|Comparing molecules and solids across structural and alchemical space|
S De, AP Bartók, G Csányi, M Ceriotti
Physical Chemistry Chemical Physics 18 (20), 13754-13769, 2016
|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
|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
|Promoting transparency and reproducibility in enhanced molecular simulations|
M Bonomi, G Bussi, C Camilloni, GA Tribello, P Banáš, A Barducci, ...
Nature methods 16 (8), 670-673, 2019
|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
|Chemical shifts in molecular solids by machine learning|
FM Paruzzo, A Hofstetter, F Musil, S De, M Ceriotti, L Emsley
Nature communications 9 (1), 1-10, 2018
|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
|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 83 (8), 081403, 2011
|Trap generation in IL and HK layers during BTI/TDDB stress in scaled HKMG N and P MOSFETs|
S Mukhopadhyay, K Joshi, V Chaudhary, N Goel, S De, RK Pandey, ...
2014 IEEE International Reliability Physics Symposium, GD. 3.1-GD. 3.11, 2014
|Mapping and classifying molecules from a high-throughput structural database|
D Sandip, M Felix, I Teresa, B Carsten, C Michele
Journal of Cheminformatics 9, 6, 2017
|A comprehensive DC/AC model for ultra-fast NBTI in deep EOT scaled HKMG p-MOSFETs|
N Goel, S Mukhopadhyay, N Nanaware, S De, RK Pandey, K Murali, ...
2014 IEEE International Reliability Physics Symposium, 6A. 4.1-6A. 4.12, 2014
|Microhydration of ion: A density functional theory study on clusters |
SM Ali, S De, DK Maity
The Journal of chemical physics 127 (4), 044303, 2007
|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
|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
|Understanding process impact of hole traps and NBTI in HKMG p-MOSFETs using measurements and atomistic simulations|
S Mahapatra, S De, K Joshi, S Mukhopadhyay, RK Pandey, K Murali
IEEE electron device letters 34 (8), 963-965, 2013
|Relation between fat intake and mortality: an ecological analysis in Belgium.|
L Staessen, D De Bacquer, S De Henauw, G De Backer, C Van Peteghem
European journal of cancer prevention: the official journal of the European …, 1997
|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
|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), 124302, 2011
|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, 2020
|Characterization and Optimization of Charge Trapping in High-k Dielectrics|
E Cartier, T Ando, M Hopstaken, V Narayanan, R Krishnan, JF Shepard Jr, ...