集成的工作流程和接口用于数据驱动的半经验电子结构计算
Pavel Stishenko1, Adam McSloy2, Berk Onat2
1Cardiff Catalysis Institute, School of Chemistry, Cardiff University, Park Place, Cardiff CF10 3AT, United Kingdom.
The Journal of chemical physics
|July 3, 2024
概括
现代软件工程将电子结构代码转移到模块化,使灵活的数据驱动分析成为可能. 新的DFTB+接口通过整合机器学习和多尺度工作流来加速科学发现.
科学领域:
- 计算化学计算化学
- 材料科学 材料科学 材料科学
- 软件工程 软件工程 软件工程
背景情况:
- 传统的电子结构代码通常使用单体工作流.
- 软件模块化为计算任务提供了更大的灵活性.
- 将电子结构计算与数据驱动分析相结合,提供了机会.
研究的目的:
- 讨论创建电子结构代码和大数据工作流之间的模块化接口的方法.
- 探索这些接口所能实现的各种各样的用例.
- 为DFTB+包提供特定的接口实现.
主要方法:
- 为DFTB+套餐开发了两个不同的接口方法.
- 一种方法使用DFTB+作为向外部工作流提供数据的库.
- 另一种方法使用DFTB+的外部绑定来内部接收和处理数据.
- 建立了数据交换工作流程的一般框架.
主要成果:
- 展示了连接DFTB+与外部工作流程的模块化接口.
- 让DFTB+能够同时充当数据提供者和数据消费者.
- 促进了在DFTB+中嵌入基于机器学习的哈密尔顿理论.
- 实现了DFTB+深度集成到多尺度嵌入工作流中.
结论:
- 模块化接口提高了电子结构代码的灵活性和适用性.
- 这些接口通过启用新的软件和数据工作流来加速科学发现.
- 提出的框架支持集成先进的计算方法,如机器学习.
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