Nanofluids for Efficient Energy Conservation and Process Intensification presents mathematical, numerical, and experimental methodologies of applying nanofluids in renewable and non-renewable energy conservation and process intensification. It explores the mechanisms for developing high-performance heat transfer and mass transfer hybrid nanofluids. Beginning with thermophysical and optical properties enhancement of nanofluids, the book covers nanoparticle synthesis, stabilization techniques, and life-cycle assessment (LCA). It delves into the use of ionanofluids in environmental remediation, hybrid nanofluids for carbon capture, and the role of nanofluids in solar thermal systems. The book also discusses the use of Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) to facilitate optimization and predictive modeling of nanofluid performance. This book will interest researchers, graduate students, and industry practitioners studying the advances in applications of nanofluids within mechanical and chemical engineering.