Feed Flow Research Articles

Continuous UV/H2O2 Process: A Sustainable Wastewater Treatment Approach for Enhancing the Biodegradability of Aqueous PVA

Implementing efficient and cost-effective wastewater treatment methods in wastewater treatment plants (WWTPs) is crucial for ensuring sustainable development in contemporary societies. This study explores the feasibility of a continuous UV/ tubular photoreactor as a pre-treatment to enhance the biodegradability of aqueous polyvinyl alcohol (PVA) solutions, known as a nonbiodegradable wastewater. Using a combination of a Box–Behnken design (BBD) and the response surface methodology (RSM), three main process variables, including the PVA feed concentration, the inlet concentration, and the PVA feed flow rate, are studied within ranges of 500–1500 mg/L, 390–780 mg/L, and 50–150 mL/min, respectively. The results show significant interaction effects between the PVA feed and inlet concentrations on the effluent /COD ratio. The optimal operating conditions are determined using the RSM, with a PVA feed concentration of 665 mg/L, an inlet concentration of 390 mg/L, and a PVA feed flow rate of 59 mL/min. Operating at this point leads to an increase in the effluent /COD ratio from 0.15 to 0.53, which is validated experimentally with a ±5% error. Under these conditions, the effluent demonstrates an enhanced biodegradability, allowing for redirection to a subsequent biological post-treatment phase. This study demonstrates that using the UV/ process to enhance the biodegradability of an aqueous PVA solution is more economical than focusing on the complete removal of total organic carbon (TOC). Also, a comparison of these results with those of our previous study indicates that wastewater becomes more biodegradable by progressing the UV/ process due to the breakdown of polymer molecules, which reduces their molecular weight and makes them more consumable for biomass.

Supercritical water valorization of a model wastewater containing anxiolytic and antidepressant drugs: Experimental and thermodynamic assessment

This study presents a continuous hydrothermal process based on the supercritical water (ScW) technology for the treatment of pharmaceutical contaminants in wastewater. Using a simulated wastewater as feedstock, which was prepared with 5 psychoactive drugs (sertraline, paroxetine, zolpidem, escitalopram, and clonazepam), the impact of temperature, feed flow rate, and concentration of H2O2 in the degradation of organic matter was investigated. Thermodynamic aspects of the process were also assessed. The optimal conditions of treatment were at a temperature of 692.8 °C, feed flow rate of 6.6 mL/min, and H2O2 concentration in terms of oxidant coefficient (Ox. C.) of 1.03. Under these conditions, the experimental test achieved a total organic carbon removal efficiency (%RTOC) of 85.9 ± 0.5 %. Biochemical oxygen demand (BOD) and chemical oxygen demand (COD) concentrations decreased from 559.0 and 1118.4 mg/L to 66.0 and 152.5 mg/L, respectively. The liquid phase was also assessed by toxicity assays against Artemia salina microcrustaceans. For the gaseous phase, hydrogen was identified as the main component (57.7 %). Additionally, an assessment of the energy efficiency of the process scale-up was investigated. The ScW process showed a promising potential for large-scale continuous operations as an energy-efficient solution for wastewater treatment and valorization due to the concomitant production of H2-rich gas.

Utilizing waste heat in wastewater treatment plants for water desalination: Modeling and Multi-Objective optimization of a Multi-Effect desalination system using Decision Tree Regression and Pelican optimization algorithm

This paper examines the feasibility of using waste heat from wastewater treatment plants (WWTPs) for water desalination. A model was developed to utilize waste heat from the gensets at As Samra WWTP in Jordan, using real data and TRNSYS® software to calculate available waste heat. The desalination process was then modeled with ASPEN PLUS® software, focusing on multi-effect desalination (MED). Both series and parallel configurations for the MED system were compared. The study investigated the effects of system feeding flow rate, feeding pressure, and heat input on productivity, performance ratio, and recovery ratio. The study also introduces a novel optimization technique combining machine learning and modern optimization algorithms to maximize system productivity and performance. Initially, a decision tree regression (DTR) model is developed to establish relationships between key independent variables (flow rate, feed pressure, and heat input) and dependent variables (productivity, performance ratio, and recovery ratio). The Pelican Optimization Algorithm (POA) is then used to identify the optimal values of the independent variables for maximum productivity and performance. The results show that using a series configuration yields a system productivity of 3984.2 kg/hr, a performance ratio of 3.78, and a recovery ratio of 0.991 at a feed flow rate of 4000 kg/hr, feed pressure of 3 bars, and heat input of 719 kW. Optimal productivity (4421 kg/hr), performance ratio (3.81), and recovery ratio (0.851) are achieved at a feed flow rate of 5166 kg/hr, feed pressure of 3.2 bars, and heat input of 794 kW. The techno-economic assessment indicates a levelized cost of water of 1.63 USD/m3 for parallel configurations and 1.65 USD/m3 for series configurations, with a payback period of less than two years.

Energy cost prediction for chromium removal by nanofiltration membrane

Abstract This paper aims to investigate the energy cost of eliminating Cr(VI) by nanofiltration membranes (NF). The modified pore flow model was utilized to predict the performance of NF membrane in terms of ion retention and water productivity. Then, the energy cost was estimated according to the obtained results from this model as well as available data from literature. The effect of feed flow, applied pressure, and temperature on energy cost were highlighted and thoroughly assessed. It is shown that high retention values can be achieved with relatively high energy cost. Nonetheless, energy cost of 0.04 $/m3 have been estimated for Cr retention less than 95 % at a pressure of 5 bar. It is also assessed that feed flow has a significant influence on energy cost relative to other operating parameters. In particular, increasing feed flow from 40 to 760 L/h leading the energy cost to be increased by twelve times. At high feed flow, however, energy cost can be largely reduced by applying pressure higher than 10 bar. It is concluded that high feed temperature is favored if there is no need for heating equipment.

Innovative utilization of olive mill wastewater phenolics extracted by lecithin: spray-dried powders in cake formulations

In the present study, the olive mill wastewater (OMW) phenolics were extracted with soy lecithin using the cloud point extraction method, and this enriched lecithin (OMW-L) was converted into spray-dried powders using maltodextrin (MD) and whey protein concentrate to be utilized as a dry food ingredient in a cake premix. The inlet temperature of 170 °C and a 3 mL/min feed flow rate yielded the highest powder yield (70.88 ± 2.12%) with a moisture content of 3.78 ± 0.03% when the mass ratio of lecithin to MD was 1:3 (w:w). The hydroxytyrosol and tyrosol contents of the powder were 42.60 ± 4.51 mg/100 g and 15.48 ± 2.50 mg/100 g, respectively. Vanillic acid, caffeic acid, 3-hydroxybenzoic acid, catechin, and rutin were also identified in the powders. The spray-dried OMW-L powder with a higher loading of polyphenols was then used in a cake premix, replacing 1% and 3% of wheat flour. This substitution significantly reduced the K value of the cake batter, as determined by rheological analyses. The addition of spray-dried OMW-L powder to the cake samples, particularly at higher concentrations (3%), influenced both crust and crumb color, causing changes in L*, a*, and b* values. The hardness values of the cake samples did not alter when blank or OMW-enriched lecithin powders were added; rather, the hardness value was influenced by the powder content. Overall, this research offers a different perspective on the use of OMW phenolics in food applications, especially in ready-to-use blends, and demonstrates the effects of the obtained spray-dried lecithin powders on batter rheology and cake characteristics.Graphical abstract

A vapor phase side stream intensified extractive distillation process for separation of azeotropic mixture 2, 2, 2-trifluoroethanol and water

2,2,2-Trifluoroethanol (TFE) is an important organic fluoride with various commercial applications. During the production of TFE through hydrolysis, an azeotrope of TFE and water can form, making it challenging to separate using conventional distillation. This study proposes a novel approach employing vapor phase side stream intensified extractive distillation separation (VSED) with glycerol serving as an entrainer to address this challenge. Additionally, a dividing wall column process (DWC) is established. The total annual cost (TAC), CO2 emissions and total energy cost (TEC) of the proposed separation processes are calculated and compared. The results indicate that VSED process can recover TFE with a purity of 0.9995 (mole fraction). VSED exhibits a TAC reduction of 34.2 % and a CO2 emissions reduction of 33.9 % compared to the CED process. In addition, a dual-composition control strategy is proposed for the VSED process. The results show that control strategy can effectively cope with the feed flow perturbation of ±20 % and the feed composition perturbation of ±5 %.

Membrane fouling analysis of air-gap membrane distillation (AGMD) for recovery of water and removal of antibiotics from a model wastewater containing antibiotics and humic acid

The study investigates the efficiency of air-gap membrane distillation (AGMD) in water recovery and antibiotics removal from wastewater, focusing on high-concentration scenarios. Experimental findings reveal enhanced membrane performance with increasing the feed temperature, resulting in vapor permeate fluxes of up to 5 kg/m2.h at higher temperatures. Despite experiencing flux reduction caused by fouling from humic acid (HA) in the feed antibiotics solution, the antibiotics consistently maintain near-complete rejection rates (>99%) over 48 h. The foulant on the membrane surface was illustrated by SEM imaging. To know the temperature polarization and the fouling resistance, mathematical modeling was used, and it validates experimental results, elucidating temperature polarization effects and mass transfer coefficients. An increase in feed flow rates reduced thermal boundary layers, enhancing heat flux. Higher temperatures reduced HA fouling resistance. Therefore, AGMD proves effective in water recovery and antibiotics removal, with mathematical models aiding fouling understanding for future research and detailed computational fluid dynamics (CFD) models.

Spray-Dried Jaboticaba Powder as Food Resource

Jaboticaba, a popular Brazilian fruit, has recently garnered scientific interest due to its nutritional properties and high levels of bioactive compounds. However, this fruit is highly perishable due to its high moisture content and physical–chemical structure. Therefore, it is imperative to employ methods for preserving it and explore its potential as a food resource. This study investigates the use of a spray drying method to dehydrate whole jaboticaba fruits. The effects of air temperature (T) ranging from 67.9 to 132.1 °C, air flow rate (AF) from 1.54 to 1.86 m3/min, maltodextrin concentration (M) from 8.9 to 41.1%, and feed flow rate (FF) from 0.36 to 0.84 L/h on the moisture content, drying yield, and bioactive compounds (total phenolic, total flavonoid, citric acid, and ascorbic acid contents) were quantified. The results indicate that spray drying can produce a powder with reduced moisture content levels, a satisfactory drying yield, and high levels of bioactive compounds if performed under specific conditions. An optimization study using desirability analysis shows that having T, AF, M, and FF at 132.1 °C, 1.86 m3/min, 15.0%, and 0.4549 L/h, respectively, is the optimal condition for the studied variables. Spray drying has proven to be a very promising alternative for jaboticaba processing, enabling better applications as a food resource.

Mathematical Modeling of NaCl Scaling Development in Long-Distance Membrane Distillation for Improved Scaling Control.

Membrane distillation is a novel membrane-based separation technology with the potential to produce pure water from high-salinity brine. It couples transport behaviors along the membrane and across the membrane. The brine in the feed is gradually concentrated due to the permeate flux across the membrane, which is a significant factor in initiating the scaling behavior on the membrane surface along the feed flow direction. It is of great interest to investigate and estimate the development of scaling on the membrane surface. This work specifically focuses on a long-distance membrane distillation process with a sodium chloride solution as the feed. A modeling approach has been developed to estimate the sodium chloride scaling development on the membrane surface along the flow direction. A set of experiments was conducted to validate the results. Based on mathematical simplification and analytical fitting, a simplified model was summarized to predict the initiating position of sodium chloride scaling on the membrane, which is meaningful for scaling control in industrial-scale applications of membrane distillation.

Performance of capacitive deionizing membrane distillation (CDIMD) process for the organic sewage treatment and how operating parameters can affect it

To solve the fouling issue of traditional membrane distillation (MD) technique, a newly-designed hybrid purification system integrating capacitive deionization (CDI) with MD technology was established for the organic sewage treatment in this study, namely capacitive deionizing membrane distillation (CDIMD) technology. Complexes formation via cross-linking among protein, divalent cations, and polysaccharide, an archcriminal inducing MD fouling, was remarkably alleviated in the CDIMD system considering that negatively-charged organics were clearly divided away from those divalent cations in an electric field circumstance. The CDIMD performance was deeply explored in this study focusing on the impact mechanisms of core operational parameters. An appropriate increment of feed temperature (60–65 °C) and feed flow velocity (15.72–17.82 mm/s) contributed to the anti-fouling performance of CDIMD. Considering the side reactions at voltage >1.2 v, setting working voltage at around 1.2 v seemed to be optimal for CDIMD operation. With an overall consideration of pure water production and anti-fouling performance, a properly thicker CNTs layer (40–60 μm) efficiently enhanced the fouling mitigation of CDIMD. A frequent switching of electric field direction (9/1 min) facilitated the timely regeneration of electrode and composite membranes, accordingly promoting a reliable purification of organic wastewater by CDIMD technique.

Electrospun O-quaternary ammonium chitosan/polyvinyl alcohol nanofibrous film by application of Box–Behnken design response surface method for eliminating pathogenic bacteria

In this study, O-quaternary ammonium chitosan (O-HTCC) containing bicationic antibacterial active groups was synthesized to develop an O-HTCC/PVA porous nanofibrous film to enhance antibacterial activity, leveraging surface modification and nano-porous structure design. Uniform and smooth nanofibrous structures (average diameter: 72–294 nm) were successfully obtained using a simple and feasible electrospinning method. A response surface model via Box-Behnken design (BBD) was used to clarify the interaction relationship between O-HTCC fiber diameter and three critical electrospinning parameters (O-HTCC concentration, applied voltage, feed flow rate), predicting that the minimum O-HTCC fiber diameter (174 nm) could be achieved with 7 wt% of O-HTCC concentration, 14 kV of voltage, and 0.11 mL/h of feed flow rate. Linear regression (R2 = 0.9736, Radj2 = 0.9716) and the Anderson Darling test demonstrated the excellent fit of the RSM-BBD model. Compared to N-HTCC/PVA nanofibrous film, the O-HTCC/PVA version showed increased growth inhibition and more effective antibacterial efficacies against Escherichia coli (E. coli) (~;86.34 %) and Staphylococcus aureus (S. aureus) (~;99.99 %). DSC revealed improved thermal stability with an increased melting temperature (238 °C) and endothermic enthalpy (157.7 J/g). This study holds potential for further development of antibacterial packaging to extend food shelf-life to reduce bacterial infection.

Computational fluid dynamic model for the prediction of the unsteady operation process of a non-dispersive gold extraction from wastewater

The current study tries to investigate gold extraction in a membrane extractor in unsteady mode. The model was successfully validated using experimental results. The results showed that the diffusive flux on the zone close to the membrane surface is dominant in the first minutes of extraction but later the convective flux is the main flux, particularly at the centre of the shell side. The extraction time of one hour was not ample to extract all gold from the aqueous solution when the volume of solutions was 2000 mL and 3000 mL. Finally, the change in feed flow rate in the range of 30–55 cm3/min did not have a significant influence on the gold extraction time. However, the outlet dimensionless concentration of gold after one hour was increased from 0.24 to 44 with the increase of feed flow rate from 30 cm3/min to 55 cm3/min.

Toward smart wastewater treatment plants: a novel data-driven sludge blanket model based on stochastic differential equations

ABSTRACT A novel data-driven model for forecasting the sludge blanket height in secondary clarifiers is presented. The model is trained on sensor measurements of the sludge blanket height and used as inputs such as (1) the clarifier feed flow rate, (2) feed suspended solids concentration, and (3) the clarifier recycle flow rate. The model’s prediction accuracy is evaluated based on data from two Danish wastewater treatment plants by means of root-mean-square errors (RMSEs), and results are compared against a persistence model. We demonstrate that the developed model is superior to the persistence forecast at both plants during high blanket dynamics. In the best scenario, the model improves the RMSE by 0.1/0.4 m at prediction horizons of 2.5/10 h, assuming known inputs. The model performance is subsequently considered with forecasted inputs using two different forecast scenarios. We discuss differences in the two plants’ performance and requirements to achieve good model performance. The model is well-suited for a model predictive control strategy, whose purpose ultimately is to improve clarifier control, increasing hydraulic capacity and reducing overflow suspended solids.

Fractional neutron point kinetics model for reactivity transients of the NuScale and comparison with the classical kinetics approach

In this work, the behavior of the neutron and natural circulation parameters for Reactivity Transients in the PWR reactor called NuScale are analyzed through the novel system equations. It model includes non-integer and ordinary order differentials coupling the neutron point kinetic with the thermos-hydraulic core of the reactor. Transient processes of increase and decrease of the feed flow and the coolant inlet temperature are analyzed to identify the feedback of the thermohydraulic effects with the neutron phenomena in a non-integer order scheme. In the results, it is observed that for short times the power and reactivity have the same behavior with the classical model and the non-integer order model for all values of the anomalous diffusion coefficient simulated. However, for long times of simulation, there is more reactivity and less power, in contrast to the classical model, when reducing the value of the anomalous diffusion coefficient these counter-intuitive effects are increased. Additionally, a delay is observed between the change in reactivity and power. In conclusion, it is observed that sub-diffusive processes are relevant when there are slow changes in reactivity, which can be analyzed through the Fractional Order Neutron Density Equation.

Exploring the performance of Co/Al2O3–ZrO2 nanocatalysts developed through the thermal evaporation method in dry reforming of methane

Abstract This study aimed to investigate the performance of the thin layer nanostructures of Co/Al2O3–ZrO2 in the dry reforming of methane (DRM) in a microchannel reactor. The nanostructures were prepared via utilizing the thermal evaporation method. Reactor tests were carried out at various coating times of 2, 3, and 4 min and temperatures of 700, 750, and 800 °C with a feed flow rate of 10 ml/min and a 1:1:8 ratio of helium, carbon dioxide, and methane. Also, grazing incidence X-ray diffraction (GIXRD), field emission scanning electron microscopy (FESEM), and energy-dispersive X-ray (EDX) were used to identify catalyst features. According to the obtained results, the highest percentage of conversion in all samples was observed at 800 °C. The results of the reactor tests also revealed that the activity of catalyst layers highly depends on coating time. The findings demonstrated that raising deposition time improves the distribution of particle size and catalyst loading. Considering the nanostructure of Co/Al2O3–ZrO2, the sample undergoing 4 min coating time yielded the highest amount of primary methane conversion (89.3 %), primary carbon dioxide conversion (92.4 %), and H2/CO molar ratio (0.91). The stability test of the catalyst layers for 28 h at the optimum condition (P = 1 atm, T = 800 °C, t = 4 min deposition time, CH4/CO2 = 1, and GHSV = 48,000 mL g−1 h−1) showed that the catalysts prepared by this method had a good stability.

Dynamic Control Analysis of Various Side‐Stream Quaternary Extractive Distillation Configurations

AbstractA thermally coupled distillation technology can bring energy‐saving benefits, but it poses challenges to process control. This article explores dynamic control of different side‐stream quaternary extractive distillation configurations. One the one hand, the open‐loop controllability of these processes is analyzed in terms of various criteria by the control design interface technology of Aspen Plus Dynamics. On the other hand, their control structures are established and examined by introducing large feed flow and composition perturbations. The results show that the triple‐side‐stream distillation still performs the best state and input–output controllability in spite of the strongest nonlinearity, and is also well resistant to large feed perturbations using a simple control structure.

Integrating physical knowledge and artificial intelligence approaches for simulation and optimization of direct urea fuel cell

Direct urea fuel cell (DUFC) has recently gained attention as a potentially effective fuel cell because of urea’s ease of use, low-cost, high-energy density, and toxicity-free nature. To develop a fast and accurate mathematical tool to model and optimize the performance of DUFC, this study, for the first time, combined the kinetic model and artificial intelligence approaches. Accordingly, an artificial neural network (ANN) model was developed based on the synthetic datasets produced from the verified kinetic model and then was optimized by particle swarm optimization to determine the optimal conditions for DUFC. The peak power density output and substrate-based energy recovery were chosen as the target functions that depend on several fundamental operating and designing parameters (i.e., types of catholyte, membrane thickness, diffusion layer thickness and porosity, feeding flow rate, temperature, urea and KOH concentrations). Along with significantly reducing the computational simulation time to the kinetic model (from 1500 s to 2 s), the proposed approach exhibited superior accuracy compared to the response surface methodology. With nickel nanoparticles as the anode catalyst material and pure oxygen as the catholyte, the highest power density output and energy recovery from DUFC were predicted at 15.1 mW/cm2 and 19.6 %, respectively. On the other hand, with the natural air supply, the optimal power density and energy recovery values were only 14.4 mW/cm2 and 18.9 %, respectively, due to lower oxygen concentration. These poor performances suggest that more efficient catalyst materials for DUFC need to be further investigated and applied.

Experiment Evaluation on the Porosity of Plasma Coating from Ceramic Al2O3 – TiO2 Using the Metallography

Background: The objective of this paper is an experimental investigation of the metallographic porosity of plasma coating using standard materials from the ceramic system Al2O3-TiO2 on the substrate of steel SS400 at laboratory scale Lab at the Research Institute of Mechanical Engineering. Contribution: The main contribution of the research is the evaluation of the porosity of the coating under the influence of the main technological parameters since the porosity plays a significant role in the performance of the working surface using the built-in Image Pro-Analyzer software in the Axiovert 25 MAT microscope. Method: The spraying material is Al2O3-TiO2 powder. The input parameters are: spraying distance (Lp; current of plasma stream (Ip); powder feed flow (Gp and spraying rate (Vp). Results: The findings show that the average porosity of the Al2O3-TiO2 plasma coating is inversely decreasing in the increasing direction of the distance: spray in the range Lp = 100–200 mm, increase proportional to the increase of the current plasma flow rate in the range Ip = 400–600 A, provided that the powder feed flow Gp = 1.7 kg/h and the spraying rate Vp = 50 mm/min. Conclusion: The degree of influence of the three main technological parameters (Lp, Ip, and Gp) in the survey limit domain may be due to the selected Lp spray distance within the relatively wide recommended range of the plasma spraying equipment supplier. It is recommended to conduct the experimental planning of the L27 type to localize the optimum area.

Fault root cause analysis using degree of change and mean variable threshold limit in non-linear dynamic distillation column

The chemical industrial processes are both dynamic and complex. The presence of instability and danger in the production process poses significant challenges to safety management. Early and accurate fault diagnosis is essential to ensure a sustainable and stable chemical process performance. Most studies in literature do not provide detailed information about diagnosing the root cause of faults in distillation columns using contribution plots. Using principal component analysis (PCA) in conventional contribution plots leads to a large number of contributing variables, making it difficult to identify the root cause of a specific fault. In this study, the authors suggest employing the Degree of Change of Contribution Values (DCC) and Mean Variable Threshold Limit (LMVT) techniques alongside the Wavelet Transform-Principal Component Analysis (WT-PCA) method to decrease the quantity of fault identification variables in a non-linear system (distillation column). The Aspen Plus software is utilized to perform a dynamic simulation of a distillation column, generating data for both normal and faulty operations. Two distinct types of faults are considered, which include loss of feed flow and feed temperature changes. This study aims to analyze the results obtained from the Hotelling T2 and SPE contribution plots by calculating the average difference between the normal and faulty conditions using the Degree of Change in Contribution Values. This procedure is performed to determine the extent of deviation from the standard state. Subsequently, the variables that have surpassed the threshold limit for means variables (LMVT) are designated as the variables that serve as the primary underlying cause of the fault. The technique was employed in a case study involving a nonlinear distillation column, and the results indicate that only one "dominant" variable intersects the LMVT by Hotelling T2, which represents the true underlying cause of the corresponding fault.

Removal of Chromium ions (Cr6+) and Nickel ions (Ni2+) from Simulated Industrial Wastewater Using Flow-by-Porous Electrode

The quality of water is significantly impacted by the presence of Cr6+ and Ni2+ ions. This study investigates the effectiveness of a flow-by porous graphite electrode cell in removing these contaminants from simulated industrial wastewater. We explore the impact of various factors on the removal process, demonstrating the method's potential for efficient removal. The initial concentration of nickel and chromium ions (20 to 80 mg/l and 20 to 100 mg/l, respectively), the feed flow rate (0.28 to 1.11 ml/s), current density (0.2 to 2.25 mA/cm2) and pH all influence the removal rate and efficiency. A higher feed flow rate negatively affects the removal efficiency of both Ni2+ and Cr6+ ions. Nickel removal efficiency decreased by 34.9% at 20 ppm and 26% at 80 ppm, representing the highest and lowest reductions in efficiency, respectively. Chromium removal efficiency decreased by 19% at 100 ppm and 6.5% at 50 ppm, indicating the highest and lowest reductions in efficiency, respectively, under the same flow rate change. Under optimal conditions, the removal efficiency for Ni2+ was 99.47% after 15 min of operation at a current density of 1.96 mA/cm2, a flow rate of 0.28 ml/s, and a pH of 8 and the removal efficiency for Cr6+ was 99.97% after 10 min of operation at a current density of 2.25 mA/cm2, a flow rate of 0.28 ml/s, and a pH of 2. The flow-through porous electrode system achieves efficient heavy metal removal with operating costs of 0.24 USD/m3 for nickel and 0.38 USD/m3 for chromium at optimal conditions.