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Martin Uhrin
Martin Uhrin
Université Grenoble Alpes
Bestätigte E-Mail-Adresse bei ucl.ac.uk
Titel
Zitiert von
Zitiert von
Jahr
Materials Cloud, a platform for open computational science
L Talirz, S Kumbhar, E Passaro, AV Yakutovich, V Granata, F Gargiulo, ...
Scientific data 7 (1), 299, 2020
2652020
Single-layered hittorf’s phosphorus: a wide-bandgap high mobility 2D material
G Schusteritsch, M Uhrin, CJ Pickard
Nano letters 16 (5), 2975-2980, 2016
2242016
AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance
SP Huber, S Zoupanos, M Uhrin, L Talirz, L Kahle, R Häuselmann, ...
Scientific data 7 (1), 300, 2020
2202020
Workflows in AiiDA: Engineering a high-throughput, event-based engine for robust and modular computational workflows
M Uhrin, SP Huber, J Yu, N Marzari, G Pizzi
Computational Materials Science 187, 110086, 2021
1062021
OPTIMADE, an API for exchanging materials data
CW Andersen, R Armiento, E Blokhin, GJ Conduit, S Dwaraknath, ...
Scientific data 8 (1), 217, 2021
812021
The MOLDY short-range molecular dynamics package
GJ Ackland, K DʼMellow, SL Daraszewicz, DJ Hepburn, M Uhrin, ...
Computer Physics Communications 182 (12), 2587-2604, 2011
512011
Toward a unified description of battery data
S Clark, FL Bleken, S Stier, E Flores, CW Andersen, M Marcinek, ...
Advanced Energy Materials 12 (17), 2102702, 2022
502022
Data Management Plans: the Importance of Data Management in the BIG‐MAP Project
IE Castelli, DJ Arismendi‐Arrieta, A Bhowmik, I Cekic‐Laskovic, S Clark, ...
Batteries & Supercaps 4 (12), 1803-1812, 2021
272021
Euclidean neural networks: e3nn
M Geiger, T Smidt, M Alby, BK Miller, W Boomsma, B Dice, K Lapchevskyi, ...
arXiv preprint arXiv:2207.09453, 2022
242022
Common workflows for computing material properties using different quantum engines
SP Huber, E Bosoni, M Bercx, J Bröder, A Degomme, V Dikan, K Eimre, ...
npj Computational Materials 7 (1), 136, 2021
202021
Through the eyes of a descriptor: Constructing complete, invertible descriptions of atomic environments
M Uhrin
Physical Review B 104 (14), 144110, 2021
192021
Euclidean neural networks: e3nn, 2020
M Geiger, T Smidt, M Alby, BK Miller, W Boomsma, B Dice, K Lapchevskyi, ...
URL https://doi. org/10.5281/zenodo 5292912, 0
12
Euclidean neural networks: e3nn, April 2022
M Geiger, T Smidt, M Alby, BK Miller, W Boomsma, B Dice, K Lapchevskyi, ...
URL https://doi. org/10.5281/zenodo 6459381 (4), 0
10
Materials cloud, a platform for open computational science. Sci Data 7: 299
L Talirz, S Kumbhar, E Passaro, AV Yakutovich, V Granata, F Gargiulo, ...
52020
The OPTIMADE Specification
C Andersen, R Armiento, E Blokhin, G Conduit, S Dwaraknath, M Evans, ...
42020
Sci. Data 7, 299 (2020)
L Talirz, S Kumbhar, E Passaro, AV Yakutovich, V Granata, F Gargiulo, ...
4
kiwiPy: Robust, high-volume, messaging for big-data and computational science workflows
M Uhrin, SP Huber
arXiv preprint arXiv:2005.07475, 2020
12020
Data Management Plan
M Uhrin, S Waychal, G Pizzi, N Marzari
Deliverable D3 1, 0
1
A High‐Throughput Computational Study Driven by the AiiDA Materials Informatics Framework and the PAULING FILE as Reference Database
M Uhrin, G Pizzi, N Mounet, N Marzari, P Villars
Materials Informatics: Methods, Tools and Applications, 149-170, 2019
2019
Understanding the Structure of Materials at the Intersection of Rationalisation, Prediction and Big Data
M Uhrin
UCL (University College London), 2015
2015
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