Search Results (645)

In most commercial lithium-ion batteries, graphite remains the primary anode material. However, its theoretical specific capacity is only 372 mAh∙g⁻¹, which falls short of meeting the demands of high-performance electronic devices. Silicon anodes, despite boasting an ultra-high theoretical specific capacity of 4200 mAh∙g⁻¹, suffer from significant volume expansion (>300%) during cycling, leading to severe capacity fade and limiting their commercial viability. Currently, silicon-based polymer-derived ceramics have emerged as a highly promising next-generation anode material for lithium-ion batteries, thanks to their unique nano-cluster structure, tunable composition, and low volume expansion characteristics. The maximum capacity of the ceramics can exceed 1000 mAh∙g⁻¹, and their unique synthesis routes enable customization to align with diverse electrochemical application requirements. In this paper, we present the progress of silicon oxycarbide (SiOC), silicon carbonitride (SiCN), silicon boron carbonitride (SiBCN) and silicon oxycarbonitride (SiOCN) in the field of LIBs, including their synthesis, structural characteristics and electrochemical properties, etc. The mechanisms of lithium-ion storage in the Si-based anode materials are summarized as well, including the key role of free carbon in these materials. Full article

The efficient depolymerization of lignin has become a key challenge in the preparation of high-value-added chemicals. Graphitic carbon nitride (g-C₃N₄)-based photocatalytic system shows potential due to its mild and green characteristics over other depolymerization methods. However, its inherent defects, such as a wide band gap and rapid carrier recombination, severely limit its catalytic performance. In this paper, a g-C₃N₄ modification strategy of K⁺ doping and surface alkalinization is proposed, which is firstly applied to the photocatalytic depolymerization of the lignin β-O-4 model compound (2-phenoxy-1-phenylethanol). K⁺ doping is achieved by introducing KCl in the precursor thermal polymerization stage to weaken the edge structure strength of g-C₃N₄, and post-treatment with KOH solution is combined to optimize the surface basic groups. The structural/compositional evolution of the materials was analyzed by XRD, FTIR, and XPS. The morphology/element distribution was visualized by SEM-EDS, and the optoelectronic properties were evaluated by UV–vis DRS, PL, EIS, and transient photocurrent (TPC). K⁺ doping and surface alkalinization synergistically regulate the layered structure of the material, significantly increase the specific surface area, introduce nitrogen vacancies and hydroxyl functional groups, effectively narrow the band gap (optimized to 2.35 eV), and inhibit the recombination of photogenerated carriers by forming electron capture centers. Photocatalytic experiments show that the alkalinized g-C₃N₄ can completely depolymerize 2-phenoxy-1-phenylethanol with tunable product selectivity. By adjusting reaction time and catalyst dosage, the dominant product can be shifted from benzaldehyde (up to 77.28% selectivity) to benzoic acid, demonstrating precise control over oxidation degree. Mechanistic analysis shows that the surface alkaline sites synergistically optimize the C_β-O bond breakage path by enhancing substrate adsorption and promoting the generation of active oxygen species (·OH, ·O₂⁻). This study provides a new idea for the efficient photocatalytic depolymerization of lignin and lays an experimental foundation for the interface engineering and band regulation strategies of g-C₃N₄-based catalysts. Full article

MXenes, a family of two-dimensional carbide and nitride nanomaterials, have demonstrated significant promise across various technological domains, particularly in energy storage applications. This review critically examines scalable synthesis techniques for MXenes and their potential integration into next-generation rechargeable battery systems. We highlight both top-down and emerging bottom-up approaches, exploring their respective efficiencies, environmental impacts, and industrial feasibility. The paper further discusses the electrochemical behavior of MXenes in lithium-ion, sodium-ion, and aluminum-ion batteries, as well as their multifunctional roles in solid-state batteries—including as electrodes, additives, and solid electrolytes. Special emphasis is placed on surface functionalization, interlayer engineering, and ion transport properties. We also compare MXenes with conventional graphite anodes, analyzing their gravimetric and volumetric performance potential. Finally, challenges such as diffusion kinetics, power density limitations, and scalability are addressed, providing a comprehensive outlook on the future of MXenes in sustainable energy storage technologies. Full article

Accurate prediction of the State of Health (SOH) of lithium-ion batteries is essential for ensuring their safe and reliable operation. However, traditional deep learning approaches often suffer from challenges such as overfitting, limited generalization capability, and suboptimal prediction accuracy. To address these issues, this paper proposes a novel framework that combines a Long Short-Term Memory (LSTM) network with a Physics-Informed Neural Network (PINN), referred to as LSTM-PINN, for high-precision SOH estimation. The proposed framework models battery degradation using state-space equations and extracts latent temporal features. These features are further integrated into a Deep Hidden Temporal Physical Module (DeepHTPM), which incorporates physical prior knowledge into the learning process. This integration significantly enhances the model’s ability to accurately capture the complex dynamics of battery degradation. The effectiveness of LSTM-PINN is validated using two publicly available datasets based on graphite cathode materials (NASA and CACLE). Extensive experimental results demonstrate the superior predictive performance of the proposed model, achieving Mean Absolute Errors (MAEs) of just 0.594% and 0.746% and Root Mean Square Errors (RMSEs) of 0.791% and 0.897% on the respective datasets. Our proposed LSTM-PINN framework enables accurate battery aging modeling, advancing lithium-ion battery SOH prediction for industrial applications. Full article

Graphite carbon nitride (g-C₃N₄) is a low band gap non-metallic polymer semiconductor that has broad application prospects and is an ideal material for absorbing visible light, as g-C₃N₄ materials have strong oxidation properties and are easy to modify. The structure formation of g-C₃N₄-based materials makes a series of photocatalytic synthesis reactions possible and improves photocatalytic reaction activity. In this paper, the development history, structures, and performance of g-C₃N₄ are briefly introduced, and the modification strategies of g-C₃N₄ are summarized to improve its photocatalytic and photoelectric catalytic properties via doping, heterojunction construction, etc. The light absorption and utilization of the catalysts are also analyzed in terms of light source conditions, and the application of g-C₃N₄ and its modified materials in photocatalysis and photocatalytic degradation is reviewed. Full article

This paper presents a comparative study examining the effects of carbon nanotubes (CNTs) and expanded graphite (EG) on the thermal, mechanical, morphological, electrical, and piezoresistive properties of poly(ethylene-co-methacrylic acid) (EMAA) nanocomposites. To this end, different amounts of carbonaceous fillers (EG and CNTs separately) were added to the EMAA thermoplastic matrix, and the relative electrical percolation thresholds (EPTs) were determined. The effect of filler concentration on thermo-oxidative degradation and the EMAA crystallinity was investigated via thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), respectively. Dynamic mechanical analysis (DMA) demonstrated that both fillers enhance the Young’s and storage moduli, as well as the glass transition temperature, with a greater improvement for the bidimensional nanofiller, most likely due to the cumulative effect of more extensive EG-matrix interactions. In tensile tests, a very relevant difference was detected in the Gauge Factor (G.F.) and the elongation at break of the two typologies of nanocomposites. The G.F. of EMAA 10% CNT and EMAA 15% EG were found to be 0.5 ± 0.08 and 165 ± 14, respectively, while elongation at break was about 68% for EMAA 10% CNT and 8% for EMAA 15% EG. Emission Scanning Electron Microscopy (FESEM) and Tunneling Atomic Force Microscopy (TUNA) have contributed to explaining the differences between EG- and CNT-based nanocomposites from a morphological point of view, underlying the pivotal role of the filler aspect ratio and its structural features in determining different mechanical and piezoresistive performance. The comprehensive analysis of EMAA-EG and EMAA-CNT nanocomposites provides a guide for selecting the best self-sensing system for the specific application. More specifically, EMAA-CNT nanocomposites with high elongation at break and lower sensitivity to small strains are suitable for movement sensors in the soft robotic field, where high deformation has to be detected. On the other hand, the high sensitivity at a low strain of EMAA-EG systems makes them suitable for integrated sensors in more rigid composite structures, such as aeronautical and automotive components or wind turbines. Full article

In the methylation of pseudocumene with methanol over IM-5 zeolite, the yield of durene can be enhanced. However, poorer stability of the catalytic activity was observed, especially at a higher methanol/pseudocumene ratio. In this paper, conventional characterization methods (XRD, XRF, TGA, SEM, physical adsorption, OH-IR, NH₃-TPD, and Py-IR) were used to characterize fresh and deactivated IM-5 zeolite and ZSM-5. FT-IR, XPS, TG-MS, GC-MS, FT-ICR MS, and NMR were employed to characterize deactivated IM-5 zeolite. It was found that the deactivation of IM-5 zeolite was mainly due to the severe coverage of acidic sites and pore channels by carbon deposits. The carbon deposits within the internal surface had a higher abundance, mainly in the form of linear unsaturated chain-like structures with a high degree of unsaturation. The carbon deposits on the external surface were mainly polycyclic aromatic hydrocarbons with alkyl side chains and a high degree of saturation, accompanied by unreacted methanol. Moreover, graphitized carbon existed on both the internal and external surfaces, which made the conventional coke-burning regeneration method unable to restore the activity of the post-reaction IM-5 zeolite. This work had certain reference significance for modulating the acidity and pore channels of zeolite catalysts, thus improving the activity and stability of the catalysts and extending their service life. Full article

The possibility of reinforcing polymeric matrices with multifunctional fillers for improving structural and functional properties is widely exploited. The compatibility between the filler and the polymeric matrix is crucial, especially for high filler content. In this paper, polymeric matrices of Nylon 6,6 with pyrene chains were successfully synthesized to improve the compatibility with carbonaceous fillers. The compatibility was proven using graphite as a carbonaceous filler. The different properties, including thermal stability, crystallinity, morphology, and local mechanical properties, have been evaluated for various filler contents, and the results have been compared to those of synthetic Nylon 6,6 without pyrene chain terminals. XRD results highlighted that the compatibilization of the composite matrix may lead to an intercalation of the polymeric chains among the graphite layers. This phenomenon leads to the protection of the polymer from thermal degradation, as highlighted by the thermogravimetric analysis (i.e., for a filler content of 20%, the beginning degradation temperature goes from 357 °C for the non-compatibilized matrix to 401 °C for the compatibilized one and the residual at 750 °C goes from 33% to 67%, respectively. A significant improvement in the interphase properties, as proven via Atomic Force Microscopy in Harmonix mode, leads to a considerable increase in local mechanical modulus values. Specifically, the compatibilization of the matrix hosting the graphite leads to a less pronounced difference in modulus values, with more frequent reinforcements that are quantitatively similar along the sample surface. This results from a significantly improved filler distribution with respect to the composite with the non-compatibilized matrix. The present study shows how the thermoplastic/filler compatibilization can sensitively enhance thermal and mechanical properties of the thermoplastic composite, widening its potential use for various high-performance applications, such as in the transport field, e.g., for automotive components (engine parts, gears, bushings, washers), and electrical and electronics applications (heat sinks, casing for electronic devices, and insulating materials). Full article

Efficient identification and removal of low-grade minerals during graphite ore processing is essential for improving product quality, optimizing resource recovery, and promoting sustainable production. To address the limitations of traditional sorting methods and performance bottlenecks in edge devices, this paper proposes a lightweight instance segmentation model, GS-YOLO-seg, for rapid identification and intelligent sorting of low-grade graphite ore in industrial production lines. The model first reduces network depth by adjusting the depth factor. Subsequently, the backbone network adopts the lightweight and efficient GSConv to perform downsampling, while a novel C3k2-Faster architecture is proposed to improve the effectiveness of feature extraction. Finally, the Segment-Efficient segmentation head is optimized to reduce redundant computations, further lowering the model load. On a self-constructed graphite ore image dataset, GS-YOLO-seg achieved comparable segmentation performance to the baseline YOLO11n-seg, while achieving a 30% reduction in FLOPs, 59% fewer parameters, 56% smaller model size, and 8% higher FPS. This method enhances the intelligence of the sorting process, preventing low-grade ores from entering subsequent stages, thus reducing resource waste, energy consumption, and carbon emissions, providing crucial technical support and feasible deployment pathways for building intelligent, green, and sustainable mining systems. Full article

Past studies have offered insights into how graphite-derived graphene oxide (GDGO) can improve the mechanical properties and alter microstructural characteristics of concrete. These advantages can significantly impact the construction industry regarding cost, sustainability, and efficiency. However, the high cost of GDGO can make commercial implementation unattainable. This paper comprehensively investigates coal-derived GO as a cost-saving alternative to commercial GDGO while achieving comparable concrete performance. Different GO proportions were incorporated into concrete mixes through laboratory experiments to determine the effect on mechanical properties and microstructures. In this research, concrete mixes were formulated by replacing a portion of cement with coal-derived GO and adding this GO as an additive to concrete at varying percentages (0.05%, 0.10%, 0.25%, 0.50%, 1%, and 1.5% by weight of cement). The study revealed flexural, split tensile, and compressive strength improvements of 3.3%, 2.3%, and 21.2%, respectively, at a minimal 0.05 wt.% GO replacement. Optimal inclusions of GO as an additive ranging from 0.05 to 0.25 wt.% were identified to exhibit a maximum increase in mechanical properties. More precisely, adding 0.10 weight percent of GO as an additive to concrete showed increases in flexural, split tensile, and compressive strengths of 14.05%, 9.7%, and 34.2%, respectively. Furthermore, detailed analyses, including modulus of elasticity, Poisson’s ratio, heat of hydration, and microstructural analysis provided comprehensive insights into the enhanced mechanical performance of GO-incorporated concrete. Additionally, the study revealed a lower Ca/Si ratio in GO concrete, further validating the reinforcing properties of the GO. Full article

The primary challenge associated with stainless steel in fuel cell operation is its susceptibility to corrosion, which leads to increased contact resistance and subsequent degradation of electrochemical performance. In general, the protective layers have been loaded onto the metal surface by widely used traditional techniques such as physical vapor deposition (PVD), or cathode arc ion plating. However, the above sputtering and evaporation ways require a high-vacuum condition, complicated experimental setups, higher costs, and an elevated temperature. Therefore, herein the achievement for uniform coatings over a large surface area has been realized by using a cost-effective strategy through a complete wet chemical process. The synergistic regulation of two conductive components and a plastic additive has been employed together with the entrapment of a surfactant to optimize the microstructure of the coating surface. The assembly of layered graphite and a polystyrene sphere could maintain both the high corrosion resistance feature and excellent electrical conductivity. In particular, the intrinsic vacant space in the above physical barriers has been filled with fine powders of indium tin oxide (ITO) due to its small size, and the interconnected conductive network with vertical/horizontal directions would be formed. All the key technical targets based on the U.S. Department of Energy (DOE) have been achieved under the simulated operating environments of a proton exchange membrane fuel cell. The corrosion current density has been measured as low as 0.52 μA/cm² (for the sample of graphite/mixed layer) over the applied potentials from −0.6 V to 1.2 V and its protective efficiency is evaluated to be 99.8%. The interfacial contact resistance between the sample and the carbon paper is much less than 10 mΩ·cm² (3.4 mΩ·cm²) under a contact pressure of 165 N/cm². The wettability has been investigated and its contact angle has been evolved from 48° (uncoated sample) to even 110°, providing superior hydrophobicity to prevent water penetration. Such an innovative approach opens up new possibilities for improving the durability and reducing the costs of carbon-based coatings. Full article

The current economic growth and increasing needs of society have led to developing processes that harm our environment and have severe long-term consequences. For this reason, different attempts have been made to mitigate these effects by substituting conventional toxic materials with environmentally friendly ones. Industry sectors related to energy storage, printed electronics, and wearable technology are moving towards applying sustainable strategies. Renewable biopolymers such as cellulose and its derivatives, as well as carbon-based alternatives, which include carbon nanotubes (CNTs), single-wall carbon nanotubes (SWCNTs), graphite, graphene, and carbon black (CB), are leading the advances in this field. The present research aimed to develop conductive cellulose paper using environmentally friendly components compatible with the paper recycling process. Coating formulations based on carbon black were proposed using three different types of binders: polytetrafluoroethylene (PTFE), latex (styrene butadiene), and sodium carboxymethyl cellulose (CMC). The formulation, composition, and preparation were studied, and they were related to the coating’s electrical resistance and integrity. This last parameter was determined through a new method described in this research, implementing a mechanical/optical technique to measure the coating’s durability. The formulation with the best performance in terms of electrical resistance (0.29 kΩ), integrity, and non-toxicity was obtained using sodium carboxymethyl cellulose (CMC) as a binder and dispersant. Full article

The paper presents the effect of the symmetric and asymmetric semi-metallic gasket core shape on the tightness level in bolted flange joints. Experimental tests, as well as numerical calculations based on the finite element method, revealed that the asymmetric gasket core provides a higher strain on the sealing graphite layer and leads to a more uniform distribution of strain on the particular ridges of the core. Furthermore, the leakage rate of the asymmetric gasket was reduced by approximately 60% compared to the symmetric gasket. It was also observed that the uniformity of pressure and strain distribution in a gasket with an asymmetric core occurs over about 80% of the gasket width. The leakage reduction effect in a flange joint sealed with a gasket with an asymmetric core was theoretically explained. As shown, the main leakage flows through the porous structure of the graphite layer, while the leakage path at the interface between the metal rough profile and the graphite layer is several orders of magnitude smaller. Full article

Printed electronics employ established printing methods to create low-cost, mechanically flexible devices including batteries, supercapacitors, sensors, antennas and RFID tags on plastic, paper and textile substrates. This review focuses on the specific contribution of screen printing to that landscape, examining how ink viscosity, mesh selection and squeegee dynamics govern film uniformity, pattern resolution and ultimately device performance. Recent progress in advanced ink systems is surveyed, highlighting carbon allotropes (graphene, carbon nano-onions, carbon nanotubes, graphite), silver and copper nanostructures, MXene and functional oxides that collectively enhance mechanical robustness, electrical conductivity and radio-frequency behavior. Parallel improvements in substrate engineering such as polyimide, PET, TPU, cellulose and elastomers demonstrate the technique’s capacity to accommodate complex geometries for wearable, medical and industrial applications while supporting environmentally responsible material choices such as water-borne binders and bio-based solvents. By mapping two decades of developments across energy-storage layers and functional electronics, the article identifies the key process elements, recurring challenges and emerging sustainable practices that will guide future optimization of screen-printing materials and protocols for high-performance, customizable and eco-friendly flexible devices. Full article

Lithium-ion batteries (LIBs) are widely used in diverse applications, ranging from portable ones to stationary ones. The appropriate handling of the immense amount of spent batteries has, therefore, become significant. Whether recycled or repurposed for second-life applications, knowing their chemistry type can lead to higher efficiency. In this paper, we propose a novel machine learning-based approach for accurate chemistry identification of the electrode materials in LIBs based on their temperature dynamics under constant current cycling using gated recurrent unit (GRU) networks. Three different chemistry types, namely lithium nickel cobalt aluminium oxide cathode with silicon-doped graphite anode (NCA-GS), nickel cobalt aluminium oxide cathode with graphite anode (NCA-G), and lithium nickel manganese cobalt oxide cathode with graphite anode (NMC-G), were examined under four conditions, 0.2 C charge, 0.2 C discharge, 1 C charge, and 1 C discharge. Experimental results showed that the unique characteristics in the surface temperature measurement during the full charge or discharge of the different chemistry types can accurately carry out the classification task in both experimental setups, where the model is trained on data under different cycling conditions separately and jointly. Furthermore, experimental results show that the proposed approach for chemistry type identification based on temperature dynamics appears to be more universal than voltage characteristics. As the proposed approach has proven to be efficient in the chemistry identification of the electrode materials LIBs in most cases, we believe it can greatly benefit the recycling and second-life application of spent LIBs in real-life applications. Full article