Spatial Cooling

Spatial cooling research focuses on efficiently managing heat dissipation in localized areas of complex systems, aiming to optimize temperature control and minimize energy consumption. Current efforts leverage machine learning, particularly neural networks (including convolutional and physics-informed architectures), and generative AI models to design and control cooling systems, often targeting specific applications like electronics thermal management and battery thermal management systems. These advanced modeling techniques offer significant improvements in speed and accuracy compared to traditional methods, leading to more efficient and effective cooling solutions across diverse technological domains. The resulting optimized designs promise enhanced performance and reduced energy waste in various applications.