A method for rapid evaluation of powder hardness based on compaction density difference
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- XTC NEW ENERGY MATERIALS (NINGDE) CO LTD
- Filing Date
- 2026-03-24
- Publication Date
- 2026-06-30
Smart Images
Figure CN121898946B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to a rapid method for evaluating the hardness of powder based on the difference in compaction density, belonging to the technical field of testing or analyzing materials by measuring their chemical or physical properties. Background Technology
[0002] The mechanical properties of powder materials, especially their hardness (resistance to breakage), are among the core indicators determining their processing performance and final product quality. In the field of new energy battery materials, ternary cathode materials for lithium-ion batteries require high-temperature sintering during synthesis. The hardness of the intermediate product after sintering (usually a mixture of lumps and granules) directly determines the difficulty and energy consumption of crushing and pulverizing in subsequent powdering processes. Accurately assessing material hardness is of great guiding significance for optimizing production process parameters and ensuring batch-to-batch product consistency.
[0003] Currently, the industry mainly uses the following methods to evaluate the hardness and breakage resistance of powder or bulk materials:
[0004] The first method is the compaction hardness test. This method typically measures the macroscopic hardness of the powder aggregate after compaction. However, the measurement results of this method are strongly influenced by a variety of external factors, including particle geometry, particle size distribution, surface friction, and added lubricants. It reflects the overall performance of the powder aggregate rather than the intrinsic crushing resistance of the particles themselves, resulting in a weak correlation with the crushing performance of sintered blocks in subsequent actual production, making it difficult to serve as a reliable basis for process adjustments.
[0005] The second method is the powder shear test. Shear testing indirectly reflects hardness by measuring the cohesive strength and flowability of powders, and it has high repeatability in specific granular powder fields. However, this method has significant limitations: First, it requires the sample to be a "granular" material with a certain degree of flowability and cohesion. For hard, blocky materials formed after sintering, it is completely unsuitable because an effective shear surface cannot be formed within the shear chamber, and it may even damage the testing equipment. Second, shear testing usually involves measuring multiple normal stress points, and a single test takes a long time (usually more than 20 minutes), which cannot meet the needs of rapid detection and real-time feedback in production settings.
[0006] The third method relies on experience-based judgment. In actual production lines, operators often judge the hardness of materials based on the instantaneous current of the crusher or their sensory experience. This method is highly subjective, lacks quantitative standards, and has a significant time lag, making it difficult to achieve precise production control.
[0007] Therefore, there is an urgent need in this field for a rapid powder hardness assessment method that can eliminate external interference factors, accurately characterize the intrinsic plastic deformation behavior of materials, and is compatible with both powders and sintered blocks with high testing efficiency. Summary of the Invention
[0008] This invention provides a rapid method for evaluating powder hardness based on compaction density difference, which can effectively solve the above-mentioned problems.
[0009] This invention provides a rapid method for evaluating powder hardness based on compaction density difference, comprising the following steps:
[0010] The powdered material of ternary cathode material is obtained and subjected to sieving pretreatment to separate and remove fine powder particles;
[0011] The sieved material is loaded into a test mold and a multi-point compaction density test is performed to obtain the compaction density of the material at multiple increasing pressure points.
[0012] Based on the Heckel analysis model of powder compaction, the characteristic pressure ranges of the rearrangement zone and the plastic deformation zone of the material during the compaction process are determined; the pressure range corresponding to the characteristic pressure range of the rearrangement zone is 7.5 MPa to 50 MPa; the pressure range corresponding to the characteristic pressure range of the plastic deformation zone is 50 MPa to 150 MPa.
[0013] Calculate the compaction density difference Δρ_rearrangement in the rearrangement zone and the compaction density difference Δρ_plasticity in the plastic deformation zone within the characteristic pressure range of the rearrangement zone.
[0014] The Δρ rearrangement and Δρ plasticity are input into a pre-trained hardness classification discriminant model to calculate the classification threshold, thereby determining the hardness category of the ternary cathode material powder; the hardness classification discriminant model is a linear discriminant analysis (LDA) model or a logistic regression (LR) model.
[0015] The formula for calculating the compaction density of this invention is as follows: Where ρ is the compacted density of the powder (g / cm³) 3 m is the mass of the powder (g), and S is the cross-sectional area of the compacted powder (cm²). 2 h represents the thickness (mm) of the compacted powder.
[0016] The equation based on Heckel analysis is: Where D is the relative density (compacted density / true density) under pressure P, k is the slope of the straight line, and A is the intercept, which is related to the rearrangement during the powder compaction process.
[0017] In some embodiments, the specific conditions for the screening pretreatment are: using a 300 to 500 mesh screen and vibrating screening time of 10 to 15 minutes.
[0018] In some embodiments, when using a circular mold with a diameter of 16 mm, the characteristic pressure range of the rearrangement zone is 1500 N to 10000 N, and the characteristic pressure range of the plastic deformation zone is 10000 N to 30000 N.
[0019] In some embodiments, prior to performing the multi-point compaction density test, a blank calibration test is also performed on the test mold and system to eliminate the system's own elastic deformation under stress.
[0020] In some embodiments, the hardness classification model is a Linear Discriminant Analysis (LDA) model or a Logistic Regression (LR) model. This invention assesses hardness by analyzing the compaction behavior of powder within the plastic deformation characteristic range. The compaction range theory and Heckel model used are applicable to various powder systems. Furthermore, the core objective of the LDA model is to find the linear projection direction that most effectively separates samples of different categories. This is mathematically consistent with the objective of this invention—to find a linear decision boundary that accurately distinguishes between "soft" and "hard" materials. Features such as Δρ (plasticity) exhibit a strong linear trend with hardness categories, making LDA a suitable choice for handling such problems. In addition, the Logistic Regression (LR) model is also well-suited for handling binary classification problems, outputting the probability that a sample belongs to a particular category.
[0021] In some embodiments, when the hardness classification model is a Linear Discriminant Analysis (LDA) model, the classification threshold is calculated using the formula: Classification threshold F = A + B * Δρ rearrangement + C * Δρ plasticity, where A, B, and C are coefficients determined through training. When the classification threshold F is greater than 0, the material is classified as soft; when the classification threshold F is less than 0, the material is classified as hard.
[0022] In some embodiments, when using a circular mold with a diameter of 16 mm, the calculation formulas for Δρ rearrangement and Δρ plasticity are: Δρ rearrangement = ρ10000N - ρ1500N; Δρ plasticity = ρ30000N - ρ10000N.
[0023] The beneficial effects of this invention are:
[0024] High accuracy: This invention eliminates fine powder interference through screening pretreatment and focuses on the compaction density difference (Δρ) of the rearrangement zone and plastic zone, which is not sensitive to accidental factors such as particle shape. This parameter is strongly correlated with the intrinsic hardness of the material and is not sensitive to accidental factors such as particle shape. It fundamentally solves the problem of evaluation distortion caused by signal coupling in the traditional compaction method, and the material hardness recognition rate reaches 93.33%.
[0025] Highly efficient testing: It eliminates the need for complex powder shear testing, and the time for a complete single-sample test is controlled within 3 minutes, meeting the needs of real-time process adjustment on the production site.
[0026] Wide applicability: It is perfectly suited for hard and brittle materials, from powder to sintered blocks, overcoming the stringent requirement of shear testing and other techniques that require the sample to be a cohesive granular material. It breaks through the limitations of these techniques in the detection of bulk materials, thus achieving a direct and accurate characterization of resistance to breakage. Attached Figure Description
[0027] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained from these drawings without creative effort.
[0028] Figure 1 This is a schematic diagram of the test mold.
[0029] Figure 2 The compaction density-pressure curves are for materials with different hardness in Example 1.
[0030] Figure 3 This is a scatter plot of Heckel function values and pressure from Example 1.
[0031] Figure 4 This is a diagram showing the relationship between material hardness and production crushing process in Example 3.
[0032] Figure 5 This is a scatter plot of Heckel function values and pressure for the unscreened batch in Example 4. Detailed Implementation
[0033] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention.
[0034] Example 1: Standard procedure and parameter determination for powder hardness assessment
[0035] This embodiment uses the intermediate product (a mixture of block and coarse powder) after sintering of medium-nickel 7-series ternary cathode material as an example to illustrate the standard evaluation process of this invention:
[0036] (1) Material pretreatment: The material to be tested is extracted from the production line and vibrated and screened using a 400-mesh standard sieve for 10 minutes. After screening, the material on the sieve is put into a clean PE bag. The purpose of this step is to remove fine powder with too small a particle size (such as fine debris generated due to local breakage) from the material, so as to reduce the interference of fine powder filling the voids on the subsequent compaction density determination.
[0037] (2) Blank calibration test of the test mold and system: Using a Ф16mm stainless steel mold, from bottom to top, place the base, mold body, module, and push rod in sequence to complete the mold assembly, as follows: Figure 1 Click "Edit Scheme" on the software interface and select the "Blank Calibration" scheme. Place the mold in the center of the testing machine's pressure platen and click the "Fast Up" button to adjust the equipment height. When the upper end of the mold push rod is close to the upper pressure platen, zero the pressure, parallelism, and displacement, then press the "Slow Up" button until it contacts the upper pressure platen. When the pressure reaches approximately 20N, click "Run." After the equipment finishes running, click the "Zero" button for deformation and displacement in the software; at this point, the deformation and displacement will be 0. Specific parameters for the scheme are shown in Table 1.
[0038] Table 1 Blank Calibration Process Parameters
[0039]
[0040] (3) Multi-point compaction density test: Take 30 groups of sintered materials of nickel 7 series ternary materials (30 batches of soft materials and 30 batches of hard materials) for multi-point compaction density test. Weigh 3.0g±0.1g of the material to be tested after screening in step 1 into weighing paper. Slowly place one module on the mold base and transfer the weighed sample into the mold. Manually vibrate twice, each time with an amplitude of 1cm. Then put in another module, add the push rod, and record the weight. Select the "multi-point compaction density test" scheme to conduct the test. After the equipment runs, record the value of deformation under the corresponding pressure. Calculate the compaction density ρ under the corresponding pressure automatically according to the set formula. The specific parameters of the multi-point compaction density test scheme are shown in Table 2, and the average data are as follows. Figure 2 As shown.
[0041] The formula for calculating the compaction density of this invention is as follows: Where ρ is the compacted density of the powder (g / cm³) 3 m is the mass of the powder (g), and S is the cross-sectional area of the compacted powder (cm²). 2h is the thickness of the compacted powder minus the thickness after blank calibration (mm), where 10 is the unit conversion factor between mm and cm. The original data for h and m can be found in Appendix 1.
[0042] Table 2. Process parameters for multi-point compaction density testing of ternary materials.
[0043]
[0044] (3) Heckel analysis of rearrangement zone and plastic deformation zone: In this embodiment of the invention, the initial pressure of the rearrangement zone and the plastic deformation characteristic zone is determined as follows: According to Heckel theory, the powder compaction process can be divided into two characteristic stages: the low-pressure nonlinear stage corresponds to the particle rearrangement-dominated stage, and the curve shows obvious nonlinear bending; the high-pressure linear stage corresponds to the plastic deformation-dominated stage, and the curve shows a good linear relationship, which conforms to the equation Where D is the relative density (compacted density / true density) under pressure P, k is the slope of the straight line, and A is the intercept, which is related to the rearrangement during powder compaction. Several representative groups of 'soft' and 'hard' material samples were selected, and curves (i.e., Heckel plots) showing the change of Heckel function values with pressure were plotted based on their compaction data. The Heckel function value-pressure scatter plot is shown below. Figure 3 As shown.
[0045] Observations revealed that for the sintered ternary cathode materials involved in this technical field, the Heckel curves of all samples transitioned from a nonlinear bending segment in the low-pressure region to a stable linear segment in the high-pressure region only after the pressure reached approximately 10000 N (150 MPa). This transition point represents the critical point where the compaction mechanism shifts from being dominated by particle rearrangement to being dominated by plastic deformation. Linear regression fitting was performed on the 10000 N-30000 N range, and the goodness of fit R0 was [not specified]. 2 All values reached above 0.985, with a standard deviation of 0.04%, as shown in Table 3. This meets the criteria for determining that the dominant plastic deformation region exhibits linear characteristics. Among these, batch numbers 1-30 represent hard materials with R... 2 The values 31-60 represent values for soft materials. Therefore, for standardization and ease of rapid application, this invention sets the starting pressure of the plastic deformation characteristic range at 10000N. Since the compaction density of all samples is essentially the same at 50000N, the endpoint of the plastic deformation zone is chosen to be 30000N. This range is suitable for any circular mold. For molds of different diameters, the pressure range can be calculated using the following formula: =4 ,
[0046] In the formula: F: Pressure (MPa), F: Applied pressure (N), A: Mold cross-sectional area (mm²) 2), d: mold diameter (mm), π: pi.
[0047] Table 3 shows the goodness-of-fit R of the plasticity-dominant range for nickel-7 series ternary materials. 2
[0048]
[0049] (5) Calculation of compaction density difference: Based on the characteristic stage division of the Heckel analysis curve, the following two key parameters are calculated:
[0050] The density difference in the rearrangement zone (Δρrearrangement): Δρrearrangement = ρ10000N - ρ1500N. This parameter reflects the ability of particles to fill pores through displacement under lower pressure. The density difference in the plastic zone (Δρplasticity): Δρplasticity = ρ30000N - ρ10000N. This parameter reflects the intrinsic characteristics of particles undergoing plastic deformation and breakup / reorganization under high pressure.
[0051] Table 4 shows the multi-point compaction density, Δρ rearrangement, and Δρ plasticity data of nickel-7 series ternary materials.
[0052]
[0053] (6) Establishment and verification of LDA discriminant model
[0054] This embodiment trains data on 60 batches of medium-nickel 7-series materials with known hardness grades (inversely calibrated by experienced process engineers through crushing energy consumption). The final hardness is considered a weighted sum of different compaction mechanisms. The model-predicted hardness is defined as β0 + β1*(Δρrearrangement) + β2*(Δρplasticity). Multiple linear regression is performed, followed by linear discriminant analysis (LDA) to establish a model. Here, β0 represents the fitting intercept; β1 is the weighting coefficient for the rearrangement stage, revealing the influence of powder flowability and filling properties on the final performance; and β2 is the weighting coefficient for the plastic deformation stage, representing the influence of intrinsic powder plasticity on the final performance.
[0055] ① Model Training: The Δρ rearrangement and Δρ plasticity of 60 batches of samples were used as input variables, and the hardness label (hard / soft) was used as the classification target. Hardness grades were based on crushing pressure; materials crushed at pressures above 0.3 MPa were classified as hard materials. Multivariate discriminant analysis was used in the Minitab software's statistical function to fit the discrimination formulas for soft and hard materials. The discrimination formulas for soft and hard materials are as follows:
[0056] Score (soft) = -144.70 + (-102.77 * Δρ rearrangement) + 954.06 * Δρ plasticity
[0057] Score (hardness) = -129.36 + (-101.75 * Δρ rearrangement) + (-908.61 * Δρ plasticity)
[0058] The classification function obtained by fitting using the LDA algorithm is: F = -15.34 + (-1.02 * Δρ rearrangement) + 45.45 * Δρ plasticity.
[0059] ② Model judgment logic: When the calculated classification threshold F>0, it is judged as "soft material"; when F<0, it is judged as "hard material".
[0060] ③ Validation Results: Blind testing was conducted on 60 batches of materials, and the experimental results are shown in Table 5. The results show that the model achieves an accuracy rate of 93.33%, and the single-sample test time is only 2.8 minutes, which is much faster than the traditional shear test.
[0061] Table 5 shows the accuracy of hardness assessment results for nickel-7 series ternary materials based on compressive behavior.
[0062]
[0063] (8) Stability data: Two batches of samples with different hardness were tested for stability, and the results are shown in Table 6. The key indicators Δρ rearrangement and Δρ plasticity RSD in the hardness evaluation model of all samples were less than 10%, indicating that the method has good stability.
[0064] Table 6 shows the stability data of hardness evaluation results for nickel-7 series ternary materials based on compressive behavior.
[0065]
[0066] Example 2: Compared with traditional shear force testing methods
[0067] In powder shear testing, powder hardness is assessed by characterizing powder flowability. Lower shear strength generally indicates a "softer" powder. Three groups of samples (three batches of soft powder and three batches of hard powder) were tested for shear force, and the results are shown in Table 7 (WL refers to feed weight, representing the weight crushed per unit time, in kg / min; F refers to crushing pressure, in MPa. Higher WL and lower F indicate softer material). It should be noted that the shear force data here are values obtained at a pre-shear normal stress of 6 kPa and a normal stress of 3.6 kPa, in kPa. The shear force results show no significant difference in shear force between materials of different hardnesses (paired t-test, P value 0.881 > 0.05). Compared to shear force testing, the method for determining hardness based on compaction behavior in this embodiment of the invention has higher accuracy, shorter processing time, and 50% higher efficiency.
[0068] Table 7 Comparison of Results from Different Hardness Assessment Methods and Actual Production Processes
[0069]
[0070] In addition, a batch of samples was selected for powder shear force repeatability testing. The results are shown in Table 8. The highest single-point RSD was 11.53%, which did not meet the requirement of <10% (due to the coarse and hard particles after sintering, there is a high risk of damaging the shear box, and the deviation between the two sets of data is large, so multiple experiments were not conducted). The test fluctuations were large, and the stability was far less than that of the method for determining hardness based on compressive behavior in the embodiment of the present invention.
[0071] Table 8 shows the shear force stability data of nickel-7 series ternary materials in soft powder form.
[0072]
[0073] Example 3: Relationship between material hardness and production crushing process
[0074] Combining the sintered material evaluation method in Example 1, several batches of sintered materials with historically significant differences in crushing process parameters were randomly selected from production records. The method of this invention was used to rapidly evaluate the hardness of these batches, calculate their characteristic compaction density difference Δρ, and input it into a trained LDA discriminant model to obtain their classification thresholds. All batches of materials that historically required high crushing strength (e.g., unit crushing energy consumption > 0.34 MPa) for effective crushing, tested using the method of this invention, had classification thresholds less than 0 and were consistently classified as "hard" materials by the model. Correspondingly, batches of materials historically easy to crush (unit crushing energy consumption < 0.34 MPa) had classification thresholds greater than 0 and were classified as "soft" materials by the model. The verification results are as follows: Figure 4 As shown in the figure, the verification results fully demonstrate that the hardness assessed by this invention has a high positive correlation with the "crushing difficulty" of materials in actual production. The "soft / hard" classification provided by this invention can accurately predict the behavior of materials in subsequent crushing processes, thus providing a direct and reliable basis for optimizing crushing process parameters in advance (such as adjusting crushing pressure and feed frequency).
[0075] Example 4: Comparison of the impact of screening pretreatment on evaluation accuracy
[0076] To verify the necessity of the screening pretreatment in step (1), this embodiment conducted a comparative experiment on the same batch of nickel 7 series materials:
[0077] Experimental group: The samples were pretreated by 400-mesh sieving according to Example 1 before testing.
[0078] Control group: The compaction density of the raw material was directly tested.
[0079] The Heckel function values-pressure scatter plot of the non-sieved batches in the control group is shown below. Figure 5 As shown.
[0080] Based on the LDA model training classification threshold formula in Example 1, hardness was identified for unscreened samples, and the results are shown in Table 9.
[0081] Table 9 Thresholds for Raw Material Classification
[0082]
[0083] As shown in Table 9, the accuracy rate is only 33.33%, which fails to meet the requirements for guiding production. This is because when the material is not pre-treated by screening, fine powder (particles with a diameter <45μm) preferentially fills the pores between particles in the low-pressure stage (pressure 7500N, pressure 37MPa), resulting in a "premature densification illusion." This leads to an artificially high apparent compaction density and a deviation in the pressure range between the plastic zone and the rearrangement zone. This directly causes a sharp decline in the accuracy of the hardness discrimination model constructed based on this.
[0084] Example 5: Validation with different screening times
[0085] The material to be tested was extracted from the production line and vibrated through a 400-mesh standard sieve, divided into three groups, with vibration times set to 5, 10, and 15 minutes respectively. Other steps were the same as in Example 1. The accuracy of the evaluation is shown in Table 10.
[0086] Table 10 shows the accuracy of hardness assessment results for nickel-7 series ternary materials based on compressive behavior at different sieving times.
[0087]
[0088] Comparative experiments with multiple sets of different sieving times (5 min, 10 min, and 15 min) revealed that, under the same sieve mesh size, rearrangement zone, and plastic zone conditions, the model evaluation accuracy was 93.33% when the sieving time was 10 min and 15 min, significantly better than the accuracy rate when the sieving time was 5 min. This is because: firstly, 10 minutes is sufficient to reach the sieving endpoint (the weight of the material on the sieve no longer decreases), and the results under the 15-minute condition are consistent with those under the 10-minute condition; secondly, 10 minutes is sufficient to completely separate large and small particles. In subsequent multi-point compaction density tests, this effectively eliminates the interference of "premature densification" caused by fine particles prematurely filling pores under low pressure, allowing the obtained compaction curve to more realistically reflect the compression behavior of the main particles. This makes the model based on compaction behavior to determine hardness more accurate. Combining the data and observations, a 10-minute sieving time ensures thorough separation of large and small particles, making it a more efficient and accurate parameter for hardness assessment within the experimental conditions.
[0089] Example 6: Verification of the universality of the method (different material systems)
[0090] To verify the effectiveness of this method on materials with different nickel contents, this embodiment selected medium-nickel 5-series and high-nickel 9-series ternary materials for testing, and the results are shown in Table 11.
[0091] Table 11. Accuracy data of hardness assessment results for ternary materials with different nickel-cobalt-manganese ratios based on compressive behavior.
[0092]
[0093] For medium-nickel 5-series materials: the classification thresholds are generally concentrated between -2.8 and -3.6 (hard materials) and between 1.5 and 2.4 (soft materials), with a discrimination accuracy of 100%.
[0094] High-nickel 9-series materials: Although the physical properties of the materials themselves are different, after the same Δρ calculation, except for a very few samples that deviate near the threshold 0, the discrimination accuracy remains above 83.33%.
[0095] Experiments have shown that this method successfully captures the common intrinsic mechanical characteristics of ternary materials by extracting the density difference during the plastic deformation stage, and has good potential for cross-type application.
[0096] Example 7: Multi-model (LR) discriminant confirmation
[0097] In this embodiment, a logistic regression (LR) model is used to refit the 60 batches of sample data from Example 1:
[0098] Fitting process: Regression analysis was performed using statistical software, and the goodness-of-fit test P-value was greater than 0.05, indicating that the model is reliable.
[0099] Judgment logic: Calculate the probability that the sample belongs to "hard". If the predicted probability value is >0.5, it is judged to be a hard material.
[0100] The results are shown in Table 12.
[0101] Table 12 shows the accuracy data of the LR model evaluation for nickel-7 series ternary materials.
[0102]
[0103] The analysis is as follows: the LR model achieved a discrimination accuracy of 91.67%, which corroborates the LDA model. This indicates that the proposed method of using compaction density difference (Δρ rearrangement and Δρ plasticity) as a feature variable is highly scientific and does not rely on a single mathematical algorithm.
[0104] In summary, this invention provides a method for evaluating the hardness of materials in the sintering process of ternary lithium-ion cathode materials through the compaction density difference Δρ. The method first uses sieving pretreatment to eliminate the influence of small particles on the material's resistance to breakage. Then, it obtains a complete compaction density-pressure curve through multi-point pressure testing. Based on the Heckel model, it quantifies the characteristic compaction density differences (Δρ_rearrangement and Δρ_plasticity) of the material in the rearrangement and plastic deformation zones respectively. These two physical quantities together reflect the compressive resistance of the sample throughout the entire process from loose filling to plastic compaction, achieving a scientific mapping from microscopic compaction difficulty to macroscopic breakage difficulty. Furthermore, the two parameters are jointly input into a linear discriminant analysis model for training, constructing a discriminant function that can comprehensively evaluate the material's macroscopic resistance to breakage. This method fundamentally avoids the inherent defects of signal mixing in traditional compaction methods and the inapplicability of shear testing methods to hard and brittle sintered blocks. It forms a fast, accurate, and closed-loop action chain of "physical measurement → feature extraction → intelligent discrimination → process guidance", providing a reliable basis for the precise and forward-looking control of downstream crushing processes.
[0105] The core innovation of this invention lies in abandoning the traditional indirect method of measuring interparticle forces or macroscopic aggregate properties. Instead, it directly quantifies the material's inherent resistance to deformation and breakage by analyzing its intrinsic plastic compressive behavior in high-pressure ranges. This method provides accurate hardness assessments beforehand, offering precise guidance for crushing process parameters and effectively avoiding problems such as "over-crushing" or "under-crushing" caused by blindly setting parameters. This significantly reduces rework energy consumption and material costs. Addressing the current technological gap in rapidly and effectively measuring the hardness of nickel-cobalt-manganese ternary sintered materials, this invention provides a novel testing paradigm, filling this technological gap and providing a reliable tool for process optimization and quality control in related industries. This promotes the advancement and industrial application of powder mechanical property testing technology.
[0106] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the invention by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the invention should be included within the scope of protection of the invention.
Claims
1. A rapid method for evaluating powder hardness based on compaction density difference, characterized in that, Includes the following steps: The powdered material of ternary cathode material is obtained and subjected to sieving pretreatment to separate and remove fine powder particles; The sieved material is loaded into a test mold and a multi-point compaction density test is performed to obtain the compaction density of the material at multiple increasing pressure points. Based on the Heckel analysis model of powder compaction, the characteristic pressure ranges of the rearrangement zone and the plastic deformation zone of the material during the compaction process are determined; the equations of the Heckel analysis model are as follows: Where D is the relative density under pressure P, relative density = compacted density / true density, k is the slope of the straight line, and A is the intercept; the pressure range corresponding to the characteristic pressure range of the rearrangement zone is 7.5 MPa to 50 MPa; the pressure range corresponding to the characteristic pressure range of the plastic deformation zone is 50 MPa to 150 MPa. Calculate the compaction density difference Δρ_rearrangement in the rearrangement zone and the compaction density difference Δρ_plasticity in the plastic deformation zone within the characteristic pressure range of the rearrangement zone. The Δρ rearrangement and Δρ plasticity are input into a pre-trained hardness classification and discrimination model to calculate the classification threshold, thereby determining the hardness category of the ternary cathode material powder. The hardness classification model is a linear discriminant analysis (LDA) model; the classification threshold is calculated as follows: classification threshold F = A + B * Δρ rearrangement + C * Δρ plasticity, where A, B, and C are coefficients determined through training; when the classification threshold F is greater than 0, it is classified as a soft material; when the classification threshold F is less than 0, it is classified as a hard material.
2. The method according to claim 1, characterized in that, The specific conditions for the screening pretreatment are: using a 300 to 500 mesh screen and vibrating screening time of 10 to 15 minutes.
3. The method according to claim 1, characterized in that, Before conducting the multi-point compaction density test, a blank calibration test is also performed on the test mold and system to eliminate the system's own elastic deformation under stress.
4. The method according to claim 1, characterized in that, When using a circular mold with a diameter of 16mm, the calculation formulas for Δρ rearrangement and Δρ plasticity are: Δρ rearrangement = ρ10000N - ρ1500N; Δρ plasticity = ρ30000N - ρ10000N.