IIT Gandhinagar Researchers Use Machine Learning to Identify Materials for CO₂ Recycling
Gandhinagar: Researchers at the Indian Institute of Technology Gandhinagar (IITGN) have used computational approaches and machine learning to identify promising two-dimensional materials that could help convert carbon dioxide (CO₂) into carbon monoxide (CO).
The findings, published in npj Computational Materials, identify three high-entropy MBenes as potential catalysts for CO₂ reduction. According to the researchers, the materials could facilitate the conversion without requiring an additional electrical boost to drive the reaction.
The work could contribute to future technologies focused on carbon capture, utilisation and recycling, particularly systems powered by renewable electricity.
Searching for Better CO₂ Conversion Materials
CO₂ is a highly stable molecule, making its conversion into useful chemicals challenging. Researchers have therefore been exploring catalysts that can activate CO₂ while requiring less energy.
One potential pathway is electrochemical CO₂ reduction, which can operate under relatively mild, water-based conditions and can potentially be powered using renewable electricity.
The IITGN team focused on producing carbon monoxide, an important industrial building block that can be used to produce fuels and chemicals.
Combining MBenes With High-Entropy Materials
The study combines two areas of materials research: MBenes and high-entropy materials.
MBenes are ultrathin, two-dimensional materials containing metal and boron. Their structure provides a large exposed surface that can potentially support chemical reactions.
High-entropy materials, meanwhile, contain multiple metallic elements. The combination creates a chemically diverse surface where different elements can contribute to different stages of a catalytic reaction.
The researchers explored whether combining these properties could produce more effective catalysts for CO₂ reduction.
Three Materials Identified From Computational Screening
The researchers initially identified 18 viable compositions through computational screening and simulations.
Three high-entropy MBene compositions emerged as particularly promising for CO₂-to-CO conversion without the need for additional electrical energy.
The materials contain combinations of five metals selected from chromium, niobium, zirconium, molybdenum, titanium, hafnium and tantalum, along with boron.
Different Metals Could Play Different Roles
The researchers found indications that the different metals in the materials could contribute to different parts of the catalytic process.
For example, chromium was identified as a preferred site for CO₂ adsorption, while zirconium and hafnium could help supply electrons required for the reaction.
This interaction between multiple elements is associated with the “cocktail effect” observed in multi-element materials, where combining different components can produce properties that are difficult to achieve with individual elements alone.
The resulting carbon monoxide could serve as a feedstock for producing industrial chemicals and fuels, including syngas.
Potential for Carbon Recycling
The researchers said the findings could eventually contribute to technologies in which captured CO₂ is converted into useful products and returned to the industrial cycle.
Dr Raghavan Ranganathan, Associate Professor in the Department of Materials Engineering at IITGN and Principal Investigator of the Computational Molecular Engineering Group, said the results are promising but require further investigation.
The next steps would include experimental synthesis of the identified materials and electrochemical testing to determine whether the computational predictions can be demonstrated under laboratory conditions.
Study Supports Broader CO₂ Utilisation Efforts
The research is relevant to wider efforts to develop carbon capture, utilisation and storage (CCUS) technologies as part of strategies to reduce greenhouse gas emissions.
The researchers acknowledged the Param Ananta supercomputing facility at IIT Gandhinagar, supported by the National Supercomputing Mission, for computational resources used in the study.
Key Highlights
- Institute: IIT Gandhinagar
- Research area: CO₂ reduction and carbon utilisation
- Materials: High-entropy MBenes
- Materials identified: 3 promising candidates
- Initial computational candidates: 18
- Target conversion: CO₂ to carbon monoxide
- Approach: Computational screening and machine learning
- Potential application: CO₂ recycling and industrial carbon utilisation
- Next step: Experimental synthesis and electrochemical testing
- Publication: npj Computational Materials
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