ReviewBioresources and bioprocessing2026
Recent advances in biomass deconstruction, microbial conversion, artificial intelligence, and carbon capture for sustainable bioenergy.
Review in Bioresources and bioprocessing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The transition from fossil fuels to low-carbon bio-based energy systems is increasingly constrained by the efficiency, scalability, and integration of conversion technologies. Addressing this challenge, this review critically analyzes microbial biofuel production through a conversion-centric and systems-level framework, emphasizing how feedstock diversity, pretreatment chemistry, enzymatic deconstruction, and microbial metabolism collectively govern overall process performance. This review evaluates how pretreatment strategies modulate biomass recalcitrance, hydrolysate chemical ecologies, inhibitor profiles, and redox balance, thereby imposing fundamental constraints on enzymatic efficiency, microbial conversion yields, and emissions outcomes. Advances in enzymatic hydrolysis are assessed in terms of bond-specific catalysis, enzyme synergy, and persistent bottlenecks arising from substrate heterogeneity, lignin enzyme interactions, and non-productive binding, while microbial engineering strategies from robust monocultures to synthetic consortia and cell-free systems are examined through techno-economic and metabolic flux perspectives. It further highlights the emerging role of artificial intelligence and multi-omics integration in enabling predictive optimization of pretreatment severity, enzyme cocktails, and metabolic routing, moving beyond empirical process tuning. This article establishes a unified framework for integrated "microbial lignocellulose-to-fuel" pathways, demonstrating how coordinated advances in conversion technologies are essential for achieving scalable, economically viable, and environmentally sustainable bioenergy systems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.