Energy Efficiency through Green Materials: A Physics-based Approach
グリーンマテリアルによるエネルギー効率：物理に基づくアプローチ (AI 翻訳)
R. Venkateswarlu, Rekha Yashaswi
🤖 gxceed AI 要約
日本語
本稿は、建築環境と再生可能エネルギーシステムにおけるエネルギー効率向上のためのグリーンマテリアルをレビュー。物理に基づく設計戦略、機械学習・シミュレーション活用、循環経済と気候レジリエンスへの示唆を提供。
English
This review covers green materials for energy efficiency in the built environment and renewable energy systems, highlighting physics-based design, machine learning and simulation tools, and implications for climate resilience and circular economy.
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
日本では2024年度に改正省エネ法が施行され、建築物のエネルギー消費基準が強化。本レビューが示す先進複合材やエココンクリート等のグリーンマテリアルは、基準達成やZEB実現に貢献する可能性がある。
In the global GX context
Globally, green materials are critical for meeting net-zero building targets under initiatives like the Paris Agreement and EU Taxonomy. This paper provides a physics-based lens on material innovations that can reduce operational carbon and embodied energy.
👥 読者別の含意
🔬研究者:A consolidated overview of physics-based design strategies and machine learning integration for green materials.
🏢実務担当者:Insights on material options (e.g., advanced composites, eco-concretes) and simulation tools for energy-efficient building design.
🏛政策担当者:Evidence that green material innovation is a viable pathway for tightening building energy codes and promoting circular economy.
📄 Abstract（原文）
The drive towards energy efficiency in the built environment has accelerated research into innovative green materials that are engineered to conserve energy, minimize carbon footprints, and promote environmental sustainability. This paper reviews the current state and future potential of green materials, highlighting physics-based design strategies that underpin advancements in energy-efficient technologies. Through a multidisciplinary lens, it explores materials such as advanced composites, eco-friendly concretes, smart thin films, and nano materials, providing a holistic account of their physical principles, real-world applications, and performance metrics. The integration of passive and active energy-saving technologies, along with machine learning and simulation tools, is examined to outline pathways for optimizing energy use in construction and renewable energy systems. Recommendations for future research and implementation in the context of climate resilience and circular economy principles are discussed.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.36948/ijfmr.2026.nssfigtma-2025.2017first seen 2026-06-29 09:02:33
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