Understanding Local Crystallography in Solar Cell Absorbers with Scanning Electron Diffraction [* Cross-Reference *]

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Andrea Griesi; Yurii P. Ivanov; Simon M. Fairclough; Arivazhagan Valluvar Oli; Gunnar Kusch; Rachel A. Oliver; Paola De Padova; C. Ottaviani; Udari Wijesinghe; Susanne Siebentritt; Aldo Di Carlo; Oliver S. Hutter; Giulia Longo; Giorgio Divitini, 2026, "Understanding Local Crystallography in Solar Cell Absorbers with Scanning Electron Diffraction [* Cross-Reference *]", https://lore.list.lu/citation?persistentId=perma:LIST.NWX0VP, LIST Open Repository, V1

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Description	In thin film photovoltaic devices, the control of grain structure and local crystallography are fundamental for high power conversion efficiency and reliable long-term operation. Structural defects, grain boundaries, and unwanted phases can stem from compositional inhomogeneities or from specific synthesis parameters, and they need to be thoroughly understood and carefully engineered. However, comprehensive studies of the crystallographic properties of complex systems, including different phases and/or a large number of grains, are often prohibitively challenging. Here, the use of 4D Scanning Transmission Electron Microscopy (4D-STEM) is demonstrated on cross-sections to unravel the nanoscale properties of three different materials for photovoltaics: Cu(In,Ga)S2, halide perovskite, and Sb2Se3. These materials are chosen because of the variety of challenges they present: the presence of multiple phases and complex stoichiometry, electron beam sensitivity, and very high density of grains. 4D-STEM provides comprehensive insights into crystallinity and microstructure, but navigating its large datasets and extracting actionable, statistically sound information requires advanced algorithms. How unsupervised machine learning, including dimensionality reduction and hierarchical clustering, can extract key information from 4D-STEM datasets is demonstrated. The analytical framework follows FAIR principles, employing open-source software and enabling data sharing. (2025-09-25) *This entry has been automatically imported via OpenAlex by LIST harvest scripts. Please refer to https://doi.org/10.1002/smtd.202501334 for the original and latest version of the publication* (2026-07-01)
Subject	Engineering; Physics
Keyword	Scanning transmission electron microscopy, Photovoltaics, Photovoltaic system, Crystallinity, Grain boundary, Solar cell, Reduction (mathematics), Cathode ray, Dimensionality reduction
License/Data Use Agreement	CC BY 4.0


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Persistent Identifier	perma:LIST.NWX0VP
Publication Date	2026-07-06
Title	Understanding Local Crystallography in Solar Cell Absorbers with Scanning Electron Diffraction [* Cross-Reference *]
Other Identifier	https://doi.org/10.1002/smtd.202501334 OpenAlex ID: https://openalex.org/W4414514251
Author	Andrea Griesi (Italian Institute of Technology) - ORCID: https://orcid.org/0000-0003-2173-5164 Yurii P. Ivanov (Italian Institute of Technology) - ORCID: https://orcid.org/0000-0003-0271-5504 Simon M. Fairclough (University of Cambridge) - ORCID: https://orcid.org/0000-0003-3781-8212 Arivazhagan Valluvar Oli (University of Luxembourg, Luxembourg Institute of Science and Technology) - ORCID: https://orcid.org/0000-0003-2821-6076 Gunnar Kusch (University of Cambridge) - ORCID: https://orcid.org/0000-0003-2743-1022 Rachel A. Oliver (University of Cambridge) - ORCID: https://orcid.org/0000-0003-0029-3993 Paola De Padova (Institute of Structure of Matter) - ORCID: https://orcid.org/0000-0001-5836-4884 C. Ottaviani (Institute of Structure of Matter) - ORCID: https://orcid.org/0000-0001-9364-8591 Udari Wijesinghe (Northumbria University) - ORCID: https://orcid.org/0000-0001-5422-7321 Susanne Siebentritt (University of Luxembourg, Luxembourg Institute of Science and Technology) - ORCID: https://orcid.org/0000-0001-6522-1427 Aldo Di Carlo (Institute of Structure of Matter) - ORCID: https://orcid.org/0000-0001-6828-2380 Oliver S. Hutter (Northumbria University) - ORCID: https://orcid.org/0000-0002-8838-8956 Giulia Longo (Northumbria University, Universitat Politècnica de València) - ORCID: https://orcid.org/0000-0002-1163-1110 Giorgio Divitini (Italian Institute of Technology) - ORCID: https://orcid.org/0000-0003-2775-610X
Point of Contact	Use email button above to contact. LIST QDKM (LIST)
Description	In thin film photovoltaic devices, the control of grain structure and local crystallography are fundamental for high power conversion efficiency and reliable long-term operation. Structural defects, grain boundaries, and unwanted phases can stem from compositional inhomogeneities or from specific synthesis parameters, and they need to be thoroughly understood and carefully engineered. However, comprehensive studies of the crystallographic properties of complex systems, including different phases and/or a large number of grains, are often prohibitively challenging. Here, the use of 4D Scanning Transmission Electron Microscopy (4D-STEM) is demonstrated on cross-sections to unravel the nanoscale properties of three different materials for photovoltaics: Cu(In,Ga)S2, halide perovskite, and Sb2Se3. These materials are chosen because of the variety of challenges they present: the presence of multiple phases and complex stoichiometry, electron beam sensitivity, and very high density of grains. 4D-STEM provides comprehensive insights into crystallinity and microstructure, but navigating its large datasets and extracting actionable, statistically sound information requires advanced algorithms. How unsupervised machine learning, including dimensionality reduction and hierarchical clustering, can extract key information from 4D-STEM datasets is demonstrated. The analytical framework follows FAIR principles, employing open-source software and enabling data sharing. (2025-09-25) *This entry has been automatically imported via OpenAlex by LIST harvest scripts. Please refer to https://doi.org/10.1002/smtd.202501334 for the original and latest version of the publication* (2026-07-01)
Subject	Engineering; Physics
Keyword	Scanning transmission electron microscopy Photovoltaics Photovoltaic system Crystallinity Grain boundary Solar cell Reduction (mathematics) Cathode ray Dimensionality reduction
Topic Classification	Chalcogenide Semiconductor Thin Films Perovskite Materials and Applications Quantum Dots Synthesis And Properties
Deposit Date	2025-09-25
Data Type	Article
Data Source	Small Methods

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