The global shift towards carbon neutrality demands innovative approaches that combine geochemistry, data science, and circular resource utilization. Geochemical processes govern key technologies such as CO₂ sequestration, hydrogen storage, and the development of sustainable materials, yet their complexity requires advanced predictive tools. Data-driven modeling and machine learning now offer powerful ways to analyze multiscale geochemical reactions, enhance accuracy, and optimize energy storage. Meanwhile, circular geochemistry promotes the valorization of industrial by products into reactive materials for CCUS. Integrating these two paradigms enables more sustainable and efficient energy systems. This Research Topic aims to highlight recent advances in data driven geochemistry, modeling and waste utilization that support global energy transition.
The goal of this Research Topic is to advance scientific understanding and technological innovation at the intersection of geochemistry, data-driven modeling, and circular resource utilization. It seeks to promote research that leverages geochemical principles, machine learning, and waste valorization to develop sustainable solutions for CO₂ and H₂ storage, mineral carbonation, and clean energy systems. By integrating experimental, modeling, and data-centric approaches, this issue to provide new insights into geochemical mechanisms, predictive modeling frameworks, and material reuse strategies that enhance the safety, efficiency, and environmental sustainability of energy storage technologies.
This Research Topic focuses on integrating data-driven geochemistry and circular resource utilization to enable sustainable and efficient energy storage systems. It welcomes contributions exploring geochemical mechanisms, predictive modeling, and waste valorization strategies related to CO₂ sequestration, hydrogen storage, mineral carbonation, and low-carbon material development.
Authors are invited to submit original research articles, comprehensive reviews, short communications, and perspective papers that advance the understanding and application of geochemistry in clean energy storage and circular economy systems. Interdisciplinary studies combining geochemistry, data science, materials engineering, and environmental sustainability are particularly encouraged.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
Hypothesis and Theory
Methods
Mini Review
Opinion
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
Hypothesis and Theory
Methods
Mini Review
Opinion
Original Research
Perspective
Review
Technology and Code
Keywords: Geochemistry, Machine Learning, CO₂ Storage, Hydrogen Storage, Waste Valorization, Mineral Carbonation, Geopolymers, Circular Economy, Reactive Transport Modeling, Energy Transition
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
