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

arXiv:2604.28148v1 Announce Type: new Abstract: 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. The device integrates thermoelectric junctions with linear or nonlinear interlayer resistive elements to perform simultaneous sensing and in-sensor compression. We focus on the single-event (1-sparse) operation and define four performance metrics: range, efficiency, sensitivity, and accuracy. Numerical modeling shows that a linear resistive interlayer flattens the sensitivity distribution and improves minimum sensitivity by approximately tenfold for a 16imes16 mesh. Nonlinear temperature-dependent interlayers further enhance minimum sensitivity at scale: a ceramic negative-temperature-coefficient (NTC) layer over 973--1273K yields a sim14{,}500imes higher minimum sensitivity than the linear design at a 200imes200 mesh, while a VO_2 interlayer modeled across its metal--insulator transition (MIT) over 298--373K yields a sim24imes improvement. Using synthetic 1-sparse datasets with white boundary-channel noise at a signal-to-noise ratio of 40dB, the VO_2 case achieved 98% localization accuracy, a mean absolute temperature error of 0.23K, and a noise-equivalent temperature (NET) of 0.07K. For the ceramic-NTC case no localization errors were observed under the tested conditions, with a mean absolute temperature error of 1.83K and a NET of 1.49~K. These results indicate that ThermoMesh could enable energy-efficient embedded thermal sensing in scenarios where conventional infrared imaging is limited, such as molten-droplet detection or hot-spot monitoring in harsh environments.

Source: arXiv cs.RO | 2026-05-01