Remarkable Electrical Conductivity Increase and Pure Metallic Properties from Semiconducting Colloidal Nanocrystals by Cation Exchange for Solution-Processable Optoelectronic Applications
The authors report a strategic approach to achieve metallic properties from semiconducting Cu-Fe-S colloidal nanocrystal (NC) solids through cation exchange method. An unprecedentedly high electrical conductivity is realized by the efficient generation of charge carriers onto a semiconducting Cu-S NC template via minimal Fe exchange. An electrical conductivity exceeding 10 500 S cm−1 (13 400 S cm−1 at 2 K) and a sheet resistance of 17 Ω/sq at room temperature, which are among the highest values for solution-processable semiconducting NCs, are achieved successfully from bornite-phase Cu-Fe-S NC films possessing 10% Fe atom. The temperature dependence of the corresponding films exhibits pure metallic characteristics. Highly conducting NCs are demonstrated for a thermoelectric layer exhibiting a high power factor over 1.2 mW m−1K−2 at room temperature, electrical wires for switching on light emitting diods (LEDs), and source–drain electrodes for p- and n-type organic field-effect transistors. Ambient stability, eco-friendly composition, and solution-processability further validate their sustainable and practical applicability. The present study provides a simple but very effective method for significantly increasing charge carrier concentrations in semiconducting colloidal NCs to achieve metallic properties, which is applicable to various optoelectronic devices.
S.E.Y., Y.K., H.K., and H.-G.K. contributed equally to this work. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (NRF-2021R1A2C1007304, NRF-2021M3H4A1A02049634, NRF-2021K1A4A7A03093851, 2022M3H4A1A03076093, 2019R1A6A1A11051471, 2021R1A5A6002853, 2020R1A2C1004943, and 2021M3H4A3A01062960). The computational resources were provided by UNIST-HPC and KISTI (KSC-2020-CRE-0164).S.E.Y., Y.K., H.K., and H.‐G.K. contributed equally to this work. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (NRF‐2021R1A2C1007304, NRF‐2021M3H4A1A02049634, NRF‐2021K1A4A7A03093851, 2022M3H4A1A03076093, 2019R1A6A1A11051471, 2021R1A5A6002853, 2020R1A2C1004943, and 2021M3H4A3A01062960). The computational resources were provided by UNIST‐HPC and KISTI (KSC‐2020‐CRE‐0164).