A Data Driven Approach to Enhancing Specific Capacity in n-Type OMEICs for Energy Storage

Organic mixed ionic-electronic conductor materials (OMEICS) are attractive candidates for the electrodes of electrochemical energy storage devices because the materials are earth abundant, easy to process and recycle, compatible with aqueous electrolytes [1], and electronically tuneable [2]. However, batteries based on these materials currently suffer from low energy densities compared to conventional LIB chemistries so working to improve specific capacity is a critical challenge [3].
Structures that are easier to oxidise or reduce to higher charge states can lead to higher specific capacity and are an important target for future chemical design. Starting from a library of n-type materials extracted from literature, this work sets out to elucidate molecular design rules for high-capacity materials with a narrow operational voltage range that also offer compatibility with aqueous electrolytes. We first demonstrate our approach using density functional theory to calculate theoretical redox potentials for different levels of charging and the corresponding theoretical specific capacities for a set of small oligomers. We then develop a workflow that allows the chemical space to be expanded in order to search for structural characteristics associated with high specific capacity. We will present a data driven, high through-put approach utilising semi-empirical methods to reduce computational intensity. We have applied our workflow to screen the redox potentials of ~200k organic semiconductor-like structures from the Cambridge Structural Database. Using machine learning models for analysis, with an emphasise on model interpretability, we aim to gain physical insight into structural motifs associated with high capacity. This approach will enable more targeted molecular design to achieve the higher energy densities required for effective device level operation.

[1]Liang, Y., Yao, Y. Designing modern aqueous batteries. Nat Rev Mater 8, 109–122 (2023). https://doi.org/10.1038/s41578-022-00511-3
[2] Philippe Poizot, Joël Gaubicher, Stéven Renault, Lionel Dubois, Yanliang Liang, and Yan Yao. Chemical Reviews 2020 120 (14), 6490-6557. DOI: 10.1021/acs.chemrev.9b00482
[3] Nicolas Goujon, Nerea Casado, Nagaraj Patil, Rebeca Marcilla, David Mecerreyes, Organic batteries based on just redox polymers, Progress in Polymer Science, Volume 122, 2021, 101449, ISSN 0079-6700, https://doi.org/10.1016/j.progpolymsci.2021.101449.