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Meeting 2025 TMS Annual Meeting & Exhibition
Symposium Innovations in Energy Materials: Unveiling Future Possibilities of Computational Modelling and Atomically Controlled Experiments
Presentation Title A Journey from Atoms to Materials: Designing Functional Materials for Energy and Microelectronics
Author(s) Prashun Gorai
On-Site Speaker (Planned) Prashun Gorai
Abstract Scope Technological developments often rely on specifically designed materials and molecules. The increasing pace of technology development, coupled with rising energy needs and climate challenges, requires faster approaches for materials discovery. Historically, materials have been discovered by trial-and-error approaches that rely on chemical intuition. Designing materials with tailored properties is challenging because of the astronomical number of possible compounds and structures, and materials behaviors that do not adhere to standard chemical intuition. In this talk, I will share examples from our work on the computational discovery and design of functional materials, specifically focusing on ferroelectrics and solid-state energy storage. We employ first-principles computations and machine learning in close collaboration with experiments to discover novel materials and generate new materials design principles, with the goal to accelerate materials discovery and guide experimental realization.
Proceedings Inclusion? Planned:
Keywords Computational Materials Science & Engineering, Machine Learning, Energy Conversion and Storage

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

A Journey from Atoms to Materials: Designing Functional Materials for Energy and Microelectronics
Ab initio calculations of the thermoelectric figure of merit
Beyond the Linear Scaling Relation: Novel Strategies
Body heat harvester based on thermoelectrics for continuous operation of sensors and actuators
Bragg coherent x-ray diffraction imaging of strain in energy materials
Coordination Engineering in Nanomaterials Design for Energy Applications
Design of eco-friendly and high-efficiency thermo-photoelectric conversion materials
Development of kinetic lattice Monte Carlo model to study ionic diffusion at misfit dislocations in oxide heterostructures
Exploring Ultra-Stable Green Rust Compositions for Green Energy Catalysis
From Prediction to Experimental Realization of Ferroelectric Wurtzite AlN-Based Alloys
High-performance electronic structure calculations in the exascale era
Local Thermal Conductivity Imaging and Modelling to Guide Microstructure Engineering in Energy Materials
Machine Learned Multiphysics Modeling: Enhancing Uniform Distribution of Low-Energy Lithium-Ion Transport Channels in Solid Electrolyte Interphase of Electrodes
Magnetic Metasurfaces for sustainable Information and Communication technologies
Multiphasic model of Solid Electrolyte Interface formation in Lithium-ion batteries
Nanomaterial and nanostructure physics for thermoelectric performance enhancement
Nanoscale design of 3D anode and high effective catalysis for high performance Aluminum-air batteries
Optimization of CO2 Reduction Reaction Using Nanoporous Copper Catalysts through Machine Learning-Driven Process Parameter Modeling
Quantum-Assisted Machine Learning Analysis of Silicon-Based Anodes for Lithium Batteries: Thermodynamics, Structural Insights, and Lithium Diffusion. Identifying Challenges and Exploring Novel Candidates
Reaching new frontiers to for superconductors using pulsed high magnetic fields
Resonant Ultrasound Spectroscopy for Rapid Down Selection, Elastic Property Determination, and Model Validation in High-Entropy Materials
Role of ‘sustainability’ in computational materials development for alternate energy technologies
Specialized Machine Learning Interatomic Potential to assess Self-Healing at a W Grain Boundary
Starrydata2: an Open Platform for Materials Data Curated from Literature
Structure Low Dimensionality and Lone-Pair Stereochemical Activity: the Key to Low Thermal Conductivity in sulfides
The Exploration of FeNiMoW-based alloys for High Value Magnetic Materials
The magic and myths of Machine Learning in Materials Science
Two-dimensional oxides: structural modulation and energy storage applications
Understanding the role of surface hydrogens in the hydrogenolysis of plastic waste catalysed by ruthenium nanoparticles
Unraveling the Effects of Dislocations on Ferroelectric Behavior by Molecular Dynamics Simulations
Ab Initio Models for the Prediction of Corrosion-Passivation Behavior in Aqueous Media

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