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机器学习辅助发现双金属氧化物,以实现高效的催化臭氧化

Chaohui Zhang¹, Shasha Li¹, Hanyue Zhang¹

¹Key Laboratory of Pollution Process and Environmental Criteria, Ministry of Education, Carbon Neutrality Interdisciplinary Science Centre, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.

Environmental science & technology

|July 28, 2025

概括

一种新型的催化剂,ZnCu2O4,是通过机器学习发现的,用于先进的废水处理. 这种催化剂显著改善了工业废水中的污染物降解和臭氧效率,提供了一个稳定的,非激进的途径.

科学领域:

环境化学环境化学
材料科学材料科学材料科学
催化剂是一种催化剂.

背景情况:

催化臭氧化对于工业废水处理至关重要.
异质催化剂是先进氧化过程中的关键组成部分.
为复杂的废水开发高效的催化剂仍然是一个挑战.

研究的目的:

发现和验证一种用于增强催化臭氧化的新型异质催化剂.
提高污染物的降解效率,如氧酸,化学氧气需求 (COD) 和总有机碳 (TOC).
阐明催化机制,并评估催化剂的稳定性,用于工业应用.

主要方法:

使用机器学习 (ML) 对1603个双金属氧化物的选.
通过密度函数理论 (DFT) 计算和实验研究验证主要候选物 (ZnCu2O4).
使用氧化酸降解和高盐度煤化废水 (hsCCW) 处理的催化性能评估.
机理学研究以确定反应途径和催化剂稳定性.

主要成果:

确定ZnCu2O4作为一种高效的催化剂.
氧化酸降解率显著提高 (1.30-61.22倍高于文献).
在hsCCW.中提高了COD (0.61-4.60倍) 和TOC (1.32-4.84倍) 的臭氧处理效率.
发现一种由单一氧 (1O2) 主导的非激进通路,可以抵抗环境干扰.
由于Cu-O-Zn配置,证明了催化剂的稳定性和活性场所暴露.

结论:

ZnCu2O4是通过催化臭氧化先进废水处理的开创性催化剂.
开发的研发框架为智能材料创新提供了可通用的方法.
催化剂的独特机制和稳定性支持其用于可扩展的环境应用的潜力.

关键词:

通过先进的氧化过程.双金属氧化物双金属氧化物催化臭氧化催化臭氧化机器学习是机器学习.不激进的路径.

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