Programmable interfacial Nanofluids for high-heat-flux Chip cooling via heat networks

To overcome thermal bottlenecks in high–heat-flux chip cooling, we develop a programmable interfacial nanofluid (CuO@APTES/L-cysteine/SSA) through surface molecular engineering integrated with a multiscale framework spanning material synthesis, density functional theory (DFT), molecular dynamics (MD), microchannel experiments, and computational fluid dynamics (CFD) validation. DFT calculations confirm robust interfacial stability enabled by Si–O–Cu anchoring, yielding a total binding energy of −33.48 eV. Spectroscopic and microscopic characterizations verify ordered multilayer functionalization, defining a grafting maximum load (GML) of 174.97% and excellent dispersion stability (zeta potential up to +59 mV). At 358.15 K and 2.5 vol%, the nanofluid achieves a thermal conductivity of 1.517 W/m·K (138.5% enhancement over water), significantly exceeding Maxwell predictions, with the optimized S30.4 formulation reaching 1.79 W/m·K. Molecular-level analysis reveals a transition from passive to programmable interfacial heat transport, characterized by enhanced Cu O radial distribution functions, increased coordination numbers, and strengthened Si O and O S heat-transfer pathways. Microchannel experiments demonstrate a 14.7% reduction in junction temperature and a 17.3% improvement in temperature uniformity at 10 W/cm 2 , accompanied by reduced thermal resistance and improved convective heat transfer. CFD predictions agree well with experiments (deviation <1.5%) and confirm superior cooling performance up to 10,000 W/cm 2 with only a modest pressure-drop penalty. Thereby establishing a validated multiscale framework that provides predictive insight into interfacial heat transport and guides the design of advanced nanofluids for high–heat-flux electronic cooling.