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Biomass carbon mining to develop nature-inspired materials for a circular economy

Summary

This paper explains how we can turn waste biomass from agriculture and industry into valuable materials to replace petroleum-based products. By using computational methods and artificial intelligence, researchers can design more efficient processes to convert plant and animal waste into bioplastics, chemicals, and building materials. Over 100 companies are already successfully doing this, creating products from waste coffee grounds, seaweed, agricultural residue, and other biomass sources.

Background

The transition from a linear to circular economy requires redefining material sources and redesigning products to reduce pressure on natural resources. Biomass wastes represent extensively available carbon sources that can be valorized into biobased materials mimicking nature’s efficiency. Advances in materials processing, characterization, artificial intelligence, and machine learning are supporting this transition to sustainable materials mining.

Objective

This perspective article examines new alternatives for carbon mining in biomass wastes and the valorization of biomass using available processing techniques. The work focuses on implementing computational modeling, artificial intelligence, and machine learning to accelerate development of biobased materials and process engineering for a circular economy.

Results

Over 1,000 Mt of agricultural biomass and 4,600 Mt of wood-derived biomass are produced yearly with significant portions underutilized. The paper identifies 100+ startups and enterprises successfully valorizing biomass waste into bioplastics, chemicals, construction materials, and other applications. Tables summarizing HTP experiments show diverse functional groups and chemical compositions achievable from different biomass types under various processing conditions.

Conclusion

Biomass represents a critical resource for transitioning to a circular economy through carbon mining from waste streams. Integration of computational tools, AI, and ML into biomass processing and material design accelerates development of nature-inspired, high-performance biobased alternatives to petroleum-derived products. Standardization of biomass classification, resource quantification, and responsible AI implementation are essential for scaling biorefinery technologies.
  • Published in:iScience,
  • Study Type:Review,
  • Source: PMID: 37123246, DOI: 10.1016/j.isci.2023.106549
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