A data fusion approach to optimize compositional stability of halide perovskites

Sun, Shijing; Tiihonen, Armi; Oviedo, Felipe; Liu, Zhe; Thapa, Janak; Zhao, Yicheng; Hartono, Noor P.; Goyal, Anuj; Heumueller, Thomas; Batali, Clio; Encinas, Alex; Yoo, Jason J.; Li, Ruipeng; Ren, Zekun; Peters, I. Marius; Brabec, Christoph J.; Bawendi, Moungi G.; Stevanovic, Vladan; Fisher, John; Buonassisi, Tonio

doi:10.1016/j.matt.2021.01.008

A data fusion approach to optimize compositional stability of halide perovskites

Journal Article · Mon Feb 01 00:00:00 EST 2021 · Matter (Online)

DOI:https://doi.org/10.1016/j.matt.2021.01.008· OSTI ID:1778797

^[1]; ^[1]; Oviedo, Felipe ^[1]; Liu, Zhe ^[1]; Thapa, Janak ^[1]; Zhao, Yicheng ^[2]; ^[1]; Goyal, Anuj ^[3]; ^[2]; Batali, Clio ^[1]; Encinas, Alex ^[1]; ^[1]; Li, Ruipeng ^[4]; Ren, Zekun ^[5]; Peters, I. Marius ^[6]; Brabec, Christoph J. ^[2]; Bawendi, Moungi G. ^[1]; Stevanovic, Vladan ^[3]; Fisher, John ^[1]; Buonassisi, Tonio ^[7]

Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Helmholz Institute Erlangen-Nürnberg (HI-ERN), Erlangen (Germany); Freidrich Alexander Univ. Erlangen-Nürnberg (FAU), Erlangen (Germany). Institute of Materials for Electronics and Energy Technology (i-MEET)
Colorado School of Mines, Golden, CO (United States)
Brookhaven National Lab. (BNL), Upton, NY (United States)
Singapore-MIT Alliance for Research and Technology (Singapore)
Helmholz Institute Erlangen-Nürnberg (HI-ERN), Erlangen (Germany)
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Singapore-MIT Alliance for Research and Technology (Singapore)

Search for resource-efficient materials in vast compositional spaces is an outstanding challenge in creating environmentally stable perovskite semiconductors. We demonstrate a physics-constrained sequential learning framework to subsequently identify the most stable alloyed organic-inorganic perovskites. We fuse data from high-throughput degradation tests and first-principle calculations of phase thermodynamics into an end-to-end Bayesian optimization algorithm using probabilistic constraints. By sampling just 1.8% of the discretized Cs_xMA_yFA_1-x-yPbI₃ (MA, methylammonium; FA, formamidinium) compositional space, perovskites centered at Cs_0.17MA_0.03FA_0.80PbI₃ show minimal optical change under increased temperature, moisture, and illumination with >17-fold stability improvement over MAPbI3. The thin films have 3-fold improved stability compared with state-of-the-art multi-halide Cs_0.05(MA_0.17FA_0.83)_0.95Pb(I_0.83Br_0.17)₃, translating into enhanced solar cell stability without compromising conversion efficiency. Synchrotron-based X-ray scattering validates the suppression of chemical decomposition and minority phase formation achieved using fewer elements and a maximum of 8% MA. We anticipate that this data fusion approach can be extended to guide materials discovery for a wide range of multinary systems.

View Accepted Manuscript (DOE)

Research Organization:: Brookhaven National Laboratory (BNL), Upton, NY (United States); National Science Foundation (NSF); Singapore-MIT Alliance for Research and Technology Low Energy Electronic Systems Program; Skotech NGP Program

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)

Grant/Contract Number:: SC0012704

OSTI ID:: 1778797

Alternate ID(s):: OSTI ID: 1824693

Report Number(s):: BNL--221308-2021-JAAM

Journal Information:: Matter (Online), Journal Name: Matter (Online) Journal Issue: 4 Vol. 4; ISSN 2590-2385

Publisher:: Cell Press/ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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