Carbon Letters最新文献

Graphene materials show great potential in the field of supercapacitors, but their tendency to agglomerate leads to a significant decrease in performance. Herein, manganese dioxide intercalated graphene oxide precursor was prepared using the modified Hummer method. During pyrolysis, manganese dioxide can not only act as a separator to prevent graphene aggregation but also undergo redox reactions with graphene to obtain oxygen-rich mesopore graphene (OMG). Benefiting from the mesoporous structure and abundant oxygen-containing functional groups, the OMG-600 electrode shows a specific capacitance of 248.67 F g⁻¹ at 0.5 A g⁻¹ and good electrochemical stability (92.25% capacitance retention after 10,000 cycles). Moreover, the assembled OMG-600//OMG-600 symmetric supercapacitor delivers an energy density of 17.69 Wh kg⁻¹ and superior electrochemical stabilization in 1 M Na₂SO₄ electrolyte.

The loss of soil available nutrients may affect soil quality and crop growth. Biochar can form a multi-level fixed network because of its rich pore structure and surface functional groups, which can effectively fix available nutrients in soil and maintain nutrient utilization rate. Because it is difficult to directly prepare biochar materials with good adsorption characteristics through experimental results. This study employed an XGBoost machine learning prediction model to determine the optimal nutrient-rich biochar preparation conditions. The R² value ranged from 0.97 to 0.99. The results indicated that specific surface area was the primary factor influencing ammonium nitrogen adsorption, with a feature importance of 56.13%. Production conditions (hydrothermal temperature and time) significantly affected the adsorption of nitrate nitrogen and available phosphorus, with feature importances of 75.91% and 81.54%, respectively. Mean pore diameter was negatively correlated with potassium ion adsorption characteristics. Biochar prepared under hydrothermal conditions at 202.50–251.25 °C for 3 h exhibited favorable adsorption characteristics for multiple soil available nutrients. This study provides new insights into biochar’s application in the field of soil nutrient adsorption through data analysis. It is helpful to avoid the waste in the process of energy utilization from biomass to biochar.

Thermal property represents a critical metric when evaluating the performance of next generation nuclear graphite. Despite the extensive measurement data available, a detailed investigation into the influence of microstructure on graphite’s thermal conductivity remains underexplored. In this work, taking advantage of the distinct microstructures between different graphite grades, a comparative study of four graphite grades was conducted to elucidate the structure–property relationship. The microstructures of graphite were characterized by Raman spectroscopy and X-ray diffraction techniques, demonstrating specimen preparation induced damage and annealing induced restoration. Thermal properties were investigated across multiple scales using laser flash analysis and photothermal radiometry. The results indicate that despite similar densities, thermal conductivity varies significantly between different grades and correlates positively with crystallite sizes. By interpolating an infinitely large crystallite and removing the impact of macroscale porosity, an upper bound for the thermal conductivity of isotropic defect-free nuclear graphite has been established.

Due to the severity of environmental degradation and depletion of natural energy resources, research on sustainable energy storage systems have become quite popular. Supercapacitor is one of the most innovative and promising type of energy storage devices. The effective performance of supercapacitor greatly depends on the electrode material. Therefore, new type of nanocomposite has been fabricated with βCD-stabilized CuO nanoparticles (CuO-βCD NPs) on Co-Al layered double hydroxide (Co-Al LDH) utilizing solvothermal process. The wet impregnation technique facilitates the formation of three distinct CuO-βCD/Co-Al LDH nanocomposites in the ratios of 1:1, 1:2, and 2:1 by promoting the growth of CuO-βCD on Co-Al LDH in corresponding compositions. Synthesized nanocomposites are characterized using a variety of spectroscopic techniques. The average pore size of 2:1 CuO-βCD/Co-Al LDH is 1.7 nm whereas the specific surface area and approximate pore volume of this nanocomposite are 38.306 m² g⁻¹ and 0.043 cm³ g⁻¹, respectively. Electrochemical investigations like cyclic voltammetry (CV), galvanostatic charge–discharge (GCD), electrochemical impedance spectroscopic (EIS) measurements and along with cycle stability studies are performed to examine the electrochemical performance of synthesized nanocomposites. The 2:1 ratio has revealed improved specific capacitance (SC) of 1567 F g⁻¹ at 0.45 A g⁻¹ in 1 M potassium hydroxide medium in three electrode systems and maintains 76% of its original SC even after 5000 cycles. The improved electrochemical performance of 2:1 ratio reveals the appropriateness of this material as an effective electrode for supercapacitor application.

Electrospun nanofibers have emerged as transformative materials due to their unparalleled surface-to-volume ratios, tunable porosity, and excellent mechanical flexibility, making them suitable for energy storage, catalysis, biomedicine, and environmental remediation. However, their inherent surface limitations—poor chemical stability, insufficient active sites, and limited functionality—restrict their full potential. Chemical vapor deposition (CVD) has risen as a game-changing post-synthesis modification strategy, enabling atomic-scale precision in surface engineering. This is also impactful for carbon-based nanofibers, where surface inertness limits their electrochemical performance. This review critically examines advanced CVD techniques, including atomic layer deposition (ALD), plasma-enhanced CVD (PECVD), and initiated CVD (iCVD), which enable the formation of conformal coatings, hierarchical functionalization, carbon nanotube integration, and interfacial optimization of as-spun nanofibers. We highlight breakthroughs in hydrophobicity, catalytic activity, biocompatibility, and energy storage performance, with applications ranging from oil–water separation to nerve gas detoxification, pH-responsive drug delivery, and high-capacity carbon-composite lithium-ion batteries. By dissecting deposition mechanisms, material innovations, and emerging applications, this work highlights the synergy between as-spun nanofibers and the exploitation of CVD techniques in designing versatile materials. Furthermore, advancements hinge on computational modeling, novel precursors, including carbon-rich sources, and scalable processes to bridge lab-scale innovations with industrial deployment are desired. This comprehensive analysis provides a guiding framework for researchers utilizing CVD techniques as a post-modification tool to develop nanofiber-based solutions addressing global challenges in sustainability, healthcare, and energy.

With high redox activity, superior conductivity, abundant pores, and large specific surface area, nitrogen-doped graphitic carbon featuring a hierarchically porous structure is regarded as ideal electrode material for supercapacitors. In this work, hierarchically porous nitrogen-doped graphitic carbon (PG-PZC₅₀) was fabricated via non-solvent induced phase separation and high-temperature calcination processes. SEM images showed its three-dimensional network structure, with abundant macro- and mesopores distributed throughout. XRD and Raman spectra confirmed the phase purity and graphitic nature of the as-prepared material, while XPS revealed its surface elemental composition, especially the content and doping states of nitrogen atoms. The graphene oxide-induced three-dimensional network, combined with the mesoporous structure of metal-organic framework-derived N-doped carbon particles, creates abundant migration channels and a large adsorption surface area for the electrolyte ions. Benefiting from its hierarchically porous structure and high nitrogen-doping content, the formed PG-PZC₅₀ reached high specific capacitances of 499.7 F g⁻¹ at 0.1 A g⁻¹ and 179.6 F g⁻¹ at 20 A g⁻¹. Notably, the material also demonstrated robust cyclic stability with no capacitance loss after 10,000 charge–discharge cycles. The proposed synthetic strategy provides new ideas for the facile and reproducible construction of nitrogen-doped graphitic carbon with 3D hierarchically porous structure and high capacitive performances.

The ZnCl₂ chemical activation method is widely employed for the preparation of biomass-derived porous carbons. In most of the related studies, the emphasis lies on investigating how experimental preparation conditions impact the performance of the final products. However, the performance of the porous carbon also depends on the chemical structure of the carbon source. In this study, we used alkali lignin, ammoxidized lignin and sodium lignosulfonate as carbon sources to prepare porous carbon through ZnCl₂ activation. The influence of the chemical structures of lignin on the activation process is explored. The porous carbons prepared from alkali lignin (ALC) and ammoxidized lignin (AOLC) both exhibit similar and relatively high specific surface areas (ALC: 1164 m² g⁻¹, AOLC: 1156 m² g⁻¹) and capacitance contribution ratios (ALC: 80.6%, AOLC: 79.4%). The porous carbon prepared from sodium lignosulfonate has a specific surface area of 890 m² g⁻¹ and a mesopore ratio of 26.1%, with the capacitance contribution accounting for only 75.1%. ZnS and NaCl generated during the activation process involving sodium lignosulfonate can partially enable mesopores by template effect, which in turn results in lower electrochemical properties. This study explores the reasons for the differences in ZnCl₂ activation on different lignins, providing data to support research on the mechanism of how lignin structure influences ZnCl₂ activation.

Laser-induced graphene (LIG) has emerged as a promising carbon nanomaterial platform owing to its scalability and tunable surface properties. Although its electrical and structural characteristics have been widely explored, the precise modulation of the surface energy remains challenging, particularly in ultrathin configurations. In this study, we investigated the wetting behavior of an ultrathin LIG synthesized from a fluorinated polyimide (F-PI) thin-film precursor using ultraviolet (UV) laser irradiation. Systematic variations in laser exposure induced morphologic transitions from hierarchical porous networks to compact planar structures, accompanied by changes in the chemical composition, including fluorine depletion and oxygen incorporation. These combined effects result in a broad range of wetting behaviors, including superhydrophobicity and hydrophilicity. Remarkably, LIG produced under single irradiation exhibited a rose-petal-like wetting state characterized by a high contact angle and strong droplet adhesion, a phenomenon not previously reported in LIG systems. This work elucidates the interplay between laser-induced nanostructuring and surface chemistry in governing wetting behavior and establishes a controllable strategy for fabricating functional carbon surfaces for applications in microfluidics, selective adhesion, and water-repellent coating technologies.

The mixed-ion electron conductor, Ag₂Se, has shown strong potential as a thermoelectric material operating near room temperature. In this study, we demonstrate that the incorporation of polyaniline (PANI) into Ag₂Se forms Ag₂Se/PANI nanocomposites with significantly enhanced thermoelectric performances. Ag₂Se was synthesized using a hydrothermal method followed by hot pressing to obtain dense composite pellets. The novelty of this work lies in the systematic tuning of the PANI content and its dual role in enhancing electrical transport while suppressing lattice thermal conductivity. Microstructural analysis reveals that PANI-induced defects, such as dislocations and point defects, effectively scatter phonons at multiple scales, resulting in a remarkably low lattice thermal conductivity (κₗ ≈ 0.08 Wm⁻¹ K⁻¹) at 393 K. Simultaneously, PANI improves carrier mobility by modifying the Coulomb potential at grain boundaries, reducing interfacial energy barriers. These effects lead to an improved power factor of 2028 μWm⁻¹ K⁻² and a peak figure of merit (zT ≈ 0.67) at 393 K for the 0.5 wt% PANI sample. This study introduces a novel polymer-assisted interface engineering approach to improve the thermoelectric performance of Ag₂Se-based materials.

Carbon nanotube (CNT) has promising applications in several fields due to their excellent thermal, electrical, mechanical, and biocompatible properties. However, the complexity of its structure leads to the problems of computationally intensive and inefficient synthetic characterization optimization and prediction by traditional research methods, which seriously restricts the development process. Machine learning (ML), as an emerging technology, has been widely used in CNT research due to its ability to reduce computational cost, shorten the development cycle, and improve the accuracy. ML not only optimizes the synthetic control parameters for precise structural control, but also combines various imaging and spectroscopic techniques to significantly improve the accuracy and efficiency of characterization. In addition, ML helps to improve the performance of CNT devices at the optimization and prediction levels, and achieve accurate performance prediction. However, ML in CNT research still faces challenges such as algorithmic processing of complex data situations, insufficient space for algorithmic combined optimization, and lack of model interpretability. Future research can focus on developing more efficient ML algorithms and unified standardized databases, exploring the deep integration of different algorithms, further improving the performance of ML in CNT research, and promoting its application in more fields.