journal article·2024-04-12

Scanning Tunneling Microscopy Investigation of Synaptic Behavior in AgInS2 Quantum Dots: Effect of Ion Transport in Neuromorphic Applications

Atanu Betal, Anupam Chetia, Jayanta Bera, Dibyajyoti Saikia, Ashish Sharma, Arup K. Rath, Satyajit Sahu

ACS Applied Nano Materials· Volume 7· Issue 7
Publisher page

Abstract

Scanning tunneling microscopy (STM) is a powerful technique for investigating the nanoscale properties of functional materials. Additionally, scanning tunneling spectroscopy (STS) facilitates the determination of the local density of states (LDOS) within the material. In this study, we present an exploration of the resistive switching (RS) properties and neuromorphic computing capabilities of individual AgInS 2 quantum dots, utilizing STM and STS techniques. By examining the material’s bandgap and its temperature dependence, we uncover a nonlinear variation below the Debye temperature and a linear trend at higher temperatures. Moreover, STS measurements demonstrate changes in the conducting states induced by localized pulses, further confirming the unique characteristics of the quantum dots. The experimental devices constructed by using these quantum dots effectively replicate the RS properties observed at the nanoscale. To assess the neuromorphic application of the devices, pulse transient measurements simulating the learning and forgetting processes were conducted. The gradual set and reset processes successfully mimic the information retention and erasure capabilities essential for neuromorphic computing. Notably, the resistive switching mechanism in these devices is attributed to localized ionic transport, which highlights the significant involvement of ionic species in the observed RS behavior. The outcomes of this study contribute to the fundamental understanding of RS properties in single AgInS 2 quantum dots and offer valuable insights into their potential applications in neuromorphic computing.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Neuroscience and Neural Engineering · Photoreceptor and optogenetics research

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

Affiliations

Department of Physics, Indian Institute of Technology Jodhpur, Jodhpur 342037, India

National Chemical Laboratory, Council of Scientific and Industrial Research, Pune 411008, India

Academy of Scientific and Innovative Research, Ghaziabad 201002, India

Funding

Science and Engineering Research Board · Ministry of Education, India

References (59)

Show source-provided references
1. 10.1038/s41467-022-31157-y10.1038/s41467-022-31157-y ↗
2. 10.1038/s42254-020-0208-210.1038/s42254-020-0208-2 ↗
3. 10.1002/adem.20220031410.1002/adem.202200314 ↗
4. 10.1002/adfm.20180169010.1002/adfm.201801690 ↗
5. 10.1038/d41586-018-01683-110.1038/d41586-018-01683-1 ↗
6. 10.1002/gch2.20190001510.1002/gch2.201900015 ↗
7. 10.1016/j.mtphys.2021.10039310.1016/j.mtphys.2021.100393 ↗
8. 10.1002/adma.20190355810.1002/adma.201903558 ↗
9. 10.1038/s41586-019-1424-810.1038/s41586-019-1424-8 ↗
10. 10.3390/nano1008143710.3390/nano10081437 ↗
11. 10.1016/j.mattod.2023.04.01310.1016/j.mattod.2023.04.013 ↗
12. 10.1038/nmat305410.1038/nmat3054 ↗
13. 10.1002/adma.20170326110.1002/adma.201703261 ↗
14. 10.1002/adfm.20180372810.1002/adfm.201803728 ↗
15. 10.1002/adma.20180528410.1002/adma.201805284 ↗
16. 10.1063/5.009489210.1063/5.0094892 ↗
17. 10.1039/d2cp05014e10.1039/d2cp05014e ↗
18. 10.1088/1361-6528/aae47010.1088/1361-6528/aae470 ↗
19. 10.1002/adfm.20221266610.1002/adfm.202212666 ↗
20. 10.1063/1.504564310.1063/1.5045643 ↗
21. 10.1039/C9TC02802A10.1039/C9TC02802A ↗
22. 10.1063/5.011343310.1063/5.0113433 ↗
23. 10.1021/acsami.1c0320210.1021/acsami.1c03202 ↗
24. 10.1021/acs.jpclett.2c0196210.1021/acs.jpclett.2c01962 ↗
25. 10.1016/j.mee.2018.01.00910.1016/j.mee.2018.01.009 ↗
26. 10.1039/D2QM00614F10.1039/D2QM00614F ↗
27. 10.1002/admt.20180034210.1002/admt.201800342 ↗
28. 10.1063/1.475415010.1063/1.4754150 ↗
29. 10.1002/smll.20160430610.1002/smll.201604306 ↗
30. 10.1063/5.005044810.1063/5.0050448 ↗
31. 10.1021/nl401563810.1021/nl4015638 ↗
32. 10.1021/acsami.7b0971010.1021/acsami.7b09710 ↗
33. 10.1063/1.368352310.1063/1.3683523 ↗
34. 10.1002/adma.20180032710.1002/adma.201800327 ↗
35. 10.1002/aelm.20220085010.1002/aelm.202200850 ↗
36. 10.1002/celc.20130016510.1002/celc.201300165 ↗
37. 10.1063/1.327542610.1063/1.3275426 ↗
38. 10.1007/978-3-540-77899-8_610.1007/978-3-540-77899-8_6 ↗
39. 10.3390/nano1101008510.3390/nano11010085 ↗
40. 10.1103/PhysRevLett.86.575110.1103/PhysRevLett.86.5751 ↗
41. 10.3390/ma703215510.3390/ma7032155 ↗
42. 10.1063/1.471488810.1063/1.4714888 ↗
43. 10.1002/adfm.20200294810.1002/adfm.202002948 ↗
44. 10.1038/nmat330710.1038/nmat3307 ↗
45. 10.1021/acsnano.5b0702010.1021/acsnano.5b07020 ↗
46. 10.1038/nnano.2015.22110.1038/nnano.2015.221 ↗
47. 10.1063/5.007294910.1063/5.0072949 ↗
48. 10.1021/acsaelm.1c0123410.1021/acsaelm.1c01234 ↗
49. 10.1088/0953-8984/21/39/39550210.1088/0953-8984/21/39/395502 ↗
50. 10.1103/PhysRevB.50.1795310.1103/PhysRevB.50.17953 ↗
51. 10.1103/PhysRevLett.77.386510.1103/PhysRevLett.77.3865 ↗
52. 10.1107/S002188981103897010.1107/S0021889811038970 ↗
53. 10.1016/j.apsusc.2012.05.09510.1016/j.apsusc.2012.05.095 ↗
54. 10.1016/j.chemosphere.2022.13529210.1016/j.chemosphere.2022.135292 ↗
55. Wiesendanger R. · 199410.1017/CBO9780511524356 ↗
56. 10.1016/0031-8914(67)90062-610.1016/0031-8914(67)90062-6 ↗
57. 10.1002/aelm.20210023710.1002/aelm.202100237 ↗
58. 10.1039/D3TC00227F10.1039/D3TC00227F ↗
59. 10.1016/j.commatsci.2014.05.01010.1016/j.commatsci.2014.05.010 ↗