- L.M. Ghiringhelli, C. Baldauf, T. Bereau, S. Brockhauser, C. Carbogno, J. Chamanara, S. Cozzini, S. Curtarolo, C. Draxl, S. Dwaraknath, Á. Fekete, J. Kermode, C.T. Koch, M. Kühbach, A.N. Ladines, P. Lambrix, M.O. Lenz-Himmer, S. Levchenko, M. Oliveira, A. Michalchuk, R. Miller, B. Onat, P. Pavone, G. Pizzi, B. Regler, G.M. Rignanese, J. Schaarschmidt, M. Scheidgen, A. Schneidewind, T. Sheveleva, C. Su, D. Usvyat, O. Valsson, C. Wöll, and M. Scheffler
Shared Metadata for Data-Centric Materials Science
Scientific Data 10, 626 (2023). [DOI] - Mehrdad Jalali, A.D. Dinga Wonanke, Christof Wöll
MOFGalaxyNet: a social network analysis for predicting guest accessibility in metal–organic frameworks utilizing graph convolutional networks
Journal of Cheminformatics 15, 1 (2023). [DOI] - Markus Scheidgen, Lauri Himanen , Alvin Noe Ladines , David Sikter, Mohammad Nakhaee, Ádám Fekete ,Theodore Chang ,Amir Golparvar ,José A. Márquez, Sandor Brockhauser, Sebastian Brückner, Luca M. Ghiringhelli, Felix Dietrich, Daniel Lehmberg , Thea Denell, Andrea Albino, Hampus Näsström, Sherjeel Shabih, Florian Dobener, Markus Kühbach, Rubel Mozumder, Joseph F. Rudzinski , Nathan Daelman, José M. Pizarro, Martin Kuban, Cuauhtemoc Salazar, Pavel Ondračka, Hans-Joachim Bungartz and Claudia Draxl
NOMAD: A distributed web-based platform for
managing materials science research data
Journal of open source software 8, 4 (2023). [DOI] - Clara Patricia Marshall, Julia Schumann, Anette Trunschke
Achieving Digital Catalysis: Strategies for Data Acquisition, Storage and Use
Angew. Chem. Int. Ed 62, 18 (2023). [DOI] - C. Draxl, M. Kuban, S. Rigamonti, and M. Scheidgen
Challenges and perspectives for interoperability and reuse of heterogenous data collections
Section 4.1 in H. J. Kulik, et al.
Electronic Structure 4, 023004 (2022). [DOI]
Roadmap on Machine Learning in Electronic Structure - M. Kuban, S. Rigamonti, M. Scheidgen, and C. Draxl
Density-of-states similarity descriptor for unsupervised learning from materials data
Sci. Data 9, 646 (2022). [DOI] [arXiv] - M. Scheffler, M. Aeschlimann, M. Albrecht, T. Bereau, H.-J. Bungartz, C.Felser, M. Greiner, A. Groß, C. Koch, K. Kremer, W. E. Nagel, M. Scheidgen, C. Wöll, and C. Draxl
FAIR data enabling new horizons for materials research
Nature 604, 635 (2022). [DOI] [arXiv] - A. M. Teale, T. Helgaker, A. Savin, C. Adamo, B. Aradi, A. V. Arbuznikov, P. W. Ayers, E. J. Baerends, V. Barone, P. Calaminici, E. Cancès, E. A. Carter, P. K. Chattaraj, H. Chermette, I. Ciofini, T. D. Crawford, F. De Proft, J. F. Dobson, C. Draxl, T. Frauenheim, E. Fromager, P. Fuentealba, L. Gagliardi, G. Galli, J. Gao, P. Geerlings, N. Gidopoulos, P. M. W. Gill, P. Gori-Giorgi, A. Görling, T. Gould, S. Grimme, O. Gritsenko, H. J. A.Jensen, E. R. Johnson, R. O. Jones, M. Kaupp, A. M. Köster, L. Kronik, A. I. Krylov, S. Kvaal, A. Laestadius, M. Levy, M. Lewin, S. Liu, P.-F. Loos, N. T. Maitra, F. Neese, J. P. Perdew, K. Pernal, P. Pernot, P. Piecuch, E. Rebolini, L. Reining, P. Romaniello, A. Ruzsinszky, D. R. Salahub, M. Scheffler, P. Schwerdtfeger, V. N. Staroverov, J. Sun, E. Tellgren, D. J. Tozer, S. B. Trickey, C. A. Ullrich, A. Vela, G. Vignale, T. A. Wesolowski, and X. W. Yang
DFT Exchange: Sharing Perspectives on the Workhorse of Quantum Chemistry and Materials Science
Phys. Chem. Chem. Phys. , (2022). [DOI] [arXiv] - M. Kuban, Š. Gabaj, W. Aggoune, C. Vona, S. Rigamonti, and C. Draxl
Similarity of materials and data‑quality assessment by fingerprinting
MRS Bulletin Impact section
MRS Bulletin 47, 1 (2022). [DOI] [arXiv] - Y. Luo, S. Bag, O. Zaremba, A. Cierpka, J. Andreo, S. Wuttke, P. Friederich, and M. Tsotsalas
MOF Synthesis Prediction Enabled by Automatic Data Mining and Machine Learning
Angew. Chem. Int. Ed. 61, (2022). [DOI] - M. Jalali, M. Tsotsalas, and C. Wöll
MOFSocialNet: Exploiting Metal-Organic Framework Relationships via Social Network Analysis
Nanomaterials 12, 704 (2022). [DOI]
