Polymer-based Resistive Switching Device
The structural characteristics of ultra-thin solid polymer thin film are considered to play a crucial role in both cation and anion transport behaviors. Mostly, polymer thin films that are confined to the characteristic nano-scale can cause anisotropy in the polymer chain orientation. This anisotropic polymer chain orientation is important for the functionalization because the electrical, optical, and mechanical properties of polymer films much depend on the degree and direction of the polymer chain orientation.
Redox-mediated electrochemical metallization (ECM) devices, comprising of a metal/insulator/metal (MIM) structure showing resistive switching characteristics, which are key for many technological perspectives. In particular, controlling of ionic/charge transport on the characteristic nano-scale can explore new strategy in the development of atomic/molecular electronics with high-speed operation and less power consumption. Significantly, the quantum transport in which the conductance could exhibit discrete quantized states, becomes more pronounced when the lateral dimension of the conducting transport pathway is equivalent to the Fermi wavelength. Nevertheless, quantum conductance in ECM memory systems due to the confined redox-reaction is of particular interest, not only because of the opportunity it offers to investigate electronic transport for atomic contact, but also due to the potential benefit in the development of quantum information systmes such as high-density multilevel memories, logic-in-memory, and synaptic devices, etc,.
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Quantum conductance behavior is mostly observed in the two broad classes of switching devices, based on the ECM and valence change memory (VCM) principle. Mostly, the ECM principle is originated in the organic polymer-based devices by the redox-induced nanoionics phenomenon, whereas, VCM principle is originated in the inorganic- based devices by the oxygen vacancy-mediated migration phenomenon. As compared with inorganic devices, polymer-based organic devices offer excellent opportunity in the development of atomic-scale devices due to the highly confined ionic transport property and atomic growth in the interfacial regime at ambient conditions.
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Configurable Switching Behavior in the Polymer-based Memories
The poly(methyl methacrylate) (PMMA)-based resistive switching device with four different combinations of electrode/electrolyte arrangement in the device geometry influence the switching behavior. The I-V studies disclosed more stable nonvolatile memory behavior with higher ON/OFF resistance ratio in the PMMA-based devices. It is also found that the current conduction in filament and resistive switching behavior depends highly on the presence of Al electrode and electrochemically active silver (Ag) element in the PMMA matrix. Inclusion of Al as electrode in the device exhibits the trap-controlled space charge limited conduction (SCLC) mechanism constitute the resistive switching. But, addition of Ag in the device configuration unveils ohmic behavior in the current conduction, dominating the resistive switching characteristics by ECM mechanism. By using the depth-profiling XPS analysis, we discussed the effects of the device configuration on the conducting channel formation for resistive switching operation. These results with different conduction mechanisms provide new insights into the understanding of the resistive switching behavior in the resistive memory devices by simply modifying the device architecture. The obtained knowledge is also applicable for other resistive switching devices.
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Figure. Schematic illustration of the proposed switching mechanisms for (a) Al/PMMA/Al, (b) Al/AgNP-PMMA/Al, (c) Al/Ag/PMMA/Al, and (d) Al/Ag/AgNP-PMMA/Al devices under biasing conditions.
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Organic Polymer-based Memristor for Multilevel Memory
By introducing the synaptic plasticity, we could circumvent the von Neumann bottleneck, traditional binary data storage mechanism observed in the conventional computing systems and move forward to the more complex multilevel data storage system for the advanced neuromorphic device. These results demonstrated that the device showed the feasibility of multilevel data storage by modulating the I-V measurement parameters. Following Figure shows the schematic representation of the conductance modulation in the memristor devices by confining the QPC region and the fabricated large array of cross-point structured memristor device. As we know that, classical system works either ON/OFF or ‘0’/’1’ (2^1 states= 2 bits per cell) but the QPC enabled memristors works with many possible states, i.e. more than 1 level, interpreting more than 2-bits per cell is possible.
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Figure. Schematic representation of the narrowest region of the quantum point contact (QPC) in the memristor for single to multi-atom point contact. (b) Fabricated large array of memristor for high-density multilevel memory storage.
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Organic Polymer-based Memristor for Neuromorphic Computing
Controlling of quantum point contact (APC) in memristive devices is considered as an essential approach in mimicking biological synaptic functions and paves the way for future neuromorphic computing systems. In our research, we demonstrated the modulation of conductance in a polymer-based memristor that mimics the synaptic functions underlying the sensory memory (SM), short-term memory (STM), long-term memory (LTM) and forgetting events of the human brain. A thorough investigations of conductance quantization and synaptic characteristics of the polymer-based memristor is progressed by means of DC sweep and pulse current-voltage (I-V) measurements. Owing to the highly controlled synaptic plasticity of the memristor, the biological synaptic events such as learning / forgetting behaviours are emulated. This study is essential in understanding and implementing the artificial memristive synapses for developing neuromorphic computing devices.
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Figure. The resistive switching mechanisms for stacked a,b) Ag–PEO, c,d) PEO, and e,f) Ag–PEO devices with differnt electrode configurations under forward bias and reverse bias, respectively.
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