Enhancing CO2 sequestration efficiency: A comprehensive study of nanostructured MOF-composite membrane for sustainable climate solution

Carbon Capture Science & Technology, Journal Year: 2025, Volume and Issue: unknown, P. 100366 - 100366

Published: Jan. 1, 2025

Language: Английский

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Review and analysis of porous adsorbents for effective CO2 capture

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 215, P. 115589 - 115589

Published: March 16, 2025

Language: Английский

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Engineering Insights into Tailored Metal–Organic Frameworks for CO₂ Capture in Industrial Processes

Langmuir, Journal Year: 2024, Volume and Issue: 40(33), P. 17387 - 17395

Published: Aug. 8, 2024

Despite the known impacts on climate change of carbon dioxide emissions, continued use fossil fuels for energy generation leading to emission (CO

Language: Английский

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Recent Progress and Challenges in the Field of Metal–Organic Framework-Based Membranes for Gas Separation

Compounds, Journal Year: 2024, Volume and Issue: 4(1), P. 141 - 171

Published: Feb. 2, 2024

Metal–organic frameworks (MOFs) represent the largest class of materials among crystalline porous ever developed, and have attracted attention as core for separation technology. Their extremely uniform pore aperture nearly unlimited structural chemical characteristics great interest promise applying MOFs to adsorptive membrane-based separations. This paper reviews recent research into development MOF membranes gas separation. Strategies polycrystalline mixed-matrix are discussed, with a focus on systems involving hydrocarbon separation, CO2 capture, H2 purification. Challenges opportunities industrial deployment also providing guidance design fabrication future high-performance membranes. The contributions underlying mechanism performance adopted strategies membrane-processing technologies breaking selectivity/permeability trade-off discussed.

Language: Английский

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Balancing computational chemistry's potential with its environmental impact

Green Chemistry, Journal Year: 2024, Volume and Issue: 26(15), P. 8669 - 8679

Published: Jan. 1, 2024

Digital chemistry methods accelerated discoveries of sustainable processes but require assessing and minimizing their carbon footprint caused by the required computing power.

Language: Английский

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Accelerated Discovery of CO₂ Solid Sorbents Using Active Machine Learning: Review and Perspectives

Energy & Fuels, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 31, 2024

With the escalating severity of global climate change, significance carbon capture technology has become increasingly evident with respect to aim reaching peak and neutrality. Due exceptional selectivity, high adsorption capacity, long-term stability, solid sorbents are regarded as crucial materials for effective CO2 capture. Machine learning, an emerging tool in artificial intelligence, been adopted high-efficient screen catalysts recent years. By analyzing available data on material properties, machine learning can greatly enhance effectiveness precision identifying high-efficiency sorbents. This work provides overview latest advancements application capture, which specifically focuses by Several techniques their applications different types fully summarized concise comments, followed conclusion some challenges perspectives. review serve a guide development facilitate extensive utilization environmental protection.

Language: Английский

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Computational Modeling of Reticular Materials: The Past, the Present, and the Future

Advanced Materials, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 26, 2024

Abstract Reticular materials rely on a unique building concept where inorganic and organic units are stitched together giving access to an almost limitless number of structured ordered porous materials. Given the versatility chemical elements, underlying nets, topologies, reticular provide platform design for timely technological applications. have now found their way in important societal applications, like carbon capture address climate change, water harvesting extract atmospheric moisture arid environments, clean energy Combining predictions from computational chemistry with advanced experimental characterization synthesis procedures unlocks strategy synthesize new desired properties functions. Within this review, current status modeling is addressed supplemented topical examples highlighting necessity molecular This review as templated study starting structure realistic material towards prediction functions At end, authors perspective past, present future formulate open challenges inspire model method developments.

Language: Английский

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Computational Screening and Design of Metal-Organic Frameworks for CO2 Separation from Flue Gas

Applied and Computational Engineering, Journal Year: 2025, Volume and Issue: 123(1), P. 88 - 99

Published: Jan. 7, 2025

Rising CO2 levels, largely from flue gas emissions, are a significant contributor to global climate change. Adsorption using Metal-Organic Frameworks (MOFs) offers promising solution for capture due their high surface area, tunable porosity, and selectivity. To streamline the discovery of efficient MOFs, we developed high-throughput virtual screening (HTVS) pipeline by integrating Grand-Canonical Monte Carlo (GCMC) simulations, molecular modeling machine learning. We screened filtered subset CoREMOF database user-defined hypothetical MOF bank identify candidates with adsorption capacity This approach yielded several high-performing including five dataset new structure exceeding performance existing MOFs. Our findings highlight complex relationship between geometries performance, emphasizing importance features like open metal sites pore geometry. computational framework accelerates provides valuable insights experimental synthesis. Future work will focus on expanding dataset, improving simulation accuracy, employing advanced optimization techniques enhance process.

Language: Английский

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Enhancing the CO₂ Separation Performance of Mixed Matrix Membranes Based on Block Copolymer via Nonsolvent-Induced Microstructure Rearrangement

Industrial & Engineering Chemistry Research, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 2, 2025

Language: Английский

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The concept of ‘nature’ in chemistry in a digital and ecological age

Foundations of Chemistry, Journal Year: 2025, Volume and Issue: unknown

Published: March 14, 2025

Language: Английский

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