Self-Sensing AlCrFeNiSi/Ti₃AlC₂ Nanolaminates Enable Innovative Temperature-Compensated Monitoring of Molten-Chloride Damage
Keywords:
AlCrFeNiSi nanolaminates, Ti₃AlC₂ sentinels, Molten-chloride corrosion, Resistance sensing, Interface engineeringAbstract
Molten chloride salts support high-temperature heat transfer and thermal-energy storage, but aggressive dissolution and unstable protective scales restrict structural-alloy durability. Multifunctional coatings integrating corrosion resistance with damage detection are therefore required for reliable molten-salt components. Existing inorganic coatings do not provide depth-resolved, temperature-compensated electrical warning before substrate breakthrough. This investigation establishes an innovative AlCrFeNiSi/Ti₃AlC₂ nanolaminate that combines chloride protection with embedded MAX-phase damage sentinels. Three modulation-period architectures were evaluated using composition-derived descriptors, geometrical calculations, four-terminal resistance sensing, temperature correction, electrochemical impedance spectroscopy, dissolved-metal monitoring, and event-triggered microscopy. A 3.50 µm coating containing 0.50 µm Ti₃AlC₂ produced a 14.29% full-coating MAX fraction. Interface density decreased from 13.33 to 3.33 µm⁻¹ across the L150–L600 architectures while phase proportions remained constant, isolating modulation-period effects. Changing H21S8 to H21S5 increased the Al/Si ratio by 60%, whereas configurational entropy decreased by only 2.6%. Idealized conductive-area loss doubled normalized resistance at 50% remaining area and increased it tenfold at 10%, demonstrating nonlinear damage sensitivity. The architecture provides a quantitative platform for separating thermal, chemical, and mechanical resistance changes. It supports condition-based monitoring of thermal-storage and reactor components exposed to chloride melts. Future research validates warning lead, interfacial stability, and sensor durability through long-duration exposures and depth-correlated microscopy.
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