Heterostructured MnCo2S4@Ni(OH)2 nanosheet arrays (NSAs) were successfully grown on nickel foam (NF) via a simple hydrothermal strategy. This hierarchical architecture effectively addresses key limitations of conventional supercapacitor electrodes, including the intrinsically low specific capacitance of transition metal oxide-based materials and the agglomeration or restacking of nanostructures, while simultaneously mitigating volume fluctuations during long-term electrochemical cycling. The MnCo2S4 NSAs offer rich redox-active sites due to multiple oxidation states, thereby delivering high specific capacitance. The conformally coated Ni(OH)2 nanosheets not only introduce additional redox pairs but also serve as a protective layer, preserving the structural and electrochemical integrity of the sulfide core. As a result, the MnCo2S4@Ni(OH)2 NSAs exhibit outstanding electrochemical performance, achieving a high specific capacitance of 2512 F g-1 at 1 A g-1 and excellent cycling stability. Furthermore, asymmetric supercapacitors (ASCs) assembled with these heterostructures as positive electrodes and activated carbon (AC) as negative electrodes deliver a high energy density of 41 Wh kg-1 along with superior cycling durability. These findings underscore the potential of this heterostructure-engineering approach as a promising route toward high-performance energy storage devices with high energy and longterm stability.

The tribological performance of self-lubricating composites is a complex system influenced by material properties and test conditions. Data-driven approaches, including machine learning (ML) algorithms, can provide a more comprehensive understanding of complex problems influenced by multiple parameters. The correlation between the tribological wear performance of graphite-filled polytetrafluoroethylene (PTFE) composites and the inherent material properties and test variables was investigated using two-parameter relationship analyses methods. Then a generative adversarial network (GAN) data augmentation method is proposed to address the problem of poor model generalization due to data scarcity, and five machine learning algorithms (K-nearest neighbor, eXtreme gradient boosting, gradient boosting decision tree, random forest regression and gradient boosting regression) are used to predict tribological properties based on the augmented data. The results show that the GBR model has good prediction ability for friction coefficient and wear rate, with R2 values of 0.9476 and 0.9346, respectively. The feature significance analysis shows that normal load and sliding speed have the greatest influence on the friction coefficient, and graphite content and matrix hardness have the greatest influence on the wear rate. Finally, the validity of the model was experimentally verified. This study provides a new method for predicting the tribological properties of composites using machine learning techniques and provides a theoretical basis for material design and optimization.

Supercapacitors, with remarkable advantages such as excellent power density, extremely short charging and discharging times, and an ultra-long cycle life, exhibit great application potential within the realm of energy storage. However, the bottleneck issue of their relatively low energy density has become a key factor restricting their in-depth application in a wider range of fields and further development, and effective solutions are urgently needed. In this paper, a sacrificial template method and an electrostatic self-assembly strategy were employed to controllably synthesize the mulberry-layered cubic composite electrode material Cu2O@NiCo-LDH/Mxene (Cu2O@NCL/M). In this material, a part of the residual Cu2O template exhibits certain redox activity and can undergo reversible redox reactions during the electrochemical process, thereby providing additional capacitance contributions. The cubic structure remaining after etching itself has a high degree of symmetry and stability, and the mulberry-like assembly method enables the nanosheets of the layered double hydroxide (LDH) to support each other. The introduction of a single layer of Mxene can not only promote the electron transfer between Cu2O and NiCo-LDH, but also the interfacial interaction among the three components is advantageous for improving the structural stability, enabling it to maintain good electrochemical performance during charge-discharge processes. The specific capacitance of Cu2O@NCL/M is 1713F center dot g-1 (at 1 A center dot g-1). Cu2O@NCL/M exhibits remarkable rate performance, maintaining 82.3 % of its capacitance as the current density increases to 10 A center dot g-1. Moreover, after undergoing 5000 cycles, it demonstrates impressive long-term stability by retaining 80 % of its initial specific capacitance. Interestingly, the energy density of the asymmetric supercapacitors (ASCs) Cu2O@NCL/M//AC can be significantly increased to 49.5 Wh center dot kg-1 (with a power density of 750 W center dot kg-1) and 45.0 Wh center dot kg-1 (with a power density of 700 W center dot kg-1). Therefore, this work demonstrates a simple and successful synthetic approach for fabricating high-performance energy storage devices with special morphology.

Metal–organic framework (MOF) compounds are particularly attractive as promising advanced functional materials in energy storage and conversion. However, they exhibit limited electrochemical properties due to their inherent instability and poor electrical conductivity. Herein, a high-conductive electrode material of trimetallic Co/Ni/Fe-MOF was prepared using a solvothermal method. The morphology, specific surface area, and electrochemical properties of the Co/Ni/Fe-MOF were measured. Experimental results show that Co/Ni/Fe-MOF materials have a mesoporous structure and a large available specific surface area of 17.04 m2·g−1. When the discharge current density is 1 A·g−1, the specific capacitance of Co/Ni/Fe-MOF is as high as 2290 F·g−1. An asymmetric supercapacitor device was assembled using Co/Ni/Fe-MOF material as the positive electrode and activated carbon (AC) as the negative electrode. The Co/Ni/Fe-MOF//AC asymmetric supercapacitor has a power density of 7500 W·kg−1 and an energy density of 132.3 Wh·kg−1 in a potential window of 1.5 V. The excellent electrochemical properties of Co/Ni/Fe-MOF make it a wide application prospect as an electrode material for supercapacitors in the energy storage field.

The fabrication of sulfide/graphene composites is an important strategy to improve the performance of supercapacitors. It is still a challenge to synthesize three-dimensional sulfide/graphene nanostructures with special morphologies and structures because it is difficult to realize the effective arrangement of graphene. In this work, a simple method has been successfully developed for the fabrication of three-dimensional NiS2/graphene nanostructures. The rod-like morphology of the precursors is preserved during the carbonization and sulfurization process. The carbonization temperature can affect the size of NiS2 nanoparticles formed in the nanostructures. The as-obtained materials can serve as electrode materials in supercapacitors and present excellent electrochemical behavior due to their good electrical conductivity and unique structures.

Porous carbons are considered as promising electrode materials for electrical double layer capacitors due to their high surface area, abundant pores and high conductivity. However, the preparation of porous carbons with controlled morphology and graphitization degree is still a challenge, since the structure of the precursor tends to collapse and the amorphous carbon tends to form during the synthesis process. Herein, an efficient ball millingassisted method for the preparation of porous carbons with controlled morphology and graphitization degree is developed. The results show that the amount of FeCl3 center dot 6H(2)O determines the morphologies, graphitization degree and yield of porous carbons. The as-prepared porous carbon exhibits a superior specific capacitance of 168 F g(-1) at 1 A g(-1) and a good cycling stability of a 94.7% capacitance retention after 10,000 cycles when used as supercapacitor electrode materials. The excellent electrochemical performance is attributed to the high surface area (992 m(2) g(-1)) and rich micropores, which can supply more active sites and ensure high specific capacitance. The abundant mesopores and high graphitization degree can accelerate the electron transfer and the ion diffusion within the electrodes. In addition, the thin sheets can also shorten the ion diffusion and electron transfer length.

A simple method by using Ni-based salts as the catalysts has been successfully developed to prepare porous carbons. The results show that Ni-based salts significantly affect the morphology, porous structure and graphitization degree of carbon materials. More importantly, it is found that the anions in the Ni-based salts also play important roles sor have synergistic effects for the formation of carbon materials. The obtained porous carbons can be used as electrode materials for supercapacitors and present excellent electrochemical behaviors. It is found that mesopores can accelerate the ion diffusion, ensuring full utilization of micropores and increasing gravimetric capacitance. Furthermore, a rational proportion between mesopores and micropores is also important for improving the electrochemical performance of porous carbons. In addition, the better electron conductivity arising from higher graphitization degree is also beneficial for the improvement of electrochemical behaviors.