United States
A Review and Inventory of U.S. Hydrogen Emissions for Production, Distribution and Storage
Nov 2025
Publication
In response to the growing global interest in hydrogen as an energy carrier this study provides the first attempt to develop a baseline inventory of U.S. hydrogen emissions from production distribution and storage. The scope of this study was limited to pure hydrogen emissions and excludes emissions from low purity hydrogen streams and carriers. A detailed literature search was conducted utilizing various greenhouse gas emissions inventory protocol principles and guidelines to consolidate a list of activity data and emission factors. The best available activity data and emission factors were then selected via a Multi-Criteria-Based Decision Making Method named Technique for Order Preference by Similarity to Ideal Solution or modelled using best-engineering estimates. The study estimated total U.S. hydrogen emissions of 0.063 MMTA with emission bounds ranging from 0.02 to 0.11 MMTA. Given the total estimated H2 production capacity of 7.97 MMTA the study estimates a total U.S. hydrogen emission rate for production distribution and storage of 0.79% (0.26%–1.32%). To reduce the uncertainty in the estimated total hydrogen emissions future work should be conducted to measure facility-level hydrogen emission factors across multiple sectors. The inventory framework developed in this study can serve as a living document that can be updated and enhanced as more empirical data is obtained. This study also provides detailed insights regarding key emission or leakage sources and causes from each supply chain stage. The insights and conclusions from this study can provide direction for hydrogen production companies and safety professionals as they develop hydrogen emission mitigation measures and controls.
Hybrid Renewable Energy Systems for Off-Grid Electrification: A Comprehensive Review of Storage Technologies, Metaheuristic Optimization Approaches and Key Challenges
Nov 2025
Publication
Hybrid Renewable Energy Systems (HRESs) are a practical solution for providing reliable low-carbon electricity to off-grid and remote communities. This review examines the role of energy storage within HRESs by systematically comparing electrochemical mechanical thermal and hydrogen-based technologies in terms of technical performance lifecycle cost operational constraints and environmental impact. We synthesize findings from implemented off-grid projects across multiple countries to evaluate real-world performance metrics including renewable fraction expected energy not supplied (EENS) lifecycle cost and operation & maintenance burdens. Special attention is given to the emerging role of hydrogen as a long-term and cross-sector energy carrier addressing its technical regulatory and financial barriers to widespread deployment. In addition the paper reviews real-world implementations of off-grid HRES in various countries summarizing practical outcomes and lessons for system design and policy. The discussion also includes recent advances in metaheuristic optimization algorithms which have improved planning efficiency system reliability and cost-effectiveness. By combining technological operational and policy perspectives this review identifies current challenges and future directions for developing sustainable resilient and economically viable HRES that can accelerate equitable electrification in remote areas. Finally the review outlines key limitations and future directions calling for more systematic quantitative studies long-term field validation of emerging technologies and the development of intelligent Artificial Intelligence (AI)-driven energy management systems within broader socio-techno-economic frameworks. Overall this work offers concise insights to guide researchers and policymakers in advancing the practical deployment of sustainable and resilient HRES.
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.
Material Compatibility in Hydrogen Infrastructure: Challenges, Advances, and Future Prospects
Oct 2025
Publication
The adoption of hydrogen as a clean energy carrier depends heavily on the development of materials capable of enduring the extreme conditions associated with its production storage and transportation. This review critically evaluates the performance of metals polymers and composites in hydrogen-rich environments focusing on degradation mechanisms such as hydrogen embrittlement rapid gas decompression and long-term fatigue. Metals like carbon steels and high-strength alloys can experience a 30–50 % loss in tensile strength due to hydrogen exposure while polymers suffer from permeability increases and sealing degradation. Composite materials though strong and lightweight may lose up to 15 % of their mechanical properties over time in hydrogen environments. The review highlights current mitigation strategies including hydrogen-resistant alloys polymer blends protective coatings composite liners and emerging technologies like predictive modeling and AI-based material design. With hydrogen production expected to reach 500 GW globally by 2030 improving material compatibility and developing international standards are essential for scaling hydrogen infrastructure safely and cost-effectively. This work presents an integrated analysis of material degradation mechanisms highlights key challenges across metals polymers and composites in hydrogen environments and explores recent innovations and future strategies to enhance durability and performance in hydrogen infrastructure.
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