Double-layer Model Research Articles

Electrolyte effects on the alkaline hydrogen evolution reaction: A mean-field approach

This paper introduces the combination of an advanced double-layer model with electrochemical kinetics to explain electrolyte effects on the alkaline hydrogen evolution reaction. It is known from experimental studies that the alkaline hydrogen evolution current shows a strong dependence on the concentration and identity of cations in the electrolyte, but is independent of pH. To explain these effects, we formulate the faradaic current in terms of the electric potential in the double layer, which is calculated using a mean-field model that takes into account the cation and anion sizes as well as the electric dipole moment of water molecules. We propose that the Volmer step consists of two activated processes: a water reduction sub-step, and a sub-step in which OH− is transferred away from the reaction plane through the double layer. Either of these sub-steps may limit the rate. The proposed models for these sub-steps qualitatively explain experimental observations, including cation effects, pH-independence, and the trend reversal between gold and platinum electrodes. We also assess the quantitative accuracy of the water-reduction-limited current model; we suggest that the predicted functional relationship is valid as long as the hydrogen bonding structure of water near the electrode is sufficiently maintained.

Exploring diclofenac potassium adsorption on activated carbon: A comprehensive statistical physics and experimental approach

This study aims to contribute to understanding the removal processes of diclofenac potassium (DP) medicine in wastewater treatment systems, employing activated carbon (AC) as an adsorbent. To achieve this goal, a multidisciplinary approach was adopted, integrating experimental and theoretical analyses of equilibrium data regarding the adsorption of DP on AC. Five statistical physics models were applied to determine the model best for the adsorption process. The selection of the most appropriate model considered both the performance of the models and the analysis of the estimated parameters. Statistically, all models exhibited satisfactory results. However, when analyzing the estimated parameters, the double-layer model with single adsorption energy emerged as the most suitable model to describe the analyzed process. Based on the chosen model’s parameters, we observed that as the temperature increases, the number of active sites occupied during adsorption and their availability on the adsorbent also increases. However, the number of available adsorption sites decreases as the temperature rises. The half-saturation concentration, in turn, increases with increasing temperature, suggesting that the process is favored when temperatures above room temperature are used. Additionally, higher temperatures provide better removal results, indicating that DP molecules’ non-parallel and parallel orientations on the AC surface favor the adsorption process. Finally, our combined results led to the proposal of a mechanism for DP adsorption on AC, which is based on physical adsorption interactions between adsorbate-adsorbent and adsorbate–adsorbate.

Artificial neural network based optimization of sunflower oil supplementation in polyhydroxyalkanoates production by Cupriavidus necator

The assessment of feeding strategy and availability of alternate carbon source in vegetable oil-supplemented microbial polyhydroxyalkanoates (PHA) production remains largely qualitative. This study aims to model the impact of sunflower oil to sucrose ratio, and feeding strategy on PHA production by Cupriavidus necator. Sets containing oil (20 ml l−1), and oil-sucrose mixture (10 ml l−1, 10 g l−1) resulted in 3.907 g l−1 and 3.342 g l−1 of PHA, much higher than in sucrose-only (2.081 g l−1) set. Shifting sucrose (20 g l−1) pre-grown biomass on into oil (20 ml l−1) containing medium resulted in a substantial increase in polymer than in sets either amended with oil or having an equal proportion sucrose-oil blend. Hyperparameter optimized double-layer (6-3) ANN model for PHA production, developed from factorial design experiment with different sucrose-oil ratios (0.053–19 w/v), inoculum dose (0.853–1.219 g l−1), and time-of-shift (24–72 h), offered reasonably good fitness both on training (R2: 0.960) and cross-validation (R2CV: 0.593). Optimization of the ANN model projected 10.411 g l−1 of PHA from a sucrose-oil ratio of 1.729 (w/v), inoculum dose (0.854 g l−1), and sucrose-to-oil shift after 44 h of incubation.

A reliability-based multidisciplinary design parallel optimization method based on double-layer approximation model for nuclear fuel assembly bottom nozzle

The design of intricate systems such as the nuclear fuel assembly necessitates elevated levels of multi-disciplinary performance and reliability. In current reliability-based multidisciplinary design optimization methods, the decoupling strategy between optimization and reliability assessment involves sequential optimization and reliability assessment, with reliability serving as a constraint for optimization. This approach often suffers failure in locating the global optimal solution. In light of this issue, a reliability-based multidisciplinary design parallel optimization method based on double-layer approximation model is hereby proposed, achieving parallel separation and global efficient optimization of deterministic disciplinary performances and reliability, while performing efficient and accurate calculation on the multi-disciplinary reliability numerical solution. This method has been implemented for the multi-disciplinary uncertain optimization of the nuclear fuel assembly bottom nozzle. In comparison to conventional optimization methods, this approach demonstrates enhanced global optimization effectiveness.

Enhancing Logistics Optimization

With the expansion of the logistics network, enterprise logistics distribution faces increasing challenges, including high transportation costs, low distribution efficiency, and unstable distribution networks. To address these issues, this study focuses on optimizing enterprise logistics distribution using a double-layer (DL) model. In this paper, we propose a DL model for optimizing enterprise logistics distribution. The DL model is designed to find the optimal solution using the particle swarm optimization (PSO) algorithm. By leveraging location data from the region, the DL model evaluates and compares alternative distribution centers to determine the most efficient distribution strategy. The results demonstrate that the DL site selection model developed in this study effectively addresses the tasks of logistics center location and distribution optimization among alternative distribution centers. Comparison tests reveal that the distribution path proposed by the DL model is more accessible and cost-effective compared to alternative approaches.

Understanding the adsorption of Reactive red 2 onto metal hydroxide sludge: analysis with physico-statistical steric and energetic perspectives.

This theoretical investigation delves into the analysis of Reactive red 2 (RR-2) adsorption isotherms on metal hydroxide employing a sophisticated double-layer model characterized by dual-energy levels within the realm of physical adsorption phenomena. An examination of five distinct statistical physics frameworks was undertaken to elucidate the modeling and interpretation of equilibrium data. Expression for the physico-chemical parameters involved in the adsorption phenomena was derived based on statistical physics treatment. Fitting experimental adsorption isotherms (308-333K) to a DAMTBS has revealed the number of anchored molecules per site, occupied receptor site density, and the number of adsorbed layers. The steric parameter n varies between 0.92 and 1.05. More importantly, it is evidenced that the adhesion mechanism of (RR-2) onto metal hydroxide as determined by the estimated adsorption energies (< 40kJ/mol) supports a spontaneous and exothermic physisorption process. Thermodynamic potential functions such as entropy, Gibbs free energy, and internal energy have been computed based on the most suitable model. This research advances our physical understanding of how metal hydroxide captures dye molecules RR-2 through adsorption reaction for water depollution treatment.

Hydraulic modeling study and control algorithm design of double-layer pipe dual-gradient drilling

Deepwater drilling has the problem of narrow safe density window, and double-layer pipe dual-gradient drilling is one of the effective ways to solve the narrow safe density window. Due to the different structure and process principle with MPD, there is an urgent need to establish the hydraulic model and control algorithm of double-layer pipe dual-gradient drilling in order to realize the normal regulation of bottom hole pressure during drilling. Based on the hydraulic theory of managed pressure drilling and considering the influence of the three-channel structure of double-layer pipe and the downhole hydraulic lift pump in double-layer pipe dual-gradient drilling, a hydraulic model of double-layer pipe dual-gradient drilling has been established and verified in land well tests. Based on the double-layer pipe dual-gradient drilling hydraulic model, a control algorithm based on pressure regulation and flow rate regulation is established considering the principle of double-layer pipe dual-gradient drilling process. The simulation results show that the control algorithm based on flow rate regulation can greatly reduce the bottom hole pressure regulation time by controlling the size of the flow rate of the return fluid. When the bottom hole pressure is increased from 25 MPa to 26 MPa, the regulation time is 11min, which basically meets the requirements of field operation. The hydraulic model and control algorithm of double-layer pipe dual-gradient drilling are favorable to the bottom hole pressure regulation during drilling and reduce the response time.

Activation Energy of Ion Desorption at Ionic Liquid/Pt Electrode Interfaces: A Sum-Frequency Generation Vibrational Spectroscopic Study.

Electrolyte/electrode interfaces of room-temperature ionic liquids (RTILs) exhibit hysteretic responses to different applied potentials owing to the differences in the ion adsorption/desorption processes; the ion desorption requires excess potential, which reflects the activation energy of ion desorption. Thus far, the contributions of the ion adsorption energy and the activation barrier for ion desorption toward the ion-dependent excess potential have not been quantified. Herein, we report on our infrared-visible sum-frequency generation vibrational spectroscopy study of the hysteretic responses of the anion adsorption/desorption at Pt electrode interfaces using neat, binary, and diluted RTILs composed of 1-butyl-3-methylimidazolium cations ([C4mim]+) and bis(trifluoromethanesulfonyl)amide ([TFSA]-) and trifluoromethanesulfonate ([OTf]-) anions. Experimental results are compared to the theoretical calculations for the electric double layer model. The hysteretic response of the RTIL/Pt interface derives predominantly from the activation energy of anion desorption, which causes the negative excess potential required for anion desorption. A comparison of the anion adsorption/desorption behaviors of neat RTILs with those of binary and diluted RTILs reveals that the large activation energy of anion desorption at the neat RTIL/Pt interface originates largely from the activation barrier for restructuring ionic layering in the diffuse layer.

Crash severity analysis: A data-enhanced double layer stacking model using semantic understanding

The crash severity analysis is of significant importance in traffic crash prevention and emergency resource allocation. A range of innovations offers potential traffic crash severity prediction models to improve road safety. However, the semantic information inherent in traffic crash data, which is crucial in enabling a deeper understanding of its underlying factors and impacts, has yet to be fully utilized. Moreover, traffic crash data are commonly characterized by a small sample size, which leads to sample imbalance problem resulting in prediction performance decline. To tackle these problems, we propose a semantic understanding-based data-enhanced double-layer stacking model, named EnLKtreeGBDT, for crash severity prediction. Specifically, to fully leverage the inherent semantic information within traffic crash data and analyze the factors influencing crashes, we design a semantic enhancement module for multi-dimensional feature extraction. This module aims to enhance the understanding of crash semantics and improve prediction accuracy. Then we introduce a data enhancement module that utilizes data denoising and migration techniques to address the challenge of data imbalance, reducing the prediction model's dependence on large sample crash data. Furthermore, we construct a two-layer stacking model that combines multiple linear and nonlinear classifiers. This model is designed to augment the capability of learning linear and nonlinear mixed relationships, thereby improving the accuracy of predicting the severity of crashes on complex urban roads. Experiments on historical datasets of UK road safety crashes validate the effectiveness of the proposed model, and superior performance of prediction precision is achieved compared with the state-of-the-arts. The ablation experiments on both semantic and data enhancement modules further confirm the indispensability of each module in the proposed model.

Theoretical analysis of Ellis fluid flow in two layers due to metachronal propulsion subject to heat and mass transfer: Application in biological function

This study uses a metaphor to describe the motion of cilia with heat and mass transfer, and it highlights the importance of research for understanding biological function. This research article depicts analysis of double-layer of cilia induced flow for non-Newtonian (Ellis fluid) with additional effects of thermal and concentration fields. The Ellis fluid model is considering as mucus present in Human bronchial airways. Respiratory tract and bronchial airways consisted of ciliated epithelium which is further divided into two layers, Airway Ciliary Layer (ACL) and Peri Ciliary liquid Layer (PCL). Due to which double-layer model has been constructed in this investigation. Mathematical modeling of double-layer flow problem has been simplified using long-wavelength and small-Reynolds number approximation. Consequent governing equations with boundary conditions gives an exact/accurate result for velocity field, temperature distribution and concentration distribution in double-layers. The influence of emerging parameters on velocity profile, temperature distribution, concentration field was illuminated by graphs and discussed comprehensively. Contour plots have also been plotted to visualize flow pattern in both layers. Evidenced graphs show that velocity profile and temperature profile are the highest in inner layer of fluid (PCL) and concentration profile is the highest at outer layers of fluid (ACL).

A diffused double-layer model of bulk nanobubbles in aqueous NaCl solutions

Bulk nanobubbles, known for their extraordinary stability due to their electrically charged surface, still have an elusive mechanism. This research examines the surface electrical properties of oxygen nanobubbles in various NaCl solution concentrations, utilizing a diffused double-layer model. The process involves the creation of nanobubbles through the hydrodynamic cavitation technique, followed by an assessment of their size and zeta potential. To quantify their influence on nanobubble stability, the thickness of the double layer, the density of surface charge, electrostatic repulsion and attractive force, and interaction energy between bubbles are evaluated. The results show that adding NaCl to nanobubble solutions increases bubble size while decreasing their negative zeta potential, minimizing repulsive electrostatic interactions among the bubbles. These findings are consistent with the diffused double-layer theory. Specifically, higher NaCl concentrations in solutions lead to thinner double layers and decreased energy barriers. Observing nanobubble stability in a 10 mM NaCl solution over six months reveals a decrease in bubble size accompanied by an increase in zeta potential. This rise in negative zeta potential correlates with changes in Debye length and ionic strength, inversely proportional to the solution's conductivity, likely due to reduced NaCl concentration over time. Furthermore, the pressure differential at the bubble interface is insufficient to overcome the pressure caused by the liquid's surface tension, indicating potential limitations in applying the diffused double-layer model. This highlights the need for further investigation to establish a more comprehensive understanding of the mechanical stability of bulk nanobubbles.

MgAl2O4 capping effects on the magnetic properties of TbFeCo films

We investigate MgAl2O4 (MAO) capping effects on the magnetic properties of TbFeCo films. Compared with TbFeCo films, a shift of compensation point to lower temperatures together with significantly reduced saturation magnetization is found in the case of MAO capping. An antiferromagnetic exchange coupling is observed in TbFeCo/MAO structures. This can be well explained by a double layer model with opposite phases. An exchange energy density of ∼ 0.5 erg/cm2 is obtained, which is comparable but lower than that of TbFeCo bilayers with opposite phases. Our findings may be useful for developing ultrathin TbFeCo/MAO heterostructure-based spintronic devices.

Experiment and modelling of texture and sliding direction dependence on finger friction behavior

Humans rely on their fingers to sense and interact with external environment. Understanding the tribological behavior between finger skin and object surface is crucial for various fields, including tactile perception, product appearance design, and electronic skin research. Quantitatively describing finger frictional behavior is always challenging, given the complex structure of the finger. In this study, the texture and sliding direction dependence of finger skin friction was quantified based on explicit mathematic models. The proposed double-layer model of finger skin effectively described the nonlinear elastic response of skin and predicted the scaling-law of effective elastic modulus with contact radius. Additionally, the skin friction model on textured surface considering adhesion and deformation factors was established. It revealed that adhesive term dominated finger friction behavior in daily life, and suggested that object texture size mainly influenced friction-induced vibrations rather than the average friction force. Combined with digital image correlation (DIC) technique, the effect of sliding direction on finger friction was analyzed. It was found that the anisotropy in finger friction was governed by the finger’s ratchet pawl structure, which also contributes to enhanced stick-slip vibrations in the distal sliding direction. The proposed friction models can offer valuable insights into the underlying mechanism of skin friction under various operating conditions, and can provide quantitative guidance for effectively encoding friction into haptics.

Theoretical investigation of electromagnetic-thermal coupling of double-layer cylindrical concrete under microwave irradiation

Many experiments have been performed to study the heating properties of concrete under microwave irradiation. Microwave provides the non-uniform heating process, which cannot be reflected clearly through the experimental investigations. In this paper, a theoretical method is presented to investigate the electromagnetic-thermal coupling process of double-layer cylindrical concrete under microwave heating. The wave transmission and reflection were considered. An analytic solution is presented to predict transient heating process within a 3-dimensional double-layer concrete model induced by microwave heating. The inner aggregate is a microwave high loss material and the outer mortar was microwave low loss medium. Poynting theorem was employed to calculate the electric field distribution and microwave energy loss within concrete. Transient heat transfer process with an internal microwave heat source was investigated based on the classical heat transfer theory by employing integral transform technique. The results indicate that microwave heating effect depend on the concrete size, dielectric properties as well as microwave energy input. The temperature gradient was formed at the mortar-aggregate interface, which varied with the microwave heating parameters inputs. The analytical study will provide significant insight to promote the understanding of electric and temperature field in the two-layer composite concrete materials under microwave heating.

Two-Layer Optimization Strategy of Electric Vehicle and Air Conditioning Load Considering the Benefit of Peak-to-Valley Smoothing

To satisfy the interests of multiple agents and those of comprehensive indicators such as peak-to-valley differences and load fluctuations occurring on the network side, this paper presents a flexible load demand-side response optimization method that considers the benefits of peak-to-valley smoothing. First, load aggregation modelling of air conditioning and electric vehicles was conducted, and the complementarity of the power consumption behavior of different types of flexible loads was used to improve the responsiveness of the load aggregator. Second, considering demand-side responses and taking into account the interests of both supply and demand, the load fluctuation and peak-to-valley difference on the network side are reduced, and a flexible load double-layer optimization model incorporating the peak-to-valley smoothing benefit is established. Finally, the effectiveness of the proposed optimization model is verified by using the KKT condition and the big M method to evaluate this two-layer optimization problem as a single-layer optimization problem. Comparative examples show that the proposed two-layer optimization method can take advantage of the complementarity of air conditioning and electric vehicles to improve the income of load aggregators. Moreover, the proposed method can effectively reduce the load peak-to-valley difference and load fluctuation of the distribution network by introducing the peak-to-valley smoothing benefit model.

A cloud-edge cooperative scheduling model and its optimization method for regional multi-energy systems

In the process of multi-energy system optimal scheduling, due to the high data processing requirements of the multi-energy devices and loads and the complexity of the operating states of the multi-energy devices, the scheduling optimization of the system is to some extent more difficult. To address this problem, this paper proposes a regional multi-energy system optimal scheduling model based on the theory of cloud-edge collaboration. First, based on intelligent data sensors, a cloud-edge cooperative scheduling framework of the regional multi-energy system is constructed. Then, the physical model of operating state data of multi-energy system equipment and the allocation mechanism of system scheduling tasks are studied. With the cloud service application layer and the edge computing layer as the upper and lower optimization scheduling layers, the double-layer optimization scheduling model of the regional multi-energy system is established. The objectives of the model are optimal scheduling cost and minimum delay of scheduling data transmission. The multi-objective whale optimization algorithm is used to solve the model. Finally, a simulation model is built for verification. The simulation results show that the scheduling model established in this paper can effectively improve the scheduling data processing capability and improve the economy of regional multi-energy system scheduling.

Analytical model for geotextile-enhanced horizontal drain vacuum consolidation of slurries

Horizontal drains are gradually introduced to the vacuum preloading method to improve dredged slurries by adding geotextiles to alleviate the blockage in the consolidation process. This study considers the consolidation of slurries enhanced by the vacuum preloading method with geotextile combined horizontal drains based on a double-layered consolidation model. The model approximates geotextile as a special soil layer possessing an equivalent consolidation factor. An analytical solution of the layered consolidation model is obtained using the Laplace transform and the finite Fourier transform method. The effectiveness of the solution is verified by comparing it with the one-dimensional double-layered consolidation solution and the one-dimensional consolidation with a partially permeable boundary. Through comparison with laboratory experiments, the model shows good fitness with the test results in the literature. The influences of related parameters, including the drain arrangement densities, soil parameters, and geotextile parameters, are discussed on average consolidation degree and pore water pressure. The influence mechanism is explained regarding drainage path and vacuum pressure transfer. Findings demonstrate that geotextile facilitates vacuum transfer and promotes soil consolidation, especially when the smaller density of drains’ deposition and lower soil permeability are applied.

Electrochemical corrosion behaviour of UNS S32205 duplex stainless steel dependent on sigma phase precipitation

Abstract In this study, the microstructure and electrochemical corrosion behavior of the UNS S32205 alloy were investigated. Firstly, the phase diagram of the studied samples was determined by Thermo-Calc 2022 software, and the solution treatment temperature was designated. The studied samples were cooled by various cooling rates following the solution treatment at 1050 °C for 30 min. The samples were characterized by optical microscope, scanning electron microscope, and XRD analysis. Also, electrochemical corrosion behavior was investigated by potentiodynamic polarization, cyclic potentiodynamic polarization and electrochemical impedance spectroscopy analyses. Microstructural examinations revealed that decreasing cooling rate causes the precipitation of the sigma phase, and the ratio of the sigma phase was increased up to 29 % by the decreasing cooling rate. Furthermore, it was determined that precipitation of the sigma phase reduces the E pit values, and the sample with the highest amount of sigma exhibits the lowest corrosion resistance. On the other hand, presence of the sigma changed the electrochemical impedance spectroscopy behavior of the UNS S32205 and double-layered model fit the results.

Metro Monolithic Track Bed Vibration Characterization

With the rapid development of cities, metro transportation has also developed rapidly to solve the congestion problems caused by urban development. However, with the continuous development of metro transportation, the vibration problems caused by it have become increasingly obvious. Based on the phonon crystal theory, this paper investigates the vibration characteristics of the metro track structure. It analyzes the influence of the track structure parameters on the band gap characteristics to regulate the metro vibration band gap range. To study the band gap characteristics of metro monolithic bed track structure, establish the double-layer Euler beam model and use the plane wave expansion method (PWE) to calculate its energy band structure; use the finite element method (FEM) to calculate to get its band structure, frequency response function, and time domain analysis. The calculation of PWE shows that there is a band gap in the range of 0–300[Formula: see text]Hz for the metro monolithic track bed, which is 0–194.5[Formula: see text]Hz; the calculation of FEM shows that the range of band gap is 0–193.7[Formula: see text]Hz. Fastening spacing, stiffness, and sub-slab support stiffness will have an impact on the band gap, so appropriate fastening and spacing need to be selected for effective vibration damping of the track structure. The results show that the band gap characteristics of the metro monolithic track bed can be calculated effectively and accurately by using the phononic crystal theory.

Analysis of the potential application of a residential composite energy storage system based on a double-layer optimization model

Along with the further integration of demand management and renewable energy technology, making optimal use of energy storage devices and coordinating operation with other devices are key. The present study takes into account the current situation of power storage equipment. Based on one year of measured data, four cases are designed for a composite energy storage system (ESS). In this paper, a two-tiered optimization model is proposed and is used to optimizing the capacity of power storage devices and the yearly production of the system. Furthermore, this paper performs a comparative analysis of the performance of the four cases from the energy, environmental and economic perspectives. It is concluded that this kind of energy storage equipment can enhance the economics and environment of residential energy systems. The thermal energy storage system (TESS) has the shortest payback period (7.84 years), and the CO2 emissions are the lowest. Coupled with future price volatility and the carbon tax, the electrothermal hybrid energy storage system (HESS) has good development potential. However, the current investment cost is very high, and it will not be possible to recover this cost in 10 years. Finally, it is recommended that the cost of equipment be reduced in combination with subsidies and incentives for further promotion. The research results not only fill a gap in the study area, but also provide some suggestions for further development of industry and research on user-side energy storage.