Design and Discovery of Multiple Anion Functional Materials—Synthesis, Structure, Computation and Machine Learning

This presentation will cover our recent work on the synthesis of new multiple anion materials, including the distinctive structures accessible from the ordering of distinct formally negatively charged species (<i>J</i><i>. Am. Chem. Soc.</i> 2017, 139, 44, 15568–15571; <i>J. Am. Chem. Soc.</i> 2020, 142, 2, 847–856).<br/>It will focus on new materials with low thermal conductivity (Science 373, 1017-1022, 2021) and structural families for lithium ion transport (Chem. Mater. 33, 2206-2217, 2021) and as sodium ion cathodes (J. Mater. Chem. A, 2020, <b>8</b>, 20553-20569). The role of machine learning (<i>Angewandte Chemie-International Edition.</i> <b>2021</b>, 60, 2–11) in supporting the search for new multiple anion systems will be discussed, using the example of stable interfaces to lithium in solid state batteries (<i>Nature Communications</i> <b>2021</b>, 12, 5561).