通过进化计算实现高斯轨道扩张的人工智能驱动优化:对受限原子和分子的应用
Victor García1, Manuel Fernández1
1Departamento de Química-Física, Facultad de Ciencias, Campus Universitario Río San Pedro, Universidad de Cádiz, 11510, Puerto Real, Cádiz, Spain.
概括
人工智能,使用遗传算法和差异进化,为原子轨道产生准确的高斯扩张. 这种方法改进了各种分子中溶剂效应的模型.
科学领域:
- 计算化学是一种计算化学.
- 在量子力学中的人工智能.
背景情况:
- 对原子轨道的准确表示对于计算化学至关重要.
- 现有的生成高斯扩展的方法可能是计算密集的.
研究的目的:
- 开发和应用人工智能技术来生成原子轨道的高斯扩张.
- 创建一个有效的程序来计算这些扩展.
- 完善自相一致的反应场模型,用于溶剂效应.
主要方法:
- 利用遗传算法和差异进化,这两种人工智能技术.
- 开发了一个名为UCA-GSS-GA的程序,用于高斯扩张的高效计算.
- 应用生成的扩展来改进自我一致的反应场模型.
主要成果:
- 为自由和局限于球体的原子轨道生成精确的高斯膨胀 (φ-nG).
- 证明了该程序处理简单系统 (H,H2,CH4) 和复杂分子/溶剂的能力.
- 显著改进了溶剂效应的自我一致的反应场模型.
结论:
- 开发的AI方法提供了一种高效和准确的方法来生成高斯扩展.
- 该UCA-GSS-GA程序为计算化学提供了一个多功能工具,适用于广泛的系统.
- 通过精细的高斯轨道表示,改进了溶剂效应建模.
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