Articles with public access mandates - Sandip DeLearn more
Not available anywhere: 1
Density functional investigations on structural and electronic properties of anionic and neutral sodium clusters NaN (N= 40–147): comparison with the experimental photoelectron …
SM Ghazi, S De, DG Kanhere, S Goedecker
Journal of Physics: Condensed Matter 23 (40), 405303, 2011
Mandates: Swiss National Science Foundation
Available somewhere: 19
Machine learning unifies the modeling of materials and molecules
AP Bartók, S De, C Poelking, N Bernstein, JR Kermode, G Csányi, ...
Science advances 3 (12), e1701816, 2017
Mandates: Swiss National Science Foundation, US Department of Defense, UK Engineering …
Chemical shifts in molecular solids by machine learning
FM Paruzzo, A Hofstetter, F Musil, S De, M Ceriotti, L Emsley
Nature communications 9 (1), 4501, 2018
Mandates: Swiss National Science Foundation, European Commission
Machine learning for the structure–energy–property landscapes of molecular crystals
F Musil, S De, J Yang, JE Campbell, GM Day, M Ceriotti
Chemical science 9 (5), 1289-1300, 2018
Mandates: Swiss National Science Foundation, US National Institutes of Health …
Energy landscape of fullerene materials: a comparison of boron to boron nitride and carbon
S De, A Willand, M Amsler, P Pochet, L Genovese, S Goedecker
Physical review letters 106 (22), 225502, 2011
Mandates: Swiss National Science Foundation
Large-scale computational screening of molecular organic semiconductors using crystal structure prediction
J Yang, S De, JE Campbell, S Li, M Ceriotti, GM Day
Chemistry of Materials 30 (13), 4361-4371, 2018
Mandates: Swiss National Science Foundation, Australian Research Council, European …
Growth and Structural Properties of MgN (N = 10–56) Clusters: Density Functional Theory Study
I Heidari, S De, SM Ghazi, S Goedecker, DG Kanhere
The Journal of Physical Chemistry A 115 (44), 12307-12314, 2011
Mandates: Swiss National Science Foundation
An assessment of the structural resolution of various fingerprints commonly used in machine learning
B Parsaeifard, DS De, AS Christensen, FA Faber, E Kocer, S De, J Behler, ...
Machine Learning: Science and Technology 2 (1), 015018, 2021
Mandates: Swiss National Science Foundation, German Research Foundation
Machine learning-guided approach for studying solvation environments
Y Basdogan, MC Groenenboom, E Henderson, S De, SB Rempe, ...
Journal of chemical theory and computation 16 (1), 633-642, 2019
Mandates: US National Science Foundation, US Department of Energy
Low-energy boron fullerenes: Role of disorder and potential synthesis pathways
P Pochet, L Genovese, S De, S Goedecker, D Caliste, SA Ghasemi, K Bao, ...
Physical Review B—Condensed Matter and Materials Physics 83 (8), 081403, 2011
Mandates: Swiss National Science Foundation
Learning design rules for selective oxidation catalysts from high-throughput experimentation and artificial intelligence
L Foppa, C Sutton, LM Ghiringhelli, S De, P Löser, SA Schunk, ...
ACS catalysis 12 (4), 2223-2232, 2022
Mandates: European Commission
Relation between the dynamics of glassy clusters and characteristic features of their energy landscape
S De, B Schaefer, A Sadeghi, M Sicher, DG Kanhere, S Goedecker
Physical Review Letters 112 (8), 083401, 2014
Mandates: Swiss National Science Foundation
Modeling high-entropy transition metal alloys with alchemical compression
N Lopanitsyna, G Fraux, MA Springer, S De, M Ceriotti
Physical Review Materials 7 (4), 045802, 2023
Mandates: Swiss National Science Foundation
The effect of ionization on the global minima of small and medium sized silicon and magnesium clusters
S De, SA Ghasemi, A Willand, L Genovese, D Kanhere, S Goedecker
The Journal of chemical physics 134 (12), 2011
Mandates: Swiss National Science Foundation
Accurate energy barriers for catalytic reaction pathways: an automatic training protocol for machine learning force fields
LL Schaaf, E Fako, S De, A Schäfer, G Csányi
npj Computational Materials 9 (1), 180, 2023
Mandates: UK Engineering and Physical Sciences Research Council
Quantification and Tuning of Surface Oxygen Vacancies for the Hydrogenation of CO2 on Indium Oxide Catalysts
R Baumgarten, R Naumann d'Alnoncourt, S Lohr, E Gioria, E Frei, E Fako, ...
Chemie Ingenieur Technik 94 (11), 1765-1775, 2022
Mandates: German Research Foundation
Surface segregation in high-entropy alloys from alchemical machine learning
A Mazitov, MA Springer, N Lopanitsyna, G Fraux, S De, M Ceriotti
Journal of Physics: Materials 7 (2), 025007, 2024
Mandates: Swiss National Science Foundation
Data‐driven Design of Enhanced In‐based Catalyst for CO2 to Methanol Reaction
M Khatamirad, E Fako, S De, M Müller, C Boscagli, R Baumgarten, ...
ChemCatChem 15 (16), e202300570, 2023
Mandates: German Research Foundation
Chemical machine learning with kernels: The impact of loss functions
QV Nguyen, S De, J Lin, V Cevher
International Journal Of Quantum Chemistry 119 (9), e25872, 2019
Mandates: Swiss National Science Foundation, European Commission
Chemical machine learning with kernels: The key impact of loss functions
VQ Nguyen, S De, J Lin, V Cevher
Mandates: Swiss National Science Foundation
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