Band alignment study at the $SrTaO_2N/H_2O$ interface varying lattice constants and surface termination from first-principles calculations
R. C. Bastidas Brice\~no, V. I. Fernandez, and R. E. Alonso

TL;DR
This study uses first-principles DFT calculations to analyze the band alignment at the SrTaO2N/water interface, considering surface termination and lattice mismatch, to identify suitable configurations for photoelectrochemical water splitting.
Contribution
It provides a detailed first-principles analysis of band alignment at SrTaO2N/water interfaces, considering surface termination and lattice mismatch effects, which was not previously comprehensively studied.
Findings
SrTaO2N (001) is suitable for PEC applications within certain lattice strain ranges.
SrTaO2N (110) shows wider lattice compatibility for PEC devices.
Band alignment is sensitive to surface termination and lattice constants.
Abstract
In the search for new renewable energy to replace fossil fuels, Hydrogen is one of the most promising candidates for clean energy production. But cheap Hydrogen separation and storage is still a big challenge. Photoelectrochemical devices look promising for the decomposition of the water molecule into . Every day new materials and combinations are discovered or invented to improve the efficiency of the complex total process. A necessary condition for the photoelectrochemical process to work without a bias voltage is that the minimum of the semiconductor conduction band (CBM) must be more positive than the reduction potential to , whereas the highest value of the semiconductor valence band (VBM) must be more negative than the oxidation potential of to . Thus, band alignment studies in interfaces of semiconductors with water become of vital importance.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsElectronic and Structural Properties of Oxides · Machine Learning in Materials Science · Advanced Photocatalysis Techniques
