Strain-induced metal–insulator phase coexistence in perovskite manganites KH Ahn, T Lookman, AR Bishop Nature 428 (6981), 401-404, 2004 | 677 | 2004 |
Accelerated search for materials with targeted properties by adaptive design D Xue, PV Balachandran, J Hogden, J Theiler, D Xue, T Lookman Nature communications 7 (1), 1-9, 2016 | 578 | 2016 |
Machine learning bandgaps of double perovskites G Pilania, A Mannodi-Kanakkithodi, BP Uberuaga, R Ramprasad, ... Scientific reports 6 (1), 19375, 2016 | 379 | 2016 |
Machine learning assisted design of high entropy alloys with desired property C Wen, Y Zhang, C Wang, D Xue, Y Bai, S Antonov, L Dai, T Lookman, ... Acta Materialia 170, 109-117, 2019 | 361 | 2019 |
Efficient computation of the structural phase behavior of block copolymers G Tzeremes, KØ Rasmussen, T Lookman, A Saxena Physical Review E 65 (4), 041806, 2002 | 313 | 2002 |
Machine learning strategy for accelerated design of polymer dielectrics A Mannodi-Kanakkithodi, G Pilania, TD Huan, T Lookman, R Ramprasad Scientific reports 6 (1), 1-10, 2016 | 303 | 2016 |
Chaotic time series analyses of epileptic seizures GW Frank, T Lookman, MAH Nerenberg, C Essex, J Lemieux, W Blume Physica D: Nonlinear Phenomena 46 (3), 427-438, 1990 | 266 | 1990 |
Active learning in materials science with emphasis on adaptive sampling using uncertainties for targeted design T Lookman, PV Balachandran, D Xue, R Yuan npj Computational Materials 5 (1), 21, 2019 | 251 | 2019 |
Accelerated Discovery of Large Electrostrains in BaTiO3‐Based Piezoelectrics Using Active Learning R Yuan, Z Liu, PV Balachandran, D Xue, Y Zhou, X Ding, J Sun, D Xue, ... Advanced materials 30 (7), 1702884, 2018 | 246 | 2018 |
Multi-fidelity machine learning models for accurate bandgap predictions of solids G Pilania, JE Gubernatis, T Lookman Computational Materials Science 129, 156-163, 2017 | 239 | 2017 |
Surface phase transitions in polymer systems K De'Bell, T Lookman Reviews of modern physics 65 (1), 87, 1993 | 234 | 1993 |
Adaptive strategies for materials design using uncertainties PV Balachandran, D Xue, J Theiler, J Hogden, T Lookman Scientific reports 6 (1), 1-9, 2016 | 199 | 2016 |
Experimental search for high-temperature ferroelectric perovskites guided by two-step machine learning PV Balachandran, B Kowalski, A Sehirlioglu, T Lookman Nature communications 9 (1), 1668, 2018 | 193 | 2018 |
Ferroelastic dynamics and strain compatibility T Lookman, SR Shenoy, KØ Rasmussen, A Saxena, AR Bishop Physical Review B 67 (2), 024114, 2003 | 190 | 2003 |
Martensitic textures: Multiscale consequences of elastic compatibility SR Shenoy, T Lookman, A Saxena, AR Bishop Physical Review B 60 (18), R12537, 1999 | 184 | 1999 |
The climate attractor over short timescales C Essex, T Lookman, MAH Nerenberg Nature 326 (6108), 64-66, 1987 | 165 | 1987 |
Onset of irreversibility and chaos in amorphous solids under periodic shear I Regev, T Lookman, C Reichhardt Physical Review E 88 (6), 062401, 2013 | 163 | 2013 |
An informatics approach to transformation temperatures of NiTi-based shape memory alloys D Xue, D Xue, R Yuan, Y Zhou, PV Balachandran, X Ding, J Sun, ... Acta Materialia 125, 532-541, 2017 | 156 | 2017 |
Improved convergence in block copolymer self-consistent field theory by Anderson mixing RB Thompson, KO Rasmussen, T Lookman The Journal of chemical physics 120 (1), 31-34, 2004 | 153 | 2004 |
Predictions of new perovskite compounds by combining machine learning and density functional theory PV Balachandran, AA Emery, JE Gubernatis, T Lookman, C Wolverton, ... Physical Review Materials 2 (4), 043802, 2018 | 150 | 2018 |