Advances in Photocatalytic Materials through SALSA

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8 Oct 2024

(1) Sean M. Stafford, Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing, MI, 48824, USA;

(2) Alexander Aduenko, Moscow Institute of Physics and Technology, Moscow, Russia;

(3) Marcus Djokic, Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing, MI, 48824, USA;

(4) Yu-Hsiu Lin, Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing, MI, 48824, USA;

(5) Jose L. Mendoza-Cortes, Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing, MI, 48824, USA (Email: [email protected]).

Abstract and Introduction

SALSA- (S)ubstitution, (A)pproximation, Evo(L)utionary (S)earch, and (A)B-Initio Calculations

SALSA Applied to Photocatalytic Water-splitting

Discussion

Methods

Conclusions, Data Availability Statement and References

Appendix: Supplementary Material

VI. CONCLUSIONS

We have introduced a general materials design process that can be used for many applications. The process only requires a dataset of known compounds with known properties and the ability to calculate some of the properties from first-principles for a small set of structures. We applied our new process to an unrealized artificial photosynthesis technology and were able to discover materials that are good candidates for photocatalytic water-splitting. This includes PbCuSeCl, a material with a novel structure, which we were able to discover because our process allows for an expansive search of structure space. It also includes Ti2O4Pb3Se3 which has band gap and interpolated redox potentials within the ideal range for photocatalytic water-splitting.

Furthermore, work is underway to improve several methods used in the SALSA process. We may expand and enhance further the substitution matrix. We are also working on a way to generalize the redox potential calculation method with larger datasets.

ACKNOWLEDGMENTS

SMS is supported by the Mendoza Lab start-up funds. JLMC acknowledges start-up funds from Michigan State University. This work was supported in part by computational resources and services provided by the Institute for CyberEnabled Research at Michigan State University.

Author Contributions. AA and JLMC started the project in 2012-2013. JLMC conceived the idea and executed the first iterations of the search algorithms. AA and JLMC wrote the first draft. AA and JLMC implemented and developed the first iteration of the algorithms. SMS, MD, YL continued and finished the project. SMS implemented the next generation of the algorithm. Conceptualization: AA, JLMC. Methodology: AA, SMS, MD, YL, JLMC. Software: AA, SMS, MD, YL, JLMC. Validation: AA, SMS, MD, YL, JLMC. Formal Analysis: SMS, MD, JLMC. Investigation: AA, SMS, MD, JLMC. Resources: JLMC. Writing—original draft preparation: AA, JLMC. Writing—review and editing: SMS, AA, MD, YL, JLMC. Visualization: SMS, MD, JLMC. Supervision: JLMC. Project administration: JLMC. Funding Acquisition: JLMC. All authors have read and agreed to the published version of the manuscript.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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