Symposium FP
Computational-aided Energy Materials Design
Convener:
Nicola SERIANI, International Center Theoretical Physics, Italy
Members:
Mark ASTA, University of California, Berkeley, USA
Gerbrand CEDER, University of California, Berkeley, USA
Hsin-Yi Tiffany CHEN, National Tsing Hua University, Taiwan
Long-Qing CHEN, The Pennsylvania State University, USA
Alessio FILIPPETTI, CNR-IOM and University of Cagliari, Italy
Cesare FRANCHINI, University of Vienna, Austria
Geoffroy HAUTIER, Dartmouth College, USA
Jianwen JIANG, National University of Singapore, Singapore
Yousung JUNG, Seoul National University, South Korea
Sergey V. LEVCHENKO, Center for Energy and Technology (CEST), Russia
Christian MASQUELIER, Université of Picardie Jules Verne, France
Fumiyasu OBA, Tokyo Institute of Technology, Japan
Pablo ORDEJON, Institut Català d'Investigaciò Nanotecnologia, Spain
Mariachiara PASTORE, CNRS and University of Lorraine, France
Oleg PREZHDO, University of Southern California, USA
Zhigang SHUAI, Tsinghua University, China
Isao TANAKA, Kyoto University, Japan
Matthias VANDICHEL, University of Limerick, Ireland
Christofer M. WOLVERTON, Northwestern University, USA
Dawei ZHANG, University of Science and Technology Beijing, China
Shijun ZHAO, City University of Hong Kong, China
Nicola SERIANI, International Center Theoretical Physics, Italy
Members:
Mark ASTA, University of California, Berkeley, USA
Gerbrand CEDER, University of California, Berkeley, USA
Hsin-Yi Tiffany CHEN, National Tsing Hua University, Taiwan
Long-Qing CHEN, The Pennsylvania State University, USA
Alessio FILIPPETTI, CNR-IOM and University of Cagliari, Italy
Cesare FRANCHINI, University of Vienna, Austria
Geoffroy HAUTIER, Dartmouth College, USA
Jianwen JIANG, National University of Singapore, Singapore
Yousung JUNG, Seoul National University, South Korea
Sergey V. LEVCHENKO, Center for Energy and Technology (CEST), Russia
Christian MASQUELIER, Université of Picardie Jules Verne, France
Fumiyasu OBA, Tokyo Institute of Technology, Japan
Pablo ORDEJON, Institut Català d'Investigaciò Nanotecnologia, Spain
Mariachiara PASTORE, CNRS and University of Lorraine, France
Oleg PREZHDO, University of Southern California, USA
Zhigang SHUAI, Tsinghua University, China
Isao TANAKA, Kyoto University, Japan
Matthias VANDICHEL, University of Limerick, Ireland
Christofer M. WOLVERTON, Northwestern University, USA
Dawei ZHANG, University of Science and Technology Beijing, China
Shijun ZHAO, City University of Hong Kong, China
The list of Invited Speakers will be available at the end of July 2025
Computational materials science has demonstrated its power in modelling structure and functional properties of real materials, and in predicting novel materials with improved performance. It naturally is cross - disciplinary as it is based on physics, chemistry, engineering, data science, and even biology. It addresses properties of materials that span several length and time scales, and as such it often takes advantage of multiscale computing strategies. In the last decades computational materials science has increased tis predictive power and scope for materials development because of progress in methods and in computational power. More recently, it has received a further boost from the emergence of machine learning and data science.
This Symposium is devoted to advances in development and application of computational methods, including multiscale computing strategies and machine learning methods, for predicting materials properties, with applications in energy systems. Appropriate are studies that combine data- and physics-driven models for the identification of structure-property relationships and the predictive design, possibly experimentally validated, of novel energy materials.
The methods may range from high-accuracy electronic structure techniques for atomistic simulations, through mesoscopic simulations, to continuum models, with particular interest in integrated multi-scale modelling. All materials for energy applications are relevant for the symposium, ranging from nanostructured functional inorganic materials through solid/liquid interfaces and bio-inspired materials to structural materials.
This Symposium is devoted to advances in development and application of computational methods, including multiscale computing strategies and machine learning methods, for predicting materials properties, with applications in energy systems. Appropriate are studies that combine data- and physics-driven models for the identification of structure-property relationships and the predictive design, possibly experimentally validated, of novel energy materials.
The methods may range from high-accuracy electronic structure techniques for atomistic simulations, through mesoscopic simulations, to continuum models, with particular interest in integrated multi-scale modelling. All materials for energy applications are relevant for the symposium, ranging from nanostructured functional inorganic materials through solid/liquid interfaces and bio-inspired materials to structural materials.
Session Topics
FP-1 Solar technologies (photovoltaics, solar fuels, solar thermal)
FP-2 Electrochemical energy systems (batteries, supercapacitors, fuel cells)
FP-3 Catalysts for energy conversion and storage
FP-4 Materials for production, capture, separation, storage, and utilization of gases
FP-5 Thermal energy storage
FP-6 Thermoelectrics, energy harvesting materials and nanogenerators
FP-7 Permanent magnets for electric generators and motors
FP-8 Nuclear materials for fission and fusion: fuels, plants, and waste
FP-9 Data science and artificial intelligence for materials development