合理设计
生化工程
工程制图
计算机科学
工艺工程
人工智能
化学工程
数学
工程类
材料科学
纳米技术
作者
St Mardiana,Arxhel S. F. Nanda,I Made Arcana,Ismunandar Ismunandar,Adroit T. N. Fajar,Grandprix T. M. Kadja
标识
DOI:10.5614/j.eng.technol.sci.2025.57.4.4
摘要
Zeolites are widely applied in various fields owing to their outstanding properties. However, our understanding on the nature of zeolite synthesis is not completed yet due to its high dimensional parameters. Machine learning has the ability to unravel fundamental relationships between complex parameters and predict the possible outcomes; thus, it can potentially reveal the nature of zeolite synthesis. This mini review highlights the current use of machine learning to comprehend the black box issue in zeolite synthesis. Conventional syntheses of zeolite were also elaborated to showcase the gap between traditional methods and machine learning approaches in zeolite synthesis. The future prospects of machine learning applications in zeolite synthesis are also discussed. This mini-review may bring crucial insights on the zeolite synthesis process.
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