化工学报 ›› 2021, Vol. 72 ›› Issue (1): 27-41.doi: 10.11949/0438-1157.20201037
SHI Xiangcheng1,2,3(),ZHAO Zhijian1,2(
),GONG Jinlong1,2,3
摘要:
对催化体系进行全局结构优化,搜寻基态结构对预测催化剂结构、分析反应物的吸附特性、研究多相催化反应机理、构建实际反应路径等方面至关重要。遗传算法通过交叉、变异和选择等操作,模拟了自然淘汰进化过程,来搜索势能面上的基态结构。作为一种无偏优化算法,遗传算法的优化过程不依赖于输入结构,具有很强的全局搜索能力。对遗传算法在催化体系的全局结构优化问题中的应用进行了综述,介绍了遗传算法在实空间上进行全局结构优化的基本程序框架以及近年来结合并行计算、机器学习等技术发展的改进框架,并讨论了它们在团簇优化、负载型催化剂的结构优化问题上的相关应用,为遗传算法的进一步改进以及更广泛的应用提供理论指导。
中图分类号:
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