Integrated modelling of CO2 plume geothermal energy systems in carbonate reservoirs: Technology, operations, economics and sustainability DOI

Abdulrasheed Ibrahim Yerima,

Haylay Tsegab,

Maman Hermana

et al.

Renewable Energy, Journal Year: 2024, Volume and Issue: 233, P. 121162 - 121162

Published: Aug. 10, 2024

Language: Английский

Carbon capture and utilisation (CCU) solutions: Assessing environmental, economic, and social impacts using a new integrated methodology DOI
Gabriella Maselli, Giuseppina Oliva, Antonio Nestıcò

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 948, P. 174873 - 174873

Published: July 20, 2024

Language: Английский

Citations

5

One-step synthesis of SO42−/ZrO2‑SEP solid-acid catalyst for energy-efficient CO2 capture DOI

Minhua Li,

Saeed Askari, Yingjie Niu

et al.

Separation and Purification Technology, Journal Year: 2024, Volume and Issue: 359, P. 130577 - 130577

Published: Nov. 16, 2024

Language: Английский

Citations

5

Machine Learning-Aided Inverse Design and Discovery of Novel Polymeric Materials for Membrane Separation DOI Creative Commons

Raghav Dangayach,

Nohyeong Jeong, Elif Demirel

et al.

Environmental Science & Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 16, 2024

Polymeric membranes have been widely used for liquid and gas separation in various industrial applications over the past few decades because of their exceptional versatility high tunability. Traditional trial-and-error methods material synthesis are inadequate to meet growing demands high-performance membranes. Machine learning (ML) has demonstrated huge potential accelerate design discovery membrane materials. In this review, we cover strengths weaknesses traditional methods, followed by a discussion on emergence ML developing advanced polymeric We describe methodologies data collection, preparation, commonly models, explainable artificial intelligence (XAI) tools implemented research. Furthermore, explain experimental computational validation steps verify results provided these models. Subsequently, showcase successful case studies emphasize inverse methodology within ML-driven structured framework. Finally, conclude highlighting recent progress, challenges, future research directions advance next generation With aim provide comprehensive guideline researchers, scientists, engineers assisting implementation process.

Language: Английский

Citations

5

The Bio Steel Cycle Meets Indoor Farming - CCUS with the SusCiP Principle in Agriculture DOI Creative Commons
Sandra Kiessling

Advances in Environmental and Engineering Research, Journal Year: 2025, Volume and Issue: 06(01), P. 1 - 18

Published: Jan. 15, 2025

The World climate is changing, with a great impact on global food production systems. Extreme weather events, floods, wildfires and draughts are phenomena of disrupted previously stable natural patterns, which vital for crop animal husbandry alike. Most the World’s produced in temperate climatic zones rich arable land those affected by increasing unpredictability naturally occurring seasons conditions. This work aims to provide possible sustainable solution challenges under pressures change. Changing methods moving indoor agriculture poses immense opportunities at same time. Technical solutions currently researched explored innovators, governments industry leaders developed Bio Steel Cycle can be seen as nucleus other industries, including production, could starting point new standard all systems: SusCip principle.

Language: Английский

Citations

0

Carbon Capture and Sequestration: Cutting-Edge Technologies to Combat Climate Change DOI

Gourav Dhingra,

Rajeev Ranjan Kumar

Sustainable Energy Technologies and Assessments, Journal Year: 2025, Volume and Issue: 75, P. 104226 - 104226

Published: Feb. 7, 2025

Language: Английский

Citations

0

Carbon capture, utilization and storage in buildings: Analysis of performance, social acceptance, policy measures, and the role of artificial intelligence DOI
Y. Elaouzy, Abdelghafour Zaabout

Building and Environment, Journal Year: 2025, Volume and Issue: 275, P. 112817 - 112817

Published: March 9, 2025

Language: Английский

Citations

0

Technoeconomic Assessment of Offshore Carbon Storage Multiphase Source-Sink Matching Based on Multiwell Optimization in Eastern Coastal China DOI
Xiaoqing Lin,

Xiaoxiao Zan,

Yuxuan Ying

et al.

ACS Sustainable Chemistry & Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: April 2, 2025

Language: Английский

Citations

0

Recent advances in CO2 capture and utilization: From the perspective of process integration and optimization DOI
Nuo Wang, Jianzhao Zhou, Jingzheng Ren

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 216, P. 115688 - 115688

Published: April 9, 2025

Language: Английский

Citations

0

Synergistic Regulation of Rare Earth and Noble Metal Promoters on Ni-based Bifunctional Materials for Enhanced CO2 Methanation Performance and Reaction Mechanism DOI

Yang Zheng,

Wei Su, Zhenghao Wang

et al.

Catalysis Letters, Journal Year: 2025, Volume and Issue: 155(5)

Published: April 9, 2025

Language: Английский

Citations

0

Machine Learning in Carbon Capture, Utilization, Storage, and Transportation: A Review of Applications in Greenhouse Gas Emissions Reduction DOI Open Access
Xuejia Du, Muhammad Noman Khan, Ganesh Thakur

et al.

Processes, Journal Year: 2025, Volume and Issue: 13(4), P. 1160 - 1160

Published: April 11, 2025

Carbon Capture, Utilization, and Storage (CCUS) technologies have emerged as indispensable tools in reducing greenhouse gas (GHG) emissions combating climate change. However, the optimization scalability of CCUS processes face significant technical economic challenges that hinder their widespread implementation. Machine Learning (ML) offers innovative solutions by providing faster, more accurate alternatives to traditional methods across value chain. Despite growing body research this field, applications ML remain fragmented, lacking a cohesive synthesis bridges these advancements practical This review addresses gap systematically evaluating all major components—CO2 capture, transport, storage, utilization. We provide structured representative examples for each category critically examine various techniques, objectives, methodological frameworks employed recent studies. Additionally, we identify key parameters, limitations, future opportunities applying enhance systems. Our thus comprehensive insights guidance stakeholders, supporting informed decision-making accelerating ML-driven commercialization.

Language: Английский

Citations

0