Simulation of hexavalent chromium removal by electrocoagulation using iron anode in flow-through reactor.

An electrocoagulation (EC) model is developed for hexavalent chromium reduction and precipitation, using iron electrodes. Parallel removal mechanisms such as adsorption of chromium on ferrihydrite and direct reduction at the cathode is assumed negligible due to low concentration of Cr(VI). The reaction model presented for batch system represents species complexation, precipitation/dissolution, acid/base, and oxidation-reduction reactions. Batch reactor simulation is verified using experimental data obtained by Sarahney et al. (2012), where the effect of initial chromium concentration, pH, volumetric current density, and ionic strength is considered (Sarahney et al., 2012). The model couples multicomponent ionic transport in MATLAB with chemical reaction model in PHREEQC, as a widely used computational programming tool and a geochemical reaction simulator with comprehensive geochemistry databases. The suggested current density is 0.05-0.3mA/cm2 and the surface to volume ratio in batch reactor is considered 0.017 1/cm. Design parameters are presented for operation of a flow-through hexavalent chromium removal using electrocoagulation by iron electrode to treat Cr(VI) in range of 10-50 mg/L. The operational parameters for a flow-through EC reactor for Cr(VI) removal is suggested to follow [Formula: see text] .

The Monitoring and Management of an Operating Environment to Enhance the Safety of a Container-Type Energy Storage System.

The implementation of an energy storage system (ESS) as a container-type package is common due to its ease of installation, management, and safety. The control of the operating environment of an ESS mainly considers the temperature rise due to the heat generated through the battery operation. However, the relative humidity of the container often increases by over 75% in many cases because of the operation of the air conditioner which pursues temperature-first control. Humidity is a major factor which can cause safety issues such as fires owing to insulation breakdown caused by condensation. However, the importance of humidity control in ESS is underestimated compared to temperature control. In this study, temperature and humidity monitoring and management issues were addressed for a container-type ESS by building sensor-based monitoring and control systems. Furthermore, a rule-based air conditioner control algorithm was proposed for temperature and humidity management. A case study was conducted to compare the conventional and proposed control algorithms and verify the feasibility of the proposed algorithm. The results showed that the proposed algorithm reduced the average humidity by 11.4% compared to the value achieved with the existing temperature control method while also maintaining the temperature.

An Efficient Methodology Combining K-Means Machine Learning and Electrochemical Modelling for the Determination of Ionic Diffusivity and Kinetic Properties in Battery Electrodes.

This paper presents an innovative and efficient methodology for the determination of the solid-state diffusion coefficient in electrode materials with phase transitions for which the assumption of applying the well-known formula from the work of Weppner et al. is not satisfied. This methodology includes a k-means machine learning screening of Galvanostatic Intermittent Titration Technique (GITT) steps, whose outcomes feed a physics-informed algorithm, the latter involving a pseudo-two-dimensional (P2D) electrochemical model for carrying out the numerical simulations. This methodology enables determining, for all of the 47 steps of the GITT characterization, the dependency of the Na+ diffusion coefficient as well as the reaction rate constant during the sodiation of an NVPF electrode to vary between 9 × 10-18 and 6.8 × 10-16 m2·s-1 and between 2.7 × 10-14 and 1.5 × 10-12 m2.5·mol-0.5·s-1, respectively. This methodology, also validated in this paper, is (a) innovative since it presents for the first time the successful application of unsupervised machine learning via k-means clustering for the categorization of GITT steps according to their characteristics in terms of voltage; (b) efficient given the considerable reduction in the number of iterations required with an average number of iterations equal to 8, and given the fact the entire experimental duration of each step should not be simulated anymore and hence can be simply restricted to the part with current and a small part of the rest period; (c) generically applicable since the methodology and its physics-informed algorithm only rely on "if" and "else" statements, i.e., no particular module/toolbox is required, which enables its replication and implementation for electrochemical models written in any programming language.

Prediction of lead leaching from galvanic corrosion of lead-containing components in copper pipe drinking water supply systems.

Galvanic corrosion is one of the main reasons for pipe degradation and lead contamination in drinking water systems. The electrical connection of dissimilar metals in corrosive tap water accelerates the dissolution rate of lead from leaded materials. This paper reports an electrochemistry based model to predict lead leaching from a copper pipe fitted with leaded connections. The corrosion of lead at the metal-electrolyte interface depends on the charge transfer and the electric field across the interface. The electric potential field and the mass transport process are dynamically coupled for corrosion propagation in stagnant water; they are respectively governed by the conservation of charge and reactant mass. Using polarization parameters for the electrodes as a function of concentration of oxidizing agents, a dynamic electrochemical model is developed to predict lead leaching from galvanic corrosion. The predicted lead and copper leaching curves are in good agreement with the experimental data for a lead-soldered coupled copper pipe, a brass valve coupled copper pipe, and a pure copper pipe. The findings offer a quantitative understanding on galvanic corrosion in drinking water supply systems and a practical modeling framework for prediction of lead leaching in tap water as a function of stagnation time.

Open-Source CFD Elucidating Mechanism of 3D Pillar Electrode in Improving All-Solid-State Battery Performance.

All-solid-state batteries (ASSBs) have become an important technology because of their high performance and low-risk operation. However, the high interface resistance and low ionic conductivity of ASSBs hinder their application. In this study, a self-developed electrochemical model based on an open-source computational fluid dynamics platform is presented. The effect of contact area reduction at the electrode/solid-state electrolyte interface is investigated. Then, a new conceptual 3D structure is introduced to circumvent the existing barriers. The results demonstrate that the discharge time is shortened by over 20% when the area contact ratio reduces from 1.0 to 0.8 at 1 C-rate, owing to the increased overpotential. By adopting the new 3D pillar design, the energy density of ASSBs can be improved. However, it is only when a 3D current collector is contained in the cathode that the battery energy/power density, capacity, and material utilization can be greatly enhanced without being limited by pillar height issues. Therefore, this work provides important insight into the enhanced performance of 3D structures.

Modelling the coupling of the M-clock and C-clock in lymphatic muscle cells.

Chronic dysfunction of the lymphatic vascular system results in fluid accumulation between cells: lymphoedema. The condition is commonly acquired secondary to diseases such as cancer or the associated therapies. The primary driving force for fluid return through the lymphatic vasculature is provided by contractions of the muscularized lymphatic collecting vessels, driven by electrochemical oscillations. However, there is an incomplete understanding of the molecular and bioelectric mechanisms involved in lymphatic muscle cell excitation, hampering the development and use of pharmacological therapies. Modelling in silico has contributed greatly to understanding the contributions of specific ion channels to the cardiac action potential, but modelling of these processes in lymphatic muscle remains limited. Here, we propose a model of oscillations in the membrane voltage (M-clock) and intracellular calcium concentrations (C-clock) of lymphatic muscle cells. We modify a model by Imtiaz and colleagues to enable the M-clock to drive the C-clock oscillations. This approach differs from typical models of calcium oscillators in lymphatic and related cell types, but is required to fit recent experimental data. We include an additional voltage dependence in the gating variable control for the L-type calcium channel, enabling the M-clock to oscillate independently of the C-clock. We use phase-plane analysis to show that these M-clock oscillations are qualitatively similar to those of a generalised FitzHugh-Nagumo model. We also provide phase plane analysis to understand the interaction of the M-clock and C-clock oscillations. The model and methods have the potential to help determine mechanisms and find targets for pharmacological treatment of lymphoedema.

Electrochemical modeling of microbial fuel cells performance at different operating and structural conditions.

Organic matters are directly converted to electricity by microorganisms in microbial fuel cells (MFC). Modeling the performance of MFC sheds light on the behavior of MFC in various operational conditions (e.g. pH and temperature). In the present research, three voltage losses were considered for modeling of the MFC polarization curve. The current research is composed of two parts. In the first part, the polarization curves of various MFCs with different substrates (synthetic wastewater or industrial wastewaters) were reproduced by our model, and model parameters were obtained using experimental data and genetic algorithm optimization. In this part, the electrical performance of 26 systems (12 systems with synthetic wastewater and 14 systems with industrial wastewaters) were modeled with average relative error (ARE) of 17% and a coefficient of determination of 0.9. In the second part, the influence of temperature, pH and hydraulic retention time on the electrical performance of MFC were studied. In this part, parameters were estimated by conventional (estimation of model parameters in each point), and a novel method (estimation of model parameters as a function of operating parameters). It was shown that using second tuning method, the number of estimated parameters decreased, while the error of the model remained at an acceptable level.

Modelling recovery of ammonium from urine by electro-concentration in a 3-chamber cell.

Electro-concentration enables treatment and nutrient recovery from source-separated urine, and is a potential technology for on-site treatment using a 3 compartment configuration that has anode, cathode and middle concentrate compartments. There is a particular focus on driving concentration towards the precipitation threshold in the concentrate compartment to generate solid ammonium salts, including ammonium bicarbonate. To evaluate controlling mechanisms and the feasibility of achieving high concentrations, a dynamic mechanistic model was developed and validated using experiments with synthetic urine. It was identified that high concentrations are prevented by increased back diffusion (diffusion from the middle chamber to the anolyte and catholyte) due to large concentration gradients, and the preferential migration of protons or hydroxide ions due to a loss of buffering capacity in the anolyte and catholyte (due to pH extremes). Model-based sensitivity analysis also identified that electrolyte ion concentrations (including buffer capacity) were the main controlling mechanisms, rather than membrane or electrolyte current transfer capacity. To attain high concentrations, operation should be done using a) a high current density (however there is a maximum efficient current density); b) feed at short hydraulic retention time to ensure sufficient buffer capacity; and c) a feed high in ammonium and carbonate, not diluted, and not contaminated with other salts, such as pure ureolysed urine. Taking into account electron supply and bio-anodic buffer limitations, model testing shows at least double the aqueous concentrations observed in the experiments may be achieved by optimising simple process and operational parameters such as flow rate, current density and feed solution composition. Removal of total ammonium nitrogen (TAN) and total carbonate carbon (TCC) was between 43-57% and 39-53%, respectively. Balancing the sometimes conflicting process goals of high concentrations and removal percentage will need to be considered in further application. Future experimental work should be directed towards developing electrodes capable of higher current densities. In addition it would be desirable to use ion exchange membranes with higher resistance to water fluxes and which limit back diffusion. Future modelling work should describe osmotic and electro-osmotic water fluxes as a function of the concentration gradient across the membranes and ionic fluxes, respectively. More generalised wastewater physico-chemistry speciation models should identify best methods where relatively simple Davies activity corrections do not apply.

Investigation on the Mechanical and Electrical Behavior of a Tuning Fork-Shaped Ionic Polymer Metal Composite Actuator with a Continuous Water Supply Mechanism.

This paper presents an innovative tuning fork-shaped ionic polymer metal composite (IPMC) actuator. With an integrated soft strain gauge and water supply mechanism (WSM), the surface strain of the actuator can be sensed in situ, and providing a continuous water supply maintains the water content inside the IPMC for long-term operation in air. The actuator was fabricated using a micromachining technique and plated with a nickel electrode. The device performance was experimentally characterized and compared with an actuator without a WSM. A large displacement of 1.5 mm was achieved for a 6 mm-long prong with 7-V dc actuation applied for 30 s. The measured current was analyzed using an electrochemical model. The results revealed that the faradaic current plays a crucial role during operation, particularly after 10 s. The measured strain confirms both the bending and axial strain generation during the open-and-close motion of the actuator prongs. Most of the water loss during device operation was due to evaporation rather than hydrolysis. The constructed WSM effectively maintained the water content inside the IPMC for long-term continuous operation.

Parameter-dependent behavior of articular cartilage: 3D mechano-electrochemical computational model.

BACKGROUND AND OBJECTIVE: Changes in mechano-electrochemical properties of articular cartilage play an essential role in the majority of cartilage diseases. Despite of this importance, the specific effect of each parameter into tissue behavior remains still obscure. Parametric computational modeling of cartilage can provide some insights into this matter, specifically the study of mechano-electrochemical properties variation and their correlation with tissue swelling, water and ion fluxes. Thus, the aim of this study is to evaluate the influence of the main mechanical and electrochemical parameters on the determination of articular cartilage behavior by a parametric analysis through a 3D finite element model. METHODS: For this purpose, a previous 3D mechano-electrochemical model, developed by the same authors, of articular cartilage behavior has been used. Young's modulus, Poisson coefficient, ion diffusivities and ion activity coefficients variations have been analyzed and quantified through monitoring tissue simulated response. RESULTS: Simulation results show how Young's modulus and Poisson coefficient control tissue behavior rather than electrochemical properties. Meanwhile, ion diffusivity and ion activity coefficients appear to be vital in controlling velocity of incoming and outgoing fluxes. CONCLUSIONS: This parametric study establishes a basic guide when defining the main properties that are essential to be included into computational modeling of articular cartilage providing a helpful tool in tissue simulations.

Altered swelling and ion fluxes in articular cartilage as a biomarker in osteoarthritis and joint immobilization: a computational analysis.

In healthy cartilage, mechano-electrochemical phenomena act together to maintain tissue homeostasis. Osteoarthritis (OA) and degenerative diseases disrupt this biological equilibrium by causing structural deterioration and subsequent dysfunction of the tissue. Swelling and ion flux alteration as well as abnormal ion distribution are proposed as primary indicators of tissue degradation. In this paper, we present an extension of a previous three-dimensional computational model of the cartilage behaviour developed by the authors to simulate the contribution of the main tissue components in its behaviour. The model considers the mechano-electrochemical events as concurrent phenomena in a three-dimensional environment. This model has been extended here to include the effect of repulsion of negative charges attached to proteoglycans. Moreover, we have studied the fluctuation of these charges owning to proteoglycan variations in healthy and pathological articular cartilage. In this sense, standard patterns of healthy and degraded tissue behaviour can be obtained which could be a helpful diagnostic tool. By introducing measured properties of unhealthy cartilage into the computational model, the severity of tissue degeneration can be predicted avoiding complex tissue extraction and subsequent in vitro analysis. In this work, the model has been applied to monitor and analyse cartilage behaviour at different stages of OA and in both short (four, six and eight weeks) and long-term (11 weeks) fully immobilized joints. Simulation results showed marked differences in the corresponding swelling phenomena, in outgoing cation fluxes and in cation distributions. Furthermore, long-term immobilized patients display similar swelling as well as fluxes and distribution of cations to patients in the early stages of OA, thus, preventive treatments are highly recommended to avoid tissue deterioration.

Study on the Carbonation Behavior of Cement Mortar by Electrochemical Impedance Spectroscopy.

A new electrochemical model has been carefully established to explain the carbonation behavior of cement mortar, and the model has been validated by the experimental results. In fact, it is shown by this study that the electrochemical impedance behavior of mortars varies in the process of carbonation. With the cement/sand ratio reduced, the carbonation rate reveals more remarkable. The carbonation process can be quantitatively accessed by a parameter, which can be obtained by means of the electrochemical impedance spectroscopy (EIS)-based electrochemical model. It has been found that the parameter is a function of carbonation depth and of carbonation time. Thereby, prediction of carbonation depth can be achieved.