Cover of ACS Central Science
The perspective of Daniele and Leopold on the cover of ACS Central Science. D. Ongari, L. Talirz, and B. Smit, Too Many Materials and Too Many Applications: An Experimental Problem Waiting for a Computational Solution ACS Cent. Sci. (2020) http://dx.doi.org/10.1021/acscentsci.0c00988
Sauradeep wins the world finals of FameLab
Here is his winning presentation:
AiiDAlab
A. V. Yakutovich, K. Eimre, O. Schütt, L. Talirz, C. S. Adorf, C. W. Andersen, E. Ditler, D. Du, D. Passerone, B. Smit, N. Marzari, G. Pizzi, and C. A. Pignedoli, AiiDAlab – an ecosystem for developing, executing, and sharing scientific workflows Comput. Mater. Sci. 188, 110165 (2021) doi: 10.1016/j.commatsci.2020.110165 Abstract: Cloud platforms allow users (…)
Machine Learning: Understanding and Design of Materials
S. M. Moosavi, K. M. Jablonka, and B. Smit, The Role of Machine Learning in the Understanding and Design of Materials J Am Chem Soc (2020) Doi: 10.1021/jacs.0c09105 Abstract: Developing algorithmic approaches for the rational design and discovery of materials can enable us to systematically find novel materials, which can have huge technological and social (…)
Sauradeep wins Swiss Finals of FameLab
You can find an interview with Sauradeep here: https://actu.epfl.ch/news/sauradeep-majumdar-winner-of-famelab-switzerland-2/? See here his winning presentation for the Swiss edition of FameLab
Too Many Materials and Too Many Applications
D. Ongari, L. Talirz, and B. Smit, Too Many Materials and Too Many Applications: An Experimental Problem Waiting for a Computational Solution ACS Cent. Sci. (2020) http://dx.doi.org/10.1021/acscentsci.0c00988 Abstract: Finding the best material for a specific application is the ultimate goal of materials discovery. However, there is also the reverse problem: when experimental groups discover a (…)
Charge Separation and Charge Carrier Mobility in Photocatalytic MOFs
M. Fumanal, A. Ortega-Guerrero, K. M. Jablonka, B. Smit, and I. Tavernelli, Charge Separation and Charge Carrier Mobility in Photocatalytic Metal-Organic Frameworks Adv. Funct. Mater. (2020) http://dx.doi.org/10.1002/adfm.202003792 Abstract Metal‐organic frameworks (MOFs) are highly versatile materials owing to their vast structural and chemical tunability. These hybrid inorganic–organic crystalline materials offer an ideal platform to incorporate light‐harvesting (…)
Thermoelasticity of Flexible Organic Crystals
J. Maul, D. Ongari, S. M. Moosavi, B. Smit, and A. Erba, Thermoelasticity of Flexible Organic Crystals from Quasi-harmonic Lattice Dynamics: The Case of Copper(II) Acetylacetonate J Phys Chem Lett, 8543 (2020) doi: 10.1021/acs.jpclett.0c02762 Abstract: A computationally affordable approach, based on quasi-harmonic lattice dynamics, is presented for the quantum-mechanical calculation of thermoelastic moduli of flexible, (…)
Cover of Chem Rev
MOFs are made for big-data science: The neurons of artificial neural networks, representing the big-data approach to chemistry, become one with the framework of a metal-organic framework (figure by Alexander Tokarev) Ref: K. M. Jablonka, D. Ongari, S. M. Moosavi, and B. Smit, Big-Data Science in Porous Materials: Materials Genomics and Machine Learning Chem. Rev. (…)
From Isolated Porphyrin Ligands to Periodic Al-PMOF
A. Ortega-Guerrero, M. Fumanal, G. Capano, and B. Smit, From Isolated Porphyrin Ligands to Periodic Al-PMOF: A Comparative Study of the Optical Properties using DFT/TDDFT J Phys Chem C (2020) doi:10.1021/acs.jpcc.0c06885 Abstract: The use of photosensitizers as organic ligands in Metal-Organic Frameworks (MOFs) is a common practice to engineer their UV/Vis optical absorption. For instance, (…)