This symposium invites contributions on computational modeling and simulation of materials for energy conversion, energy storage, and emerging functional applications. It will showcase theory- and computation-driven advances in the discovery, design, and understanding of materials for thermoelectrics, photocatalysis, neuromorphic and brain-inspired computing, bioelectronics, and related technologies. Contributions employing atomistic, electronic-structure, multiscale, and data-driven approaches are especially encouraged, particularly when they provide insight into structure–property relationships, transport phenomena, interfacial processes, and device operation. To strengthen the connection between theory and practice, the symposium will also include selected invited experimentalists leading research in these areas, with the aim of fostering active discussion and new collaborations between theoreticians and experimentalists. Additional topics of interest include molecular solar thermal energy storage (MOST), osmotic energy harvesting, piezo(ferro)electricity, and other emerging concepts at the interface of materials science, physics, chemistry, and computation.
- Thermoelectrics
- Photocatalysis
- Energy conversion materials
- Energy storage materials
- Neuromorphic and brain-inspired computing
- Bioelectronics
- Molecular solar thermal energy storage (MOST)
- Osmotic energy and piezo(ferro)electric materials
Perla BalbuenaMaria Chan is a Scientist at the Center for Nanoscale Materials at Argonne National Laboratory. She holds joint appointments as a Senior Fellow at the Northwestern Argonne Institute for Science and Engineering (NAISE) and a Fellow at the University of Chicago Consortium for Advanced Science and Engineering (CASE). Chan earned her BSc in Physics and Applied Mathematics from the University of California, Los Angeles, and her PhD in Physics from the Massachusetts Institute of Technology.
Chan’s research focuses on computational materials science and theory-guided artificial intelligence and machine learning (AI/ML) for energy materials. Her work integrates atomistic modeling with multimodal experimental characterization, including X-ray, electron microscopy, and scanning probe techniques, to study energy storage materials, catalysts, photovoltaics, and thermoelectrics. She leads efforts in developing AI/ML frameworks for characterization data inversion and scientific literature data extraction. She also contributes towards computational materials design and autonomous materials discovery. Chan serves on the leadership teams for multiple U.S. Department of Energy (DOE) projects on energy storage, catalysis, and computational materials science.
KMP studied organic chemistry at the University of Copenhagen where he obtained the Cand. Scient. (2003) and Ph.D. (2007) In 2009, he continued his career as a postdoc U.C. Berkeley, where he worked with professors Rachel Segalman and Peter Vollhardt. In 2011 KMP was recruited to Chalmers University of Technology, as an assistant professor, and later promoted to associate (2014), professor (2017) and full professor (2019). Since October 2021 KMP is awarded a professor position at the Catalan Institute of Advanced Studies (ICREA) and joined the Institute of Materials Science of Barcelona (ICMAB-CSIC) as an ICREA research professor. In January 2023 he joined the Department of Chemical Engineering at the Polytechnic University of Catalunya (UPC) as the leader of the molecular materials (MOMA) group. Since 2027 he is back at Chalmers in Sweden.
Yue Qi is the Joan Wernig Sorensen Professor of Engineering at Brown University. She received her Ph.D. from Caltech in 2001. She spent the next 12 years working at General Motors and transitioned back to academia in 2013 as a faculty member at Michigan State University before joining Brown in 2020. She develops multi-scale simulation methods, starting from quantum mechanics, to design materials and interfaces for energy efficiency and sustainability. She has served in multiple inaugural roles aimed at increasing diversity in Engineering.
Zhigang Shuai received B.Sc. in 1983 from Sun Yat-sen University majoring in physics and PhD in theoretical physics in 1989 from Fudan University. Then he went to work with Prof. Jean-Luc Brédas in the University of Mons, Belgium, as a postdoc and then as a research associate. In 2000, he received the support of "Hundred-Talent Program” in the Institute of Chemistry of the Chinese Academy of Sciences. He was granted the Outstanding Young Investigator's Fund from the National Natural Science Foundation of China in 2004. He moved to Tsinghua University in 2008 as a Changjiang Scholar Chair Professor. Since 2022, he is the X. Q. Deng Presiential Chair Professor in the Chinese University of Hong Kong-Shenzhen. He pioneered the quantum chemistry density matrix renormalization group (DMRG) theory. He has developed a number of computational methods to modelling and understanding the electronic processes in organic and polymeric materials focusing on the excited state structure and dynamics. His computational package MOMAP has been successfully commercialized. He has published more than 480 papers in scientific peer-reviewed journals with H-index 110. He is a member of International Academy of Quantum Molecular Science, foreign member of the Academia Europaea, foreign member of Royal Academy of Belgium, scientific board member of the World Association of Theoretical and Computational Chemists (WATOC), and fellow of Royal Society of Chemistry. He was the recipient of the Chinese Chemical Society – AkzoNobel Chemical Science Award (2012), the French Chemical Society Prix Franco-Chinois (2018), and the First-Class Award of Beijing Municipal Natural Science Prize (2020). He is a Member of Executive Board of IUPAC since 2022. He is Vice President of the Chinese Chemical Society (2019-2022, 2023-2026).
Hanna Türk