Evaluating Material Design Principles for Calcium-Ion\nMobility in Intercalation Cathodes

Multivalent-ion batteries\noffer an alternative to Li-based technologies,\nwith the potential for greater sustainability, improved safety, and\nhigher energy density, primarily due to their rechargeable system\nfeaturing a passivating metal anode. Although a system based on the\nCa<sup>2+</sup>/Ca couple is particularly attractive given the low\nelectrochemical plating potential of Ca<sup>2+</sup>, the remaining\nchallenge for a viable rechargeable Ca battery is to identify Ca cathodes\nwith fast ion transport. In this work, a high-throughput computational\npipeline is adapted to (1) discover novel Ca cathodes in a largely\nunexplored space of “empty intercalation hosts” and\n(2) develop material design rules for Ca-ion mobility. One candidate\nfrom the screening, W<sub>2</sub>O<sub>3</sub>(PO<sub>4</sub>)<sub>2</sub>, is confirmed to have a low Nudged Elastic Band (NEB) barrier\nof 168 meV within a one-dimensional (1D) ion percolation topology.\nThis candidate is subsequently synthesized and electrochemically tested,\nachieving reversible Ca cycling with a capacity of 25 mA h/g. To further\naccelerate the screening for promising Ca intercalation electrodes,\nmachine learning (ML) Random Forest (RF) and Extreme Gradient Boosting\n(XGB) classification models are created with local environment descriptors\nbased on a large, structurally and chemically diverse dataset of minimum\nenergy pathways, spanning over 5,000 density functional theory (DFT)\nsite energy calculations. Accuracies of 92% are achieved, material\ndesign metrics are quantified, ML force-fields are leveraged in an\naccelerated iteration of the screening, and a total of 27 novel Ca\ncathode materials are highlighted for further investigation.