Hybrid Point-to-Line Conductive Network of Carbon Nanotubes and Denka Black for High-Rate Lithium-Ion Battery Cathodes

Article information

J. Electrochem. Sci. Technol. 2026;17(3):373-381

Publication date (electronic) : 2026 January 2

doi : https://doi.org/10.33961/jecst.2025.01123

Jekyeong Yu ¹, Yujeong Yun ¹, Sunkyung You ¹, Su-Won Yang ², Jong-Ho Song ², Jinjoo Park ¹, Seongki Ahn ³^,

¹Department of Energy Convergence Engineering, Cheongju University, 111 Taejeong-ro, Maengdong-myeon, Eumseong-gun, Chungcheongbuk-do, 27739, Republic of Korea

²Songjeong Co., Ltd., 493 Seobu-ro, Gangnae-myeon, Cheongju-si, Chungcheongbuk-do, 28177, Republic of Korea

³Department of Chemical Engineering, Research Center of Chemical Technology, Hankyong National University, 27, Jungangro, Anseong-si, Gyeonggi-do, 17738, Republic of Korea

^*CORRESPONDENCE T: +82-43-883-4789 E: skahn@hknu.ac.kr (S. Ahn) jeha@cju.ac.kr (J. Kim) hikim007@cju.ac.kr (H.-I. Kim)

Received 2025 November 25; Accepted 2026 January 1.

Abstract

In this study, a composite dispersion of conductive additives, comprising carbon nanotubes (CNT) and Denka Black (DB), was prepared via a high-pressure homogenization (HPH) process. This approach was designed to overcome the limitations of carbon black-based conductive networks in lithium-ion battery cathodes. Raman mapping confirmed the uniform dispersion of the CNT+DB mixture, while scanning electron microscopy revealed that the composite additive formed a more continuous point-to-line conductive network compared to individual CNT or DB electrodes. Electrical conductivity measurements and electrochemical impedance spectroscopy revealed higher electronic conductivity and lower charge-transfer resistance of the CNT+DB than the individual additives. During cyclic voltammetry, the CNT+DB electrode exhibited the highest peak current among the samples, suggesting more active redox behavior. Electrochemical performance tests demonstrated that the CNT+DB electrode retained 55.7% of its initial capacity at 5C and maintained 71.9% of its capacity during long-term cycling at 2C, exhibiting enhanced high-rate stability. These findings indicate that the three-dimensional conductive network created by combining CNT and DB effectively enhances electron pathways and stabilizes ion transport within the electrode.

Keywords: Carbon Nanotubes; Denka Black; Conductive Network; High-pressure homogenization

INTRODUCTION

Lithium-ion batteries (LIBs) offer several advantages, such as high energy density, excellent capacity retention, and long cycle life, making them widely applicable in portable electronic devices, electric vehicles (EVs), and energy storage systems [1–3]. Owing to the rapid growth of the EV market, fast-charging capability and long-term performance stability have become increasingly crucial for LIBs [4,5]. Consequently, extensive research has focused on enhancing electrode performance through strategies such as active material surface coating [6], using conductive binders [7], and optimizing the dispersion and conductive network structures of conductive additives [8]. LIB electrodes comprise active materials, conductive additives, and binders, with the active material being the primary component [9]. However, active materials such as LiFePO₄ and LiNi_xCo_yMn_zO₂ (NCM) have inherently low electrical conductivity, hindering efficient electron transport within the electrode and degrading overall electrochemical performance [10–14]. Therefore, establishing a well-connected conductive network is crucial, achieved by forming conductive binder domains through the interaction between conductive additives and binders to facilitate efficient electron transport pathways within the electrode [15–17]. Carbon-based conductive additives such as carbon black (CB), graphite, and carbon nanotubes (CNTs) are commonly used for this purpose [18–20]. Among these, CB is widely used in commercial electrodes due to its excellent dispersibility and low cost. However, its point-to-point contact structure provides only partially continuous electron pathways, limiting electrical conductivity [21–23]. In contrast, CNTs, due to their one-dimensional linear structure, exhibit exceptional electrical conductivity and mechanical stability [24–26]. These characteristics enable CNTs to form continuous conductive frameworks within electrodes, providing long and efficient electron-transport pathways that enhance electrochemical performance [27–29]. However, CNTs suffer from strong van der Waals interactions, causing severe agglomeration and poor dispersibility in most solvent systems [30–32]. To address this issue, high-pressure homogenization (HPH) technology has recently been widely utilized in the dispersion process of nanocarbon-based materials [33,34]. The HPH process effectively disaggregates CNT bundles and creates a more uniform dispersion by applying pressures of several hundred MPa through a narrow orifice, generating shear, turbulence, and cavitation [35,36]. In addition, composite conductive materials combining the fine particle structure of CB with the superior electrical conductivity of CNTs have been developed, forming a three-dimensional (3D) conductive network within the electrode that integrates point-to-point and line-to-line electron connections [37–41]. Representative examples of these hybrid conductive additives reported in the literature are summarized in Table S1. This 3D conductive network reduces interfacial resistance between the electrode and the electrolyte, improving long-term stability and high-rate charge–discharge performance [42,43]. In this study, Denka Black (DB), a type of CB, was used as the conductive additive. To overcome CNT dispersion limitations, CNT and CNT+DB composite dispersions were prepared using a HPH. Subsequently, electrodes were fabricated under identical conditions using CNT dispersion, DB, and the CNT+DB composite. Their electrochemical properties were then comparatively evaluated. Therefore, this study aims to investigate the effects of HPH-assisted dispersion on the microstructure and conductive network formation of CNT and CNT+DB composite dispersions, and to determine how these HPH-induced structural differences affect the electrochemical performance of NCM622 cathodes compared to conventional DB powders. The results highlight the electrochemical advantages of the composite conductive additive in enhancing electron transport and overall conductive network within the electrode.

EXPERIMENTAL

Materials

LiNi_0.6Co_0.2Mn_0.2O₂ (NCM 622) powder was used as the cathode active material. Poly(vinylidene fluoride) (PVDF, Solef^® 5130) was used as a binder and dissolved in N-methyl-2-pyrrolidone (NMP, analytical grade) to prepare a 6 wt% solution. Commercially available Denka Black (DB) and commercially available surface-functionalized multi-walled CNTs were used as conductive additives. CNT and CNT+DB composite dispersions were prepared in-house using a high-pressure homogenization method. DB is a carbon-based conductive material composed of primary particles with a size of approximately 35–50 nm, and CNTs are known as a one-dimensional carbon nanostructure material with a diameter of 10–20 nm and a length of several hundred micrometers [44,45].

Preparation of CNT and CNT+DB Dispersions

The CNT and CNT+DB dispersions were prepared using the same method. NMP, supplier-pretreated (surface-functionalized) multi-walled CNTs, a polymer-based dispersant, and DB (for composite dispersion) were initially mixed with an overhead stirrer at 600 rpm for 1 h. The pre-dispersed mixture underwent HPH at 700 bar for eight passes, followed by three passes at 200 bar. This homogenization process regulated particle size, yielding a uniformly dispersed CNT+DB dispersion.

Electrode Fabrication

NCM 622 and DB powders were vacuum-dried at 120°C for 14 h to eliminate residual moisture. The dispersions of CNT and CNT+DB were prepared following the same procedure. A 6 wt% PVDF solution was prepared by dissolving PVDF in NMP and used as the binder solution. The active material, conductive additive, and binder were mixed at a weight ratio of 94:3:3 (w/w) using a Thinky Mixer (ARE-310, Thinky Corp., Japan). Initially, the conductive additive was added to the pre-dispersed binder solution and mixed at 1100 rpm for 7 min, followed by defoaming at the same speed for 3 min (one mixing cycle). Subsequently, high-speed dispersion was carried out at 2000 rpm for three cycles (10 min per cycle) to ensure effective dispersion of the conductive additives within the binder matrix. Afterward, the active material was added and pre-mixed at 1100 rpm for one cycle (10 min), followed by homogenization at 1500 rpm for four cycles (10 min per cycle) while adding NMP to adjust the slurry viscosity. The total mixing time was approximately 90 min. The final slurry had a solid content of approximately 45–50 wt% and was prepared and processed at room temperature. The resulting slurry was sieved to remove impurities and cast onto aluminum foil using a doctor blade with a coating gap of 125 μm. The coated electrodes were dried overnight at 80°C to evaporate NMP, followed by cold rolling, and finally vacuum-dried at 120°C for 14 h to completely remove any remaining solvent. All electrodes were fabricated under identical conditions. The NCM622 cathodes had an active material loading of approximately 5.46 mg cm^-2, a dried electrode thickness of 78 μm after calendering, and a corresponding electrode density of 0.70 g cm^-3. A polyethylene separator with a thickness of 24 μm was used, and 60 μL of electrolyte was injected into each 2032-type coin cell. For each electrode composition (DB, CNT, and CNT+DB), at least three coin cells were assembled and tested under identical conditions, and representative data are presented. Based on the comparable electrode thickness and density obtained under identical fabrication conditions, the electrode porosity is expected to be similar across all samples.

Characterization

The fabricated cathodes (diameter: 14 mm) were utilized in coin-cell assembly, alongside polyethylene separators (diameter: 19 mm) and Li metal foils (diameter: 16 mm) as anodes. The electrolyte employed was 1 M LiPF₆ in ethylene carbonate/dimethyl carbonate (1:1 v/v) with 2 wt% vinylene carbonate. 2032-type coin cells were constructed for electrochemical assessment. Electrochemical impedance spectroscopy (EIS) was conducted using a ZIVE SP2 (Wonatech, Seoul, Republic of Korea) across a frequency range of 2 MHz to 100 mHz, with data analyzed as Nyquist plots. Measurements were performed using an AC amplitude of 10 mV, and the DC bias was set to the end-of-charge (EOC) voltage of the cell to ensure reproducibility. Charge–discharge characteristics were evaluated at 2C within a voltage range of 3.0–4.2 V. The morphology of conductive additives and electrode surfaces was examined using field-emission scanning electron microscopes (MIRA3 LMU, Tescan, Czech Republic; Gemini 560, Carl Zeiss, Germany). Raman spectra and mapping analyses were performed using a confocal micro-Raman spectroscopy system (HEDA, NOST; RAMANtouch, Nanophoton Corp., Japan). Electrical conductivity was determined using a Hall Effect Measurement System (HMS-3000, Ecopia, Republic of Korea).

RESULTS AND DISCUSSION

The diagram outlines how CNT and DB are dispersed using a HPH. CNTs agglomerate due to van der Waals forces, while DB particles cluster together, resulting in point-to-point electron conduction paths. These limited pathways impede electron transport and reduce electrical mobility. To address this, a pre-dispersed CNT+DB solution underwent further processing with a HPH. The solution was injected into the homogenizer, where high pressure pushed it through a narrow channel, breaking down CNT and DB agglomerates. Subsequent collisions between the impact head and ring, along with microbubble formation and collapse, facilitated complete deagglomeration. Repetition of this process yielded a uniformly dispersed CNT+DB solution. In this dispersion, CNTs formed a continuous conductive network, with DB particles interspersed, enhancing contact points for electron transport and improving electrode electrochemical performance [40].

Fig. 1.

Schematic of the dispersion mechanism of CNT and DB using a HPH.

Fig. 2(a) shows the typical aggregated morphology of spherical CB particles, which depend on point-to-point contact between particles to establish electron-conducting pathways, potentially causing discontinuous electron transport within the electrode. Fig. 2(b) depicts CNTs before dispersion treatment, where strong van der Waals interactions lead to their bundling into thick agglomerates. During the drying process, these bundles become compressed and partially aligned, hindering uniform network formation due to strong inter-tube attraction [46]. Fig. 2(c) and (d) display the dried CNT and CNT+DB dispersions obtained via HPH. Both samples display an entangled and interconnected linear CNT network, as the HPH process effectively breaks down CNT bundles through strong shear force and turbulence, contributing to the formation of a more uniform and well-dispersed conductive structure. Particularly, Fig. 2(d) illustrates that DB fills the gaps between CNTs, forming a point-to-line hybrid conductive network. Consequently, the combination of CNT and DB forms a 3D conductive network, enhancing electron transport and structural stability within the electrode, thereby improving electrochemical performance.

Fig. 2.

SEM images of conductive materials: (a) DB, (b) CNT, (c) dried CNT dispersion, and (d) dried CNT+DB dispersion.

Fig. 3(a) shows the Raman spectra of pure DB powder and dried CNT and CNT+DB dispersions, and Raman mapping analysis was performed on the dried CNT and CNT+DB dispersion samples. DB was analyzed in powder form, while CNT and CNT+DB composite conductive additives were examined after drying their dispersions. The Raman spectrum of pure CNT powder is provided in Fig. S1 for direct comparison. All samples exhibited the characteristic D band (~1350 cm^-1), G band (~1580 cm^-1), and 2D band (~2700 cm^-1). The D band signifies structural disorder in the carbon lattice, while the G band indicates the crystallinity of sp²-hybridized carbon. Thus, the I_D/I_G ratio serves as a crucial indicator of the defect degree and crystallinity of each conductive additive. The I_D/I_G values of DB, CNT, and CNT+DB were 0.985, 1.150, and 1.059, respectively, indicating that DB has relatively higher crystallinity compared to the other additives, while CNT and CNT+DB exhibit higher defect levels. The increase in the I_D/I_G ratio of the CNT sample is attributed to the introduction of structural defects during the high-pressure homogenization process. The strong shear forces, turbulence, and cavitation occurring under high pressure can partially destroy the graphitic structure of the CNT, leading to defect formation. This is consistent with previous research on high-energy dispersion processes. CNT exhibited an increased I_D/I_G value due to structural defects arising during the dispersion process, whereas the CNT+DB composite showed a lower I_D/I_G than CNT, suggesting that the presence of DB mitigates CNT aggregation and partially maintains the graphitic ordering of CNT. Additionally, the 2D band of Denka Black appeared broadened and weak, characteristic of disordered carbon materials [47]. Fig. 3(b) and 3(c) illustrate the I_D/I_G Raman mapping (100 × 100 μm²) of the dried CNT and CNT+DB samples. The coefficients of variation (CV) were calculated as 5.78% and 6.33%, respectively. Both samples displayed uniform intensity distributions across the entire area, confirming highly uniform I_D/I_G distributions. Particularly, the CNT+DB sample maintained a high level of uniformity, as the HPH process effectively separated CNT bundles and uniformly dispersed DB, even within the composite structure. These outcomes indicate that CNT+DB composite conductive additive forms a stable and homogeneous 3D conductive network.

Fig. 3.

(a) Raman spectra of pristine DB powder, CNT, and CNT+DB obtained from dried dispersions, (b) Raman mapping of the dried CNT dispersion, (c) Raman mapping of the dried CNT+DB dispersion.

Fig. 4 shows the surface SEM images of electrodes prepared using Denka Black, CNT dispersion, and CNT+DB composite dispersion. (a) represents the electrode containing Denka Black, where the conductive additive exhibits a typical spherical carbon black morphology and is distributed on the surface of active materials in an aggregated form. This structure provides limited point-to-point particle connections, resulting in insufficient connectivity of the conductive network and potential non-uniformity in electrical conductivity across the electrode. (b) shows the electrode fabricated with the CNT dispersion, where CNTs form a continuous line-to-line conductive network along with partially aggregated regions. Such a structure can enhance the electrical conductivity of the electrode by extending electron transport pathways between active material particles; however, locally aggregated CNTs may lead to concentrated electron flow in certain regions. (c) and (d) correspond to the electrode prepared with the CNT+DB composite dispersion and its magnified image. In these images, CNTs are entangled and cross-linked, forming a continuous conductive network, while DB serves as an auxiliary conductive pathway. In particular, (d) clearly reveals the coexistence of the line-to-line network formed by CNTs, the point-to-line pathways formed by CNT–DB contacts, and the point-to-point contacts formed by DB itself on the active material surface. The formation of this three-dimensional (3D) hybrid conductive network plays a crucial role in enhancing charge-transfer efficiency within the electrode [48].

Fig. 4.

SEM images of electrode surfaces: (a) DB, (b) dried CNT dispersion, (c) dried CNT+DB dispersion. (d) High-magnification image of the CNT+DB dispersion sample.

Fig. 5 compares the electrical and electrochemical properties of electrodes fabricated using DB, CNT, and CNT+DB as conductive additives for the NCM622 electrodes. The electrodes in Fig. 5(a) were prepared by blending the active material, conductive additive, and binder at a ratio of 94:3:3 (w/w) and applying the mixture onto the PET film. Electrical conductivity, measured using a four-point probe, was 9.3, 118.2, and 125.6 S m^-1 for DB, CNT, and CNT+DB, respectively. The superior conductivity of CNT+DB is attributed to the combination of one-dimensional CNT pathways and particle-to-particle connections of DB, forming a more continuous composite network. CNT also exhibited high conductivity due to its extended linear electron pathways, while DB exhibited lower conductivity due to limitations of CB-based point-to-point conduction. Nyquist plots in Fig. 5(b) indicated that CNT+DB had the lowest charge-transfer resistance (90 Ω), followed by CNT (108 Ω) and DB (113 Ω). This observation suggests that the composite additive enhances charge-transfer kinetics more effectively. Cyclic voltammograms of all electrodes (Fig. 5(c)) revealed similar shapes with redox peaks at identical potentials, indicating normal lithium insertion/extraction behavior. However, the peak current intensity varied significantly among the electrodes. DB exhibited the lowest peak current, CNT showed a higher response, and CNT+DB exhibited the highest, consistent with the trends observed in conductivity, EIS, and rate performance measurements. Additional cyclic voltammetry results are presented in Fig. S2. The charge–discharge profiles at 2C for the 1st, 20th, 30th, 50th, and 100th cycles (Fig. 5(d–f)) indicated that the DB delivered capacities of 61.63, 120.92, 118.40, 112.60, and 79.62 mAh g^-1, respectively, showing moderate decay due to stable but limited particle-based conduction. The full charge–discharge voltage profile corresponding to Fig. 5d is shown over the entire voltage range, including the low-voltage region below 3.0 V, in the Supporting Information (Fig. S3). For transparency, the original profile is presented without modification. The CNT electrode exhibited capacities of 119.63, 89.42, 89.75, 85.56, and 58.64 mAh g^-1, reflecting a faster decline caused by the reduced stability of one-dimensional CNT pathways during long-term high-rate cycling. In contrast, the CNT+DB exhibited capacities of 127.86, 110.59, 111.38, 107.84, and 98.45 mAh g^-1 maintaining high capacities and stable profiles due to the synergistic 3D conductive framework formed by CNT and DB. As shown in Fig. 5(g), during the rate capability test, the CNT+DB electrode delivered a specific capacity of 163.13 mAh g^-1 at 0.1 C and retained 90.8 mAh g^-1 at 5C, corresponding to 55.7% retention. The CNT electrode exhibited an initial specific capacity of 154.76 mAh g^-1 and retained 80.26 mAh g^-1 at 5C (51.8%). In comparison, the specific capacity of DB decreased from 165.52 to 60.87 mAh g^-1 (37%). These results indicate that CNT+DB exhibits the most stable performance under high-rate conditions. Fig. 5(h) shows that long-term cycling at 2C further differentiated the electrodes. DB exhibited an initial capacity of 61 mAh g^-1, which was increased to 120 mAh g^-1 after activation, and decreased to 44 mAh g^-1 after 130 cycles (71.5%). The initial capacity of CNT was 119.6 mAh g^-1, which decreased to 34.43 mAh g^-1 (28.79%). In contrast, CNT+DB exhibited an initial capacity of 127.9 mAh g^-1 and maintained 91.9 mAh g^-1 (71.9%) over the same number of cycles. The superior stability of CNT+DB is attributed to a more interconnected 3D conductive network combining CNT pathways with DB particle contacts. This hybrid conductive structure helps maintain electron transport pathways even after microcracks in the active material particles occur, promotes more uniform reaction distribution across the electrode, reduces local polarization, and mitigates mechanical damage during long-term charge-discharge processes. The gradual increase in capacity during the initial cycles (activation behavior) is commonly attributed to progressive electrolyte wetting of the electrode, improved electrode–electrolyte interfacial contact, and gradual formation and stabilization of conductive pathways within the electrode. In addition, partial activation of electrochemically accessible active-material surfaces during early cycling may contribute to the observed capacity increase.

Fig. 5.

Comparison of electrode characteristics for DB, CNT, and CNT+DB (a) Four-probe electrical conductivity of slurry films dried on PET substrates, (b) Nyquist plots, (c) cyclic voltammograms at 0.2 mV s^-1, (d–f) charge-discharge voltage profiles for DB, CNT, and CNT+DB electrodes. (g) rate performance, and (h) cycle performance at a charge-discharge current of 2C

CONCLUSIONS

In this study, a composite CNT+DB conductive additive was fabricated using a HPH technique and applied to NCM622 cathodes. The hybrid additive formed a more continuous and interconnected conductive network compared to electrodes with only CNT or DB, leading to enhanced electrical conductivity and decreased charge-transfer resistance. During high-rate charge–discharge conditions, the electrode maintained 55.7% of the initial capacity at 5C and 71.9% during 2C cycling, demonstrating enhanced stability at elevated rates. These results indicate that the three-dimensional conductive framework created by combining CNT and DB enables efficient electron pathways and supports stable ion transport within the electrode. Hence, the CNT+DB composite conductive additive offers a promising approach to enhance the performance of lithium-ion battery cathodes.

Notes

ACKNOWLEDGMENTS

This work was partly supported by Korea Institute of Energy Technology Evaluation and Planning(KETEP) grant funded by the Ministry of Climate, Energy & Environment(MCEE) of the Republic of Korea(No. 20224000000070, Human Resource Training For Smart Energy New Industry Cluster).

This study received funding from the Human Resources Development of the Korea Institute of Energy Technology Evaluation and Planning (KETEP), which is supported by the Korean government (RS-2024-00394769).

This research was supported by the Cheongju University Research Scholarship Grants in 2024~2025.

SUPPORTING INFORMATION

jecst-2025-01123-Supplementary-Table-S1.pdf

jecst-2025-01123-Supplementary-Fig-S1-S3.pdf

References

1. Hasan M. M, Haque R, Jahirul M. I, Rasul M. G, Fattah I. M. R, Hassan N. M. S, Mofijur M. J. Energy Storage 2025;120:116511.

2. Nasajpour-Esfahani N, Garmestani H, Bagheritabar M, Jasim D. J, Toghraie D, Dadkhah S, Firoozeh H. Renew. Sustain. Energy Rev. 2024;203:114783.

3. Chen T, Jin Y, Lv H, Yang A, Liu M, Chen B, Xie Y, Chen Q. J. Energy Storage 2020;26:208–217.

4. Yao Y.-X, Xu L, Yan C, Zhang Q. EES Batteries 2025;1:9–22.

5. Arsad S. R, Hannan M. A, Ker P. J, Wong R. T. K, Begum R. A, Hossain M. J, Jang G. J. Energy Storage 2025;131:117551.

6. Al-Samet M. A. M. M, Burgaz E. Electrochim. Acta 2024;507:145167.

7. Grygiel M, Ratyński M, Czerwiński A, Hamankiewicz B. Appl. Phys. A 2024;130:889.

8. Wang Z, Tu J, Yu X, Li F, Zhao Z, Cui Y, Zhao T. Particuology 2024;92:1–12.

9. Miranda D, Gören A, Costa C. M, Silva M. M, Almeida A. M, Lanceros-Méndez S. Energy 2019;172:68–78.

10. Zhong Y, Yang M, Zhou X, Zhou Z. Mater. Horiz. 2015;2(6):553–566.

11. Jang J, Im H, Koo J. K, Kim M. S, Mun J, Kim Y.-J. J. Energy Storage 2025;114:115935.

12. Yücel Y. D, Adolfsson E, Dykhoff H, Pettersson J, Trey S, Wysocki M, Zetterström E. W, Zenkert D, Lindström R. W, Lindbergh G. Compos. Sci. Technol. 2024;251:110571.

13. Du Z, Li J, Wood M, Mao C, Daniel C, Wood D. L III. Electrochim. Acta 2018;270:54–61.

14. Bauer W, Nötzel D, Wenzel V, Nirschl H. J. Power Sources 2015;288:359–367.

15. Beran L, Knapp T. V, Nexha A, Lay M, Niebuur B.-J, Kraus T. Adv. Eng. Mater. 2025;27(8):2401813.

16. Weber M, Gerstenberg J, Kwade A. J. Energy Storage 2024;99:113244.

17. Baumgärtner J. F, Kravchyk K. V, Kovalenko M. V. Adv. Energy Mater. 2025;15(2):2400499.

18. Entwistle J, Ge R, Pardikar K, Smith R, Cumming D. Renew. Sustain. Energy Rev. 2022;166:112624.

19. Choi J. H, Lee C, Park S, Hwang M, Embleton T. J, Ko K, Jo M, Saqib K. S, Yun J, Jo M, Son Y, Oh P. Electrochem. Commun. 2023;146:107419.

20. Huang L, You Y, Liu M, Liu J, Gu J, Zhan X, Wang W, Wang F, Tan H, Wu S, Zhang L. Carbon 2024;230:119688.

21. Muchuweni E, Mombeshora E. T, Muiva C. M, Sathiaraj T. S. Nano Trends 2024;6:100034.

22. Lee Y, Choi J, Kang S. H, Lee Y.-G, Lim J, Jin H. M, Kim J. Y. Chem. Eng. J. 2025;511:162096.

23. He L, Peng J, Liu X, Liu P, Yang J, Tang Y, Wang X. Electrochim. Acta 2025;511:145353.

24. Shahpouri E, Hassani S, Yousefi-Mashhour H, Aghababaeian S, Kalantarian M. M. Carbon Trends 2023;13:100293.

25. Ghosh A, Sahoo N, Das B, Patel P, Patil G. M, Sachan V, Basak S. Synth. Met. 2025;314:117944.

26. Jia Y, Zhou K, Sun W, Ding M, Wang Y, Kong X, Jia D, Wu M, Fu Y. J. Mater. Res. Technol. 2024;32:1395–1415.

27. Tian H, Kuang X, Liu P, Chen X. J. Alloys Compd. 2025;1020:179421.

28. Wang L, Zhao Y, Zhang H, Wang H, Chen C, Huang Y, Xue H, Lan Y, Qiao F, Wang J, Lou Z, Pan F. Energy Storage Mater. 2025;78:104255.

29. Lee J, Bak M, Yoo P. J, Kim W.-J. Appl. Surf. Sci. 2025;688:162440.

30. Ali A, Koloor S. S. R, Alshehri A. H, Arockiarajan A. J. Mater. Res. Technol. 2023;24:6495–6521.

31. Ramachandrarao M, Khan S. H, Abdullah K. Compos. C: Open Access 2025;16:100551.

32. Lee S, Baek S, Park C, Shin D, Kim J, Sung Y. Case Stud. Therm. Eng. 2025;67:105814.

33. Inguva P, Grasselli S, Heng P. W. S. Chem. Eng. Res. Des. 2024;202:284–302.

34. Wu H, Zhou W, Liu Q, Cai X, Qu Z, Li P, Hu D, Ji X. J. Appl. Polym. Sci. 2022;139(12)e51838.

35. Li Y, Huang X. Compos. - A: Appl. Sci. Manuf. 2015;78:166–173.

36. Azoubel S, Magdassi S. Carbon 2010;48(12):3346–3352.

37. Xiang H, Ren H, Liu Y, Yang D, Feng X. J. Power Sources 2024;609:234672.

38. Cho Y, Lee E, Lee K. S, Hwang S. J, Kim C. W, Kim T.-G, Kang S.-K, Park S. Y, Yoo K, Piao Y. Electrochim. Acta 2023;447:142134.

39. Fang Y, Yu H, Wang Y, Zhang Z, Zhuang C, Fang G, Luo Z, Zhang B, Wang B. J. Polym. Eng. 2020;40:806–814.

40. Hamed S, Obrezkov F, Huotari S, Colalongo M, Mousavihashemi S, Kallio T. J. Power Sources 2024;608:234549.

41. Coban A, Gungor H. Arab. J. Sci. Eng. 2022;47:7147–7155.

42. Choi C. J, Kim T. H, Kim H. W, Jeon D. M, Han J. Nanomaterials 2025;15(3):156.

43. Wang K, Wu Y, Luo S, He X, Wang J, Jiang K, Fan S. J. Power Sources 2013;233:209–215.

44. Zainol M. M, Abidin A. Z, Rahman S. N. F. S. A, Mustaffa N, Azli A. A. M, Mustapa A. N, Mamat M. H, Syed-Hassan S. S. A, Ali N. H. N, Ahmad M. H, Hamdan K. Energy 2025;340:139123.

45. Xiong Z, Yun Y. S, Jin H.-J. Materials 2013;6(3):1138–1158.

46. Guo M, Cao Z, Liu Y, Ni Y, Chen X, Terrones M, Wang Y. Adv. Sci. 2023;10:2207355.

47. Li Z, Deng L, Kinloch I. A, Young R. J. Prog. Mater. Sci. 2023;135:101089.

48. Wang F, Han Q, Ji S, Wang J, Du B, Li K, Tian L, Zhang W, Tang S, Cheng S, Cao Y.-C. J. Colloid Interface Sci. 2025;699:138055.

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