Optimizing Compaction Density for Accurate Electrochemical Characterization of Graphite Anodes in Li-ion Simulated Cells

Optimizing Compaction Density for Accurate Electrochemical Characterization of Graphite Anodes in Li-ion Simulated Cells | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimizing Compaction Density for Accurate Electrochemical Characterization of Graphite Anodes in Li-ion Simulated Cells Xianzhen Du, Yong Wang, Jingpeng Zhang, Juanjuan Xue, Xiwen Ke, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7739881/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Graphite anodes are critical for lithium-ion batteries, and simulated cells are indispensable tools for their electrochemical evaluation. However, the accuracy of these tests is often compromised by the overlooked parameter of compaction density. This study systematically investigates its impact on performance, interfacial impedance, and structural integrity. We demonstrate an optimal density range for consistent measurements of specific capacity and Coulombic efficiency. Excessive compaction degrades performance and increases data scatter, due to particle cracking, fresh surface exposure, increased side reactions, and hindered ion diffusion, as supported by SEM and EIS-DRT analysis. These findings provide pivotal guidelines for standardizing testing protocols and optimizing manufacturing processes. Graphite anode Simulated cell Compaction density Electrochemical impedance spectroscopy Distribution of relaxation times (DRT) Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Accurate electrochemical evaluation of graphite anode materials is crucial for the development of both liquid and solid-state lithium-ion batteries. Simulated cells (e.g., coin cells) serve as a fundamental tool for obtaining key performance metrics. Among anode materials, graphite remains the most prevalent choice due to its unique layered structure, which facilitates efficient lithium-ion intercalation [ 1 , 2 ]. However, a significant challenge persists: the performance indicators derived from simulated cells often exhibit considerable discreteness and poor reproducibility. A critical yet frequently overlooked parameter contributing to this variability is the compaction density of the electrode. Although its importance is occasionally acknowledged [ 3 , 4 , 6 , 10 ], a systematic investigation into how compaction density influences the accuracy and consistency of simulated cell data—particularly the underlying mechanisms—is notably absent from the literature. Existing research on graphite materials predominantly focuses on horizontal comparisons within full-cell configurations [ 4 ] or on strategies for material performance enhancement [ 5 – 8 ]. Studies concerning the processing compatibility of different graphite grades [ 9 – 13 ] are also abundant. Nevertheless, there is a conspicuous gap regarding the methodology for determining the optimal compaction density range within simulated half-cells to achieve the most accurate and representative electrochemical data. To address this research gap and the lack of systematic, comparative studies on process parameters in simulated cell testing, this work presents a comprehensive analysis of how compaction density affects key electrochemical properties, such as specific capacity and initial Coulombic efficiency. We employed a multi-faceted characterization approach, including electrochemical impedance spectroscopy (EIS), distribution of relaxation times (DRT) analysis, cyclic voltammetry (CV), and scanning electron microscopy (SEM). Our findings reveal that EIS, particularly when interpreted through DRT, can effectively diagnose the electrochemical response and predict the compatibility of graphite materials under various compaction conditions. This study provides substantive insights for standardizing testing protocols and obtaining reliable data for optimized battery design. 2. Experimental 2.1. Electrode Preparation and Cell Assembly Two types of commercial graphite anodes, denoted as A-Sample and B-Sample, were used as active materials. The electrode slurry was prepared by mixing graphite, Super-P conductive carbon (IMERYS), and polyvinylidene fluoride (PVDF-5130, Solvay) binder at a weight ratio of 91.5:3.5:5 in N-methyl-2-pyrrolidone (NMP) solvent. The slurry was coated onto a copper foil current collector using a doctor blade with a 200 µm gap, followed by drying at 110°C under vacuum. The electrodes were then punched into discs and further dried before being transferred into an argon-filled glovebox. CR2032-type coin cells were assembled with the prepared graphite electrode as the working electrode, lithium metal as the counter/reference electrode, a polypropylene separator, and 1.0 M LiPF₆ in EC/DEC (1:1 v/v) as the electrolyte. 2.2. Electrochemical Measurements Galvanostatic charge-discharge tests were performed using a LAND CT-3002AU battery test system at 25 ± 1°C. The cells were tested between 0.001 V and 2.5 V (vs. Li⁺/Li) with specific current rates as described in the main text. The specific capacity and initial Coulombic efficiency were calculated based on the mass of the active material. Electrochemical impedance spectroscopy (EIS) was conducted on a Zahner electrochemical workstation over a frequency range of 100 kHz to 10 mHz. Distribution of relaxation times (DRT) analysis was applied to deconvolute the impedance contributions. 2.3. Material Characterization The morphologies of the graphite powders and electrodes were observed using a ZEISS EVO MA10 scanning electron microscope (SEM). Samples were sputter-coated with gold prior to imaging. 2.4. BET Specific Surface Area and Pore Structure Analysis The specific surface area and pore size distribution of the graphite powders were determined by nitrogen adsorption-desorption measurements at 77 K using a static nitrogen adsorption analyzer (JW-BK222, JWGB Sci. & Tech.) analyzer. Prior to the measurements, the samples were degassed under vacuum at 250°C for 1 hours to remove any adsorbed moisture and impurities. The specific surface area was calculated using the Brunauer–Emmett–Teller (BET) method in the relative pressure (P/P₀) range of 0.05–0.30. The pore size distribution was derived from the adsorption branch of the isotherm using the Barrett–Joyner–Halenda (BJH) model. 3. Results and Discussion 3.1. The Effect of Compaction Density on Electrochemical Performance The compaction density exerts a significant and non-monotonic influence on the specific capacity and initial Coulombic efficiency of the graphite anode. To investigate the variation of electrochemical performance with compaction density, a range of conditions—including unrolled, compacted at 1.0, 1.1, and 1.4 g/cm³—were systematically evaluated. As clearly summarized in Tables 1 and 2 , distinct trends in specific capacity and initial efficiency were observed across these compaction levels. Table 1 Comparative electrochemical performance metrics of sample A under different rolling degrees Compaction 0.2C /mAh/g ICE /% Deviation of Capacity /mAh/g Deviation of ICE /% unrolled 344 94.2 unrolled 344.9 94.3 1.1 0.3 unrolled 343.8 94.5 compacted 1.0 345.4 95.2 compacted 1.0 345.3 95.5 1.2 0.5 compacted 1.0 346.5 95 compacted 1.2 345.1 94.4 compacted 1.2 345.7 94.2 1.6 0.3 compacted 1.2 344.5 94.1 compacted 1.4 345.4 91.8 compacted 1.4 345.8 91.9 1.7 0.9 compacted 1.4 344.1 91.1 Table 2 Comparative electrochemical performance metrics of sample B under different rolling degrees Compaction 0.2C /mAh/g ICE /% Deviation of Capacity /mAh/g Deviation of ICE /% unrolled 340.8 94.2 unrolled 341.1 94.4 0.9 0.5 unrolled 341.7 94.7 compacted 1.0 341.4 94.1 compacted 1.0 342.1 94.4 1.4 0.4 compacted 1.0 342.5 94.5 compacted 1.2 343.1 94.4 compacted 1.2 341.7 94.2 1.4 0.3 compacted 1.2 342.5 94.7 compacted 1.4 341.4 92.1 compacted 1.4 339.9 92.3 1.5 0.6 compacted 1.4 340.8 92.7 The experimental results indicate that the specific capacity exhibits a distinct trend of initial increase followed by a decrease as the compaction density rises. For Graphite Sample A, the optimal electrochemical performance was achieved at approximately 1.0 g/cm³, whereas Sample B reached its peak performance at a slightly higher compaction density of around 1.1 g/cm³. Beyond these optimal points, both samples demonstrated a notable decline in performance, accompanied by a significant increase in data dispersion (as indicated by the enlarged range of deviation) [ 3 , 4 , 6 , 10 ]. This observed performance degradation and increased data scatter suggest that excessive compaction density likely induces detrimental structural and interfacial changes. To elucidate the underlying mechanisms, further in-depth analysis using electrochemical impedance spectroscopy and morphological characterization was conducted. 3.2. Probing the Underlying Mechanisms via EIS and DRT Analysis Electrochemical impedance spectroscopy (EIS) was performed on graphite samples under optimal, uncompacted, and over-compacted conditions. The results revealed that the optimally compacted sample exhibited the lowest overall impedance, while both uncompacted and over-compacted conditions showed significantly larger impedance responses. The optimal compaction density for common commercial graphites lies in the 1.0–1.2 g cm⁻³ range.Moving to ≥ 1.4 g cm⁻³ routinely yields scattered or abnormally low capacity data, making this region unsuitable for reliable electrode fabrication. Table 3 Charge transfer impedance, of A samples Name unrolled compacted 1.0 compacted 1.2 compacted 1.4 R 1 /Ω 4.067 4.444 4.522 4.264 R 2 /Ω 6.149 5.934 5.106 5.622 R 3 /Ω 135.7 114.8 126.2 153.2 R w /Ω 170.1 152.5 152.6 171 Table 4 Charge transfer impedance, of B samples Name unrolled compacted 1.0 compacted 1.2 compacted 1.4 R 1 /Ω 3.669 3.898 4.23 3.941 R 2 /Ω 7.718 6.967 7.05 5.485 R 3 /Ω 170.1 144.2 131.3 155.8 R w /Ω 380.7 190.6 170.9 248.3 According to the Nernst equation, the overall impedance of a battery is influenced by multiple factors, including electrode material properties, lithium-ion concentration, electrical conductivity of the electrodes, battery polarization, assembly process, and charge-discharge efficiency. These factors collectively determine the initial voltage and performance characteristics of lithium-ion batteries. As shown in Fig. 1 , the EIS Nyquist plots of both Graphite A and B under different compaction levels exhibited similar shapes, though with notable variations in magnitude. Since coin cells do not require formation cycling, their total impedance remains on the order of ohms. The uncompacted electrodes showed higher internal resistance due to poor interfacial contact, whereas the sample compacted at 1.4 g/cm³ demonstrated slightly greater resistance than those at intermediate levels. Distribution of relaxation times (DRT) analysis was employed to resolve fine features within the EIS data by transforming it into the time domain [ 13 ]. The DRT profiles displayed four distinct peaks, each corresponding to a specific electrochemical or physical process within the simulated cell. The peak in the shortest time constant region (10⁻⁵ to 10⁻³ s) represents physical impedance, largely attributed to contact resistance between cell components. This peak remained consistent across samples, indicating that slight variations in electrode thickness did not significantly affect interfacial contact. A small but consistent peak in the 10⁻³ to 10⁻² s range suggested the presence of a preliminary SEI layer, likely formed during cell assembly despite the absence of a formal aging process. The mid-frequency time constants correspond to charge transfer resistance (Rct) [ 10 , 14 ], while the dominant low-frequency peak reflects solid-state diffusion processes (Rdiff). These two peaks exhibited clear dependence on compaction density. The observed behavior can be interpreted as follows[ 13 ]: lithium-ion diffusion occurs on a timescale of seconds and is influenced by the diffusion coefficient and diffusion distance. As compaction density increases, the ease of electrolyte infiltration and ion transport directly affects the charge transfer and diffusion-related resistances. Table 5 EIS Time-Domain Parameter Reference Table Time Domain 10 − 5 to 10 − 3 10 − 3 to 10 − 1 10 − 1 to 10 0 10 0 to 10 Physical Process Ohmic Impedance SEI Film Impedance Charge Transfer Impedance Diffusion Impedance Initially, increasing compaction significantly reduced lithium-ion diffusion impedance. Uncompacted electrodes possess loosely distributed active material, resulting in poor particle-to-particle and particle-to-current-collector contact, thereby leading to high resistance [ 3 ]. Moderate compaction shortened interparticle conduction pathways, reducing both Rct and Rdiff. However, excessive compaction beyond the optimal point caused a sharp increase in Rdiff, indicating severely hindered ion transport through clogged electrode pores. Subsequently, Rct also increased, suggesting deteriorated kinetics at the electrode-electrolyte interface[ 16 ]. 3.3. Correlation between Electrode Morphology and Electrochemical Response SEM imaging clearly revealed the structural origins of the increased impedance. Under optimal compaction (1.1 g/cm³), the electrode exhibited a dense yet porous morphology. In contrast, severe particle cracking and deformation were observed in the over-compacted electrode (1.4 g/cm³), as indicated by the red arrows in Fig. 3 . Morphological evolution shown in Fig. 3 further demonstrates that a coherent compressed layer had formed on the electrode surface at 1.1 g/cm³ without significant particle fracture, indicating satisfactory mechanical stability of the graphite powder under moderate compression [ 15 ]. However, at 1.4 g/cm³, clear particle fragmentation occurred, coinciding with altered lithium-ion diffusion impedance. This microstructural degradation accounts for the increased data scatter in specific capacity measurements—finely crushed graphite particles filled interparticle voids, increasing exposed superficial area [ 8 , 9 ] and electroactive edge sites available for lithiation. Meanwhile, the local porosity reduction impeded ionic permeability, resulting in dispersed capacity and efficiency values with heightened variability. BET adsorption-desorption analysis confirmed that Sample A displays characteristics typical of non-porous materials (Type II isotherm), while Sample B possesses a mesoporous structure (Type IV isotherm with H3 hysteresis). This fundamental difference explains why Sample A reached its performance limit at lower compaction density—its inherently lower porosity renders it more susceptible to pore clogging under compression[ 1 , 15 ]. The crushed particles not only reduce the ionic diffusion pathways but also create fresh, active surfaces that continuously consume electrolytes to form a thick and resistive SEI layer [ 16 ], which is consistent with the increase in the mid-frequency DRT peak assigned to SEI/interface resistance. 3.4. Comprehensive Mechanism Analysis Cyclic voltammetry (CV) further corroborated the aforementioned conclusions. Under over-compaction conditions, the diminished area of the redox peaks indicates a reduction in the number of effectively reactive lithium ions, which is consistent with the observed capacity decay. Furthermore, the absence of peak shift suggests that compaction density did not alter the fundamental lithiation/delithiation reaction mechanisms, and that the performance degradation is primarily attributed to kinetic limitations. A comparative CV analysis of Sample A at two extreme compaction levels (1.0 and 1.4 g/cm³) is presented in Fig. 5 . Figure 5 CV curves at different compaction levels CV profiles are commonly used to evaluate the reversibility of electrode reactions. As shown in Fig. 5, despite the differing compaction levels at a fixed areal density, the oxidation peak (0.28 V) and reduction peak (0.01 V) positions remained unchanged. However, the peak areas decreased notably at higher compaction, indicating reduced active lithium participation. Since peak area correlates with the quantity of electrochemically active lithium, these results confirm that excessive compaction hinders lithium utilization efficiency—a finding consistent with the specific capacity measurements reported in previous sections[ 11 ]. The electrochemical performance of graphite anodes is critically determined by their microstructural and interfacial properties[ 17 – 21 ], which are in turn governed by the compaction density. An optimal compaction density achieves the best compromise between electronic conductivity and ionic transport efficiency. In contrast, excessive compaction induces particle fragmentation and pore clogging[ 22 – 24 ], which impedes ion diffusion, and simultaneously generates fresh surfaces that exacerbate side reactions[ 20 , 24 ]. These combined effects ultimately lead to performance degradation and reduced reliability of electrochemical data[ 25 ]. 4. Conclusion Optimizing the compaction density is crucial for the accurate characterization of graphite anodes in simulated cells, as it profoundly influences key electrochemical metrics including specific capacity, Coulombic efficiency, and internal impedance. An optimal range of compaction density exists that maximizes electrochemical performance[ 1 , 3 , 10 ]. Insufficient compaction results in a loose electrode structure with poor interparticle contact and compromised electronic conduction, leading to underutilization of active material. Conversely, excessive compaction induces graphite particle cracking, which exposes fresh surfaces to electrolytes, promotes deleterious side reactions, and increases ionic diffusion resistance, thereby degrading both capacity and efficiency. It is noteworthy that compaction density alters the kinetic limitations rather than the intrinsic phase transformation behavior of graphite, as evidenced by unchanged CV profiles. Given the distinct morphological and mesoporous structural characteristics of different graphite materials, the ideal compaction density is uniquely defined as the range where the combined charge transfer and solid-state diffusion impedances are minimized, ensuring the full realization of the material's electrochemical potential. Declarations Author Contribution X.D. wrote the main manuscript text.Y.W. guided the testing method for the simulated batteries.J.Z. researched the testing method for the simulated batteries and the method for manuscript writing.J.X. prepared Figures 1–2.X.K. guided the ideas for material testing.Q.M. prepared Figures 3–5.K.C. prepared Figure 6. Acknowledgments The authors are grateful to the Major Science and Technology Innovation Project of Shandong Province, China (No. 2024CXPT016),for the financial support to this work. References Winter M, Novák P, Monnier A, et al. Graphites for lithium-ion cells: the correlation of the first-cycle charge loss with the Brunauer-Emmett-Teller surface area[J]. Electrochem Soc, 1998, 145(2): 428–436. He Y, Jian Z, Liu H, et al. Preparation and lithium storage performance of expanded graphite[J]. Inorg Mater, 2013, 28(9): 931–936 (in Chinese). Jiang H, Xu Q, Meng F, et al. Effect of compaction density on the performance of lithium ion battery[J]. 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Angewandte Chemie International Edition, 2022, 61: e202210365. Niu Z, Yuan S, Gao H, et al. Research progress on the failure mechanism of silicon-carbon composite anodes for lithium-ion batteries[J]. Mater Rev, 2022, 36(21): 67–73 (in Chinese). Lin Y, Liu Z, Leng K, et al. Effects of electrode density on the electrochemical performance of lithium-ion batteries[J]. J Power Sources, 2016, 309: 221–226. Wang Y, Dang D, Li D, et al. Relationship between the electrode surface nature and the first-cycle coulombic efficiency of a Li-ion battery: an in situ FTIR study[J]. J Power Sources, 2019, 438: 226938. Zaghib K, Nadeau G, Kinoshita K. Effect of graphite particle size on irreversible capacity loss[J]. J Electrochem Soc, 2000, 147(6): 2110–2115. Landesfeind J, Hattendorff J, Ehrl A, et al. Tortuosity determination of battery electrodes and separators by impedance spectroscopy[J]. J Electrochem Soc, 2016, 163(7): A1373-A1387. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 30 Nov, 2025 Reviews received at journal 26 Nov, 2025 Reviews received at journal 18 Nov, 2025 Reviewers agreed at journal 06 Nov, 2025 Reviewers agreed at journal 28 Oct, 2025 Reviewers invited by journal 28 Oct, 2025 Editor assigned by journal 09 Oct, 2025 Submission checks completed at journal 09 Oct, 2025 First submitted to journal 29 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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13:40:04","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":160714,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7739881/v1/571d1c431b6389d34ffed72f.png"},{"id":95526104,"identity":"b27db568-1d65-4d81-b9c7-5e8e444e7490","added_by":"auto","created_at":"2025-11-10 10:06:14","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":18938,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7739881/v1/4fba5dd5a020bf88c7101087.png"},{"id":95525829,"identity":"48ffccd1-5eed-44ca-bb33-27deca245639","added_by":"auto","created_at":"2025-11-10 10:05:43","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":37083,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7739881/v1/453d7236e20b2452103817d7.png"},{"id":95389662,"identity":"afbdb4ab-1f70-411e-9e72-162b0fabd82e","added_by":"auto","created_at":"2025-11-07 13:40:04","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":26109,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7739881/v1/92b08755baa709061e806a03.png"},{"id":95389664,"identity":"70827cae-0e33-4c27-ba1d-4bf436d52816","added_by":"auto","created_at":"2025-11-07 13:40:04","extension":"xml","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":72482,"visible":true,"origin":"","legend":"","description":"","filename":"756a7baf73f64003a57cff41c242dfa51structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7739881/v1/94014c4ae82b274d4942cb78.xml"},{"id":95389665,"identity":"742b0d53-aa1e-4456-b3c5-39201e26ccc2","added_by":"auto","created_at":"2025-11-07 13:40:04","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":78018,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7739881/v1/ce3ecfb17d9f030c8c23d31d.html"},{"id":95389643,"identity":"987d9355-5272-48bb-9011-26f8a7c00926","added_by":"auto","created_at":"2025-11-07 13:40:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":23304,"visible":true,"origin":"","legend":"\u003cp\u003eEIS Analysis Curves of Graphite Samples A(left) and B(right)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7739881/v1/ae6fbb9406a4fcc3fc4c92ea.png"},{"id":95389644,"identity":"cf8a0228-a55d-4d0e-966e-87f3704cc73b","added_by":"auto","created_at":"2025-11-07 13:40:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":23970,"visible":true,"origin":"","legend":"\u003cp\u003eDRT Analysis Curves of Graphite Samples A(left) and B(right)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7739881/v1/01041a754340c069a526ab6a.png"},{"id":95526316,"identity":"77c47833-b0cc-4ba4-a03c-4a43240fa4bd","added_by":"auto","created_at":"2025-11-10 10:06:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":213307,"visible":true,"origin":"","legend":"\u003cp\u003eSEM images of electrode sheets at various compaction densities\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7739881/v1/5cd70ae0170f37cf1df9a814.png"},{"id":95389648,"identity":"efa1246e-4da3-4709-b006-f4c8e04e8abc","added_by":"auto","created_at":"2025-11-07 13:40:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":15719,"visible":true,"origin":"","legend":"\u003cp\u003eIsothermal adsorption-desorption curves of samples A and B\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7739881/v1/fae353eeefb1b20f9889a224.png"},{"id":95525666,"identity":"62eef028-ae67-4719-866a-b7ef4e2dd8e8","added_by":"auto","created_at":"2025-11-10 10:05:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":15991,"visible":true,"origin":"","legend":"\u003cp\u003eCV curves at different compaction levels\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7739881/v1/d167db41ac2596cf3ec12cb1.png"},{"id":95389654,"identity":"951f4c16-2ac1-438d-89bc-6ce33af6477a","added_by":"auto","created_at":"2025-11-07 13:40:04","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":38102,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic illustration of the proposed mechanism for the impact of compaction density on the electrode microstructure and ion transport. (a) Insufficient compaction leads to poor interparticle contact and inefficient electronic conduction (represented by sparse red lightning bolts), despite the presence of large pores. (b) Optimal compaction achieves a balanced microstructure with uniform porosity, forming efficient percolation networks for both lithium-ion diffusion (blue arrows) and electron transport (red network). (c) Excessive compaction causes particle cracking and pore clogging, which severely tortuos and blocks the ion transport pathways, while electronic contact remains adequate. This imbalance leads to significantly increased diffusion impedance (Rdiff) and performance degradation.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7739881/v1/83efed73ec4586f6c8f6caca.png"},{"id":95531138,"identity":"3f7441ab-fc6e-47cb-9be7-c620e60e3935","added_by":"auto","created_at":"2025-11-10 10:22:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1083210,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7739881/v1/d5e786a8-fc5a-4cc3-acd1-c5939b6f6b94.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Optimizing Compaction Density for Accurate Electrochemical Characterization of Graphite Anodes in Li-ion Simulated Cells","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAccurate electrochemical evaluation of graphite anode materials is crucial for the development of both liquid and solid-state lithium-ion batteries. Simulated cells (e.g., coin cells) serve as a fundamental tool for obtaining key performance metrics. Among anode materials, graphite remains the most prevalent choice due to its unique layered structure, which facilitates efficient lithium-ion intercalation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, a significant challenge persists: the performance indicators derived from simulated cells often exhibit considerable discreteness and poor reproducibility. A critical yet frequently overlooked parameter contributing to this variability is the compaction density of the electrode. Although its importance is occasionally acknowledged [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], a systematic investigation into how compaction density influences the accuracy and consistency of simulated cell data\u0026mdash;particularly the underlying mechanisms\u0026mdash;is notably absent from the literature.\u003c/p\u003e\u003cp\u003eExisting research on graphite materials predominantly focuses on horizontal comparisons within full-cell configurations [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] or on strategies for material performance enhancement [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Studies concerning the processing compatibility of different graphite grades [\u003cspan additionalcitationids=\"CR10 CR11 CR12\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] are also abundant. Nevertheless, there is a conspicuous gap regarding the methodology for determining the optimal compaction density range within simulated half-cells to achieve the most accurate and representative electrochemical data.\u003c/p\u003e\u003cp\u003eTo address this research gap and the lack of systematic, comparative studies on process parameters in simulated cell testing, this work presents a comprehensive analysis of how compaction density affects key electrochemical properties, such as specific capacity and initial Coulombic efficiency. We employed a multi-faceted characterization approach, including electrochemical impedance spectroscopy (EIS), distribution of relaxation times (DRT) analysis, cyclic voltammetry (CV), and scanning electron microscopy (SEM). Our findings reveal that EIS, particularly when interpreted through DRT, can effectively diagnose the electrochemical response and predict the compatibility of graphite materials under various compaction conditions. This study provides substantive insights for standardizing testing protocols and obtaining reliable data for optimized battery design.\u003c/p\u003e"},{"header":"2. Experimental","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Electrode Preparation and Cell Assembly\u003c/h2\u003e\u003cp\u003eTwo types of commercial graphite anodes, denoted as A-Sample and B-Sample, were used as active materials. The electrode slurry was prepared by mixing graphite, Super-P conductive carbon (IMERYS), and polyvinylidene fluoride (PVDF-5130, Solvay) binder at a weight ratio of 91.5:3.5:5 in N-methyl-2-pyrrolidone (NMP) solvent.\u003c/p\u003e\u003cp\u003eThe slurry was coated onto a copper foil current collector using a doctor blade with a 200 \u0026micro;m gap, followed by drying at 110\u0026deg;C under vacuum. The electrodes were then punched into discs and further dried before being transferred into an argon-filled glovebox.\u003c/p\u003e\u003cp\u003eCR2032-type coin cells were assembled with the prepared graphite electrode as the working electrode, lithium metal as the counter/reference electrode, a polypropylene separator, and 1.0 M LiPF₆ in EC/DEC (1:1 v/v) as the electrolyte.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Electrochemical Measurements\u003c/h2\u003e\u003cp\u003eGalvanostatic charge-discharge tests were performed using a LAND CT-3002AU battery test system at 25\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C. The cells were tested between 0.001 V and 2.5 V (vs. Li⁺/Li) with specific current rates as described in the main text. The specific capacity and initial Coulombic efficiency were calculated based on the mass of the active material.\u003c/p\u003e\u003cp\u003eElectrochemical impedance spectroscopy (EIS) was conducted on a Zahner electrochemical workstation over a frequency range of 100 kHz to 10 mHz. Distribution of relaxation times (DRT) analysis was applied to deconvolute the impedance contributions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Material Characterization\u003c/h2\u003e\u003cp\u003eThe morphologies of the graphite powders and electrodes were observed using a ZEISS EVO MA10 scanning electron microscope (SEM). Samples were sputter-coated with gold prior to imaging.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. BET Specific Surface Area and Pore Structure Analysis\u003c/h2\u003e\u003cp\u003eThe specific surface area and pore size distribution of the graphite powders were determined by nitrogen adsorption-desorption measurements at 77 K using a static nitrogen adsorption analyzer (JW-BK222, JWGB Sci. \u0026amp; Tech.) analyzer. Prior to the measurements, the samples were degassed under vacuum at 250\u0026deg;C for 1 hours to remove any adsorbed moisture and impurities. The specific surface area was calculated using the Brunauer\u0026ndash;Emmett\u0026ndash;Teller (BET) method in the relative pressure (P/P₀) range of 0.05\u0026ndash;0.30. The pore size distribution was derived from the adsorption branch of the isotherm using the Barrett\u0026ndash;Joyner\u0026ndash;Halenda (BJH) model.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1. The Effect of Compaction Density on Electrochemical Performance\u003c/h2\u003e\u003cp\u003eThe compaction density exerts a significant and non-monotonic influence on the specific capacity and initial Coulombic efficiency of the graphite anode. To investigate the variation of electrochemical performance with compaction density, a range of conditions\u0026mdash;including unrolled, compacted at 1.0, 1.1, and 1.4 g/cm\u0026sup3;\u0026mdash;were systematically evaluated. As clearly summarized in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, distinct trends in specific capacity and initial efficiency were observed across these compaction levels.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparative electrochemical performance metrics of sample A under different rolling degrees\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCompaction\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.2C\u003c/p\u003e\u003cp\u003e/mAh/g\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eICE\u003c/p\u003e\u003cp\u003e/%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDeviation of Capacity /mAh/g\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDeviation of ICE\u003c/p\u003e\u003cp\u003e/%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eunrolled\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e344\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eunrolled\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e344.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eunrolled\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e343.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e345.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e345.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e346.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e345.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e345.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e344.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e345.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e91.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e345.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e91.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e344.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e91.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparative electrochemical performance metrics of sample B under different rolling degrees\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCompaction\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.2C\u003c/p\u003e\u003cp\u003e/mAh/g\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eICE\u003c/p\u003e\u003cp\u003e/%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDeviation of Capacity /mAh/g\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDeviation of ICE\u003c/p\u003e\u003cp\u003e/%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eunrolled\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e340.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eunrolled\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e341.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eunrolled\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e341.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e341.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e342.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e342.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e343.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e341.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e342.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e341.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e92.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e339.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e92.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecompacted 1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e340.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e92.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe experimental results indicate that the specific capacity exhibits a distinct trend of initial increase followed by a decrease as the compaction density rises. For Graphite Sample A, the optimal electrochemical performance was achieved at approximately 1.0 g/cm\u0026sup3;, whereas Sample B reached its peak performance at a slightly higher compaction density of around 1.1 g/cm\u0026sup3;. Beyond these optimal points, both samples demonstrated a notable decline in performance, accompanied by a significant increase in data dispersion (as indicated by the enlarged range of deviation) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis observed performance degradation and increased data scatter suggest that excessive compaction density likely induces detrimental structural and interfacial changes. To elucidate the underlying mechanisms, further in-depth analysis using electrochemical impedance spectroscopy and morphological characterization was conducted.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Probing the Underlying Mechanisms via EIS and DRT Analysis\u003c/h2\u003e\u003cp\u003eElectrochemical impedance spectroscopy (EIS) was performed on graphite samples under optimal, uncompacted, and over-compacted conditions. The results revealed that the optimally compacted sample exhibited the lowest overall impedance, while both uncompacted and over-compacted conditions showed significantly larger impedance responses. The optimal compaction density for common commercial graphites lies in the 1.0\u0026ndash;1.2 g cm⁻\u0026sup3; range.Moving to \u0026ge;\u0026thinsp;1.4 g cm⁻\u0026sup3; routinely yields scattered or abnormally low capacity data, making this region unsuitable for reliable electrode fabrication.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharge transfer impedance, of A samples\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eName\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eunrolled\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ecompacted 1.0\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ecompacted 1.2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ecompacted 1.4\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR\u003csub\u003e1\u003c/sub\u003e/Ω\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.067\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.444\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.522\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.264\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR\u003csub\u003e2\u003c/sub\u003e/Ω\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.149\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.934\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.106\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.622\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eR\u003c/b\u003e\u003csub\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sub\u003e\u003cb\u003e/Ω\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e135.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e114.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e126.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e153.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eR\u003c/b\u003e\u003csub\u003e\u003cb\u003ew\u003c/b\u003e\u003c/sub\u003e\u003cb\u003e/Ω\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e170.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e152.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e152.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e171\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharge transfer impedance, of B samples\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eName\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eunrolled\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ecompacted 1.0\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ecompacted 1.2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ecompacted 1.4\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR\u003csub\u003e1\u003c/sub\u003e/Ω\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.669\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.898\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.941\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR\u003csub\u003e2\u003c/sub\u003e/Ω\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7.718\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.967\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.485\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eR\u003c/b\u003e\u003csub\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sub\u003e\u003cb\u003e/Ω\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e170.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e144.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e131.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e155.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eR\u003c/b\u003e\u003csub\u003e\u003cb\u003ew\u003c/b\u003e\u003c/sub\u003e\u003cb\u003e/Ω\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e380.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e190.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e170.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e248.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAccording to the Nernst equation, the overall impedance of a battery is influenced by multiple factors, including electrode material properties, lithium-ion concentration, electrical conductivity of the electrodes, battery polarization, assembly process, and charge-discharge efficiency. These factors collectively determine the initial voltage and performance characteristics of lithium-ion batteries. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the EIS Nyquist plots of both Graphite A and B under different compaction levels exhibited similar shapes, though with notable variations in magnitude. Since coin cells do not require formation cycling, their total impedance remains on the order of ohms. The uncompacted electrodes showed higher internal resistance due to poor interfacial contact, whereas the sample compacted at 1.4 g/cm\u0026sup3; demonstrated slightly greater resistance than those at intermediate levels.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eDistribution of relaxation times (DRT) analysis was employed to resolve fine features within the EIS data by transforming it into the time domain [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The DRT profiles displayed four distinct peaks, each corresponding to a specific electrochemical or physical process within the simulated cell. The peak in the shortest time constant region (10⁻⁵ to 10⁻\u0026sup3; s) represents physical impedance, largely attributed to contact resistance between cell components. This peak remained consistent across samples, indicating that slight variations in electrode thickness did not significantly affect interfacial contact. A small but consistent peak in the 10⁻\u0026sup3; to 10⁻\u0026sup2; s range suggested the presence of a preliminary SEI layer, likely formed during cell assembly despite the absence of a formal aging process. The mid-frequency time constants correspond to charge transfer resistance (Rct) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], while the dominant low-frequency peak reflects solid-state diffusion processes (Rdiff). These two peaks exhibited clear dependence on compaction density.\u003c/p\u003e\u003cp\u003eThe observed behavior can be interpreted as follows[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]: lithium-ion diffusion occurs on a timescale of seconds and is influenced by the diffusion coefficient and diffusion distance. As compaction density increases, the ease of electrolyte infiltration and ion transport directly affects the charge transfer and diffusion-related resistances.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEIS Time-Domain Parameter Reference Table\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTime Domain\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e to 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e to 10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 10\u003csup\u003e0\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10\u003csup\u003e0\u003c/sup\u003e to 10\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical Process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOhmic Impedance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSEI Film Impedance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCharge Transfer Impedance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDiffusion Impedance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eInitially, increasing compaction significantly reduced lithium-ion diffusion impedance. Uncompacted electrodes possess loosely distributed active material, resulting in poor particle-to-particle and particle-to-current-collector contact, thereby leading to high resistance [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Moderate compaction shortened interparticle conduction pathways, reducing both Rct and Rdiff. However, excessive compaction beyond the optimal point caused a sharp increase in Rdiff, indicating severely hindered ion transport through clogged electrode pores. Subsequently, Rct also increased, suggesting deteriorated kinetics at the electrode-electrolyte interface[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Correlation between Electrode Morphology and Electrochemical Response\u003c/h2\u003e\u003cp\u003eSEM imaging clearly revealed the structural origins of the increased impedance. Under optimal compaction (1.1 g/cm\u0026sup3;), the electrode exhibited a dense yet porous morphology. In contrast, severe particle cracking and deformation were observed in the over-compacted electrode (1.4 g/cm\u0026sup3;), as indicated by the red arrows in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eMorphological evolution shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e further demonstrates that a coherent compressed layer had formed on the electrode surface at 1.1 g/cm\u0026sup3; without significant particle fracture, indicating satisfactory mechanical stability of the graphite powder under moderate compression [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, at 1.4 g/cm\u0026sup3;, clear particle fragmentation occurred, coinciding with altered lithium-ion diffusion impedance. This microstructural degradation accounts for the increased data scatter in specific capacity measurements\u0026mdash;finely crushed graphite particles filled interparticle voids, increasing exposed superficial area [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and electroactive edge sites available for lithiation. Meanwhile, the local porosity reduction impeded ionic permeability, resulting in dispersed capacity and efficiency values with heightened variability.\u003c/p\u003e\u003cp\u003eBET adsorption-desorption analysis confirmed that Sample A displays characteristics typical of non-porous materials (Type II isotherm), while Sample B possesses a mesoporous structure (Type IV isotherm with H3 hysteresis). This fundamental difference explains why Sample A reached its performance limit at lower compaction density\u0026mdash;its inherently lower porosity renders it more susceptible to pore clogging under compression[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe crushed particles not only reduce the ionic diffusion pathways but also create fresh, active surfaces that continuously consume electrolytes to form a thick and resistive SEI layer [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], which is consistent with the increase in the mid-frequency DRT peak assigned to SEI/interface resistance.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.4. Comprehensive Mechanism Analysis\u003c/h2\u003e\u003cp\u003eCyclic voltammetry (CV) further corroborated the aforementioned conclusions. Under over-compaction conditions, the diminished area of the redox peaks indicates a reduction in the number of effectively reactive lithium ions, which is consistent with the observed capacity decay. Furthermore, the absence of peak shift suggests that compaction density did not alter the fundamental lithiation/delithiation reaction mechanisms, and that the performance degradation is primarily attributed to kinetic limitations. A comparative CV analysis of Sample A at two extreme compaction levels (1.0 and 1.4 g/cm\u0026sup3;) is presented in Fig.\u0026nbsp;5\u003c/p\u003e\u003cp\u003e.\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;5 CV curves at different compaction levels\u003c/p\u003e\u003cp\u003eCV profiles are commonly used to evaluate the reversibility of electrode reactions. As shown in Fig.\u0026nbsp;5, despite the differing compaction levels at a fixed areal density, the oxidation peak (0.28 V) and reduction peak (0.01 V) positions remained unchanged. However, the peak areas decreased notably at higher compaction, indicating reduced active lithium participation. Since peak area correlates with the quantity of electrochemically active lithium, these results confirm that excessive compaction hinders lithium utilization efficiency\u0026mdash;a finding consistent with the specific capacity measurements reported in previous sections[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe electrochemical performance of graphite anodes is critically determined by their microstructural and interfacial properties[\u003cspan additionalcitationids=\"CR18 CR19 CR20\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], which are in turn governed by the compaction density. An optimal compaction density achieves the best compromise between electronic conductivity and ionic transport efficiency. In contrast, excessive compaction induces particle fragmentation and pore clogging[\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], which impedes ion diffusion, and simultaneously generates fresh surfaces that exacerbate side reactions[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. These combined effects ultimately lead to performance degradation and reduced reliability of electrochemical data[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eOptimizing the compaction density is crucial for the accurate characterization of graphite anodes in simulated cells, as it profoundly influences key electrochemical metrics including specific capacity, Coulombic efficiency, and internal impedance. An optimal range of compaction density exists that maximizes electrochemical performance[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Insufficient compaction results in a loose electrode structure with poor interparticle contact and compromised electronic conduction, leading to underutilization of active material. Conversely, excessive compaction induces graphite particle cracking, which exposes fresh surfaces to electrolytes, promotes deleterious side reactions, and increases ionic diffusion resistance, thereby degrading both capacity and efficiency. It is noteworthy that compaction density alters the kinetic limitations rather than the intrinsic phase transformation behavior of graphite, as evidenced by unchanged CV profiles. Given the distinct morphological and mesoporous structural characteristics of different graphite materials, the ideal compaction density is uniquely defined as the range where the combined charge transfer and solid-state diffusion impedances are minimized, ensuring the full realization of the material's electrochemical potential.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eX.D. wrote the main manuscript text.Y.W. guided the testing method for the simulated batteries.J.Z. researched the testing method for the simulated batteries and the method for manuscript writing.J.X. prepared Figures 1\u0026ndash;2.X.K. guided the ideas for material testing.Q.M. prepared Figures 3\u0026ndash;5.K.C. prepared Figure 6.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThe authors are grateful to the Major Science and Technology Innovation Project of Shandong Province, China (No. 2024CXPT016),for the financial support to this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWinter M, Nov\u0026aacute;k P, Monnier A, et al. 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J Electrochem Soc, 2016, 163(7): A1373-A1387.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"ionics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":" Learn more about [Ionics](https://www.springer.com/journal/11581) ","snPcode":"11581","submissionUrl":"https://mc.manuscriptcentral.com/ionics","title":"Ionics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Graphite anode, Simulated cell, Compaction density, Electrochemical impedance spectroscopy, Distribution of relaxation times (DRT)","lastPublishedDoi":"10.21203/rs.3.rs-7739881/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7739881/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGraphite anodes are critical for lithium-ion batteries, and simulated cells are indispensable tools for their electrochemical evaluation. However, the accuracy of these tests is often compromised by the overlooked parameter of compaction density. This study systematically investigates its impact on performance, interfacial impedance, and structural integrity. We demonstrate an optimal density range for consistent measurements of specific capacity and Coulombic efficiency. Excessive compaction degrades performance and increases data scatter, due to particle cracking, fresh surface exposure, increased side reactions, and hindered ion diffusion, as supported by SEM and EIS-DRT analysis. These findings provide pivotal guidelines for standardizing testing protocols and optimizing manufacturing processes.\u003c/p\u003e","manuscriptTitle":"Optimizing Compaction Density for Accurate Electrochemical Characterization of Graphite Anodes in Li-ion Simulated Cells","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-07 13:39:59","doi":"10.21203/rs.3.rs-7739881/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-30T18:11:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-26T16:22:21+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-18T11:44:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"52166029257494276201881705800303893775","date":"2025-11-06T11:56:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"83841767024578947510052999104401087207","date":"2025-10-28T16:47:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-28T16:17:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-10T03:37:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-10T03:37:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Ionics","date":"2025-09-29T08:49:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"ionics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":" Learn more about [Ionics](https://www.springer.com/journal/11581) ","snPcode":"11581","submissionUrl":"https://mc.manuscriptcentral.com/ionics","title":"Ionics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"86e777b0-a3d0-4b97-b1e2-fee5711f5e8f","owner":[],"postedDate":"November 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2025-11-30T18:23:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-07 13:39:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7739881","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7739881","identity":"rs-7739881","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}