958 results about "Optical microscope" patented technology

The invention discloses an optimized preparation method of a high-strength flame-retardant polyamide-based composite material in the technical field of information, which comprises the following steps: in the preparation process of the composite material, acquiring online dispersed state monitoring data of a modified filler by using a laser particle size analyzer and an optical microscope, including particle size distribution, agglomeration degree and dispersion uniformity of the filler; according to online dispersion state monitoring data, parameter ranges of melt flow property characterization are determined, the parameter ranges comprise the shearing rate and the temperature, particle size distribution data are used for determining the shearing rate range, small particle size distribution corresponds to the high shearing rate range, and agglomeration degree data are used for determining the temperature range; the higher degree of agglomeration corresponds to a higher temperature range to promote the dispersion of the filler, and these parameters are directly used to guide the setting of the subsequent rheological test.

The invention provides a flat-field apochromatic objective lens and an optical microscope, and relates to the technical field of optical imaging. The flat-field apochromatic objective lens comprises a first lens group, a second lens group and a third lens group which are sequentially arranged from an object plane to an image plane, both the first lens group and the second lens group have positive refractive power, the third lens group has positive refractive power or negative refractive power, the first lens group comprises at least two sub-lens groups with positive refractive power, and the second lens group comprises at least two sub-lens groups with negative refractive power. The sub-lens group is a single lens or a balsaming lens formed by gluing at least two single lenses, and the second lens group comprises at least one balsaming lens with positive refractive power and at least one balsaming lens with positive refractive power or negative refractive power. The third lens group includes at least one cemented lens having a positive refractive power and at least one cemented lens having a positive refractive power or a negative refractive power. On the basis, the flat-field apochromatic objective lens has a large field of view, a large numerical aperture and a long working distance.

The invention relates to the technical field of oil exploration, and discloses a rock mechanical parameter logging intelligent evaluation method considering continental facies shale fabric characteristics. The method comprises the following steps: 1, dividing shale lithofacies, identifying and determining the bedding development thickness of a sample through an optical microscope, determining a granularity experiment of the sample through granularity analysis, and forming mineral composition and bedding factor lithofacies division; 2, constructing a typical logging facies based on a rock electricity response relationship, and dividing the imaging logging facies of the research area according to natural gamma curves of conventional logging and imaging logging, core deposition structure characteristics and imaging logging image characteristics; 3, testing the longitudinal and transverse wave velocities and the porosity of different shale lithofacies, and calculating the dynamic elastic modulus and the Poisson's ratio. Through fine division and description, the method for accurately evaluating the bedding development condition, the particle size characteristics and the mineral components of the shale sample is provided, the testing time is short, the cost is low, and accurate evaluation of shale can be achieved.

The invention relates to the technical field of semiconductors, and discloses a semiconductor sample defect detection system which comprises an imaging module, a data acquisition module, a data processing module, an automation and integration module and a user interface module. According to the defect detection system and method for the semiconductor sample, by integrating the imaging modules of the optical microscope, the electron microscope, the X-ray diffractometer and the super-resolution microscope, details of the semiconductor sample can be comprehensively captured from macroscopic to microscopic and from the surface to a crystal structure, so that precise recognition of tiny or deep defects is ensured; the application of the deep learning model further improves the accuracy of image processing, through feature extraction and intelligent identification, even defects difficult to perceive by naked eyes have no place to hide, and the high-precision detection capability greatly reduces the risk that quality problems are only found in subsequent production links, reduces the possibility of reworking and scrapping, and improves the production efficiency. Therefore, the product quality and the production yield are improved.

The invention discloses a metallographic detection method and system based on image recognition, and belongs to the technical field of metallographic detection. The detection method comprises the following steps: image acquisition and preprocessing: acquiring a metal metallographic image by an optical microscope, performing median filtering and denoising, and extracting a grain boundary by adaptive binarization; and field-of-view and scale calibration: selecting a corresponding scale according to the shooting magnification. The multi-parameter automatic measurement comprises grain size analysis, grain size rating, second phase analysis and intelligent report generation, a report is automatically generated based on a preset template and comprises an original image, a binary image, measurement data and a histogram, and report fonts and layout can be adjusted in real time through a visual control. According to the detection method disclosed by the invention, the efficiency, the precision and the reliability of metallographic structure analysis of the metal material are remarkably improved through the full-process design of image acquisition standardization, preprocessing intellectualization, data analysis automation and report generation templating.

The invention relates to the field of biological recognition and environmental monitoring, and discloses a chironomidae larva recognition system based on deep learning and image recognition, which comprises an image acquisition module, an automatic sample processing device, an image superposition processing module, a deep learning recognition module and an automatic category classification and statistics module, the image acquisition module acquires multi-focal plane chironomidae larva images through an optical microscope and a digital camera, the automatic sample processing device realizes automatic loading operation of a sample, and the image superposition processing module performs adaptive fusion on the multi-focal plane images to generate a full-focal plane image containing multiple pieces of depth information; the deep learning recognition module is used for extracting fine structure features of chironomidae larvae and automatically recognizing and classifying different types of chironomidae larvae, and the automatic type classification and statistics module is used for performing statistical analysis according to classification results and generating a report of type distribution and time sequence change. The method is suitable for automatic monitoring of water ecological environment.

The invention relates to a depth-of-field expansion method for an optical surgical microscope. The method comprises the following steps: collecting an open-source high-definition high-frequency image database; acquiring point spread functions corresponding to different focus depths of the operating microscope; constructing a random depth surface type database; simulating a partial out-of-focus image of the non-flat sample imaged by the optical microscope; simulating a perfect focusing image of the flat sample imaged by the optical microscope; combining a large number of paired data partial out-of-focus images-perfect focusing images; and constructing an encoder-decoder structure network model from the image end to the image end to carry out model training and application. The problem that high-quality pairing training data conforming to imaging of the operating microscope is difficult to obtain for model training is solved, partial defocusing / focusing simulation data of the operating microscope conforming to a real physical rule generation effect can be synthesized in batches, a high-quality training data set is constructed at low cost, the number, diversity and randomness of the training data are ensured, and the training efficiency is improved. And defocus information is efficiently learned and recovered while focusing information is kept.

The invention provides a large-view-field and high-temporal-spatial-resolution light sheet imaging system and method, and relates to the field of optical microscope imaging, and the system comprises a laser which is used for generating Gaussian laser; the 1 / 2 wave plate is used for adjusting the polarization direction of the laser; the spatial light modulator is used for light field regulation and control, and the Gaussian laser is modulated into a bent light beam through the spatial light modulator; the scanning galvanometer is used for synchronously scanning the modulated exciting light and controlling the light beam to form area array imaging on the sample; the scanning lens is positioned behind the galvanometer and is used for collecting the laser beams subjected to area array scanning, so that the laser is focused to a target area of the sample; the tube lens I is matched with the illumination objective lens to form a microscope system; the sample pool is used for placing and fixing a sample; a four-dimensional displacement table, a detection objective lens, an optical filter and a camera. According to the invention, through LSFM imaging of the curved light beam with the axial focal length obviously stretched, high-flux three-dimensional imaging with large field of view and high spatial-temporal resolution is realized.

The invention discloses a method for evaluating the quality of a metal part, which comprises the following steps of: determining the laser type according to the characteristics of the metal part, obtaining various laser parameters for evaluating the quality of the metal part through an experimental method, and performing laser irradiation by adopting the accurately controlled laser parameters. In combination with real-time monitoring and regulation of instruments such as a power meter, a spectrograph, a roughmeter and an optical microscope, a laser parameter-grain boundary definition data set is formed, and finally a quality evaluation model is established to realize accurate evaluation of the quality of the metal parts. According to the method, the quality of the metal parts can be evaluated quickly and economically.

The invention discloses a method for automatically evaluating the average grain size of a metal material by using a cross-point method, and relates to the field of metal material metallographic image analysis, and the method comprises the following steps: selecting an identification model according to a tested material; inputting the optical microscope image pic into a system with an identification model; extracting scale information of the input image pic by using mask extraction and Hough straight line detection: firstly extracting a scale region by using a mask, then extracting a scale length by using a Hough straight line detection algorithm, and finally extracting a scale value by using a KNN classifier; and identifying the grain boundary pixels of the input image by using the selected identification model: classifying each pixel of the input optical microscope image pic by using UNet, judging whether the pixel is the grain boundary pixel, finally performing optimization, performing intercept method rating according to the optimized grain boundary image, counting the number of intersections per unit length, and calculating the grain size G. According to the method, the precision and consistency of grain size evaluation are remarkably improved.

The invention discloses an annealing temperature control method based on a differentiated ohmic contact material, and aims to solve the problems that the annealing temperature of an N-surface Au / Ge ohmic contact layer of an existing AlGaInP-based red light Micro-LED is not accurately monitored, a temperature field is not uniform and is difficult to detect, and abnormal response lags, the method comprises seven steps of processes (two times of patterning, two times of metal coating, two times of photoresist removal, annealing and observation), and the annealing temperature of the N-surface Au / Ge ohmic contact layer of the existing AlGaInP-based red light Micro-LED is controlled. Preparing a first Au / Ge ohmic contact layer (for function) and a second Au / Ge / Ni ohmic contact layer (for detection) on the N surface of the wafer; by means of the characteristic that Ni inhibits Au / Ge agglomeration, the two-layer agglomeration state difference is observed through an optical microscope, and the temperature is judged (in the normal state, the former agglomerates, and the latter does not agglomerate); the method is convenient in detection, supports batch detection, can find temperature abnormity in real time, improves the process stability, and is suitable for industrial mass production.

The invention belongs to the technical field of fiber size measurement, and particularly relates to a method for measuring the length of fibers in a fiber reinforced thermoplastic composite material. Mixing and diluting the fiber reinforced thermoplastic composite material and thermoplastic resin to obtain a diluted material, pressing the diluted material to obtain a test sample strip, cutting the test sample strip into a sample wafer, and measuring the length of the fiber in the sample wafer under an optical microscope; wherein the fiber reinforced thermoplastic composite material is prepared from matrix resin and reinforced fibers, and the matrix resin is the same as thermoplastic resin. According to the invention, the problems of poor measurement result accuracy and reproducibility and low measurement efficiency of the existing fiber length measurement method for the fiber reinforced thermoplastic composite material are solved.

Disclosed in the present invention is a stimulated emission depletion and super-resolution fluorescence lifetime imaging method, which is applied to the technical field of optical microscope imaging. The method provided in the present invention combines the stimulated emission depletion and fluorescence lifetime imaging principles, a depletion laser pulse frequency used therein is half of an excitation light pulse frequency, and a time interval between two pulse sequences is adjusted, such that a depletion laser pulse follows an adjacent excitation light pulse; and analysis processing is performed on collected fluorescence lifetime data, such that a super-resolution fluorescence lifetime image is obtained, thereby solving the problem of the fluorescence lifetime of a stimulated emission depletion and fluorescence lifetime imaging microscope being significantly shortened under the action of a high-energy depletion laser, and thus accurately reflecting real information of a fluorochrome and a micro-environment. Therefore, the innovative technique provides important technical support for life science research, significantly improves the accuracy and effectiveness of research, and promotes further development in the field of biomedicine.

The invention provides a floor wear resistance detection method and system, is applied to the technical field of floor wear detection, and reflects the wear resistance of a floor coating by obtaining the variation of porosity before and after floor wear. When the porosity after abrasion is obtained, a two-dimensional optical image of a to-be-detected surface is collected through multi-direction illumination, and the image is subjected to alignment processing. By analyzing the light and shade change information and the shadow form information of the dark area in different illumination directions, when the light and shade change information of the dark area changes along with the change of the position of the light source and the shadow form information shows the dynamic change of rotation or movement, it is judged that the hole is the floor hole. The discrimination mechanism based on the illumination dynamic change effectively solves the problem that a two-dimensional optical microscope scheme in the prior art cannot distinguish real pores and shallow scratches, and avoids misjudgment of scratches generated by a large amount of wear as pores, thereby significantly improving the accuracy of porosity calculation after wear.

The invention discloses a method for counting micro-plastics in a water body, and belongs to the technical field of micro-plastic counting, and the method comprises the following steps: 1, taking out a plurality of water samples from different positions of the water body to be detected, mixing the water samples, and randomly taking out quantitative water as a sample to be detected, 2, placing the obtained sample to be detected under an optical microscope for observation, step 3, identifying and marking the micro-plastics in the image according to the acquired image, counting the number of the micro-plastics in the sample according to the marking number, and determining the number of the micro-plastics in the sample according to the number of the micro-plastics in the sample according to the number of the micro-plastics in the sample. And 4, distinguishing the types of the micro-plastics in the sample, and respectively marking and counting the micro-plastics.

An optical microscope device comprises an optically integrated configuration of components for imaging a target device within a field of view of the optical microscope device, and for laser annealing the target device by generating a laser beam spot pattern from a laser beam received on an optical fiber from a remote laser source, and for controlling a duration of exposure of the laser beam spot pattern for laser annealing the target device.

A deep learning-based super-resolution fluorescence lifetime imaging microscopy (SR-FLIM) method includes the steps of: S1, performing fluorescence microscopic imaging on a sample to obtain confocal intensity images and stimulated emission depletion (STED) intensity images at a same location; S2, co-registering the acquired confocal and STED intensity images; S3, pairing the co-registered confocal and STED intensity images as input (Input) and ground truth (GT) to assemble a dataset; S4, partitioning the dataset into training and validation sets following a predefined ratio; and S5, constructing a network, and selecting hyperparameters and an optimizer. This method may achieve SR-FLIM within a conventional confocal FLIM system, surpassing spatial resolution limitations of FLIM, breaking through resolution barriers of conventional optical microscopy, while preserving normal fluorescence lifetime characteristics of fluorescent probes.

The invention relates to the technical field of section analysis of printed circuit boards, in particular to a section analysis method for PCB positioning cutting, a target abnormal area is positioned on a PCB through an optical microscope, the optical microscope not only can observe the morphology of the surface layer of a sample, but also can observe the morphology within a certain range below the surface layer, and the accuracy of section analysis is improved. And meanwhile, the optical microscope is very sensitive and accurate in color identification, so that compared with the prior art in which the target abnormal area is positioned on the PCB through a scanning electron microscope, the target abnormal area can be more effectively positioned on the PCB, and the purpose of reducing the positioning difficulty of the target abnormal area is achieved. Besides, the positioning layer and the protection layer are deposited in the target abnormal area, so that the cross section sample can be prevented from being physically and chemically damaged in the cutting process on the basis of improving the cutting precision of the cross section sample, and the failure analysis precision of the PCB is improved.

The invention discloses a lithium mineral component detection method based on improved YOLOv8, and belongs to the technical field of computer vision and mineral detection.The method comprises the steps that dry powder samples of various lithium mineral components are collected, the collected dry powder samples are shot under an optical microscope, and then the shot images are segmented and marked to obtain lithium mineral components; constructing a sample data set covering various lithium mineral components; the method comprises the following steps of: improving a YOLOv8 network to obtain an improved YOLOv8 network; training the improved YOLOv8 network on the basis of the sample data set; and the trained and improved YOLOv8 network is utilized to realize lithium mineral component detection. By adopting the scheme, the lithium mineral component detection effect and efficiency can be improved, and technical support is provided for intelligent detection of lithium ores.

The invention discloses a three-dimensional visualization method for deformation dislocation Schmidt factor distribution, and the method comprises the steps: preparing a transmission sample based on a deformation sample, and obtaining a physical identifier marking the direction of an external load; dislocation images of a plurality of different angles of the transmission sample are obtained through a transmission electron microscope, three-dimensional reconstruction is carried out, and a dislocation three-dimensional image under a sample coordinate system is obtained; tilting the sample in situ, and obtaining conversion parameters of a sample coordinate system and a crystal coordinate system according to the tilting parameters and the diffraction pattern; acquiring optical images of the sample rod and the transmission sample through an optical microscope, acquiring an applied load direction under a sample coordinate system according to the optical images, and acquiring an applied load direction under a crystal coordinate system based on the conversion parameters; and determining a dislocation slippage system according to the dislocation Burkholtz vector and the dislocation three-dimensional image, and calculating to obtain a dislocation Schmidt factor by combining with the direction of the external load under the crystal coordinate system, and displaying the dislocation Schmidt factor in the three-dimensional image. According to the method, the deformation dislocation Schmidt factor can be accurately and intuitively represented in the dislocation three-dimensional image.

The invention relates to the field of cell analysis, and provides a multi-mode digital micro-fluidic system and method for cell sorting analysis, the system comprises an active digital micro-fluidic platform, the active digital micro-fluidic platform comprises a micro-fluidic chip, an upper computer control system and an FPGA hardware circuit, an upper computer generates a liquid drop path planning instruction, the FPGA hardware circuit converts the liquid drop path planning instruction into an electrode driving signal, and the electrode driving signal is transmitted to the micro-fluidic chip; the nanoliter-grade liquid drops are driven to change between the electrodes; the optical tweezers platform comprises a laser device, an optical microscope and a CMOS camera, laser beams are generated by the laser device to form a three-dimensional optical potential well, the laser beams are transmitted into the micro-fluidic chip through the optical microscope to realize non-contact control on cells, and the CMOS camera records images and transmits the images back to the upper computer; the objective table clamp is used for realizing cooperative control of the optical tweezers and the active digital microfluidics; and the image recognition system is used for recognizing morphological characteristics of cells in the liquid drops based on a convolutional neural network and screening target cells. According to the invention, integration of high-throughput nondestructive cell sorting and in-situ multi-modal analysis is realized.

A detection method and detection apparatus for atomic-scale defects in gallium oxide crystals. In the detection method, a scattering-type scanning near-field optical microscope system and / or a nano-infrared system are used to detect atomic-scale defects in gallium oxide crystals. Aiming at real requirements for the detection of internal structural defects in Ga2O3 materials and devices, a near-field optical microscope system and a nano-infrared system are used to detect structural defects in Ga2O3 crystals, thereby realizing highly sensitive and nondestructive detection of atomic-scale defects in materials.

The present invention provides a real-time flow cytometric analyzer of single-cell dynamics combining droplet microfluidics and multimodal optical microscopy, and belongs to the field of cell biology experimental devices. The analyzer comprises a cell / signal loading & acquisition and control system, a high-throughput microfluidic single-cell manipulation chip, a multi-channel optical microscopy and multimodal signal acquisition and control system, and a data processing and analysis system. Based on droplet-based microfluidic chip technology, multimodal optical microscopy technology, single-cell dynamics theoretical modeling and analysis methods, and artificial intelligence technology, the integrated detection of spatiotemporal information of single-cell dynamics can be realized. The analyzer provides a new rapid and accurate single-cell dynamics analysis platform for exploring the occurrence and development mechanism of major human diseases, disease diagnosis, cell sorting and drug screening, etc.

A super-resolution single-objective light-sheet optical microscopy system and method, and a related imaging system, are configured to generate two light sheets that are guided to a single objective. The single objective is configured to allow the two light sheets to transmit through same and interfere with each other to generate structured light fringe regions. The single objective is further configured to receive a fluorescence signal that is recorded by a fluorescence detection module.

The invention relates to the technical field of material mechanical property testing, and discloses a material indentation and scratch testing device and method under a composite energy field, and the device comprises a supporting experiment table, a vertical micro-motion platform, a horizontal micro-motion platform, a high-definition optical microscope, a force sensor, a displacement sensor and an additional energy field generation system. According to the method, a controllable additional energy field is synchronously applied while a mechanical indentation or scratch load is applied to a hard and brittle material sample, and load displacement data is collected in real time. In the data processing stage, the real hardness is calculated by adopting a corrected proportion sample resistance model, the elastic modulus is calculated based on the Oliver-Pharr theory, and the fracture toughness of the material is analyzed and calculated according to the size of the indentation tip crack. The problem that in-situ mechanical property characterization cannot be carried out in a composite energy field in a traditional test is solved, the hardness calculation precision is improved, the fracture toughness measurement function is expanded, and the experimental device and method are provided for research of a hard and brittle material composite machining mechanism.

The invention provides a sample pretreatment method for in-situ analysis of impurities in high-purity quartz sand, which comprises the following steps: crushing, screening, scrubbing, desliming and grading a raw ore sample to obtain a mineral with the particle size of-2mm + 0.5 mm; carrying out quartz single mineral selection on minerals with the particle size of + 0.5 mm by adopting an optical microscope; the method comprises the following steps: uniformly dispersing selected quartz single minerals on a glass slide, and preparing an oil-immersed sheet; placing the oil immersed sheet under a polarizing microscope, selecting quartz single mineral particles with low gas-liquid inclusion content, and cleaning and drying the quartz single mineral particles; and embedding the quartz single mineral particles into epoxy resin, polishing and cleaning to obtain the high-purity quartz sand sample target sheet. According to the method, an oil immersion observation method is firstly adopted to select quartz single minerals with relatively low gas-liquid inclusion content, so that the sample representativeness of subsequent in-situ analysis test is ensured; then, epoxy resin is adopted for embedding, polishing and cleaning, target material preparation is simplified, and secondary pollution to a to-be-detected surface is avoided.

PURPOSE: To provide a light guide plate and a light source module that have more superior uniformity of light distribution.SOLUTION: A light guide plate includes a light incident surface, a first surface, and a plurality of optical microstructures. The first surface is connected to the light incident surface. The optical microstructures are disposed on the first surface. Each optical microstructure has a first cross-sectional profile along a first cross section and a second cross-sectional profile along a second cross section. The first cross section is perpendicular to the second cross section. The first cross-sectional profile is different from the second cross-sectional profile. The optical microstructures include a plurality of first optical microstructures and a plurality of second optical microstructures. The second cross-sectional profile of each first optical microstructure is different from the second cross-sectional profile of each second optical microstructure. There is also provided a light source module including the light guide plate.SELECTED DRAWING: Figure 2A

The invention belongs to the technical field of semiconductor material detection, and particularly relates to a method for representing micro-defects of a near-perfect czochralski silicon wafer by regulating and controlling near-surface copper concentration. The invention discloses a method for representing micro-defects of a near-perfect czochralski silicon wafer by regulating and controlling the concentration of near-surface copper. The method specifically comprises the following steps: (S.1) cleaning the silicon wafer and immersing the silicon wafer into a copper nitrate solution for standing; (S.2) rinsing the silicon wafer with ionized water, taking out the silicon wafer and airing the silicon wafer; (S.3) performing high-temperature heat treatment on the silicon wafer for a period of time, and quickly cooling; (S.4) carrying out chemical polishing on the cooled silicon wafer; (S.5) horizontally placing the silicon wafer in the corrosive liquid; and (S.6) observing the surface of the silicon wafer by using an optical microscope or a scanning electron microscope so as to display the microdefects. According to the invention, copper precipitates at different depths are observed after copper is introduced at high temperature, so that the microdefect condition of the silicon wafer can be reflected. The method can clearly display the micro-defects in the nearly perfect czochralski silicon wafer, and has high detection efficiency and accuracy. The method is easy to operate, low in cost and suitable for silicon wafer microdefect detection in large-scale production.

Systems and methods for capturing and processing image data captured by an optical microscope, such as an Open Top Light Sheet (OTLS) microscope are disclosed. Image data can be processed by techniques including flat fielding, image depth correction, and edge correction, and pixel classification and image segmentation techniques can be applied to more accurately identify lipid droplets and fibrous structures for assessment of, for example, steatosis and fibrosis in human liver biopsy tissue samples. Systems and methods are also related to capturing low resolution images of a sample, identifying regions of interest, and then capturing high resolution image of the regions of interest to reduce memory used for storage, increase computation speed, and reduce computational power.

The invention provides a method for realizing super-resolution optical microscopic imaging on the basis that an optical axis of an objective lens deviates from a primary optical axis of a microscope. The invention provides a method for realizing super-resolution imaging by using a conventional optical microscope without modifying or adding complex equipment. By finely adjusting the angle of the objective lens turntable, an included angle of 3-4 degrees is formed between the optical axis of the objective lens and the main optical axis of the microscope, and the opening diameter of the aperture diaphragm is reduced, so that the resolution of the microscope can be improved from about 300nm to 100nm. According to the method, the optical imaging condition of the microscope is reasonably optimized and utilized, and the method is particularly suitable for high-resolution, real-time and nondestructive observation of the periodic linear array nanostructure on the surface of the sample. The method is easy to operate and low in cost, the application range of a conventional optical microscope is expanded, and the method has good practical value and application prospects in the fields of material microstructure analysis, semiconductor chip detection and the like.