Polyoxometalates‐Modulated Reduced Graphene Oxide Flash Memory with Ambipolar Trapping as Bidirectional Artificial Synapse

Abstract

operation per second) with ultralow power consumption. [1,2] The biological synapses are fast conductive connections between typical cortical neurons which is capable to transmit and receive electrochemical signals. [3] The parallel data processing is ensured since the neurons have one to ten thousand synapse links to connect with each other. Inspired by the high efficient brain, emerging nanoelectronic devices and complementary metal-oxide-semiconductor technology have been recently demonstrated to emulate the synaptic functions including short-term potentiation (STP), long-term potentiation (LTP), long-term depression (LTD), paired-pulse facilitation (PPF), paired-pulse depression (PPD), and post-tetanic potentiation, which are expected to settle the von Neumann architecture bottleneck. [4][5][6][7] In biological synapse, the plasticity defined as signal-modulated conductivity originated from ion movements is less than 15% in term of asymmetric behavior which is related to signal direction. [8] The LTP and LTD observed in biological synapses correspond to the continuously increased and decreased conductivity in the artificial counterpart in which the desirable variation should be both symmetric (direction of change) and linear (differential magnitude). [2] One of the most vigorously studied synaptic devices is memristor which can be operated between the high resistance state and the low resistance state with continuous internal resistance states with applied bias history. [9][10][11][12][13] Nevertheless, it is hard for memristors to exhibit either linear or symmetric conductivity variation in function with successive SET and RESET operations. Alternatively, integrating augmentative functionalities into a single synapse to enhance the plasticity and parallelism allows the development of robust neuromorphic circuit. [14] Field-effect transistor (FET)-based flash memory with an extra gate-control is promising to achieve hysteresis for mimicking dynamic, linear plasticity. In this structure, the charge carriers can be trapped and released from the charge trapping sites by reversed polarity of bias conducted programming and erasing operations in which the type of trapped charge carriers can be verified by judging the shifting direction of the threshold voltage (V th ). [15][16][17][18][19][20][21][22][23][24] For Employing flash memories that function as the analogue synapse cleft for implementation of neural systems is a popular approach. For practical application in synapse mimicking, ambipolar trapping of both holes and electrons enables the weight updated linearity, symmetric conductivity variation, and desired variation margin, which are consistent with biological synapse. Nevertheless, most of the flash memory exhibits unipolar charge trapping behavior. Here, the first polyoxometalates (POMs)-modulated reduced graphene oxide (RGO)-based flash memory with ambipolar charge trapping characteristics is reported. Keggin type [PW 12 O 40 ] 3− (PW) is selected to function as both catalyst for in situ photoreduction ...

Bioinspired Artificial Sensory Nerve Based on Nafion Memristor

“…Figure a,b shows typical I–V curves of the Nafion‐based memristor as a function of consecutive positive bias sweeps from 0 to 0.5 V and negative bias sweeps from 0 to −0.5 V, respectively. Different from devices which exhibit abrupt conductance change in resistive random access memories (RRAMs) with binary states, the conductance of Nafion‐based memristor varies gradually under both positive and negative scans, which is fingerprint for synaptic devices . Moreover, a dynamic negative differential resistance (NDR) behavior in which decreased current responding to increased applied voltage is observed during negative bias scan .…”

“…The fitted short‐term phase decay time τ 1 is 410 ms and long‐term phase decay time τ 2 is 2710 ms, respectively. [12,24a] The inset of Figure d shows the influence of pulse width on PPF index, which increases exponentially from 5% to 97% as the pulse width increased from 10 ms to 1 s. Given that the latter spike is reinforced by the residual migration species triggered by the former spike, which do not have sufficient time to diffuse back, both shorter interval and wider width are favorable for the facilitation . Figure e exhibits the PPF index and post‐tetanic potentiation index (PTP, ( A 10 − A 1)/ A 1) with respect to different temperatures.…”

Photon assisted-inversion of majority charge carriers in molecular semiconductor-based organic heterojunctions

“…Such materials have demonstrated high prospects in CMOS-like inverters in which n-type and ptype transistors can be replaced by one ambipolar transistor, enabling simpler circuit designs, reducing the power dissipation and improving the switching efficiency, 2, 3 as well as in high density data storage, 4 photonic memory 5 and artificial synapses. 6 Chemical sensors are another widely researched area inspiring numerous studies on organic semiconductors, but only a few deal with ambipolar carrier transport despite of their advantages of dual mode operation (device operating at negative and positive bias), bias-dependent selectivity, 7 miniaturized multiplexed detection platforms and lower fabrication cost compared to their inorganic counterparts.…”

Floating-gate photosensitive synaptic transistors with tunable functions for neuromorphic computing

“…The coexistence of computing and memory in synapses has inspired scientists to imitate synapse functions to overcome the "von Neumann bottleneck" of traditional digital computers [7,14,[36][37][38][39]. Over the past few years, floating-gate transistors have received extensive attention in mimicking synaptic functions because of their gate controllable channel conductance and nonvolatile memory effect [40][41][42]. Since our floating-gate device has two control terminals (gate voltage and light), it can realize adjustable synaptic functions, thus providing the possibility of building a robust neural circuit for different application scenarios.…”