Many metal–insulator–metal systems show electrically induced resistive switching effects and have therefore been proposed as the basis for future non-volatile memories. They combine the advantages of Flash and DRAM (dynamic random access memories) while avoiding their drawbacks, and they might be highly scalable. Here we propose a coarse-grained classification into primarily thermal, electrical or ion-migration-induced switching mechanisms. The ion-migration effects are coupled to redox processes which cause the change in resistance. They are subdivided into cation-migration cells, based on the electrochemical growth and dissolution of metallic filaments, and anion-migration cells, typically realized with transition metal oxides as the insulator, in which electronically conducting paths of sub-oxides are formed and removed by local redox processes. From this insight, we take a brief look into molecular switching systems. Finally, we discuss chip architecture and scaling issues.

http://chialvo.org/Curso/UBACurso/DIA7/Papers/Aono_NatMat_07_Ionic%20Switching%20Memory.pdf

Nanoionics-based resistive switching memories

Redox‐Based Resistive Switching Memories – Nanoionic Mechanisms, Prospects, and Challenges

Bose-Einstein condensation (BEC) has been observed in a dilute gas of sodium atoms. A Bose-Einstein condensate consists of a macroscopic population of the ground state of the system, and is a coherent state of matter. In an ideal gas, this phase transition is purely quantum-statistical. The study of BEC in weakly interacting systems which can be controlled and observed with precision holds the promise of revealing new macroscopic quantum phenomena that can be understood from first principles.

Bose-Einstein condensation in a gas of sodium atoms

Memristive devices are electrical resistance switches that can retain a state of internal resistance based on the history of applied voltage and current. These devices can store and process information, and offer several key performance characteristics that exceed conventional integrated circuit technology. An important class of memristive devices are two-terminal resistance switches based on ionic motion, which are built from a simple conductor/insulator/conductor thin-film stack. These devices were originally conceived in the late 1960s and recent progress has led to fast, low-energy, high-endurance devices that can be scaled down to less than 10 nm and stacked in three dimensions. However, the underlying device mechanisms remain unclear, which is a significant barrier to their widespread application. Here, we review recent progress in the development and understanding of memristive devices. We also examine the performance requirements for computing with memristive devices and detail how the outstanding challenges could be met.

Memristive devices for computing

Despite much progress in semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex, with its approximately 10(14) synapses, makes the hardware implementation of neuromorphic networks with a comparable number of devices exceptionally challenging. To provide comparable complexity while operating much faster and with manageable power dissipation, networks based on circuits combining complementary metal-oxide-semiconductors (CMOSs) and adjustable two-terminal resistive devices (memristors) have been developed. In such circuits, the usual CMOS stack is augmented with one or several crossbar layers, with memristors at each crosspoint. There have recently been notable improvements in the fabrication of such memristive crossbars and their integration with CMOS circuits, including first demonstrations of their vertical integration. Separately, discrete memristors have been used as artificial synapses in neuromorphic networks. Very recently, such experiments have been extended to crossbar arrays of phase-change memristive devices. The adjustment of such devices, however, requires an additional transistor at each crosspoint, and hence these devices are much harder to scale than metal-oxide memristors, whose nonlinear current-voltage curves enable transistor-free operation. Here we report the experimental implementation of transistor-free metal-oxide memristor crossbars, with device variability sufficiently low to allow operation of integrated neural networks, in a simple network: a single-layer perceptron (an algorithm for linear classification). The network can be taught in situ using a coarse-grain variety of the delta rule algorithm to perform the perfect classification of 3 × 3-pixel black/white images into three classes (representing letters). This demonstration is an important step towards much larger and more complex memristive neuromorphic networks.

Training and operation of an integrated neuromorphic network based on metal-oxide memristors

Discusses fabrication of electrically variable shallow junction MOSFETs (EJ-MOSFETs) to investigate transistor characteristics in ultra-fine gate MOSFETs. By using electron beam (EB) lithography and an ultra-high resolution resist (Calixarene), we could achieve a gate length of 30 nm for the first time. Since the short-channel effects are effectively suppressed by electrically induced ultra-shallow source/drain regions in the structure, the fabricated device exhibited normal transistor characteristics in the 30-nm-gate-length regime at 300 K.

Transistor operations in 30-nm-gate-length EJ-MOSFETs

This chapter introduces the applications of atomic switches, which are expected to be used for sensor systems in space. Artificial satellites are regarded as the sensor nodes and communication relay nodes of Internet of Things (IoT). Processor elements using atomic switch field programmable gate array (FPGA) are anticipated as essential element for building embedded system applications for the IoT. We start by looking at the role played by embedded system processors first and point out that leaving from stored program architecture is inevitable and essential to achieve processing speed and low power consumption required for embedded system applications. Space-born sensor application is referred in this chapter as an example of embedded system applications because space systems are somewhat specialized but in many ways typical embedded applications intended to be used for IoT applications which require dependability as an essential feature. We also introduce Generic Processor element (GPE) architecture to exploit atomic switches. GPE architecture is based on the embedded automaton realized with the contribution of high-level behavioral synthesis technology. Practical application implementation on the reconfigurable processor is realized using the matured tool of high-level behavioral synthesis technology.

Atomic Switch FPGA: Application for IoT Sensing Systems in Space

PROBLEM TO BE SOLVED: To easily check the state of a resistance change element.SOLUTION: A semiconductor integrated circuit includes a crossbar switch circuit, and a determination circuit 102 which measures the electric potential of a data output side wiring of a reconfigurable circuit including the crossbar switch circuit, compares the measured electric potential with a predetermined electric potential threshold, and, on the basis of the result of the comparison, determines a failure of the crossbar switch circuit targeted in the reconfigurable circuit.SELECTED DRAWING: Figure 23

Semiconductor integrated circuit and method of operating the same

Solid-electrolyte nanometer switch implemented in Si LSI

A switching element is provided with a first electrode (14) and a second electrode (15) arranged at a prescribed interval; a solid electrolytic layer (16) brought into contact with the first electrode (14) and the second electrode (15); a third electrode (18) which is brought into contact with the solid electrolytic layer (16) and can supply a metal ion; and a metal diffusion preventing film (17) for covering a portion on the surface of the solid electrolytic layer (16) not covering any of the first electrode (14), the second electrode (15) and the third electrode (18). Thus, metal ion is prevented from affecting other elements.

Toshitsugu Sakamoto

Papers

Transistor operations in 30-nm-gate-length EJ-MOSFETs

Atomic Switch FPGA: Application for IoT Sensing Systems in Space

Semiconductor integrated circuit and method of operating the same

Solid-electrolyte nanometer switch implemented in Si LSI

Solid electrolytic switching element, method for manufacturing such solid electrolytic switching element and integrated circuit