PySTH: A Python program for calculating and analyzing theoretical solar-to-hydrogen efficiency
Solar-to-hydrogen (STH) efficiency is a key metric for evaluating the economic feasibility of hydrogen production via solar-driven water splitting. However, accurately calculating theoretical STH efficiency remains challenging due to the complexity of the underlying integrals and the presence of mul...
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| Published in: | Computer physics communications Vol. 317; p. 109822 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier B.V
01.12.2025
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| Subjects: | |
| ISSN: | 0010-4655 |
| Online Access: | Get full text |
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| Summary: | Solar-to-hydrogen (STH) efficiency is a key metric for evaluating the economic feasibility of hydrogen production via solar-driven water splitting. However, accurately calculating theoretical STH efficiency remains challenging due to the complexity of the underlying integrals and the presence of multiple interdependent material parameters, which hampers computational efficiency and reproducibility. In this work, we introduce PySTH, a Python-based command-line program designed to enable rapid and reliable computation and intuitive visualization of theoretical STH efficiencies for two-dimensional photocatalysts under various sets of material property parameters. All required parameters are derived from first-principles calculations. The program supports four distinct photocatalytic systems: conventional photocatalysts, Janus materials, Z-scheme heterojunctions, and Janus Z-scheme systems. PySTH also generates high-resolution efficiency maps that reveal how the interplay among different material parameters affects STH efficiency, thereby offering valuable insights into synergistic optimization strategies. A series of benchmark examples demonstrate the accuracy, versatility, and practical utility of the program in theoretical photocatalysis research.
Program Title: PySTH
CPC Library link to program files:https://doi.org/10.17632/jxc5j8vtvb.1
Developer's repository link:https://github.com/Quanli2022/PySTH
Licensing provisions: MIT license
Programming language: Python3
Nature of problem: Theoretical solar-to-hydrogen (STH) efficiency is a widely adopted descriptor for assessing the performance of 2D photocatalysts in solar-driven water-splitting applications targeted at hydrogen production. However, accurate evaluation of theoretical STH efficiency remains challenging due to complex integral formulations, multiple input parameters, and the absence of standardized computational tools. Moreover, the combined influence of these parameters on STH efficiency is not yet fully understood.Solution method: PySTH enables users to compute theoretical STH efficiencies by selecting the photocatalyst type and providing key electronic property parameters (e.g., band-edge potentials and vacuum level difference). The program performs spectral integration using AM1.5G data and outputs both pH-dependent efficiency curves and STH efficiency maps to visualize the effects of synergistic parameter variations.
Additional comments including restrictions and unusual features: All efficiency calculations in PySTH are based on the AM1.5G solar spectrum. The software supports four classes of 2D materials: conventional photocatalysts, Janus materials, Z-scheme heterojunctions, and Janus Z-scheme systems. It employs a modular design and supports both numerical integration and parameter visualization, making it particularly suitable for high-throughput theoretical screening of photocatalysts.
•A novel tool for efficient calculation of theoretical solar-to-hydrogen efficiency.•PySTH supports conventional, Janus, Z-scheme, and Janus Z-scheme photocatalysts.•Uses DFT-derived parameters for reliable and reproducible efficiency predictions.•Generates high-resolution maps to visualize interdependencies on STH efficiency.•Compares with 100+ literature values, achieving a high accuracy (≤3% deviation). |
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| ISSN: | 0010-4655 |
| DOI: | 10.1016/j.cpc.2025.109822 |