Symposium FA
Advanced Characterization and Computational-aided Energy Materials Design
Convener:
Paola PRETE, University of Salento, Italy
Nicola SERIANI, International Center Theoretical Physics, Italy
Members:
Mark ASTA, University of California, Berkeley, USA
Annalisa BRUNO, Nanyang Technological University, Singapore
Montserrat CASAS-CABANAS, CIC EnergiGUNE, Spain
Alessio FILIPPETTI, CNR-IOM and University of Cagliari, Italy
Laurence HARDWICK, The University of Liverpool, UK
Yuichi IKUHARA, The University of Tokyo, Japan
Karl LEO, TU Dresden, Germany
Michal LESKES, Weizmann Institute of Science, Israel
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
Neeraj SHARMA, University of New South Wales, Australia
Emmanuelle SUARD, Institut Laue-Langevin, France
Michael TONEY, University of Colorado at Boulder, USA
Matthias VANDICHEL, University of Limerick, Ireland
Christopher M. WOLVERTON, Northwestern University, USA
Shijun ZHAO, City University of Hong Kong, China
Paola PRETE, University of Salento, Italy
Nicola SERIANI, International Center Theoretical Physics, Italy
Members:
Mark ASTA, University of California, Berkeley, USA
Annalisa BRUNO, Nanyang Technological University, Singapore
Montserrat CASAS-CABANAS, CIC EnergiGUNE, Spain
Alessio FILIPPETTI, CNR-IOM and University of Cagliari, Italy
Laurence HARDWICK, The University of Liverpool, UK
Yuichi IKUHARA, The University of Tokyo, Japan
Karl LEO, TU Dresden, Germany
Michal LESKES, Weizmann Institute of Science, Israel
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
Neeraj SHARMA, University of New South Wales, Australia
Emmanuelle SUARD, Institut Laue-Langevin, France
Michael TONEY, University of Colorado at Boulder, USA
Matthias VANDICHEL, University of Limerick, Ireland
Christopher M. WOLVERTON, Northwestern University, USA
Shijun ZHAO, City University of Hong Kong, China
Alexander BAGGER, Danish Technical University, Denmark
Ernst BAUER, Vienna University of Technology, Austria
Pieremanuele CANEPA, University of Houston, USA
Sara CAVALIERE, CNRS-UM-ENSCM, France
Jim CHELIKOWSKY, University of Texas at Austin, USA
Paul ERHART, Chalmers University of Technology, Sweden
Yi GAO, Shanghai Advanced Research Institute, CAS, China
Mirco GROSSE, KIT, Germany
Rongying JIN, University of South Carolina, USA
Hyun Sik KIM, University of Seoul, South Korea
Heather J. KULIK, MIT, USA
Arun Kumar MANNODI KANAKKITHODI, Purdue University, USA
Claudio MELIS, University of Cagliari, Italy
Dario NARDUCCI, University of Milano Bicocca, Italy
Johnpierre PAGLIONE, University of Maryland, USA
Krzysztof PIELICHOWSKI, Cracow University of Technology, Poland
Rampi RAMPRASAD, Georgia Institute of Technology, USA
Donald SIEGEL, University of Texas at Austin, USA
Lorenzo STIEVANO, Université de Montpellier, France
Peizhe TANG, Beihang University, China
Steven TORRISI, Toyota Research Institute, USA
Andrea TRAVERSO / Alessandro LEVERATTO, CNR-SPIN, Italy
Christopher M. WOLVERTON, Northwestern University, USA
Ernst BAUER, Vienna University of Technology, Austria
Pieremanuele CANEPA, University of Houston, USA
Sara CAVALIERE, CNRS-UM-ENSCM, France
Jim CHELIKOWSKY, University of Texas at Austin, USA
Paul ERHART, Chalmers University of Technology, Sweden
Yi GAO, Shanghai Advanced Research Institute, CAS, China
Mirco GROSSE, KIT, Germany
Rongying JIN, University of South Carolina, USA
Hyun Sik KIM, University of Seoul, South Korea
Heather J. KULIK, MIT, USA
Arun Kumar MANNODI KANAKKITHODI, Purdue University, USA
Claudio MELIS, University of Cagliari, Italy
Dario NARDUCCI, University of Milano Bicocca, Italy
Johnpierre PAGLIONE, University of Maryland, USA
Krzysztof PIELICHOWSKI, Cracow University of Technology, Poland
Rampi RAMPRASAD, Georgia Institute of Technology, USA
Donald SIEGEL, University of Texas at Austin, USA
Lorenzo STIEVANO, Université de Montpellier, France
Peizhe TANG, Beihang University, China
Steven TORRISI, Toyota Research Institute, USA
Andrea TRAVERSO / Alessandro LEVERATTO, CNR-SPIN, Italy
Christopher M. WOLVERTON, Northwestern University, USA
Advances in energy technologies critically depend on the availability of novel functional materials (dielectrics, semiconductors, ion conductors, catalysts, absorbents, structural materials, nuclear fuels, etc.) whose properties are optimized and tailored to a specific task by the use of appropriate characterization and computational-aided design strategies.
The broad range of microscopy, spectroscopy, spectrometry and other advanced characterization techniques now available, the use of machine learning, of automated experimentation as well as of the time-dependent data obtained from In-Situ/Operando methods allows obtaining useful information, down to the atomic scale, of composition, morphology, structure and on the variety of chemical and physical dynamic processes involved inside a material, at its surface and interfaces, so to create a path to accelerate their implementation in selected areas of energy technologies. The combination of different advanced techniques, providing a feedback loop between device design and performance optimization, gives rise to new insights in the field, where a multi-physics/multiscale approach may be an essential synergy tool.
Indeed computational materials science has demonstrated its power in modelling structure and functional properties of real materials, and in predicting novel materials with improved performances.
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.
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, are particularly appreciated.
The broad range of microscopy, spectroscopy, spectrometry and other advanced characterization techniques now available, the use of machine learning, of automated experimentation as well as of the time-dependent data obtained from In-Situ/Operando methods allows obtaining useful information, down to the atomic scale, of composition, morphology, structure and on the variety of chemical and physical dynamic processes involved inside a material, at its surface and interfaces, so to create a path to accelerate their implementation in selected areas of energy technologies. The combination of different advanced techniques, providing a feedback loop between device design and performance optimization, gives rise to new insights in the field, where a multi-physics/multiscale approach may be an essential synergy tool.
Indeed computational materials science has demonstrated its power in modelling structure and functional properties of real materials, and in predicting novel materials with improved performances.
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.
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, are particularly appreciated.
Session Topics
FA-1 Computational-aided energy materials design
FA-2 Advanced characterization of energy materials
FA-3 Data science and artificial intelligence for materials development