Advanced Science · 2024 · 19 citations · 54 references
Natural SciencesMaterials EngineeringMaterials ScienceElectronic MaterialsOptoelectronicsSynaptic PlasticityLong-term PotentiationLuminescent MaterialsOptoelectronic DevicesOptoelectronic MaterialsRare-earth-doped MaterialsSynaptic Strength RegulationEnergy ConsumptionLong-term Synaptic PlasticityNeuromorphic DevicesNeuromorphic HardwareNeuromorphic Synaptic MaterialsOptoelectronic PropertiesPersistent LuminescenceRare-earth-doped Luminescent Materials
Abstract Neuromorphic computation draws inspiration from the remarkable features of the human brain including low energy consumption, parallelism, adaptivity, cognitive functions, and learning ability. These qualities hold the promise of unlocking groundbreaking computational techniques that surpass the limitations of traditional computing systems. This paper reports a remarkable photo‐synaptic behavior in the field of rare earth ion‐doped luminescent oxides by using long‐persistent luminescence (LPL). This system utilizes electron trap states to regulate the synaptic behavior, operating through a fundamentally different mechanism from that of electronic‐based synaptic devices. To realize this strategy, Tb 3+ doped CaSnO 3 , which shows a significant LPL property under UV‐light excitation, is prepared. The luminescent system shows key neuromorphic characteristics such as paired‐pulse facilitation, pulse‐number/timing dependent potentiation, and pulse‐number/timing dependent short‐ to long‐term plasticity transition, which are required for realizing synaptic devices. This feature expands the way for advanced neuromorphic technologies employing light stimuli.
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Energy transfer in oxidic phosphors
G. Blasse · Physics Letters A · 1968 · 2.5K citations
Reservoir computing using dynamic memristors for temporal information processing
Chao Du, Fuxi Cai, Mohammed A. Zidan et al. · Nature Communications · 2017 · 993 citations · Full text