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Record W4321018137 · doi:10.1126/science.ade3970

Rational design of Lewis base molecules for stable and efficient inverted perovskite solar cells

2023· article· en· W4321018137 on OpenAlexaff
Chongwen Li, Xiaoming Wang, Enbing Bi, Fangyuan Jiang, So Min Park, You Li, Lei Chen, Zaiwei Wang, Lewei Zeng, Hao Chen, Yanjiang Liu, Corey R. Grice, Abasi Abudulimu, Jaehoon Chung, Yeming Xian, Tao Zhu, Huagui Lai, Bin Chen, Randy J. Ellingson, Fan Fu, David S. Ginger, Zhaoning Song, Edward H. Sargent, Yanfa Yan

Bibliographic record

VenueScience · 2023
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Toronto
FundersLawrence Berkeley National LaboratoryU.S. Air ForceAir Force Research LaboratoryDivision of Materials ResearchCenter for Hybrid Organic Inorganic Semiconductors for EnergyOffice of ScienceOffice of Energy EfficiencyBasic Energy SciencesNational Energy Research Scientific Computing CenterOffice of Energy Efficiency and Renewable EnergyU.S. Department of EnergyU.S. Department of DefenseNational Science Foundation
KeywordsPerovskite (structure)Lewis acids and basesMoleculeBase (topology)Rational designMaterials scienceChemistryNanotechnologyCrystallographyMathematicsCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

Lewis base molecules that bind undercoordinated lead atoms at interfaces and grain boundaries (GBs) are known to enhance the durability of metal halide perovskite solar cells (PSCs). Using density functional theory calculations, we found that phosphine-containing molecules have the strongest binding energy among members of a library of Lewis base molecules studied herein. Experimentally, we found that the best inverted PSC treated with 1,3-bis(diphenylphosphino)propane (DPPP), a diphosphine Lewis base that passivates, binds, and bridges interfaces and GBs, retained a power conversion efficiency (PCE) slightly higher than its initial PCE of ~23% after continuous operation under simulated AM1.5 illumination at the maximum power point and at ~40°C for >3500 hours. DPPP-treated devices showed a similar increase in PCE after being kept under open-circuit conditions at 85°C for >1500 hours.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.227
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations622
Published2023
Admission routes1
Has abstractyes

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