In this paper, the recent progress of synaptic electronics is reviewed. The basics of biological synaptic plasticity and learning are described. The material properties and electrical switching characteristics of a variety of synaptic devices are discussed, with a focus on the use of synaptic devices for neuromorphic or brain-inspired computing. Performance metrics desirable for large-scale implementations of synaptic devices are illustrated. A review of recent work on targeted computing applications with synaptic devices is presented.

https://iopscience.iop.org/article/10.1088/0957-4484/24/38/382001/pdf

Synaptic electronics: materials, devices and applications

Pressurized blister tests show that the adhesion energies of graphene samples on silicon oxide are much higher than those measured in typical micromechanical structures.

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Ultrastrong adhesion of graphene membranes

Recent progress in electronic skin or e-skin research is broadly reviewed, focusing on technologies needed in three main applications: skin-attachable electronics, robotics, and prosthetics. First, since e-skin will be exposed to prolonged stresses of various kinds and needs to be conformally adhered to irregularly shaped surfaces, materials with intrinsic stretchability and self-healing properties are of great importance. Second, tactile sensing capability such as the detection of pressure, strain, slip, force vector, and temperature are important for health monitoring in skin attachable devices, and to enable object manipulation and detection of surrounding environment for robotics and prosthetics. For skin attachable devices, chemical and electrophysiological sensing and wireless signal communication are of high significance to fully gauge the state of health of users and to ensure user comfort. For robotics and prosthetics, large-area integration on 3D surfaces in a facile and scalable manner is critical. Furthermore, new signal processing strategies using neuromorphic devices are needed to efficiently process tactile information in a parallel and low power manner. For prosthetics, neural interfacing electrodes are of high importance. These topics are discussed, focusing on progress, current challenges, and future prospects.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/adma.201904765

Electronic Skin: Recent Progress and Future Prospects for Skin‐Attachable Devices for Health Monitoring, Robotics, and Prosthetics

A review on mechanics and mechanical properties of 2D materials—Graphene and beyond

Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path for implementing massively-parallel and highly energy-efficient neuromorphic computing systems. We first revie...

https://www.tandfonline.com/doi/pdf/10.1080/23746149.2016.1259585

Neuromorphic computing using non-volatile memory

Parylene-C, which is traditionally used to coat implantable devices, has emerged as a promising material to generate miniaturized devices due to its unique mechanical properties and inertness. In this paper we compared the surface properties and cell and protein compatibility of parylene-C relative to other commonly used BioMEMS materials. We evaluated the surface hydrophobicity and roughness of parylene-C and compared these results to those of tissue culture-treated polystyrene, poly(dimethylsiloxane) (PDMS), and glass. We also treated parylene-C and PDMS with air plasma, and coated the surfaces with fibronectin to demonstrate that biochemical treatments modify the surface properties of parylene-C. Although plasma treatment caused both parylene-C and PDMS to become hydrophilic, only parylene-C substrates retained their hydrophilic properties over time. Furthermore, parylene-C substrates display a higher degree of nanoscale surface roughness (>20 nm) than the other substrates. We also examined the level of BSA and IgG protein adsorption on various surfaces and found that surface plasma treatment decreased the degree of protein adsorption on both PDMS and parylene-C substrates. After testing the degree of cell adhesion and spreading of two mammalian cell types, NIH-3T3 fibroblasts and AML-12 hepatocytes, we found that the adhesion of both cell types to surface-treated parylene-C variants were comparable to standard tissue culture substrates, such as polystyrene. Overall, these results indicate that parylene-C, along with its surface-treated variants, could potentially be a useful material for fabricating cell-based microdevices.

http://www.tissueeng.net/lab/papers/la070925.pdf

Cell and protein compatibility of parylene-C surfaces.

A carbon nanotube (CNT) synapse emulates a biological synapse with its dynamic logic, learning, and memory functions induced by the interactions between CNTs and hydrogen ions in an electrochemical cell. A circuit of CNT synapses operates with extremely low-energy consumption and could potentially emulate the functions of the neuronal network.

A Carbon Nanotube Synapse with Dynamic Logic and Learning

We report a technique to characterize adhesion of monolayered/multilayered graphene sheets on silicon wafer. Nanoparticles trapped at graphene-silicon interface act as point wedges to support axisymmetric blisters. Local adhesion strength is found by measuring the particle height and blister radius using a scanning electron microscope. Adhesion energy of the typical graphene-silicon interface is measured to be 151±28 mJ/m2. The proposed method and our measurements provide insights in fabrication and reliability of microelectromechanical/nanoelectromechanical systems.

https://repository.library.northeastern.edu/files/neu:378411/fulltext.pdf

Direct measurement of graphene adhesion on silicon surface by intercalation of nanoparticles

We report an analog neuromorphic module composed of p-type carbon nanotube (CNT) synapses and an integrate-and-fire (I&F) circuit. The CNT synapse has a field-effect transistor structure with a random CNT network as its channel and an aluminum oxide dielectric layer implanted with indium ions as its gate. A positive voltage pulse (spike) applied on the gate attracts electrons into the defect sites of the gate dielectric layer, and the trapped electrons are gradually released after the pulse is removed. The electrons modify the hole concentration and induce a dynamic postsynaptic current in the CNT channel. Multiple input spikes induce excitatory or inhibitory postsynaptic currents via excitatory or inhibitory CNT synapses, which flow toward an I&F circuit to trigger output spikes. The dynamic transfer function between the input and output spikes of the neuromorphic module is analyzed. The module could potentially be scaled up to emulate biological neural networks and their functions.

Analog neuromorphic module based on carbon nanotube synapses.

In this paper, we present a low cost, flexible and reusable parylene-C shadow mask technology for diverse micropatterning applications. The smallest feature size of 4m is demonstrated and the technology is scalable up to full wafer scale. With the addition of SU-8 pillars, we also demonstrate multimask processing with an alignment accuracy of about 4–9m. To achieve features with fine resolution, a low temperature and high aspect ratio (>8:1) parylene etch process is also developed. Utilizing this shadow mask, we successfully patterned proteins and cells on various surfaces (glass, PDMS, methacrylate). High pattern flexibility (structures with different shapes and dimensions are successfully patterned) and patterning on curved PDMS surfaces are also demonstrated. This technology has potential applications for patterning proteins, cells and organic transistors on conventional and/or unconventional substrates. © 2007 Elsevier B.V. All rights reserved.

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Chia-Ling Chen

Papers

Cell and protein compatibility of parylene-C surfaces.

A Carbon Nanotube Synapse with Dynamic Logic and Learning

Direct measurement of graphene adhesion on silicon surface by intercalation of nanoparticles

Analog neuromorphic module based on carbon nanotube synapses.

A reusable high aspect ratio parylene-C shadow mask technology for diverse micropatterning applications