Recent advances in biomass deconstruction, microbial conversion, artificial intelligence, and carbon capture for sustainable bioenergy
持続可能なバイオエネルギーのためのバイオマス分解、微生物変換、人工知能、炭素回収の最近の進歩 (AI 翻訳)
Vishwajit Kumar, Shikha Mishra, Pratham Joshi, J. P. Misra, Prakash Peralam Yegneswaran, Bhavanari Mallikarjun, Syed Shams Yazdani, Piyush Behari Lal
🤖 gxceed AI 要約
日本語
本レビューは、持続可能なバイオエネルギー実現に向けた微生物燃料生産の統合的フレームワークを提示。前処理、酵素加水分解、微生物工学の進歩に加え、人工知能とマルチオミクス統合によるプロセス最適化の役割を強調している。
English
This review presents an integrated framework for microbial biofuel production towards sustainable bioenergy. It covers advances in pretreatment, enzymatic hydrolysis, and microbial engineering, and highlights the emerging role of AI and multi-omics for predictive process optimization.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本はバイオマス発電の導入が進んでいるが、効率的な変換技術の確立が課題。本レビューは原料柔軟性や前処理最適化など、日本のバイオマス利用拡大に示唆を与える。
In the global GX context
While global bioenergy deployment grows, conversion efficiency remains a bottleneck. This review offers a systems-level perspective on integrating pretreatment, microbial conversion, and AI optimization, relevant to international efforts in sustainable biofuel production.
👥 読者別の含意
🔬研究者:Provides a comprehensive overview of conversion technologies and AI-driven optimization pathways in bioenergy.
📄 Abstract（原文）
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.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1186/s40643-026-01081-wfirst seen 2026-06-13 04:58:52
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