Can machines “learn” halide #perovskite crystal formation without accurate physicochemical features?

Published in ACS, 2020

Recommended citation: see below http://aadharna.github.io/files/perovskite.pdf

This paper is about using machine learning to learn perovskite reactions when ones model of the world is not accurate.

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Citation and link inside post.

@article{Pendleton2020,
  doi = {10.1021/acs.jpcc.0c01726},
  url = {https://doi.org/10.1021/acs.jpcc.0c01726},
  year = {2020},
  month = jun,
  publisher = {American Chemical Society ({ACS})},
  author = {Ian M. Pendleton and Mary K. Caucci and Michael Tynes and Aaron Dharna and Mansoor Ani Najeeb Nellikkal and Zhi Li and Emory M. Chan and Alexander J. Norquist and Joshua Schrier},
  title = {Can Machines {\textquotedblleft}Learn{\textquotedblright} Halide Perovskite Crystal Formation without Accurate Physicochemical Features?},
  journal = {The Journal of Physical Chemistry C}
}