Enhancing Heat Transfer and Thermal Management Efficiency in Micro Heat Sinks through Machine Learning Algorithms

The growing power densities and rapid miniaturisation of modern electronics necessitate advanced thermal management solutions beyond conventional heat sinks, which struggle with limited performance and adaptability. This research is the first of its kind to simultaneously combine machine learning, numerical simulations, and experimental investigations while incorporating manufacturing philosophies, creating a comprehensive methodology that establishes a new benchmark to provide holistic thermal management solutions. The proposed bioinspired designs via hybrid pin-fin structures inspired by mushrooms, scutoids, cruciform flowers, and flying fish represent a departure from conventional configurations. Due to strategic modifications, these unique geometries exhibited a 30-70% increase in heat transfer potential, coupled with reduced thermal resistance and enhanced flow manipulation. The research is also the first to systematically incorporate such complex nature-inspired structures into micro heat sinks, showing the potential for high thermal efficiency whilst addressing manufacturability. Additionally, the integration of machine learning significantly advanced the design process by enabling rapid, high-accuracy predictions of thermal characteristics and flow behaviours. Using ensemble learning and combined techniques the developed models achieved over 90% accuracy in predicting heat transfer coefficients and classifying complex flow regimes. This novel application of smart data-driven methods transformed the traditionally laborious optimisation process, reducing computational time by 60-70% and allowing realtime performance monitoring. The introduction of such predictive capabilities for HTC, new correlations, sustainability analyses, and a custom data pipeline for flow regime identification represents a leap forward in artificial intelligence use in heat transfer research. Furthermore, to enhance scalability, a hybrid production strategy integrating Lean, Agile, and Design for Manufacturing resulted in a 43% reduction in production cost, a 29% savings in energy consumption, and a 19% cut in carbon emissions. Therefore, the research findings align with UK Net Zero and the EU Green Deal and Digital Agenda goals to present a practical model for developing high-performance thermal management solutions with minimal detrimental environmental impact. Thus, this research bridges the gap between theoretical innovation and practical implementation, offering a transformative framework for next-generation thermal management by adding new dimensions and strategies in air-cooled, liquid-cooled, and flowboiling systems. Its contributions have a wide range of applications in high-performance electronics, automotive and aerospace thermal systems, and renewable energy technologies, setting a new benchmark for adaptable, efficient, and sustainable global cooling solutions.