Barkerlynn2598

The results show that, for low-porosity and low-permeability sandstone, the main forms of formation damage by drilling fluid include solid damage and liquid damage. Solid damage is mainly caused by the blockage of small pores and narrow throats with solid particles of the size 0.1~30.0 μm in drilling fluid, while liquid damage is mainly caused by the water lock and hydrocarbon lock effects formed by the oil-water two-phase interface, gas-water two-phase interface, or the oil-gas-water three-phase interface.Fabrication of high-performance, flexible quantum-dot light-emitting diodes (QLEDs) requires the reliable manufacture of a flexible transparent electrode to replace the conventional brittle indium tin oxide (ITO) transparent electrode, along with flexible substrate planarization. We deposited a transparent oxide/metal/oxide (OMO) electrode on a polymer planarization layer and co-optimized both layers. The visible transmittance of the OMO electrode on a polyethylene terephthalate substrate increased markedly. Good electron supply and injection into an electron-transporting layer were achieved using WOX/Ag/ WOX and MoOx/Ag/MoOX OMO electrodes. High-performance flexible QLEDs were fabricated from these electrodes; a QLED with a MoOX/Ag/ MoOX cathode and an SU-8 planarization layer had a current efficiency of 30.3 cd/A and luminance more than 7 × 104 cd/m2. The current efficiency was significantly higher than that of a rigid QLED with an ITO cathode and was higher than current efficiency values obtained from previously reported QLEDs that utilized the same quantum-dot and electron-transporting layer materials as our study.The vision chip is widely used to acquire and process images. It connects the image sensor directly with the vision processing unit (VPU) to execute the vision tasks. Modern vision tasks mainly consist of image signal processing (ISP) algorithms and deep neural networks (DNNs). However, the traditional VPUs are unsuitable for the DNNs, and the DNN processing units (DNPUs) cannot process the ISP algorithms. Meanwhile, only the CNNs and the CNN-RNN frameworks are used in the vision tasks, and few DNPUs are specifically designed for this. In this paper, we propose a heterogeneous architecture for the VPU with a hybrid accelerator for the DNNs. It can process the ISP, CNNs, and hybrid DNN subtasks on one unit. Furthermore, we present a sharing scheme to multiplex the hardware resources for different subtasks. We also adopt a pipelined workflow for the vision tasks to fully use the different processing modules and achieve a high processing speed. We implement the proposed VPU on the field-programmable gate array (FPGA), and several vision tasks are tested on it. The experiment results show that our design can process the vision tasks efficiently with an average performance of 22.6 giga operations per second/W (GOPS/W).This paper proposes a near-perfect absorption device based on a cross-shaped titanium nanostructure and a multilayered structure. The multilayered bottom structure consists of alternately SiO2 and Ti. The whole device is put on a TiN substrate. The coupling between cross-shaped titanium nanostructures, and that between the cross-shaped titanium nanostructure and bottom multilayer, can further enhance the absorption at some wavelength where most of the energy is reflected or passes through in the device with a single structure. According to the simulation results, the device presents a nearly perfect absorption in a wavelength range from 300 nm to 2000 nm. The average absorptance in the wavelength range from 500 nm to 1400 nm exceeds 96%. This paper also provides a new idea for realizing perfect absorption, which is extensively used in sensing, controllable thermal emission, solar energy harvesting solar thermo-photovoltaic devices, and optoelectronic metrology.Based on the electrical conductivity model built for graphene oxide, the thermal crosstalk effects of resistive random access memory (RRAM) with graphene electrode and Pt electrode are simulated and compared. The thermal crosstalk effects of Pt-RRAM with different metal oxides of TiOx, NiOx, HfOx, and ZrOx are further simulated and compared to guide its compatibility design. In the Pt-RRAM array, the distributions of oxygen vacancy density and temperature are obtained, and the minimum spacing between adjacent conduction filaments to avoid device operation failure is discussed. The abovementioned four metal oxides have different physical parameters such as diffusivity, electrical conductivity, and thermal conductivity, from which the characters of the RRAMs based on one of the oxides are analyzed. Numerical results reveal that thermal crosstalk effects are severe as the spacing between adjacent conduction filaments is small, even leading to the change of logic state and device failure.A new data transformation method for micro-manufacturing using a topological model for a micro-/nano-texture was proposed for a surface-decorated product. Femtosecond laser printing was utilized to form the micro-/nano-textures into the hardened thick layer of dies by plasma nitriding. At first, the plasma-nitrided AISI316L flat substrate was laser-printed as a punch to imprint the tailored nano-textures onto the AA1060 aluminum plate for its surface decoration with topological emblems. Second, the plasma-nitrided SKD11 cylindrical punch was laser-trimmed to form the nanostructures on its side surface. This nano-texture was imprinted onto the hole surface concurrently with piercing a circular hole into electrical steel sheet. The fully burnished surface had a shiny, metallic quality due to the nano-texturing. The plasma nitriding, the laser printing and the CNC (computer numerical control) imprinting provided a way of transforming the tailored textures on the metallic product.Anodic bonding is broadly utilized to realize the structure support and electrical connection in the process of fabrication and packaging of MEMS devices, and the mechanical and electrical characteristics of the bonded interface of structure exhibit a significant impact on the stability and reliability of devices. For the anodic bonding structure, including the gold electrode of micro accelerometers, the elastic/plastic contact model of a gold-silicon rough surface is established based on Hertz contact theory to gain the contact area and force of Gauss surface bonding. The trans-scale finite element model of a silicon-gold glass structure is built in Workbench through the reconstruction of Gauss surface net by the reverse engineering technique. The translation load is added to mimic the process of contact to acquire the contact behaviors through the coupling of mechanical and electrical fields, and then the change law of contact resistance is obtained. Transmembrane Transporters inhibitor Finally, the measurement shows a good agreement between the experimental results, theoretical analysis and simulation, which indicates there is almost no change of resistance when the surface gap is less than 20 nm and the resistance is less than 5Ω, while the resistance changes rapidly after the gap exceeds 20 nm.An extraction method of the interface-trap densities (Dit) of the stacked bonding structure in 3D integration using high-frequency capacitance-voltage technique is proposed. First, an accurate high-frequency capacitance-voltage model is derived. Next, by numerically solving the charge-balance equation and charge conservation equation, Dit is extracted by fitting the measured and calculated capacitance-voltage curves based on the derived model. Subsequently, the accuracy of the derived model is verified by the agreements between the analytical results and TCAD simulation results. The average extraction error proves the precision and efficiency of the extraction method. Finally, the stacked bonding structure has been fabricated, and Dit at the interface between silicon and insulator is extracted to diagnose and calibrate the fabrication processes.The molecular dynamics method was used to study the removal mechanism of boron nitride particles by multi-angle microcutting of single-crystal copper from the microscopic point of view. The mechanical properties and energy conversion characteristics of single-crystal copper during microcutting were analyzed and the atomic displacement and dislocation formation in the microcutting process are discussed. The research results showed that during the energy transfer between atoms during the microcutting process of boron nitride particles, the crystal lattice of the single-crystal copper atom in the cutting extrusion region was deformed and displaced, the atomic temperature and thermal motion in the contact area between boron nitride particles and Newtonian layer of workpiece increased, the single-crystal copper atom lattice was defective, and the atomic arrangement structure was destroyed and recombined. The interface of different crystal structures formed a dislocation structure and produced plastic deformation. With the increase of the impact cutting angle, the dislocation density inside the crystal increased, the defect structure increased and the surface quality of the workpiece decreased. To protect the internal structure of the workpiece and improve the material removal rate, a smaller cutting angle should be selected for the abrasive flow microcutting function, which can reduce the formation of an internal defect structure and effectively improve the quality of abrasive flow precision machining. The research conclusions can provide a theoretical basis and technical support for the development of precision abrasive flow processing technology.Deep learning (DL) is a subfield of machine learning (ML), which has recently demonstrated its potency to significantly improve the quantification and classification workflows in biomedical and clinical applications. Among the end applications profoundly benefitting from DL, cellular morphology quantification is one of the pioneers. Here, we first briefly explain fundamental concepts in DL and then we review some of the emerging DL-enabled applications in cell morphology quantification in the fields of embryology, point-of-care ovulation testing, as a predictive tool for fetal heart pregnancy, cancer diagnostics via classification of cancer histology images, autosomal polycystic kidney disease, and chronic kidney diseases.Standard DEP theory, based on the Clausius-Mossotti (CM) factor derived from solving the boundary-value problem of macroscopic electrostatics, fails to describe the dielectrophoresis (DEP) data obtained for 22 different globular proteins over the past three decades. The calculated DEP force appears far too small to overcome the dispersive forces associated with Brownian motion. An empirical theory, employing the equivalent of a molecular version of the macroscopic CM-factor, predicts a protein's DEP response from the magnitude of the dielectric β-dispersion produced by its relaxing permanent dipole moment. A new theory, supported by molecular dynamics simulations, replaces the macroscopic boundary-value problem with calculation of the cross-correlation between the protein and water dipoles of its hydration shell. The empirical and formal theory predicts a positive DEP response for protein molecules up to MHz frequencies, a result consistently reported by electrode-based (eDEP) experiments. However, insulator-based (iDEP) experiments have reported negative DEP responses.