| Abstract | Screen printing is the most common method used for the production of printed electronics. Formulating copper (Cu) inks that yield conductive fine features with oxidation and mechanical robustness on low-temperature substrates will open up opportunities to fabricate cost-effective devices. We have formulated a screen-printable Cu metal-organic decomposition (MOD) ink comprising Cu formate coordinated to 3-(diethylamino)-1,2-propanediol, a fractional amount of Cu nanoparticles (CuNPs), and a binder. This simple formulation enables ∼70–550 μm trace widths with excellent electrical [∼8–15 mΩ/□/mil or 20–38 μΩ·cm] and mechanical properties with submicron-thick traces obtained by intense pulse light (IPL) sintering on Kapton and poly(ethylene terephthalate) (PET) substrates. These traces are mechanically robust to flexing and creasing where less than 10% change in resistance is observed on Kapton and ∼20% change is observed on PET. Solderable Cu traces were obtained only with the combination of the Cu MOD precursor, CuNP, and polymer binder. Both thermally and IPL sintered traces showed shelf stability (<10% change in resistance) of over a month in ambient conditions and 10–70% relative humidity, suitable for day-to-day fabrication. To demonstrate utility, light-emitting diodes (LEDs) were directly soldered to IPL sintered Cu traces in a reflow oven without the need for a precious metal interlayer. The LEDs were functional not only during bending and creasing of the Cu traces but even after 180 min at 140 °C in ambient air without losing illumination intensity. High definition television antennas printed on Kapton and PET were found to perform well in the ultrahigh frequency region. Lastly, single-walled carbon nanotube-based thin-film transistors on a silicon wafer were fabricated with a screen-printed Cu source and drain electrodes, which performed comparably to silver electrodes with mobility values of 12–15 cm² V−¹ s−¹ and current on/off ratios of ∼10⁵ and as effective ammonia sensors providing parts per billion-level detection. |
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