Matter devoted one of its first previews to highlight our recently published article providing an interactive machine learning approach to predict the mechanical stability of metal-organic frameworks. The preview, written by prof. Randall Q. Snurr of Northwestern University, not only focuses on the article's contribution to the development of mechanically stable MOFs, but also highlights the highly collaborative and multidisciplinary effort leading to the work:
"First, the 11 authors come from six different institutions and three countries. Rather than viewing each other as “competitors,” the authors have come together to solve an important problem, each research group bringing different expertise to the project. Second, the project both uses and creates open-source computational tools, including a database of MOFs, molecular modeling software, the ANN, and the web-based interactive data visualizer. Such sharing of codes, databases, and other tools can drastically speed up research and has other benefits as well, such as the potential for improved reproducibility of results. Finally, machine learning and other methods from data science—while perhaps overhyped at the moment—truly can lead to new ways of doing research. The results and insights developed in the work of Moghadam et al. were only possible because of the large amount of data generated by molecular modeling. It is possible that we are at the beginning of a new era of scientific research due to this shift toward team research, open-source tools, and data science."
Technical info
These results were published in the inaugural edition of the Cell Press journal Matter:
Structure-Mechanical Stability Relations of Metal-Organic Frameworks via Machine Learning
Peyman Z. Moghadam, Sven M. J. Rogge, Aurelia Li, Chun-Man Chow, Jelle Wieme, Noushin Moharrami, Marta Aragones-Anglada, Gareth Conduit, Diego A. Gomez-Gualdron, Veronique Van Speybroeck, and David Fairen-Jimenez
Matter, 1(1): 219-234, 2019. http://doi.org/10.1016/j.matt.2019.03.002
Dr. ir. Sven M. J. Rogge, prof. dr. ir. Veronique Van Speybroeck
Center for Molecular Modeling Technologiepark 46, 9052 Zwijnaarde
T +32 (0)9 264 65 75 | M +32 (0)478 82 34 19