Aza-fused aromatic π-conjugated networks are an important class of 2D graphitic analogs, which are generally constructed using aromatic precursors. Herein, the study describes a new synthetic approach and electrochemical properties of a self-exfoliating benzotristriazine 2D network (BTTN) constructed using aliphatic precursors, under relatively mild conditions. The obtained BTTN exhibits a nanodisc-like morphology, the self-exfoliation tendency of which is ascribed to the presence of structurally different macrocycles with high electronic repulsion between the layers. The benzotristriazine repeat units of BTTN is electroactive and holds higher carbon/nitrogen ratio when compared with the conventional graphitic aza-fused π-conjugated networks. The self-exfoliated BTTN nanodiscs show excellent electrochemical energy storage of 485 and 333 F g-1 at 1 A g-1 in three-electrode and two-electrode measurements, respectively. BTTN in a symmetric coin-cell architecture exhibits a high specific energy value of 46 Wh kg-1 at a power density of 1 kW kg-1 and shows excellent cyclic stability of 96% for 10 000 and 90% for 30 000 charge-discharge cycles at a higher current density of 5 A g-1, surpassing the device performance of most of the reported all-organic pseudocapacitive 2D networks.

Rechargeable aluminum ion batteries (AIBs) have recently gained widespread research concern as energy storage technologies because of their advantages of being safe, economical, environmentally friendly, sustainable, and displaying high performance. Nevertheless, the intense Coulombic interactions between the Al3+ ions with high charge density and the lattice of the electrode body lead to poor cathode kinetics and limited cycle life in AIBs. This paper reviews the recent advances in the cathode design of AIBs to gain a comprehensive understanding of the opportunities and challenges presented by current AIBs. In addition, the advantages, limitations, and possible solutions of each cathode material are discussed. Finally, the future development prospect of the cathode materials is presented.

Two-dimensional nanosheets, with their distinct characteristics, are widely used in various applications such as water splitting, supercapacitors, catalysis etc. In this research, we produced Cu-BDC MOF nanosheets by using Cu2O nanotubes for metal ions and H2BDC as the organic linker. We combined these Cu-BDC MOF nanosheets with reduced graphene oxide (rGO) to form a nanocomposite. The collaboration between Cu-BDC MOF and rGO boosts both the catalytic reduction of 4-nitrophenol and the electrochemical capabilities. The conversion of 4-nitrophenol to 4-aminophenol is achieved using sodium borohydride as both a reducing agent and a catalyst. The study explores the impact of different concentrations of 4-nitrophenol and sodium borohydride on catalytic efficiency. The increase in sodium borohydride concentration enhances catalytic efficiency by providing more BH4- ions and electrons for the reduction process. The catalytic reduction process adheres to the Langmuir-Hinshelwood mechanism with apparent pseudo-first-order kinetics. Specifically, Cu-BDC MOF and rGO/Cu-BDC MOF exhibit specific capacities of 468.4 mA h/g and 656.4 mA h/g at a current density of 2 A/g, respectively, while also enhancing the operating voltage window. Therefore, electrodes based on rGO/Cu-BDC MOF nanosheets present a novel approach for environmental remediation and energy storage applications across various fields.

The development of self-powered sensors with interference-resistant detection is a priority area of research for the next generation of wearable electronic devices. Nevertheless, the presence of multiple stimuli in the actual environment will result in crosstalk with the sensor, thereby hindering the ability to obtain an accurate response to a singular stimulus. Here, we present a self-powered sensor composed of silk-based conductive composite fibers (CNFA@ESF), which is capable of energy storage and sensing. The fabricated CNFA@ESF exhibits excellent mechanical performance, as well as flexibility that can withstand various deformations. The CNFA@ESF provides a good areal capacitance (44.44 mF cm-2), high-rate capability, and excellent cycle stability (91 % for 5000 cycles). In addition, CNFA@ESF also shows good sensing performance for multiple signals including strain, temperature, and humidity. It was observed that the assembly of the symmetrical device with a stiff hydrogel surface layer for protection enabled the real-time, interference-free monitoring of temperature signals. Also, the CNFA@ESF can be woven into fabrics and integrated with a solar cell to form a self-powered sensor system, which has been proven to convert and store solar energy to power electronic watches, indicating its huge potential for future wearable electronics.

Due to their low production cost, sodium-ion batteries (SIBs) are considered attractive alternatives to lithium-ion batteries (LIBs) for next generation sustainable and large-scale energy storage systems. However, during the charge/discharge cycle, a large volume strain is resulted due to the presence of a large radius of sodium ions and high molar compared to lithium ions, which further leads to poor cyclic stability and lower reversible capacity. Hence, as a promising anode material for SIBs, the two-dimensional (2D) materials including graphene and its derivatives and metal oxides have attracted remarkable attention due to their layered structure and superior physical and chemical properties. The inclusion of graphene and metal oxides with other nanomaterials in electrodes have led to the significant enhancements in electrical conductivity, reaction kinetics, capacity, rate performance and accommodating the large volume change respectively. In this review article, the fabrication techniques, structural configuration, sodium ion storage mechanism and its electrochemical performances will be introduced. Subsequently, an insight into the recent advancements in SIBs associated with 2D anode materials (graphene, graphene oxide (GO), transition metal oxides etc.) and other graphene-like elementary analogues (germanene, stanine etc.) as anode materials respectively will be discussed.

In pulse power systems, multilayer ceramic capacitors (MLCCs) encounter significant challenges due to the heightened loading electric field (E), which can lead to fatigue damage and ultrasonic concussion caused by electrostrictive strain. To address these issues, an innovative strategy focused on achieving an ultra-weak polarization-strain coupling effect is proposed, which effectively reduces strain in MLCCs. Remarkably, an ultra-low electrostrictive coefficient (Q33) of 0.012 m4 C-2 is achieved in the composition 0.55(Bi0.5Na0.5)TiO3-0.45Pb(Mg1/3Nb2/3)O3, resulting in a significantly reduced strain of 0.118% at 330 kV cm-1. At the atomic scale, the local structural heterogeneity leads to an expanded and loose lattice structure, providing ample space for large ionic displacement polarization instead of lattice stretching when subjected to the applied E. This unique behavior not only promotes energy storage performance (ESP) but also accounts for the observed ultra-low Q33 and strain. Consequently, the MLCC device exhibits an impressive energy storage density of 14.6 J cm-3 and an ultrahigh efficiency of 93% at 720 kV cm-1. Furthermore, the superior ESP of the MLCC demonstrates excellent fatigue resistance and temperature stability, making it a promising solution for practical applications. Overall, this pivotal strategy offers a cost-effective solution for state-of-the-art MLCCs with ultra-low strain-vibration in pulse power systems.

In order to facilitate electrochemical oxygen reactions in electrically rechargeable zinc-air batteries (ZABs), there is a need to develop innovative approaches for efficient oxygen electrocatalysts. Due to their reliability, high energy density, material abundance, and ecofriendliness, rechargeable ZABs hold promise as next-generation energy storage and conversion devices. However, the large-scale application of ZABs is currently hindered by the slow kinetics of the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER). However, the development of heterostructure-based electrocatalysts has the potential to surpass the limitations imposed by the intrinsic properties of a single material. This Account begins with an explanation of the configurations of ZABs and the fundamentals of the oxygen electrochemistry of the air electrode. Then, we summarize recent progress with respect to the variety of heterostructures that exploit bifunctional electrocatalytic reactions and overview their impact on ZAB performance. The range of heterointerfacial engineering strategies for improving the ORR/OER and ZAB performance includes tailoring the surface chemistry, dimensionality of catalysts, interfacial charge transfer, mass and charge transport, and morphology. We highlight the multicomponent design approaches that take these features into account to create advanced highly active bifunctional catalysts. Finally, we discuss the challenges and future perspectives on this important topic that aim to enhance the bifunctional activity and performance of zinc-air batteries.

Thermochromic phase change materials (TPCMs) are gaining increasing interest among scientists. These multifunctional materials can store thermal energy but also, at the same time, during the phase transition, they can change colour. Thermal conductivity is also extremely important for this type of material, which is why various additives are used for this purpose. This work aimed to study the properties of thermochromic phase change materials with an inorganic modifier. Stearic acid, behenyl alcohol, and bromocresol purple were used as thermochromic system components, while boron nitride particles were used as an additive. The key tests for such systems are thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), which allow determining the thermal stability of the materials (at around 170 °C) and phase transition parameters (thermal energy storage of 300 J/g in the range of 40-75 °C). The thermochromic properties were tested, and satisfactory results were obtained. In the end, laser flash analysis (LFA) tests indicated that boron nitride improves the thermal conductivity of the organic thermochromic phase change material by almost 30%. The results showed that the tested materials have great potential as thermochromic phase change materials for thermal energy storage.

Focus on advancement of energy storage has now turned to curbing carbon emissions in the transportation sector by adopting electric vehicles (EVs). Technological advancements in lithium-ion batteries (LIBs), valued for their lightweight and high capacity, are critical to making this switch a reality. Integrating structurally enhanced LIBs directly into vehicular design tackles two EV limitations: vehicle range and weight. In this study, 3D-carbon (3D-C) lattices, prepared with an inexpensive stereolithography-type 3D printer followed by carbonization, are proposed as scaffolds for Li metal anodes for structural LIBs. Mechanical stability tests revealed that the 3D-C lattice can withstand a maximum stress of 5.15 ± 0.15 MPa, which makes 3D-C lattices an ideal candidate for structural battery electrodes. Symmetric cell tests show the superior cycling stability of 3D-C scaffolds compared to conventional bare Cu foil current collectors. When 3D-C scaffolds are used, a small overpotential (≈0.075 V) is retained over 100 cycles at 1 mA cm-2 for 3 mAh cm-2, while the overpotential of a bare Cu symmetric cell is unstable and increased to 0.74 V at the 96th cycle. The precisely oriented internal pores of the 3D-C lattice confine lithium metal deposits within the 3D scaffold, effectively preventing short circuits.

It is challenging to accurately model the overall uncertainty of the power system when it is connected to large-scale intermittent generation sources such as wind and photovoltaic generation due to the inherent volatility, uncertainty, and indivisibility of renewable energy. Deep reinforcement learning (DRL) algorithms are introduced as a solution to avoid modeling the complex uncertainties and to adapt the fluctuation of uncertainty by interacting with the environment and using feedback to continuously improve their strategies. However, the large-scale nature and uncertainty of the system lead to the sparse reward problem and high-dimensional space issue in DRL. A hierarchical deep reinforcement learning (HDRL) scheme is designed to decompose the process of solving this problem into two stages, using the reinforcement learning (RL) agent in the global stage and the heuristic algorithm in the local stage to find optimal dispatching decisions for power systems under uncertainty. Simulation studies have shown that the proposed HDRL scheme is efficient in solving power system economic dispatch problems under both deterministic and uncertain scenarios thanks to its adaptation system uncertainty, and coping with the volatility of uncertain factors while significantly improving the speed of online decision-making.