gxceed
GX Research Hub · English

GX & Decarbonization Research

This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.

The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.

Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.

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Topic: #Hydrogen (clear)

Showing 301–320 of 754 papers

🌍 Global📚 Peer-reviewed · JournalJoule2024#HydrogenDOI

On the cost competitiveness of blue and green hydrogen

Ueckerdt F.

This paper analyzes the cost competitiveness of blue hydrogen (produced from natural gas with carbon capture and storage) and green hydrogen (produced via electrolysis using renewable energy). It examines key cost drivers and the impact of …

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📚 Peer-reviewed · JournalRenewable and Sustainable Energy Reviews2026#HydrogenDOI

Synergistic integration of green hydrogen in renewable power systems: A comprehensive review of key technologies, research landscape, and future perspectives

Jia W.

This review systematically examines the integration of green hydrogen into renewable power systems, covering electrolysis, storage, and utilization technologies. It maps the research landscape and identifies future pathways for grid-scale d…

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📚 Peer-reviewed · JournalDianwang Jishu Power System Technology2026#HydrogenDOI

Optimal Source-Load-Storage Scheduling for Regional Integrated Energy Systems Considering a Joint Green Power-green Hydrogen Certificate Trading Mechanism

Jinglei L.

This paper proposes an optimal source-load-storage scheduling model for regional integrated energy systems, considering a joint green power-green hydrogen certificate trading mechanism. It aims to improve economic and environmental performa…

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🌍 GlobalConference2026 International Conference on AI Innovations and Industry (ICAIII)2026#HydrogenDOI

Machine-Learning-Driven Operational Optimisation of Electrolyser-Based Hydrogen Production Using a Physics-Informed Digital Twin for UK Industrial Clusters

M. Tariq, Irfan Ahmed

This paper proposes an operational optimization framework for electrolyser-based hydrogen production by integrating a physics-informed digital twin with machine learning. Applied to UK industrial clusters, it demonstrates significant reduct…

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🇪🇺 Europe📚 Peer-reviewed · JournalInternational Journal of Hydrogen Energy2026#HydrogenDOI

Too soon, too late: An analysis of electrolyser supply and demand dynamics in Europe

Rui Gonçalves, Niels Gorm Malý Rytter, Yohanes Nugroho +1

This paper analyzes the imbalance between electrolyser manufacturing capacity and demand in Europe. It finds oversupply of 2.5 GW in 2025, but demand growth leads to undersupply after 2027, reaching a maximum gap of 17 GW by 2033. Long-term…

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