journal article·2025-03-01Open access

Photo-enhanced output in memdiode devices based on hybrid materials

Jacob Lee, Prabir Patra, Xiaojuan Fan

AIP Advances· Volume 15· Issue 3

Abstract

The discovery of photo-enhanced outputs in the fabricated memdiodes based on metal halide-embedded polymeric hybrid composites has meaningful and practical implications. The two-terminal devices exhibit typical rectifying characteristics, similar to a standard pn junction diode, with unusual photo-enhanced charge transportation and hysteresis behaviors. The MDs consist of an active layer of blended organic–inorganic hybrid material [a mixture of CuCl2 and polyethylene glycol (PEG)] deposited on a layer of pure polymer (polymethyl methacrylate) and, in turn, on a rigid substrate (ITO glass or Si wafer). It is found that the photoinduced current increases hundreds of times in magnitude on the ITO glass-substrate sample, much higher than that of the Si-substrate sample. The substrate-dependent photocurrent can be attributed to charge carrier generation by optical absorption correlated with transport paths at different interfaces and variations of working areas by different substrates. The energy bandgaps extrapolated from the UV–Vis absorption spectroscopy are at 1.50 and 3.1 eV, consistent with two applied voltages at which the currents jump abruptly under light-on and light-off statuses, respectively. The study of time-dependent resistances displays an exponential decay, a memristive feature, and a long relaxation time between high-resistance and low-resistance. The memdiodes are stable with repeatable working values in a bio-applicable range, assuring that the hybrid materials are excellent candidates for potential applications in biomedical electronic circuits, artificial neuromorphic synapses, and brain-inspired quantum computing.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Semiconductor materials and devices · Semiconductor materials and interfaces

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Mathematics and Physics, Marshall University 1 , Huntington, West Virginia 25755,

Department of Computer Sciences and Electrical Engineering, Marshall University 2 , Huntington, West Virginia 25755,

Department of Biomedical Engineering, Marshall University 3 , Huntington, West Virginia 25755,

Funding

Louisiana NASA EPSCoR · West Virginia Science and Research, West Virginia Higher Education Policy Commission

References (23)

Show source-provided references
1. J. Phys. D: Appl. Phys. · 2013 · 46 · 09300110.1088/0022-3727/46/9/093001 ↗
2. IEEE Trans. Circuit Theory · 1971 · 18 · 50710.1109/tct.1971.1083337 ↗
3. Appl. Phys. A · 2011 · 102 · 76510.1007/s00339-011-6264-9 ↗
4. Appl. Phys. Lett. · 2022 · 120 · 04310110.1063/5.0078332 ↗
5. IEEE Electron Device Lett. · 2019 · 40 · 54210.1109/led.2019.2898443 ↗
6. Sci. Adv. · 2021 · 7 · eabh064810.1126/sciadv.abh0648 ↗
7. Sci. Rep. · 2018 · 8 · 1293510.1038/s41598-018-30727-9 ↗
8. Nano-Micro Lett. · 2021 · 13 · 8510.1007/s40820-021-00618-2 ↗
9. ACS Appl. Electron. Mater. · 2022 · 4 · 232610.1021/acsaelm.2c00161 ↗
10. Front. Neurosci. · 2021 · 15 · 66089410.3389/fnins.2021.660894 ↗
11. Adv. Electron. Mater. · 2019 · 5 · 180051910.1002/aelm.201800519 ↗
12. Sci. Adv. · 2022 · 8 · eade007210.1126/sciadv.ade0072 ↗
13. Sci. Adv. · 2018 · 4 · e170132910.1126/sciadv.1701329 ↗
14. Micromachines · 2022 · 13 · 33010.3390/mi13020330 ↗
15. Int. J. Circuit Theory Appl. · 2018 · 46 · 3910.1002/cta.2419 ↗
16. Nature · 2008 · 453 · 8010.1038/nature06932 ↗
18. Appl. Phys. A · 2022 · 128 · 9410.1007/s00339-021-05188-z ↗
19. AIP Adv. · 2015 · 5 · 04714310.1063/1.4919323 ↗
20. Thermochim. Acta · 2010 · 498 · 7110.1016/j.tca.2009.10.005 ↗
21. J. Comput. Theor. Nanosci. · 2014 · 11 · 77610.1166/jctn.2014.3427 ↗
22. J. Polym. Sci., Part B:Polym. Phys. · 2007 · 45 · 35810.1002/polb.21038 ↗
23. Phys. Rev. B · 1990 · 41 · 831310.1103/physrevb.41.8313 ↗