The scientific scope of AIDME-2026 centres on the application of digital modelling and artificial intelligence to energy science and engineering. The conference welcomes research employing physics-based, data-driven, and hybrid modelling, together with machine learning, scientific computing, and high-performance computing, to understand, predict, design, optimise, and manage energy materials, processes, technologies, and systems.
Applications may span the full energy value chain, including advanced materials for energy conversion and storage; chemical and process systems; batteries and other storage technologies; renewable and conventional energy systems; power generation, transmission, and distribution; subsurface energy resources; multiphase flow and transport in porous media; carbon capture, utilisation and storage; environmental monitoring and remediation; energy efficiency; and sustainable resource management. Contributions from chemical and process engineering, materials science, petroleum engineering, geosciences, environmental engineering, power and energy systems, computational physics, applied mathematics, computer science, and data science are welcome where they demonstrate a clear connection to energy research.
Both methodological advances and application-oriented studies are encouraged. Relevant topics include multiscale and multiphysics simulation, reduced-order and surrogate modelling, uncertainty quantification, interpretable and physics-informed artificial intelligence, optimisation, model validation, experimental–computational integration, and the coupling of physical models with research or operational data. Particular emphasis will be placed on scientifically rigorous approaches that improve physical understanding, predictive capability, computational efficiency, or decision-making in energy science and engineering.