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6189 results about "Wafer" patented technology

In electronics, a wafer (also called a slice or substrate) is a thin slice of semiconductor, such as a crystalline silicon (c-Si), used for the fabrication of integrated circuits and, in photovoltaics, to manufacture solar cells. The wafer serves as the substrate for microelectronic devices built in and upon the wafer. It undergoes many microfabrication processes, such as doping, ion implantation, etching, thin-film deposition of various materials, and photolithographic patterning. Finally, the individual microcircuits are separated by wafer dicing and packaged as an integrated circuit.

Fabrication method for wafer-level mono-axial strain Si on AlN-buried insulation layer based on non-crystallization and scale effect

The invention discloses a fabrication method for wafer-level mono-axial strain Si on a AlN-buried insulation layer based on non-crystallization and a scale effect. The fabrication method is implemented according to the following steps of depositing a SiO2 layer at a Si layer at a top layer of a Si wafer on the cleaned AlN-buried insulation layer; performing ion injection on the Si layer at the top layer to form a non-crystallization layer, and removing the SiO2 layer on the non-crystallization layer; depositing a tensile stress SiN thin film or a press stress SiN thin film on the Si layer at the top layer, etching the SiN thin film to a mono-axial tensile stress SiN strip-shaped array or a mono-axial press stress SiN strip-shaped array, annealing the wafer to make the non-crystallization layer re-crystallized, and enabling the AlN-buried insulation layer to generate plastic deformation; and etching the SiN strip-shaped array to obtain the wafer-level mono-axial strain Si on the AlN-buried insulation layer. The wafer-level mono-axial strain Si has the advantages of high heat dissipation and large strain, and the fabrication method can be used for fabricating a wafer-level mono-axial strain Si material on the AlN-buried insulation layer.
Owner:XIDIAN UNIV

Method for preparing and applying single orientation Cu6Sn5 intermetallic compound micro-interconnecting welding point structure

The invention provides a method for preparing and applying a single orientation Cu6Sn5 intermetallic compound micro-interconnecting welding point structure. The method for preparing the single orientation Cu6Sn5 intermetallic compound micro-interconnecting welding point structure comprises the first step of arraying a Cu welding disc on a wafer through the electroplating technology, the second step of manufacturing bosses by preparing brazing filler metal prepared on the Cu welding disc, the third step of carrying out hot-wind remelting on the manufactured bosses for 30s-120s, the fourth step of carrying out solid-phase aging processes on chips obtained in the third step, the fifth step of placing the welding point bosses prepared in the fourth step into hydrochloric acid, oscillating the welding point bosses through ultrasound, washing and drying the welding point bosses to obtain a preferred orientation Cu6Sn5 welding disc, the sixth step of reversely buckling the welding point bosses prepared in the fifth step into a corresponding circuit board Cu metal layer, and obtaining the single orientation Cu6Sn5 intermetallic compound micro-interconnecting welding point structure through the reflow welding technology. Uniform and stable welding point structure can be obtained when the single orientation Cu6Sn5 intermetallic compound micro-interconnecting welding point structure is applied to large two-level packaging at the appropriate conditions.
Owner:HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL +3

Three dimensional chip structure implementing machine trained network

Some embodiments provide a three-dimensional (3D) circuit structure that has two or more vertically stacked bonded layers with a machine-trained network on at least one bonded layer. As described above, each bonded layer can be an IC die or an IC wafer in some embodiments with different embodiments encompassing different combinations of wafers and dies for the different bonded layers. The machine-trained network in some embodiments includes several stages of machine-trained processing nodes with routing fabric that supplies the outputs of earlier stage nodes to drive the inputs of later stage nodes. In some embodiments, the machine-trained network is a neural network and the processing nodes are neurons of the neural network. In some embodiments, one or more parameters associated with each processing node (e.g., each neuron) is defined through machine-trained processes that define the values of these parameters in order to allow the machine-trained network (e.g., neural network) to perform particular operations (e.g., face recognition, voice recognition, etc.). For example, in some embodiments, the machine-trained parameters are weight values that are used to aggregate (e.g., to sum) several output values of several earlier stage processing nodes to produce an input value for a later stage processing node.
Owner:XCELSIS CORP

Production method of 50-micron ultrathin chips

The invention provides a production method of 50-micron ultrathin chips. An adhesive film is pasted to the surface of a wafer graph, and a film cutter is inclined to cut the film; the wafer is thinned through coarse grinding, fine grinding, polishing and eroding, four feeding speeds exist only in the coarse grinding, and three speeds exist in the polishing; a film is tightly stretched on the back face of the thinned wafer, the adhesive film on the front face of the wafer is torn off, and feeding and discharging are performed automatically; scribing is performed with a step mode and an anti-cracking scribing process of the double-shaft scribing technology, and production of the 50-microns ultrathin chips is completed. The production method can guarantee the processing capability of a back-end process along with increasing of sizes of the chips, reduce the quality abnormities that in the scribing process, the surfaces of the chips are cracked and the back faces are stretched to be broken, reduce the resistance borne by a scribing cutter in the cutting process, effectively solve the quality problem that the chips are cracked and stretched to be broken, achieve the processing of the ultrathin chips and provide technical preparation for the development direction of high-density, high-performance, light and thin IC packaging products.
Owner:TIANSHUI HUATIAN TECH +1

Silicon-glass-silicon structure surface acoustic wave temperature and pressure integrated sensor and preparation thereof

The invention provides a silicon-glass-silicon structure surface acoustic wave temperature and pressure integrated sensor and preparation thereof, and relates to a sensor. The sensor has a silicon-glass-silicon sandwich structure. A pressure sensor is integrated on a silicon-based pressure-sensitive film of the upper layer. A temperature sensor is integrated on a silicon substrate of the bottom part. The silicon substrate and the upper layer are isolated by a glass framework. The manufacturing method comprises the steps that the silicon substrate is prepared; the silicon-based pressure-sensitive film is prepared; a sandwich structure cavity is formed by the silicon substrate, the silicon-based pressure-sensitive film and the glass framework through bonding; the substrate layer of an SOI wafer is etched with the buried silicon oxide layer in the SOI wafer acting as a corrosion auto-stop layer so that the device layer of the SOI wafer is remained to act as the silicon-based pressure-sensitive film of the pressure sensor; four electrode regions are formed on the silicon-based pressure-sensitive film through etching, and the etching regions are arranged above the electrode regions of the temperature sensor and the pressure sensor with the bonding interface of the glass framework and the silicon-based pressure-sensitive film and the inlaid electrodes in the silicon-based pressure-sensitive film acting as the etching stop layer respectively; and array devices are split and then single devices are obtained.
Owner:厦门纵能电子科技有限公司

Optoelectronic systems providing high-power high-brightness laser light based on field coupled arrays, bars and stacks of semicondutor diode lasers

A semiconductor diode laser having a broad vertical waveguide and a broad lateral waveguide is disclosed emitting laser-light in a single vertical mode and a single lateral mode narrow beam. The vertical waveguide comprises a coupled cavity structure, wherein light, generated in the active medium placed in the first cavity leaks into the second cavity and returns back. Phase matching conditions govern the selection of a single vertical mode. A multi-stripe lateral waveguide comprises preferably a lateral photonic band crystal with a lateral optical defect created by selected pumping of multistripes. This approach allows the selection of a single lateral mode having a higher optical confinement factor and / or a lower absorption loss and / or a lower leakage loss compared to the rest lateral optical modes. This enables a single lateral mode lasing from a broad area field coupled laser array. A laser system comprised of multiple field coupled laser arrays on a single wafer and a set of external mirrors enables an ultra-broad field coupled laser bar emitting a coherent laser light in a single vertical optical mode and a single lateral optical mode. A laser system comprised of multiple ultra-broad field coupled laser bars on different wafers and a set of external mirrors enables an ultra-broad field coupled laser stack emitting coherent laser light in a single vertical optical mode and a single lateral optical mode. This allows realization of ultrahigh power ultrahigh brightness laser systems based on semiconductor diode lasers.
Owner:VI SYST GMBH

Preparation method of film bulk acoustic wave resonator with isolation layer and bulk acoustic wave resonator

The invention relates to the technical field of acoustic wave resonator preparation, in particular to a preparation method of a film bulk acoustic wave resonator with an isolation layer and the bulk acoustic wave resonator. The method comprises the following steps: injecting high-energy ions from the lower surface of a single crystal wafer, enabling the high-energy ions to enter the single crystalwafer to form a damage layer, and dividing the single crystal wafer into an upper piezoelectric layer and a single crystal film layer to obtain a damaged single crystal wafer; sequentially preparinga graphical lower electrode, a graphical sacrificial layer, an isolation layer and a bonding layer on the lower surface of the single crystal film layer; stacking the substrate and the bonding layer,performing wafer splitting treatment, stripping the upper piezoelectric layer at the upper end of the single crystal film layer, and preparing an upper electrode on the upper surface of the single crystal film layer; and forming a sacrificial layer release hole required by the graphical sacrificial layer on the upper surface of the single crystal film layer, and releasing the sacrificial layer toobtain the high-quality cavity type bulk acoustic wave resonator of the single crystal film body.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA

Integrated circuit defect image recognition and classification system based on fusion deep learning model

The invention discloses an integrated circuit defect image recognition and classification system based on a fusion deep learning model, and provides a mode of using a fusion model based on a deep convolutional neural network (CNN) to carry out on-line automatic recognition and classification on defect images of a wafer so as to timely detect the change of the number of various defects of the wafer. The core mechanism of the method is a defect image feature extraction method constructed by two deep learning models integrated into a learning mechanism. According to the deep CNN fusion model, a Combined3 defect image classification model is constructed on the basis of two frameworks of SE _ Inception _ V4 and SE _ Inception _ ResNet _ V2; and a sequence model optimization (SMBO) algorithm isutilized to perform hyper-parameter optimization on the fusion depth CNN recognition model, so that the model recognition precision is improved. Increasing automation levels. And the identification cost is reduced because an engineer is replaced by the AI model, and the working efficiency is greatly improved. Based on a real-time identification and classification result, engineers can count defectdata and search reasons in time, so that process parameters are adjusted, and the yield is improved.
Owner:上海众壹云计算科技有限公司
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