A curriculum built at the frontier of clean-energy science and engineering.

The chemical foundations of clean energy — atomic structure, bonding, states of matter, and introductory organic and solid-state chemistry, with the spectroscopy used to characterise energy-relevant materials.

Single- and multivariable calculus for engineers: limits and continuity, differentiation and integration, sequences and Taylor series, partial derivatives, gradients and optimisation with Lagrange multipliers.

Core physics for energy study — classical mechanics, work and energy, electrostatics and circuits, and an introduction to magnetism and electromagnetic induction, taught through applied problem-solving.

Algorithmic thinking and scientific computing in Python, with hands-on labs in NumPy, Pandas, Matplotlib and Jupyter to analyse data, visualise results and simulate scientific systems.

The foundation of engineering analysis: free-body diagrams, equilibrium, internal forces and friction, then stress, strain and elasticity to understand how materials deform under load.

Thermodynamics, phase and chemical equilibria, electrolytes and introductory electrochemistry, plus kinetics and catalysis central to combustion, electrolysis and hydrogen production, with laboratory diagnostics.

Matrices, linear systems, vector spaces, orthogonality and eigenvalue problems, with numerical implementation and applications to regression, simulation and optimisation in energy systems.

A survey of the whole energy landscape — fossil fuels, nuclear, hydro, solar, wind, biomass, geothermal and marine — plus storage, system integration, and the economics and policy of the transition.

Probability and statistics for data analysis: descriptive statistics and distributions, the central limit theorem, estimation and confidence intervals, hypothesis testing, and introductory linear regression.

Data science and machine learning for energy problems — cleaning and visualising data, regression and classification, time-series forecasting, clustering, PCA and an introduction to neural networks.

A unified introduction to the three pillars of energy technology: thermodynamics (first and second laws), fluid mechanics (continuity, Bernoulli, momentum) and heat transfer by conduction, convection and radiation.

The materials paradigm — bonding, crystal structures and defects, phase diagrams, mechanical and functional properties, processing routes, and materials selection with sustainability in mind.

Mathematical modelling and simulation of energy processes — mass and energy balances, unit operations, heat-exchanger networks and pinch analysis — using ASPEN Plus and GAMS for simulation and optimisation.

Systematic design methodology applied to energy-conversion systems such as turbines, pressure vessels and solar panels, integrating performance, material selection, optimisation and life-cycle thinking.

Principles and technologies of batteries, supercapacitors and introductory fuel cells — electrode reactions, ion transport and major chemistries — with hands-on electrochemical characterisation in the lab.

Atomistic modelling of energy materials with open-source tools (LAMMPS, ASE) and Python — molecular dynamics and Monte Carlo methods applied to hydrogen storage, battery alloys and thermoelectrics.

DC and AC circuit analysis, power factor and grid stability, then semiconductor devices — diodes, transistors as switches and operational amplifiers for sensing and signal conditioning in energy systems.

Cell structure, metabolism, enzymes and genetics, with molecular techniques and applications spanning microbial, plant and waste biotechnology, bioremediation and sustainable resource recovery.

Circular-economy and environmental-economics principles, the UN SDGs and ESG criteria, key EU directives (CSRD, SEVESO) and Life Cycle Assessment, applied through real sustainability case studies.

Magnetic circuits and the theory and operation of transformers, DC machines, induction and synchronous motors and generators, and permanent-magnet drives with their control.

Combustion thermodynamics and kinetics, reactor types and flame structure, conventional and alternative fuels (biofuels, biomethane, hydrogen, ammonia), and the formation and control of pollutants.

Bioprocess engineering for clean energy — biomass feedstocks and pretreatment, bioreactor design, anaerobic digestion and biomethane, biohydrogen, microbial fuel cells and integrated biorefineries.

Electronic-structure methods for energy materials — running calculations via WebMO on the university HPC to interpret bonding, HOMO–LUMO gaps and reactivity in batteries, catalysts and photovoltaics.

Engineering ethics, codes of conduct and accountability (including responsible AI use), plus technical writing, presentation and publication skills, culminating in a technical report and oral defence.

Design and sizing of renewable systems — solar thermal and photovoltaic, wind, geothermal, hydroelectric and ocean energy — alongside energy storage and heat pumps.

Reaction kinetics and reactor design, then physical separation processes (membranes, distillation, adsorption), applied to renewable biofuels and the integrated biorefinery concept.

Environmental Impact Assessment and management systems (ISO 14001/50001), assessing pollutants, waste and environmental risk across the energy–environment interface through real case studies.