8,244 research outputs found
Modeling the underlying mechanisms for organic memory devices: Tunneling, electron emission and oxygen adsorbing
We present a combined experimental and theoretical study to get insight into
both memory and negative differential resistance (NDR) effect in organic memory
devices. The theoretical model we propose is simply a one-dimensional metallic
island array embedding within two electrodes. We use scattering operator method
to evaluate the tunneling current among the electrode and islands to establish
the basic bistable I-V curves for several devices. The theoretical results
match the experiments very well, and both memory and NDR effect could be
understood comprehensively. The experimental correspondence, say, the
experiment of changing the pressure of oxygen, is addressed as well.Comment: 5 pages, 3 figure
THz Nanoscopy of Metal and Gallium Implanted Silicon
Drude model successfully quantifies the optical constants for bulk matter,
but it is not suitable for subwavelength objects. In this paper, terahertz
near-field optical microscopy and finite element simulation are used to study
gold patches fabricated by Gallium etching. Electron transport is discovered in
determining the optical signal strength. The signal from substrate is more
complicated and still not fully understood. As the etching area decreases,
near-field interaction is not dominated by doping concentration, and a higher
signal is observed near connected metals. With the help of simulation, the
abnormal enhancement phenomenon is discussed in detail, which lays the
foundation for further experimental verification
A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network
In this paper, we employ Probabilistic Neural Network (PNN) with image and
data processing techniques to implement a general purpose automated leaf
recognition algorithm. 12 leaf features are extracted and orthogonalized into 5
principal variables which consist the input vector of the PNN. The PNN is
trained by 1800 leaves to classify 32 kinds of plants with an accuracy greater
than 90%. Compared with other approaches, our algorithm is an accurate
artificial intelligence approach which is fast in execution and easy in
implementation.Comment: 6 pages, 3 figures, 2 table
Extraction of Uranium from Seawater: Design and Testing of a Symbiotic System
Uranium present in low concentration in ocean water has the potential to greatly augment the current fuel reserve for nuclear power generation, but the challenge of extracting it economically remains. Two new designs of seawater uranium extraction systems are proposed in this paper—a stationary system and a continuous system—both of which utilize a braided polymer adsorbent. The stationary system simplifies the recovery procedure, and it is predicted to produce uranium at 403/kg of uranium.MIT Energy InitiativeS. D. Bechtel, Jr. Foundatio
Influence of electrode thermal conductivity on resistive switching behavior during reset process
Resistive random access memory (RRAM) is the most promising candidate for non-volatile memory (NVM) due to its extremely low operation voltage, extremely fast write/erase speed, and excellent scaling capability. However, an obstacle hindering mass production of RRAM is the non-uniform physical mechanism in its resistance switching process. This study examines the influence of different electrode thermal conductivity on switching behavior during the reset process. Electrical analysis methods and an analysis of current conduction mechanism indicate that better thermal conductivity in the electrode will require larger input power in order to induce more active oxygen ions to take part in the reset process. More active oxygen ions cause a more complete reaction during the reset process, and cause the effective switching gap (dsw) to become thicker. The effect of the electrode thermal conductivity and input power are explained by our model and clarified by electrical analysis methods.
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