Sequence determinants of protein phase separation and recognition by protein phase-separated condensates through molecular dynamics and active learning

Arya Changiarath, Aayush Arya, Vasileios A. Xenidis, Jan Padeken and Lukas S. Stelzl

Faraday Discuss., 2025, 256, 235
DOI: 10.1039/D4FD00099D

Large property models: a new generative machine-learning formulation for molecules

Tianfan Jin, Veerupaksh Singla, Hsuan-Hao Hsu and Brett M. Savoie

Faraday Discuss., 2025, 256, 104
DOI: 10.1039/D4FD00113C

Integrating model-based design of experiments and computer-aided solvent design

Lingfeng Gui, Yijun Yu, Titilola O. Oliyide, Eirini Siougkrou, Alan Armstrong, Amparo Galindo, Fareed Bhasha Sayyed, Stanley P. Kolis and Claire S. Adjiman

Computers & Chemical Engineering, 2023, 177, 108345
DOI: 10.1016/j.compchemeng.2023.108345

Nano-Cu Derived from a Copper Nitride Precatalyst for Reductive Coupling of Nitroaromatics to Azo Compounds

Xianting Du, Wanchun Duan, Yanan Gao, Tong Wang, Tairan Li, Yunxiang Lin, Zhi-peng Yu and Kun Xu

Inorg. Chem., 2024, 63, 4328
DOI: 10.1021/acs.inorgchem.3c04552

Predicting success in Cu-catalyzed C–N coupling reactions using data science

Mohammad H. Samha, Lucas J. Karas, David B. Vogt, Emmanuel C. Odogwu, Jennifer Elward, Jennifer M. Crawford, Janelle E. Steves and Matthew S. Sigman

Sci. Adv., 2024, 10
DOI: 10.1126/sciadv.adn3478

Amorphous RuCoP Ultrafine Nanoparticles Supported on Carbon as Efficient Catalysts for Hydrogenation of Adipic Acid to 1,6-Hexanediol

Wei Gong, Xuyun Wang, Shan Ji and Hui Wang

Materials, 2022, 15, 8084
DOI: 10.3390/ma15228084

Chemical space of the singlet C4H8O2 species. A systematic theoretical analysis on their structural and thermochemical properties

Zsófia Borbála Rózsa, Anita Rágyanszki, Béla Viskolcz and Milán Szőri

Computational and Theoretical Chemistry, 2023, 1225, 114162
DOI: 10.1016/j.comptc.2023.114162