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AI-Based Model for CO2-to-Fuel Conversion

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October 12, 2026

Prelims: Current events of national and international importance | Science & Technology  

Why in News?

Researchers at the IISc, Bengaluru, developed a computational framework that maps 9,389 elementary chemical reactions for converting CO₂ into useful fuels and chemicals.

co2 hydration AI mechanism

Key Findings

  • The researchers expanded the initial database from 152 to 9,389 reactions.
  • The network includes 105 chemical species present on the catalyst surface.
  • A model limited to 152 reactions predicted formic acid as the main product and underestimated CO₂ conversion.
  • The expanded model predicted a 40-fold increase in CO₂ conversion and identified methanol and carbon monoxide as major products, consistent with experimental results.
  • The model also identified a less conventional pathway where molecular hydrogen (H₂) transfers hydrogen directly to intermediates without first splitting into individual atoms.

Technologies Used

  • Quantum-mechanical simulations – Estimate reaction energies and barriers based on quantum mechanics.
  • Machine learning (ML) – Predicts energy barriers for additional reactions to reduce computational effort.
  • Automated reaction mapping – Identifies potential reactions among chemical species to build a comprehensive reaction network.

Significance

  • Improved accuracy – This approach reduces errors by ensuring that potentially important reactions are not excluded.
  • Catalyst design – It may assist in developing catalysts that favor pathways leading to methanol.
  • Carbon utilisation – This framework supports research focused on converting captured CO₂ into valuable products.
  • Wider applications – The framework can also be applied to CO₂ reduction with other catalysts, as well as to nitrogen reduction and water splitting.

Reference

TOI | CO₂ Hydrogenation

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