Schrier, Joshua

Machine-learning-assisted materials discovery using failed experiments

Raccuglia, P., Elbert, K. C., Adler, P. D. F., Falk, C., Wenny, M. B., Mollo, A., Zeller, M., Friedler, S. A., Schrier, J., & Norquist, A. J. (2016) · Nature

Machine Learning in Materials ScienceComputational Drug Discovery Methods

Cited by 1,727

Anthropogenic biases in chemical reaction data hinder exploratory inorganic synthesis

Jia, X., Lynch, A., Huang, Y., Danielson, M., Lang’at, I., Milder, A., Ruby, A. E., Wang, H., Friedler, S. A., Norquist, A. J., et al. (2019) · Nature

Machine Learning in Materials ScienceEthics and Social Impacts of AI

Cited by 222

Robot-Accelerated Perovskite Investigation and Discovery

Li, Z., Najeeb, M. A., Alves, L., Sherman, A. Z., Shekar, V., Cruz Parrilla, P., Pendleton, I. M., Wang, W., Nega, P. W., Zeller, M., et al. (2020) · Chemistry of Materials

Perovskite Materials and ApplicationsMachine Learning in Materials Science

Cited by 187

Active meta-learning for predicting and selecting perovskite crystallization experiments

Shekar, V., Nicholas, G., Najeeb, M. A., Zeile, M., Yu, V., Wang, X., Slack, D., Li, Z., Nega, P. W., Chan, E. M., et al. (2022) · The Journal of Chemical Physics

Machine Learning in Materials ScienceMachine Learning and Algorithms

Cited by 25

Principled Exploration of Bipyridine and Terpyridine Additives to Promote Methylammonium Lead Iodide Perovskite Crystallization

Hartono, N. T. P., Ani Najeeb, M., Li, Z., Nega, P. W., Fleming, C. A., Sun, X., Chan, E. M., Abate, A., Norquist, A. J., Schrier, J., et al. (2022) · Crystal Growth & Design

Perovskite Materials and ApplicationsMachine Learning in Materials Science

Cited by 13