The Effect of Compression on the Morphological and Electrical Properties of Semiconducting Nanosheet Networks
Source abstract
Abstract
Solution-processed networks of two-dimensional (2D) semiconducting nanosheets are promising for flexible and printed electronics but often suffer from limited electrical properties due to poor inter-nanosheet charge transport. We examine how uniaxial mechanical compression alters the morphology and electrical properties of networks made from liquid-phase-exfoliated WS 2 nanosheets of varying sizes. Compression reduces network thickness considerably (20–60%) and substantially smooths the surface. Three-dimensional imaging shows extensive porosity collapse and a strong decrease in tortuosity, with the most pronounced structural changes occurring in networks formed from the largest nanosheets. All networks display improved electrical conductivity after compression, and the enhancement increases systematically with nanosheet size, reaching a 20-fold increase for the largest sheets. Modeling the conductivity as a function of nanosheet length indicates that the average junction resistance is largely independent of nanosheet size, both before and after compression; however, compression reduces the junction resistance by roughly an order of magnitude. Temperature-dependent conductivity and impedance spectroscopy measurements further show that inter-nanosheet junctions remain point-like after compression, suggesting that the reduction in the junction resistance is caused by shortening of the effective hopping distance rather than converting point-like junctions into extended planar contacts. These findings clarify the mechanisms by which mechanical compression enhances charge transport and outline its capabilities and limitations for improving the electrical properties of solution-processed 2D networks.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: 2D Materials and Applications · Nanomaterials and Printing Technologies · Advanced Sensor and Energy Harvesting Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Physics, CRANN & AMBER Research Centres
Trinity College Dublin
Funding
Science Foundation Ireland · HORIZON EUROPE Digital, Industry and Space · Research Ireland
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