Design and Characteristics of a Thin-Film ThermoMesh for the Efficient Embedded Sensing of a Spatio-Temporally Sparse Heat Source

This work presents ThermoMesh, a passive thin-film thermoelectric mesh sensor designed to detect and characterize spatio-temporally sparse heat sources through conduction-based thermal imaging. Numerical modeling shows that a linear resistive interlayer flattens sensitivity and improves minimum sensitivity roughly tenfold for a 16×16 mesh. A ceramic NTC layer over 973–1273 K yields ~14,500× higher minimum sensitivity than the linear design at a 200×200 mesh, while a VO₂ interlayer modeled across its metal–insulator transition over 298–373 K yields ~24× improvement. Using synthetic 1-sparse datasets with white boundary-channel noise at 40 dB SNR, the VO₂ case achieved 98% localization accuracy, mean absolute temperature error of 0.23 K, and noise-equivalent temperature of 0.07 K. For the ceramic NTC case, no localization errors were observed under the tested conditions, with mean absolute temperature error of 1.83 K and NET of 1.49 K. These results indicate ThermoMesh could enable energy-efficient embedded thermal sensing where conventional infrared imaging is limited, such as molten-droplet detection or hot-spot monitoring in harsh environments.