Litcius/Paper detail

Recent Advances in Hydrate-Based CO <sub>2</sub> Capture: Energy Consumption, Cost Analysis, Policy Perspectives, and Machine Learning-Driven Simulation of CO <sub>2</sub> Hydrate Formation

Manjusha Anipeddi, Bhajan Lal, Baldeep Singh

2025ACS Omega5 citationsDOIOpen Access PDF

Abstract

High Resolution Image Download MS PowerPoint Slide Gas hydrate-based carbon capture and storage (CCUS) technologies represent a promising approach to mitigating climate change by efficiently capturing and storing carbon dioxide (CO 2 ). This review examines the technical and economic aspects of gas hydrate-based CCUS, including the latest developments related to CO 2 hydrate formation studies. With special attention to flue gas decarbonization, this paper discusses the challenges faced and the focus areas that need improvement in advancing and scaling up hydrate-based CCUS. The review also provides a systematic approach to understanding the techno-economic aspects of CCUS plants and concisely discusses the technical opportunities and the associated cost dynamics within various CCUS technologies. The review also discusses the integration of hydrate-based capture with broader decarbonization strategies, underscoring the critical role of supportive policies and technological advancements in scaling up these solutions for global impact.

Topics & Concepts

Flue gasCarbon capture and storage (timeline)Clathrate hydrateEnvironmental scienceScalingProcess engineeringGreenhouse gasRisk analysis (engineering)Climate changeEnvironmental economicsComputer scienceCarbon fibersClimate policyFocus (optics)Systems engineeringEngineeringEmerging technologiesEnergy systemLead (geology)Global warmingBiochemical engineeringSystem integrationTechnical progressEnergy policyMacroEfficient energy useMethane Hydrates and Related PhenomenaCO2 Sequestration and Geologic InteractionsOffshore Engineering and Technologies
Recent Advances in Hydrate-Based CO <sub>2</sub> Capture: Energy Consumption, Cost Analysis, Policy Perspectives, and Machine Learning-Driven Simulation of CO <sub>2</sub> Hydrate Formation | Litcius