Low-cost Energy Research Articles

A non-dominated sorting based multi-objective neural network algorithm of ethylene glycol hydrogenation reactor in energy reduction

Artificial intelligence has revolutionized various industries, including chemical process optimization. Artificial intelligence (AI) can be applied to various ethylene glycol (EG) production aspects to improve efficiency, quality, and overall process optimization. Process optimization of dimethyl oxalate (DMO) hydrogenation to ethylene glycol (EG) is carried out to minimize/maximize conversion, energy, productivity, bare module cost (CBM), and side product in the presence of pressure and temperature variables. A non-dominated sorting-based multi-objective neural network algorithm (MONNA) is applied to tackle problem optimization for EG production. The results show that the highest productivity, minimum energy cost, side product, and highest conversion are 172 Million RM/year, 0.00600 Million RM/year, 0.0320 kmol/hr, and 99.6%, respectively. The intermediate points in the Pareto Front PF for various three-objective situations provide lower energy costs than the bi-objective function. While bi-objective optimization might seem more straightforward, the intermediate points on the Pareto Front in three-objective optimization can provide lower energy costs due to more effective balancing of trade-offs, richer exploration of the solution space, capturing complex interdependencies, and offering more robust and flexible solutions. Decision makers can use the resulting pareto to decide on the most acceptable alternative according to their preferences. The decision variable plots show that the pressure highly affected the optimal solution with the opposite action. This work’s analysis is predicted to provide insight into optimization literature for energy savings and sustainability and promote commercial growth for the industry. Identifying optimal trade-offs between various objectives, such as energy cost and productivity, can help reduce overall production costs, making the production process more competitive.

Sustainable stabilization/solidification of electroplating sludge using a low-carbon ternary cementitious binder

Electroplating sludge (ES), due to its high dosages of heavy metals (HMs), is classified as hazardous waste, presenting risks to both health and environment. Stabilization/solidification (S/S) technology is extensively applied in ES treatment. This study designs a low-carbon ternary cementitious binder, limestone calcined clay cement (LC3), for S/S treatment of ES and investigates the immobilization mechanism of HMs in the crystalline products and calcium alumino-silicate hydrate (C-A-S-H) within LC3. Results show that CrO42- and Cd2+ are primarily stabilized in aluminate crystalline products by replacing SO42- and Ca2+ in the double-layered plate structure, respectively. The remaining CrO42- is captured by the (SiOOH)2AlCa⁺ groups in C-A-S-H generated from substitution of aluminum tetrahedra to bridging silicon tetrahedra. For positively charged Cd2+, it is mainly stabilized through ion exchange with Ca2+ on the C-A-S-H chains. The pozzolanic reaction of calcined clay increases the Al/Ca and Si/Ca atomic ratios in C-A-S-H, enhancing the immobilization efficiency of C-A-S-H to CrO42- and Cd2+. The synergistic effect of calcined clay and limestone, along with the dissolution of aluminosilicates in calcined clay, changes the structure and composition of hydration products, facilitating the chemical binding of CrO42- and Cd2+ by aluminate products. Moreover, the extra hydration products generated by the pozzolanic reaction and the formation of numerous carboaluminate phases strengthen the physical encapsulation performance to HMs. Regarding actual S/S performance, multi-scale evaluation results show that the designed LC3 binder achieves sustainable S/S of ES with high strength, low carbon emission, low cost, and low energy consumption.

Amino-acid surface modulation of cobalt-tin sulfide and band broadening in cobalt-iron selenide heterostructure for high-performing asymmetric supercapacitor

Controlled synthesis of hierarchical flowerlike cobalt tin sulfide (SnCoSx) is successfully obtained using the chelation of the biomolecule l-asparagine with cobalt-tin metal cations by a hydrothermal technique. l-asparagine plays a crucial role as an inducer and a good structure-directing activity. Subsequently, pine needle-shaped cobalt iron selenium (FeCoSey) is tightly deposited on the SnCoSx surface to construct cobalt tin sulfide coated with cobalt iron selenide (FeCoSey@SnCoSx) heterostructure, which has exposed more active sites and the most abundant channels for electron/ion transfer. Among all prepared electrodes, the optimized FeCoSey@SnCoSx demonstrates the highest energy storage capacity (1754.65 F/g at 1 A g−1) and excellent cycling steadiness (86.71 % after 10,000 cycles at 15 A g−1). The heterogeneous interface engineering of FeCoSey and SnCoSx enables the FeCoSey@SnCoSx composite to generate outstanding electrochemical performance for supercapacitor devices. As expected, an asymmetric hybrid supercapacitor (AHSC) based on FeCoSey@SnCoSx cathode and nitrogen-doped hierarchy porous activated carbon (NHPC) derived from soybeans anode displays a high energy density of 59.44 Wh kg−1 at 402.09 W kg−1 and a super-long steady presentation with a preliminary capacitance holding ratio of 92.2 % following 10,000 cycles with an 8 A g−1 voltage density. This strategy provides a new approach for the controllable preparation of electrode material morphology, opens up new methods for high-performance heterogeneous interface composite electrode materials, and guides the designing of low-cost energy storage devices.

DFT investigations of doping effects on the structural stability, thermal diffusion, and absorption/desorption kinetics in cubic, hexagonal, and monoclinic Mg2NiHx hydrides

The pseudo-potential plane-wave method, based on Density Functional Theory (DFT) and using the Generalized Gradient Approximation (GGA), is applied to investigate the effects of progressive hydrogen insertion on the structural stability and energetics of Mg2NiHx hydrides. The obtained results indicate that Mg2Ni crystallizes in the hexagonal (P6222) structure. Taking into account the site preference of H atoms, the progressive hydrogenation of Mg2Ni favors the formation of Mg2NiHx hydrides in cubic (Fm-3m) and monoclinic (C2/c) phases rather than the parent hexagonal phase. The alloying effects of Cu, Y, Si, Ti, Cr, and Fe on the structural stability and absorption/desorption kinetics of monoclinic Mg2NiH4 are also investigated. More particularly, systems with Cu and Si additions have the lowest desorption temperatures, as confirmed by Molecular Dynamic (MD) calculations. The thermal diffusion is well observed in all studied compounds. The corresponding average thermal diffusion coefficients are mainly attributed to hydrogen atoms and are increased by the addition of Cu. These trends are expected to have an important role in phase transitions observed during hydrogen insertion. The present study based on DFT and MD calculations shows that doped Mg2NiHx are promising hydrides with interesting kinetic behavior. The obtained results can be useful for future experimental studies devoted to improving hydrogen absorption/desorption temperatures, low energy costs, and high atomic hydrogen storage capacities in Mg2Ni.

Multiscale approaches for optimizing the impact of strain on Na-ion battery cycle life

Abstract The high costs and geopolitical challenges inherent to the lithium-ion (Li-ion) battery supply chain have driven a rising interest in the development of sodium-ion (Na-ion) batteries as a potential alternative. Unfortunately, the larger ionic radius of Na limits the reversibility of cycling because of the extensive atomic rearrangements that accompany Na-ion insertion, which in turn limit diffusion and charging speed, and lead to rapid degradation of the electrodes. The Center for Strain Optimization for Renewable Energy (STORE) was established to address these challenges and develop new electrode materials for Na-ion cells. This article discusses the current state-of-the-art materials used in Na-ion cells and several directions that STORE believes are critical to understand and control the structural and volumetric changes during the reversible (de)insertion of large cations. Graphical abstract Highlights Understanding the fundamental way materials respond to localized strains at the atomic length-scale is a critical first step in the development of highly reversible, long cycle life, Na-ion insertion hosts. This perspective explores a variety of methods that can be employed to mitigate the detrimental effects of large strain. The insights gained from these investigations should help lay the foundation for the creation of more economical and sustainable batteries that could have immediate impact on global energy infrastructure. Discussion Although there is near universal agreement that electrochemical energy storage must be an integral part of a green-energy future, there is less agreement about how to reduce the cost of energy storage. Replacing high-cost lithium-ion cells with lower-cost sodium-ion batteries is one option frequently considered in future energy models, but the details of what can be achieve with optimized sodium cell performance remains unclear. Here we posit that developing methods to mitigating strain on the electrode particle length scale is a key factor for achieving long-cycle-life sodium-ion batteries. Mitigating strain on the atomic scale suppress electrode-level volume change. Allowing for fast cycling in materials without the problems of electrode cracking or delamination. We further posit that understanding volume change in sodium-ion electrodes at a fundamental level will lead to the designing new sodium-ion electrode materials that will allow for efficient, stable, lower-cost energy storage.

A novel atmospheric microwave plasma source based on circular waveguide with double ridges for nitrogen fixation

A novel atmospheric microwave plasma source based on circular waveguide with double ridges for nitrogen fixation

Investigation of biodiesel production from Ethiopia leather industry fleshing wastes through numerical and experimental studies

ABSTRACT Investigating the potential of biodiesel production from fleshing wastes derived from Ethiopia's leather industry involves both numerical modelling and experimental approaches. The collection and characterisation of fleshing wastes, followed by the application of transesterification methods to produce biodiesel. This integrated approach not only showcases a sustainable waste management solution but also contributes to renewable energy sources, reducing dependence on fossil fuels while addressing environmental concerns associated with leather waste. In this study, fleshing oil has a high acid value of 24.66 mg KOH/g and a 12.33% FFA level. To lower the FFA to 2.5%, an acid pretreatment and transesterification reaction are required. According to the simulation result, azeotrope did not form in the biodiesel separation column, and standard distillation columns could easily separate the biodiesel. It was also revealed by the distillation column purification process that only four stages were required to produce high-grade biodiesel. 99.9% of the introduced methanol was recovered from the separation column, 95% of the biodiesel yield was acquired from the reactor, and 99.4% of the refined biodiesel was obtained from the purification procedure. the investigation of biodiesel production from Ethiopian leather industry waste represents a significant step towards the development of low-cost renewable energy sources.

Coordinating variable refrigerant flow system for effective demand response in commercial buildings

Model Predictive Control (MPC) is extensively utilized for demand response (DR) in commercial buildings. When deploying MPC in real buildings, the model uncertainty is unavoidable, which could come from multiple sources: incorrectly identified values of model parameters, unmeasured disturbances, sensor errors, etc. However, there is a lack of research on the effects of model uncertainty on the performance of MPC for DR events. This study addresses this gap by analyzing the impact of model uncertainty on MPC in coordinating multiple VRF systems in commercial buildings. A virtual testbed was developed to benchmark and evaluate different DR control algorithms. We compared rule-based control (RBC), priority stack-based control (PSBC), and MPC with model uncertainties. This involved assuming normal distributions with various means for biased and unbiased uncertainties and different standard deviations. Our results show that MPC is robust to model uncertainty. For costs saving tasks, when the model uncertainty is unbiased, MPC outperforms the RBC controller with fewer discomfort hours and lower energy costs when the uncertainty of cooling load is below 40 % and 90 %, respectively; when the model uncertainty is biased and increases gradually, MPC can only outperform RBC under small uncertainties of cooling load. For load tracking tasks, when the model uncertainty is unbiased, MPC outperforms PSBC in terms of fewer discomfort hours and lower power tracking error, even with a 100 % uncertainty of cooling load; when the model uncertainty is biased, it exhibits a similar pattern to the unbiased uncertainty. Last, this study compared the computation time and control performance of formulating MPC as integer versus linear programming, demonstrating that linear programming is more suitable for coordinating thermally controllable loads (TCLs) at large-scales due to its faster computation time and good tracking performance. This study provides valuable insights into the effects of model uncertainty on MPC performance in demand response and supports its practical application in commercial buildings.

3D flux configuration cost effective switched reluctance motor with small torque ripple content; design and prototyping

AbstractSwitch reluctance motors (SRMs) have many advantages, such as easy construction, high reliability, low cost, and higher energy efficiency compared to the inductance motors. However, SRMs have a major drawback—severe torque ripple (TR), which causes a great deal of noise and movement. Hence, these motors are rarely used in industrial applications. Torque ripple reduction in reluctance motors has been studied since their invention in the 1950s, but the effectiveness of any such reduction methods remain controversial. Significant reductions in TR remain necessary to make the SRM more applicable for industrial use. The main objective of this study is to propose a new configuration of the SRM which greatly reduces TR and has low manufacturing costs. Although this new structure greatly reduces the TR, like most previous research, some aspects such as drive control and design optimisation methods could be used to more obviously reduce TR. The proposed motor has a simple configuration which is more efficient. Finite element method is used to verify the design, and a prototype has been fabricated and tested to experimentally verify its performance.

Optimization of Heat Reflective Triple Glazing Thickness Using the Artificial Fish Swarm Algorithm

Abstract. The significance of this research lies in its potential to improve energy efficiency in buildings, particularly in regions prone to high temperatures. By optimizing the thermal performance of heat-reflective glass, buildings can achieve better temperature regulation, leading to reduced dependency on air conditioning systems and lower energy costs. This research specifically targets the optimization of glass thickness, a critical factor influencing the overall effectiveness of heat-reflective glazing. The focus is on minimizing the transmitted light intensity for sunlight within the wavelength range of 300 to 2000 nm, which is vertically incident on the glass. The optimized glass thickness aims to maximize the thermal reflective properties while ensuring adequate natural light within indoor spaces. This study employs the Artificial Fish Swarm Algorithm to explore the optimal thickness of heat-reflective triple glazing. The effectiveness of this optimization method is assessed by comparing its results with experimental findings obtained through a systematic traversal of glazing thicknesses. The results highlight the potential of the Artificial Fish Swarm Algorithm to significantly enhance the thermal performance of heat-reflective glass, offering a practical solution for energy-efficient building design in hot climates.

Ant lion based optimization for performance improvement of methanol production

Abstract Methanol (CH3OH) is a versatile compound used in various industries. Catalytic reactors used in CH3OH production are expensive due to high energy and raw material costs. Multi-objective optimization (MOO) is used to optimize CH3OH production, but it is still lacking. Researchers use alternative strategies or modify existing ones to achieve better results. This study applied model-based optimization using an ASPEN Plus simulator and Multi-objective Ant Lion Optimization (MOALO) to address the issue. The results revealed the highest conversion and product rate, with the lowest energy cost, side product, and bare module cost, CBM. The decision variable plots indicate that the reactor’s pressure significantly affects the optimal solution. This study provides valuable insight into optimizing CH3OH production.

Differential Game Theory in Electric Vehicle Charging Optimization

Differential Game Theory is a strong way to solve the hard optimization problems that come up when charging electric vehicles (EVs) in smart grids. This method takes into account the strategic exchanges between many parties, such as EV users, charging station operators, and grid operators, each of whom has their own goals. In this study, we look at how differential game theory can be used to find the best charging plans for electric vehicles. Our goal is to lower total energy costs, make the grid less crowded, and get more energy from green sources. We take into account how power prices change, the different types of green energy that are available, and how EVs move around by modeling the charging process as a difference game. The game-theoretic method lets you come up with plans where each player maximizes their own reward while taking into account what other players do. To find the best price methods for different situations, such as peak and off-peak hours, different amounts of green energy usage, and different pricing plans, we use Nash equilibrium solutions. Our findings show that differential game theory can successfully balance the different needs of parties, which can lead to EV charging systems that work better and last longer. Furthermore, the suggested way not only makes smart grids work better, but it also helps lower carbon emissions by supporting the use of clean energy. In addition, this method helps us understand how to create reward systems that match individuals' goals with world improvement goals. This makes it possible for EV charging strategies to work together better. This study shows that differential game theory could be a very useful tool in the development of smart and environmentally friendly transportation systems.

Basics and Advances of Manganese-Based Cathode Materials for Aqueous Zinc-Ion Batteries.

It is greatly crucial to develop low-cost energy storage candidates with high safety and stability to replace alkali metal systems for a sustainable future. Recently, aqueous zinc-ion batteries (ZIBs) have received tremendous interest owing to their low cost, high safety, wide oxidation states, and sophisticated fabrication process. Nanostructured manganese (Mn)-based oxides in different polymorphs are the potential cathode materials for the widespread application of ZIBs. However, Mn-based oxide materials suffer from several drawbacks, such as low electronic/ionic conductivity and poor cycling performance. To overcome these issues, various structural modification strategies have been adopted to enhance their electrochemical activity, including phase/defect engineering, doping with foreign atoms (e.g., metal and/or nonmetal atoms), and coupling with carbon materials or conducting polymers. Herein, this review targets to summarize the advantages and disadvantages of the above-mentioned strategies to improve the electrochemical performance of the cathodic part of ZIBs. The challenges and suggestions for the development of manganese oxides for ZIBs are put forward.

Iodine Boosted Fluoro-Organic Borate Electrolytes Enabling Fluent Ion-Conductive Solid Electrolyte Interphase for High-Performance Magnesium Metal Batteries.

Rechargeable magnesium batteries are regarded as a promising multi-valent battery system for low-cost and sustainable energy storage applications. Boron-based organic magnesium salts with terminal substituent fluorinated anions (Mg[B(ORF)4]2, RF=fluorinated alkyl) have exhibited impressive electrochemical stability and oxidative stability. Nevertheless, their deployment is hindered by the complicated synthesis routes and the surface passivation of Mg metal anode. Herein, we report the design of an advanced electrolyte formulation comprised of tri(hexafluoroisopropyl) borate (B(HFIP)3) and iodine (I2) in 1,2-dimethoxyethane (DME) solvent, which eventually convert into a Mg[B(HFIP)4]2/DME-MgI2 electrolyte system upon interacting with Mg anode. The Mg anode reacts with I2 and the electron-accepting B(HFIP)3, leading to the in situ formation of a solid-electrolyte interphase layer composed of MgF2 and MgI2 species that can facilitate fast and stable Mg plating/stripping. Compared with the pristine Mg[B(HFIP)4]2/DME electrolyte, the Mg[B(HFIP)4]2/DME-MgI2 electrolyte exhibited superior electrochemical performance including an ultra-low overpotential (~80 mV), high Coulombic efficiency and a long-cycling period over 1500 h. In result, the rechargeable magnesium batteries with Mg[B(HFIP)4]2/DME-MgI2 electrolyte and Chevrel-phase Mo6S8 cathode show outstanding compatibility, rapid kinetics, and stable cyclability for over 1200 cycles, surpassing all previously reported boron-based electrolytes. This work introduces a promising halogen-enhancement strategy for boron-based Mg-ion electrolytes, with the overarching goal of establishing favorable solid-electrolyte interphases that are pivotal for the advancement and optimization of multi-valent secondary batteries.

A tripartite synergistic optimization strategy for zinc-iodine batteries

The energy industry has taken notice of zinc-iodine (Zn-I2) batteries for their high safety, low cost, and attractive energy density. However, the shuttling of I3− by-products at cathode electrode and dendrite issues at Zn metal anode result in short cycle lifespan. Here, a tripartite synergistic optimization strategy is proposed, involving a MXene cathode host, a n-butanol electrolyte additive, and the in-situ solid electrolyte interface (SEI) protection. The MXene possesses catalytic ability to enhance the reaction kinetics and reduce I3− by-products. Meanwhile, the partially dissolved n-butanol additive can work synergistically with MXene to inhibit the shuttling of I3−. Besides, the n-butanol and I− in the electrolyte can synergistically improve the solvation structure of Zn2+. Moreover, an organic-inorganic hybrid SEI is in situ generated on the surface of the Zn anode, which induces stable non-dendritic zinc deposition. As a result, the fabricated batteries exhibit a high capacity of 0.30 mAh cm−2 and a superior energy density of 0.34 mWh cm−2 at a high specific current of 5 A g−1 across 30,000 cycles, with a minimal capacity decay of 0.0004% per cycle. This work offers a promising strategy for the subsequent research to comprehensively improve battery performance.

Electrolyte Design Enables Stable and Energy-Dense Potassium-Ion Batteries.

Free from strategically important elements such as lithium, nickel, cobalt, and copper, potassium-ion batteries (PIBs) are heralded as promising low-cost and sustainable electrochemical energy storage systems that complement the existing lithium-ion batteries (LIBs). However, the reported electrochemical performance of PIBs is still suboptimal, especially under practically relevant battery manufacturing conditions. The primary challenge stems from the lack of electrolytes capable of concurrently supporting both the low-voltage anode and high-voltage cathode with satisfactory Coulombic efficiency (CE) and cycling stability. Herein, we report a promising electrolyte that facilitates the commercially mature graphite anode (>3 mAh cm-2) to achieve an initial CE of 91.14 % (with an average cycling CE around 99.94 %), fast redox kinetics, and negligible capacity fading for hundreds of cycles. Meanwhile, the electrolyte also demonstrates good compatibility with the 4.4 V (vs. K+/K) high-voltage K2Mn[Fe(CN)6] (KMF) cathode. Consequently, the KMF||graphite full-cell without precycling treatment of both electrodes can provide an average discharge voltage of 3.61 V with a specific energy of 316.5 Wh kg-1-(KMF+graphite), comparable to the LiFePO4||graphite LIBs, and maintain 71.01 % capacity retention after 2000 cycles.

Further experimental analysis of undershot water wheels towards the development of a prototype model

ABSTRACT The current research aims to analyse the effect of the number and shape of the blades and the curvature of the flume bottom on the performance curves of undershot water wheels, based on experimental tests conducted in a fully instrumented laboratory facility. Six wheels are tested: four wheels with plane blades (16, 24, 36, 48) and two with 24 curved blades for two flume bottom configurations. Torque, mechanical power and mechanical efficiency performance curves are determined for several rotational speed and flow rate values. Results demonstrate that the maximum efficiency is achieved for the 36-plane blade wheel, the curved flume bottom reduces water losses under the wheel and increases efficiency, and the blades’ shape strongly influences the wheel efficiency. Non-dimensional performance curves are provided to generalise the results. This research provides relevant contributions towards the development of a low-cost energy recovery solution to be applied in water infrastructures.

Time-optimal control of a solid-state spin amidst dynamical quantum wind

Time-optimal control holds promise across the full spectrum of quantum technologies, where the rapid generation of unitary gates and state transformations is crucial to mitigate decoherence effects. In practical scenarios, quantum systems are always immersed in an external time-dependent field or potential, either owing to the inevitable influence of the environment or as a sought-after effect for enhanced coherence. The challenge then lies in finding the time-optimal approach to navigate quantum systems amidst dynamical ambient Hamiltonians, a pursuit that has proven elusive thus far. We showcase the implementation of arbitrary quantum state transformations and a universal set of single-qubit gates under a background Landau-Zener Hamiltonian. Leveraging the favorable coherence properties of timedomain Rabi oscillations, we achieve velocities surpassing the Mandelstam-Tamm quantum speed limit and significantly lower energy costs than those incurred by conventional quantum control techniques. These findings highlight a promising pathway to expedite and economize high-fidelity quantum operations.

Effect of the microwave treatment on anti-nutrients of soybeans

BACKGROUND: Soybeans contain anti-nutrients that have to be inactivated before being used as feed for livestock and poultry. AIM: Obtaining the new data on the effect of the heat treatment on soybeans. MATERIALS AND METHODS: Soybeans of the Dongsheng 22 and SK Alta varieties were processed with micronization, autoclaving and microwaves in the developed microwave unit. RESULTS: After micronization, the decrease in total starch was 10–16%, after autoclaving and microwave treatment — 15–17%. The three kinds of treatment did not have a significant effect on total phenolic content. The content of flavonoids increased by 7–9% after autoclaving and micronization and by 16% after microwave treatment. When micronizing and autoclaving soybeans, no changes in antioxidant activity were observed, but with microwave treatment, it increased by 3–5%. The decrease in trypsin inhibitor activity was 80% after microwave treatment and 73–79% after micronization and autoclaving. The tannin content was reduced by 10% with microwave treatment and by 7–9% after micronization and autoclaving. The decrease in phytic acid content was 43–45% and repeated for all kinds of treatment. CONCLUSION: The reduction of antinutrients after micronization, autoclaving and microwave processing ensures the use of soybeans for feed. Milder temperature conditions and cyclic processes of heating and cooling during microwave processing increase the safety of soybeans. The higher heating rate and low energy costs of microwave processing ensure economic feasibility.

Construction of Nano ZnV2O4/N‐Doped Porous Carbon Composites with Optimized Ionic and Electronic Conductivities as Competitive Cathodes toward Zinc‐Ion Capacitors

AbstractZinc‐ion capacitors (ZICs) have great potential for energy storage applications due to high safety, environmental friendliness, low cost, and high energy density. However, challenges such as poor ion diffusion kinetics and the low conductivity of cathode materials still need to be addressed. Nano ZnV2O4/nitrogen‐doped porous carbon (ZVO/N‐PC) composites are efficiently synthesized via a simple annealing process. Highly crystalline ZVO nanoparticles are in‐situ grown on the three‐dimensional N‐PC surface by precisely tuning the ratio of the vanadium source, achieving a dual enhancement in electronic and ionic conductivities. Benefiting from the nanoengineering build‐up, the optimized ZVO‐0.6/N‐PC anode exhibits impressive rate performance (405.9/308.8 mAh g−1 at 0.2/5.0 A g−1) and cycling capability (0.0029 % capacity drop per cycle at 5.0 A g−1 after 5,800 cycles). Using nitrogen‐doped porous activated carbon (N‐PAC) as the anode and ZVO‐0.6/N‐PC as the cathode, the assembled ZICs deliver a high energy density of 27.5 Wh kg−1 at a power density of 450.0 W kg−1. After 10,000 cycles at 1.0 A g−1, the capacity retention rate remains as 72.8 %, demonstrating excellent cycling stability. This highlights the promising application of nano ZVO/N‐PC composites towards ZICs as competitive cathodes.