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pmid: 30652478
Recently, multifunctional devices printed on flexible substrates, with multisensing capability, have found new demand in practical fields of application, such as wearable electronics, soft robotics, interactive interfaces, and electronic skin design, revealing the vital importance of precise control of the fundamental properties of metal oxide nanomaterials. In this paper, a novel low-cost and scalable processing strategy is proposed to fabricate all-printed multisensing devices with UV- and gas-sensing capabilities. This undertaken approach is based on the hierarchical combination of the screen-printing process and laser irradiation post-treatment. The screen-printing is used for the patterning of silver interdigitated electrodes and the active layer based on anatase TiO2 nanoparticles, whereas the laser processing is utilized to fine-tune the UV and ethanol-sensing properties of the active layer. Different characterization techniques demonstrate that the laser fluence can be adjusted to optimize the morphology of the TiO2 film by increasing the contribution from volume porosity, to improve its electrical properties and enhance its UV photoresponse and ethanol-sensing characteristics at room temperature. Furthermore, results of the UV and ethanol-sensing investigation show that the optimized UV and ethanol sensors have good repeatability, relatively fast response/recovery times, and excellent mechanical flexibility.
flexible substrates; laser processing; multifunctional sensors; screen-printing; titanium dioxide
flexible substrates; laser processing; multifunctional sensors; screen-printing; titanium dioxide
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 61 | |
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
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