A bio-inspired physically transient/biodegradable synapse for security neuromorphic computing based on memristors

Nanoscale ◽  
2018 ◽  
Vol 10 (43) ◽  
pp. 20089-20095 ◽  
Author(s):  
Bingjie Dang ◽  
Quantan Wu ◽  
Fang Song ◽  
Jing Sun ◽  
Mei Yang ◽  
...  
Keyword(s):  
Silk Protein ◽  
Information Storage ◽  
Neuromorphic Computing ◽  
Protein Substrate

Fully degradable biomimetic synaptic devices based on a W/MgO/ZnO/Mo memristor on a silk protein substrate show remarkable information storage and synaptic characteristics.

Reliable analog resistive switching behaviors achieved using memristive devices in AlOx/HfOx bilayer structure for neuromorphic systems

2021 ◽  
Author(s):  
Meng Qi ◽  
Tianquan Fu ◽  
Huadong Yang ◽  
ye tao ◽  
Chunran Li ◽  
...  
Keyword(s):  
Resistive Switching ◽  
Learning Experience ◽  
Random Access ◽  
Resistive Random Access Memory ◽  
Spike Timing ◽  
Information Storage ◽  
Bilayer Structure ◽  
Neuromorphic Computing ◽  
Von Neumann ◽  
Simulation Based

Abstract Human brain synaptic memory simulation based on resistive random access memory (RRAM) has an enormous potential to replace traditional Von Neumann digital computer thanks to several advantages, including its simple structure, high-density integration, and the capability to information storage and neuromorphic computing. Herein, the reliable resistive switching (RS) behaviors of RRAM are demonstrated by engineering AlOx/HfOx bilayer structure. This allows for uniform multibit information storage. Further, the analog switching behaviors are capable of imitate several synaptic learning functions, including learning experience behaviors, short-term plasticity-long-term plasticity transition, and spike-timing-dependent-plasticity (STDP). In addition, the memristor based on STDP learning rules are implemented in image pattern recognition. These results may offer a promising potential of HfOx-based memristors for future information storage and neuromorphic computing applications.

scholarly journals A New Approach to the Fabrication of Memristive Neuromorphic Devices: Compositionally Graded Films

Materials ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 3680
Author(s):  
Jong-Gul Yoon
Keyword(s):  
Short Term Memory ◽  
Chemical Vapor ◽  
Complementary Metal Oxide Semiconductor ◽  
Information Storage ◽  
Oxide Semiconductor ◽  
Film Electrode ◽  
Retention Performance ◽  
Short Term ◽  
Neuromorphic Computing ◽  
Term Memory

Energy-efficient computing paradigms beyond conventional von-Neumann architecture, such as neuromorphic computing, require novel devices that enable information storage at nanoscale in an analogue way and in-memory computing. Memristive devices with long-/short-term synaptic plasticity are expected to provide a more capable neuromorphic system compared to traditional Si-based complementary metal-oxide-semiconductor circuits. Here, compositionally graded oxide films of Al-doped MgxZn1−xO (g-Al:MgZnO) are studied to fabricate a memristive device, in which the composition of the film changes continuously through the film thickness. Compositional grading in the films should give rise to asymmetry of Schottky barrier heights at the film-electrode interfaces. The g-Al:MgZnO films are grown by using aerosol-assisted chemical vapor deposition. The current-voltage (I-V) and capacitance-voltage (C-V) characteristics of the films show self-rectifying memristive behaviors which are dependent on maximum applied voltage and repeated application of electrical pulses. Endurance and retention performance tests of the device show stable bipolar resistance switching (BRS) with a short-term memory effect. The short-term memory effects are ascribed to the thermally activated release of the trapped electrons near/at the g-Al:MgZnO film-electrode interface of the device. The volatile resistive switching can be used as a potential selector device in a crossbar memory array and a short-term synapse in neuromorphic computing.

Materials Strategies for Organic Neuromorphic Devices

2021 ◽  
Vol 51 (1) ◽  
Author(s):  
Aristide Gumyusenge ◽  
Armantas Melianas ◽  
Scott T. Keene ◽  
Alberto Salleo
Keyword(s):  
Energy Efficiency ◽  
High Performance ◽  
Materials Science ◽  
High Energy ◽  
Information Storage ◽  
Oxide Semiconductor ◽  
Future Research ◽  
Annual Review ◽  
Publication Date ◽  
Neuromorphic Computing

Neuromorphic computing is becoming increasingly prominent as artificial intelligence (AI) facilitates progressively seamless interaction between humans and machines. The conventional von Neumann architecture and complementary metal-oxide semiconductor transistor scaling are unable to meet the highly demanding computational density and energy efficiency requirements of AI. Neuromorphic computing aims to address these challenges by using brain-like computing architectures and novel synaptic memories that coallocate information storage and computation, thereby enabling low latency at high energy efficiency and high memory density. Though various emerging memory devices have been extensively studied to emulate the functionality of biological synapses, there is currently no material/device system that encompasses both the needed metrics for high-performance neuromorphic computing and the required biocompatibility for potential body-computer integration. In this review, we aim to equip the reader with general design principles and materials requirements for realizing high-performance organic neuromorphic devices. We use instructive examples from recent literature to discuss each requirement, illustrating the challenges as well as future research opportunities. Though organic devices still face many challenges to become major players in neuromorphic computing, mostly due to their lack of compliance with back-end-of-the-line processes required for integration with digital logic, we propose that their biocompatibility and mechanical conformability give them an advantage for creating adaptive biointerfaces, brain-machine interfaces, and biology-inspired prosthetics. Expected final online publication date for the Annual Review of Materials Science, Volume 51 is July 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Silk Protein Based Volatile Threshold Switching Memristors for Neuromorphic Computing

2022 ◽  
pp. 2101139
Author(s):  
Momo Zhao ◽  
Saisai Wang ◽  
Dingwei Li ◽  
Rui Wang ◽  
Fanfan Li ◽  
...  
Keyword(s):  
Silk Protein ◽  
Neuromorphic Computing ◽  
Threshold Switching

Materials for Electron Beam Information Storage

1969 ◽  
Vol 27 ◽  
pp. 152-153 ◽  
Author(s):  
D. E. Speliotis
Keyword(s):  
Magnetic Field ◽  
Electron Beam ◽  
Recent Literature ◽  
Electron Beams ◽  
Information Storage ◽  
The Subject ◽  
The Magnetic Field

The interaction of electron beams with a large variety of materials for information storage has been the subject of numerous proposals and studies in the recent literature. The materials range from photographic to thermoplastic and magnetic, and the interactions with the electron beam for writing and reading the information utilize the energy, or the current, or even the magnetic field associated with the electron beam.

Transmission Electron Microscopy of oriented Co84Cr14Ta2 thin films for longitudinal magnetic recording

1991 ◽  
Vol 49 ◽  
pp. 756-757
Author(s):  
T. P. Nolan
Keyword(s):  
Thin Film ◽  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
Low Cost ◽  
Low Noise ◽  
Information Storage ◽  
High Coercivity ◽  
Magnetic Alloy ◽  
Magnetic Media ◽  
Transmission Electron

Thin film magnetic media are being used as low cost, high density forms of information storage. The development of this technology requires the study, at the sub-micron level, of morphological, crystallographic, and magnetic properties, throughout the depth of the deposited films. As the microstructure becomes increasingly fine, widi grain sizes approaching 100Å, the unique characterization capabilities of transmission electron microscopy (TEM) have become indispensable to the analysis of such thin film magnetic media.Films were deposited at 225°C, on two NiP plated Al substrates, one polished, and one circumferentially textured with a mean roughness of 55Å. Three layers, a 750Å chromium underlayer, a 600Å layer of magnetic alloy of composition Co84Cr14Ta2, and a 300Å amorphous carbon overcoat were then sputter deposited using a dc magnetron system at a power of 1kW, in a chamber evacuated below 10-6 torr and filled to 12μm Ar pressure. The textured medium is presently used in industry owing to its high coercivity, Hc, and relatively low noise. One important feature is that the coercivity in the circumferential read/write direction is significandy higher than that in the radial direction.

Indirect measurements in micro-space with the EM

1995 ◽  
Vol 53 ◽  
pp. 598-599
Author(s):  
Sterling P. Newberry
Keyword(s):  
Electron Microscope ◽  
Standard Model ◽  
Particle Physics ◽  
Information Storage ◽  
Storage Space ◽  
Indirect Measurements ◽  
Storage And Retrieval ◽  
Adequate Information ◽  
Compelling Reason ◽  
The Standard Model

At the 1958 meeting of our society, then known as EMSA, the author introduced the concept of microspace and suggested its use to provide adequate information storage space and the use of electron microscope techniques to provide storage and retrieval access. At this current meeting of MSA, he wishes to suggest an additional use of the power of the electron microscope.The author has been contemplating this new use for some time and would have suggested it in the EMSA fiftieth year commemorative volume, but for page limitations. There is compelling reason to put forth this suggestion today because problems have arisen in the “Standard Model” of particle physics and funds are being greatly reduced just as we need higher energy machines to resolve these problems. Therefore, any techniques which complement or augment what we can accomplish during this austerity period with the machines at hand is worth exploring.

Sign in / Sign up

Export Citation Format

Share Document