Interfacial thermodynamics and data-driven design of polymeric nanofluids: Structure–property relationships, spectroscopic insights, and intelligent functional performance

Polymeric nanofluids have emerged as advanced multifunctional materials with significant potential in thermal management, energy systems, biomedical engineering, advanced manufacturing, and smart-material applications. Their performance is governed by complex interfacial interactions between nanoparticles and polymer matrices, which influence colloidal stability, rheological behavior, thermal transport, electrical conductivity, and long-term durability. This review provides a comprehensive overview of the fundamental interfacial science, structure–property relationships, and functional performance mechanisms governing polymeric nanofluids. Particular emphasis is placed on nanoparticle–polymer interactions, surface functionalization strategies, interphase formation, microstructural evolution, rheo-chemical coupling, thermal transport pathways, and electrokinetic phenomena. The review further highlights the application of advanced characterization techniques, especially ATR-FTIR spectroscopy and chemometric analysis, for elucidating molecular interactions and establishing quantitative structure–property correlations. Recent developments in machine learning, materials informatics, response surface methodology, and digital-twin frameworks are critically discussed as transformative tools for predictive modeling, formulation optimization, and real-time adaptive control. Key findings indicate that interfacial architecture and microstructural organization are the primary determinants of multifunctional performance, while data-driven approaches significantly accelerate materials discovery and optimization. Emerging directions involving stimuli-responsive nanofluids, artificial-intelligence-assisted design, sustainable formulations, and autonomous monitoring systems are also explored. By integrating molecular-level understanding with advanced analytical and computational approaches, this review establishes a unified framework for the rational design of intelligent, high-performance polymeric nanofluids and identifies future opportunities for their large-scale implementation in energy, environmental, biomedical, and industrial technologies.