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RESEARCH PAPER · Engineering · 2025

Progress of Machine Learning in Molecular Crystal Design and Crystallization Development

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Progress of Machine Learning in Molecular Crystal Design and Crystallization DevelopmentOriginalA New Hybrid Virtual Screening Model for Predicting Solvate Formation Propensity in Pharmaceutical Crystallization2Development and applications of epitaxial heterostructures based on organic nanowires0Data-mechanism dual-driven modeling for enhanced prediction of lignin Hansen solubility parameters2Recent advances in the digital transformation of crystallization process development and operation: Synergy between model- and AI-driven strategies4Functional slow feature analysis based in-situ monitoring of crystallization process via near-infrared spectrum0Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments0A deep‐learning‐enhanced multi‐objective framework for crystallization kinetics determination via image analysis0Model-guided intensified crystallization for high-purity vitamin E intermediate: process regulation and impurity migration mechanism0Synergistic CoNi bimetallic MOF-74 for enhanced π-complexation separation of 1-hexene from hexane0In-situ monitoring of crystal size distribution in solution crystallization via stereoscopic image analysis0Computationally assisted and inherently safer solvent screening for solution crystallization with experimental validation0

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  1. A New Hybrid Virtual Screening Model for Predicting Solvate Formation Propensity in Pharmaceutical Crystallization

    Crystal Growth & Design · 2025-10-29

    Yuriy A. Abramov

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  2. Development and applications of epitaxial heterostructures based on organic nanowires

    Chemical Society Reviews · 2026-01-01

    J. Y. Lu, Y. J. Bao, T. Z. Feng, Q. Lv, Yi Shi, Xuedong Wang

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  3. Data-mechanism dual-driven modeling for enhanced prediction of lignin Hansen solubility parameters

    Chemical Engineering Science · 2026-01-07

    Huaze Sun, Zhenyuan Xiao, Danyang Cao, ZiTao YU, Yongguang Yu, Xiaojing Guo, Jiahua Zhu, Liwen Mu

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  4. Recent advances in the digital transformation of crystallization process development and operation: Synergy between model- and AI-driven strategies

    Particuology · 2026-01-23

    Yiming Ma, Xuming Yuan, Ashish Yewale, Brahim Benyahia

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  5. Functional slow feature analysis based in-situ monitoring of crystallization process via near-infrared spectrum

    Process Safety and Environmental Protection · 2026-04-03

    J. S. Liu, Shihao Song, Zhiheng Cui, Deshun Sun

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  6. Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

    Advanced Intelligent Discovery · 2026-04-27

    Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa

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  7. A deep‐learning‐enhanced multi‐objective framework for crystallization kinetics determination via image analysis

    AIChE Journal · 2026-07-19

    Tuo Yao, Zishuo Fu, Muyang Li, Zhenguo Gao, Junbo Gong

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  8. Model-guided intensified crystallization for high-purity vitamin E intermediate: process regulation and impurity migration mechanism

    Separation and Purification Technology · 2026-07-21

    Shengzhe Jia, zhuangzhuang yun, Guozhi Lv, Xiaoqi Liu, Yan Liu, Junbo Gong, Tingan Zhang

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  9. Synergistic CoNi bimetallic MOF-74 for enhanced π-complexation separation of 1-hexene from hexane

    Separation and Purification Technology · 2026-07-28

    Chuanqi Geng, Yushan Guo, Zhipeng Li, Wenxin Wang, Zhenyu Zhao, Qiuyan Ding, Hong Li, Xin Gao

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  10. In-situ monitoring of crystal size distribution in solution crystallization via stereoscopic image analysis

    Powder Technology · 2026-07-29

    Ji Fan, Junghui Chen

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  11. Computationally assisted and inherently safer solvent screening for solution crystallization with experimental validation

    Journal of the Taiwan Institute of Chemical Engineers · 2026-09-11

    Jiaxing Zhu, Tianshuo Zheng, Hao Ling, Liuguo Zhao, Bo Zhang, Ao Yang, Hao Zhang, Hongyuan Wei

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