AI-Powered Green Revolution: Radiation-Based Refrigeration Materials Lead the Future of Zero-Energy Buildings

Under the global wave of urbanization and digitization, the rapid increase in data centers and rising energy consumption have intensified climate change and environmental pressure. According to statistics, the construction industry contributes approximately 40% of global carbon emissions, with cooling energy consumption accounting for 8.5% of building electricity usage—a figure growing at a rapid pace. Traditional cooling methods, reliant on electricity and harmful refrigerants, further amplify carbon footprints, highlighting the urgency of developing green, low-carbon cooling technologies.

In this context, passive radiative cooling technology, with its characteristic of "zero-energy cooling," has emerged as a breakthrough direction in building energy efficiency. By leveraging high reflectivity in the solar spectrum and high emissivity in the mid-infrared band on material surfaces, this technology dissipates heat directly into space, achieving cooling without additional energy input. In recent years, with the deep integration of materials science and artificial intelligence (AI) technology, the design, optimization, and application of radiative cooling materials have entered a new stage of intelligence and precision.

AI technology is empowering the development of new radiative cooling materials in three key aspects:

1.    Intelligent Material Design and Performance Prediction
Leveraging machine learning and computational simulations, AI efficiently screens material combinations and predicts optical and thermal properties, significantly shortening R&D cycles and enabling the "on-demand design" of radiative cooling materials.

2.    Dynamic Control and System Optimization
Integrated with the Internet of Things (IoT) and smart sensing, AI analyzes real-time environmental parameters inside and outside buildings, dynamically adjusts the application strategies of cooling materials, and enhances their adaptability and energy efficiency in complex climatic conditions.

3.    Full Lifecycle Management and Service Innovation
Based on a data-driven Product-as-a-Service (PaaS) model, AI supports continuous monitoring and evaluation of material performance degradation, energy-saving effects, and carbon reduction outcomes, promoting the implementation of sustainable business models.

As a pioneer in this field, Jiangsu SmartCool Engineering Co., Ltd. has centered its efforts on "AI + Radiative Cooling," launching the "SmartCool" series of green energy-saving materials and establishing the T-ZELCA service system to achieve full-cycle management from material supply to performance assurance. In collaboration with partners such as Nantong Fanhua Construction Group, the company has implemented large-scale applications in various scenarios, including building exteriors, municipal facilities, 5G base stations, and hotel energy efficiency, demonstrating significant cooling and energy-saving effects in real-world environments.

Looking ahead, as AI technology further integrates with radiative cooling materials, building cooling systems will gradually shift away from reliance on traditional power systems, evolving toward zero-energy, adaptive, and tunable smart cooling systems. This will not only substantially reduce operational carbon emissions in buildings but also provide a practical technological pathway to address global high-temperature challenges and drive the green transformation of the construction industry.