Chemical Engineering Journal Advances最新文献

The electrochemical determination of chemical oxygen demand (COD) presents a promising alternative to the standard method, addressing concerns related to toxic chemicals, extended measurement time, and automation challenges. This review aims to comprehensively examine the current state of research and offer insights for future advancements. The discussion spans three key areas: working electrode materials (including Cu-based, carbon-based, Boron-Doped Diamond (BDD), and PbO₂), electrochemical methods (amperometry, coulometry, and voltammetry), and measurement setups. Special emphasis is placed on exploring the dependencies of the amperometric method on organic compounds and discerning the distinct application scopes of various electrochemical methods. Future perspectives are outlined for each research aspect. The review also delves into the evaluation of developed methods, proposing measures for a more standardized and cohesive evaluation approach. Through these efforts, the review seeks to propel research towards the practical application of electrochemical COD determination.

In the current era of wastewater treatment, integrating reusable water production with resource recovery is a key goal. This study aims to treat fuel-synthesis wastewater (FSW), intending to recover various resources, including polyhydroxybutyrate (PHBs), single cell protein, bacteriochlorophylls, carotenoids, and coenzyme Q10 from suspended and biofilm growth to decrease the harvesting costs. The study considered the treatment process, biofilm growth, and resource recovery potential in a mixed-culture system enriched with purple non-sulfur bacteria for treating FSW. Specifically, the effects of four different FSW strengths (25–100 %) and nitrogen sufficiency (N⁺) or deficiency (N⁻) were evaluated in eight biofilm photobioreactors. This study observed a direct correlation between the concentration of FSW and PHB content; specifically, as the FSW content decreased from 100 % (undiluted) to 25 % the PHB content decreased. The undiluted condition achieved 17 % dry cell weight as PHB in the suspended growth and 22.6 % in the biofilm growth under N⁻ condition. The protein content ranged between 33 and 44 %, and the presence of nitrogen had a slight positive effect on higher protein content. No trend was observed for carotenoids or bacteriochlorophylls in the N⁻ condition. In contrast, for the N⁺ condition, the concentration of bacteriochlorophylls increased with decreasing wastewater concentration under suspended growth, while it decreased with decreasing wastewater concentration under biofilm growth. Coenzyme Q10 concentration was enhanced under the most growth-limited condition (25 %, N⁻). PHB and protein content of these resources seem most promising when using N⁻ and N⁺ conditions, respectively.

The viscosity of highly concentrated slurries is reduced by adding a small amount of fine particle with the same material of main particles (high concentration ratio particles per total concentration) in the slurries. We investigated how added fine particles affect the liquid behavior and forces acting on the main particles in the slurry by using direct numerical simulations, and we examined one factor that contributes to the viscosity reduction mechanism in highly concentrated slurries containing a small amount of fine particle. The results indicated that whether fine particles are coated (they contact) on the surface or not have little influence on the change in forces acting on the main particles. In highly concentrated slurries containing a small amount of fine particle, there was a large change in the liquid velocity between and around the main particles. From these results, we proposed a possible mechanism to assist in reducing the viscosity of highly concentrated slurries containing a small amount of fine particle. The magnitude and direction of the forces acting on each main particle were non-uniform by adding fine particles, resulting in non-uniform strength within the main particle bed in the slurry, which could facilitate particle bed deformation and assist in reducing the viscosity.

Climate change and the continual rise in cooling demand means more efficient and environmentally friendly refrigeration technologies are required more than ever. One attractive route to reducing future demand is to improve adsorption refrigeration technologies based on natural refrigerants such as ammonia. The choice of ammonia adsorbent plays an important role in achieving improved refrigeration efficiency and suitable operating conditions. This paper reports a detailed study on the suitability of zeolites as an adsorbent of ammonia in refrigeration applications. Systematic Monte Carlo simulations were conducted to study ammonia adsorption in five high-silica zeolites with a wide range of pores sizes and porosities. Simulations were carried out at temperatures between -50 and 50°C and pressures up to 4.0 bar. It is found that zeolites, in particular the ones with large porosities, could be very good ammonia adsorbents for adsorption refrigeration applications, since their use allows for large refrigeration capacities and tuneable operating conditions with good coefficients of performance (COP).

Excessive phosphorus load to surface water is undesirable since it can cause eutrophication. In this study, three different pyrolyzed hydrochars from corn stover were synthesized by applying hydrothermal carbonization (HTC) at 260 °C and then eventual pyrolysis at 400°, 600°, and 800 °C, respectively, and finally were used for phosphorus removal from aqueous solution. By linking the physicochemical properties of these pyrolyzed hydrochars investigated here, we tried to comprehend the effect of HTC and pyrolysis temperature on the hydrochar structure and phosphorus adsorption. Results show that high pyrolysis temperatures (600 °C and 800 °C) enhanced the hydrochar's phosphorus adsorption compared to low pyrolysis temperature (400 °C). HTC260P800 type hydrochar showed a fast phosphorus adsorption kinetics, while the HTC260P600 showed an overall high adsorption capacity, with the maximum phosphate adsorption capacity of 5090 mg/kg calculated using isotherm model. Three different adsorption isotherm models (Langmuir, Fruendlich, and Redlich-Peterson) were used to fit the isotherm data; among them, the Redlich-Peterson isotherm model fit the data best for all three hydrochars. pH was found to be a critical factor in terms of phosphorus removal, and the optimum pH was found to be 5, probably due to the enhanced electrostatic interaction between positively charged hydrochar and negatively charged phosphate ions. The desorption experiment showed that a small fraction of the adsorbed phosphate (15.6 % to 24.4 %) was released from the spent hydrochar samples, which might be due to the strong attachment of phosphate ions to the sorption sites. Reusing the spent pyrolyzed hydrochar showed lower phosphate adsorption capacity than the fresh ones, ranging from 423 mg/kg to 903 mg/kg.

Methylene blue (MB) is a well-known dye that is used in many industries and is highly polluting to the environment. Therefore, this paper proposes using sunflower husks (SFH) through a coating with a nanomaterial made of silicon dioxide (SiO₂) with a weight percentage (w/w) of 5:1 to produce (SFH-SiO₂) nanoparticles for removing MB from aqueous solutions. This method, known as green synthesis, is characterized by being environmentally friendly and low-cost, as well as efficient in the removal process. The prepared composite was characterized by conducting analysis using Field emission scanning electron microscopy (SEM) with (EDX), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR) were used to look at the samples. The optimal conditions for the removal process were found to be at a pH of 6, with 0.2 g/50 mL of dose adsorbent. At a temperature of 25 °C, the best time to remove the dye was 150 min. With a maximal adsorption capacity (q_max) of 70.16 mg g⁻¹, the findings match the Freundlich model. The adsorption process follows a pseudo-second-order. The negative value of Gibbs free energy (ΔG^°) indicated the reaction was spontaneous. (SFH-SiO₂) nanoparticles could represent a suitable method for removing cationic dyes from aquatic environments.

All solid-state batteries, combining metallic lithium with a solid-state electrolyte, are now considered as a very promising answer to the growing need for higher energy density in safer batteries. While research interests are quickly raising on this topic, the number of experiments to perform in order to find the best combination of active material and solid electrolyte composition could be infinite. Therefore, an easy and low computational-cost model forecasting all solid-state cells performance could accelerate the optimization and lower the number of experiments, reaching more rapidly an up scalable solution.

In this work, an innovative electrochemical model for a metallic lithium – argyrodite Li₆PS₅Cl – NMC622 cell is developed. In particular, two important aspects, characterizing this new battery generation, are implemented inside a P2D model.

The first aspect is the implementation of a solid-state electrolyte, in substitution to liquid electrolyte, which means using the single ion conducting electrolyte theory, according to which Ohm's law is the only equation to be solved in the electrolyte domain. This reduces the number of parameters characterizing the electrolyte from three, for the liquid electrolyte (ionic conductivity, transference number, and mean molar activity coefficient), to only one, for the solid electrolyte (ionic conductivity). The second aspect regards the anode side, lithium metal is chosen, in substitution to graphite, and this implies a different treatment from an electrochemical point of view, which is to consider the anode as a boundary condition instead of a porous electrode. Such drastic simplification of the P2D model allows, after careful calibration and validation based on experimental data, to obtain reliable charge/discharge profiles at C/10 and C/5 for lithium – argyrodite Li₆PS₅Cl – NMC622 cells.

Electrochemical pathogen sensing has gathered limelight for its effective and ultrafast detection capabilities. More recently, several electrochemical sensors were developed to counter the increasing testing requirement for the 2019 coronavirus disease (COVID-19) diagnosis. One such sensor developed was the Ultrafast COVID-19 (UFC-19) diagnostic sensor which could detect the SARS-CoV-2 spike protein in saliva samples. Although UFC-19 was established in literature to sense SARS-CoV-2 in saliva samples, the factors causing such an interaction or parameters to model such an interaction are yet to be studied in detail. In this work, an attempt has been made to electrochemically characterize the interactions at the interface by employing cyclic and linear sweep voltammetry on a rotating disk electrode setup. As a result, electrochemical parameters were calculated using chemical and electrochemical principles. The electrochemical surface area, electrode surface coverage, diffusion coefficient, reaction order with respect to SARS-CoV-2 whole virus, electron transfer coefficient have been estimated providing additional insights into the events occurring at the electrical double layer. The reaction order for the interaction was reckoned to be 0.7 confirming a non-elementary, multi-step process occurring at the interface. Theoretical and experimental calculations confirm higher hydroxide ion accumulation at the interface in the presence of SARS-CoV-2 whole virus. Results from this work lay the foundation for developing models for electrochemical SARS-CoV-2 interaction and possible extension toward other pathogenic viruses.

In this study, first, a fed-batch biogas fermenter was established using anaerobic digester sludge treating secondary sludge from a municipal wastewater treatment plant and operated for 120 days on glycerol as the sole substrate. Then, the prefiltered effluent of the anaerobic digester unit was loaded subsequently into a stirred-tank coupled with a hollow-fibre, polydimethylsiloxane (PDMS) gas-liquid membrane contactor and a dissolved methane sensor for studying the gas recovery process under continuous biogas supply, consisting of CH₄ and CO₂ in different proportions (70/30 CH₄/CO₂ vol.%; 50/50 CH₄/CO₂ vol.%; 30/70 CH₄/CO₂ vol.%.). Experiments showed that besides the actual composition of the internal biogas, the ratio (0.5–2) of sweep gas (N₂) and effluent (liquid) volumetric flow rates (G/L) could be a crucial operating factor with influence on the degassing efficiency attainable by the 1 m² PDMS membrane module. Results were compared to the performance of the same PDMS membrane module working with synthetic anaerobic digester effluents, indicating the dissolved methane recoveries observed with the synthetic effluents (>50 %) considerably surpassed those with the real effluent (<20 %) where the dissolved methane concentrations, at G/L of 1, were in the range of 12.4 to 17.3 mg L⁻¹.

Ability to characterise droplet size distribution (DSD) of emulsions in real-time is essential for on-demand production of customised emulsions. In this work, for the first time, we demonstrate a possibility of estimating full DSD of oil in water emulsions from turbidity measurements using a single wavelength light source. We used recently published data of DSD and turbidity measurements of rapeseed oil in water emulsions (oil volume fractions of 0.15, 0.3 and 0.45) produced with vortex based hydrodynamic cavitation device. Measured DSDs are represented by weighted sum of three log-normal distributions. We developed an approach and a methodology based on artificial neural network (ANN) to estimate DSD from a single measurement of turbidity. A mathematical model is developed to simulate measured turbidity profiles using the known DSDs. The validated model was then used to generate simulated data of turbidity and oil volume fraction pairs (10⁵ pairs). This synthetic data was used to train ANN which used turbidity and volume fraction as input and eight parameters of DSD as output. The developed ANN was able to capture the experimentally measured characteristic diameters and DSDs very well for three oil volume fractions and four different number of passes. The presented methodology and results will be useful for developing an in-line soft sensor based on turbidity measurements for real time estimation of full DSDs of emulsions.