PySTH: A Python program for calculating and analyzing theoretical solar-to-hydrogen efficiency

IF 3.4 2区物理与天体物理 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer Physics Communications Pub Date : 2025-08-28 DOI:10.1016/j.cpc.2025.109822

Quan Li , Maoxiang Tao , Yuxian Liu , Hao Huang , Qian Li , Xiaojun Zhu

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引用次数: 0

Abstract

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 summary

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.

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用于计算和分析理论太阳能制氢效率的Python程序

太阳能制氢（STH）效率是评估太阳能驱动的水分解制氢经济可行性的关键指标。然而，由于潜在积分的复杂性和多个相互依赖的材料参数的存在，精确计算理论STH效率仍然具有挑战性，这阻碍了计算效率和再现性。在这项工作中，我们介绍了PySTH，一个基于python的命令行程序，旨在实现快速可靠的计算和直观的可视化二维光催化剂在不同材料性质参数下的理论STH效率。所有必需的参数都是由第一性原理计算得出的。该项目支持四种不同的光催化系统：传统光催化剂、Janus材料、Z-scheme异质结和Janus Z-scheme系统。PySTH还生成高分辨率效率图，揭示不同材料参数之间的相互作用如何影响STH效率，从而为协同优化策略提供有价值的见解。一系列的基准例子证明了该程序在理论光催化研究中的准确性、通用性和实用性。项目摘要项目标题：PySTHCPC库链接到程序文件：https://doi.org/10.17632/jxc5j8vtvb.1Developer's存储库链接：https://github.com/Quanli2022/PySTHLicensing条款：MIT许可证编程语言：python3问题的性质：理论太阳能制氢（STH）效率是一个广泛采用的描述符，用于评估2D光催化剂在太阳能驱动的水分解应用中的性能，目标是制氢。然而，由于复杂的积分公式、多个输入参数以及缺乏标准化的计算工具，对理论STH效率的准确评估仍然具有挑战性。此外，这些参数对STH效率的综合影响尚不完全清楚。解决方法：PySTH允许用户通过选择光催化剂类型和提供关键电子特性参数（例如带边电位和真空度差）来计算理论STH效率。该程序使用AM1.5G数据进行光谱积分，并输出ph相关的效率曲线和STH效率图，以可视化协同参数变化的影响。附加说明，包括限制和不寻常的功能：PySTH的所有效率计算都是基于AM1.5G太阳光谱。该软件支持四类二维材料：传统光催化剂，Janus材料，Z-scheme异质结和Janus Z-scheme系统。它采用模块化设计，支持数值积分和参数可视化，使其特别适合于光催化剂的高通量理论筛选。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computer Physics Communications 物理-计算机：跨学科应用

CiteScore

12.10

自引率

3.20%

发文量

287

审稿时长

5.3 months

期刊介绍： The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper. Computer Programs in Physics (CPiP) These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged. Computational Physics Papers (CP) These are research papers in, but are not limited to, the following themes across computational physics and related disciplines. mathematical and numerical methods and algorithms; computational models including those associated with the design, control and analysis of experiments; and algebraic computation. Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.