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    Jesús CapistránJesús Capistrán
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    My inspiration to learn/apply machine learning to accelerate the development of solar cells comes from the following literature:

    [1] J.-P. Correa-Baena, K. Hippalgaonkar, J. van Duren, S. Jaffer, V.R. Chandrasekhar, V. Stevanovic, C. Wadia, S. Guha, T. Buonassisi, Accelerating Materials Development via Automation, Machine Learning, and High-Performance Computing, Joule. 2 (2018) 1410–1420. https://doi.org/10.1016/j.joule.2018.05.009.

    [2] J. Wagner, C.G. Berger, X. Du, T. Stubhan, J.A. Hauch, C.J. Brabec, The evolution of Materials Acceleration Platforms: toward the laboratory of the future with AMANDA, J Mater Sci. 56 (2021) 16422–16446. https://doi.org/10.1007/s10853-021-06281-7.

    [3] G.R. Schleder, A.C.M. Padilha, C.M. Acosta, M. Costa, A. Fazzio, From DFT to machine learning: recent approaches to materials science–a review, J. Phys. Mater. 2 (2019) 032001. https://doi.org/10.1088/2515-7639/ab084b.

    Do you have a favorite research paper about Machine Learning applied to material science?

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