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3rd Edition of Understanding Molecular Simulation
D. Frenkel and B. Smit, Understanding Molecular Simulations: from Algorithms to Applications, 3rd ed. (Academic Press, San Diego, 2023)A copy can be obtained from the Elsevier website https://shop.elsevier.com/books/understanding-molecular-simulation/frenkel/9780323902922, and with the promo code “CHEM30” one can get a 30% reduction.
Cover of Digital Discovery
M. V. Gil, K. M. Jablonka, S. García, C. Pevida, and B. Smit, Biomass to energy: A machine learning model for optimum gasification pathways Digital Discovery 2, 929 (2023) http://dx.doi.org/10.1039/D3DD00079F
Cover of ACS Central Science
An ecosystem for reticular chemistry generated using artificial intelligence.K. M. Jablonka, A. S. Rosen, A. S. Krishnapriyan, and B. Smit, An Ecosystem for Digital Reticular Chemistry ACS Cent Sci 9 (4), 563 (2023) http://dx.doi.org/10.1021/acscentsci.2c01177acscentsci.2c01177Download
Latest publications
Adsorption in Pyrene-Based Metal–Organic Frameworks
M. J. Pougin, N. P. Domingues, F. P. Uran, A. Ortega-Guerrero, C. P. Ireland, J. Espín, W. Lee Queen, and B. Smit, Adsorption in Pyrene-Based Metal–Organic Frameworks: The Role of Pore Structure and Topology ACS Appl. Mater. Interfaces (2024) doi: 10.1021/acsami.4c05527Abstact: Pore topology and chemistry play crucial roles in the adsorption characteristics of metal–organic frameworks (MOFs). (…)
A novel PEG-mediated approach to entrap hemoglobin (Hb) within ZIF-8 nanoparticles
C. Coll-Satue, M. Rubio-Huertas, A. Ducrot, E. Norkute, X. Liu, F. M. Ebrahim, B. Smit, P. W. Thulstrup, and L. Hosta-Rigau, A novel PEG-mediated approach to entrap hemoglobin (Hb) within ZIF-8 nanoparticles: Balancing crystalline structure, Hb content and functionality Biomater. Adv, 213953 (2024) DOI: 10.1016/j.bioadv.2024.213953Abstract: Hemoglobin (Hb)-based oxygen carriers are investigated as a potential alternative or (…)
Deep learning-based recommendation system for MOFs
X. Zhang, K. M. Jablonka, and B. Smit, Deep learning-based recommendation system for metal–organic frameworks (MOFs), Digit Discov 3 (7), 1410 (2024) DOI: 10.1039/D4DD00116HAbstract: This work presents a recommendation system for metal–organic frameworks (MOFs) inspired by online content platforms. By leveraging the unsupervised Doc2Vec model trained on document-structured intrinsic MOF characteristics, the model embeds MOFs into (…)