Emulating Ebbinghaus forgetting behavior in a neuromorphic device based on low dimensional h-BN
Artificial synaptic devices that can mimic the biological synaptic functions of learning and forgetting are essential for the realization of neuromorphic computation, which could replace the von Neumann architecture. In this Letter, we have described a high-performing ultraviolet photodetector (wave...
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Veröffentlicht in: | AIP advances 2024-08, Vol.14 (8), p.085010-085010-6 |
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description | Artificial synaptic devices that can mimic the biological synaptic functions of learning and forgetting are essential for the realization of neuromorphic computation, which could replace the von Neumann architecture. In this Letter, we have described a high-performing ultraviolet photodetector (wavelength 375 nm) using thin films of single-layer hexagonal boron nitride (h-BN) for potential use in fabricating a neuromorphic device. Furthermore, the classical Ebbinghaus forgetting curve can be optimized using various parameters such as the optical pulse width, number of pulses, and frequency of pulses. Our results show that the characteristic time constant (τ) has much more variability, indicating better performance control than the Ebbinghaus exponent (β). Furthermore, the performance of the optical synapse is very stable for low energy consumption, as low as 2–3 pJ. |
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In this Letter, we have described a high-performing ultraviolet photodetector (wavelength 375 nm) using thin films of single-layer hexagonal boron nitride (h-BN) for potential use in fabricating a neuromorphic device. Furthermore, the classical Ebbinghaus forgetting curve can be optimized using various parameters such as the optical pulse width, number of pulses, and frequency of pulses. Our results show that the characteristic time constant (τ) has much more variability, indicating better performance control than the Ebbinghaus exponent (β). 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Furthermore, the performance of the optical synapse is very stable for low energy consumption, as low as 2–3 pJ.</description><subject>Biological computing</subject><subject>Boron nitride</subject><subject>Energy consumption</subject><subject>Neuromorphic computing</subject><subject>Pulse duration</subject><subject>Thin films</subject><subject>Time constant</subject><subject>Ultraviolet detectors</subject><issn>2158-3226</issn><issn>2158-3226</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNp9kctKAzEUhgdRsNQufIOAK4WpyWTSySy11AsU3eg65HLSpkwnNZmp-PbGThFXns05_Hz855ZllwRPCZ7RWzbFBaYYFyfZqCCM57QoZqd_6vNsEuMGpyhrgnk5ysRi2zeyc-0KLZRKaS37iKwPK-gOqoK13DsfkGuRRC30wW992K2dRgb2TgNSMoJBvkWN_0TGbaGNzreyQev8_uUiO7OyiTA55nH2_rB4mz_ly9fH5_ndMtcFp12exq9rKBln1JbUALMMFLaaMlOD0sSaFMqAIhSoJkaSSnJFKtC8ZsQqOs6eB1_j5UbsgtvK8CW8dOIgpH2EDJ3TDQha4IpYzTgnsqxpVWuooATOmS6LmYHkdTV47YL_6CF2YuP7kDaKgmLOOa0orRN1PVA6-BgD2N-uBIufdwgmju9I7M3ARu26dG3f_gN_A86zidc</recordid><startdate>20240801</startdate><enddate>20240801</enddate><creator>Sunny, Ashly</creator><creator>Thamankar, R.</creator><general>American Institute of Physics</general><general>AIP Publishing LLC</general><scope>AJDQP</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-3743-8180</orcidid><orcidid>https://orcid.org/0000-0002-1761-1970</orcidid></search><sort><creationdate>20240801</creationdate><title>Emulating Ebbinghaus forgetting behavior in a neuromorphic device based on low dimensional h-BN</title><author>Sunny, Ashly ; Thamankar, R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c283t-10699e45853f43de5f5eb0fc35d9ebc1fddddbdeb13e3c1da17a8b17ec8951fb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Biological computing</topic><topic>Boron nitride</topic><topic>Energy consumption</topic><topic>Neuromorphic computing</topic><topic>Pulse duration</topic><topic>Thin films</topic><topic>Time constant</topic><topic>Ultraviolet detectors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sunny, Ashly</creatorcontrib><creatorcontrib>Thamankar, R.</creatorcontrib><collection>AIP Open Access Journals</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>AIP advances</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sunny, Ashly</au><au>Thamankar, R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Emulating Ebbinghaus forgetting behavior in a neuromorphic device based on low dimensional h-BN</atitle><jtitle>AIP advances</jtitle><date>2024-08-01</date><risdate>2024</risdate><volume>14</volume><issue>8</issue><spage>085010</spage><epage>085010-6</epage><pages>085010-085010-6</pages><issn>2158-3226</issn><eissn>2158-3226</eissn><coden>AAIDBI</coden><abstract>Artificial synaptic devices that can mimic the biological synaptic functions of learning and forgetting are essential for the realization of neuromorphic computation, which could replace the von Neumann architecture. 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subjects | Biological computing Boron nitride Energy consumption Neuromorphic computing Pulse duration Thin films Time constant Ultraviolet detectors |
title | Emulating Ebbinghaus forgetting behavior in a neuromorphic device based on low dimensional h-BN |
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