ZnO/GaN heterojunction based self-powered photodetectors: Influence of interfacial states on UV sensing
Source abstract
Abstract
Abstract Gallium Nitride (GaN) and Zinc Oxide (ZnO) are well established semiconductors with their heterostructures opening avenues for the future of next generation sensing and opto-electronics technologies due to their low lattice mismatch and high exciton energy. ZnO/GaN heterostructure based ultraviolet photodetectors with complimentary material properties are expected to yield optimum efficiency, though their performance has remained low due to challenges related to interfacial properties. Inadequate analysis of ZnO/GaN interfacial properties/states viz. electronic structure, band offsets, localized charge density and defect states associated with overlayer (i.e. ZnO) thickness, and their influence on device performance has remained as an underestimated issue. Interestingly, literature reports a huge anomaly in the valence band offset (VBO) at ZnO/GaN interfaces, which being an effective measure of charge transport assist in the optimization of photodetector efficiency. Therefore, in the present report, we have fabricated ZnO/GaN heterostructure (with variable ZnO thickness) based Schottky barrier photodectors and investigated the dependence of photosensitivity & other device parameters on interfacial states/properties. We have witnessed a peak responsivity & detectivity of 225 mA/W−1 & 4.83 (×1013) Jones and a high speed photoswitching associated with the band offset, barrier height & defect states at the ZnO/GaN heterojunction. The underlying scientific phenomenon (e.g. interfacial dipole strength, charge accumulation etc.) leading to perturbations & discontinuities in interfacial/electronic states were also correlated and discussed in detail.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Ga2O3 and related materials · ZnO doping and properties · GaN-based semiconductor devices and materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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