人工智能辐射冷却技术

IF 4.6 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

iScience Pub Date : 2024-11-05 DOI:10.1016/j.isci.2024.111325

Yeongju Jung , Seung Hwan Ko

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引用次数: 0

摘要

随着可持续热管理成为全球优先考虑的问题，辐射冷却（RC）技术的发展近来成为一种前景广阔的解决方案。与此同时，最近出现的人工智能（AI）为当前的可持续冷却战略研究提供了革命性的潜力。本文讨论了通过整合人工智能推进辐射冷却技术，解决传统方法中出现的挑战性问题，并为解决全球性问题提供战略性解决方案。人工智能能够通过各种算法模仿或超越人类的能力，从而有效优化 RC 结构。此外，将人工智能与先进的 RC 技术相结合，可以进一步加快 RC 领域的发展，这些技术有可能超越传统的 RC 结构和应用，但目前仍处于早期阶段。因此，人工智能驱动的 RC 技术将有助于应对日益普遍的环境挑战，并随着这些技术的不断成熟，进一步成为下一代可持续热管理的领先解决方案。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Radiative cooling technology with artificial intelligence

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Radiative cooling technology with artificial intelligence

As sustainable thermal management becomes a global priority, the development of radiative cooling (RC) technology has recently emerged as a promising solution. Simultaneously, recent advent of artificial intelligence (AI) offers the potential to revolutionize current research in sustainable cooling strategies. This article discusses the advancement of radiative cooling technology through the integration of AI, tackling the challenging issues arising from the conventional approach and offering strategic solutions to address global issues. AI, capable of mimicking or exceeding human capabilities through various algorithms, enables the efficient optimization of RC structures. Moreover, integrating AI with advanced RC technologies, which have the potential to surpass traditional RC configurations and applications but are still in the early stages, can further accelerate progress in the field of RC. Hence, AI-driven RC technologies will contribute to addressing the increasingly prevalent environmental challenges, further being a leading solution for next-generation sustainable thermal managements as these technologies continue to mature.

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来源期刊

iScience Multidisciplinary-Multidisciplinary

CiteScore

7.20

自引率

1.70%

发文量

1972

审稿时长

6 weeks

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