TY - JOUR
T1 - Sustainable materials acceleration platform reveals stable and efficient wide-bandgap metal halide perovskite alloys
AU - Wang, Tonghui
AU - Li, Ruipeng
AU - Ardekani, Hossein
AU - Serrano-Luján, Lucía
AU - Wang, Jiantao
AU - Ramezani, Mahdi
AU - Wilmington, Ryan
AU - Chauhan, Mihirsinh
AU - Epps, Robert W.
AU - Darabi, Kasra
AU - Guo, Boyu
AU - Sun, Dali
AU - Abolhasani, Milad
AU - Gundogdu, Kenan
AU - Amassian, Aram
N1 - Generated from Scopus record by KAUST IRTS on 2023-10-23
PY - 2023/9/6
Y1 - 2023/9/6
N2 - The vast chemical space of emerging semiconductors, like metal halide perovskites, and their varied requirements for semiconductor applications have rendered trial-and-error environmentally unsustainable. In this work, we demonstrate RoboMapper, a materials acceleration platform (MAP), that achieves 10-fold research acceleration by formulating and palletizing semiconductors on a chip, thereby allowing high-throughput (HT) measurements to generate quantitative structure-property relationships (QSPRs) considerably more efficiently and sustainably. We leverage the RoboMapper to construct QSPR maps for the mixed ion FA1−yCsyPb(I1−xBrx)3 halide perovskite in terms of structure, bandgap, and photostability with respect to its composition. We identify wide-bandgap alloys suitable for perovskite-Si hybrid tandem solar cells exhibiting a pure cubic perovskite phase with favorable defect chemistry while achieving superior stability at the target bandgap of ∼1.7 eV. RoboMapper's palletization strategy reduces environmental impacts of data generation in materials research by more than an order of magnitude, paving the way for sustainable data-driven materials research.
AB - The vast chemical space of emerging semiconductors, like metal halide perovskites, and their varied requirements for semiconductor applications have rendered trial-and-error environmentally unsustainable. In this work, we demonstrate RoboMapper, a materials acceleration platform (MAP), that achieves 10-fold research acceleration by formulating and palletizing semiconductors on a chip, thereby allowing high-throughput (HT) measurements to generate quantitative structure-property relationships (QSPRs) considerably more efficiently and sustainably. We leverage the RoboMapper to construct QSPR maps for the mixed ion FA1−yCsyPb(I1−xBrx)3 halide perovskite in terms of structure, bandgap, and photostability with respect to its composition. We identify wide-bandgap alloys suitable for perovskite-Si hybrid tandem solar cells exhibiting a pure cubic perovskite phase with favorable defect chemistry while achieving superior stability at the target bandgap of ∼1.7 eV. RoboMapper's palletization strategy reduces environmental impacts of data generation in materials research by more than an order of magnitude, paving the way for sustainable data-driven materials research.
UR - https://linkinghub.elsevier.com/retrieve/pii/S2590238523003442
UR - http://www.scopus.com/inward/record.url?scp=85169801625&partnerID=8YFLogxK
U2 - 10.1016/j.matt.2023.06.040
DO - 10.1016/j.matt.2023.06.040
M3 - Article
SN - 2590-2385
VL - 6
SP - 2963
EP - 2986
JO - Matter
JF - Matter
IS - 9
ER -