Trifan, Anda; Gorgun, Defne; Salim, Michael; Li, Zongyi; Brace, Alexander; Zvyagin, Maxim; Ma, Heng; Clyde, Austin; Clark, David; Hardy, David J.; Burnley, Tom; Huang, Lei; McCalpin, John; Emani, Murali; Yoo, Hyenseung; Yin, Junqi; Tsaris, Aristeidis; Subbiah, Vishal; Raza, Tanveer; Liu, Jessica; Trebesch, Noah; Wells, Geoffrey; Mysore, Venkatesh; Gibbs, Thomas; Phillips, James; Chennubhotla, S. Chakra; Foster, Ian; Stevens, Rick; Anandkumar, Anima; Vishwanath, Venkatram; Stone, John E.; Tajkhorshid, Emad; Harris, Sarah A.; Ramanathan, Arvind

Neural network-based order parameter for phase transitions and its applications in high-entropy alloys

基于神经网络的相变序参量及其在高熵合金中的应用

NATURE COMPUTATIONAL SCIENCE

IF18.3

2021-10-1825

PREAI

The Role of Hydrophobic Nodes in the Dynamics of Class A β-Lactamases

FRONTIERS IN MICROBIOLOGY

IF4.5

2021-09-218

OAAI

Inter-Subunit Dynamics Controls Tunnel Formation During the Oxygenation Process in Hemocyanin Hexamers

FRONTIERS IN MOLECULAR BIOSCIENCES

IF4

2021-09-155

OAAI

Dynamic Profiling of β-Coronavirus 3CL Mpro Protease Ligand-Binding Sites

JOURNAL OF CHEMICAL INFORMATION AND MODELING

IF5.3

2021-06-1438

OAAI

Geometrical-Based Generative Adversarial Network to Enhance Digital Rock Image Quality

PHYSICAL REVIEW APPLIED

IF4.4

2021-06-149

OAAI

Monte Carlo simulation of order-disorder transition in refractory high entropy alloys: A data-driven approach

难熔高熵合金有序-无序转变的Monte Carlo模拟: 数据驱动方法

COMPUTATIONAL MATERIALS SCIENCE

IF3.3

2021-02-0152

OAAI

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19

JOURNAL OF CHEMICAL INFORMATION AND MODELING

IF5.3

2020-12-16130

OAAI

Acharya, A.; Agarwal, R.; Baker, M. B.; Baudry, J.; Bhowmik, D.; Boehm, S.; Byler, K. G.; Chen, S. Y.; Coates, L.; Cooper, C. J.; Demerdash, O.; Daidone, I; Eblen, J. D.; Ellingson, S.; Forli, S.; Glaser, J.; Gumbart, J. C.; Gunnels, J.; Hernandez, O.; Irle, S.; Kneller, D. W.; Kovalevsky, A.; Larkin, J.; Lawrence, T. J.; LeGrand, S.; Liu, S-H; Mitchell, J. C.; Park, G.; Parks, J. M.; Pavlova, A.; Petridis, L.; Poole, D.; Pouchard, L.; Ramanathan, A.; Rogers, D. M.; Santos-Martins, D.; Scheinberg, A.; Sedova, A.; Shen, Y.; Smith, J. C.; Smith, M. D.; Soto, C.; Tsaris, A.; Thavappiragasam, M.; Tillack, A. F.; Vermaas, J. V.; Vuong, V. Q.; Yin, J.; Yoo, S.; Zahran, M.; Zanetti-Polzi, L.

Machine-learning informed prediction of high-entropy solid solution formation: Beyond the Hume-Rothery rules

NPJ COMPUTATIONAL MATERIALS

IF11.9

2020-05-07144

OAAI

Robust data-driven approach for predicting the configurational energy of high entropy alloys

预测高熵合金构型能的鲁棒数据驱动方法

MATERIALS & DESIGN

IF7.9

2020-01-0161

OAAI

The relation between two ductility mechanisms for Mg alloys revealed by high-throughput simulations