ReviewFundamental research2025
Low-carbon operation technologies and challenges for process industry.
Review in Fundamental research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The process industry plays a crucial role in national economic development and national defense construction. However, as a typical energy-intensive industry, it is at the forefront of efforts to reduce carbon emissions. Information and communications technology (ICT) is an important means of achieving low-carbon operation in the process industry by strengthening the regulation of carbon flow in the production process. This paper first introduces the relevant research on low-carbon operation of industrial processes, and analyzes and summarizes the current research status and bottleneck. Then, the challenging problems faced by ICT in achieving low-carbon operation in the process industry are analyzed from four aspects: carbon emission sensing, carbon transfer modeling, carbon migration control, as well as low-carbon operation optimization throughout the entire process. Finally, the overall framework and vision for implementing low-carbon operation in the process industry through ICT are presented, and future research directions are proposed in conjunction with industrial artificial intelligence.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.