Effects of humidity on the electrical properties of thermal inkjet-printed films of copper tetrasulfonated phthalocyanine (CuTsPc) onto paper substrates
Source abstract
Abstract
The effects of humidity on the electrical properties of thermal inkjet-printed copper tetrasulfonated phthalocyanine (CuTsPc) films onto paper substrates are reported. DC electrical measurements revealed that sample resistance decreases from 1012 Ω in moderate vacuum to approximately 107 Ω at highly water-saturated atmosphere. This behavior is attributed to the creation of water pathways on the cellulose fibers that allow ionic species such as impurities, protons (H+), and dissociated Na+ ions from the CuTsPc molecules, to flow. The contribution of the CuTsPc molecules and their dissociated Na+ ions on the sample resistance was elucidated analyzing the electrical response of bare and printed paper substrates. An increase of relative humidity levels (RH) from 10 % to 40–45 % revealed an increase of current of four orders of magnitude for printed samples, whereas less than one order of magnitude was registered for bare paper substrates. Electrical measurements as a function of temperature have shown that moisture can inhibit the semiconducting properties of CuTsPc. Thermal gravimetric studies revealed that approximately 11 % of mass accounting to the presence of water is released above 70 °C, the same temperature in which the sample recovers its dry-state semiconducting behavior. The semiconducting properties of CuTsPc can also be observed upon white light illumination, whereas the charge carrier extraction is governed by the RH level. These results point out the important role of humidity on the electrical properties of paper-based organic, electronic, and optoelectronic devices.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Nanomaterials and Printing Technologies · Conducting polymers and applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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