on these guidance and recent progress in Ca-ion batteries, we will screen potential materials at a high-throughput fashion to maximize the separation factor alpha. The solid phase includes Ca salts, Ca-ion battery materials, Ca alloys. The target is to have strong bonding and potentially high TD. The liquid phase includes salts with large and weak cation-anion interactions. The solvent will be those with low dielectric constant to reduce the strength of ion-solvent interactions. The separation of isotopes will be measured by multi-cup inductively coupled plasma mass spectroscopy (MC-ICP-MS) with high accuracy of 0.01%. Moreover, machine learning-based algorithm will also be applied to understand the relation between material properties and separation factors, for speeding up material screening. Simple 3-5 stage enrichment will also be demonstrated to validate scaling up.