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946 results about "Model system" patented technology

Model system. An organism or other self-contained system used to evaluate a particular biologic activity or disease process.

Monolayer and/or Few-Layer Graphene On Metal or Metal-Coated Substrates

Graphene is a single atomic layer of sp2-bonded C atoms densely packed into a two-dimensional honeycomb crystal lattice. A method of forming structurally perfect and defect-free graphene films comprising individual mono crystalline domains with in-plane lateral dimensions of up to 200 μm or more is presented. This is accomplished by controlling the temperature-dependent solubility of interstitial C of a transition metal substrate having a suitable surface structure. At elevated temperatures, C is incorporated into the bulk at higher concentrations. As the substrate is cooled, a lowering of the interstitial C solubility drives a significant amount of C atoms to the surface where graphene islands nucleate and gradually increase in size with continued cooling. Ru(0001) is selected as a model system and electron microscopy is used to observe graphene growth during cooling from elevated temperatures. With controlled cooling, large arrays of macroscopic single-crystalline graphene domains covering the entire transition metal surface are produced. As the graphene domains coalesce to a complete layer, a second graphene layer is formed, etc. By controlling the interstitial C concentration and the cooling rate, graphene layers with thickness up to 10 atomic layers or more are formed in a controlled, layer-by-layer fashion.
Owner:BROOKHAVEN SCI ASSOCS

Modeling system and method for visual machine learning training model

The invention relates to a modeling system and method for a visual machine learning training model. The modeling system for a visual machine learning training model includes a process designer, a process analyzer, and a process scheduler, wherein the process designer is used for according to dragging operation of the graphic algorithm component selected by a user, establishing the data flow direction between the algorithms in the graphic algorithm component, and generating the process description language; the process analyzer is used for analyzing the process description language generated from the process designer, creating the corresponding learning component, and generating the corresponding Spark learning pipeline; and the process scheduler is used for submitting the Spark learning pipeline to a Spark cluster to perform model training. By selecting the corresponding graphic algorithm component, establishing the data flow direction between the algorithms through dragging, generating the process description language, analyzing the process description language, creating the corresponding learning components according to the node class name and the attribute, generating the corresponding Spark learning pipeline, and submitting the Spark learning pipeline to the Spark cluster for performing model training, the modeling system and method for a visual machine learning training model can realize high quality machine learning modeling.
Owner:北京天机数测数据科技有限公司

Shale gas reservoir recovery simulation experimental device

InactiveCN102944666AAccurately simulate the mining processEarth material testingDesorptionModel system
The invention relates to an experimental device in the field of natural gas recovery, and particularly relates to a shale gas reservoir recovery simulation experimental device. The shale gas reservoir recovery simulation experimental device comprises a high-pressure gas source system, an injection system, a model system, a thermostat system, a pressure return system and a data acquisition system, wherein an intermediate container in the injection system and a core holding unit in the model system are positioned in a thermostat. The shale gas reservoir recovery simulation experimental device has the advantages that a plate model core clamping device and two full-diameter core clamping devices are connected, the cores of different dimensions are connected in series, multi-scale pore characteristics in the shale gas reservoir can be simulated, the multi-scale characteristics of shale gas seepage influenced by the multi-scale effect are reflected, the recovery process of the shale gas reservoir can be accurately simulated, and recovery mechanisms and recovery dynamics of the shale gas reservoir in different modes can be comprehensively evaluated; and meanwhile, a large-scale shale core adsorption/desorption experiment can be performed by utilizing the experimental device, and a gas adsorption/desorption rule of the large-scale shale core under different conditions is researched.
Owner:SOUTHWEST PETROLEUM UNIV
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