Antimicrobial and self-cleaning coatings in building engineering: Materials, mechanisms and long-term performance for low-carbon environments
建築工学における抗菌・自己洗浄コーティング: 低炭素環境のための材料、メカニズム、長期性能 (AI 翻訳)
Jaya Verma, Varshika Singh, Jiqiang Wang, Yongda Yan, Ching Yern Chee, Gajendra Gaur, Yanquan Geng
🤖 gxceed AI 要約
日本語
本レビューは、建築工学における抗菌・自己洗浄コーティングの最近の進歩を調査し、メンテナンスの脱炭素化への関連性に焦点を当てています。主要なメカニズム、材料システム、製造戦略、および耐久性や耐候性などの実用的性能特性を検討しています。また、ライフサイクル炭素削減効果を評価し、技術的、経済的、規制上の障壁と導入フレームワークを提示しています。
English
This review examines recent advances in antimicrobial and self-cleaning coatings for building engineering, focusing on their relevance for maintenance decarbonization. It covers fundamental mechanisms, emerging material systems, fabrication strategies, and key performance characteristics such as durability and weathering resistance. The life-cycle carbon reduction from operational and embodied approaches is evaluated, along with technical, economic, and regulatory barriers and implementation frameworks.
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
日本の建築分野では、GX推進の一環として建物の運用段階でのCO2削減が求められており、本レビューで扱うメンテナンス回避による省エネ・省資源コーティングは、ZEBや省エネ基準の達成に貢献する可能性があります。ただし、具体的な日本市場への適合性や日本の規制との関連性は限定的です。
In the global GX context
In the global context, this review aligns with the push for low-carbon and net-zero buildings under frameworks like LEED and BREEAM. The coatings discussed can reduce operational carbon by lowering cleaning-related energy and water use, and extend building lifespan, contributing to circular economy goals. However, the paper is a broad materials review with limited direct connection to climate disclosure or transition finance.
👥 読者別の含意
🔬研究者:Researchers in building materials or surface engineering can gain an overview of antimicrobial/self-cleaning technologies and their carbon reduction potential.
🏢実務担当者:Practitioners in building design and facility management can identify coating solutions to reduce maintenance costs and operational carbon.
🏛政策担当者:Policymakers developing building codes or green building standards may consider incorporating such coatings as part of low-carbon maintenance strategies.
📄 Abstract（原文）
Surface engineering technologies, which can improve hygiene while lower the environmental impact associated with maintenance, have broader applicability and are being increasingly researched to meet the demand for low-carbon and net-zero buildings. Multifunctional solutions can be achieved with antimicrobial and self-cleaning coatings with applications to suppress microbial growth, restricting the spreading of surface or contact contamination and reducing water, energy and chemical-intensive cleaning processes. The goal of this review is to investigate recent advancements in these coatings, with a focus on their relevance for maintenance decarbonization from a building-engineering perspective. This Review discusses fundamental mechanisms such as antimicrobial activity and self-cleaning behavior along with emerging material systems and fabrication strategies that enable these developments for large-scale building applications. The key engineering performance characteristics, namely durability, weathering resistance, functional stability and compatibility with the substrate are examined thoroughly in realistic service conditions. The life-cycle carbon reduction attributable to these coatings is evaluated against two primary non-mutually exclusive approaches operational, through maintenance avoidance and embodied, through much greater service-life extension. Reviewing various field applications will focus on issues associated with scale, durability, environmental exposure. Ultimately, technical, economic and regulatory impediments are delineated, followed by frameworks directed towards implementation that can help facilitate the adoption of these coatings into sustainable building systems.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.nxmate.2026.102685first seen 2026-07-26 05:16:55
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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。