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Related Concept Videos

Carbon-dioxide Fixation01:28

Carbon-dioxide Fixation

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Carbon dioxide fixation in prokaryotes enables the assimilation of inorganic carbon into organic molecules, supporting biosynthetic pathways, sustaining ecosystems, and contributing to the global carbon cycle. It also has industrial applications in carbon capture and bioproduct synthesis. Autotrophic organisms rely on this process to utilize CO₂ as a carbon source in diverse environments.The Calvin CycleThe Calvin cycle is the most widespread carbon fixation mechanism, primarily used by...
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An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
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Ribulose 1,5- bisphosphate carboxylase/oxygenase (RuBisCo) is a critical enzyme that catalyzes carbon dioxide assimilation during photosynthesis. However, it is an inefficient enzyme, having an extremely slow catalytic rate. A typical enzyme can process about a thousand molecules per second; however, RuBisCo fixes only around three-carbon dioxides per second. Photosynthetic cells compensate for this slow rate by synthesizing very high amounts of RuBisCo, making it the most abundant single...
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Bioremediation00:46

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Bioremediation is the use of prokaryotes, fungi, or plants to remove pollutants from the environment. This process has been used to remove harmful toxins in groundwater as a byproduct of agricultural run-off and also to clean up oil spills.
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The Carbon Cycle01:14

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Carbon is the basis of all organic matter on Earth, and is recycled through the ecosystem in two primary processes: one in which carbon is exchanged among living organisms, and one in which carbon is cycled over long periods of time through fossilized organic remains, weathering of rocks, and volcanic activity. Human activities, including increased agricultural practices and the burning of fossil fuels, has greatly affected the balance of the natural carbon cycle.
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Synthetic Biology02:55

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Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
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Related Experiment Video

Updated: Jul 31, 2025

Author Spotlight: Standardizing the Development of Amine-Based Silica Composites as CO2 Adsorbents for Direct Air Capture
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Artificial intelligence enabled carbon capture: A review.

A K Priya1, Balaji Devarajan2, Avinash Alagumalai3

  • 1Department of Chemical Engineering, KPR Institute of Engineering and Technology, Tamilnadu, India.

The Science of the Total Environment
|May 7, 2023
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) aids carbon capturing to combat climate change. This study explores AI techniques, tools, and patents for effective carbon emission mitigation and achieving SDG 13.

Keywords:
AI in carbon captureMachine learningPatent landscapePrediction capability

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Area of Science:

  • Environmental Science and Engineering
  • Computer Science and Artificial Intelligence

Background:

  • Rising atmospheric carbon emissions exacerbate climate change and environmental degradation.
  • Digital technologies, particularly artificial intelligence (AI), offer novel solutions for environmental challenges.

Purpose of the Study:

  • To investigate the application of AI in carbon capturing technologies.
  • To analyze AI techniques, tools, and the patent landscape in carbon capture.
  • To project the future role of AI in climate change mitigation and achieving Sustainable Development Goal 13 (Climate Action).

Main Methods:

  • Review of AI techniques including machine learning (ML), deep learning (DL), and hybrid approaches in carbon capture.
  • Analysis of AI tools, frameworks, and mathematical models relevant to carbon capture.
  • Exploration of the AI in carbon capture patent landscape.

Main Results:

  • AI, ML, DL, and hybrid methods are increasingly adopted in carbon capture strategies.
  • Various AI tools, frameworks, and models are instrumental in advancing carbon capture efficiency.
  • The patent landscape reveals significant innovation at the confluence of AI and carbon capture.

Conclusions:

  • AI-assisted carbon capturing presents a promising pathway for mitigating climate change.
  • Further research and development in AI for carbon capture are crucial for meeting climate action goals.
  • This study provides insights for researchers on the trajectory of AI in climate change mitigation.