Publications

Zou, X., Zhao, Y.*, Shan, X., Jiang, J., Mitchell, R.N., Zou, Y., Wang, H., Yang, W., Yao, Z., Qin, K., Li, X.-H., 2026. Rare earth element partitioning in hadean zircons establishes granitic magma source. Earth Planet. Sci. Lett. 690, 120136. https://doi.org/10.1016/j.epsl.2026.120136

Lv, P., Zou, X., Jiang, J., Zhao, Y., Chen, W., Gao, S., Xue, G., Qin, K., Mitchell, R.N., Yang, W., 2026. Quality/quantity quandary: machine learning framework for assessing tradeoffs in zircon geochemistry. Earth Planet. Sci. Lett. 683, 119983. https://doi.org/10.1016/j.epsl.2026.119983

Jiang, J., Zou, X., Mitchell, R.N., Zhang, Y., Zhao, Y., Yin, Q.-Z., Yang, W., Zhou, X., Wang, H., Spencer, C.J., Shan, X., Wu, S., Li, G., Qin, K., Li, X.-H., 2024. Sediment subduction in hadean revealed by machine learning. Proc. Natl. Acad. Sci. 121, e2405160121. https://doi.org/10.1073/pnas.2405160121

Zhao, Y., Liu, Z., Ni, D., Chen, Z., 2024. Comparison of machine-learning and bayesian inferences for the interior of rocky exoplanets with large compositional diversity. Astrophys. J. Suppl. Ser. 272, 35. https://doi.org/10.3847/1538-4365/ad3f1c

Zhao, Y., Ni, D., 2022. Understanding the interior structure of gaseous giant exoplanets with machine learning techniques. A & A 658, A201. https://doi.org/10.1051/0004-6361/202142874

Zhao, Y., Ni, D., 2021. Machine learning techniques in studies of the interior structure of rocky exoplanets. A & A 650, A177. https://doi.org/10.1051/0004-6361/202140375

Zhao, Y., Ni, D., Liu, Z., 2023a. Machine-learning inferences of the interior structure of rocky exoplanets from bulk observational constraints. Astrophys. J. Suppl. Ser. 269, 1. https://doi.org/10.3847/1538-4365/acf31a

Zhao, Y., Zhang, Y., Ni, D., 2023b. Dynamic evolution of changbaishan volcanism in northeast china illuminated by machine learning. Front. Earth Sci. 10. https://doi.org/10.3389/feart.2022.1084213

Zhao, Y., Zhang, Y., Geng, M., Jiang, J., Zou, X., 2019. Involvement of slab‐derived fluid in the generation of cenozoic basalts in northeast china inferred from machine learning. Geophys. Res. Lett. 46, 5234–5242. https://doi.org/10.1029/2019gl082322

Li, C., Shen, P., Zhao, Y., Li, P., Zhang, L., Pan, H., 2022. Mineral chemistry of chlorite in different geologic environments and its implications for porphyry Cu ± Au ± Mo deposits. Ore Geol. Rev. 149, 105112. https://doi.org/10.1016/j.oregeorev.2022.105112

Liu, W., Zhang, Y., Yin, Q.-Z., Zhao, Y., Zhang, Z., 2020. Magnesium partitioning between silicate melt and liquid iron using first-principles molecular dynamics: implications for the early thermal history of the Earth’s core. Earth Planet. Sci. Lett. 531, 115934. https://doi.org/10.1016/j.epsl.2019.115934

Zhang, Q., Sun, W., Zhao, Y., Yuan, F., Jiao, S., Chen, W., 2019. New discrimination diagrams for basalts based on big data research. Big Earth Data 3, 45–55. https://doi.org/10.1080/20964471.2019.1576262

Liu, X.L., Zhang, Q., Li, W.C., Yang, F.C., Zhao, Y., Li, Z., Jiao, S.T., Wang, J.R., Zhang, N., Wang, S.S., Chen, W.F., Pan, Z.J., Yang, J., Du, X.L., 2018. Applicability of large-ion lithophile and high field strength element basalt discrimination diagrams. Int. J. Digital Earth 11, 752–760. https://doi.org/10.1080/17538947.2017.1365959

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