Perspective on machine learning in electrochemistry published in ACS Energy Letters

This article, which was written in collaboration with international battery modeling and machine learning experts from Argonne NL (A. Mistry), Carnegie Mellon (V. Viswanathan), Imperial College (S. Cooper), and LRCS (A. Franco), discusses how machine learning has impacted the electrochemical sciences over the past decade.  Even more importantly, is proposes future areas where the authors expect machine learning will have increased impact in the coming decade, potentially revolutionizing the field.  DOI: 10.1021/acsenergylett.1c00194