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Atomic switch networks (ASNs) have been shown to generate network level dynamics that resemble those observed in biological neural networks. To facilitate understanding and control of these behaviors, we developed a numerical model based on the synapse-like properties of individual atomic switches and the random nature of the network wiring. We validated(More)
Memory is believed to occur in the human brain as a result of two types of synaptic plasticity: short-term plasticity (STP) and long-term potentiation (LTP; refs 1-4). In neuromorphic engineering, emulation of known neural behaviour has proven to be difficult to implement in software because of the highly complex interconnected nature of thought processes.(More)
Recent advances in the neuromorphic operation of atomic switches as individual synapse-like devices demonstrate the ability to process information with both short-term and long-term memorization in a single two terminal junction. Here it is shown that atomic switches can be self-assembled within a highly interconnected network of silver nanowires similar in(More)
Efforts to emulate the formidable information processing capabilities of the brain through neuromorphic engineering have been bolstered by recent progress in the fabrication of nonlinear, nanoscale circuit elements that exhibit synapse-like operational characteristics. However, conventional fabrication techniques are unable to efficiently generate(More)
We demonstrate the ppt-level single-step selective monitoring of the presence of mercury ions (Hg²⁺) dissolved in environmental water by plasmon-enhanced vibrational spectroscopy. We combined a nanogap-optimized mid-infrared plasmonic structure with mercury-binding DNA aptamers to monitor in-situ the spectral evolution of the vibrational signal of the DNA(More)
Ultraviolet (UV) photodetection has drawn a great deal of attention in recent years due to a wide range of civil and military applications. Because of its wide band gap, low cost, strong radiation hardness and high chemical stability, ZnO are regarded as one of the most promising candidates for UV photodetectors. Additionally, doping in ZnO with Mg elements(More)
A compact neuromorphic nanodevice with inherent learning and memory properties emulating those of biological synapses is the key to developing artificial neural networks rivaling their biological counterparts. Experimental results showed that memorization with a wide time scale from volatile to permanent can be achieved in a WO3-x-based nanoionics device(More)
We present a new generation of piezoresistive nanomechanical Membrane-type Surface stress Sensor (MSS) chips, which consist of a two dimensional array of MSS on a single chip. The implementation of several optimization techniques in the design and microfabrication improved the piezoresistive sensitivity by 3~4 times compared to the first generation MSS(More)