Simulation Experiments Research Articles

Fixation behavior of oceanic manganese nodule-sodium alginate composite microspheres for heavy metal release during manganese nodule mining

Research on the environmental impact of deep-sea mining is crucial, particularly for fragile deep-sea ecosystems. This research focuses on the issue of heavy metal release during mining activities. Through simulation experiments, we investigated the release of Cu2+, Co2+, and Ni2+ from sediments under disturbance conditions and the fixation behavior during the deployment of ocean manganese nodule-sodium alginate composite microspheres (OMN@SA). The experimental results revealed that mining disturbances cause the release of 0.291% of Cu2+, 7.34% of Co2+, and 4.13% of Ni2+ from sediments into the water, primarily in the form of exchangeable metals. Compared with the bottom adsorption, OMN@SA has a faster adsorption rate in the slow settling process. The removal rates of Cu2+, Co2+ and Ni2+ reached 54.0%, 78.3% and 61.8% for 5 h adsorption, and the bottom adsorption removal rates reached 96.4%, 97.8% and 95.1% for 30 d adsorption, which has a good removal effect. In addition, OMN@SA can effectively block the diffusion of Cu2+, Co2+, and Ni2+ from interstitial water to overlying water, and reduce the influence of interstitial water on overlying water. SEM-EDS, FTIR, and XRD analyses revealed that OMN@SA adsorbs heavy metal ions through its abundant -OH groups and incorporates Cu2+, Co2+, and Ni2+ into the crystal lattices of vernadite and todorokite via substitution or intercalation. This study provides guidance for the remediation of heavy metal release from deep-sea mining using adsorption methods and demonstrates the promising application prospects of OMN@SA.

Regularization of the Ensemble Kalman Filter using a non-parametric, non-stationary spatial model

The sample covariance matrix of a random vector is a good estimate of the true covariance matrix if the sample size is much larger than the length of the vector. In high-dimensional problems, this condition is never met. As a result, in high dimensions the Ensemble Kalman Filter’s (EnKF) ensemble does not contain enough information to specify the prior covariance matrix accurately. This necessitates the need for regularization of the analysis (observation update) problem. We propose a regularization technique based on a new spatial model. The model is a constrained version of the general Gaussian process convolution model. The constraints include local stationarity and smoothness of local spectra. We regularize EnKF by postulating that its prior covariances obey the spatial model. Placing a hyperprior distribution on the model parameters and using the likelihood of the prior ensemble data allows for an optimized use of both the ensemble and the hyperprior. A linear version of the respective estimator is shown to be consistent. A more accurate nonlinear neural-Bayes implementation of the estimator is developed. In simulation experiments, the new technique led to substantially better EnKF performance than several existing techniques.

Dynamic workload balancing to part input sequencing for integrated scheduling decision-making of flexible manufacturing systems

Flexible manufacturing systems (FMSs) are crucial in contemporary manufacturing environments because they provide the required agility and adaptability to face volatile customer demands. Balancing workload among different work stations of an FMS is essential to ensure optimal resource utilization, minimize idle times, and improve overall system performance. This research is aimed to study the application of dynamic workload balancing to part input sequencing for integrated FMS scheduling decision-making. In this work, we propose an online algorithm that balances workload dynamically in FMSs. A mathematical model of FMS scheduling integration is presented. The proposed approach schedules tasks not only on machines but also on the robot responsible for part movement within a shop floor. The proposed approach is evaluated in two aspects of comparison and analysis. Data analysis is made by simulation experiment and statistical analysis. Conclusions with managerial implications for practical applications and future research suggestions are provided.

Secure fuzzy retrieval protocol for multiple datasets

With the diversification of data sources and the massive growth of datasets, data retrieval has become increasingly complex and time-consuming. In the traditional retrieval method, if a user wants to query multiple datasets, the general approach is to retrieve them one by one in order, which may lead to duplication of work and waste of resources. Private set intersection is a specific issue in secure multi-party computation. It allows several participants, each holding different sets, to jointly calculate the intersection of their sets without revealing any information other than the intersection. This method is naturally suitable for data fusion. In this work, we propose a secure fuzzy retrieval protocol for multiple datasets. First, we use private set intersection technology to fuse multiple datasets. Then, we perform secure retrieval based on this fused dataset, effectively avoiding the waste of resources caused by separate retrievals, thereby maximizing resource efficiency. It is worth mentioning that the protocol proposed in this paper can also be used for fuzzy retrieval to improve the user’s search experience. More importantly, the protocol can maximize privacy protection during the retrieval process, including strict protection of sensitive information such as retrieval keywords, ensuring that user data and query intentions will not be leaked during the entire retrieval process. Finally, we provide a rigorous security proof and demonstrate the effectiveness of the protocol through simulation experiments.

Energy level engineering strategy to S-scheme BiOI0.15/α-FeOOH heterojunction with I vacancy for superior photo-Fenton catalytic tetracycline hydrochloride degradation

A novel S-scheme BiOI0.15/α-FeOOH heterojunction was fabricated by hydrolysis method, and its photo-Fenton oxidation performance was evaluated by removing antibiotics. The optimal BiOI0.15/α-FeOOH shows significantly enhanced photo-Fenton degradation activity of tetracycline hydrochloride (TC), reaching 98.2% within 10min, compared with the photocatalytic (48.1%) and Fenton (60.5%) degradation activity. The excellent degradation performance of BiOI0.15/α-FeOOH can be vested in the presence of I vacancies and S-scheme heterostructure. I vacancies could provide the enriched electron sites to foster the photo-Fenton-like activity (88.8% of BiOI0.15 and 65.5% of BiOI) and modulate the valence/conduction band positions of BiOIX to obtain S-scheme heterojunction catalyst. S-scheme heterostructure provides the high specific surface area and built-in electric field. Simulated wastewater studies and cycling experiments proof the practicability and stability of BiOI0.15/α-FeOOH.

Differences in the Accumulation of Pentachloronitrobenzene and Cadmium in Vegetables Grown in Contaminated Soils

The capability of different vegetable species to accumulate Pentachloronitrobenzene (PCNB) and cadmium (Cd) in soils varies significantly. Investigating these characteristics can guide the rational use of farmland contaminated with PCNB and Cd. The growth of five common vegetables (three vegetable species and three varieties of one species) in PCNB and Cd co-contaminated soils in Southwest China was investigated through a 100-day simulated contamination pot experiment. Interspecific and intervariety differences in the uptake and accumulation of PCNB and Cd were also examined. These vegetables included leafy types such as Lactuca sativa (CL), Lactuca sativa var. longifolia (RL), and Brassica rapa subsp. chinensis (BC), and root types such as Red Raphanus sativus (RR) and Lactuca sativa var. angustata (AL). Results showed that light to medium PCNB contamination (0.44 to 6.74 mg·kg-1) promoted the growth of leafy vegetables, while severe contamination (9.88 to 9.96 mg·kg-1) inhibited their growth. Root vegetables were inhibited by PCNB. Soil Cd contamination reduced the biomass of all five vegetables. In co-contamination soil (PCNB: 0.47 to 9.88 mg·kg-1; Cd: 0.46 to 1.63 mg·kg-1), vegetable growth was affected by the interaction between PCNB and Cd. In severely PCNB-contaminated soil, PCNB contents of CL, RL, BC, and AL leaves exceeded food safety limits, while those in RR and AL stems did not. The five vegetables showed varying Cd contamination, with AL leaves being the most contaminated, exceeding the standard by 60 times. PCNB accumulation followed the order: AL leaves > BC > AL stems > RL> CL> RR. Cd accumulation was highest in AL leaves, followed by stems, RR, BC, CL, and lowest in RL, with significant differences (P<0.05). Co-contaminated soil did not promote PCNB and Cd uptake in vegetables. CL and RL, with low PCNB and Cd accumulation capacities, could be considered low-accumulation varieties for lightly contaminated soils.

A molten salt energy storage integrated with combined heat and power system: scheme design and performance analysis

To investigate the flexibility and economic characteristics of a molten salt-combined heat and power (CHP) integrated system under different heat sources, this paper proposes a design scheme for a molten salt-CHP system based on flue gas heat storage, comparing it with main steam heat storage and reheated steam heat source schemes. First, a molten salt heat release sub-loop is designed, where the steam heated by the molten salt can either compensate for heating demands or enter the low-pressure turbine for work, meeting the flexible operation requirements of the unit. Secondly, in response to fluctuations in temperature and pressure parameters of the main steam and reheated steam in the flue gas heat storage scheme, a water-spray desuperheating device is arranged. Finally, a simulation experiment based on a 350 MW CHP was conducted, and the results show that the flue gas molten salt heat storage technology significantly reduces energy loss on the boiler side. Underrated load, compared to the main steam and reheated steam heat storage schemes, the flue gas heat storage scheme has the highest boiler exergy efficiency and total energy utilization efficiency, at 55.8% and 59.1% respectively. During the thermal storage process, the coal consumption index of the flue gas heat storage scheme decreases with increasing load, while conversely, during the heat release process, it increases with the load. The peak-shaving capacity increases with the load, reaching 78.4 MWh under the 75% THA condition. In the steam extraction heating scenario, coupling with the molten salt subsystem can expand the safe heating operation range of the original unit, increasing the maximum peak shaving range by 13.9%, and increasing the maximum heating capacity by 65.4%.

Response of sediment with Ca/Al composites capping to cyanobacterial bloom decline: Blocking the formation and the release of sediment iron-bound phosphorus (Fe-P)

The immobilization of phosphorus (P) in sediments plays a pivotal role in managing lake eutrophication over the long term. Therefore, key factors that may cause uncertainties in P fixation are of increasing interest to researchers. Calcium‑aluminum composites (CA) can passivate sediment P well; however, the effect of cyanobacterial bloom decline on their sediment P remediation remains unclear. In this study, CA addition significantly reduced P equilibrium concentration as well as augmented P adsorption capacity of sediment characterized as cyanobacterial dominance zone (CDZ). The results of the simulated experiments on cyanobacterial bloom decline indicated that the algae decomposition led to a rapid decrease in dissolved oxygen (DO) level, and to release amounts of P, thus increasing the P concentration in the overlying water. The released algal P into the sediment primarily encouraged the formation of iron-bound phosphorus (Fe-P), followed by calcium-bound phosphorus (Ca-P). The subsequent anaerobic incubation led to a notable release of the newly formed Fe-P, strengthening the anaerobic P release from sediments. Conversely, CA-capping accelerated the adsorption of algal P by sediments, and promoted the formation of Ca-P in sediment from cyanobacterial P, hindering the generation of reactive Fe-P. Moreover, during subsequent anaerobic incubation, the P forms in sediments capped with CA remained stable, showing no obvious P release. These findings suggested that CA capping induced the formation of stable P from algal P and disrupted the positive feedback effect between P contamination in sediments and cyanobacterial blooms, which would provide valuable insights for the remediation of sediments in CDZ.

Abiotic chlorination of organic matter in the soil environment: A simulation study

Chlorination of organic matter occurs naturally and is an important part of the chlorine cycle. To investigate the likelihood that inorganic oxidants, (Fe(NO3)3, H2O2, and hydroxyl radicals (·OH), frequently present in soil environments, could promote the synthesis of chlorinated organic matter in the soil environment, litterfall, humus, and soil (0–20 cm) were collected and used in laboratory based simulation experiments. Results indicate that these inorganic oxidants might promote the synthesis of chlorinated organic matter, but their impact varied due to varying suitable reaction circumstances. Litterfall was the most sensitive to chlorination, likely caused by the presence of abundant amounts of labile organic matter, and the chlorination process was limited by its Cl− level. Hydroxyl radicals showed a dual effect (producing or degrading chlorinated organic matter) on the three materials assessed, which was controlled by both ·OH concentration and the stability of organic matter, and the dual effect was evident in order of litterfall > humus > soil. The Fe(NO3)3-mediated chlorination of organic matter was only significant in litterfall due to its labile organic matter composition, while the peroxidative reaction caused by H2O2 in the producing chlorinated organic matter was only obvious in soil, most likely due to the presence of metals, facilitating the process. Combined this study sheds light on the chlorine cycle by verifying that inorganic oxidants might mediate abiotic chlorination of organic matter in a natural soil environment.

3D path planning for UAV based on A hybrid algorithm of marine predators algorithm with quasi-oppositional learning and differential evolution

3D path planning is a critical requirement for the autonomy of unmanned aerial vehicle (UAV) navigation systems. In this paper, we propose a novel approach, the differential evolution combined marine predators algorithm (DECMPA), specifically tailored to address the UAV 3D path planning problem in complex scenarios. To handle stringent constraints, DECMPA adopts a multi-step approach. Initially, it utilizes quasi-oppositional learning to generate a more uniformly distributed initial population. Throughout the iterative process, it probabilistically generates quasi-oppositional populations and merges them with existing populations, selecting the superior individuals for the next generation to mitigate local optima. Additionally, DECMPA integrates the variance, crossover, and selection processes of differential evolution into the marine predators algorithm iterations. The greedy selection of test and target vectors further accelerates population convergence. Numerical optimization experiments are conducted using the 10 and 20-dimensional CEC 2021 test suite. Compared to other algorithms, DECMPA exhibits superior solution accuracy and convergence speed, resulting in substantial performance enhancement, thus establishing itself as an efficient algorithm. Furthermore, the adoption of spherical vector coordinates in solution encoding ensures higher quality and facilitates the production of feasible solutions. To verify the effectiveness and practicality of the proposed algorithm, comprehensive path planning simulation experiments are conducted. DECMPA is compared against nine other state-of-the-art heuristic algorithms across six 3D scenarios of varying complexity. The experimental results demonstrate DECMPA’s superiority in terms of optimal cost acquisition, solution quality, and stability. In conclusion, DECMPA presents a promising solution for addressing the challenges of UAV 3D path planning in complex environments. Its innovative approach and superior performance underscore its potential for real-world application in autonomous UAV navigation systems.

Photoelectric sensor-based belt-type high-speed seed guiding device performance monitoring method and system

The belt-type high-speed seed guiding device encounters difficulties in seed guidance due to its distinctive seed transporting belt structure. The monitoring point is situated between the seed belt support plate and the seeds, which pass through it, making it difficult to distinguish the characteristics of the seed pulses. This presents challenges in monitoring the device’s performance. This study proposes a monitoring method for the belt-type high-speed seed guiding device using photoelectric sensors. The monitoring module employs a photoelectric sensor as a signal source and designs hardware and software for the monitoring module. The research introduces the deviation pulse extraction algorithm (DPEA), which utilises the seed guidance performance monitoring mechanism. This achieves precise monitoring of seed transport on the transporting seed belt, thereby eliminating the increased multiple index caused by “pulse sinking”. Simulation experiments demonstrate that the optimal deviation pulse extraction algorithm (ODPEA) is highly effective in identifying and eliminating “pulse sinking”, resolving the issue of increased multiple index. The DPEA is unable to achieve the same effect. The results of comparative tests of seeding monitoring accuracy indicate that both algorithms exhibit average monitoring accuracy above 96% across varying operating speeds. The DPEA, however, demonstrates heightened sensitivity to changes in operating speed. It can be observed that the operating speed has a significant impact on the monitoring accuracy of both algorithms. The monitoring system performance evaluation comparative test reveals that the DPEA-based monitoring system registers the smallest deviations in qualified feed index, miss index, and multiple index at 0.25 percentage points, 0.10 percentage points, and 0.35 percentage points, respectively. In contrast, the ODPEA-based system shows minimum deviations in qualified feed index and miss index at 0.12 percentage points each, and no deviation in multiple index. Both algorithms demonstrate minimal influence of operating speed on missing and multiple seeding rates. The impact of changes in operating speed on these metrics is significantly lower. The efficacy of the ODPEA in eliminating ’pulse sinking’ enhances the algorithm’s ability to assess multiple seeding rates and overall accuracy. The ODPEA-based monitoring system exhibits superior performance, providing theoretical support for the development of monitoring systems in high-speed belt-type seed guiding devices.

The HADRIAN novel human–machine interface prototype for automated driving: safety and impact assessment

AbstractThe current paper was performed within the HADRIAN project and focuses on exploring the effects of innovative Human–Machine Interface (HMI) prototypes on safety, driving performance, and driver perceptions. Employing driving simulator experiments and questionnaires, this study investigates whether HADRIAN innovative HMI enhances safety and receives positive evaluations from drivers. Specifically, the research centers on a driving simulator experiment that evaluates novel HMI prototypes designed to improve automated driving at SAE Levels 2 or 3. To facilitate HMI assessment, a tailored safety and impact assessment methodology was developed using unique Key Performance Indicators (KPIs). To benchmark and generate a total score for the HADRIAN HMI, data envelopment analysis was deployed based on the aforementioned KPIs. The findings shed light on the influence of HADRIAN HMI innovations on safety and perceived impact when compared to a baseline “state-of-the-art” HMI. Subsequently, a comprehensive discussion unfolds, highlighting the key KPIs that contributed significantly to the safety and perceived impact scores. This method and its outcomes can serve as a valuable resource for other HMI stakeholders, enabling them to employ similar human-centered assessment methodologies to assess the safety and perceived impact of potential HMI configurations.

Robust joint estimation of sideslip angle and tire lateral force for distributed drive electric vehicle

Accurate estimation of vehicle sideslip angle (SA) and tire lateral force (TLF) is essential for the effective functioning of vehicle active safety control systems. However, effective estimation of SA and TLF using low-cost on-board sensors is a major challenge. In this paper, a robust joint estimation method of SA and TLF for distributed drive electric vehicle (DDEV) is proposed. Adaptive sliding-mode observer (ASMO) is used to estimate the TLF and is used as the input to the subsequent filter. Maximum correntropy criterion (MCC) is introduced to improve the robustness of the unscented Kalman filter (UKF) under mixed Gaussian noise, and the maximum correntropy unscented Kalman filter (MCUKF) algorithm is composed to estimate SA. The effectiveness of the proposed ASMO and MCUKF joint estimation method is verified by Simulink/Carsim joint simulation experiments. The experimental results show that compared with the existing methods, the estimation method proposed in this paper effectively improves the estimation accuracy and robustness of SA and TLF under the mixed Gaussian environment, which is of great significance for the improvement of vehicle active safety.

Application of an Improved State Feedback Control in the Selective Catalytic Reduction Denitrification Systems of Coal Power Units Under Variable Load Conditions

Selective catalytic reduction (SCR) flue gas denitrification systems are inherently complex, typically embodying characteristics of non-linearity, significant time delays, and susceptibility to multiple disturbances. In the context of coal power units engaging in deep load cycling and rapid frequency adjustment, conventional proportional-integral-derivative (PID) control struggles to meet the demands of effective control. This study introduces a control strategy that incorporates a “state observer + Linear Quadratic Regulator (LQR) state feedback + Improved Quantum Genetic Algorithm (IQGA) optimized PID”. Initially, local linear mathematical models of an SCR denitrification system at 340 MW, 450 MW, and 540 MW loads were used to design state observer and LQR state feedback control parameters for each operational condition. At a single load point, the IQGA was employed to optimize the outer loop PID parameters, followed by simulation experiments of load increases and decreases between 340 MW and 540 MW. The results demonstrated that, compared to two other strategies, the proposed approach reduced the overshoot by a minimum of 1.5% and shortened the adjustment time by 31.7% under conditions of step disturbances and internal perturbations. Throughout variable operational conditions, the strategy consistently exhibited minimal output fluctuations, rapid adjustment capabilities, strong disturbance rejection, and robust stability. This algorithm proves to be an effective method for controlling NOx concentrations, offering insights for precise ammonia injection control in future applications.

Migration-connected networks of Lotka–Volterra and quasi-polynomial systems: modeling and decentralized control

AbstractThis paper introduces a modeling and a control approach for Lotka-Volterra systems that are interconnected through population size-dependent migration flows. First, a control-oriented model is proposed for networks of Lotka-Volterra systems. Based on this model, a decentralized control method is introduced which assures that the states of each Lotka-Volterra system in the network can be driven into a prescribed setpoint regardless of migration. The results have been generalized to quasi-polynomial systems, and networks of Lotka-Volterra systems having interconnections with distributed delay. Simulation experiments are also presented in the paper to show the implementability of the theoretical results.

Path Planning for Robots Combined with Zero-Shot and Hierarchical Reinforcement Learning in Novel Environments

Path planning for robots based on reinforcement learning encounters challenges in integrating semantic information about environments into the training process. In unseen or complex environmental information, agents often perform sub-optimally and require more training time. In response to these challenges, this manuscript pioneers a framework integrating zero-shot learning combined with hierarchical reinforcement learning to enhance agent decision-making in complex environments. Zero-shot learning enables agents to infer correct actions for previously unseen objects or situations based on learned semantic associations. Subsequently, the path planning component utilizes hierarchical reinforcement learning with adaptive replay buffer, directed by the insights gained from zero-shot learning, to make decisions effectively. Two parts are trained separately, so zero-shot learning is available in different and unseen environments. Through simulation experiments, we compare the traditional hierarchical reinforcement learning method with the proposed method. The results prove that this structure can make full use of environmental information to generalize across unseen environments and plan collision-free paths.

Modeling and analysis of heterogeneous traffic flow with mixed regular and connected human-driven vehicles considering driver stochasticity

This paper presents a novel microscopic modeling framework to explore the impact of driver stochasticity and other related factors on heterogeneous traffic flows, consisting of both regular human-driven vehicles (RHDVs) and connected human-driven vehicles (CHDVs). We apply the stochastic optimal velocity car-following model for RHDVs, while an extended version of the stochastic continuous car-following model, taking into account optimal velocity guidance and driver compliance, is devised for CHDVs. The stability of CHDV car-following model is examined theoretically and numerically. Simulation experiments are conducted to analyze the stochastic heterogeneous traffic flow properties (i.e. stability and safety) with the proposed microscopic modeling framework under diverse parameter settings including CHDV penetration rate, driver compliance, and driver stochasticity. Results show that traffic flow stability and safety improve with the increase in CHDV penetration rate and driver compliance but deteriorate as the driver’s stochasticity strength increases. CHDVs significantly enhance traffic stability when the CHDV penetration rate or driver compliance exceeds a certain threshold, typically ranging between 0.5 and 0.7. Additionally, there is an interaction between driver stochasticity and CHDV penetration rate in their effect on traffic flow stability, where the contribution of stochasticity to traffic oscillations first increases and then decreases as the penetration rate rises. When the penetration rate is between 0 and 0.4, the traffic risk in emergency situations can be significantly reduced as the penetration rate increases. These findings may guide the management and control strategies of heterogeneous traffic flow.

Experimental Study on Interlayer Interference Characteristics During Commingled Production in a Multilayer Tight Sandstone Gas Reservoir

In this study, a practical and comprehensive experimental technique has been proposed to investigate the interlayer interference characteristics in multilayer tight sandstone gas reservoirs with multi-pressure systems and different reserves. Firstly, single-layer depletion simulation experiments were conducted to measure the gas flow rate and gas extraction efficiency for each of the six layers. A series of physical simulation experiments were then conducted to monitor gas production and pressure variations in commingled multilayer production scenarios under various conditions. Finally, interlayer interference characteristics and gas extraction efficiencies and the main controlling factors were evaluated, analyzed, and identified. The interlayer pressure differential is found to be the primary factor dictating both interference and gas production, followed by initial gas production rates, and permeability variations in the order of positive significance. A higher interlayer pressure differential, a lower initial gas production rate, and a larger permeability variation result in an increase in interlayer interference and a reduction in gas production during commingled production. Increasing the number of commingled layers leads to an overall increase in gas production losses of 10.95% for two layers to 13.35% for four layers. Layers exhibiting small interlayer pressure difference are positively compatible for commingled production.

Application of the hybrid integration displacement algorithm based on CEEMDAN and wavelet threshold denoising in vibration screening equipment

Abstract Vibration screening equipment has an extensive application profile in material screening, in which the displacement parameters can reveal the motion state of the material and affect the screening efficiency. These displacement parameters can be obtained by integrating the acceleration signal of the equipment. In this paper, to prevent the noise in the acceleration signal from further amplifying its negative effects on the subsequent integration, the acceleration signal is preprocessed by the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and wavelet threshold denoising. Besides, a hybrid integration displacement algorithm is utilized to mitigate the influence of integration errors. The consistent results between simulation and platform experiments demonstrate that CEEMDAN in combination with wavelet threshold denoising can effectively remove noise while retaining the main frequency signal. In addition, the displacement signal obtained by the hybrid integration algorithm proposed in this paper is closer to the original displacement signal. Compared with the 2nd time-domain integration, the 2nd frequency-domain integration, and the empirical mode decomposition (EMD) integration methods, the integration method proposed in this paper achieves a smaller peak error, mean absolute error (MAE), and root mean square error (RMSE). The experimental results corroborate the superiority of this method in the application of vibration screening equipment.

High-Entropy Boride HfZrTiTaMoB: Promising Materials for Solar Selective Absorption Coatings in Photothermal Applications.

High-entropy borides (HEBs), as a category of high-entropy materials, exhibit remarkable thermal stability, a broad compositional range, and finely tuned electronic structures, leading to an excellent functional performance. Despite these advantages, their application in photothermal materials has rarely been reported. Herein, we employ a HEB target with multiple transition-metal elements to develop solar selective absorption coatings (SSACs) with simple and scalable bilayer structures for photothermal applications. The performance of these coatings is enhanced by designing different antireflective layers. The designed SSACs, both stainless steel (SS)/HEB/Al2O3 and SS/HEB/Si3N4, exhibit high absorptivity and low thermal emittance (α/ε = 90.0%/8.6% and 91.6%/8.6% at 82 °C). Thermal stability tests show that the absorbers could withstand annealing at 500 °C for 5 h, while maintaining a good optical performance. Long-term thermal stability tests indicate that the coatings retained good spectral selectivity after annealing at 400 °C for 100 h. Notably, the coatings demonstrate advanced photothermal conversion efficiencies of 88.3% and 89.9%, respectively, at 400 °C under 100 sun. In practical simulated solar irradiation experiments, the absorber achieves temperatures of about 85 °C under 1 sun, surpassing the performance of commercial nonselective absorbing coatings. Additionally, the absorbers maintained a stable photothermal performance through six on-off cycle experiments. In summary, the designed SSACs based on HEBs exhibit excellent optical properties and efficient photothermal conversion at moderate temperatures. This study highlights the significant benefits and potential advancements in solar energy collection offered by HEB-based SSACs.