Computational Physics, Artificial Intelligence, and Digital Technologies for Sustainability, Book: Emerging Trends in Physics for Sustainable Development

Computational physics provides a bridge between fundamental physical laws, mathematical modelling, numerical methods, experimental observations, and real-world technological systems. With increasing availability of computational power and environmental data, computational methods are becoming central to the design, prediction, optimization, and management of sustainable technologies. This chapter examines the foundations of computational physics, including numerical methods, simulation, optimization, high-performance computing, data-driven modelling, and uncertainty analysis. It then explores artificial intelligence and machine learning for
materials discovery, renewable-energy forecasting, energy-system optimization, climate modelling,
environmental monitoring, battery management, and smart infrastructure. Digital technologies including digital
twins, Internet-of-Things systems, edge computing, cloud computing, and advanced visualization are discussed
as tools for connecting physical systems with real-time data. Particular attention is given to the energy and resource requirements of computation itself and to approaches for developing energy-efficient digital infrastructure. The chapter also considers physics-informed artificial intelligence, explainable models, cybersecurity, data quality, and lifecycle sustainability. The objective is to demonstrate how computational physics and digital technologies can support efficient resource use, scientific discovery, resilient infrastructure, and sustainable development.