Publikationen von Christopher A. Sutton

Foppa, L., C.A. Sutton, L.M. Ghiringhelli, S. De, P. Löser, S.A. Schunk, A. Schäfer und M. Scheffler: Learning Design Rules for Selective Oxidation Catalysts from High-Throughput Experimentation and Artificial Intelligence. ACS Catalysis 12 (4), 2233–2232 (2022).

Bartel, C.J., J.M. Clary, C.A. Sutton, D. Vigil-Fowler, B.R. Goldsmith, A.M. Holder und C.B. Musgrave: Inorganic Halide Double Perovskites with Optoelectronic Properties Modulated by Sublattice Mixing. Journal of the American Chemical Society 142 (11), 5135–5145 (2020).

Sutton, C.A., M. Boley, L.M. Ghiringhelli, M. Rupp, J. Vreeken und M. Scheffler: Identifying domains of applicability of machine learning models for materials science. Nature Communications 11, 4428 (2020).

Wouters, C., C.A. Sutton, L.M. Ghiringhelli, T. Markut, R. Schewski, A. Hassa, H. Von Wenckstern, M. Grundmann, M. Scheffler und M. Albrecht: Investigating the ranges of (meta)stable phase formation in (In_xGa_1−x)₂O₃: Impact of the cation coordination. Physical Review Materials 4 (12), 125001 (2020).

Bartel, C.J., C.A. Sutton, B.R. Goldsmith, R. Ouyang, C.B. Musgrave, L.M. Ghiringhelli und M. Scheffler: New tolerance factor to predict the stability of perovskite oxides and halides. Science Advances 5 (2), eaav0693 (2019).

Sutton, C.A., L.M. Ghiringhelli, T. Yamamoto, Y. Lysogorskiy, L. Blumenthal, T. Hammerschmidt, J.R. Golebiowski, X. Liu, A. Ziletti und M. Scheffler: Crowd-sourcing materials-science challenges with the NOMAD 2018 Kaggle competition. npj Computational Materials 5, 111 (2019).

Goldsmith, B.R., J. Esterhuizen, J.X. Liu, C.J. Bartel und C.A. Sutton: Machine learning for heterogeneous catalyst design and discovery. AIChE-Journal 64 (7), 2311–2323 (2018).

Sutton, C.A., N.R. Tummala, D. Beljonne und Brédas Jean-Luc: Singlet Fission in Rubrene Derivatives: Impact of Molecular Packing. Chemistry of Materials 29 (7), 2777–2787 (2017).

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