Recent advances in biomass deconstruction, microbial conversion, artificial intelligence, and carbon capture for sustainable bioenergy
Vishwajit Kumar, Shikha Mishra, Pratham Joshi, Jyotsna 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、バイオマス分解、微生物変換、人工知能、炭素回収を統合した持続可能なバイオエネルギーシステムの最近の進歩を概説する。前処理戦略、酵素加水分解、微生物工学の技術的課題とAIによる最適化の可能性を評価し、スケーラブルで経済的に viable なバイオ燃料生産への統一フレームワークを提案する。
English
This review critically analyzes recent advances in biomass deconstruction, microbial conversion, artificial intelligence, and carbon capture for sustainable bioenergy. It evaluates pretreatment strategies, enzymatic hydrolysis, and microbial engineering within a systems-level framework, highlighting the role of AI and multi-omics for predictive optimization. The paper establishes an integrated pathway for scalable, economically viable, and environmentally sustainable biofuel production.
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
日本でもバイオエネルギーはGX実現の一翼を担うが、本稿は主に技術レビューであり、日本の政策やSSBJとの直接的な接点は限定的。ただし、AI活用によるプロセス最適化はバイオ燃料コスト低減に寄与する可能性がある。
In the global GX context
This review contributes to the global discourse on low-carbon bioenergy by providing a comprehensive systems-level framework. It underscores the integration of AI and carbon capture in biofuel production, relevant to global energy transition goals such as those under the Paris Agreement.
👥 読者別の含意
🔬研究者:Provides a holistic overview of bioenergy conversion pathways and identifies key research gaps in AI integration and carbon capture.
🏢実務担当者:Highlights technological bottlenecks and optimization strategies for biofuel production, useful for R&D planning.
🏛政策担当者:Offers insights into the potential of advanced bioenergy systems to support national climate targets.
📄 Abstract（原文）
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. Graphical abstract
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.6084/m9.figshare.c.8532516.v1first seen 2026-06-14 04:49:34 · last seen 2026-06-16 04:52:09
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