Korea University · 工学
Professor Kyoungah Cho's research lab specializes in advanced thermoelectric materials and devices, focusing on the development of flexible, high-performance thin-film thermoelectrics using nanomaterials such as chalcogenide nanocrystals, silicon nanowires, and MXenes. The lab explores innovative fabrication techniques—like solution processing and top-down nanofabrication—to optimize thermoelectric efficiency, with an emphasis on enhancing the figure of merit (ZT) and scalability for wearable and portable energy harvesting. Additionally, the lab integrates machine learning to predict and improve the performance of hybrid energy devices combining photovoltaics and thermoelectrics.
Figures are computed from collected data and may differ slightly.
Abstract This paper demonstrates that thermal energy radiated from a human finger can be converted efficiently into electricity by a nanocrystal (NC) thin film that substantially suppresses thermal conduction, but still allows electric conduction. The converting efficiencies of the chalcogenide NC thin films with dimensions 40 µm × 20 µm × 20 nm, prepared on flexible substrates by a solution process, are maximized by adjusting the NC size. A Seebeck coefficient of S = 1829 µV K −1 , and a dimens
This study demonstrates the fabrication and characterization of a flexible thermoelectric (TE) power generator composed of silicon nanowires (SiNWs) fabricated by top‐down method and discusses its strain‐dependence analysis. The Seebeck coefficients of the p‐ and n‐type SiNWs used to form a pn‐module are 156.4 and −146.1 µV K −1 , respectively. The maximum power factors of the p‐ and n‐type SiNWs are obtained as 8.79 and 8.87 mW (m K 2 ) −1 , respectively, under a convex bending of 1.11%, respec
In this study, we used machine learning to predict the output power of hybrid energy devices (HEDs) comprising photovoltaic cells (PVCs) and thermoelectric generators (TEGs). For the five types of HEDs, eight different machine learning models were trained and tested with experimental data; the HED each had different interface materials between the PVCs and the TEGs. An artificial neural network (ANN) model, which is the most appropriate model, predicted the correlation between HED performance an
Abstract In this study, the thermoelectric characteristics of spin‐coated p‐Mo 2 C and n‐Mo 2 Ti 2 C 3 thin films and the scalability of MXene thin‐film thermoelectric generators (TFTEGs) constructed with pn modules are investigated. The in‐plane thermal conductivities are measured at room temperature to be 0.37 and 0.45 W (m K) −1 for the p‐Mo 2 C and n‐Mo 2 Ti 2 C 3 thin films, respectively. The dimensionless figures of merit ZT are determined to be 1.7 × 10 −5 and 2.6 × 10 −4 for the p‐Mo 2 C
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