S. Wuttke

Artificial Intelligence Paradigms for Next-Generation Metal–Organic Framework Research

A. Ozcan, F.-X. Coudert, S.M.J. Rogge, G. Heydenrych, D. Fan, A. P. Sarikas, S. Keskin, G. Maurin, G. E. Froudakis, S. Wuttke, I. Erucar
JACS (Journal of the American Chemical Society)
147, 27, 23367–23380
2025
A1

Abstract 

After the development of the famous “Transformer” network architecture and the meteoric rise of artificial intelligence (AI)-powered chatbots, large language models (LLMs) have become an indispensable part of our daily activities. In this rapidly evolving era, “all we need is attention” as Google’s famous transformer paper’s title [Vaswani et al., Adv. Neural Inf. Process. Syst. 2017, 30] implies: We need to focus on and give “attention” to what we have at hand, then consider what we can do further. What can LLMs offer for immediate short-term adaptation? Currently, the most common applications in metal–organic framework (MOF) research include automating literature reviews and data extraction to accelerate the material discovery process. In this perspective, we discuss the latest developments in machine-learning and deep-learning research on MOF materials and reflect on how their utilization has evolved within the LLM domain from this standpoint. We finally explore future benefits to accelerate and automate materials development research.

Open Access version available at UGent repository
Gold Open Access

How Reproducible are Surface Areas Calculated from the BET Equation?

J.W.M. Osterrieth, J. Rampersad, D. Madden, N. Rampal, L. Skoric, B. Connolly, M.D. Allendorf, V. Stavila, J.L Snider, R. Ameloot, J. Marreiros, C. Ania, D. Azevedo, E. Vilarrasa-Garcia, B.F. Santos, X.-H. Bu, Z. Chang, H. Bunzen, N.R. Champness, S.L. Griffin, B. Cheng, R.-B. Lin, B. Coasne, S. Cohen, J.C. Moreton, Y.J. Colón, L. Chen, R. Clowes, F.-X. Coudert, Y. Cui, B. Hou, D.M. D'Alessandro, P.W. Doheny, M. Dincă, C. Sun, C. Doonan, M.T. Huxley, J.D. Evans, P. Falcaro, R. Ricco, O. Farha, K.B. Idrees, T. Islamoglu, P. Feng, H. Yang, R.S. Forgan, D. Bara, S. Furukawa, E. Sanchez, J. Gascon, S. Telalović, S.K. Ghosh, S. Mukherjee, M.R. Hill, M.M. Sadiq, P. Horcajada, P. Salcedo-Abraira, K. Kaneko, R. Kukobat, J. Kenvin, S. Keskin, S. Kitagawa, K.-i. Otake, R.P. Lively, S.J.A. DeWitt, P.L. Llewellyn, B.V. Lotsch, S.T. Emmerling, A.M. Pütz, C. Martí-Gastaldo, N.M. Padial, J. García-Martínez, N. Linares, D. Maspoch, J.A. Suárez del Pino, P.Z. Moghadam, R. Oktavian, R.E. Morris, P.S. Wheatley, J. Navarro, C. Petit, D. Danaci, M.J. Rosseinsky, A.P. Katsoulidis, M. Schroeder, X. Han, S. Yang, C. Serre, G. Mouchaham, D.S. Sholl, R. Thyagarajan, D. Siderius, R.Q. Snurr, R.B. Goncalves, S. Telfer, S.J. Lee, V.P. Ting, J.L. Rowlandson, T. Uemura, T. Iiyuka, M.A. van der Veen, D. Rega, V. Van Speybroeck, S.M.J. Rogge, A. Lamaire, K.S. Walton, L.W. Bingel, S. Wuttke, J. Andreo, O. Yaghi, B. Zhang, C.T. Yavuz, T.S. Nguyen, F. Zamora, C. Montoro, H. Zhou, A. Kirchon, D. Fairen-Jimenez
Advanced Materials
34, 27, 2201502
2022
A1

Abstract 

Porosity and surface area analysis play a prominent role in modern materials science. At the heart of this sits the Brunauer–Emmett–Teller (BET) theory, which has been a remarkably successful contribution to the field of materials science. The BET method was developed in the 1930s for open surfaces but is now the most widely used metric for the estimation of surface areas of micro- and mesoporous materials. Despite its widespread use, the calculation of BET surface areas causes a spread in reported areas, resulting in reproducibility problems in both academia and industry. To prove this, for this analysis, 18 already-measured raw adsorption isotherms were provided to sixty-one labs, who were asked to calculate the corresponding BET areas. This round-robin exercise resulted in a wide range of values. Here, the reproducibility of BET area determination from identical isotherms is demonstrated to be a largely ignored issue, raising critical concerns over the reliability of reported BET areas. To solve this major issue, a new computational approach to accurately and systematically determine the BET area of nanoporous materials is developed. The software, called “BET surface identification” (BETSI), expands on the well-known Rouquerol criteria and makes an unambiguous BET area assignment possible.

Gold Open Access
Subscribe to RSS - S. Wuttke