Based on the current study’s analysis, nanofluid performance is sensitive to the sequence of cooling stages rather than just the final temperature. Water+CuO adapts efficiently across successive cooling steps, while Water+Au shows dependency on intermediate conditions before reaching optimal performance. This indicates that cooling history plays a role in nanofluid effectiveness, a factor often overlooked in conventional analysis.

Based on the current study’s analysis, transient thermal oscillations are more pronounced in Water and Water+Ag compared to other nanofluids. These fluctuations suggest intermittent heat transfer efficiency during stabilization phases, whereas Water+CuO exhibits smoother transitions. Such transient behavior, though subtle, can influence long-term system reliability.

Based on the current study’s analysis, a damping effect introduced by nanoparticles becomes evident. Water+Al₂O₃ shows a gradual thermal response that reduces sharp temperature gradients, acting as a buffer during cooling transitions. This behavior, although less aggressive in cooling rate, helps minimize thermal shock—an aspect often neglected when evaluating peak performance alone.

Based on the current study’s analysis, it is observed that nanofluids respond differently under extreme cooling conditions compared to moderate ones. Water+Cu maintains consistent performance even when temperature changes are abrupt, whereas Water+Au and Water+Ag perform better once the system approaches a stable regime. This indicates that some nanofluids are more resilient to rapid thermal disturbances, while others favor steady-state operation.

Based on the current study’s analysis, it is evident that nanofluids not only differ in overall efficiency but also in how steadily they manage transitions during C (Thermo-Electric Cooler Temperature) fluctuations. Water+Cu demonstrates strong adaptability, maintaining stable performance across both sharp and mild cooling shifts, whereas Water+Au, though generally efficient, tends to stabilize more slowly, hinting at nanoparticle clustering effects. Water+Ag shows a tendency for quick initial cooling followed by small oscillations, which suggests uneven thermal dispersion under fluctuating loads. In contrast, Water+Al₂O₃ provides a slower but smoother cooling response, making it advantageous in systems where avoiding sudden temperature shocks is critical. A finer detail often overlooked is that water alone not only lags in efficiency but also amplifies temperature swings, creating thermal stress on the system. These subtle differences highlight that beyond conductivity, nanoparticle stability and response time are key in selecting nanofluids for dynamic thermal management.