Efficient Performance Research Articles

Composite Structure MgB2@KNO3 With Multi-Effect Synergies to Improve Combustion Performance and Energy Release of B

ABSTRACT With the deepening of research, boron compounds have gradually gained favor among researchers due to their high calorific value and excellent ignition and combustion performance. In this paper, MgB2@KNO3, which exhibits excellent ignition and combustion properties, was synthesized using ultrasonic dispersion and magnetic stirring. The improved ignition mechanism and energy release characteristics of MgB2@KNO3 were elucidated using DSC/TG, SEM, EDS, XRD, and optical characterization, in conjunction with computational results from NASA-CEA. The surface activation energy and ignition energy of MgB2@KNO3 are 35.7% and 25%, respectively, lower than those of conventional B/KNO3 mixtures. Compared to the mixed sample of B/KNO3, the heat release of MgB2@KNO3 increased by 72.4%. The synergistic and effective interactions between oxygen, magnesium vapor, and boron in MgB2@KNO3 systems result in efficient energy release performance, making MgB2@KNO3 a promising material for use as a high-energy fuel in propellants, explosives, and pyrotechnic products.

Performance Assessment of Branch Office Assistant (KCP) Leaders Using the Simple Additive Weighting Method

Abstract— Performance Appraisal is a process that allows organizations to know, evaluate, measure and assess the performance of their members appropriately and accurately. This activity is closely related and influences the effectiveness of the implementation of human resource activities in the company, such as promotion, compensation, training, career management development and others. This is because the performance appraisal function can provide important information to the company to improve decisions and provide feedback to employees about their actual performance.The implementation of the achievement and performance appraisal of KCP leaders at KSPPS Tunas Artha Mandiri Nganjuk Branch has so far still used manual and has not used a decision support sistem so that the data generated is not accurate and takes a long time. As a result, if used in decision making, it is not appropriate and causes problems such as non-transparent management, decreased quality and performance of KCP leaders. The author applies and implements the Additive Weighting method (SAW) to measure the achievement and performance assessment of the Sub-Branch Office leadership at KSPPS Tunas Artha Mandiri Nganjuk Branch. With the aim of this decision support sistem can provide information and recommendations as well as accurate and efficient performance appraisal data.Keywords-Decision Support Sistem, Simple Additive Weighting, Employee Appraisal

The Influence of Efficient Performance Evaluation on Worker Productivity: A Secondary Data Analysis

Performance evaluation has been an essential tool for organizational effectiveness, in which employee efforts are aligned with the organizational goals. However, the connection between the efficiency of performance evaluation systems and worker productivity has not been well examined over the past years. This study aims to analyse the impact of efficient performance evaluation on worker productivity based on secondary data from different academic journals, organizational reports, and case studies. By analysing already conducted research on performance evaluation processes, this paper addresses how performance evaluation processes do result in productivity, enhanced engagement among employees, and the resultant success of organisations.

High-Performance Silicone Sponge Evaporators with Low Thermal Conductivity for Long-Term Solar Interfacial Evaporation and Freshwater Harvesting.

Solar interfacial evaporation (SIE) has emerged as a highly promising approach for sustainable freshwater harvesting. However, maintaining a stable evaporation rate and achieving a high freshwater yield in high-salinity brines remain a significant challenge. In this study, we present the development of silicone sponge-based evaporators with a "free-salt" structure, designed to enhance the efficiency of SIE and freshwater collection. These evaporators, designated as PSS@Fe3O4/CNTs, were fabricated by grafting durable silicone onto a silicone sponge framework, followed by the incorporation of Fe3O4 nanoparticles and carbon nanotubes. The unique combination of exceptional photothermal properties and a controlled yolk-shell structure with low thermal conductivity enabled the PSS@Fe3O4/CNT evaporators to sustain a stable evaporation rate of 1.87 kg m-2 h-1 in real seawater over 200 h of continuous operation under 1 sun illumination. Importantly, no salt accumulation was observed on the evaporator surfaces, even when exposed to highly concentrated brines. In a closed system equipped with a condenser, these evaporators achieved freshwater production rates of 14.5 and 11.8 kg m-2 over 10 h from 10 and 20 wt % NaCl solutions, respectively, under 1 sun illumination. These values correspond to normalized production rates of 1.45 and 1.18 kg m-2 h-1, showcasing the consistent and efficient performance of the evaporators across varying salinity levels. Beyond salt rejection, the PSS@Fe3O4/CNT evaporators also demonstrated the ability to effectively remove various heavy metal ions (e.g., Cu2+ and Zn2+) and organic pollutants from contaminated water. This work provides valuable insights into innovative evaporator designs for efficient freshwater production from seawater and wastewater.

Minimizing Communication Overhead in Decentralized Deep Neural Networks

Minimizing communication overhead in decentralized deep neural network (DNN) training has become a critical challenge, particularly with the increasing adoption of distributed systems for large-scale machine learning tasks. This paper introduces advanced techniques that leverage gradient compression, adaptive sparsification, and hybrid aggregation to optimize communication efficiency while maintaining model accuracy and convergence rates. Experimental results on benchmark datasets such as CIFAR-10 and ImageNet show that the proposed methods reduce communication costs by up to 70% compared to standard approaches while achieving comparable or superior model accuracy. Additionally, scalability tests on diverse neural network architectures highlight the robustness of the approach, demonstrating efficient performance across varying network sizes and computational setups. These findings underscore the potential of the proposed strategies to enable faster, cost-effective, and sustainable decentralized deep learning systems.

Control of arsenic methylation in paddy soils by iron nanoparticles

Rice, as the most essential food grain, is frequently exposed to high concentrations of arsenic. Among the arsenic species, dimethylarsenate (DMAs(V)) is preferentially translocated from paddy soils to rice grains, posing serious threats to food safety and yield. Herein, we report an efficient strategy for DMAs(V) mitigation in paddy soils with nanoscale Zero-Valent Iron (nZVI). Species and concentrations of arsenic in paddy porewater were monitored during a 28-d soil-water incubation. Effects of nZVI dose towards microbial sulfate reduction and methane generation potential in paddy soils, which are crucial for arsenic methylation and demethylation, were analyzed via metagenomic sequencing. Results demonstrated that the maximal DMAs(V) concentration in paddy porewater decreased from 0.37 to 0.04 μM in arsenic-contaminated paddy soils with nZVI dose increasing from 0 to 5.0 g/kg. Accordingly, the maximal concentration of inorganic arsenite (iAs(III)), which is the precursor of DMAs(V), decreased from 1.39 to 0.23 μM. Furthermore, the application of nZVI reshaped the structure of microbial community in paddy soils. Specifically, the relative abundance of δ-proteobacteria involved in sulfate reduction, which is crucial for iAs(III) methylation, waned from 7.62 % to 3.17 %, while that of Methanomicrobia for DMAs(V) demethylation and methanogenesis proliferated from 7.03 % to 13.62 %, with nZVI dose increasing from 0 to 5.0 g/kg. Via simultaneous inhibition of DMAs(V) formation and acceleration of DMAs(V) transformation, nZVI efficiently controls the accumulation of DMAs(V) in paddy porewater. In conclusion, these findings prove the efficient performance for DMAs(V) mitigation with nZVI and uncover its underlying mechanisms.

Safety-enhanced control for a MuscleDrive waist-assistive exoskeleton

This study introduces the MuscleDrive Powered Waist-Assistive Exoskeleton (PWE), which is specifically designed with comprehensive safety features in both its hardware and software components. The hardware of the MuscleDrive PWE incorporates fluidic muscle actuators (FMAs) to improve mechanical compliance, taking advantage of their lightweight and elastic properties. The software component features an innovative control system that utilizes the PSTC-RLESO controller. This controller ensures precise and reliable torque trajectory tracking during normal operation and facilitates smooth, safe recovery from significant torque errors during abnormal interactions. Using the Lyapunov stability theorem, this study demonstrates that the closed-loop states of the MuscleDrive PWE with PSTC-RLESO are globally uniformly ultimately bounded (UUB). Experimental comparisons between PSTC-RLESO and a PID controller show that PSTC-RLESO significantly enhances safety during MuscleDrive PWE operation while maintaining efficient tracking performance. In the experiments, safety performance is assessed through damping injection by PSTC-RLESO. Additionally, tests conducted on seven healthy subjects indicate that the MuscleDrive PWE provides adequate torque assistance and ensures user safety, as evidenced by surface electromyography (sEMG) da ta and questionnaire responses.

A Knowledge-Based Molecular Single-Source Precursor Approach to Nickel Chalcogenide Precatalysts for Electrocatalytic Water, Alcohol, and Aldehyde Oxidations.

The development and comprehensive understanding of nickel chalcogenides are critical since they constitute a class of efficient electro(pre)catalysts for the oxygen evolution reaction (OER) and value-added organic oxidations. This study introduces a knowledge-based facile approach to analogous NiE (E = S, Se, Te) phases, originating from molecular β-diketiminato [Ni2E2] complexes and their application for OER and organic oxidations. The recorded activity trends for both target reactions follow the order NiSe > NiS > NiTe. Notably, NiSe displayed efficient performance for both OER and the selective oxidation of benzyl alcohol and 5-hydroxymethylfurfural, exhibiting stability in OER for 11 days under industrially pertinent conditions. Comprehensive analysis, including quasi in situ X-ray absorption and Raman spectroscopy, in combination with several ex situ techniques, revealed a material reconstruction process under alkaline OER conditions, involving chalcogen leaching. While NiS and NiSe experienced full chalcogen leaching and reconstruction into NiIII/IV oxyhydroxide active phases with intercalated potassium ions, the transformation of NiTe is incomplete. This study highlights the structure-activity relationship of a whole series of analogous nickel chalcogenides, directly linking material activity to the availability of active sites for catalysis. Such findings hold great promise for the development of efficient electrocatalysts for a wide range of applications, impacting various industrial processes and sustainable energy solutions.

Efficient and verifiable keyword search over public-key ciphertexts based on blockchain

Public-key encryption with keyword search (PEKS) is a powerful cryptographic primitive that enables a receiver to search keywords over ciphertexts hosted on an honest-but-curious server in the asymmetric-key setting while hiding the keywords from the server. Many researchers have devoted their efforts to achieving expressive search, security against keyword guessing attacks, and efficient search performance. However, until now, no effective PEKS scheme can achieve verifiable search completeness in the standard PEKS security model. In practice, the server may intentionally or unintentionally lose the receivers’ data. Hence, verifiable search completeness is essential for receivers to audit the service quality of the server. To address this problem, this work develops a blockchain-based PEKS framework. This framework only utilizes the distributed ledger role of the blockchain, making it general. Additionally, we find that existing PEKS schemes cannot be efficiently deployed into the framework due to the inefficient use of randomness, which increases the ciphertext sizes. To tackle this problem, we utilize randomness reuse technique to propose a novel PEKS scheme. The proposed scheme achieves linear search complexity with respect to the total number of files in the dataset. To demonstrate the efficiency of our scheme, we perform comprehensive experiments to evaluate it and three other state-of-the-art schemes. The experimental results show that our PEKS scheme is superior to existing PEKS schemes in both the encryption and search phases and significantly reduces the sizes of generated ciphertexts.

Optimization of High-Performance Computing Job Scheduling Based on Offline Reinforcement Learning

In large-scale, distributed high-performance computing systems, the increasing complexity of job scheduling has expanded along with the growth of computational resources and job diversity. While heuristic scheduling strategies with various optimization objectives have shown promising results, their effectiveness is often limited in real-world applications due to the dynamic nature of workloads and system configurations. Deep reinforcement learning (DRL) methods offer the potential to address scheduling challenges. However, their trial-and-error learning approach can lead to suboptimal performance or resource wastage in the early stages. To mitigate these risks, this paper introduces an offline reinforcement learning-based job scheduling method. By training on historical data, the method avoids the pitfalls of deploying immature strategies in live environments. We constructed an offline dataset by combining expert scheduling trajectories with early-stage trial data from online reinforcement learning. This enables the development of more robust scheduling policies. Experimental results demonstrate that, compared to heuristic and online DRL algorithms, the proposed approach achieves more efficient scheduling performance across various workloads and optimization goals, showcasing its practicality and broad applicability.

Mechanisms of Low Temperature Thickening of Different Materials for Deepwater Water-Based Drilling Fluids

During deepwater drilling, the low mudline temperatures and narrow safe density window pose serious challenges to the safe and efficient performance of deepwater water-based drilling fluids. Low temperatures can lead to physical and chemical changes in the components of water-based drilling fluids and the behavior of low temperature gelation. As a coarse dispersion system, water-based drilling fluid has a complex composition of dispersed phase and dispersing medium. Further clarification of low temperature gelation would be helpful in developing technical approaches to enhance the flat rheology performance of deepwater water-based drilling fluids. In this paper, different components are separated in order to comprehensively analyze the gelation behavior of different materials in water-based drilling fluids at low temperatures. In the first place, the rheological and hydrodynamic radius alterations of inorganic salts, bentonite, and additives in aqueous solutions were examined at low temperatures. The effects of inorganic salts, bentonite, and additives on the purified water system were investigated at low (4 °C)–normal (25 °C)–high (75 °C) temperatures. The low temperature gelation of different materials in pure water systems are fully clarified. The mud containing 4% bentonite with weak low temperature gelation commonly used in deepwater water-based drilling fluids was selected as the basic test system. Inorganic salts, additives, and solid-phase materials were added to the mud containing 4% bentonite. The effects of the interactions between different materials and bentonite particles on the low temperature gelation behavior of mud were analyzed. The higher the bentonite dosage, the stronger the low temperature gelation behavior of mud. The higher the addition of inorganic salts, the more serious the low temperature gelation behavior of mud. Inorganic salts should be avoided as much as possible to add too much. The low temperature gelation behavior of mud with low-viscosity additives is weak. However, the viscosity of mud with high-viscosity additives has a small change in viscosity with increasing temperature. The low temperature gelation of mud with the addition of solid-phase particulate materials with reactive groups on the surface is strong, and the low temperature gelation with the addition of inert particles is weak. This paper elucidates the low temperature gelation mechanism of bentonite, inorganic salts, additives, and solid-phase materials in deepwater water-based drilling fluids. The conclusion can also be used to guide the construction of a drilling fluid system, which is of great significance for the research and development of deepwater water-based drilling fluid additives and the safe and efficient performance of deepwater drilling fluids.

Efficient hybrid supercapacitor performance enabled by large surface area of 2D mesoporous zinc sulfide nano-sheets synthesized via microwaves

Researchers have shown a significant amount of interest in synthesizing high energy density supercapacitors using a simplest, fast, and low cost technique. The electrochemical performance of supercapacitors can be impacted by the surface area and morphology of electrode materials. A one-step, rapid, and economical microwave-assisted synthesis technique was employed in this study in order to prepare mesoporous nanosheets that are composed of zinc sulfide. The ZnS-based nanosheets possess a large surface area of ∼120 m2g−1 and a mesoporous structure of a pore diameter of <22 nm, which offers numerous electrochemical active sites and it facilitates an excellent super capacitive performance, which is due to its shortened ion/electron diffusion path. The prepared mesoporous nanosheets exhibit a higher specific capacitance of 2282 Fg−1 (1037 C/g) when subjected to a 1 Ag−1 in 2 M KOH aqueous electrolyte with high capability rate. The fabricated device exhibits a high specific capacitance of 252.5 Fg−1 (140 C/g) at 1 Ag−1, which produces a remarkable energy density of about 90 Whkg−1 at 800 Wkg−1 value of power density and an excellent retention of ∼95 % after 10,000 cycles at 6 Ag−1. This study designed an instant, straightforward and low-cost approach to fabricate ZnS nanosheet electrode materials that exhibit excellent performance for supercapacitor applications.

Biomass-based MnO2 Composite for Efficient Microwave Absorption Performance: Strong Interfacial Polarization and Electron Transition Effects

In this study, we explored the effectiveness of enhancing microwave absorption capabilities of biomass-derived porous carbon by introducing MnO2 through thermochemical techniques. The results showed that the MnO2-C exhibited higher values in both the real and imaginary parts of the dielectric constant compared to the Control, indicating that the addition of MnO2 significantly enhanced the energy storage and dissipation capabilities. Although the magnetic loss properties of the composite were relatively weak, the increase in conductive and dielectric losses compensated for this aspect. Moreover, the loading of MnO2 optimized the dielectric losses and promoted the reconstruction of charge, enabling MnO2-C to demonstrate superior microwave absorption performance, particularly in the high-frequency range. This is attributed to the multiple polarization mechanisms present in MnO2-C, including interfacial and dipolar polarization, which play a crucial role in enhancing dielectric losses. Additionally, a multilevel porous structure significantly enhanced the scattering and reflection of microwaves, further improving the absorption effectiveness. Consequently, these characteristics contribute to the MnO2-C achieving a minimum reflection loss value of -46.2dB and an expanded effective absorption bandwidth. Overall, the MnO2-C composite, with its optimized electromagnetic properties and complex microstructure, provides valuable insights for the development of new, highly efficient microwave absorption materials.

MgCl2-facilitated synthesis and highly efficient oxygen reduction performance of Ta3N5/C catalyst

Transition metal nitrides (TMNs) are considered potential candidates for the oxygen reduction reaction (ORR) in metal batteries. Herein, we report a novel Ta3N5/C catalyst that was prepared using MgCl2—a component that could modulate the electronic structure and geometry and induce Ta-N bond formation, as suggested by density functional theory (DFT) calculations. The prepared Ta3N5/C catalyst exhibits good ORR performance in alkaline electrolytes, and has a higher stability (ΔE1/2= −17mV) after the 2000-cycle accelerated degradation test and a significantly enhanced methanol resistance compared to a 20% Pt/C catalyst or Ta2O5/NC. DFT calculations indicate that Ta3N5 has a smaller band gap and larger d-electron distribution compared to Ta2O5 catalysts. These features ensure an outstanding conductivity and a fast-electron-transfer ability during the ORR. This work provides new strategies for designing novel electrocatalysts for metal batteries.

Highly Efficient Aggregation-induced Electrochemiluminescence Performance of Covalent Organic Frameworks with Electron-rich Conjugated Structures.

Since aggregation-induced electrochemiluminescence (AIECL) luminophore overcomes the restriction of aggregation-caused quenching in solid luminescent materials, AIECL luminophore has become a promising material in the field of electrochemiluminescence (ECL) engineering. However, the lack of ECL emitters with high AIECL performance limits its wide application. Herein, imine-linked covalent organic frameworks (COFs) with C4 symmetrical tetraphenyl ethylene and C2 symmetrical five-membered heteroaromatic monomers are designed as ECL emitter in aqueous media. Significantly, the ECL intensity of COFs with terthienyl units (TTA-TAPE) is 206 times that of COFs with furan units in the presence of tri-n-propylamine (TPrA), which is the result of enhancing ECL signals by increasing the thiophene units and π-π conjugation of COFs. Furthermore, the ECL mechanism of these COFs is vested in the bandgap model. Thus, the study provides a strategy for designing highly efficient ECL-active COFs emitters with excellent AIECL efficiency.

Efficient conversion CuCl phase and improvement anti-corrosion performance of bronze via L-arginine: performance and mechanism study

Efficient conversion CuCl phase and improvement anti-corrosion performance of bronze via L-arginine: performance and mechanism study

Optimal planning for high renewable energy integration considering demand response, uncertainties, and operational performance flexibility

The operational performance of the grid needs to be considered and incorporated with other verified system flexibility measures, such as energy storage system and demand response, when planning a hybrid renewable energy system with a high fraction of renewable energy sources. Therefore, this study developed an integrated model that considers the effects of time-of-use demand response and risk-based uncertainty analysis on the operational performance of a grid-connected hybrid energy system for high renewable power penetration. A multi-stage approach for optimal scheduling of the energy systems with time-of-use pricing considering uncertainties’ impacts on grid and energy storage systems operations is modeled. Techno-economic metrics are developed to assess the decision-making effectiveness of the energy system planning and grid operation under four scenarios based on the information gap decision theory to quantify the energy system and grid operation performance flexibility. The considered scenarios are without and with demand response using risk-neutral, risk-averse, and risk-seeking strategies. The analysis of the results indicates that the risk-averse approach achieves the best techno-economic tradeoff, guaranteeing improved technical performances compared to the other risk strategies for uncertainty management in renewable power outputs and grid operational performances within the cost deviation tolerance limit. The risk-averse strategy further justified the substantial inclusion of energy storage and the adoption of the demand response to provide better operational flexibility to ensure improved grid performance, as seen in the reduced grid loss and improved voltage profile with higher power contribution from the RES. Significantly, the considered model can help system planners manage the tradeoff for efficient system performance under substantial renewable energy integration, considering the impacts of uncertainties.

Orange peel derived activated carbon supported Ni–Co3O4 as an efficient electrocatalyst for oxygen evolution and reduction reaction in alkaline media

This study focuses on the development of a cost-effective electrocatalyst with excellent activity and stability for the oxygen evolution reaction (OER) and the oxygen reduction reaction (ORR), which is crucial for water electrolysis and fuel cell technologies. Waste orange peel is utilized as a carbon precursor to synthesize biomass-derived activated carbon (OPAC) with a unique three-dimensional sheet-like microstructure. Subsequently, a simple hydrothermal method is employed to modify the OPAC by introducing Ni-doped Co3O4, leading to the formation of a Ni–Co3O4/OPAC hybrid. We propose the Ni–Co3O4/OPAC hybrid as a highly efficient bifunctional electrocatalyst for both OER and ORR. Co3O4/OPAC and Co3O4 catalysts are also prepared for comparison. Remarkably, the Ni–Co3O4/OPAC hybrid exhibits significantly enhanced OER activity compared to Co3O4/OPAC and Co3O4 catalysts. It demonstrates a lower overpotential of 360 mV and a lower Tafel slope of 55.47 mV/dec, indicative of more efficient electrochemical performance. Moreover, in the ORR analysis, the Ni–Co3O4/OPAC hybrid displays a two-step pathway and achieves a higher ORR limiting current density compared to the Co3O4/OPAC and Co3O4 catalysts. These results highlight the synergistic effects of Ni and Co species, along with the unique properties of the OPAC support, which contribute to the enhanced activity, stability, and electron transfer characteristics of the Ni–Co3O4/OPAC hybrid. Furthermore, the improved electrical conductivity of the Ni–Co3O4/OPAC hybrid makes it a promising candidate for applications in metal-air batteries and other energy conversion devices. The utilization of waste orange peel as a carbon precursor and the facile synthesis method demonstrate the potential for cost-effective and sustainable electrocatalyst production. Overall, the Ni–Co3O4/OPAC hybrid represents a significant advancement in electrocatalyst design and holds promise for advancing the field of energy conversion and storage.

A new approach for global and multi-objective optimization of fin and tube heat exchanger

Fin and tube heat exchangers (FTHEs) are widely used in buildings for various heating, ventilation, and air conditioning (HVAC) applications due to their efficiency and compact design. Optimizing the design of FTHEs for building applications can bring numerous advantages in terms of energy efficiency, performance, and overall cost-effectiveness. For this purpose, this paper introduces the Multi-Objective Set Trimming (MOST) algorithm, a robust and global optimization approach applied to the optimization of a fin and tube heat exchanger. The study compares the results obtained using MOST with the well-known semi-stochastic method, Multi-Objective Particle Swarm Optimization (MOPSO), and an exhaustive search, considering both computational time and convergence. The optimization focuses on two objectives: effectiveness and annual cost, considering eight design parameters related to heat exchanger geometry. Six different cases with varying mass flow rates on both the hot and cold sides are investigated. Results reveal that the Pareto optimal fronts achieved with MOPSO are entirely dominated by those obtained using MOST across all studied cases. Additionally, MOST improves the annual cost for the best economic solution by up to 10.69% compared to MOPSO, and effectiveness is enhanced by up to 1.95%. Notably, the computational time is significantly reduced with MOST, ranging from 49.36% to 97.49% compared to MOPSO across different cases. As a result, the implemented method provides highly effective tools for optimizing the FTHE, ensuring both fast convergence and efficient computational performance.

Novel MOF-derived hexagonal starfish-shaped hollow prismatic cone-loaded metal complexes for electrocatalytic water decomposition study

Exploring efficient and stable bifunctional electrocatalysts for oxygen evolution reaction/hydrogen evolution reaction (OER/HER) is an urgent need and challenge for sustainable energy. Non-noble metal-based catalysts have attracted more and more attention due to their low cost and high catalytic performance. The construction of heterostructures is considered to be one of the most promising strategies for revealing the efficient performance for OER and HER. As a result, we prepared a nanomaterial catalyst based on the combination of three non-precious metals, which were simultaneously used for efficient OER, HER and integral water splitting techniques. We first prepared a very novel hollow hexagram star-shaped metal-organic frameworks (MOFs) by a one-step hydrothermal method, then used it as the substrate material, introduced Mo6+ and Fe3+ through ion exchange reaction, and finally formed a composite system of Co3Fe7 and Mo2C through high-temperature calcination, and the product with hexagonal starfish morphology was named as hexagonal starfish-shaped hollow prismatic cone-loaded metal complexes (HSHP-Mo2C/Co3Fe7). Taking advantage of the synergistic effect of the Co3Fe7 site and the Mo2C site, HSHP-Mo2C/Co3Fe7 not only exhibit excellent OER and HER properties, but also exhibit good stability and durability. Specifically, the optimal catalyst HSHP-Mo2C/Co3Fe7-1 shows a Tafel slope of only 46mV dec-1 for OER and 99mV dec-1 fort HER, an overpotential of only 324 and 371mV and the stability is even up to 60h. This work provides a promising strategy for the development of cost-effective, efficient and stable catalysts for energy area.