2023
DOI: 10.1021/acsami.2c22754
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Flexibly Photo-Regulated Brain-Inspired Functions in Flexible Neuromorphic Transistors

Abstract: As an attractive prototype for neuromorphic computing, the difficultly attained three-terminal platforms have specific advantages in implementing the brain-inspired functions. Also, in these devices, the most utilized mechanisms are confined to the electrical gate-controlled ionic migrations, which are sensitive to the device defects and stoichiometric ratio. The resultant memristive responses have fluctuant characteristics, which have adverse influences on the neural emulations. Herein, we designed a specific… Show more

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Cited by 7 publications
(4 citation statements)
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“…Finally, the output layer generates the corresponding results. [ 58 ] NNs can be categorized into supervised and unsupervised learning algorithms. The main difference lies in the utilization of labeled data for supervised learning and unlabeled data for unsupervised learning.…”
Section: Resultsmentioning
confidence: 99%
“…Finally, the output layer generates the corresponding results. [ 58 ] NNs can be categorized into supervised and unsupervised learning algorithms. The main difference lies in the utilization of labeled data for supervised learning and unlabeled data for unsupervised learning.…”
Section: Resultsmentioning
confidence: 99%
“…Nowadays, a wide range of flexible devices has been developed, including flexible organic light-emitting diodes, 1,2 flexible transistors, [3][4][5] electronic/ionic skin, [6][7][8] flexible electrochromic devices (ECDs), [9][10][11][12] flexible actuators, 13,14 and flexible power supplies, 15 and so forth. These diverse, flexible devices have revolutionized user experience by providing a new level of convenience, portability, and versatility, enabling individuals to explore technology in innovative and exciting ways.…”
Section: Introductionmentioning
confidence: 99%
“…Currently, a new device prototype, namely, artificial optoelectronic synapse, is proposed to simultaneously perform sensing, memory, and processing functions. Various artificial synapse architectures based on memristors, field-effect transistors (FETs), and phase-change memory (PCM) , have been reported, which have the advantages of programmability, nonvolatility, low power consumption, and high density integration. However, due to their high manufacturing difficulty, slow write speed, and nonlinear synaptic weight problem, these devices cannot capture correlations and detailed features between data well, thereby reducing the information processing capability and image recognition accuracy of the devices.…”
Section: Introductionmentioning
confidence: 99%