スマート・グリーンケミストリー：設計・ツール・持続可能性・将来の道筋
Smart Green Chemistry: Design, Tools, Sustainability and Future Pathways (原題)
C. Hussain, Ghazanfar Hussain, Rüstem Keçili
🤖 gxceed AI 要約
日本語
グリーンケミストリーにイノベーション・適応性・AIの三要素を統合した「SMART Green Chemistry」概念を提唱するレビュー。AIによるリアルタイム意思決定や予測分析が資源管理・廃棄物削減を強化し、データ駆動型の持続可能性を再定義すると論じる。製薬・再生可能エネルギー・環境修復分野での分子設計やグリーン触媒探索の加速が期待される。
English
This review proposes 'SMART Green Chemistry,' integrating innovation, adaptability, and AI into green chemistry. AI enables real-time decision-making, process automation, and predictive analytics to improve resource management and waste reduction. The framework aims to accelerate molecular design and green catalyst discovery across pharmaceuticals, renewable energy, and environmental remediation, aligning with net-zero and circular economy goals.
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
化学産業のScope 3排出・製品ライフサイクル評価と接続しうる概念だが、SSBJや有報開示への直接的な示唆は限定的。日本企業の素材・化学セクターのGX戦略を考える上での参考枠組みとして位置づけられる。
In the global GX context
Offers a conceptual lens linking AI-driven process optimization to industrial decarbonization, relevant to Scope 3 and product-level sustainability claims under CSRD/ISSB. However, it lacks empirical grounding or direct ties to disclosure frameworks, limiting immediate applicability to global GX practice.
👥 読者別の含意
🔬研究者:AIとグリーンケミストリーの統合に関する概念的枠組みを提供するが、実証的検証が今後の課題。
🏢実務担当者:化学・製薬企業のR&Dやプロセス最適化におけるAI活用の方向性を検討する際の参考になる。
🏛政策担当者:産業界のデジタル×グリーン投資を促す政策設計の背景として参照可能。
📄 Abstract（原文）
The increasing environmental challenges and the global demand for sustainable development have necessitated innovative and effective approaches in chemistry. This evolution has led to the development of a novel scientific and industrial concept known as “SMART Green Chemistry.” This review examines the future of green chemistry by highlighting the roles of three key elements—innovation, adaptability, and artificial intelligence (AI). Innovation drives the development of novel materials and the optimization of sustainable chemical reactions, while adaptive technologies enable continuous improvement in response to dynamic environmental and economic conditions. Meanwhile, AI offers significant potential in real-time decision-making, process automation, as well as predictive analytics, thereby enhancing resource management and waste reduction. Collectively, these approaches position SMART Green Chemistry as a framework that not only promotes sustainable operations but also redefines sustainability through data-driven decision-making. This transition aligns with global trends toward net-zero emissions and a circular economy. The integration of digital technologies with green chemistry is expected to accelerate molecular design, facilitate the discovery of green catalysts, and enable more efficient process development across industries such as pharmaceuticals, renewable energy, and environmental remediation. Ultimately, SMART Green Chemistry, supported by digital innovation and sustainability principles, represents a transformative approach to addressing pressing environmental challenges in an integrated and effective manner.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.2174/0122133461490981260929061523first seen 2026-10-17 05:12:28 · last seen 2026-11-06 05:23:42
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。