Seuraa
Francesca Tavazza
Francesca Tavazza
Vahvistettu sähköpostiosoite verkkotunnuksessa nist.gov
Nimike
Viittaukset
Viittaukset
Vuosi
Reproducibility in density functional theory calculations of solids
K Lejaeghere, G Bihlmayer, T Björkman, P Blaha, S Blügel, V Blum, ...
Science 351 (6280), aad3000, 2016
10822016
MJ vanSetten, V. Van Speybroeck, JM Wills, JR Yates, GX Zhang, S. Cottenier, Reproducibility in density functional theory calculations of solids
K Lejaeghere, G Bihlmayer, T Bjorkman, P Blaha, S Blugel, V Blum, ...
Science 351, 1415-U1481, 2016
500*2016
Considerations for choosing and using force fields and interatomic potentials in materials science and engineering
CA Becker, F Tavazza, ZT Trautt, RAB de Macedo
Current Opinion in Solid State and Materials Science 17 (6), 277-283, 2013
2682013
Recent advances and applications of deep learning methods in materials science
K Choudhary, B DeCost, C Chen, A Jain, F Tavazza, R Cohn, CW Park, ...
npj Computational Materials 8 (1), 59, 2022
2482022
High-throughput identification and characterization of two-dimensional materials using density functional theory
K Choudhary, I Kalish, R Beams, F Tavazza
Scientific reports 7 (1), 5179, 2017
2292017
Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning
D Jha, K Choudhary, F Tavazza, W Liao, A Choudhary, C Campbell, ...
Nature communications 10 (1), 5316, 2019
2282019
The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design
K Choudhary, KF Garrity, ACE Reid, B DeCost, AJ Biacchi, ...
npj computational materials 6 (1), 173, 2020
2262020
Characterization of Few-Layer 1T′ MoTe2 by Polarization-Resolved Second Harmonic Generation and Raman Scattering
R Beams, LG Cançado, S Krylyuk, I Kalish, B Kalanyan, AK Singh, ...
ACS nano 10 (10), 9626-9636, 2016
1622016
Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics
RK Vasudevan, K Choudhary, A Mehta, R Smith, G Kusne, F Tavazza, ...
MRS communications 9 (3), 821-838, 2019
1352019
Machine learning with force-field-inspired descriptors for materials: Fast screening and mapping energy landscape
K Choudhary, B DeCost, F Tavazza
Physical review materials 2 (8), 083801, 2018
1352018
MPInterfaces: A Materials Project based Python tool for high-throughput computational screening of interfacial systems
K Mathew, AK Singh, JJ Gabriel, K Choudhary, SB Sinnott, AV Davydov, ...
Computational Materials Science 122, 183-190, 2016
1292016
Elastic properties of bulk and low-dimensional materials using van der Waals density functional
K Choudhary, G Cheon, E Reed, F Tavazza
Physical Review B 98 (1), 014107, 2018
1262018
Accelerated discovery of efficient solar cell materials using quantum and machine-learning methods
K Choudhary, M Bercx, J Jiang, R Pachter, D Lamoen, F Tavazza
Chemistry of materials 31 (15), 5900-5908, 2019
1072019
Computational screening of high-performance optoelectronic materials using OptB88vdW and TB-mBJ formalisms
K Choudhary, Q Zhang, ACE Reid, S Chowdhury, N Van Nguyen, Z Trautt, ...
Scientific data 5 (1), 1-12, 2018
992018
New epitaxially stabilized CoSi phase with the CsCl structure
H Von Kaenel, C Schwarz, S Goncalves-Conto, E Müller, L Miglio, ...
Physical review letters 74 (7), 1163, 1995
971995
Convergence and machine learning predictions of Monkhorst-Pack k-points and plane-wave cut-off in high-throughput DFT calculations
K Choudhary, F Tavazza
Computational materials science 161, 300-308, 2019
932019
The structural phases and vibrational properties of Mo1− xWxTe2 alloys
SM Oliver, R Beams, S Krylyuk, I Kalish, AK Singh, A Bruma, F Tavazza, ...
2D Materials 4 (4), 045008, 2017
822017
Electronically Induced Atom Motion in Engineered CoCun Nanostructures
JA Stroscio, F Tavazza, JN Crain, RJ Celotta, AM Chaka
Science 313 (5789), 948-951, 2006
802006
Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data
V Gupta, K Choudhary, F Tavazza, C Campbell, W Liao, A Choudhary, ...
Nature communications 12 (1), 6595, 2021
792021
High-throughput density functional perturbation theory and machine learning predictions of infrared, piezoelectric, and dielectric responses
K Choudhary, KF Garrity, V Sharma, AJ Biacchi, AR Hight Walker, ...
npj computational materials 6 (1), 64, 2020
702020
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Artikkelit 1–20