
Carbon Capture Science & Technology, Год журнала: 2024, Номер 13, С. 100323 - 100323
Опубликована: Ноя. 4, 2024
Язык: Английский
Carbon Capture Science & Technology, Год журнала: 2024, Номер 13, С. 100323 - 100323
Опубликована: Ноя. 4, 2024
Язык: Английский
Journal of the American Chemical Society, Год журнала: 2025, Номер unknown
Опубликована: Фев. 7, 2025
Escalating carbon dioxide (CO2) emissions have intensified the greenhouse effect, posing a significant long-term threat to environmental sustainability. Direct air capture (DAC) has emerged as promising approach achieving net-zero future, which offers several practical advantages, such independence from specific CO2 emission sources, economic feasibility, flexible deployment, and minimal risk of leakage. The design optimization DAC sorbents are crucial for accelerating industrial adoption. Metal-organic frameworks (MOFs), with high structural order tunable pore sizes, present an ideal solution strong guest-host interactions under trace conditions. This perspective highlights recent advancements in using MOFs DAC, examines molecular-level effects water vapor on capture, reviews data-driven computational screening methods develop molecularly programmable MOF platform identifying optimal sorbents, discusses scale-up cost DAC.
Язык: Английский
Процитировано
2Journal of environmental chemical engineering, Год журнала: 2025, Номер unknown, С. 116201 - 116201
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
1Sustainable Development, Год журнала: 2024, Номер unknown
Опубликована: Окт. 6, 2024
Abstract Artificial intelligence (AI) and environmental points are equally important components within the response to local weather change. Therefore, based on efforts of reducing carbon emissions more efficiently effectively, this study tries focus AI integration with capture technology. The urgency tackling climate change means we need advanced capture, is an area where can make a huge impact in how these technologies operated managed. It will minimize manufacturing improve both resource efficiency as well our planet's footprint by turning waste into something value again. could be leveraged analyze data sets from plants, searching for optimal system settings efficient ways identifying patterns available information at larger scale than currently possible. In addition, incorporated sensors monitoring mechanisms supply chain identify any operational failure reception itself allowing timely action protect those areas. also helps generative design materials, which allows researchers explore new types carbon‐absorbing material, including metal–organic frameworks polymeric materials that industrial CO 2 , such moisture. it increases accuracy reservoir simulations controls injection systems storage or enhanced oil recovery. Through applying algorithms geology, production performance real‐time would like facilitate optimization processes while assuring maximum efficiency. integrates renewable‐based employed AI‐driven smart grid methods.
Язык: Английский
Процитировано
7Separation and Purification Technology, Год журнала: 2025, Номер unknown, С. 131729 - 131729
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0Carbon Capture Science & Technology, Год журнала: 2025, Номер unknown, С. 100393 - 100393
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
0Applied Energy, Год журнала: 2025, Номер 388, С. 125666 - 125666
Опубликована: Март 10, 2025
Язык: Английский
Процитировано
0Energy, Год журнала: 2024, Номер 299, С. 131376 - 131376
Опубликована: Май 3, 2024
Язык: Английский
Процитировано
3Fuel, Год журнала: 2024, Номер 372, С. 132279 - 132279
Опубликована: Июнь 22, 2024
Язык: Английский
Процитировано
0Carbon Capture Science & Technology, Год журнала: 2024, Номер 13, С. 100323 - 100323
Опубликована: Ноя. 4, 2024
Язык: Английский
Процитировано
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