Graphite Particles Research Articles

Extracting ductile cast iron microstructure parameters from fracture surfaces: A deep learning based instance segmentation approach

This study investigates the deep-learning based microstructural analysis from SEM images of ductile cast iron fracture surfaces. A Mask R-CNN model was trained, achieving 70% precision and 75% recall in graphite particle detection. Combined with a fracture surface reconstruction using the.4-quadrant backscattered electron signal, key parameters, including the particle size, shape and distance were extracted accurately. Compared to micrograph analysis, following probabilistic simulations showed the impact of the higher microstructural variance for the fracture surfaces on crack initiation, leading to higher scatter and elevated crack resistance curves. This highlights the potential of deep-learning based analysis for comprehensive microstructural characterization.

Mechanical, electrical, and piezoresistive properties of modified conductive recycled fine aggregate smart mortar

The application of recycled fine aggregates (RFA) in smart conductive mortar is of great significance for conserving natural resources and protecting the environment. However, the high water absorption and microstructural defects of RFA limit its widespread use in smart conductive mortar. This study employs an agar gel impregnation treatment containing graphite particles to improve the properties of RFA. The resulting modified conductive recycled fine aggregate (M-RFA) exhibited a 2.8 % reduction in water absorption. The workability, mechanical properties, electrical properties, and self-sensing capabilities of the modified recycled fine aggregate mortar (M-RFAM) were studied. It was found that the workability and mechanical properties of the smart conductive mortar prepared with M-RFA were slightly reduced but remained within acceptable ranges (28-day compressive strength greater than 33 MPa). At the same time, it achieved low resistivity and high strain-sensing sensitivity, with the highest strain-sensing sensitivity being 61.9 (30 times higher than ordinary strain gauges). The influence of loading rate and moisture content on the self-sensing ability of conductive mortar was also investigated, revealing a positive correlation between moisture content and stress-sensing ability. Furthermore, the study found that factors such as AC frequency, curing age, moisture content, and temperature significantly affect resistivity. These factors should be considered in practical applications and further research.

Indentation Fracture Toughness of Aluminium-Graphite Composites: Influence of Nano-particles

In the field of composite materials, extensive research has been undertaken on aluminum-graphite composites. However, a research gap has been identified regarding the specific influence of nano-sized graphite particles on their fracture toughness. Previous studies have predominantly focused on larger graphite particles or different reinforcement materials, resulting in relatively unexplored effects of nano-graphite particles. This research is deemed critical as it has the potential to generate lightweight, high-strength materials, aligning with the demands of aerospace, automotive, and structural engineering. The primary objective of this study is to investigate how the inclusion of nano-sized graphite particles affects the fracture toughness of aluminum-graphite composites. To achieve this objective, systematic dispersion and incorporation of nano-sized graphite particles into an aluminum matrix will be carried out. Mechanical testing, including fracture toughness assessments, will be conducted to evaluate the performance of the composite materials. Factors such as particle size, distribution, volume fraction, and interfacial bonding will also be characterized within the study. It is anticipated that the presence of nano-sized graphite particles will lead to a significant enhancement of the fracture toughness of the aluminum-graphite nanocomposites. This enhancement is expected to be attributed to crack deflection, tortuosity, altered stress distribution, and increased plastic deformation around cracks.

Characterization of identical lithium-ion battery electrodes before and after charge/discharge cycles via in-plane large-area polishing

As an effective method to fabricate a large-area cross-sectional sample for lithium-ion battery electrodes, we perform in-plane polishing of LiNi0.8Co0.15Al0.05O2(NCA) cathode samples and obtain a large cross-sectional area with a diameter of 1.5 mm. The polished cross-sections of NCA cathode particles are sufficiently flat to perform the atomic force microscopy (AFM) measurements on each cathode particle. Following AFM-based Kelvin probe force microscopy and scanning spreading resistance microscopy measurements, an identical in-plane polished NCA sample is assembled into a coin cell for the charge and discharge processes. After 90 charge/discharge cycles, the in-plane-polished sample is successfully disassembled from the coin cell without causing critical damage. In addition, a microcrack structure, which is a typical degradation feature of the cycles of NCA particles, is observed for the identical in-plane polished NCA sample. This indicates that the in-plane polishing method is effective for investigating identical NCA electrode samples before and after the charge/discharge process. Furthermore, the in-plane polishing method can be successfully applied to the large-area polishing of a Si-based anode which is a mixture of Si carbon complexes and graphite particles. This study presents a novel methodology for analyzing the degradation of lithium-ion battery electrode materials.

Tribological, mechanical and microstructure characteristics of hybrid aluminium matrix composite containing titanium carbide (TiC) and graphite particles

The present study emphasize on the characterization and microstructure evaluation of aluminium composite with different weight fraction of constituents. These composites were produced by incorporating titanium carbide and graphite particles in the aluminium matrix through stir casting technique. The composites were characterized by evaluating the micro hardness, density, tensile strength, peak elongation and impact strength. Scanning electron microscopy and X-ray diffraction tests were performed to investigate uniform dispersion of the reinforcement particles in the matrix. It is evident that the addition of reinforcement particles with aluminium matrix yielded an increase in micro hardness and density by 62.82% and 7.05% respectively when compared to matrix. Tensile tests exposed that there was improvement in ultimate strength from 170 to 239.11 MPa while the elongation was dropped to 7.1%. The microscopic study of the specimen explored the plastic deformation through existence of dimples, ridges in the wrecked surfaces.

Comparison of microstructure and tribological behavior for ductile iron with quench-tempered and intensive quench-tempered

In recent years, the intensive quenched process has gained significant attention due to its low energy consumption and absence of pollution. The tribological behavior of traditional quenched and tempered ductile iron (DI_QAT) and an innovative intensive quenched and tempered ductile iron (DI_IQAT) was investigated. Both DI_QAT and DI_IQAT consist of graphite, ferrite and cementite particles. Compared to DI_QAT, DI_IQAT exhibits higher hardness, impact toughness, and yield strength. Wear tests indicate that the friction coefficient of DI_IQAT is lower and the wear resistance of DI_IQAT surpasses that of DI_QAT, it is mainly related to its enhanced wear-resistant structure. Examination of the wear surface morphology reveals that the primary wear mechanisms for DI_QAT and DI_IQAT involve adhesive and abrasive wear.

DETERMINATION THERMAL AND MECHANICAL PROPERTIES OF NANO CARBON, GRAPHITE AND GRAPHENE REINFORCED RECYCLING POLYPROPYLENE COMPOSITE SAMPLES

Polymer-based plastic materials occupy a major place in daily life. However, due to the nature of polymer materials, low thermal resistance and mechanical properties of these products, the need for new and sustainable materials in the industry has increased. With the rapid technological developments in advanced manufacturing industries such as aviation, marine, motor sports and defence industry, lightweight and high-strength composite products have become even more important. In this context, in this study, 1% carbon, graphene and graphite particle reinforced Polypropylene (PP) composite material mixed in a twin-screw extruder and MA/G series injection moulding machine standard tensile test sample produced. Melt Flow Index (MFI), Heat Deformation Test (HDT), tensile test, Shore-D hardness measurement and density tests performed on these test samples. According to the results obtained from these tests, the mechanical and thermal properties of the test samples produced from different composite materials were determined. The best mechanical and thermal properties occurred in the graphene particle. It formed in graphite and carbon, respectively.

Flotation separation of lithium–ion battery electrodes predicted by a long short-term memory network using data from physicochemical kinetic simulations and experiments

Anode and cathode active materials from spent lithium–ion batteries may be recovered and potentially used in new batteries to promote recycling and resource circulation. Froth flotation was applied to pristine active materials and the black mass obtained from pretreated spent batteries. Flotation kinetics was simulated with the use of computational fluid dynamics and surface chemistry. Bubble surface coverage and entrainment in the flotation kinetics model were selected and optimized by systematic fitting to experimental data. Entrainment influences the recovery and grade of the active materials. The optimized flotation kinetics model was used for generating additional data that, along with the fitted data, were used to train a deep learning neural network. The trained network was validated using anode–cathode and black mass flotation experiments, and its predictions showed a maximum residual error of 0.18 ± 0.11 recovery. The simulation framework was developed into a desktop application that predicts the flotation behavior of active materials. It provides information for estimating results following operational and physicochemical changes and for optimizing flotation processes. Finally, recovered anode active materials from black mass were selected for coin cell tests. The coulombic efficiency of these coin cells was initially lower (86.8 %) than that of cells made with pristine graphite particles (98.4 %).

Real-time electrochemical-strain distribution and state-of-charge mapping via distributed optical fiber for lithium-ion batteries

Deep learning has opened new avenues for estimating the dynamic state of charge in batteries. However, hindered by macroscopic and limited electrochemical inputs, data-driven models still struggle to accurately capture local states inside batteries. This study aims to leverage distributed fiber optic sensing and long short-term memory to enhance the accuracy and reliability of the state of charge estimation and to visualize its distribution. First, the internal strain is closely linked to the lithium embedded state of graphite particles, with a coefficient of 0.992 between strain amplitude and capacity over long cycles. Incorporating strain as an additional physical parameter significantly improves accuracy. The proposed model achieves a prediction error of only 2.01 %, representing a 41.2 % improvement compared to models that exclude stain data. Factors such as current and ambient temperature are considered to prove the effectiveness of this method. Furthermore, by combining the trained model with internal strain distribution, the developed intuitive imaging for local state visualization reveals aging tendencies and uneven behavior in lithium-ion batteries. This predictive and imaging approach offers valuable insights for local state analysis and advances battery research and design.

Gas adsorption analysis for quantifying the edge sites of graphite

The edge plane exposed on the surface of carbon materials is the active site that determines their properties. When graphite is used as the negative electrode in lithium-ion batteries, the edge plane acts as an access point for lithium insertion/desorption. However, because of the low specific surface area and amorphous carbon coating of graphite particles, accurately estimating the number of edge planes is challenging. Therefore, we propose a technique for determining graphite edge planes based on the stepwise adsorption of Kr onto the hexagonal carbon network surface. Graphite particles with highly modified surface structures were prepared by controlling the particle size, heat treatment temperature, and amorphous carbon coating. Electrochemical evaluation revealed significant differences in charge-transfer resistance, an indicator of edge planes. The edge plane determination results obtained using conventional methods such as X-ray diffractometry and Raman spectroscopy did not correlate well with charge-transfer resistance. Meanwhile, Kr adsorption measurements revealed that the stepwise adsorption behavior, because of the interaction of Kr with the energetically homogenous surface, varied significantly depending on the surface properties of graphite particles. The number of edge planes estimated by gas adsorption strongly correlated with charge-transfer resistance. Consequently, we determined that the graphite edge plane tied to the electrochemical index can be derived using gas adsorption analysis. This edge plane determination technique would be applicable not only to graphite but also to highly crystalline carbon materials with an exposed hexagonal carbon network surface.

EIS Behavior of Polyethylene + Graphite Composite Considered as an Approximation to an Ensemble of Microelectrodes

The electrical percolation of alternating current through two-phase polyethylene/graphite composite electrodes with different contents of graphite microparticles immersed in aqueous KCl solutions has been studied. Above the graphite content of the first percolation threshold, the electrochemical impedance response of this electrode is associated with an equivalent circuit of resistance Ru in series with a constant phase element (CPE). An insulator material + conducting filler model is proposed in which the electroactive surface is considered as the intersection of the percolation cluster through the solid and the cluster associated with the interfacial region. CPE is analyzed assuming a distribution of microcapacitors of the graphite particles in contact with the dielectric solution and inside the dielectric polymeric phase.

Investigation on spectroscopy characteristics of different metamorphic degrees of coal-based graphite

To gain insights into the spectroscopy characteristics from coal to graphite, we investigated different metamorphic degrees of coal-based graphite which were collected from Hunan Province China. In this paper, by means of X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and Raman spectroscopy, graphite with different metamorphism degrees has been characterized to explore the evolution of macromolecular structure of organic matter during graphitization. The results show that with the increase of metamorphism degree, the 002-diffraction peak of the series of samples gradually shrinks and narrows, and the peak intensity becomes stronger, indicating that the microcrystalline structure gradually becomes regular and ordered. As the degree of graphitization increase, the uniformity of particle size in coal samples observed gradually increases, and the morphology becomes more regular, transitioning from disordered and irregular shapes to a structured large-scale flake pattern. The crystallinity improves, and the massive coal particles gradually coalesce into large plate crystals, with the inter-particle pores gradually closing. The graphite structure becomes increasingly evident. The FTIR spectra show that as the degree of graphitization increases, the peak at 1,581 cm−1 corresponding to C=C vibrations gradually intensifies. Some inert functional groups are retained throughout the graphitization process. The pores between coal particles gradually close, and the morphology of graphite particles becomes more regular and ordered. Additionally, during the graphitization process, structures similar to carbon nanotubes may develop. Throughout the structural transformation from coal macromolecules to graphite crystals, the size of the sp2 planar domains in single-layer graphene increases, and the lattice structure of carbon atoms gradually enlarges. These findings contribute to a comprehensive understanding of the properties and characteristics of coal-derived graphite, and can provide theoretical reference and basis for the metallogenic mechanism of coal-derived graphite and the efficient utilization of coal.

Effect of in-situ NbC content on the microstructure and mechanical properties of Ni625 composite coating by laser cladding

To improve the mechanical properties of Ni625 coatings, different contents of Nb powder and Ni-coated graphite particles were added to Ni625 powder for in-situ generation of NbC particles. The effects of different NbC contents on the microstructure, hardness, wear resistance and corrosion resistance of Ni625 coatings were investigated. The results show that the highest XRD phase diffraction peaks of NbC in the coating are obtained with the addition of 15 % (Nb 9.9 %, Ni-coated graphite particles 5.1 %), and the coating exhibits a hardness of 441.9 HV, which is 1.53 times greater than that of the coating with the addition of 0 %. Furthermore, the wear coefficient (μ) of the coating is 0.4804, and the wear volume is 0.0042 mm3, representing a reduction of 23.5 % and 64.1 %, respectively, in comparison to the coating with 0 % additive. However, the coating with an addition of 20 % does not generate more NbC phase, and the hardness and wear resistance are not further improved. The coating with an addition of 10 % has the best corrosion resistance, with a corrosion current density of 2.1829E-10 A/cm2. Further additions do not result in an enhanced corrosion resistance of the coating. Therefore, appropriate amount of in-situ generation of NbC within the Ni625 coating during the laser cladding process can effectively enhance the mechanical properties of the Ni625 coating.

Silver with tribo-chemistry facilitation synergized with graphite particles for enhancing the tribo-performance of PEEK composites

The proactive design of tribo-chemistry at friction interface is an effective way to improve the quality of transfer film. Herein, silver served as an assistant in tribo-chemistry, along with graphite incorporated into the short carbon fiber (SCF)/ polytetrafluoroethylene (PTFE)/poly ether ether ketone (PEEK) composite. The lowest wear rate of 3.5 × 10-7 mm3/Nm was achieved for the composite at a graphite content of 5 wt% and a silver content of 5 wt% (Gr5Ag5) under dry friction condition, primarily benefiting from the synergistic interaction of silver and graphite. The transfer of silver and graphite to the friction interface endowed the transfer film with lubricity and load-bearing ability. Crucially, the oxides generated by silver enhanced the strength of the transfer film, and the tribo-chemical reaction involving Ag could increase the bonding of the transfer film to the metal.

Unveiling the Interplay Between Silicon and Graphite in Composite Anodes for Lithium-Ion Batteries.

Si provides an effective approach to achieving high-energy batteries owing to its high energy density and abundance. However, the poor stability of Si requires buffering with graphite particles when used as anodes. Currently, commercial lithium-ion batteries with Si/graphite composite anodes can provide a high energy density and are expected to replace traditional graphite-based batteries. The different lithium storage properties of Si and graphite lead to different degrees of lithiation and chemical environments for this composite anode, which significantly affects the performance of batteries. Herein, the interplay between Si and graphite in mechanically mixed Si/graphite composite anodes is emphasized, which alters the lithiation sequence of the active materials and thus the cycling performance of the battery. Furthermore, performance optimization can be achieved by changing the intrinsic properties of the active materials and external operating conditions, which are summarized and explained in detail. The investigation of the interplay based on Si/graphite composite anodes lays the foundation for developing long-life and high-energy batteries. The abovementioned experimental methods provide logical guidance for future research on composite electrodes with multiple active materials.

Effect of Mechanical Pressure on Rate Capability, Lifetime, and Expansion in Multilayer Pouch Cells with Silicon-Dominant Anodes

Microscale silicon particles have a higher specific capacity but larger volume expansion than graphite particles, leading to particle decoupling and lifetime limitations. This study investigates a wide range of external mechanical pressures from zero (ZP - 0.00 MPa) to high (HP - 0.50 MPa) pressure to determine the optimal pressure for high rate capability, cyclic lifetime, energy density, low temperature rise, and low cell thickness gain. The cells are characterized by rate tests and impedance spectroscopy, and are aged until 70% state of health (SoH). The post-mortem analysis after 70% SoH and thickness measurements over 360 cycles in a compression test bench offer insights into the thickness gain. Electrochemical results reveal an immediate reduction in discharge capacity upon transitioning from normal pressure (NP - 0.20 MPa) to ZP, with NP and HP exhibiting superior performance over aging. The impedance was reduced initially and over aging for higher mechanical pressures, especially the cathode contact resistance, resulting in lower temperature rises during the rate tests. Overall, applying higher pressures reduced the anode and cell thickness gain. Moreover, the porosity decreased with increasing pressure, as determined by mercury intrusion porosimetry and pycnometer measurements. The increase of the anode mass correlates to the total charge throughput, which is pressure-dependent and the highest for NP.

Microfluidic Shape Analysis of Non-spherical Graphite for Li-Ion Batteries via Viscoelastic Particle Focusing.

The size and shape of graphite, which is a popular active anode material for lithium-ion batteries (LIBs), significantly affect the electrochemical performance of LIBs and the rheological properties of the electrode slurries used in battery manufacturing. However, the accurate characterization of its size and shape remains challenging. In this study, the edge plane of graphite in a cross-slot microchannel via viscoelastic particle focusing is characterized. It is reported that the graphite particles are aligned in a direction that shows the edge plane by a planar extensional flow field at the stagnation point of the cross-slot region. Accurate quantification of the edge size and shape for both spheroidized natural and ball-milled graphite is achieved when aligned in this manner. Ball-milled graphite has a smaller circularity and higher aspect ratio than natural graphite, indicating a more plate-like shape. The effects of these differences in graphite shape and size on the rheological properties of the electrode slurry, the structure of the coated electrodes, and electrochemical performance are investigated. This method can contribute to the quality control of graphite for the mass production of LIBs and enhance the electrochemical performance of LIBs.

Optimization of tribological properties and corrosion resistance of MAO coatings on LY12 aluminum alloy by co-doping with graphite particles and in situ formation of zinc phosphate

Micro-arc oxidation (MAO) coatings can enhance the wear and corrosion resistance of aluminum alloys, but the high coefficient of friction and surface pores can lead to failure in the field. In this study, zinc acetate and graphite particles are introduced to the electrolyte to form corrosion-resistant and lubricating MAO coatings on the LY12 aluminum alloy. Zinc phosphate nanocrystals formed in situ are uniformly distributed in the amorphous coating, while the extrinsic graphite is mainly located in the amorphous structure. Compared to the aluminum alloy substrate, the friction coefficient of the optimal MAO coating decreases to ∼0.2, and the wear rate decreases by nearly 10 times. Zinc phosphate nanocrystals generated in situ in the coatings release Zn2+ during corrosion attack to cover the vulnerable weak corrosion areas around the pores. The corrosion resistance is improved significantly, as manifested by the increase of the corrosion potential from −1.290 V to −0.811 V and the decrease of the corrosion current density from 3.172 × 10−6 A cm−2 to 4.320 × 10−10 A cm−2. The co-doped MAO coatings have better wear and corrosion resistance and are more suitable than the LY12 alloy in many engineering applications.

Classification of Cast Iron Alloys through Convolutional Neural Networks Applied on Optical Microscopy Images

Classification of cast iron alloys based on graphite morphology plays a crucial role in materials science and engineering. Traditionally, this classification has relied on visual analysis, a method that is not only time‐consuming but also suffers from subjectivity, leading to inconsistencies. This study introduces a novel approach utilizing convolutional neural networks—MobileNet for image classification and U‐Net for semantic segmentation—to automate the classification process of cast iron alloys. A significant challenge in this domain is the limited availability of diverse and comprehensive datasets necessary for training effective machine learning models. This is addressed by generating a synthetic dataset, creating a rich collection of 2400 pure and 1500 mixed images based on the ISO 945‐1:2019 standard. This ensures a robust training process, enhancing the model's ability to generalize across various morphologies of graphite particles. The findings showcase a remarkable accuracy in classifying cast iron alloys (achieving an overall accuracy of 98.9 ± 0.4%—and exceeding 97% for all six classes—for classification of pure images and ranging between 84% and 93% for semantic segmentation of mixed images) and also demonstrate the model's ability to consistently identify and graphite morphology with a level of precision and speed unattainable through manual methods.

Effect of cyclic oxidation temperature on compressive strength of Cu-based brake pad for high-speed train

The cyclic oxidation tests of Cu-based brake pads at temperatures of 25, 300, 400, 500, 550, 600, 650 and 700 °C were conducted to simulate the oxidation of the friction surface under different braking speeds. Furthermore, the effect of cyclic oxidation temperature on the compressive strength was investigated. The results show that the cyclic oxidation process of Cu-based brake pads can be divided into three stages: mild oxidation (≤400 °C), moderate oxidation (500–600 °C) and severe oxidation (≥650 °C). Mild oxidation results in the formation of spherical Cu2O particles. The surface is covered by Cu2O and Fe2O3 nanosheets for moderate oxidation. Severe oxidation is characterized by a continuous thick CuO film, Fe2O3 nanosheets, and eroded graphite particles. The compressive strength and toughness of Cu-based brake pads show a declining trend as the cyclic oxidation temperature rises. The compressive strength of the Cu-based brake pad after oxidized at 700 °C, recorded at 30.56 MPa, is considerably lower than that of the original samples, which was 132.2 MPa. This reduction in compressive strength is attributed to the embrittlement of the metallic matrix and the formation of pores from graphite oxidation.