Desirable Performance Research Articles

Mixformer: Mixture transformer with hierarchical context for spatio-temporal wind speed forecasting

Wind energy has attracted more and more attention due to its sustainability and pollution-free nature. As wind energy is highly dependent on wind speed, wind speed forecasting is of great importance for fully harvesting wind energy and ensuring the stability and reliability of wind energy systems. By accurately predicting the future wind speed, we can make efficient power schedules and consequently improve the utilization of wind power. Although existing forecasting methods have achieved satisfactory wind forecasting performance, they may still fail to discover the intricate spatio-temporal dependencies obscured in entangled patterns. To resolve this issue and further improve the prediction accuracy, we propose Mixformer, a novel mixture Transformer with hierarchical context for spatio-temporal wind speed forecasting. Mixformer first applies seasonal-trend decomposition, and then employs an MLP to predict the trend part and an attention model to predict the seasonal part. Besides, Mixformer innovatively proposes a spatio-temporal Gaussian mixture attention (ST-GMA) layer, which fuses the periodic temporal and long-term spatial context. To capture intricate long-term spatial characteristics, Mixformer extracts global information by the Dynamic Time Warping algorithm. Moreover, with the ST-GMA layer, Mixformer builds a hierarchical encoder–decoder architecture to fully utilize the context at different scales for seasonal forecasting and further enhance the spatio-temporal modeling. Empirical experiments on four real-world benchmark datasets show that Mixformer yields the lowest prediction errors with the MAE scores of 1.66, 1.68, 3.14 and 0.70 and the RMSE scores of 2.07, 2.01, 3.99 and 0.98, and improves the prediction accuracy by 8.43%, 5.36%, 4.14%, 6.57% in term of MAE scores and 9.18%, 6.92%, 4.01%, 5.75% in term of RMSE scores compared to state-of-the-art methods, which demonstrates the superiority of Mixformer. In a nutshell, Mixformer presents a promising method for spatio-temporal wind speed forecasting and may achieve desirable performance in real-world applications of wind power systems.

Graphene footprints in energy storage systems—An overview

With the nanomaterial advancements, graphene based electrodes have been developed and used for energy storage applications. Important energy storage devices like supercapacitors and batteries have employed the electrodes based on pristine graphene or graphene derived nanocomposites. This review mainly portrays the application of efficient graphene and derived nanocomposites in substantial energy storage devices (supercapacitors and Li ion batteries). The structural and physical features of graphene-based nanocomposites such as high surface area, robustness, heat stability, electron conduction, specific capacitance, charge or energy density, charge-discharge performance, capacity, cyclic stability, performance life, etc. have been found beneficial for these devices. Despite the superior nanocomposite features and ensuing high devices performance, numerous challenges need to be overcome to attain future desirable energy storage device performance.

Reactive Molecular Dynamics Simulations of Polystyrene Pyrolysis.

Polymers' controlled pyrolysis is an economical and environmentally friendly solution to prepare activated carbon. However, due to the experimental difficulty in measuring the dependence between microstructure and pyrolysis parameters at high temperatures, the unknown pyrolysis mechanism hinders access to the target products with desirable morphologies and performances. In this study, we investigate the pyrolysis process of polystyrene (PS) under different heating rates and temperatures employing reactive molecular dynamics (ReaxFF-MD) simulations. A clear profile of the generation of pyrolysis products determined by the temperature and heating rate is constructed. It is found that the heating rate affects the type and amount of pyrolysis intermediates and their timing, and that low-rate heating helps yield more diverse pyrolysis intermediates. While the temperature affects the pyrolytic structure of the final equilibrium products, either too low or too high a target temperature is detrimental to generating large areas of the graphitized structure. The reduced time plots (RTPs) with simulation results predict a PS pyrolytic activation energy of 159.74 kJ/mol. The established theoretical evolution process matches experiments well, thus, contributing to preparing target activated carbons by referring to the regulatory mechanism of pyrolytic microstructure.

The strategic role of R&D outsourcing practices and partners in the relationship between product modularization and new product development efficiency

PurposeThe study aims to explore the conditional relationships between product modularization and new product development (NPD) efficiency. It is postulated that R&D outsourcing plays an important mediating role. Furthermore, the level of competency trust is considered an essential factor in moderating the indirect effect of product modularization on NPD efficiency via R&D outsourcing practices.Design/methodology/approachDrawing on transaction cost economics theory, this study suggests a moderated mediation model that addresses how product modularization effectively promotes NPD efficiency via outsourcing practices. The hierarchical regression and PROCESS macro model were conducted to test the hypotheses based on survey data from 273 manufacturing firms in China.FindingsProduct modularization enhances NPD efficiency directly and indirectly through the external collaboration of R&D outsourcing. Furthermore, the role of product modularization in R&D outsourcing practices is more effective when the competency trust in R&D outsourcing partners is high.Originality/valueBy showing the critical role of external collaboration, this study provides valuable insights into how manufacturing firms utilize product modularization to achieve desired NPD performance more effectively.

Design of continuous-duty high-power converter for multi-purpose welding applications

One large-current high-power full-bridge DC-DC converter is often used to cater several multi-characteristic welding loads. The load could be a welding arc or a conductive molten flux. The contour of operating point (voltage-current) of each load type is different. The converter often operates under complex light-load conditions. The design of such high power continuous-duty converter needs to meet three objectives – desired control performance, high across-the-load efficiency, and superior thermal management. To address the thermal issues, this article proposes to use parallel-connected converter modules. It helps distribute the power loss over larger component base; increased surface area would assist the heat removal process. For high operating efficiency, this article proposes superior component engineering in each module. And, for high across the load efficiency, this article proposes to enable or disable an efficient converter module based on the current demand. It means each converter module is equipped to feed the connected load in stand-alone mode. For reduction of power loss, this article elaborates the role of each critical component. The distribution of heat loss would be optimally shared if the current sharing by converter modules is equal, but it needs to be compatible to the dynamic behavior of multi-input process loads. This research proposes and practically validates that single PWM-controller driven parallel-connected converter-modules are not only compatible to process dynamics, the idea would achieve proper current sharing among similar components.

Electrochemical microfluidic chip composed of a cerium oxide-reduced graphene oxide nanocomposite screen printed carbon electrode (SPCE) for the determination of flunitrazepam

Due to its long-lasting tranquilizing effect on the human body, the abusive use of flunitrazepam (FNZ) in sexual assault and robbery is commonly encountered. In this study, the assembly of a hybrid nanocomposite comprising cerium oxide (CeO2) nanoparticles and reduced graphene oxide (rGO) nanosheets onto the surface of a screen printed carbon electrode (SPCE) is presented for the sensitive determination of flunitrazepam in various beverages. The properties of the CeO2-rGO nanocomposite were evaluated using various spectroscopic and microscopic techniques, while its electrochemical properties were investigated by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). A distinct composite structure with improved current response and electron transfer properties was achieved through the judicious application of rGO nanosheets to facilitate the in situ formation and anchoring of CeO2 nanoparticles. Under optimal conditions, the CeO2-rGO modified SPCE demonstrated flunitrazepam detection to 124 nM with a sensitivity of 40 µA µM−1 cm−2 and exhibited a broad linear response in the concentration range from 0.1 to 300 µM. The quantification of flunitrazepam in spiked beverage samples using CeO2-rGO/SPCE demonstrated satisfactory recovery from 96 to108%. The functionalized sensor was further integrated into a microfluidic chip to prepare a portable flunitrazepam electrochemical platform, in which multiple samples can be processed and reliable analysis can be conducted at low sample volumes. The designed electrochemical microfluidic platform demonstrated desirable performance for flunitrazepam determination, offering a promising solution for on-site determination of illicit drugs in the field of forensic investigations.

Analytical fragility relation for buried cast iron pipelines with lead-caulked joints based on machine learning algorithms

A new numerical-based fragility relation for cast iron (CI) pipelines with lead-caulked joints subjected to seismic body-wave propagation is proposed in this article. Two-dimensional 1600-m-length finite element models for pipelines buried in sand are developed in OpenSees. Parametric analysis is performed to investigate the influence of various parameters on the damage estimates of the buried pipelines. Numerical analyses are conducted to estimate the repair rates ( RR) for CI pipelines subjected to wave propagation. The predictive model for RR is thus developed based on the numerical results and the Gaussian Process Regression approach. The model developed employs four predictor variables, namely, the peak particle velocity and wave propagation velocity along axial direction, the maximum soil shear force per unit length, and the outer diameter of pipelines, exhibiting desirable performance in terms of predictive efficiency and generalization. The performance of the developed relation is compared to several existing fragility relations. The new fragility relation can be used to estimate RR for CI pipelines with lead-caulked joints with outer diameters ranging from 169 to 1554 mm subjected to seismic body-wave propagation.

Electrolyte Engineering Empowers Li||CFx Batteries to Achieve High Energy Density and Low Self‐Discharge at Harsh Conditions

AbstractGiven its exceptional theoretical energy density (over 2000 Wh kg−1), lithium||carbon fluoride (Li||CFx) battery has garnered global attention. N‐methylpyrrolidone (NMP)‐based electrolyte is regarded as one promising candidate for tremendously enhancing the energy density of Li||CFx battery, provided self‐discharge challenges can be resolved. This study successfully achieves a low self‐discharge (LSD) and desirable electrochemical performance in Li||CFx batteries at high temperatures by utilizing NMP as the solvent and incorporating additional ingredients, including vinylene carbonate additive, as well as the dual‐salt systems formed by LiBF4 with three different Li salts, namely lithium bis(oxalato)borate, lithium difluoro(oxalato)borate, and LiNO3. The experimental results unfold that the proposed methods not only minimize aluminum current collector corrosion, but also effectively passivate the Li metal anode. Among them, LiNO3 exhibits the most pronounced effect that achieves an energy density of ≈2400 Wh kg−1 at a current density of 10 mA g−1 at 30 °C, nearly 0% capacity‐fade rate after 300 h of storage at 60 °C, and the capability to maintain a stable open‐circuit voltage over 4000 h. This work provides a distinctive perspective on how to realize both high energy density and LSD rates at high temperature of Li||CFx battery.

Influence of Instructional Resource Utilization on Kiswahili Performance in Secondary Schools in Vihiga County, Kenya

Effective utilization of instructional resources during instruction in Kiswahili subjects is crucial for the students’ academic performance. Competence in teaching and learning the Kiswahili language has been a challenge, particularly at the secondary school level. Therefore, the purpose of the study was to establish the influence of the utilization of instructional resources on students’ performance in Kiswahili secondary schools in Kenya. The specific objective was to establish the influence of teachers' level of preparedness in the utilization of instructional resources on students’ performance in Kiswahili secondary schools. The study was based on two theories: The Cone of Experience by Dale and Bates' ACTIONS Model and mixed-methods research design were adopted in the study. Stratified random sampling and purposive sampling techniques were used to select the respondents for the study. The study was conducted in public secondary schools in Vihiga County. The study sample population included 294 teachers, 367 students, 13 principals, all selected from 42 public secondary schools, and 3 Quality Assurance and Standards Officers [QASOs]. A questionnaire was used to collect information from students and teachers, while principals and QASOs were interviewed. Additionally, observation schedules and document analysis were also used to collect more data. The instruments were validated using experts’ help for content and face validity. Piloting was done in two schools where Pearson’s Product Moment Correlation Coefficient was established for reliability. The coefficients obtained were r = 0.76 for teachers’ and r = 0.81 for students’ questionnaires. Data collected during the study was analyzed using frequencies, percentages, and regression analysis. Findings of the study revealed a serious shortage of instructional resources in schools in Vihiga County, ineffective utilization of available instructional resources, and the inability of teachers to improvise alternative resources. Therefore, the study recommends that to realize the desirable performance of students in Kiswahili, all stakeholders in education in Vihiga County should make available these resources in the schools. The study findings are envisaged to guide policymakers in the formulation of policies that would ensure appropriate utilization of instructional resources for teaching Kiswahili in secondary schools.

Requirements, Objectives, Both, or Neither: How to Formulate Complex Design Problems for Innovation Contests

Abstract Technical organizations increasingly rely on innovation contests to find novel ideas for designing complex systems. These activities involve outsiders in the early stages of the design process, leading to ground-breaking designs that often surpass expectations. Here, the contest’s rules document plays a crucial role: this design artifact communicates the organization’s problem and the desired system performance to the participants—significantly impacting the resulting solutions. However, the contest’s nature amplifies the challenges of communicating complex design problems across boundaries. Existing strategies for formulating—i.e., requirement and objective allocation—might not suit this context. We developed an inductive model of their formulation process based on a multiyear field study of five complex innovation contests. We found that a formulation team (or “seeker”) balanced the need to communicate their problem in detail with the risk of excluding valuable participants. Here, they chose among three approaches—incentivize, impose, or subsume—depending on their knowledge of potential solutions and the participants’ capabilities. Notably, the seeker formulated more granularly than the literature describes, employing multiple approaches within each rules document. These findings shed light on a poorly understood aspect of innovation contests, shed new light on a longstanding debate in the engineering design literature, and guide practitioners’ formulation processes.

Towards high strengthening efficiency of equiaxed and platelet-shaped alumina reinforced zirconia ceramics with textured microstructure using DLP-based stereolithography

ZrO2–Al2O3 (ATZ) ceramics are attracting high interest in biomedical applications because of their desirable mechanical performance and biocompatibility. However, strength and toughness are mutually exclusive in structural ceramics. In this paper, based on digital light processing, novel textured ATZ ceramics with obvious crystallographic orientations were fabricated by incorporating Al2O3 platelets with a high aspect ratio and equiaxed particles into the ZrO2 matrix. The optimized fracture toughness of 16.9 ± 0.8 MPa m1/2 was achieved in the textured ATZ ceramic, which was about 67.3 % higher than non-textured ZrO2 ceramics, without sacrificing strength. The coupling toughening effects of macrolayer structure, equiaxed and platelet-shaped Al2O3 particles, and ZrO2 particles were responsible for the enhanced mechanical performance. The macroscale toughening of 3D-printed lamellar architecture led to effective energy dissipation. Additionally, the crack deflection and crack branching induced by dual-morphology Al2O3 particles, accompanied by the phase transformation of the ZrO2 matrix, were significant microscopic toughening mechanisms.

Upgrading the oxidative desulfurization performance of metal-organic frameworks with proton stimulation

The modification of metal-organic frameworks (MOFs) to achieve desirable performance is attracting extensive investigation in heterogeneous catalysis, however, exploring the potential peculiarity of pristine MOFs for targeted applications is often overlooked. In this work, we developed an efficient approach for upgrading the oxidative desulfurization (ODS) performance of Zr-MOFs with proton stimulation. The ODS performance of pristine Zr-MOFs prepared under solvothermal conditions was commonly very poor at ambient temperature but could be activated when protons were introduced. Moreover, the upgradation of ODS efficiency by protons exhibited a sharply increasing trend (from 0.05 to 17.5 mmol g−1 h−1) with the increased density of defects in Zr-MOFs. The most defective UiO-66(Zr) showed ultrahigh activity in model oil which removed 1000 ppm sulfur after 25 min at 30 °C or after 4 min at 50 °C upon proton stimulation that is better than the sample pre-treated with 1 M HCl, and in multicomponent model oil which removed 972 ppm sulfur after 20 min at 50 °C in the present of proton. The turnover frequency (TOF) could reach 211.6 h−1 at 50 °C, surpassing the most investigated ODS catalysts. Quenching experiments and EPR tests demonstrated that the reaction pathway of UiO-66(Zr) could be altered by protons from free radical (OH• and O2•-) into non-free-radical (Zr–OOH) that manipulate the sulfur removal efficiency. Experimental results indicated that the terminal Zr–OH/OH2 sites could decompose H2O2 with assistance of H+ to form Zr–OOH, which probably accounts for the enhancement of ODS activity. Our work reveals a facile and efficient strategy for upgrading the ODS performance of pristine MOFs.

Facile synthesis of ball milling and magnetization co-modified sludge-derived biochar for efficient adsorbing environmental concentration sulfamethoxazole from various waters: Performance and mechanism

The overuse of sulfamethoxazole (SMX) has caused serious damage to aquatic ecosystem and human health even at environmental concentration. In this study, various iron salts were used to functionalize sludge-derived biochar (SBC) to simultaneously boost its adsorption ability for SMX and magnetic collection performance. Afterward, ball milling was further employed to treat optimal iron salt (FeCl3▪6H2O) functionalized SBC (MSBC) for enlarging its external-internal surface area, pore volume and exposing its functional groups. Ball milling coupled FeCl3▪6H2O co-modified SBC (BMSBC) showed the desirable adsorption performance for SMX, and it was remarkably higher than those of SBC, ball milled SBC (BSBC), MSBC and other magnetization functionalized SBC. The maximum adsorption capacity of BMSBC calculated by Langmuir model was 2.24 × 104 μg/g, and it showed the optimum adsorption performance at pH = 3 and 5. The multiple physicochemical forces including π-π conjugation, pore filling, H-bonding (dipole–dipole and Yoshida), Fe-O complexation and electrostatic interactions were confirmed as the dominant driving mechanism controlling SMX adsorption onto BMSBC by adsorption models fitting, water chemistry effect experiments, characterization analysis and DFT calculation. The greater magnetic sensitivity guaranteed it was easily collected within 1 min, also was beneficial for its reuse by NaOH regeneration. The favorable adsorption ability for SMX in actual waters and good environmental safety of BMSBC allowed it to be a viable adsorbent, in addition to the disposal approach for sludge.

A running-in strategy based on an efficient wear simulation model for double circular-arc spiral bevel gears

A proper running-in process is necessary for double circular-arc spiral bevel gears to achieve desirable meshing performance. However, this type of gear transmission lacks a suitable running-in wear model, which brings great difficulties to the design of appropriate running-in strategies. To address this problem, the present study establishes an efficient numerical wear model to reveal the wear behavior of double circular-arc spiral bevel gear pairs, based on which a step-wise load running-in strategy is proposed. The established Archard's wear model considers the meshing characteristics of double circular-arc spiral bevel gears and sets a small threshold value, which can reflect the wear behavior of this gear in the running-in stage. To improve the computation efficiency, a two-step parameter updating strategy is proposed to enhance the iteration of p and s. The wear simulation reveals the quantitative relationship contact pressure and running-in cycle during the running-in process. Based on the reveal relationship, a step-wise load running-in strategy is proposed to sharpen the running-in period. The developed wear model and the proposed running-in strategy can be extended to other types of gears with circular-arc profiles.

Experimental study of a novel quasi-active negative stiffness damper system for achieving optimal active control performance

Compared to the semi-active control and passive control systems, an active control system is able to achieve the most desirable vibration control performance because of its high adaptability and capacity to directly produce the required optimal control force (ROCF). However, the disadvantages of high energy consumption and low reliability limit its wide application. To address this dilemma, a novel ‘Quasi-active’ control concept and a representative quasi-active negative stiffness damper (QANSD) system integrating a negative stiffness element and an MR damper were proposed by the authors very recently. The QANSD system has been theoretically and numerically verified to be able to fully generate the ROCF and realize active control performance with much less external power consumption than a semi-active control system. To further validate the effectiveness of the innovative concept and the proposed QANSD system, in this study, a comprehensive experimental investigation was conducted based on the developed prototype device. The fundamentals of the QANSD system including realizations and mechanical behaviours are firstly introduced, and the experimental prototype and setup are then provided. Following that, experimental tests on the QANSD system and its MR damper and negative stiffness element components were carried out under different harmonic excitations and command currents. Based on the experimental test results, artificial neural network-based forward and inverse models are designed for the QANSD force and command current identifications. Moreover, the real-time vibration control performances of the QANSD system are investigated and compared with the active and semi-active control systems. The experimental results revealed that compared to the MR damper that was only able to generate force in the opposite direction of structural motion, the developed QANSD system had the capacity to provide both velocity-resisting and velocity-assisting forces as the ROCF does. Its vibration control performance could fully match that of the desired active control system, but with much lower energy consumption.

Hydrous ruthenium oxide quantum dots anchored on carbon nanocages for Zn-ion hybrid capacitors

Zn-ion hybrid capacitors (ZICs) are a novel and promising electrochemical energy storage system, while exploring high-performance cathode materials is essential for the development of ZICs. Herein, we propose hydrous ruthenium oxide quantum dots (RuO2 QDs) anchored on porous carbon nanocages (PCNCs) as a new cathode material for ZICs. For the RuO2 QDs@PCNCs material, hydrous RuO2 QDs with a small size of 2–3 nm uniformly disperse on the PCNC support, providing large electrode–electrolyte interface for electrochemical reactions and abundant active sites for ion storage. Consequently, the RuO2 QDs@PCNCs cathode material displays desirable electrochemical performance in ZICs, including a large capacity of 224 mAh g−1 at 0.4–1.8 V, superior rate capability (showing 156 mAh g−1 capacity even at a large current of 20 A g−1) and good stability during a long-term cycling test over 20,000 cycles, significantly superior to currently-reported cathode materials for ZICs. An ultrahigh energy density of 180 Wh/kg is achieved for the RuO2 QDs@PCNCs cathode-based ZICs. Mechanism investigations point out the capacitive behavior-dominated and Zn2+/H+ co-participated charge storage process with fast electrochemical kinetics for the RuO2 QDs@PCNCs cathode in ZICs. This work not only provides a new choice for high-performance cathodes but also enriches the electrochemical theory of ZICs.

Improving Rate Performance by Inhibiting Jahn–Teller Effect in Mn‐Based Phosphate Cathode for Na‐Ion Batteries

AbstractManganese‐based phosphate cathodes are promising candidates for developing advanced sodium‐ion batteries, primarily driven by their reliable elemental abundance, low toxicity, and desirable cycling performance. However, the cooperative Jahn–Teller effect of Mn3+ will inevitably lead to structural disorder and irreversible phase transition, thus greatly harming the reversible capacity, rate, and cycling performance. Herein, a stable NASICON‐type Na3MnHf(PO4)3 cathode is demonstrated with a volume variation of 1.9% upon the process of Na+ extraction/insertion based on the robust Hf─O bond and symmetrical MnO6 octahedron. Moreover, making full use of the stepwise redox reactions of Mn2+/Mn3+/Mn4+, this cathode reveals excellent cycling stability with a capacity retention of 85.4% after 2500 cycles at 10 C. Matching with commercial hard carbon anodes, the assembled full cell keeps a capacity retention of 92.1% with the Coulombic efficiency close to 100% after 600 cycles at 1 C. The research promises opportunities for the structural amelioration of manganese‐based phosphate cathodes toward the application in high‐performance sodium‐ion batteries.

Data-Driven Self-Triggered Control via Trajectory Prediction

Self-triggered control, a well-documented technique for reducing the communication overhead while ensuring desired system performance, is gaining increasing popularity. However, a majority of existing self-triggered control methods require explicit system models. An end-to-end control paradigm known as data-driven control designs control laws directly from data and offers a competing alternative to the routine system identification-then-control strategy. In this context, the present paper puts forth data-driven self-triggered control schemes for unknown linear systems using input-output data collected offline. Specifically, a data-driven model predictive control (MPC) scheme is proposed, which computes a sequence of control inputs while generating a predicted system trajectory. In addition, a data-driven self-triggering mechanism is designed, which determines the next triggering time using the solution of the data-driven MPC and the newly collected measurements. Finally, both feasibility and stability are established for the proposed self-triggered controller, which are validated using a numerical example.

Towards low‐complexity state estimation for rigid bodies based on range difference measurements

AbstractThe rigid body localization (RBL) technique is capable of estimating the state of a rigid body, including its translation and orientation, by utilizing the interactions between sensors and landmarks. The prevalent RBL methods employ precise time‐of‐flight measurements (or range measurements) to estimate the state. However, the clock offsets in range measurements in asynchronous networks are unavoidable, leading to performance degradation for state estimators. Therefore, range difference measurements have been adopted to solve the RBL problem. However, existing approaches struggle to achieve desirable performance while maintaining computational efficiency. To address this issue, a new closed‐form state estimator for asynchronous networks is introduced. The proposed algorithm leverages the Taylor‐series expansion technique to enhance accuracy while keeping computational overhead low. Numerical experiments demonstrate that the proposed method achieves state‐of‐the‐art performance with high computational efficiency under small Gaussian noises.

Two-dimensional ferroelectric heterostructures for overall water-splitting from DFT aspects

Currently, the construction of direct Z-type heterojunctions is an effective way to improve the overall water splitting catalytic efficiency of existing two-dimensional(2D) materials, which can simultaneously combine spatial separation of active sites and enhanced redox ability. In particular, when the internal structure of heterojunction was polarized, the polarization can effectively tune electronic properties and remove band gap (1.23 eV) limitation on water splitting. So far, the effect of polarization on water-splitting reactivity in heterojunctions based on the 2D layered polarized In2Y3 (Y = S, Se) and the nonpolarized 2D β-Sb monolayer is unclear. Therefore, we constructed a series of such heterojunctions and made theoretical predictions of overall water splitting performance by first-principles calculations. The predictions shown that As/In2Se3(up), Sb/In2Se3(down) and Sb/In2S3(down) are potential photocatalysts with direct Z-scheme band positions, and hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) will occur on different surfaces of system. It is found that the intrinsic polarization electric field of In2Y3 (Y = S, Se) monolayer effectively enhances photogenerated carrier driving force of reaction. Notably, the promising photocatalysts have a high solar-hydrogen (STH) efficiency of 17.71 %, which has potential commercial applications. Also, Bi/In2S3up (S) and As/In2Te3up (As) exhibit desirable electrocatalytic HER performance. These insights provide an important strategy for application of ferroelectric heterojunctions in water splitting.