Italy
Hydrogen Strategies Under Uncertainty: Risk-Averse Choices for Green Hydrogen Pathways
Oct 2025
Publication
The last decade has been characterized by a growing environmental awareness and the rise of climate change concerns. Continuous advancement of renewable energy technologies in this context has taken a central stage on the global agenda leading to a diverse array of innovations ranging from cutting-edge green energy production technologies to advanced energy storage solutions. In this evolving context ensuring the sustainability of energy systems—through the reduction of carbon emissions enhancement of energy resilience and responsible resource integration—has become a primary objective of modern energy planning. The integration of hydrogen technologies for power-to-gas (P2G) and power-topower (P2P) and energy storage systems is one of the areas where the most remarkable progress is being made. However real case implementations are lagging behind expectations due to large-scale investments needed which under high energy price uncertainty act as a barrier to widespread adoption. This study proposes a risk-averse approach for sizing an Integrated Hybrid Energy System considering the uncertainty of electricity and gas prices. The problem is formulated as a mixed-integer program and tested on a real-world case study. The analysis sheds light on the value of synergies and innovative solutions that hold the promise of a cleaner more sustainable future for generations to come.
Application of Machine Learning and Data Augmentation Algorithms in the Discovery of Metal Hydrides for Hydrogen Storage
Nov 2025
Publication
The development of efficient and sustainable hydrogen storage materials is a key challenge for realizing hydrogen as a clean and flexible energy carrier. Among various options metal hydrides offer high volumetric storage density and operational safety yet their application is limited by thermodynamic kinetic and compositional constraints. In this work we investigate the potential of machine learning (ML) to predict key thermodynamic properties—equilibrium plateau pressure enthalpy and entropy of hydride formation—based solely on alloy composition using Magpie-generated descriptors. We significantly expand an existing experimental dataset from ~400 to 806 entries and assess the impact of dataset size and data augmentation using the PADRE algorithm on model performance. Models including Support Vector Machines and Gradient Boosted Random Forests were trained and optimized via grid search and cross-validation. Results show a marked improvement in predictive accuracy with increased dataset size while data augmentation benefits are limited to smaller datasets and do not improve accuracy in underrepresented pressure regimes. Furthermore clustering and cross-validation analyses highlight the limited generalizability of models across different material classes though high accuracy is achieved when training and testing within a single hydride family (e.g. AB2). The study demonstrates the viability and limitations of ML for accelerating hydride discovery emphasizing the importance of dataset diversity and representation for robust property prediction.
Decarbonising Sustainable Aviation Fuel (SAF) Pathways: Emerging Perspectives on Hydrogen Integration
Oct 2025
Publication
The growing demand for air connectivity coupled with the forecasted increase in passengers by 2040 implies an exigency in the aviation sector to adopt sustainable approaches for net zero emission by 2050. Sustainable Aviation Fuel (SAF) is currently the most promising short-term solution; however ensuring its overall sustainability depends on reducing the life cycle carbon footprints. A key challenge prevails in hydrogen usage as a reactant for the approved ASTM routes of SAF. The processing conversion and refinement of feed entailing hydrodeoxygenation (HDO) decarboxylation hydrogenation isomerisation and hydrocracking requires substantial hydrogen input. This hydrogen is sourced either in situ or ex situ with the supply chain encompassing renewables or non-renewables origins. Addressing this hydrogen usage and recognising the emission implications thereof has therefore become a novel research priority. Aside from the preferred adoption of renewable water electrolysis to generate hydrogen other promising pathways encompass hydrothermal gasification biomass gasification (with or without carbon capture) and biomethane with steam methane reforming (with or without carbon capture) owing to the lower greenhouse emissions the convincing status of the technology readiness level and the lower acidification potential. Equally imperative are measures for reducing hydrogen demand in SAF pathways. Strategies involve identifying the appropriate catalyst (monometallic and bimetallic sulphide catalyst) increasing the catalyst life in the deoxygenation process deploying low-cost iso-propanol (hydrogen donor) developing the aerobic fermentation of sugar to 14 dimethyl cyclooctane with the intermediate formation of isoprene and advancing aqueous phase reforming or single-stage hydro processing. Other supportive alternatives include implementing the catalytic and co-pyrolysis of waste oil with solid feedstocks and selecting highly saturated feedstock. Thus future progress demands coordinated innovation and research endeavours to bolster the seamless integration of the cutting-edge hydrogen production processes with the SAF infrastructure. Rigorous technoeconomic and life cycle assessments alongside technological breakthroughs and biomass characterisation are indispensable for ensuring scalability and sustainability
No more items...