344 results about "Electronic microscopy" patented technology

The invention relates to the technical field of computer science, in particular to a stamping prediction method based on a multi-machine learning model and an automatic compensation device.The stamping prediction method comprises the steps that firstly, a sheet microstructure and material characteristics are obtained through a transmission electron microscope and an atomic probe tomography technology, and then finite element simulation sampling is conducted; a data set is expanded by using an adaptive algorithm, multiple models are constructed and trained to obtain a final springback prediction model, an automatic compensation device is embedded to realize automatic compensation, and the automatic compensation device covers visual parameter input, embedded springback prediction, springback compensation calculation and an automatic control module. Parameters can be visually input, springback can be accurately predicted, a compensation value can be calculated, and the process can be adjusted. The method aims at solving the problems that in the high-strength plate stamping process, due to springback, the size and shape of a part deviate from the design requirement, and a traditional prediction and compensation technology is insufficient in precision and efficiency.

Described herein are machine learning based system, method, and non-transitory computer readable medium for determining three-dimensional (3D) information of a structure of a patterned substrate. The 3D information can be determined using a neural network to convert a two-dimensional image to a 3D image. In a method, the neural network is trained by supplying simulated images of a sample with varied parameters to model a real fabricated IC structure. The trained network generates a depth map from newly supplied images of a sample to predict defect location The depth map may be converted to a binary map to predict defect dimension and location that may be used to guide inspection of a sample using an inspection tool.

A federated machine learning method is provided. The method includes providing, from a central model server, an initial trained machine learning (ML) model to a plurality of clients as a respective local ML model. The initial trained ML model is configured to identify defect features from scanning electron microscopy (SEM) images. The method additionally includes receiving, from at least one client by the central model server, information indicative of a respective updated local ML model. The method also includes determining, based on the information indicative of the respective updated local ML models, an updated global ML model.

The invention relates to a transmission electron microscope low-temperature sample rod using a flexible structure to transfer heat. The transmission electron microscope low-temperature sample rod comprises a liquid nitrogen Dewar tank; the sample rod comprises a sample rod body with a front-back through hollow cavity, a heat conduction rod and a flexible heat transfer rope, one end of the heat conduction rod extends into the liquid nitrogen Dewar tank, the other end of the heat conduction rod extends into the sample rod body, one end of the flexible heat transfer rope is wound and fixed on the heat conduction rod, and the other end of the flexible heat transfer rope is wound and fixed on the sample rod body. The other end of the sample rod extends to the outer end of the sample rod body; the sample rod head comprises a sample rod fixing outer frame and a sample rod temperature control part, the sample rod fixing outer frame is connected with the outer end of the sample rod body, the sample rod temperature control part is arranged on the sample rod fixing outer frame, the sample rod temperature control part is connected with the flexible heat transfer rope, and a heating element capable of heating a sample to be tested is further arranged on the sample rod temperature control part. Compared with the prior art, efficient heat conduction can be achieved, meanwhile, the thermal stress influence is reduced, and the temperature stability and the sample position stability are improved.

The invention discloses an in-situ TEM (Transmission Electron Microscope) device sample preparation method based on a suspended thinning and parallel carrying technology, which can be used for preparing in-situ TEM samples of semiconductor two-end devices and three-end devices, and mainly solves the problems of unstable ohm contact, nonuniform thinning, low success rate and high time cost in the prior art. According to the invention, an FIB sample preparation technology is adopted, and stable and reliable ohmic contact between a sample electrode and an MEMS chip electrode is ensured through specific-angle sample extraction, suspended thinning, parallel carrying, circuit breaking treatment and an accurate electrode welding process. According to the sample prepared by the invention, the failure state of a device can be observed in real time under a transmission electron microscope, the sample has the advantages of high sample preparation success rate, good repeatability, stable electrical parameters and wide applicable chip variety, and the reliability and repeatability of in-situ TEM test data are remarkably improved.

The invention provides a contour measurement method, electronic equipment and a storage medium. The method comprises the following steps: acquiring a standard image, a contour of the standard image and an SEM image of a to-be-measured product acquired by a critical dimension scanning electron microscope CD-SEM; adopting a target physical threshold model to extract a target contour of the SEM image; and determining a target edge placement error between the contour of the standard image and the target contour of the SEM image, and generating and outputting a contour measurement result of the to-be-measured product according to the target edge placement error, so as to improve the precision of contour extraction and the accuracy and efficiency of contour measurement.

The invention belongs to the technical field of medical instruments, particularly relates to a microscope imaging device for an ophthalmologic operation, and aims to overcome the defects that in the prior art, when an operation is carried out on a patient, an eye operation area of the patient cannot be marked, and when the operation is carried out on the patient, eyelids of the patient are inconvenient to open. A vertical electric guide rail is installed on the base, a transverse electric guide rail is installed on the vertical electric guide rail, an arc-shaped electric guide rail is installed on the transverse electric guide rail, and an installation rod is fixedly installed on the arc-shaped electric guide rail. According to the eyelid distraction device, eyelids of a patient can be conveniently distraction, meanwhile, eyeball affected parts of the patient can be marked, so that when the patient is subjected to an operation, the accuracy of the operation can be effectively improved, and good convenience can be provided for a doctor.

The invention discloses an image processing method and device, a medium and a computer program product, and relates to the technical field of semiconductor manufacturing. The image processing method comprises the following steps: acquiring target image samples of a plurality of wafer samples through a scanning electron microscope, and obtaining a first contour image label of each target image sample; based on the target image sample, a first contour image result is generated through a generator of a preset image edge model, iteration training is carried out on the preset image edge model through pixel difference loss, adversarial loss and edge supervision loss until a convergence condition is met, and a target image edge model is obtained; the generator of the target image edge model can output an edge contour image based on the target image of the target wafer. Through multi-dimensional constraints of pixel difference loss, edge supervision loss and adversarial loss, the preset image edge model is trained in the direction of generating an actual edge contour, and the accuracy of the edge contour image is improved.

The invention provides a fuzzy knowledge graph construction method related to a wafer manufacturing process, and relates to the technical field of fuzzy knowledge graphs, and the method comprises the steps: employing a three-dimensional convolutional network to extract a spatial defect feature X of a scanning electron microscope image, carrying out the coding of sensor time series data through a bidirectional LSTM, and obtaining a feature set Y, obtaining electrical performance parameters of the wafer based on impedance spectroscopy analysis from the text to obtain a feature set Z; building fuzzy knowledge based on the text to reinforce the feature sets X, Y and Z, building a fuzzy feature set and a time sequence feature set, building a weighted scoring model, and screening a candidate set from the text according to the weighted scoring model; information is extracted from the candidate set, and a tetrad structure G = (entities, relationships, time attributes and fuzzy rules) is constructed; and taking G as input, generating a time sequence fuzzy rule through a recursive reconstruction contribution method, and incrementally updating the knowledge graph. According to the method, the characterization bottleneck of space-time coupling and uncertainty correlation in a traditional method is broken through.

The invention belongs to but is not limited to the technical field of petroleum engineering, and particularly relates to a shale reservoir polymer fracturing fluid retention characteristic analysis method and system, and the method comprises the following steps: S1, carrying out a displacement experiment by using polymer solutions with different molecular weights and concentrations; s2, the retention condition of polymers in the rock core before and after displacement is observed through a micron CT and scanning electron microscope technology; and S3, analyzing the influence of the polymer solutions with different molecular weights and concentrations on the retention characteristics in the shale reservoir. The invention aims to carry out a displacement experiment on the rock core by using polymer solutions with different molecular weights and concentrations, and then observe and compare the polymer solutions of the rock core before and after displacement by using equipment such as a CT scanner and an electron microscope, so as to obtain the retention and migration conditions of the polymer in the hole seam of the rock core. The retention characteristics of fracturing fluid polymer molecules in a microporous structure and a matrix are studied, so that a correct polymer molecular weight range is provided for reservoir transformation, fracturing fluid reservoir damage is reduced, and the fracturing yield increasing effect is finally improved.

In one aspect, a specimen holder includes a first end configured to attach to a cooling device and a second end configured to be inserted into a microscope; a section with a sample tip at the second end; an interface between the first end configured to attach to the cooling device and the section with the sample tip; and an internal thermal connection section configured to be in thermal contact with a cold finger of the cooling device when the specimen holder is attached to the cooling device and extending through the section with the sample tip to the sample tip.

A method for training a local machine learning model is provided. The method includes receiving a scanning electron microscope (SEM) image of semiconductor features. The method additionally includes determining a location and dimensions of a bounding box within the SEM image. The method yet further includes determining, whether a defect feature exists within the bounding box, based on an unsupervised object detection process. The method also includes, if the defect feature exists within the bounding box, receiving positive rewards. The method also includes, if the defect feature does not exist within the bounding box, receiving negative rewards.

The present invention comprises a computer-implemented method for automating the co-registration of SEM and 3D microtomography images in rock sample cylinders, characterized by comprising three main steps: (i) image pre-processing; (ii) internal orthogonal search; (iii) external multi-angle search. The method plays a fundamental role in the creation of image pairs. These pairs capture the same region of the rock, but with different analytical properties. Thus, the co-registration between 2D microscopy and 3D tomographic data provides a fundamental basis for the application of machine learning techniques and the expansion of the originally planar mineralogy to the entire three-dimensional volume. The three-dimensional mineralogical model generated from this co-registration has fundamental implications for the creation of digital rock models. The automation of the co-registration process between these acquisitions contributes to the advancement of petroleum engineering, since co-registration accelerates the process of generating image pairs for the use of machine learning algorithms in the generation of the three-dimensional mineralogical model. This method, in its turn, has direct application both in oil reservoir engineering and in geological interpretation.

A grid for sampling a liquid specimen. The grid includes a mesh and a foil. The mesh includes a plurality of grid bars defining a plurality of openings. The plurality of grid bars forms an outer perimeter of each opening. The foil is coupled to the mesh and the foil includes a plurality of holes. A subset of the plurality of holes is aligned with each of the plurality of openings. Each hole of the subset is spaced from the outer perimeter of the corresponding opening defined by the plurality of grid bars.

Systems, methods, and devices are described herein for integrated circuit (IC) layout validation. A plurality of IC patterns are collected which include a first set of patterns capable of being manufactured and a second set of patterns incapable of being manufactured. A machine learning model is trained using the plurality of IC patterns. The machine learning model generates a prediction model for validating IC layouts. The prediction model receives data including a set of test patterns comprising scanning electron microscope (SEM) images of IC patterns. Design violations associated with an IC layout are determined based on the SEM images and the plurality of IC patterns. A summary of the design violations is provided for further characterization of the IC layout.

A toner comprising a toner particle comprising a binder resin and a release agent, wherein the binder resin comprises a first resin and a second resin; the first resin is a crystalline resin having a melting point Tp of 50° C. to 90° C.; the second resin is an amorphous resin; in a cross section of the toner particle observed by a transmission electron microscope, the cross section of the toner particle has a matrix-domain structure composed of a matrix comprising the first resin and domains comprising the second resin; an area ratio of the matrix comprising the first resin in a total area of the cross section of the toner particle is 35 to 70 area %; and where a longest direction of each of the domains is taken as a longitudinal direction, a standard deviation of an angle of the longitudinal direction of the domains is 25° or less.

An external additive for toner, wherein the external additive is an organosilicon polymer particle, and defining A (nm) as the number-average particle diameter of primary particles of the external additive measured using a scanning electron microscope, and defining B (nm) as the number-average particle diameter of the external additive measured in accordance with a centrifugal sedimentation method, the A and the B satisfy a following Expression (1):1.5≤B / A≤3.0  (1).

The disclosure relates to air transfer free of solid state batteries and electrical testing of solid state batteries in scanning electron microscopes. In one embodiment, an apparatus includes a sample stage including a base member and a sample support assembly coupled to the base member, where the sample support assembly includes a bracket having opposing first and second bracket portions, the first holder portion and the second holder portion are configured to compress a sample within the holder receiving portion, wherein the base member is configured to engage a sample stage within a microscope chamber. A method includes securing a sample stage in a microscope chamber and charging and / or discharging the sample at least partially through an electrical coupling in the chamber.

The invention relates to the technical field of biosensor detection, in particular to a food grease safety detection device based on a biosensor. The detection device comprises a biosensor and an electron microscope, and further comprises a built-in sampling device, and the sampling device comprises a sampling tank, a mounting column, a feeding pipe, a pressurizing assembly and a cleaning assembly; a spiral heat supply pipe is arranged in the side wall of the mounting column, and a discharge pipe is vertically arranged at the bottom; the sampling tank is composed of an upper tank and a lower tank which are in threaded connection, a first filtering disc is mounted in the upper tank, a second filtering disc is mounted in the lower tank, a mounting disc is arranged between the upper tank and the lower tank, a first-stage pressurizing space is formed between the first filtering disc and the upper tank, and a second-stage pressurizing space is formed between the center frame and the second filtering disc; a water level detection mechanism is arranged beside the second filter disc; the outer side of the feeding pipe is sleeved with a heat supply sleeve. Efficient layering, precise temperature control and intelligent cleaning of the grease food are achieved, the detection sensitivity is improved, the maintenance cost is reduced, and the device is suitable for multi-scene rapid detection requirements.

The invention relates to a fretting wear process evolution in-situ detection device which comprises an air flotation vibration isolation platform, a fretting friction testing machine, an industrial electron microscope group and a metallographic microscope group are arranged on the upper surface of the air flotation vibration isolation platform, the fretting friction testing machine comprises an upper clamp and a lower clamp, an upper sample is arranged in the upper clamp, and a lower sample is arranged in the lower clamp. A lower test sample is arranged in the lower clamp, the upper clamp can drive the upper test sample to move to be in contact with the lower test sample, and the fretting friction testing machine further comprises a three-way translation table for microcosmically adjusting the lower test sample. According to the invention, the upper clamp is arranged to clamp the upper sample, the lower clamp is arranged to clamp the lower sample, and the three-way translation table is arranged to carry out microscopic adjustment on the lower sample, so that the upper sample and the lower sample are rubbed so as to evolve the abrasion process of the upper sample and the lower sample; and the mechanism and the rule of fretting wear can be conveniently and deeply researched.

A method for determining distortion in an image based on a process model, comprising: determining an image transformation operation based on a relationship between a plurality of measurement locations in an image and locations corresponding to the plurality of measurement locations in a predicted image generated by a process model; and characterizing image distortion in the image based on the image transformation operation.

A toner comprising a toner particle comprising a binder resin, wherein the binder resin comprises a first resin and a second resin, the first resin is a crystalline resin, the second resin is an amorphous resin, in an observation of a cross section of the toner particle with a transmission electron microscope, a matrix-domain structure composed of a matrix comprising the first resin and domains comprising the second resin is present, an area ratio occupied by the matrix in a total area of the matrix and the domains is from 35 area % to 70 area %, a [hydrocarbon group index (Ge)] / [hydrocarbon group index (DIA)] after washing the toner with hexane is 1.10 or more.

The invention discloses a wafer scanning system, a wafer scanning method and electronic equipment, and relates to the technical field of wafer scanning. The wafer scanning system comprises a workpiece table controller which is used for controlling a workpiece table to start to move from an initial position of a preset scanning area; the positioning module is used for collecting a position signal of the workpiece table in real time under the condition that the workpiece table starts to move from the initial position of the preset scanning area, and synchronously sending the position signal to the workpiece table controller and the scanning electron microscope controller of the scanning electron microscope; the workpiece table controller is also used for controlling the movement of the workpiece table according to the position signal; and the scanning electron microscope controller is used for controlling the scanning action of the scanning electron microscope according to the position signal. According to the scheme, the position signals of the workpiece tables are accurately distributed, cooperative control is achieved, it is ensured that the workpiece tables and the scanning electron microscope work synchronously in the scanning process, and therefore the scanning precision is effectively improved.

The utility model relates to the field of PCB welding spot detection, and discloses PCB welding spot detection equipment which comprises a workbench, a first clamping groove is formed in the top of the workbench, a sliding assembly is arranged in the first clamping groove, a base is fixedly connected to the outer portion of the sliding assembly, fixing blocks are fixedly connected to the two ends of the top of the base, and the fixing blocks are fixedly connected to the top of the workbench. A telescopic block is fixedly connected to one side of the fixed block, a second moving block is slidably connected to the exterior of the second electric sliding rail, a connecting block is fixedly connected to the exterior of the second moving block, and a second motor is fixedly connected to the interior of one end of the connecting block. According to the device, the electronic microscope is electrically connected with the display screen, so that the welding condition of a welding point is detected in a more detailed manner, the electronic microscope is driven to move through the movement of the rotating block, and the effect of detecting different positions is achieved, and the second motor mounted in the connecting block rotates to drive the rotating block to rotate; and the effect of adjusting different angles for detection is achieved.

The invention provides a wafer defect detection method and device, and relates to the technical field of semiconductors, and the wafer defect detection method comprises the steps: carrying out the laser scanning of a wafer, and obtaining the first position information and the first size information of a defect on the wafer; performing optical scanning on the wafer by using an optical microscope and performing electronic scanning on the wafer by using a scanning electron microscope according to the first position information and the first size information to obtain second position information and second size information of the defect on the wafer; and taking the second position information and the second size information as positioning detection information of defects on the wafer. According to the embodiment of the invention, a combined scanning mode of laser scanning, optical scanning and electronic scanning is used for carrying out positioning detection on the wafer defects, so that missing detection and false detection of the defects are avoided, and the accuracy of wafer defect detection is improved.

A method includes extracting first feature data by applying a backbone network of a machine learning model to a layout image representing a design for a target pattern, applying a hotspot segmentation network of the machine learning model to the first feature data, the hotspot segmentation network configured to generate a hotspot map representing a hotspot area of the layout image corresponding to a fault, obtaining, from the hotspot segmentation network, second feature data, and generating a scanning electron microscope (SEM) image of a wafer by applying an SEM image generation network of the machine learning model to the first feature data and the second feature data.

1. The name of the product of this design: electron microscope. 2. Purpose of this design product: Mainly used for electron microscopes. 3. The design key point of this appearance design product lies in the shape. 4. The picture or photo that best illustrates the design points: reference diagram of the combined state.

The invention relates to an ardealite-based phase change energy storage wallboard as well as a preparation method and application of the ardealite-based phase change energy storage wallboard. LA-HD-PA and DME shape-stabilized phase-change materials are mixed according to different proportions (wherein LA-HD-PA is compounded with modified DME by adopting a vacuum adsorption method, stable combination of LA-HD-PA and DME is ensured, the mass ratio of LA-HD-PA to MDE is 45: 55, the materials are doped into phosphogypsum, and the materials are mixed with cement, fly ash and other building materials to prepare the phase-change energy-storage gypsum board. The microstructure, the mechanical property, the thermophysical property, the heat-conducting property and the thermal stability of the energy storage gypsum board under the condition of different mass fractions of phase change admixtures are analyzed through a scanning electron microscope, a differential scanning calorimeter, a heat conductivity coefficient tester and a thermogravimetric analyzer; and the heat storage and release capability and the temperature control effect of the lower phase change wallboard are evaluated through a self-made micro-room model.

Provided are a scintillator and the like capable of improving emission intensity. A scintillator (S) comprises a sapphire substrate (6), a GaN layer (4) that is provided on the incident side to the sapphire substrate (6) and includes GaN, a quantum well structure (3) provided on the incident side to the GaN layer (4), and a conductive layer (2) provided on the incident side to the quantum well structure (3), wherein a plurality of emitting layers (21) including InGaN and a plurality of barrier layers (22) including GaN are alternatively stacked in the quantum well structure (3), and an oxygen-containing layer (23) including oxygen is provided between the quantum well structure (3) and the conductive layer (2).

To provide: a substrate-holding apparatus with a sensor device, the sensor device having a substrate layer and a sensitive layer; and a manufacturing method thereof.SOLUTION: A sensor device 120 at least comprises a substrate layer 180 and a sensitive layer 140. A manufacturing method comprises providing a mechanical supporting layer 160, and connecting the mechanical supporting layer 160 to the sensor device 120. After the connection, the sensitive layer 140 is situated between the substrate layer 180 and the mechanical supporting layer 160. By connecting the mechanical supporting layer 160, it is possible to thin the substrate layer 180 for forming a charged particle detector. The mechanical supporting layer 160 forms part of the manufactured detector. The detector can be used in a charged particle microscope, such as a transmission electron microscope for direct electron detection.SELECTED DRAWING: Figure 4b