2023 MRS Spring Meeting
Symposium EL02-Material Innovation Toward Stable Halide Perovskite Electronics
Metal-halide perovskite materials are recent champions for clean energy generation and power conversion applications. Over the past decade, perovskite photovoltaics and light emitting diodes have delivered unprecedented efficiencies by virtue of the rapid development in the field. Despite these impressive progresses, one of the key remaining road blocks preventing the practical application of perovskite devices is their poor environmental stability and proneness to degradation under device operational conditions. Without addressing the stability issues, perovskite-based optoelectronic devices will remain to be laboratory scale demonstrations.
This symposium aims to bring together cutting-edge ideas that would facilitate material innovation for stable perovskite photovoltaics, light emitting diodes and detectors. Recent developments for stable performances in this area include, but are not limited to, novel perovskite nano-structures such as quantum dots, nanowires and nanosheets, hetero-structures formed by perovskites and passivation organic layers or frameworks, and ligand-mediated wavefunction engineering. These advances in material discovery and structural engineering have led to significant progresses in device stability that ranges from environmental stability, electrical field stability and stability under constant irradiation.
In addition to material growth, this symposium will also cover topics on mechanistic understanding of material and device stability through advanced characterization tools, such as operando high resolution spectroscopy and in-situ characterization techniques.
Topics will include:
- Innovative perovskite nano-structures and heterostructures for improved environmental stability
- Innovations in device layouts, electrodes, interface layers to extend the devices’ operational stability
- Novel extreme characterization techniques, such as ultra-fast, ultra-resolution optical spectroscopy, X-ray spectroscopy, and electron
- In-situ, operando characterization methods for mechanistic understanding of the materials’ structural assembly and stability
- Theoretical modeling for understanding the degradation chemistry and defect induced degradation
- Data science, machine learning tool for discovering stable perovskite structures
Invited Speakers:
- Christoph Brabec (Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany)
- Annalisa Bruno (Nanyang Technological University, Singapore)
- Caterina Ducati (University of Cambridge, United Kingdom)
- Alessio Filipetti (Università degli Studi di Cagliari, Italy)
- Mercouri Kanatzidis (Northwestern University, USA)
- Aron Lindenberg (Stanford University, USA)
- Rebecca Milot (University of Warwick, United Kingdom)
- Laura Miranda Perez (Oxford PV, United Kingdom)
- Peter Müller-Buschbaum (Technische Universität München, Germany)
- Nakita Noel (University of Oxford, United Kingdom)
- Lakshmi Polavarapu (Universidade de Vigo, Spain)
- Giuseppe Portale (University of Groningen, Netherlands)
- Loredana Protesescu (University of Groningen, Netherlands)
- Laura Schelhas (National Renewable Energy Laboratory, USA)
- Hayase Shuzi (The University of Electro-Communications, Japan)
- Sam Stranks (University of Cambridge, United Kingdom)
- Shijing Sun (Toyota Research Institute, USA)
- Sergei Tretiak (Los Alamos National Laboratory, USA)
- Hsinhan Tsai (University of California, Berkeley, USA)
- Leeyih Wang (National Taiwan University, Taiwan)
- Lydia Wong (Nanyang Technological University, Singapore)
- Yang Yang (Zhejiang University, China)
- Alvin Zhou (Hong Kong Baptist University, Hong Kong)
Symposium Organizers
Xuedan Ma
Argonna National Laboratory
Center for Nanoscale Materials
USA
Maria Antonietta Loi
University of Groningen
Zernike Institute for Advanced Materials
Netherlands
Robert Hoye
Department of Chemistry
United Kingdom
Wanyi Nie
Los Alamos National Laboratory
USA
Topics
crystal growth
electronic material
energy generation
energy storage
in situ
microstructure
modeling
nanostructure
operando
organometallic