Computation Webinar | Energy and Advanced Computing in the Age of Machine Learning: From Quantum to Grid
Welcome from the Chair
3rd Computation Webinar
Energy and Advanced Computing in the Age of Machine Learning: From Quantum to Grid
This two-day webinar brings together recent advances in computational methods, machine learning, and materials science, highlighting how modern simulation and data-driven approaches are transforming the understanding and design of complex systems.
Day 1 focuses on methodological and computational innovations. Topics include Monte Carlo entropic sampling applied to spin crossover nanoparticles to understand their thermodynamic behavior at the nanoscale, the development and fine-tuning of MACE foundation machine learning interatomic potentials for accurate and transferable atomistic modeling, and emerging approaches to improving productivity in high-performance computing through the integration of large language models and modern programming paradigms.
Day 2 shifts toward applications in energy storage, manufacturing, and next-generation computing materials. Presentations will cover digital twin frameworks for modeling battery manufacturing processes, computational studies of energy storage materials and interfacial phenomena, and redox-mediated electronic transport in metal–organic frameworks for neuromorphic computing. The program will also feature experimental and electrochemical work on the synthesis and characterization of sodium thiophosphate catholytes for nonaqueous redox flow batteries.
Together, the sessions provide a cohesive perspective on how advanced algorithms, machine learning, and multiscale modeling are accelerating discovery and enabling new functionalities across materials for energy, electronics, and intelligent systems.
Date: 31 March 2026 - 1 April 2026
Time: 4:30 p.m. CEST | 10:30 a.m. EDT
Webinar ID: 854 8999 0073
Webinar Secretariat: journal.webinar@mdpi.com
Event Chair
Department of Chemical Engineering, Texas A&M University, United States
Dr. Galvez holds an international academic background spanning Peru, the United States, and France. He earned his PhD in Electrical Engineering from Texas A&M University. He then completed postdoctoral training at LRCS (Laboratoire de Réactivité et de Chimie des Solides) in France and currently serve as a postdoctoral researcher in the Chemical Engineering Department at Texas A&M. His expertise centers on atomistic simulations of electrode–electrolyte interfaces, computational materials science, and machine learning–driven predictive modeling. His work integrates physics-based simulations with data-driven approaches to understand and accelerate the design of advanced materials, particularly for energy and electrochemical systems.
Speakers (Day 1) — 31 Mar 2026
Computational Science Division, Argonne National Laboratory, USA
MACE Foundation Machine Learning Interatomic Potentials: Performance, Application, and Fine Tuning
Dr. Bhuiyan is a postdoctoral researcher in Argonne National Laboratory’s Computational Science Division and a computational materials scientist who combines density functional theory, molecular dynamics, and machine learning to provide atomistic insight that complements experimental results. His research focuses on developing machine-learning interatomic force fields and predictive models such as graph neural networks to enable accurate, high-throughput simulations of complex materials and chemical systems, including tribochemical reactions, molten salts, electrolytes, and transition-metal containing compounds, on large-scale supercomputers. Dr. Bhuiyan earned his Ph.D. in Mechanical Engineering from the University of California, Merced (2024), and his work has been recognized with the Nor-Cal STLE Research Scholarship (2020), the Graduate Dean’s Dissertation Fellowship (2024), and a Scientific Reports “Top 100 in Materials Science” paper (2024).
Oak Ridge National Laboratory, Computer Science and Mathematics Division, USA
ORNL Research in High-Productivity for HPC Software: LLMs and Programming Languages
William F. Godoy is a Senior Computer Scientist in the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) since 2016. His research interests are in the areas of high-performance computing (HPC), AI for scientific software, programming models, and workflows. At ORNL, William has contributed to several projects for the US Department of Energy HPC scientific mission. Prior experiences include a staff position at Intel Corporation and a postdoctoral fellowship at NASA Langley. He obtained his PhD and MSc from the University at Buffalo, and a BSc from the National Engineering University (UNI) Lima, Peru, all in mechanical engineering. He has published more than 60 papers in computational and computer science venues. William is a IEEE Senior member and ACM member currently serving in several conference venues.
Monte Carlo Entropic Sampling Algorithm Applied To Spin Crossover Nanoparticles
Jorge LINARES, born in Chepén (PERU), was a full Professor at the Pontificia Universidad Catolica del Peru, Associate Professor at the Université Pierre et Marie Curie (Paris-Sorbonne) and, since 1995, a full Professor in Versailles’s University (now Paris-Saclay). He is solid state physicist and an expert in phase transitions in molecular solids and applications of MonteCarlo techniques in bistables crystals. He is member of the National Academy of Science of Peru. He has published more than 182 papers with an h-index of 43 in Google Scholar.
Universidad Nacional de Córdoba, Facultad de Ciencias Químicas, Departamento de Química Teórica y Computacional, Córdoba, Argentina,
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Instituto de Investigaciones en Fisicoquímica de Córdoba (INFIQC), Córdoba, Argentina
Integrating Modeling and Experiment for Next-Generation Lithium Metal Batteries
Dr. Guillermina L. Luque received her degree in Chemistry in 2003 and her PhD in 2009 from the National University of Córdoba (Argentina). She is currently a researcher at INFIQC-CONICET and a faculty member in the Department of Theoretical and Computational Chemistry at the Faculty of Chemical Sciences, National University of Córdoba. She has authored over 50 publications in high-impact international journals. Her research interests include the experimental and computational study of lithium-ion and next-generation post-lithium battery technologies.
Speakers (Day 2) — 1 Apr 2026
Université de Picardie Jules Verne, Amiens, France,
University of Washington, Seattle, USA
Digital Twin on Battery Manufacturing Modelling
Prof. Dr. Alejandro A. Franco is a Full Professor at the Université de Picardie Jules Verne(Amiens, France) and an Honorary Member of the Institut Universitaire de France. Prof. Franco is recipient of two ERC grants (ARTIS-TIC and SMARTISTIC projects) focusing on battery manufacturing digitalization. In 2019,he was honored with the French Prize for Pedagogy Innovation for his utilization of Virtual Reality in teaching battery sciences. He is the recipient of the 2024 Battery Division M. Stanley Whittingham Mid-Career Award of the Electrochemical Society (ECS). He coordinates the Erasmus + i-MESC (Interdisciplinarity in Materials for Energy Storage and Conversion) International MSc. Programme.
Redox-Mediated Electronic Transport in Metal-Organic Frameworks for Neuromorphic Computing
Alejandro Aviles Sanchez is a postdoctoral researcher in the Department of Chemical Engineering at Texas A&M University under the supervision of Prof. Perla Balbuena. He obtained his Ph.D. in Theoretical Chemistry, and his research focuses on first-principles modeling of redox-active materials for energy and neuromorphic applications. His work combines density functional theory (DFT), constrained DFT, ab initio molecular dynamics, and machine-learning force fields (MLFF) to study ion–electron coupling, charge transport, and structural reorganization in metal–organic frameworks, conjugated polymers, and transition-metal oxides. He is a member of reMIND (Reconfigurable Electronic Materials Inspired by Nonlinear Neuron Dynamics), a U.S. Department of Energy Frontier Research Center.
In Situ 3D Ed and 4S-Stem Tomography To Follow Structural Evolutions
Joke Hadermann is full professor at the University of Antwerp, within the laboratory EMAT, Electron Microscopy for Materials Science. While first focussed on atomic resolution imaging and spectroscopy, Joke drifted via precession electron diffraction to 3D ED. Currently, she is focussed on combining 3D ED with different in situ experiments and on optimizing the new technique of 4D-STEM tomography to be able to determine the crystal structure of each phase in multiphased materials as from single crystal data. For performing this research, she was awarded a prestigious Advanced ERC Grant, REACT. Further, her research involves the structure determination of a wide variety of inorganic materials, including, but not restricted to, perovskites, battery materials, solid oxide fuel cell electrodes and MOFs.
Computational Modeling of Energy Storage Materials and Interfacial Phenomena
Prof. Selis Vasquez holds a Bachelor of Science with a specialization in Electronic Engineering from the National University of Engineering and a Master of Science in Electrical Engineering from Texas A&M University. He specialize in computational chemistry and currently study lithium batteries using computational techniques such as molecular dynamics simulations, data science, and artificial intelligence.
Registration
This is a FREE webinar. After registering, you will receive a confirmation email containing information on how to join the webinar. Registrations with academic institutional email addresses will be prioritized.
Certificates of attendance will be delivered to those who attend the live webinar.
Can’t attend? Register anyway and we’ll let you know when the recording is available to watch.
Program (Day 1) — 31 Mar 2026
|
Speaker |
Presentation Title |
Time in CEST |
Time in EDT |
|
Dr. Diego Eduardo Galvez-Aranda |
Chair Introduction |
4:30 - 4:35 pm |
10:30 - 10:35 am |
|
Dr. Fakhrul Hasan Bhuiyan |
MACE Foundation Machine Learning Interatomic Potentials: Performance, Application, and Fine Tuning |
4:35 - 5:05 pm |
10:35 - 11:05 am |
|
Dr. Fakhrul Hasan Bhuiyan |
Q&A |
5:05 - 5:10 pm |
11:05 - 11:10 am |
| Dr. William F. Godoy | ORNL Research in High-Productivity for HPC Software: LLMs and Programming Language |
5:10 - 5:40 pm |
11:10 - 11:40 am |
|
Dr. William F. Godoy |
Q&A |
5:40 - 5:45 pm |
11:40 - 11:45 am |
|
Prof. Jorge Linares |
Monte Carlo Entropic Sampling Algorithm Applied To Spin Crossover Nanoparticle |
5:45 - 6:15 pm |
11:45 - 12:15 pm |
|
Prof. Jorge Linares |
Q&A |
6:15 - 6:20 pm |
12:15 - 12:20 pm |
|
Dr. Guillermina L. Luque |
Integrating Modeling and Experiment for Next-Generation Lithium Metal Batteries |
6:20 - 6:50 pm |
12:20 - 12:50 pm |
|
Dr. Guillermina L. Luque |
Q&A |
6:50 - 6:55 pm |
12:50 - 12:55 pm |
|
Dr. Diego Eduardo Galvez-Aranda |
Closing of Webinar Day 1 |
6:55 - 7:00 pm |
12:55 - 1:00 pm |
Program (Day 2) — 1 Apr 2026
|
Speaker |
Presentation Title |
Time in CEST |
Time in EDT |
|
Dr. Diego Eduardo Galvez-Aranda |
Chair Introduction |
4:30 - 4:35 pm |
10:30 - 10:35 am |
|
Prof. Dr. Alejandro A. Franco |
Digital Twin on Battery Manufacturing Modelling |
4:35 - 5:05 pm |
10:35 - 11:05 am |
|
Prof. Dr. Alejandro A. Franco |
Q&A |
5:05 - 5:10 pm |
11:05 - 11:10 am |
| Dr. Alejandro Aviles Sanchez | Redox-Mediated Electronic Transport in Metal-Organic Frameworks for Neuromorphic Computing |
5:10 - 5:40 pm |
11:10 - 11:40 am |
|
Dr. Alejandro Aviles Sanchez |
Q&A |
5:40 - 5:45 pm |
11:40 - 11:45 am |
|
Prof. Dr. Joke Hadermann |
In Situ 3D Ed and 4S-Stem Tomography To Follow Structural Evolutions |
5:45 - 6:15 pm |
11:45 - 12:15 pm |
|
Prof. Dr. Joke Hadermann |
Q&A |
6:15 - 6:20 pm |
12:15 - 12:20 pm |
|
Prof. Luis Antonio Selis Vasquez |
Computational Modeling of Energy Storage Materials and Interfacial Phenomena |
6:20 - 6:50 pm |
12:20 - 12:50 pm |
|
Prof. Luis Antonio Selis Vasquez |
Q&A |
6:50 - 6:55 pm |
12:50 - 12:55 pm |
|
Dr. Diego Eduardo Galvez-Aranda |
Closing of Day 2 |
6:55 - 7:00 pm |
12:55 - 1:00 pm |
Relevant Special Issue
"Energy and Advanced Computing in the Age of Machine Learning: From Quantum to Grid"
Guest Editor: Dr. Diego E. Galvez-Aranda
Deadline for submission: 15 December 2026
Sponsors and Partners
Organizers
