Dual‐Electrolyte Neuromorphic Transistor for Risk Detection and Image Processing
Source abstract
Abstract
Abstract The human brain is a highly efficient structure that can easily perform various complex tasks, such as shape recognition, presentation, and classification, while consuming minimal energy and occupying only a small volume. This study introduces a bio‐inspired electrolyte‐gated neuromorphic transistor that mimics the functionality of the human brain. A dual‐electrolyte structure combining lithium phosphorus oxynitride and lithium silicate achieves the best performance, with a mobility of 3.1 cm2 V−1 s−1, a paired‐pulse facilitation index of 162.6%, and nonlinearity coefficients of 0.02 and 0.03 (for potentiation and depression, respectively). Further, risk pre‐detection and image recognition are successfully demonstrated using the developed dual‐electrolyte synaptic transistors. A test conducted on the Modified National Institute of Standards and Technology database indicates an accuracy of 91.0%. Thus, the device has the potential to advance artificial vision systems.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Neuroscience and Neural Engineering · CCD and CMOS Imaging Sensors
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Material Science and Engineering Korea University Seoul 02841 Republic of Korea
KU‐KIST Graduate School of Converging Science and Technology Seoul 02841 Republic of Korea
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