A large-scale, LLM-assisted and validated dataset of biomass and waste conversion technologies and feedstocks

Biomass, organic wastes and by-products are increasingly targeted for low-carbon fuels and value-added chemicals. However, strategic decision-making from a circular economy perspective requires a big-picture view of the relative significance of different conversion technologies in handling diverse feedstock portfolios, and no large-scale, cross-technology mapping of these portfolios is currently available. Thus, we assembled a literature-derived dataset linking eight major waste-to-X valorisation technologies (gasification, pyrolysis, hydrothermal liquefaction, torrefaction, anaerobic digestion, aerobic digestion, fermentation and transesterification) to their reported feedstocks. Using the Scopus database, 121,365 records were retrieved with harmonised search strings, spanning publications from 1887 to 2026, including a small number of early-indexed 2026 records. This constrained yet scalable search strategy facilitates automated extraction and validation while yielding a rich dataset. Further, an LLM-assisted workflow was implemented to extract candidate technology and feedstock phrases, followed by a two-level validation that combines rule-based cleaning with targeted LLM re-evaluation to minimise manual curation. The resulting dataset provides technology-specific, validated feedstock descriptors that support comparative analyses and decision-support applications in a circular bioeconomy context.