A data fusion approach to optimize compositional stability of halide perovskites

A data fusion approach to optimize compositional stability of halide perovskites

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 perovsk...

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Bibliographic Details
Main Authors: Sun, Shijing, Tiihonen, Armi, Oviedo, Felipe, Liu, Zhe, Thapa, Janak, Zhao, Yicheng, Hartono, Noor Titan 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
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering
Format: Article
Language:English
Published: Elsevier BV 2022
Online Access:https://hdl.handle.net/1721.1/139821.2

Internet

https://hdl.handle.net/1721.1/139821.2

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