379 results about "Scan electron microscopy" patented technology

The invention discloses a scanning electron microscope. The scanning electron microscope comprises a scanning electron microscope main body and a sample table located in a sample cavity, the scanning electron microscope main body is fixedly connected with the upper cover of the sample cavity, so that a closed space is formed in the sample cavity; a closed-loop groove is formed in an upper cover of the sample cavity; wherein the groove is located outside the connection position of the upper cover of the sample cavity and the scanning electron microscope main body, and the bottom of the groove is not higher than the supporting surface of the sample table; a magnetic shielding layer is arranged in the groove; wherein the length of the magnetic shielding layer is not less than the distance from the objective lens of the scanning electron microscope main body to the supporting surface of the sample stage.

The invention discloses a multi-scale performance evaluation and optimization method and device for well cementation cement stone, and relates to the technical field of oil exploitation, the well cementation cement stone is subjected to nanoindentation test and scanning electron microscope microstructure test, and a mechanical property-microstructure test result is obtained; performing electronic computer tomography and mercury injection test on the well cementation cement stone, and constructing a pore network three-dimensional model; performing triaxial mechanical property test, thermogravimetric analysis and thermal expansion test on the well cementation cement stone to obtain a thermal-mechanical coupling test result; performing X-ray diffraction and X-ray fluorescence spectrum analysis on the well cementation cement stone to obtain mineral phase information and element information of the cement stone; according to the method, a mechanical property-microstructure test result, topological parameters, a thermal-mechanical coupling test result, cement stone mineral phase information and element information are fused, an optimal design scheme for target well conditions is generated, multi-dimensional performance testing and characterization are achieved, and an accurate basis is provided for well cementation cement stone optimal design and quality control.

Provided is a pattern inspection system, including a scanning electron microscope (SEM) including an electron gun configured to generate a first electron beam and emit the generated first electron beam toward a first wafer, a detector configured to detect electrons emitted from the first wafer based on the first electron beam emitted toward the first wafer, and at least one processor configured to generate a first SEM image including a plurality of pixels based on the detected electrons, and determine, based on a period of a pattern extracted from the first SEM image, a pixel size of a second SEM image to be generated by the SEM with respect to a second wafer.

The invention provides a semiconductor wafer surface detection method and device and a scanning electron microscope, and the method comprises the steps: collecting a to-be-detected wafer surface two-dimensional image through the scanning electron microscope, inputting the to-be-detected wafer surface two-dimensional image into a surface detection model, determining a wafer surface three-dimensional image related to the to-be-detected wafer surface two-dimensional image, identifying and outputting wafer surface parameters of the wafer surface three-dimensional image; the surface detection model is obtained by pre-training a wafer surface parameter sample and a sample pair associated with a wafer surface two-dimensional image sample and a wafer surface three-dimensional image sample, and the wafer surface two-dimensional image sample is obtained by scanning a wafer sample through a scanning electron microscope; the wafer surface three-dimensional image sample is obtained by scanning the same wafer sample through three-dimensional detection equipment, and the wafer surface three-dimensional image sample is bound with wafer surface parameters. Compared with a pure two-dimensional image of the wafer surface, the accuracy of surface data detection is improved while the detection speed is ensured.

The invention discloses a micro-positive pressure hydrogen environment in-situ stress-strain testing device and method. The device comprises a sealed reaction cavity which can be placed in a scanning electron microscope sample cabin; the loading device is arranged in the cavity and is used for fixing and applying a load; the atmosphere control system is communicated with the cavity and is used for introducing gas and maintaining a micro-positive pressure state; an electron transmission window arranged on the cavity, wherein an electronic transparent film packaged by the electron transmission window can maintain air tightness under micro-positive pressure and allows electron beams to penetrate through; and the heating module is arranged in the cavity. The method comprises the following steps: loading and sealing a sample, establishing a micro-positive pressure atmosphere, heating the sample, starting loading, and synchronously carrying out SEM real-time imaging and data recording. The problem that a traditional SEM in-situ device cannot work in a real micro-positive pressure hydrogen and high-temperature environment is solved, and synchronous visual in-situ observation of material microstructure evolution and macromechanical response under the gas-heat-force multi-physics field coupling condition is achieved.

4, 4 '-bipyridine (Bpy), 2, 5-thiophenedicarboxylic acid (Tdc), FeCl3. 6H2O, NiCl2. 6H2O, urea and tetrabutylammonium bromide are used as raw materials, a simple hydrothermal-calcination method is adopted to prepare the Fe2O3-coated Ni-MOF composite nanomaterial catalyst, X-ray diffraction (XRD), a scanning electron microscope (SEM) and a N2 adsorption and desorption technology are adopted to characterize a prepared sample, and the electro-catalytic oxygen evolution reaction (OER) activity of the Fe2O3-coated Ni-MOF composite nanomaterial catalyst is tested. Results show that compared with a single component, the activity of the composite nano-material catalyst is greatly improved, especially the composition-optimized Fe2O3-coated Ni-MOF-1 composite nano-material catalyst shows the highest catalytic activity, the composite nano-material catalyst catalyzes OER in 1M KOH, and the overpotential (eta 10) is only 330mV when the current density is 10mA / cm < 2 > and is close to the overpotential 291mV of a noble metal catalyst RuO2.

The present invention relates to a colloidal composition comprising unmodified, discrete cellulose microparticles, such as a colloidal emulsion or colloidal gel, a method of preparing the colloidal composition and uses of the colloidal composition and cellulose particles The colloidal composition comprises a continuous phase and a dispersed phase, wherein the continuous phase is a liquid; wherein the dispersed phase comprises cellulose microparticles which are dispersed in the continuous phase of the colloidal composition, wherein the cellulose microparticles have a mean average particle length of from 0.1 to 20 µm a mean average particle width from 0.05 to 1.3 µm, and a maximum thickness not exceeding 0.2 µm determined by scanning electron microscopy; and an aspect ratio of length / width of 1 to 25, and wherein the colloidal composition has a flow index n of ≤ 1 determined by a rheometer at NTP (normal temperature (25°C) and pressure (1 atm)).

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.

The invention discloses a five-axis sample stage applied to a scanning electron microscope, and belongs to the technical field of electron microscopes. The sample table comprises a Z-axis movement mechanism, a T-axis rotation mechanism, an X-axis movement mechanism, a Y-axis movement mechanism, an R-axis rotation mechanism and a sample table body. All the shafts achieve precise linear or rotary motion through crossed roller guide rails, vacuum motors are adopted for driving, a grating ruler, a travel switch and a limiting block are matched to guarantee positioning precision and motion limiting, and finally five-axis linkage of X-axis and Y-axis orthogonal linear motion, Z-axis vertical lifting, T-axis inclination and R-axis 360-degree rotation is achieved. The device has the advantages of multi-degree-of-freedom omnibearing observation, high-precision positioning, high stability of a vacuum environment, improvement of operation efficiency and the like, can meet the requirements of a scanning electron microscope on multi-angle and high-precision observation of a sample, and is suitable for micro-topography analysis in the fields of material science, electronic manufacturing and the like.

The invention provides a steel surface defect online detection method, device and system and a storage medium, and relates to the technical field of defect detection. The method comprises the following steps: acquiring a preset reference spot map; wherein the reference spot map is obtained by establishing a coordinate system for a first aluminum nitride spot image on the surface of a defect-free steel sample under a scanning electron microscope; after the target steel leaves the annealing furnace, generating raised aluminum nitride spots on the surface of the target steel through a pulse nitriding process by utilizing the residual temperature of the target steel; collecting a second aluminum nitride spot image on the surface of the target steel, converting the second aluminum nitride spot image into the coordinate system, and generating an online spot map; and taking the reference spot map as priori knowledge of a pre-trained defect identification model, inputting the online spot map into the defect identification model, and identifying the defect of the target steel. According to the invention, the interference of the steel surface condition and the image quality can be overcome, and the online detection accuracy and efficiency of the steel are improved.

The invention discloses a scanning electron microscope system and a degaussing debugging method. The scanning electron microscope system comprises a scanning electron microscope main body, an active degaussing system and a sample table located in a sample cavity, the scanning electron microscope main body is fixedly connected with the upper cover of the sample cavity, so that a closed space is formed in the sample cavity; a closed-loop groove is formed in an upper cover of the sample cavity; wherein the groove is located outside the connection position of the upper cover of the sample cavity and the scanning electron microscope main body, and the bottom of the groove is not higher than the supporting surface of the sample table; a probe of the active degaussing system is arranged in the groove and is positioned in a height range between an objective lens of the scanning electron microscope main body and the supporting surface of the sample table.

The invention provides a scanning electron microscope objective lens system and a detection method, and relates to the technical field of scanning electron microscopes. The magnetic lens device is used for focusing an incident electron beam; the deflection device, the anastigmator, the Wien analyzer group and the detection device are all located in an accommodating space in the magnetic lens device; the deflection device, the anastigmator and the Wien analyzer group are arranged along the optical axis of the incident electron beam and are arranged around the optical axis; the deflection device and the anastigmator are respectively used for adjusting the movement direction and shape of the incident electron beam so as to scan a to-be-tested sample through the incident electron beam, so that the to-be-tested sample generates signal electrons; the Wien analyzer group is used for adjusting the movement direction of the signal electrons to enable the signal electrons to enter the detection device; the detection device is located on the side, close to the magnetic lens device, of the deflection device, the anastigmator and the Wien analyzer set and used for generating a detection signal according to the signal electrons and achieving surface imaging of the to-be-detected sample. The imaging precision and the detection efficiency of the objective lens system are improved.

The invention discloses a method and a system for constructing an intelligent typing diagnosis model of psoriasis. The method comprises the following steps: S1, collecting pairing multi-modal data of a psoriasis patient whose fingernails are not tired, wherein the pairing multi-modal data comprises clinical information, scanning electron microscope images of fingernail surface morphology and infrared spectrum data of fingernail protein; s2, constructing a clinical feature encoder; s3, constructing a spectral feature encoder; s4, constructing an image feature encoder; s5, constructing a hierarchical fusion module; and S6, three loss function components are constructed, multi-objective optimization of the model is realized, and a total loss function is adopted to carry out model training. According to the method, the clinical information, the scanning electron microscope image of the nail surface morphology and the infrared spectrum data of the nail protein are integrated, and the multi-mode deep learning technology is combined, so that early recognition and prediction of psoriatic arthritis in a psoriasis patient are realized.

The invention relates to the technical field of carbon sequestration geological engineering, and particularly discloses a CO2 water rock reaction induced permeability change evaluation method based on machine learning, which comprises the following steps: firstly, acquiring multi-focal plane image data of a reacted sample on a scanning electron microscope platform; automatically identifying a reaction area by using the trained U-Net instance model, and obtaining porosity and specific surface area information; corresponding calculation coefficients are automatically selected and matched based on the area-depth information of the corrosion holes, normalization calculation is carried out, and the permeability and the spatial distribution of the permeability are directly output. According to the method, destructive detection is not needed, quantitative characterization of the rock permeability physical property is achieved, the analysis accuracy and efficiency are remarkably improved, batch processing statistics is supported, and reliable data support is provided for carbon sequestration safety research and sequestration simulation.

The invention relates to the technical field of electronic scanning imaging, in particular to a scanning electron microscope and an electron optical structure thereof. According to the scheme, the anode of the electron gun is arranged behind the focusing lens and in front of the scanning coil, and the acceleration structure is arranged between the cathode and the anode, so that the acceleration structure is connected with the power supply during application, the acceleration structure is used as the acceleration electrode, and electrons can be accelerated between the cathode and the acceleration electrode after being emitted from the cathode, so that the acceleration effect is improved. The electron optical structure is arranged between the accelerating electrode and the anode, the electron decelerates between the accelerating electrode and the anode, high energy is kept in the accelerating structure, it is guaranteed that electrons are kept at a high speed in the propagation process, and unexpected deflection of the electrons in the electron optical structure is reduced; therefore, the electron beam falling on the surface of the sample has relatively low energy, so that the anti-interference performance of the electron beam in the propagation process can be ensured, and the low-voltage imaging of the electron beam on the surface of the sample can also be ensured.

To provide a toner that offers excellent low-temperature fixation while simultaneously achieving both filming resistance in high-temperature, high-humidity environments and release properties during fixation. [Solution] A toner containing toner particles that include a polyester resin, an aromatic petroleum resin, and a mold release agent, A toner characterized in that, when the cross-section of the toner particles is observed with a scanning electron microscope, the domains of the release agent satisfy the following requirements. (Requirements) Each toner particle contains, on average, 2 to 8 release agent domains with a major axis of 400 nm or more and an aspect ratio of 0.7 or less calculated by the following formula (1). Aspect ratio = (Short diameter of release agent domain) / (Long diameter of release agent domain) Equation (1)

The application provides a method for observing glandular hairs of Ainsliaea sinensis by using a scanning electron microscope. The method comprises the following steps: (1) selecting a region to be measured in a leaf blade, cutting a sample, and immersing the sample in an aldehyde fixing solution for fixation and immersion; (2) performing gradient dehydration by using an ethanol solution, performing replacement by using isopentyl acetate, and then performing drying by using a critical point drying instrument; (3) removing non-glandular hairs by using adhesive tape; and (4) then spraying gold and observing under a scanning electron microscope. By using the method, the observation and distribution density statistics of the glandular hairs of Ainsliaea sinensis can be simply, efficiently and accurately completed. By using the method, the problem of uneven leaf blade is well solved, and the problem of non-glandular hairs shielding and interfering with the visual field is completely solved.

The invention discloses a preparation method of a functionally graded material without prefabricated powder addition, which specifically comprises the following steps: step 1, pretreatment: cutting and milling a test block workpiece, processing the test block workpiece into a fixed size and shape, and then cleaning the processed workpiece by using an ultrasonic cleaning machine; step 2, preparing a sample, and polishing the test block by using a metallographic polishing machine until the test block is polished; 3, electron beam treatment, wherein electron beams are adopted for conducting multiple times of irradiation treatment on the sample. And 4, tissue and performance testing is conducted, specifically, the microstructure is observed through a scanning electron microscope, and the mechanical performance of the functionally graded material is detected through a Vickers hardness tester. The method disclosed by the invention can be used for quickly synthesizing the functionally graded material without prefabricated addition, and has an extremely good application scene.

The invention relates to a transmission electron microscope sample and a preparation method thereof. The method comprises the following steps: determining a target area on a sample under a scanning electron microscope; forming a mark in a target area of the sample by using electron beam induced deposition, and determining a front cutter stopping position and a back cutter stopping position; forming a protective layer on the surface of the target area; and thinning the sample and the protective layer from the front side to the front side cutter stop position based on the mark by using a focused ion beam, and thinning the sample and the protective layer from the back side to the back side cutter stop position based on the mark by using the focused ion beam, so as to obtain the transmission electron microscope sample. The safety and the success rate of the preparation process can be effectively improved when the sample wafer is prepared.

This invention discloses a method for identifying the origin of quartz based on multimodal signal fusion using scanning electron microscopy (SEM). It utilizes only one SEM equipped with an energy dispersive spectroscopy (EDS) probe, a cathodoluminescence (CAT) probe, and a backscattered electron diffraction (BSE) probe. By comprehensively employing multiple indicators, including the coefficient of variation of CL band width (a), the Al-Ti influence coefficient (b), the lattice orientation difference influence coefficient (c), and the relative gravity coefficient of inclusion type (d), the method determines whether a quartz sample is of hydrothermal or metamorphic origin. This invention achieves rapid and accurate identification of the origin of quartz.

The application relates to a scanning electron microscope measurement method for the thickness of a metal compound layer, which comprises the following steps: obtaining a cross section containing the compound layer by wire cutting, and polishing after inlaying; observing under a scanning electron microscope, selecting a copper-tin alloy compound layer to be measured, selecting a backscattering electron probe to obtain a composition contrast image, adjusting the image contrast so that the measured object and the matrix have obvious differences; selecting a magnification of 2500 times matching the thickness of the metal compound layer, obtaining a high-definition backscattering electron image at a scanning speed of 28 seconds / frame; and quantitatively and finely measuring the thickness of the metal compound layer by using ImageJ software. The advantages of the application are as follows: the metal compound layer is extracted by using the ImageJ image processing software, the area is calculated to obtain the average thickness of the film thickness measurement method, not only the accurate alloy layer thickness information is obtained, but also the standard deviation value of the measured object is obtained to evaluate the uniformity of the measured object; the measurement method improves the accuracy and can be applied to detection and analysis practices.

The utility model discloses a powder sample preparation device for a scanning electron microscope, which comprises a sample seat, a conductive adhesive tape and a plurality of sample preparation tables, and a sample preparation groove with an opening on the upper surface is arranged on the sample seat; the conductive adhesive tape is adhered to the groove bottom of the sample preparation groove; the sample preparation tables are sequentially placed in the sample preparation groove and are all located above the conductive adhesive tape, so that the interior of the sample preparation groove is divided into a plurality of sample preparation sections, and different powder samples are bonded to the conductive adhesive tape in each sample preparation section. The sample preparation device has the beneficial effects that a plurality of samples can be prepared on one sample seat at the same time, the sample preparation efficiency is improved, the mutual pollution among different powder samples can be avoided, and the reliability and the accuracy of a test result are ensured.

The invention discloses a method for training a de-noising model for de-noising an image of a scanning electron microscope and a related product. The method comprises the following steps: acquiring a scanning electron microscope image and label noise data; performing noise estimation on the electron microscope image to obtain a noise estimation result; dividing the scanning electron microscope image into different noise intervals according to the noise estimation result; defining a first label and a second label based on a noise difference between a noise estimation result corresponding to each scanning electron microscope image in the corresponding noise interval and the corresponding label noise data; and combining the scanning electron microscope images of the corresponding noise intervals with the corresponding first labels or second labels to train a plurality of denoising models, and obtaining target denoising models adapted to different noise intervals. By using the scheme of the invention, accurate balance between a noise reduction effect and detail reservation can be realized.

The invention relates to an HHOF-TGU307 enhanced acrylic acid adhesive as well as a preparation method and application thereof, and belongs to the technical field of macromolecular functional materials. Aiming at the problem that the existing acrylic acid adhesive is difficult to meet the high-performance requirement in the aspects of bonding strength and mechanical property, and particularly the defects of insufficient bonding strength, easy aging, interface failure and the like in the emerging application fields of new energy and the like, HOF-TGU307 (hydrogen bond organic framework) is introduced into an adhesive system; the cohesive force and the adhesion capacity with a base material are obviously improved. The HOF-TGU307 material is a novel crystalline organic porous material with high specific surface area, high crystallinity and adjustable aperture, the HOF-TGU307 material shows unique solution processability and easy regeneration due to reversibility and flexibility of hydrogen bonds, and the HOF-TGU307 material has good biocompatibility and low cytotoxicity due to the metal-free characteristic; the characteristics enable the HOF to become a new platform of functional materials. The adhesive is formed by polymerization of two acrylic monomers in an ethanol solution through ultraviolet initiation, the process is simple and environment-friendly, and the obtained product has good storage and transportation stability. Performance tests show that the bonding strength of the adhesive on a PMMA (polymethyl methacrylate) base material can reach 1.36 MPa, and Fourier infrared spectroscopy and scanning electron microscope analysis verify good compatibility and dispersion state between HOF-TGU307 crystals and a polymer matrix. The adhesive provided by the invention has wide application prospects in the fields of structural bonding, photoelectric materials, automobiles, new energy and the like.

The invention belongs to the field of conductive slurry, and particularly discloses a method for detecting the dispersity of slurry particles. The detection method comprises the following steps: centrifuging slurry, sampling from the bottom of the slurry, and forming a film on the obtained sample to obtain a test sample film; spraying metal on the surface of the test sample film, and observing the particle size and the number of large particles in the test sample film by adopting a scanning electron microscope; the centrifugation is as follows: the slurry is centrifuged for 3-12 times by adopting a centrifugal force of 500-3000g, and each time is centrifuged for 10s-7min. The large particles are actively enriched to the bottom of the slurry through centrifugation, and then are directly sampled and observed from the bottom, so that the large particles are more easily captured and analyzed. According to the method, the problems that in a traditional method, due to the fact that large particles naturally sink to the bottom in the drying film forming process and are difficult to be effectively observed by an electron microscope, size misjudgment and number missing detection are caused are fundamentally avoided, and therefore more accurate statistics and characterization of the large particles in the slurry are achieved.

The invention relates to the technical field of carbon sequestration and geological sequestration, and particularly discloses a slice CO2 water-rock reaction corrosion identification and pore evaluation method based on machine learning, and the method comprises the steps: firstly collecting multi-focal-plane images of the same view field of a slice before and after a reaction on a scanning electron microscope platform, and carrying out the registration; utilizing the trained U-Net instance segmentation model to automatically identify a corrosion area and extract a contour; generating a relative height map through a depth-of-field reconstruction and calibration technology in combination with a multi-focal-plane sequence, and obtaining the effective corrosion depth of each corrosion area; and carrying out volume normalization calculation based on area-depth information, and directly outputting porosity increment and spatial distribution thereof. According to the method, destructive detection is not needed, quantitative volume characterization of corrosion characteristics is achieved, the analysis efficiency and accuracy are remarkably improved, batch processing and mineral phase layering statistics are supported, and reliable data support is provided for CO2 geological storage reaction mechanism research and reservoir simulation.

Provided is a surface-treated copper foil that can be used to produce printed wiring boards and the like, which exhibit excellent adhesion between a resin substrate and the surface-treated copper foil, low transmission loss, and are less likely to develop voids at the interface between the resin substrate and the surface-treated copper foil even when subjected to thermal history. The surface-treated copper foil has a roughened surface on which roughening particles are formed. The physical properties measured on the roughened surface satisfy the following: (A) when the surface-treated copper foil is cut to expose a cross section perpendicular to the roughened surface and the cross section is observed under a scanning electron microscope, the density X of protrusions of the roughening particles present on the roughened surface is 4 to 10 per 1-μm long region of the roughened surface on the cross section; (B) the average aspect ratio AR, calculated by dividing the particle height by the particle diameter of the roughening particles, is 1.5 to 3.0; and (C) the arithmetic mean height Sa, measured in accordance with the optical measurement method specified in ISO 25178, is 0.04 μm to 0.10 μm.

The utility model discloses a maintenance device for water quality and flue gas on-line monitoring equipment, and belongs to the technical field of maintenance devices. The water quality and flue gas on-line monitoring equipment maintenance device comprises a base assembly, a leak detection assembly, a damage detection mechanism and a blowing mechanism, the leak detection assembly is used for carrying out leak detection on a gas path system of the flue gas on-line monitoring equipment, and the damage detection mechanism is used for carrying out surface and internal damage detection on an optical probe of the water quality on-line monitoring equipment. The air blowing mechanism is used for conducting blow-drying maintenance and air blowing cleaning on sampling probes of the water quality online monitoring equipment and the smoke online monitoring equipment respectively, the leak detection assembly and the air blowing mechanism are installed on the two sides of the top face of the base assembly respectively, the damage detection mechanism is arranged on the top face of the leak detection assembly, and the leak detection assembly comprises an installation box. A pair of leak detector bodies is installed in the installation box body, the damage detection mechanism comprises a pair of connecting plates and a connecting frame, and a scanning electron microscope and a transmission electron microscope are installed on the two sides of the bottom end of the connecting frame respectively.

The invention discloses an FIB sample preparation SEM image-oriented chip defect automatic detection method, which comprises the following steps: acquiring a scanning electron microscope image of a chip sample subjected to focused ion beam sample preparation, and carrying out manual labeling to construct a chip defect image data set; preprocessing the data set image to obtain a sample set for training; training a deep learning chip defect detection model based on the sample set to realize automatic identification and positioning of a defect target; inputting a to-be-detected SEM image into the trained detection model to obtain a candidate defect bounding box and a corresponding confidence coefficient and category probability; performing non-maximum suppression on the candidate results of the same defect category, and removing a redundant frame to obtain a final defect detection result; and carrying out statistics on defect targets according to categories based on the final detection result, and generating structured defect statistical data containing image identifiers, defect categories and number. And high-precision automatic detection and positioning of multiple types of defects in the SEM image of the FIB sample are realized.

A non-oriented electrical steel sheet according to one embodiment of the present invention comprises, by wt%: 4.0 to 7.0% of Si; 0.001 to 2.0% of Al; 0.03 to 2.0% of Mn; and the remainder of Fe and inevitable impurities, wherein the RPc value of the surface of the steel sheet is 30 to 100, and the sum of oxygen (O) and carbon (O) components in a surface region of 1 mm2 is 1 wt% or less, as measured by EDS compositional analysis using scanning electron microscopy.