Search Results (452)

A charge-balanced aqueous hybrid supercapacitor was constructed by coupling Co-modified MnWO₄ nanorods with H₂O₂-treated carbon nanotubes (OH-CNTs) in 1 M KOH. The samples were designated by the nominal Co/(Mn + Co) precursor molar fraction; ICP-OES measured bulk Co fractions of 0.09 ± 0.01, 0.47 ± 0.03, and 0.75 ± 0.04 mol% for the nominal 0.1, 0.5, and 0.8 mol% samples, respectively. Rietveld refinement confirmed retention of the monoclinic P2/c MnWO₄ phase with only small composition-dependent lattice changes. At an active-material loading of 2.00 ± 0.05 mg cm⁻², the optimized nominal 0.5 mol% sample delivered 429.5 ± 11.0 C g⁻¹ (119.3 ± 3.1 mAh g⁻¹) at 1 A g⁻¹ and retained 280.5 ± 8.5 C g⁻¹ (77.9 ± 2.4 mAh g⁻¹) at 15 A g⁻¹. Because the positive electrode exhibits battery-type behavior, specific charge and specific capacity are used as the primary performance descriptors. Over −0.9–0 V vs. SCE, pristine CNT and OH-CNT electrodes delivered of 189.0 ± 7.2 and 246.6 ± 8.1 C g⁻¹, corresponding to electrode-level apparent specific capacitances of 215 ± 8 and 280 ± 9 F g⁻¹ at 1 A g⁻¹ after correction for the measured IR drop. These values apply to the stated 90:5:5 CNT (or OH-CNT)/acetylene-black/PVDF formulation and CNT-active-mass normalization and should not be interpreted as intrinsic capacitances of isolated commercial MWCNT powders. Charge matching based on the measured gave m⁺/m⁻ = 0.574; integration at the actual device loadings yielded q⁺ = 0.861 ± 0.015 C and q⁻ = 0.854 ± 0.015 C (q⁺/q⁻ = 1.008). The device operated over 0–1.6 V and delivered 97.9 ± 3.1 F g⁻¹ at 0.51 A g⁻¹, corresponding to 34.8 Wh kg⁻¹ at 408 W kg⁻¹ when normalized to the combined active mass of both electrodes. Three independently assembled devices retained 96.0 ± 0.7% of the initial capacitance and showed a coulombic efficiency of 98.8 ± 0.1% at the 10,000th cycle at 5.13 A g⁻¹. Device metrics are normalized to the combined active mass of both electrodes and exclude current collectors, separator, electrolyte, and packaging. Full article

Thermally sprayed metallic coatings on carbon fiber-reinforced polymer (CFRP) substrates often contain pores and microstructural defects that can reduce adhesion, durability, and protective performance. In this study, a hybrid graphene nanoplatelet (GNP)-fullerene C60 reinforced epoxy coating was applied to HVOF-metallized CFRP, while a carbon nanotube (CNT)-based surface treatment was used to modify surface wettability. Micro-CT and SEM analyses indicated morphological changes consistent with partial coverage of accessible surface-connected defects and modification of the metallized layer surface. Pull-off adhesion strength increased from 320 psi to 650 psi, accompanied by a shift from adhesive to cohesive failure. The optimal nanofiller formulation improved tensile strength from approximately 25 MPa to 56 MPa (124%) and Young’s modulus by approximately 47% compared with neat epoxy. Abrasion testing showed more than 50% reduction in mass loss, and electrochemical impedance spectroscopy indicated improved barrier performance after 200 h of salt spray exposure. CNT surface modification transformed the coating from hydrophilic to superhydrophobic behavior, achieving water contact angles above 155°, delaying ice formation, and reducing ice accumulation. These results indicate that combining hybrid nanocomposite coatings with CNT functionalization can improve mechanical, protective, and surface-functional performance of HVOF-metallized CFRP systems under the laboratory conditions investigated. Full article

Environmental impacts of wastewater from textile and dyestuff industries are of growing concern due to limited freshwater availability and inadequate treatment facilities. Carbon nanotubes (CNTs) offer excellent adsorption potential because of their outstanding mechanical and chemical properties, however; their application in textile effluent treatment has not been widely studied. Moreover, laboratory-based studies are often costly and limited to a few variables, making it challenging to reveal the underlying relationships among several physicochemical parameters and CNT treatments. Multivariate statistical analysis (MVSA) offers an effective approach to overcome this challenge. To the best of our knowledge, no studies have integrated laboratory analysis of nanotube-based textile effluent treatment with an MVSA approach. This study aims to evaluate the physicochemical characterization of textile effluent, treat effluent with CNT, and explore the relationship between physicochemical parameters and CNT by integrating laboratory experiments with MVSA. For this purpose, single-walled CNT (SWCNT) and multi-walled CNT (MWCNT) were applied in batch mode adsorption experiments using various dosages and adsorption times. Scanning electron microscopy and Fourier transform infrared spectroscopy (FTIR), along with physicochemical analyses, were conducted to characterize the effluent and adsorption processes. The FTIR spectrum indicated that the absorption peaks of C=C, C=O, and the acidic f -OH group on CNTs enhance wettability and hydrophilic character, thereby increasing adsorption capacity. Experimental results demonstrated significant reductions in electrical conductivity (EC), total dissolved solids (TDS), turbidity, total organic carbon (TOC), and chemical oxygen demand (COD). CNT dosages of 1 to 5 g/100 mL and adsorption times of 2 to 5 h achieved removal efficiencies ranging from approximately 20% to 90% for SWCNT and MWCNT. MVSA indicated that MWCNT was more strongly associated with ionic and physical parameters (turbidity, TDS, EC, and pH), whereas SWCNT was more strongly related to organic load indicators, particularly COD and TOC. Overall, this study highlights the potential of CNT coupled with the MVSA technique as an effective and sustainable approach for textile wastewater treatment and offers valuable insights for researchers working in this field. Full article

An adsorptive stripping voltammetric method for the determination of ultra trace amounts of Mo(VI) using an electrode based on a mixture of carbon nanotubes and spherical glassy carbon (CNT/SGC) was developed. The electrode was modified by depositing a lead film in situ during each measurement cycle. In a supporting electrolyte containing 0.2 mol/L of acetic buffer pH = 5.3; 0.2 mmol/L of Pb(II); and 0.15 mmol/L of cupferron, the stripping response observed at −0.62 V was proportional to the Mo(VI) concentration within the range of 7 nmol/L to 0.6 µmol/L. The measurement protocol involved a 20 s electrode modification followed by a 30 s adsorption of Mo(VI)–cupferron complexes. The limit of detection was found to be 2.5 nmol/L with a correlation coefficient of 0.997. The method has been applied to the determination of Mo(VI) in mineral water samples. Full article

Carbon nanotube (CNT) networks are promising candidate channel materials for thin-film transistors (TFTs). However, the charge trapping characteristics underlying the gate hysteresis effect still remain unclear. Herein, high-performance CNT TFTs with good consistencies were fabricated to investigate the hysteresis-induced performance variations and the dynamic charge trapping/releasing behaviors at different gate biases. Both the subthreshold and suprathreshold characteristics of the TFTs are remarkably changed under different gate sweeping directions. The origin of gate hysteresis was illustrated by comparing the effects of gas desorption and selective re-adsorption, and the adsorbed O₂ and H₂O make different contributions related to specific charge trapping characteristics. We further demonstrate that the dynamic charge trapping/releasing processes are governed by the applied gate biases, revealing the equivalency between the positive charge trapping and negative charge releasing processes, and vice versa. The time-dependent degradation of the on-state current has been fitted to perform a statistical analysis based on the measurement results of eight devices. Three characteristic time constants have been determined, corresponding to a multi-step trapping process that may be dominated by dielectric surface trapping and trap-assisted tunneling into the bulk defects in the dielectric layer near the CNTs and those in depth, respectively. Full article

The development of efficient and sustainable photothermal catalytic systems is pivotal for modern organic transformations. Herein, we report the rational design and solvothermal synthesis of NH₂-MIL-101(Fe) metal–organic frameworks (NM-101) integrated with carbon nanotubes (CNTs) for the photothermal reduction in nitronaphthalene. The optimized NM-101/75C composites exhibit exceptional catalytic activity and high selectivity under NIR light irradiation, delivering a high yield of 84.4% within 1 h, which significantly outperforms its individual components. Systematic control experiments and detailed spectroscopic investigations reveal a powerful synergistic effect at the MOF-CNT interface, where the CNTs play a dual role in augmenting light harvesting and facilitating charge carrier separation. Furthermore, the high photothermal conversion efficiency of the composite enables rapid reaction kinetics. This work provides a robust and scalable strategy for constructing high-performance photothermal catalysts, offering critical insights into the interfacial engineering of MOF-based materials for industrial chemical manufacturing. Full article

A new method is described for the determination of vanadium using adsorptive stripping voltammetry of V(V) complexed with cupferron at a CNTs/SGC electrode modified with a lead film. The CNTs/SGC electrode is based on carbon nanomaterials such as carbon nanotubes and spherical glassy carbon, which form the foundation of modern sensor technology. Optimal conditions of adsorptive voltammetric measurement were found to be modification/accumulation potential and time of −1.6 V and 60 s, respectively, and supporting electrolyte of 0.2 mol/L NaAc–HAc buffer (pH 5.3) containing 0.3 mmol/L cupferron and 0.15 mmol/L Pb(II). The response of the system was found to be linear in a range of V(V) concentrations from 0.25 nmol/L to 10 nmol/L. The detection limit was found to be 0.08 nmol/L. The selectivity of the procedure was determined by analysing the effect of other interfering ions on the vanadium analytical signal. The method was successfully validated by analysing natural environmental waters. Full article

Recently, aqueous asymmetric supercapacitors (ASCs) have attracted considerable attention as safe and high-power energy storage devices. However, achieving high energy density while maintaining long-term cycling stability remains a significant challenge. Herein, an aqueous ASC employing a Mo_1.33CT_x/CNT negative electrode and a hydrated V₂O₅·nH₂O/CNT positive electrode in a 5 M LiCl electrolyte is reported. The Mo_1.33CT_x i-MXene was synthesized via hydrothermal selective etching of an i-MAX precursor, whereas hydrated V₂O₅·nH₂O nanoflakes were prepared with peroxide-assisted hydrothermal treatment. The ordered-vacancy Mo_1.33CT_x i-MXene provides a stable negative potential window, redox-active sites, and favorable conditions for reversible Li⁺ intercalation/deintercalation, thereby contributing to pseudocapacitive charge storage. The assembled ASC delivered a stable operating voltage of 1.7 V, a specific capacitance of 61 F·g⁻¹ at 1 A·g⁻¹, an energy density of 25.2 Wh·kg⁻¹ at 883 W·kg⁻¹ and 86% capacitance retention after 10,000 cycles. Electrochemical impedance spectroscopy revealed relatively low internal resistance and efficient ion transport within the layered electrode architectures. These results highlight the strong potential of ordered-vacancy MXene/vanadium oxide systems for advanced aqueous energy storage applications. Full article

Accurate estimation of molecule–nanotube interaction energies is critical for the computational screening of carbon-based materials for hydrogen storage; however, density functional theory (DFT) calculations remain computationally expensive for extensive configurational sampling. In this work, we develop a multilayer perceptron (MLP) surrogate model to predict H₂–CNT interaction energies, represented by $E_{ads}$, for H₂ interactions with a chiral (2,1) carbon nanotube. A curated dataset comprising 696 configurations was generated using DMol³ (BIOVIA Materials Studio), varying intermolecular distance, molecular orientation, and interaction site across three regions: internal cavity, edges, and external surface. The proposed MLP architecture (64–32–1) incorporates GELU activation functions, L2 regularization, and dropout to improve generalization. The model achieves coefficients of determination in the range R² = 0.90–0.96 across all interaction regions, with particularly strong performance at the nanotube edges (R² = 0.9358, MSE = 0.046 eV²), as well as on the external surface (R² = 0.9625, MSE = 0.574 eV²) and within the internal cavity (R² = 0.9051, MSE = 1.506 eV²). The original $E_{ads}$ distribution had a mean of 4.0955 eV and a sample standard deviation of 4.3189 eV. The elevated energy values observed in the internal cavity (up to 12 eV) are consistent with steric repulsion induced by geometric confinement rather than predictive artifacts. The trained MLP showed close agreement with DFT-derived trends, enabling exploration of interaction-energy landscapes spanning both attractive and repulsive regimes. These results indicate that MLP-based models trained on diverse configurational datasets provide a computationally efficient alternative for screening carbon nanostructures in hydrogen storage applications, without substantially compromising accuracy relative to first-principles methods. Full article

Transforming existing structural surfaces into sensing interfaces offers a promising route for scalable hydrogen monitoring in hydrogen-handling facilities, where leakage poses significant safety risks, addressing the limitations of conventional point-based sensors. In this study, a surface-integrated ZnFe₂O₄–CNT (ZFC) composite coating is developed as a potentially retrofit-compatible sensing solution to enable hydrogen sensing directly on cementitious materials, combining material-level functionality with data-driven concentration prediction. The ZFC composite was synthesized via a hydrothermal method followed by CNT functionalization and composite formation, and was then applied onto cement-based substrates using a thickness-controlled coating approach. Structural and morphological characterization (XRD, FESEM, TEM, BET) confirmed the formation of a hierarchical, porous architecture, while hydrogen sensing performance was evaluated under controlled thermo-hygrometric conditions (24–72 °C, 32–87% RH) at 10,000 ppm H₂. The sensor exhibited stable and reversible responses, with optimal performance at 39–52 °C and a minimum response time of 18 s. An XGBoost model enabled accurate prediction of hydrogen concentration, achieving R² ≈ 0.92 and RMSE ≈ 820 ppm under dynamic exposure. These results demonstrate that coupling redox-active oxide surfaces with conductive CNT networks enables effective surface-based chemiresistive sensing under realistic conditions. The proposed system transforms conventional cementitious materials into smart, surface-integrated hydrogen sensing systems, offering a scalable and retrofit-compatible approach for real-time monitoring in hydrogen-related infrastructure. Full article

Nanoparticle-modified concrete can exhibit improved mechanical performance, yet its residual compressive strength (Fc) after fire-like thermal exposure is difficult to predict because the response depends on both mixture design and heating conditions. Building on recent advances in explainable machine learning (ML) for cementitious materials, this study compiles 218 literature datapoints of post-heating Fc from 100 mm concrete cubes incorporating carbon nanotubes (CNTs) and nano-alumina (NA), exposed to 20–800 °C for up to 2 h. Seven input variables are used: cement-to-total aggregate ratio, CNT-to-cement ratio, NA-to-cement ratio, coarse-to-fine aggregate ratio, water-to-cement ratio, peak temperature, and exposure duration at temperature. Two particle-swarm-optimized ensemble regression models, Extreme Gradient Boosting (XGB-PSO) and Random Forest (RF-PSO), were developed and evaluated using a 70/30 train–test split with K-fold cross-validation on the training set. SHAP, individual conditional expectation (ICE), and partial dependence plots (PDPs) were employed to study the individual and combined effects of each input parameter on Fc prediction. The results demonstrated that the XGB-PSO model provides the best predictive performance (training R² = 0.9983; testing R² = 0.9434; testing MAE = 1.3168 MPa). Model interpretability was assessed using SHAP, ICE, and PDP analyses, revealing that temperature and exposure duration dominate strength loss, while CNTs and NA contribute positively within dose-dependent regimes. The highest predicted strengths occur for CNTs of 0.05% to 0.15% and NA of 0.65 to 2.71% (by cement mass) under moderate temperature exposure. A Python-based graphical user interface is provided to support rapid what-if assessment of CNT–NA mixtures under elevated-temperature scenarios. Full article

The development of high-performance adsorbents for treating dye-laden wastewater necessitates a deep understanding of structure–property relationships. This study presents a systematic investigation into the role of carbon material dimensionality (0D biochar, BC; 1D carbon nanotubes, CNT; 2D graphene oxide, GO) in modulating the properties of a dual physically crosslinked sodium alginate/polyacrylamide (SA/PAM) hydrogel for methylene blue (MB) adsorption. A series of composite hydrogels was fabricated via a sequential physical crosslinking strategy. Comprehensive characterization confirmed the successful incorporation and dispersion of carbon materials within the dual network. The three hydrogels showed good mechanical properties. Under the conditions of 25 °C, an initial MB concentration of 100 mg/L, and pH 10–11, the incorporation of carbon materials enhanced the adsorption capacity, with maximum adsorption capacities of 411.5, 410.6, and 422.8 mg/g for BC-H, GO-H, and CNT-H, respectively. Coexisting constituents in real water samples reduce adsorption capacity via competitive adsorption and interfacial interference. After five consecutive adsorption–desorption cycles, the adsorption capacities of BC-H, GO-H, and CNT-H decreased to 57.7%, 67.2%, and 61.7% of their initial values, respectively. Adsorption isotherm and kinetic studies revealed that the process followed the Langmuir model and pseudo-second-order kinetics, indicative of monolayer chemisorption. Mechanistic analysis identified synergistic contributions from electrostatic attraction, π-π stacking, and physical entrapment. Physical structural changes and chemical site occupation are the main reasons for the decrease in the adsorption performance of hydrogels during cyclic use. This work provides a rational design strategy for advanced adsorbents and a theoretical foundation for efficient dye wastewater remediation. Full article

This study presents a hierarchical conductive-network strategy to overcome the performance trade-off in cement structural supercapacitors (CSSCs). By incorporating one-dimensional carbon nanotubes (CNTs) and two-dimensional graphene oxide (GO) into Portland cement, we simultaneously enhance its electrochemical and mechanical properties. The approach exploits the complementary roles of the two nanomaterials: CNTs establish a three-dimensional percolation network that facilitates electron transport, while GO promotes formation of a denser calcium silicate hydrate (C-S-H) gel and refines the pore structure by complexing with calcium ions, thereby improving ionic pathways. The k12gc sample attains a specific capacitance of 66.8 F g⁻¹ at 0.1 mA cm⁻², a 58.4% rise in conductivity and a 63% reduction in charge-transfer resistance. At the same time, the composite reduces harmful macropores by 27.9% and strengthens the material, with compressive and flexural strengths increasing by 4.8% and 8.3%, respectively. This work establishes a rational design principle based on functional division between CNTs and GO for developing high-performance, multifunctional CSSCs. Full article

Carbon nanotube yarn (CNTY) monofilament composites were investigated for integrated temperature sensing by embedding a single CNTY in a vinyl ester resin (VER) and measuring the electrical resistance change by tapping into the thermoresistive response of the CNTY. The effect of curing condition on the thermoresistive response was evaluated using dwell tests and repeated heating–cooling cycles, comparing specimens cured at room temperature (RT) with those post-cured at 140 °C for 1 h. RT-cured CNTY/VER monofilament composites exhibited electrical resistance drift, with the resistance failing to return to its initial value after each thermal cycle, resulting in a residual resistance change of ~8.85%. In contrast, post-cured (PC) specimens showed a much smaller residual change (−0.08%) after cycle completion. Thermal cycling from RT (~25 °C) to 100 °C produced a nearly linear negative thermoresistive response. The average heating and cooling TCR values were −7.98 × 10⁻⁴ °C⁻¹ and −8.32 × 10⁻⁴ °C⁻¹ for CNTY/VER, and −7.93 × 10⁻⁴ °C⁻¹ and −7.13 × 10⁻⁴ °C⁻¹ for CNTY/VER-PC, respectively. The hysteresis decreased from 21.65% for RT-cured specimens to 12.49% after post-curing, accompanied by improved linearity. The influence of heating rate on TCR was also examined for both freestanding CNTYs and CNTY/VER monofilament composites. The observed response is attributed to coupled matrix–yarn effects (wetting, resin infiltration, and shrinkage) together with temperature-dependent electron transport across CNT junctions. Finally, CNTY/VER monofilament composites demonstrated the ability to estimate internal temperatures under various thermal programs. Full article

Dry reforming of methane (DRM) converts the greenhouse gases methane (CH₄) and carbon dioxide (CO₂) into syngas (hydrogen (H₂) and carbon monoxide (CO)). Despite its numerous advantages, DRM has not yet been industrialized due to catalyst deactivation and competing side reactions. While Ni-based catalysts have been widely used, they are prone to increased carbon deposition and sintering, and although bimetallic systems and oxygen-based supports have shown promise, their effects on carbon deposition are yet to be fully understood. In this study, carbon nanotube (CNT)-supported Pt-Ni catalysts incorporating mixed oxides of CeZrO₂ and CeZrLaO₂ were investigated to evaluate the impact of support composition and metal–support interactions in DRM. The catalysts were synthesized and subsequently tested in DRM. Catalysts supported on CNTs displayed higher CH₄ and CO₂ conversions compared to conventional ceria–zirconia, highlighting the beneficial role of the carbon nanotube support in improving dispersion and accessibility of the metal active sites. Addition of Pt was found to promote reverse water–gas shift (RWGS) reaction, whereas the addition of La was found to decrease catalytic activity. Despite the formation of a Ni-Pt alloy, the obtained catalysts favored RWGS over DRM. These findings illustrate key limitations and design considerations for optimization of CNT-supported bimetallic catalysts in DRM. Full article