Battery single-particle dynamic process in-situ optical characterization method

Abstract

The invention relates to the crossing field of a battery material in-situ testing technology and optical imaging, in particular to a battery single-particle dynamic process in-situ optical characterization method, which comprises the following steps of: configuring an in-situ battery module; in the working process of the in-situ battery module, acquiring a differential capacity curve, a current curve and a working voltage curve of the in-situ battery module and an optical image sequence at a battery pole piece to be detected; based on the differential capacity curve, the current curve, the working voltage curve and the optical image sequence at the position of the battery pole piece to be detected, dynamic in-situ optical characterization of electrode particles on the battery pole piece to be detected in the in-situ battery module is completed based on the differential capacity curve, the current curve, the working voltage curve and the optical image sequence at the position of the battery pole piece to be detected. According to the invention, the dynamic process of the battery material can be researched under real working conditions.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of in-situ battery material testing technology and optical imaging, in particular, to an in-situ optical characterization method for dynamic processes of battery single particles. BACKGROUND

[0002] In the field of battery research, it is crucial to deeply understand the micro-dynamic processes of electrode materials under working conditions, such as lithium ion intercalation / deintercalation and phase evolution, in order to break through the performance bottleneck of batteries. In-situ characterization technology can realize real-time observation of materials in real electrochemical environments, which is the key to solving this problem. Although in-situ transmission electron microscopy and X-ray microscopy can provide high-resolution information, their high cost, complex sample preparation requirements, and potential damage to samples limit their widespread application. Therefore, optical microscopy technology has become a potential alternative solution due to its low cost, simple operation, and minimal sample damage.

[0003] However, existing optical characterization schemes often lack in system integration, environmental control stability, and real-time calibration capability, resulting in the inability to achieve long-term, high-reliability single particle dynamic observation, making it difficult to meet the demand for precise ion dynamics research. SUMMARY

[0004] In view of the defects in the prior art, the present application provides an in-situ optical characterization method for dynamic processes of battery single particles, which integrates electrochemical stimulation, environmental control, high-stability optical imaging, and real-time calibration by synergistically controlling various modules, solving the problems of poor module synergy and complex operation in the prior art, and providing a highly integrated, automated, and reliable solution to study the dynamic processes of battery materials under real working conditions.

[0005] To solve the above technical problems, the present application solves the problems by the following technical solutions: The in-situ optical characterization method for dynamic processes of battery single particles comprises: configuring an in-situ battery module; During the operation of the in-situ battery module, the differential capacity curve, current curve, working voltage curve, and optical image sequence of the in-situ battery module are collected; Based on the differential capacity curve, current curve, working voltage curve, and optical image sequence of the battery electrode sheet to be tested, the dynamic in-situ optical characterization of the electrode particles on the battery electrode sheet to be tested in the in-situ battery module is completed.

[0006] By the present application, an optical imaging system is assembled, and an optical imaging is performed on a to-be-tested battery electrode sample in an in-situ battery module by the optical imaging system; during the collection process, the collected optical images are detected and adjusted in real time to obtain a stable optical image sequence; finally, the optical image sequence is processed and analyzed to obtain an optical analysis result of the running performance of the to-be-tested battery electrode sample.

[0007] As preferred, the working process of the in-situ battery module is simulated by a battery comprehensive tester, and the collection of the differential capacity curve, the working voltage and the current curve of the in-situ battery module is completed.

[0008] As preferred, the optical image sequence at the to-be-tested battery electrode is collected based on the optical imaging system, and the optical image sequence includes a plurality of electrode particle images of the electrode particles at the to-be-tested battery electrode arranged in time sequence within a working cycle; wherein the first electrode particle image in the optical image sequence corresponds to an electrode particle image of the electrode particles at the to-be-tested battery electrode in a non-working state.

[0009] As preferred, after the original optical image sequence at the to-be-tested battery electrode is collected based on the optical imaging system, the optical image sequence is obtained based on the pre-processing and deep processing of the original optical image sequence.

[0010] In the present application, the original optical image sequence is pre-processed and deep-processed, including performing data processing on the collected optical image sequence, the data processing including: processing the optical image sequence based on a rolling differential algorithm to improve the contrast and signal-to-noise ratio of the optical image sequence; and performing image stabilization processing on the optical image sequence based on an accelerated robust feature algorithm to compensate for the overall translational jitter of the optical image sequence.

[0011] As preferred, the pre-processing of the original optical image sequence includes image stabilization processing of any original electrode particle image in the original optical image sequence based on a feature point matching algorithm.

[0012] In the actual test process, the experimental device is inevitably affected by the environment, resulting in jitter of the collected images, which will affect the accuracy of the experimental results to some extent. A video stabilization algorithm based on feature point matching is selected to suppress this phenomenon.

[0013] As preferred, the image stabilization processing of any original electrode particle image in the original optical image sequence is based on a feature point matching algorithm, including, obtaining the feature points of each electrode particle image in the original optical image sequence based on a Hessian matrix; wherein the determinant expression of the Hessian matrix is, , is a scale factor. Based on the coordinate offset values ​​of the feature points between the corresponding original electrode particle image and the first electrode particle image, the corresponding original electrode particle image is translated to complete the image stabilization processing of any original electrode particle image based on the feature point matching algorithm.

[0014] In this invention, the image stabilization process for optical image sequences based on the accelerated robust feature algorithm specifically involves: The Speeded Up Robust Features (SURF) algorithm was selected for feature point matching. This algorithm is a classic algorithm in the field of computer vision and has been widely used in video stabilization, image stitching and other fields. The algorithm mainly consists of three parts: local feature point extraction, feature point description and feature point matching.

[0015] Preferably, the deep processing of the original optical image sequence includes, For any original electrode particle image, the original electrode particle image of the previous moment in the original optical image sequence is used as the reference frame, and the original electrode particle image is used as the detection frame to obtain the rolling differential image of the original electrode particle image. The rolling differential image corresponding to each original electrode particle image in the original optical image sequence is used as the optical image sequence.

[0016] This invention further extracts and enhances useful signals at the algorithmic level and eliminates residual mechanical jitter, ultimately yielding data suitable for precise quantitative analysis. Optical image signals contain a strong reference light background. The rolling difference algorithm, by differencing the current frame with the previous frame or the average frame within a time window, can significantly suppress invariant background noise, thereby highlighting minute optical contrast changes (such as refractive index and thickness changes) caused by ion embedding / extraction. This makes phase transition fronts (such as "contraction nuclei"), which were previously difficult to detect in the original image, clearly visible. On the other hand, despite real-time calibration, sub-pixel-level high-frequency jitter may still exist. The image stabilization algorithm calculates the global translation vector between frames by detecting the feature point matching relationship between each image and the reference frame, and performs inverse compensation. Through the data processing unit's processing of the optical image sequence, the true dynamic signal of the sample is amplified and system noise is suppressed, significantly improving the signal-to-noise ratio and resolvability of the image sequence, laying a solid foundation for extracting accurate quantitative information (such as phase transition rate) from optical images. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the composition of the in-situ optical cell characterization device in this embodiment.

[0018] Figure 2This is an overall schematic diagram of the in-situ optical cell characterization device in this embodiment.

[0019] Figure 3 This is a schematic diagram of a vibration isolation device in this embodiment.

[0020] Figure 4 This is a schematic diagram of the in-situ test mold in this embodiment.

[0021] Figure 5 This is an exploded view of the in-situ test mold in this embodiment.

[0022] Figure 6 This is an exploded view of the temperature-controlled in-situ battery module in this embodiment.

[0023] Figure 7 This is a cross-sectional schematic diagram of the temperature-controlled in-situ battery module in this embodiment.

[0024] Figure 8 This is a cross-sectional schematic diagram of the temperature-controlled in-situ battery module in this embodiment.

[0025] Figure 9 This is a schematic diagram of the temperature control module in this embodiment.

[0026] Figure 10 This is a schematic diagram of the optical path in this embodiment.

[0027] Figure 11 This is another schematic diagram of the optical path in this embodiment.

[0028] Figure 12 This is a comparison chart of the electrochemical performance of the in-situ battery module and the standard coin cell in this embodiment.

[0029] Figure 13 This is a comparison of the imaging effects of the optical system imaging and SEM imaging in this embodiment.

[0030] Figure 14 This is a sequence of optical images of multiple particles collected during a single test in this embodiment.

[0031] Figure 15 This is the target particle image and the corresponding rolling difference image in this embodiment. Detailed Implementation

[0032] To further understand the content of this invention, the invention will be described in detail with reference to the embodiments. It should be understood that the embodiments are merely illustrative and not limiting of the invention.

[0033] like Figure 1 , Figure 2As shown, this embodiment provides an in-situ optical battery characterization device, which includes a support base 100, an in-situ battery module and an optical imaging system disposed on the support base 100. The in-situ battery module is used to connect to a battery comprehensive tester to simulate the battery working process, and the optical imaging system is used to acquire images of electrode particles at the electrode sheet of the battery under test during the working process of the in-situ battery module.

[0034] In this embodiment, the entire in-situ optical cell characterization device is a single-particle dynamic process in-situ optical characterization system for batteries. As a rapid and low-cost imaging platform, it is used to visualize and quantify ion dynamics at the single-particle level. Furthermore, by introducing a three-dimensional electrodynamic displacement platform, it can also achieve multi-particle acquisition of the same battery, thereby characterizing the spatial heterogeneity on the same electrode and providing more comprehensive guidance for battery design and optimization. The support base 100 primarily provides the stable environment required for the experiment; the battery electrode sample to be tested is placed in the in-situ battery module, which provides the pressure, gas, and temperature environment required for normal battery operation, ensuring the normal electrochemical performance of the electrode materials; the in-situ battery module is placed on the sample stage of the three-dimensional displacement platform, and optical images are acquired and calibrated in real time through the image acquisition unit and image calibration system, enabling long-term, rapid, and stable monitoring and analysis.

[0035] like Figure 3 As shown, in this embodiment, the support base 100 includes a vibration isolation device and a support platform 330. The vibration isolation device includes an elastic component 310 and a viscous damping component 320. The elastic component 310 is used to suspend the support platform 330. The viscous damping component 320 includes silicone oil and a damping member 321 immersed in the silicone oil. The damping member 321 is fixedly connected to the support platform 330.

[0036] In this embodiment, all modules are integrated on a support base 100 that can provide a stable vibration isolation environment for optical experiments. The support stage 330 integrates all modules used for optical experiments, and the vibration isolation device reduces the impact of mechanical vibration on experimental accuracy through reasonable design and optimization, thereby reducing the impact on the entire in-situ optical cell characterization device.

[0037] The design of the suspension platform 330 via the elastic component 310 effectively isolates common low-frequency vibrations (1Hz to 10Hz) found in buildings, such as those from pedestrians, equipment operation, or environmental noise, reducing interference from the laboratory building to experiments. The elastic component 310 can use steel springs, which have good creep resistance and can bear heavy loads for a long time without deformation, making them suitable for long-term experimental needs. The viscous damping component further enhances the vibration isolation performance. By immersing the damping element in silicone oil, vibration reduction in all six degrees of freedom (including translation and rotation) is achieved. For better results, a sphere is used for the damping element, and high-viscosity silicone oil is used. This design effectively reduces the coupling phenomenon between different degrees of freedom of vibration and optimizes the vibration attenuation efficiency, performing particularly well in the frequency range of 1Hz to 10Hz. This vibration isolation device is not only inexpensive but also superior in performance, especially in isolating low-frequency vibrations. The design of the bearing base 100 using this vibration isolation device is also highly flexible, and can be adjusted according to different requirements of load, spring constant and damping coefficient to adapt to different experimental environments.

[0038] like Figure 4 , 5 As shown, in this embodiment, the in-situ battery module includes a room temperature in-situ battery module. The ambient temperature in-situ battery module includes a main housing 410, one end of which is fixed to a base 420 by screws, and the other end of which is fixed to a cover plate 430 by screws. A transparent substrate 440 is disposed between the base 420 and the main housing 410, and a first sealing ring is disposed between the transparent substrate 440 and the main housing 410; a second sealing ring is disposed between the cover plate 430 and the main housing 410. One end of the main housing 410 forms a first battery cavity 411 for filling electrolyte. Inside the first battery cavity 411, in a direction away from the one end, the battery electrode to be tested, the insulating membrane, the auxiliary electrode and the sliding first metal pressure block 450 are arranged in sequence. A spring cavity 412 is provided through the first battery cavity 411 and the other end of the main housing 410. A second metal pressure block 460 is slidably provided in the spring cavity 412. A metal spring is provided between the first metal pressure block 450 and the second metal pressure block 460. A first auxiliary electrode lead-out threaded hole 431 is provided on the cover plate 430 corresponding to the spring cavity 412. A first auxiliary electrode lead-out threaded post is provided at the first auxiliary electrode lead-out threaded hole 431 with thread engagement. The outer diameter of the first auxiliary electrode lead-out threaded post does not exceed the inner diameter of the spring cavity 412. The main housing 410 is also provided with an eccentrically axially extending lead-out channel 413 for the first battery electrode to be tested, and the base 420 is provided with a first observation hole 421 at the battery electrode to be tested for cooperation with the optical imaging system.

[0039] In-situ battery modules can form a sealed cavity without participating in electrochemical reactions, providing the pressure, gas, and temperature environment required for normal battery operation and ensuring the normal electrochemical performance of the electrode materials (battery electrodes under test). Figure 12 As shown, the in-situ battery module in this embodiment has almost the same electrochemical performance as a standard coin cell. Meanwhile, the transparent substrate 440, i.e., the transparent glass substrate, located at one end of the sealed cavity facilitates optical observation.

[0040] like Figures 6-8 As shown, in this embodiment, the in-situ battery module also includes a temperature-controlled in-situ battery module; The temperature-controlled in-situ battery module includes a heat-conducting housing 610 made of metal, and a mounting base 620 is fixed to one end of the heat-conducting housing 610 by screws. A transparent baffle 630 is provided between the mounting base 620 and the heat-conducting housing 610, and a third sealing ring is provided between the transparent baffle 630 and the heat-conducting housing 410; A second battery cavity 611 for filling electrolyte is formed at one end of the heat-conducting housing 610. Inside the second battery cavity 611, in the direction away from the first end, the battery electrode to be tested, the insulating membrane, the auxiliary electrode, the third metal pressure block and the fourth metal pressure block are arranged sequentially. The third metal pressure block can be, for example, a stainless steel gasket, and the fourth metal pressure block can be, for example, a stainless steel spring sheet, nickel foam, etc. A second auxiliary electrode lead-out threaded hole 612 is provided radially on the side wall of the heat-conducting housing 610, and a second auxiliary electrode lead-out threaded post is provided at the second auxiliary electrode lead-out threaded hole 612; The heat-conducting housing 610 is also eccentrically provided with a second lead-out channel 613 for the battery electrode under test along the axial direction, and the mounting base 620 corresponds to the second observation hole 621 of the battery electrode under test for cooperation with the optical imaging system.

[0041] In this embodiment, the heat-conducting housing 610 is made entirely of stainless steel, which has excellent thermal conductivity. The mold also ensures that it forms a sealed cavity without participating in the electrochemical reaction. The metal heat-conducting housing 610, including stainless steel, provides excellent thermal conductivity, while the fourth metal pressure block, made of nickel foam, applies sufficient pressure between the upper and lower electrode materials while reducing the internal cavity volume, ensuring that the battery's electrochemical performance remains unaffected.

[0042] like Figure 9As shown, in this embodiment, the temperature-controlled in-situ battery module is used in conjunction with a temperature control system, which includes... A thermocouple temperature sensor is provided at the heat-conducting housing 610. The thermocouple temperature sensor is used to collect the temperature at the heat-conducting housing 610 and send it to a temperature controller. A semiconductor cooling chip is disposed on the heat-conducting housing 610, and the cold end of the semiconductor cooling chip is attached to the outer wall of the heat-conducting housing 610. A heat exchanger is installed at the hot end of a semiconductor cooling chip, and a cooling medium is circulated within the heat exchanger via a circulating pump. The temperature controller is used to control the temperature at the heat-conducting housing 610 based on the measured temperature and set temperature collected by the thermocouple temperature sensor, and by controlling the semiconductor cooling chip and the circulating pump.

[0043] In this embodiment, in cooling mode, the temperature control system activates a circulating pump to allow the cooling medium to flow through a heat exchanger attached to the hot end of the thermoelectric cooler, thereby continuously removing heat. The temperature controller dynamically adjusts the current of the thermoelectric cooler to achieve precise cooling. When heating is required, the circulating pump is shut off, and the temperature controller reverses the current flow to the thermoelectric cooler, switching its function from cooling to heating, thus achieving closed-loop temperature control. For investigating the properties of electrode materials at different temperatures, the temperature control module can attach a thermoelectric cooler or electric heating plate to a self-designed and developed temperature-controlled battery mold, using a circulating pump or thermocouple to achieve temperature regulation, thereby enabling rapid imaging detection and analysis from a minimum of -30 degrees Celsius to a maximum of 60 degrees Celsius. like Figure 10 As shown, in this embodiment, the optical imaging system includes a light source 130, a beam splitter 145, an objective lens 150, and a CCD camera 170. The light source 130 is used to generate incident light and transmit it to the electrode of the battery under test through the beam splitter 145 and the objective lens 150. The CCD camera 170 is used to collect the scattered light and reflected light from the glass substrate at the electrode of the battery under test transmitted back through the beam splitter 145.

[0044] In this embodiment, the incident light generated by the light source 130 is weakly coherent light with a wavelength of 660nm. A 4F optical system 141 consisting of two lenses, a pinhole aperture 142, a collimating lens 143, and a converging lens 144 are sequentially arranged between the light source 130 and the beam splitter 145.

[0045] In this embodiment, the light source 130 uses a weakly coherent LED as the light source to reduce the influence of the advanced interference ring and obtain higher imaging quality. In order to reduce the influence of beam energy on the battery electrode sample under test, a longer wavelength of 660nm is selected, which can minimize the photothermal effect and photochemical damage to sensitive battery materials (especially in the electrolyte environment) and ensure that the observation process does not affect the electrochemical behavior of the material itself. The selection of the light source wavelength can also be varied according to the characteristics of the sample under test. After a series of beam processing components, the beam emitted by the light source 130 is processed and then incident on the glass substrate of the in-situ battery module in the form of parallel light through the objective lens, ensuring that the light spot irradiated on the sample is uniform and collimated parallel light. After that, the incident light is reflected by the upper surface of the glass substrate and used as reference light. The incident light hits the sample particles and excites the sample scattered light. The two beams interfere and superimpose and are then incident on the camera photosensitive plane through the imaging lens.

[0046] In this embodiment, a 4f system 141 composed of two lenses corrects the diverging beam emitted by the light source 130, while accurately transmitting the intensity distribution on the surface of the light source 130 to the output surface, thus "purifying" and "shaping" the beam. A pinhole aperture 142 filters out high-frequency noise and stray light introduced by uneven LED illumination or lens edge aberrations, allowing only the central portion with the most uniform energy and flattest wavefront to pass through. A collimating lens 143 and a converging lens 144 ensure that the beam is ideally incident on the back focal plane of the objective lens 150. This series of precise beam processing operations collectively ensures that the light field illuminating the battery electrode sample under test is highly uniform and collimated parallel light, minimizing optical aberrations and providing a clean background for detecting weak ion dynamics signals.

[0047] The specific optical path for interference scattering microscopy in this embodiment is as follows: an LED is selected as the light source 130 to reduce the influence of higher-order interference rings and obtain higher imaging quality. To reduce the influence of beam energy on the sample, a longer wavelength of 660nm is selected. The diverging light emitted by the light source is corrected by a 4f system 141 consisting of two 40mm focal length lenses. After passing through a small aperture 142 to select a relatively uniform small area in the beam, it is collimated by a 50mm focal length lens and then converged by a 300mm focal length lens through a beam splitter 145 to the back focal plane of the objective lens 150. The objective lens 150 then incident the sample slide as parallel light. After this, the incident light is reflected by the upper surface of the glass substrate and used as reference light. The incident light hits the sample particles and excites sample scattered light. The two beams interfere and superimpose, and then are incident on the photosensitive plane of the CCD camera through an imaging lens 160 with a focal length of 500mm, completing the imaging.

[0048] like Figure 11As shown, the light source 130 in this disclosure can also be a laser light source. A lens, a diffuser, a fiber optic coupler, an optical fiber, a pinhole aperture 142, a collimating lens 143, and a converging lens 144 are sequentially arranged between the light source 130 and the beam splitter 145.

[0049] To reduce speckle caused by interference between optical components and the battery electrode surface, a high-speed motor drives a glass scattering plate to scatter the laser beam, reducing its spatial coherence while maintaining temporal coherence. The scattered laser beam passes through a beam processing assembly and then through an objective lens, incident as parallel light onto the glass substrate of the in-situ battery module, ensuring that the light spot irradiating the sample is uniform.

[0050] In the actual optical imaging system, two front mirrors of the beam-splitter cube 145 are used to reflect the light path, facilitating the adjustment of the beam's exit angle. A rear mirror of the beam-splitter cube 145 reflects the light to the back focal plane of the vertically placed objective lens 150. Objective lens 150 uses a 100x magnification oil immersion lens to achieve better imaging. The in-situ battery module is fixed on the sample stage 110 for placement. During testing, the battery integrated tester is connected to the in-situ battery module via alligator clips to provide the electrical signal stimulation required for battery operation.

[0051] In this embodiment, the in-situ battery module is located at a three-dimensional displacement platform 120.

[0052] The three-dimensional displacement platform consists of an XYZ three-axis stepper motor and a Z-axis piezoelectric controller. The XYZ three-axis stepper motor has a large stroke and micron-level position control capability. The Z-axis piezoelectric controller, also known as a Z-axis high-precision piezoelectric displacement driver, has a 20μm stroke and a resolution as low as 1nm. Together, they can perform high-precision, large-range scanning of the position of the in-situ battery module.

[0053] This embodiment utilizes a three-dimensional displacement platform to precisely control the position of the in-situ battery module, enabling multi-particle acquisition from the same battery unit, characterizing spatial heterogeneity, and improving measurement efficiency. The behavior of electrode materials on macroscopic electrode sheets is not uniform; particles at different locations may exhibit different electrochemical activities (i.e., spatial heterogeneity). Traditional observation methods often only focus on individual particles, failing to reflect this overall inhomogeneity. A high-precision three-dimensional displacement platform significantly expands the system's observation capabilities, allowing for precise movement of the sample stage. This means that in a single experiment, researchers can sequentially or according to a predetermined procedure move multiple different single particles to the center of the field of view for observation, achieving multi-particle acquisition from the same battery unit and thus characterizing spatial heterogeneity on the same electrode. The design of the entire mounting platform allows for comparison of the kinetic behavior of different particles under identical electrochemical conditions (same battery, same cycle), providing more comprehensive and statistical data for understanding the overall performance and failure mechanisms of electrode materials, avoiding the randomness of single-point observations, and significantly improving the information output and efficiency of the experiment.

[0054] The present invention also provides an in-situ optical cell characterization method, which uses the above-mentioned in-situ optical cell characterization device to acquire optical image sequences of electrode particle images during the working process of the electrode sheet of the battery under test; and achieves in-situ characterization of the electrode sheet of the battery under test based on the processing of the optical image sequences.

[0055] The specific steps include: assembling the in-situ optical battery characterization device, assembling each module on the support base 100, and placing the battery electrode sample to be tested in the in-situ battery module; adjusting the temperature of the in-situ battery module through the temperature control module to keep it within a preset temperature range; applying a preset electrical signal stimulus to the battery electrode sample in the in-situ battery module through a battery comprehensive tester to simulate the operation process of the battery electrode sample; performing optical imaging on the battery electrode sample through an optical imaging system; controlling the movement and motion compensation of the battery electrode sample through a three-dimensional displacement platform; acquiring optical images of the battery electrode sample, and performing real-time detection and adjustment during the acquisition process to obtain a stable optical image sequence; processing and analyzing the optical image sequence to obtain the optical analysis results of the operating performance of the battery electrode sample. This method achieves reliable in-situ characterization, obtains accurate optical analysis results, and provides key data for battery research.

[0056] During the charging and discharging process, batteries often expand and contract, and the sample tends to move downwards under the influence of gravity. This causes the Z-axis (perpendicular to the optical platform) to move in a regular direction. Under this influence, the sample will gradually move away from the focal plane, resulting in a gradually blurred image.

[0057] This embodiment provides a method for acquiring optical image sequences of electrode particles. When acquiring optical image sequences of electrode particles at the electrode sheet of a battery module under test, located on a three-dimensional displacement platform 120, using an optical imaging system, the method includes: Establish a set of scanning path points for the 3D displacement platform 120; The three-dimensional displacement platform 120 is driven to move point by point to each scanning path point in the set of scanning path points in sequence, and a target spatial database is constructed based on the identification of the target electrode particles; Set the number of iterations, perform traversal imaging of all target electrode particles in the target spatial database, and construct an optical image sequence of all target electrode particles.

[0058] In this embodiment, the in-situ battery module with the sample (i.e., the battery electrode to be tested) is fixed on a three-dimensional displacement platform 120. The three-dimensional displacement platform 120 scans different positions of the sample point by point. Specifically, after placing the experimental sample, the three-dimensional displacement platform 120 is used to move the sample to determine if there are target particles in the imaging area. If no target particles are found, the platform moves to the next position. If target particles are found, the coordinates of the three-dimensional displacement platform are recorded, and the target particle image is cropped (to reduce data volume). The center position of the target particle in the cropped image is recorded, and the platform moves to the next position. After all scans are completed, the three-dimensional coordinates of several target particles, the image center coordinates, and the corresponding serial numbers of the target particles are obtained, thus establishing a set of scanning path points for the three-dimensional displacement platform 120. Subsequently... Data acquisition begins. Upon starting acquisition, the 3D displacement platform 120 is moved to the target particle's position. At this point, the cropped image of particle n is displayed within the image acquisition frame. The platform uses z-axis movement to automatically focus and find the optimal focus point. The platform moves the sample to this z-axis coordinate, ensuring the image in the acquisition frame remains at the sharpest focal length. This image is then acquired and stored, and the z-axis coordinate of particle n in the target particle coordinate table is updated. Next, the platform moves to the position of target particle n+1 and executes the next acquisition step. Assuming that acquiring images from particles 1 to n constitutes one acquisition cycle, and with a preset number of cycles, all target electrode particles in the target spatial database are imaged, constructing an optical image sequence of all target electrode particles.

[0059] In this embodiment, the position of the in-situ battery module is precisely controlled using a three-dimensional displacement platform 120, enabling multi-particle acquisition from the same battery unit, characterizing spatial heterogeneity, and improving measurement efficiency. The behavior of electrode materials on the macroscopic electrode sheet is not uniform; particles at different locations may exhibit different electrochemical activities (i.e., spatial heterogeneity). Traditional observation methods often only focus on individual particles, making it difficult to reflect this overall non-uniformity. This embodiment utilizes a high-precision three-dimensional displacement platform 120, greatly expanding the system's observation capabilities and allowing for precise movement of the sample stage. This means that in a single experiment, researchers can sequentially or according to a predetermined program move multiple different single particles to the center of the field of view for observation, achieving multi-particle acquisition from the same battery unit, thereby characterizing the spatial heterogeneity on the same electrode sheet, such as... Figure 14 As shown, Figure 14 This is a sequence of optical images of multiple particles acquired during a single test. The design of the entire mounting platform allows for comparison of the kinetic behavior of different particles under identical electrochemical conditions (same cell, same cycle), providing more comprehensive and statistical data for understanding the overall performance and failure mechanisms of electrode materials. This avoids the randomness of single-point observations and significantly improves the information output and efficiency of the experiment.

[0060] In this embodiment, the expression for the set of scanned path points P is: ; in, This represents the i-th scan path point in the set of scan path points P. , and Indicates scanning path points The x-axis displacement, y-axis displacement, and z-axis displacement.

[0061] In this embodiment, the system is first initialized to ensure that the scanning path covers the entire sample area to be tested. The scanning path point set is obtained through pre-scanning to identify and record the initial spatial state of all target particles.

[0062] In this embodiment, the three-dimensional displacement platform 120 is driven to move point by point to each scanning path point in the set of scanning path points. Based on the identification of the target electrode particles, a target spatial database is constructed. This includes acquiring the original image of the current field of view through an optical imaging system when the three-dimensional displacement platform 120 moves to any scanning path point in the set of scanning path points. The system determines whether target electrode particles exist in the original image. If not, it controls the 3D displacement platform 120 to move to the next scanning path point. If they exist, the system uses the current order n of the target electrode particles as the corresponding target electrode particle number and the coordinates of the current scanning path point as the platform coordinates of the corresponding target electrode particle. and the image coordinates of the target electrode particles in the original image. As the image center coordinates of the corresponding target electrode particles; The identification of all target electrode particles, number n, and platform coordinates. Image center coordinates and the corresponding target image Construct the target space database Q; in, ; in, This represents the nth data entry in the target spatial database Q.

[0063] In this embodiment, after traversing all predetermined locations, the serial numbers, initial platform coordinates, initial image center coordinates, and associated cropped images of all successfully identified target particles are integrated to form an initial target spatial database. By establishing this database and introducing visual feedback and motion compensation mechanisms in subsequent acquisition cycles, high-throughput, high-precision, and long-term stable automatic observation can be achieved. Specifically, before the experiment officially begins, a pre-scanning process is executed to identify and record the initial spatial state of all target particles to construct the target spatial database, which improves the efficiency of subsequent data acquisition and correction.

[0064] In this embodiment, for any target electrode particle, the corresponding original image is cropped to obtain a sub-image region containing the corresponding target electrode particle, which is then used as the corresponding target image. ; In this context, the image coordinates of the feature points or centroids of the target electrode particles in the original image are used as the corresponding image center coordinates. .

[0065] In this embodiment, cropping the original image can reduce the amount of data and simplify the data to avoid unnecessary waste of computing power. Then, the image coordinates of the feature points or centroids of the target electrode particles in the original image are recorded, and the serial number of the target particles and the coordinates of the image center are collected.

[0066] In this embodiment, a set number of iterations is set to perform traversal imaging of all target electrode particles in the target spatial database, constructing an optical image sequence of all target electrode particles, including... In a single traversal loop, all target electrode particles in the target spatial database Q are sequentially traversed and imaged. For any target electrode particle, the target image acquired in each traversal cycle corresponds to that target electrode particle. This is an optical image sequence corresponding to the target electrode particles.

[0067] In this embodiment, traversal imaging of any target electrode particle in a single traversal loop includes, Retrieve the corresponding platform coordinates from the target space database Q. Control the three-dimensional displacement platform 120 to move to the corresponding position; Based on planar position compensation, the x-axis compensation amount and y-axis compensation amount of the three-dimensional displacement platform 120 are obtained; Based on focus compensation, the z-axis compensation amount of the three-dimensional displacement platform 120 is obtained; Platform coordinates based on x-axis compensation, y-axis compensation, and z-axis compensation. Perform the update and control the 3D displacement platform 120 to move to the updated platform coordinates. At this location, complete the corresponding target image. The collection.

[0068] This embodiment utilizes a real-time calibration system to compensate for sample offsets along the Z-axis and X and Y-axis directions, ensuring image clarity and stability during long-term acquisition, preventing target particles from moving out of the field of view, and extending the system's stable operating time. Maintaining the stability of the observed target during experiments lasting several hours or even tens of hours is a significant challenge. Volume changes during battery charging and discharging, the effects of gravity, minute tension in the electrode leads, and errors in the motor itself can all cause sample drift in three-dimensional space. Drift along the Z-axis (vertical direction) can cause the sample to defocus, resulting in image blurring; drift in the XY plane can cause target particles to move out of the camera's field of view, leading to data interruption. The image calibration system used in this embodiment integrates Z-axis calibration (focus compensation) and two-dimensional plane calibration (planar position compensation), forming an active, real-time feedback control loop, thereby maximizing the stable operating time of the entire system. This real-time active calibration, compared to post-processing digital images, fundamentally avoids defocusing, blurring, and target loss, ensuring that every frame acquired is clear and usable, providing technical support for obtaining continuous, complete, and high-quality dynamic process sequences.

[0069] In this embodiment, obtaining the x-axis compensation and y-axis compensation of the three-dimensional displacement platform 120 based on planar position compensation includes controlling the three-dimensional displacement platform 120 to move to the platform coordinates before the update. At this point, focus compensation is performed to obtain the z-axis compensation amount of the three-dimensional displacement platform 120; The z-axis offset of the three-dimensional displacement platform 120 is controlled based on the z-axis compensation amount; Acquire the first raw image; Based on the feature points or centroids of the target electrode particles, the image coordinates of the first original image and the corresponding image center coordinates The deviation is used to obtain the x-axis compensation amount. and y-axis compensation amount ; Based on x-axis compensation amount and y-axis compensation amount Control the x-axis and y-axis offset of the three-dimensional displacement platform 120; Acquire a second original image, and obtain the corresponding target image based on cropping of the second original image. .

[0070] This embodiment constructs a comprehensive active stabilization system, specifically addressing two main dimensions of sample drift in in-situ testing: In the Z-axis direction, volume changes (expansion / contraction) of active materials during battery charging and discharging, along with thermal drift, cause the sample to move along the optical axis, deviating from the optimal depth of focus of the objective lens 150, resulting in image blurring; in the XY plane, minute stresses on the electrode leads and mechanical vibrations can cause lateral movement of the sample, leading to the target particles slowly drifting out of the camera's limited field of view, resulting in observation interruption. The three-dimensional displacement platform 120 performs real-time detection and adjustment during acquisition, ensuring that calibration and image acquisition are synchronized. This allows for rapid resolution of problems as they occur, guaranteeing that the acquired original image sequence is clear and stable from the outset. This not only eliminates a significant amount of tedious post-processing data but, more importantly, ensures the integrity and continuity of long-term experimental data, providing indispensable technical support for studying slow-speed dynamic processes such as lithium-ion battery charging and discharging.

[0071] In this embodiment, focus compensation is achieved based on an external calibration laser.

[0072] The process involves emitting a calibration laser beam from a calibration laser source; guiding the calibration laser beam reflected from the battery electrode sample to be tested to an image acquisition camera to form a light spot via a feedback optical path based on the external calibration laser setting; calculating the offset of the target particle in the optical image by analyzing the movement of the light spot using a computer, and calculating reverse displacement compensation based on the offset of the target particle.

[0073] Focus compensation is achieved using an externally applied calibration laser. The laser calibration system mainly consists of two parts: a Z-axis feedback optical path and a LabVIEW program. The Z-axis feedback optical path is largely shared with the interference scattering microscopy optical path. To calibrate the Z-axis, a 780nm laser diode with lower thermal effects is selected as the laser source. After beam expansion and collimation, the light emitted from the laser source is focused onto the rear focal plane of the objective lens. Under the action of the objective lens, it is incident on the glass substrate as parallel light. The reflected light then passes through the objective lens and a polarizing beam splitter before entering the second imaging lens, ultimately being received by the camera as elliptical parallel light. Unlike the interference scattering microscopy optical path, the incident light in the feedback optical path is slightly deviated from the optical axis. Therefore, when the sample moves up and down along the Z-axis, the light spot received by the camera will move back and forth in a certain direction. This can be achieved by adjusting the angle of the second imaging lens so that the minor axis of the elliptical light spot is parallel to the direction of light spot movement, facilitating subsequent operations.

[0074] The idea behind the Z-axis feedback program is to determine the movement of the sample along the Z-axis based on the movement of the light spot position, and then control the Z-axis offset of the three-dimensional displacement platform 120 to return the sample to its previous position.

[0075] In this embodiment, the minute displacement of the sample in the Z-axis direction is converted into the linear movement of the laser spot on the detector plane, thereby achieving displacement sensing and feedback control with nanometer-level precision.

[0076] In this embodiment, focus compensation is achieved based on the gradient extreme focal length calibration algorithm.

[0077] This embodiment demonstrates a focus calibration method based on image sharpness, also known as contrast-detection autofocus. It is a passive, self-contained calibration method that eliminates the need for additional laser sources and feedback optical paths, directly utilizing information from the imaging optical path itself for focus determination. The core principle of this method is that when the sample is at its optimal focal plane, the local contrast or high-frequency components (i.e., edge information) of its optical image are richest, resulting in the clearest image. In situations where high optical path simplicity is required or additional lasers cannot be introduced, utilizing the image information itself as a feedback signal achieves fully automatic, adaptive focus maintenance, effectively improving the overall contrast and usability of the image sequence.

[0078] This embodiment also provides an in-situ optical cell characterization method, which uses the above-mentioned optical image sequence acquisition method to acquire optical image sequences of electrode particles during the working process of the battery electrode sheet under test; and based on the processing of the optical image sequence, in-situ characterization of the battery electrode sheet under test is achieved.

[0079] This embodiment achieves fully automated and synchronized control from electrochemical stimulation to optical response acquisition, greatly improving the repeatability, reliability, and throughput of the experiment.

[0080] This embodiment provides an in-situ optical characterization method for the dynamic process of a single battery particle, which includes: Configure in-situ battery module; During the operation of the in-situ battery module, the differential capacity curve, operating voltage curve, and optical image sequence of the electrode of the battery under test are acquired. Based on the differential capacity curve, the working voltage curve, and the optical image sequence at the electrode of the battery under test, dynamic in-situ optical characterization of the electrode particles on the electrode of the battery under test in the in-situ battery module is completed.

[0081] In this embodiment, an optical imaging system is assembled, and optical imaging is performed on the battery electrode sample to be tested in the original battery module using the optical imaging system. During the acquisition process, the acquired optical images are detected and adjusted in real time to obtain a stable optical image sequence. Finally, the optical image sequence is processed and analyzed to obtain the optical analysis results of the operating performance of the battery electrode sample to be tested.

[0082] In this embodiment, the working process of the in-situ battery module is simulated using a battery comprehensive tester, and the differential capacity curve and working voltage curve of the in-situ battery module are collected.

[0083] In this embodiment, the optical image sequence of the battery electrode under test is acquired based on an optical imaging system. The optical image sequence includes multiple electrode particle images of the electrode particles of the battery electrode under test arranged in a time sequence within one working cycle; wherein, the first electrode particle image in the optical image sequence corresponds to the electrode particle image of the battery electrode under test in a non-working state.

[0084] In this embodiment, after acquiring the original optical image sequence at the electrode of the battery under test based on the optical imaging system, the optical image sequence is obtained by preprocessing and deep processing the original optical image sequence.

[0085] In this embodiment, the original optical image sequence is preprocessed and deeply processed, including data processing of the acquired optical image sequence. The data processing includes: processing the optical image sequence based on the rolling difference algorithm to improve the contrast and signal-to-noise ratio of the optical image sequence; and performing image stabilization processing on the optical image sequence based on the accelerated robust feature algorithm to compensate for the overall translational jitter of the optical image sequence.

[0086] In this embodiment, the preprocessing of the original optical image sequence includes image stabilization processing of any original electrode particle image in the original optical image sequence based on a feature point matching algorithm.

[0087] In this embodiment, image stabilization processing is performed on any original electrode particle image in the original optical image sequence based on a feature point matching algorithm, including: Feature points of each electrode particle image in the original optical image sequence are obtained based on the Hessian matrix; where the determinant expression of the Hessian matrix is, , It is a scaling factor; Based on the coordinate offset values ​​of the feature points between the corresponding original electrode particle image and the first electrode particle image, the corresponding original electrode particle image is translated to complete the image stabilization processing of any original electrode particle image based on the feature point matching algorithm.

[0088] In this embodiment, during actual testing, the experimental device is inevitably affected by the environment, causing the acquired images to jitter. This jitter can affect the accuracy of the experimental results. A video stabilization algorithm based on feature point matching is selected to suppress this phenomenon. In this embodiment, the image stabilization processing of the optical image sequence based on the accelerated robust feature algorithm is specifically as follows: The Speeded Up Robust Features (SURF) algorithm was selected for feature point matching. This algorithm is a classic algorithm in the field of computer vision and has been widely used in video stabilization, image stitching and other fields. The algorithm mainly consists of three parts: local feature point extraction, feature point description and feature point matching.

[0089] First, the Hessian matrix is ​​constructed to generate stable abrupt change points in the image. For an image I(x,y), its Hessian matrix is ​​as follows:

[0090] Before processing, the original image is often subjected to Gaussian filtering. The filtered Hessian matrix is ​​represented as follows:

[0091] in: The second derivative of the Gaussian function is the same as its graph. At point The result of the convolution; , The meaning is similar; the determinant of the Hessian matrix can be obtained from the Hessian matrix.

[0092] To improve computational speed, a box filter is used instead of a Gaussian filter, so a scaling factor is introduced. (Approximately 0.9):

[0093] After obtaining the local extrema at each scale by calculating the determinant of the Hessian matrix, each local extrema, along with its eight neighboring points at the same scale and nine points at each of its upper and lower scales, forms a 3x3x3 three-dimensional neighborhood. When a local extrema is the largest (or smallest) point in this three-dimensional neighborhood, that pixel is considered a candidate feature point.

[0094] In this embodiment, the deep processing of the original optical image sequence includes, For any original electrode particle image, the original electrode particle image of the previous moment in the original optical image sequence is used as the reference frame, and the original electrode particle image is used as the detection frame to obtain the rolling differential image of the original electrode particle image. The rolling differential image corresponding to each original electrode particle image in the original optical image sequence is used as the optical image sequence.

[0095] In this embodiment, the optical image sequence is processed based on the rolling difference algorithm as follows: For the interferometric scattering microscopy technique used in this embodiment, considering the excitation light as... The reference photoelectric field is r and s are the reflection coefficient and scattering coefficient, respectively, and the signal detected by the detector. for:

[0096] The first contribution comes from the reference light: The second item is the intensity of scattered light. The third term is an interference term. ,in The second term represents the phase difference between the reference light and the scattered light. When the target particles are relatively small, this second term is generally negligible. Therefore, the normalized contrast of the optical image can be defined as follows: (This is the sum of the detected signal with particles present and the background signal without particles, followed by normalization.)

[0097] For subtle changes in a planar dimension, information often cannot be directly obtained from the original optical image acquired by the optical imaging system; therefore, processing of the original image is necessary. Similar to normalized contrast, this involves processing the frame before the change. As a reference frame, the changed frame Normalized contrast is calculated as a measure of the probe frame:

[0098] The obtained DRA is the rolling difference image. The algorithm that performs the same processing on each frame of the time series is called the rolling difference algorithm. Based on this, rolling difference can also be performed by calculating the mean of the images in the same time window of the reference frame and the probe frame. The mean is used to smooth the sequence, thereby eliminating noise in the image sequence and improving the signal-to-noise ratio of the image.

[0099] like Figure 15 As shown, Figure 15 In the diagram, AP is the optical image of the target particle during the test, while (a) and (b) are the corresponding rolling difference images obtained through the rolling difference algorithm. This embodiment further extracts and enhances useful signals at the algorithmic level and eliminates residual mechanical jitter, ultimately yielding data suitable for precise quantitative analysis. Optical image signals contain a strong reference light background. The rolling difference algorithm, by differentiating the current frame from the previous frame or the average frame within a time window, can significantly suppress invariant background noise, thereby highlighting minute optical contrast changes (such as refractive index and thickness changes) caused by ion embedding / extraction, making phase transition fronts (such as "shrinking nuclei" patterns) that were previously difficult to detect in the original image clearly visible. On the other hand, despite real-time calibration, sub-pixel-level high-frequency jitter may still exist. Image stabilization algorithms calculate the global translation vector between frames by detecting the feature point matching relationship between each frame and the reference frame, and perform reverse compensation. By processing the optical image sequence through the data processing unit, the real dynamic signal of the sample is amplified and the system noise is suppressed, which significantly improves the signal-to-noise ratio and resolvability of the image sequence, laying a solid foundation for extracting accurate quantitative information (such as phase transition rate) from optical images.

[0100] The optical system imaging and SEM imaging comparison in this embodiment are as follows: Figure 13 As shown, Figure 13 For optical image acquisition effects, among which, Figure 13 A represents a comparison between the optical image and the SEM image. Figure 13 B represents the change of the optical image over time. Figure 13 The comparison between the imaging effect of the optical imaging system of this embodiment and the SEM effect is shown, demonstrating that the optical system of this embodiment has excellent ability to characterize single particles. Figure 13 B demonstrates the detection of the same particle for up to 220 hours, indicating that the optical system of this embodiment has high stability and can stably detect changes in single or even multiple target particles with high sensitivity over a long period of time.

[0101] It is readily understood that those skilled in the art can combine, split, or reorganize the embodiments provided in this application to obtain other embodiments, all of which do not exceed the protection scope of this application.

[0102] The present invention and its embodiments have been described above illustratively. This description is not restrictive, and the embodiments shown are only part of the embodiments of the present invention. The actual structure is not limited thereto. Therefore, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A method for in-situ optical characterization of dynamic processes of battery single particles, configuring an in-situ battery module; during the working process of the in-situ battery module, collecting a differential capacity curve, a working voltage and current curve, and an optical image sequence of the battery electrode sheet to be measured of the in-situ battery module; based on the differential capacity curve, the working voltage and current curve, and the optical image sequence of the battery electrode sheet to be measured, completing the in-situ optical characterization of the dynamic processes of the electrode particles on the battery electrode sheet to be measured in the in-situ battery module.

2. The method of battery single particle dynamic processes in-situ optical characterization according to claim 1, characterized in that: The working process of the in-situ battery module is simulated by a battery comprehensive tester, and the differential capacity curve and the working voltage and current curve of the in-situ battery module are collected.

3. The method of battery single particle dynamic processes in-situ optical characterization according to claim 1, characterized in that: The optical image sequence of the battery electrode sheet to be measured is collected based on an optical imaging system, and the optical image sequence includes a plurality of electrode particle images of the electrode particles at the battery electrode sheet to be measured in a working cycle in time sequence; wherein the first electrode particle image in the optical image sequence corresponds to an electrode particle image of the electrode particles at the battery electrode sheet to be measured in a non-working state.

4. The method of battery single particle dynamic processes in-situ optical characterization according to claim 3, characterized in that: After the original optical image sequence of the battery electrode sheet to be measured is collected based on the optical imaging system, the optical image sequence is obtained based on the preprocessing and deep processing of the original optical image sequence.

5. The method of battery single particle dynamic processes in-situ optical characterization according to claim 4, characterized in that: The preprocessing of the original optical image sequence includes image anti-shake processing of any original electrode particle image in the original optical image sequence based on a feature point matching algorithm.

6. The method of battery single particle dynamic processes in-situ optical characterization according to claim 5, characterized in that: The image anti-shake processing of any original electrode particle image in the original optical image sequence based on the feature point matching algorithm includes, The characteristic points of each electrode particle image in the original optical image sequence are obtained based on a Hessian matrix, wherein a determinant expression of the Hessian matrix is, , is a proportional factor. based on the coordinate offset value of the feature points of the corresponding original electrode particle image and the first electrode particle image, performing translation on the corresponding original electrode particle image to complete the image anti-shake processing of any original electrode particle image based on the feature point matching algorithm.

7. The method of battery single particle dynamic processes in-situ optical characterization according to claim 4, characterized in that: The deep processing of the original optical image sequence includes, for any original electrode particle image, taking the original electrode particle image at the previous time in the original optical image sequence as a reference frame and taking the any original electrode particle image as a detection frame to obtain a rolling difference image of the any original electrode particle image, and taking the rolling difference image corresponding to each original electrode particle image in the original optical image sequence as the optical image sequence.

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