Low-cost machine learning prediction of excited state properties of iridium-centered phosphors-Reference-Cited by-同舟云学术

Low-cost machine learning prediction of excited state properties of iridium-centered phosphors

Author:

Terrones Gianmarco G.¹^ORCID,Duan Chenru¹²^ORCID,Nandy Aditya¹²^ORCID,Kulik Heather J.¹²^ORCID

Affiliation:

1. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

2. Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

Abstract

Neural networks are used to predict iridium phosphor excited state properties at accuracy competitive with TDDFT, enabling high-throughput screening.

Funder

Office of Naval Research

Alfred P. Sloan Foundation

National Science Foundation

Defense Advanced Research Projects Agency

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

Reference106 articles.

2. D. O.Hall and K.Rao , Photosynthesis , Cambridge University Press , 1999

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