Thin film thermoelectrics offer compact energy-harvesting and precise cooling solutions for micro-electronics central to Internet of Things and Artificial Intelligence technologies. Advancing these applications requires rapid and reliable experimental screening methods to identify high-performance thermoelectric materials at the thin-film scale. Here, we present a semi-automated, Python-controlled platform for fast room-temperature evaluation of thin-film thermoelectric power factors. The system integrates a 3D-printed sample holder with built-in thermocouple probes, a sourcemeter, and a multimeter, all operated through a custom graphical user interface that enables streamlined, repeatable measurements of electrical conductivity and Seebeck coefficient with minimal user input. Benchmarking these measurements for metallic (Au, Ag, Ti) and transparent conducting oxide (ITO, FTO) thin films demonstrates excellent agreement with the reported ones in literature, accurately capturing both the magnitude and sign of the Seebeck coefficient across substrates with varying thermal conductivities. The metallic films exhibit small, positive Seebeck coefficients consistent with complex electronic structures near the Fermi level, while the transparent oxides show small negative values characteristic of degenerately doped n-type semiconductors. This robust, high-sensitivity platform provides a practical tool for rapid laboratory-scale screening and optimization of thin-film thermoelectric materials.
AlHamidi et al. (Fri,) studied this question.
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