Yin, Wan-Jian

Simple descriptor derived from symbolic regression accelerating the discovery of new perovskite catalysts

Weng, B., Song, Z., Zhu, R., Yan, Q., Sun, Q., Grice, C. G., Yan, Y., & Yin, W.-J. (2020) · Nature Communications

Electrocatalysts for Energy ConversionMachine Learning in Materials Science

Cited by 376

Thermodynamic Stability Landscape of Halide Double Perovskites via High‐Throughput Computing and Machine Learning

Li, Z., Xu, Q., Sun, Q., Hou, Z., & Yin, W. (2019) · Advanced Functional Materials

Machine Learning in Materials SciencePerovskite Materials and Applications

Cited by 233

Achieving High-Quality Sn–Pb Perovskite Films on Complementary Metal-Oxide-Semiconductor-Compatible Metal/Silicon Substrates for Efficient Imaging Array

Zhu, H. L., Lin, H., Song, Z., Wang, Z., Ye, F., Zhang, H., Yin, W.-J., Yan, Y., & Choy, W. C. H. (2019) · ACS Nano

Perovskite Materials and ApplicationsAdvanced Semiconductor Detectors and Materials

Cited by 68

Machine learning in materials design: Algorithm and application*

Song, Z., Chen, X., Meng, F., Cheng, G., Wang, C., Sun, Z., & Yin, W.-J. (2020) · Chinese Physics B

Machine Learning in Materials ScienceComputational Drug Discovery Methods

Cited by 63

Bayesian optimization based on a unified figure of merit for accelerated materials screening: A case study of halide perovskites

Chen, X., Wang, C., Li, Z., Hou, Z., & Yin, W.-J. (2020) · Science China Materials

Machine Learning in Materials SciencePerovskite Materials and Applications

Cited by 47