Feed Flow Rate Research Articles

Advancing electrochemical water desalination: Machine learning-driven prediction and RSM optimization of activated carbon electrodes

This study presents an innovative and sustainable approach for synthesizing porous carbon electrodes from palm kernel shells (PKS) using a single-step physicochemical activation process. The study investigates the effect of carbon dioxide and zinc chloride on electrochemical features such as surface morphology and functional chemistry, intrinsic resistance and electrical conductivity. The best electrode developed from palm kernel shell derived activated carbon (PKSAC) using ZnCl2 and N2/CO2 (PKSAC_N2/CO2_ZnCl2) exhibited a superior specific capacitance, electrosorption capacity, and average salt adsorption rate of 365.4 F/g, 22.5 mg/g and 0.372 mg/g/min under optimized CDI conditions, such as applied voltage, feed flow rate, and initial NaCl concentration of 1.2 V, 7.5 ml/min, and 750 mg/L, respectively. Comparatively, electrodes developed with either N2 activation (PKSAC_N2) or N2/ZnCl2 activation (PKSAC_N2_ZnCl2) demonstrated electrosorption capacities of 12.55 and 19.74 mg/g, respectively. Response surface methodology (RSM) was applied to optimize the CDI parameters for electrochemical water desalination, ensuring process efficiency and scalability. Further, the machine learning extreme gradient boosting (XGB) regressor model predicted the performance of the developed electrodes and aligned well with the experimental data. The article provides key insights into activated carbon synthesis and its role in electrochemical water desalination, offering a sustainable solution to water scarcity that aligns with the UN's sustainability goals.

The optimum location of vapor compressor in multistage vacuum membrane distillation system

This paper investigates the performance optimization of a multistage vacuum membrane distillation (MSVMD) system integrated with a mechanical vapor compressor (MVC) for efficient water desalination. The conventional integrated MSVMD and MVC systems lack a detailed analysis regarding the optimal placement of the MVC, which can influence both productivity and energy efficiency. To address this gap, this study evaluates different compressor placements within the MSVMD setup, assessing their impact on productivity and the gained output ratio (GOR) under various operational parameters, including feed temperature, flow rate, number of stages, and vacuum pressure. The results reveal that the optimal MVC placement can increase system productivity by up to 28 % and enhance energy efficiency, achieving a GOR of about 13. Middle MVC placements maximize productivity, yielding freshwater production up to 500 L/h, while different placements, depending on the feed temperature, optimize the GOR. The parametric study demonstrates that increasing feed temperature significantly boosts productivity, particularly at lower numbers of stages, but reduces GOR due to the higher thermal losses. Additionally, higher feed flow rates improve productivity, with GOR stabilizing at the highest flow rates, and lower pressures in the permeate side increase productivity while keeping GOR consistent. The optimized MSVMD system thus offers a balanced approach, achieving substantial freshwater production with high energy efficiency

Separation of Antibiotics Using Two Commercial Nanofiltration Membranes—Experimental Study and Modelling

The widespread use of antimicrobial drugs has contributed to the increasing trace levels of contaminants in the environment, posing an environmental problem and a challenge to modern-day medicine seeking advanced solutions. Nanofiltration is one such breakthrough solution for the selective removal of antibiotics from wastewater due to their high efficiency, scalability, and versatility. This study examines the separation of antibiotics (sulfamethoxazole (SMX), trimethoprim (TMP), and metformin (MET), respectively) using commercially available membranes with an emphasis on AFC membranes (AFC 30 and AFC 80). Thus, we evaluate their efficacy, performance, and applicability in wastewater treatment processes. The data for characterizing the structural parameters of the NF membranes were determined from an uncharged organic solute rejection experiment, and the effect of various operating conditions on the retention of solutes was evaluated. All experimental data were collected using a laboratory-scale nanofiltration unit and HPLC, and rejection percentages were determined using analytical measurements. The results obtained allowed for the determination of the radius of the membrane pores using the Steric Hindrance Pore (SHP) model, resulting in values of 0.353 and 0.268 nm for the AFC 30 and AFC 80 membranes, respectively. Additionally, higher transmembrane pressure and feed flow were observed to lead to an increased rejection of antibiotics. AFC 30 demonstrated a rejection of 94% for SMX, 87% for TMP, and 87% for MET, while AFC 80 exhibited a rejection of 99.5% for SMX, 97.5% for TMP, and 98% for MET. The sieving effect appears to be the primary separation mechanism for AFC 30, as lower feed-flow rates were observed to intensify concentration polarization, thereby compromising rejection efficiency. On the contrary, AFC 80 experienced less concentration polarization due to its smaller pore sizes, effectively preventing pore clogging. Membrane performance was evaluated using the Spiegler–Kedem–Katchalsky model, based on irreversible thermodynamics, which effectively explained the mechanism of solute transport of antibiotics through the AFC 30 and AFC 80 membranes in the NF process.

Flow channel simulation and optimization design of pervaporation membrane pool based on heat-mass-flow coupling

Pervaporation (PV), recognized as a separation technology with vast potential, is highly dependent on the fluid flow patterns within the membrane module, which play a critical role in local mass transfer processes on the membrane surface. In this study, computational fluid dynamics (CFD) was employed to simulate two different flow channel designs for a PV membrane module, with experimental verification of the model’s accuracy. The results indicated that the parallel inlet–outlet and wavy flow channel design (Mode II) significantly improved the feed-side concentration and temperature distribution, leading to a 3.7 % increase in feed-side flow velocity. Further investigation into the effects of three membrane pool structural parameters on separation performance revealed that pressure drop was most significantly influenced by the inlet radius, while the wavy length-to-height ratio (L:H) has the greatest impact on separation performance. After optimization, the optimal membrane module structure was determined to be the baffle depth of 4 mm, the inlet radius of 1 mm, and the L:H of 1:1. Based on this optimized structure, the effects of operating conditions on separation performance were further explored. The study showed that increasing feed flow rate significantly enhanced separation performance, while increasing feed temperature and concentration intensified temperature and concentration polarization on the membrane surface. Through multi-objective optimization, the optimal operating conditions were determined to be the feed flow rate of 20 L·h-1, feed temperature of 55 °C, and feed concentration of 3 wt%. This study provides valuable theoretical insights and technical references for the design of PV membrane pool flow channels and the selection of operational conditions.

Study of municipal solid waste treatment using plasma gasification by application of Aspen Plus

Abstract Plasma gasification is a viable and efficient technique for handling solid waste, including hazardous waste, while also holding the potential for energy recovery. The objective of this study is to analyze the treatment of municipal solid waste (MSW) using plasma gasification by application of Aspen Plus software. An earlier proposed model was used to analyze the effect of employing different types of gasifying agents as plasma gas, on the composition of syngas produced. The lower heating value, cold gasification efficiency and carbon conversion efficiency were calculated and compared in each case. A sensitivity analysis study was also carried out to observe the effect of variation in plasma gas flow rate and feed flow rate on the composition of syngas generated. The capital, operational and maintenance costs of the process were determined using existing correlations. For a feed rate of 20,000 kg per hour of MSW, the highest yield of syngas (CO (33.48 %), and H2 (34.30 %) with the highest LHV (7.9 MJ/N-m3)) were produced when air was employed as plasma gas. The cold gas efficiency and the carbon conversion efficiency were at their peak when air was used as the gasifying agent. The sensitivity analysis revealed that as the flow rate of plasma gas increases syngas production decreases while the increase in MSW flow rate results in an increase in syngas production. Additionally, the cost analysis revealed that for a plasma gasification plant that can handle 500 tons of MSW per day, the estimated capital and annual operational and maintenance costs are $125,496,721 and $9,833,892 respectively.

Batch and continuous fixed bed adsorption of copper (II) from acid mine drainage (AMD) using green and recyclable adsorbent from cellulose microcrystals (CMCs)

The CMCs are viable materials for applications in industry and process innovation for removing heavy metal ions since they may be used in static and dynamic adsorption processes. It is necessary to develop simple, low-cost water treatment methods that use organic, biodegradable polymers such as nanomaterial-modified cellulose microcrystals. The column technique was used to investigate the effects of operational parameters such as pH, bed depth, concentration and flow rate. The input concentrations of 20, 40, 80 and 120 mg L−1, feed flow rates of 5, 10, 15 and 20 mL min−1, and bed heights of 5, 7.5, 10 and 12.5 cm. Experimental findings showed that the adsorption capacity decreased with increasing flow rate and increased with bed depth and input concentration, which were among the breakthrough parameters evaluated. The optimum adsorption capacity of 258.09 ± 0.96 mg g−1 was found to be achieved with an ideal pH of 6, an initial concentration of 200 mg L−1, a contact period of 300 min, and a dosage of 5 g/200 mL. The Langmuir model best fits the adsorption of indigo carmine, whereas the pseudo-second-order model, which governs the adsorption mechanism, may be described by physisorption combined with chemisorption. From a thermodynamic perspective, the adsorption was exothermic and spontaneous. In continuous adsorption, the Yoon-Nelson and Thomas models provided a good match for the hole curve, whereas the Bohart-Adams model fitted the breakthrough curve’s initial portion ((Ct/C0) <0.5) perfectly. A three-dimensional adsorbent that has been chemically modified. The chemically modified CMCs adsorbent was characterized using FTIR, SEM and TGA.

Granulometric properties of alkali metal chloride salts in induction heating-based pulsed spray drier: CFD-assisted study and validation

ABSTRACT Spray drying is one of the most widely used unit operation for producing solid directly from liquid solution form in single stage. In conventional co-current or counter-current spray drying arrangements, obtaining alkali metal chloride salts with uniform monosized particles and narrow particle size distribution is challenging because of anisotropic thermal utilisation of gas phase in drying chamber and also because of the hygroscopic nature of these salts. In the present work, the conventional counter-current spray drying arrangement is modified through incorporation of induction heating and mechanical pulsating techniques in the spray drying chamber to enhance the thermal uniformity of gas phase in the drying chamber. Laser diffraction analysis is used for measuring initial droplet size distribution. Meanwhile, a computational fluid dynamics (CFD)-assisted empirical model has been developed to predict particle properties at specified operating parameters of induction heating-based pulsed spray drier (IHPSD). Sensitivity analysis shows that the granulometric properties of all alkali metal chloride salts obtained from IHPSD are most significantly affected by changes in top plate temperature (induction heating temperature), followed by aqueous feed flow rate, then followed by atomiser air flow rate and are least affected by reciprocation rate of pulsating assembly.

Developing an efficient explainable artificial intelligence approach for accurate reverse osmosis desalination plant performance prediction: application of SHAP analysis

In recent decades, securing drinkable water sources has become a pressing concern for populations in various regions worldwide. Therefore, to address the growing need for potable water, contemporary water purification technologies can be employed to convert saline sources into drinkable supplies. Therefore, the prediction of important parameters of desalination plants is a key task for designing and implementing these facilities. In this regard, artificial intelligence techniques have proven to be powerful assets in this field. These methods offer an expedited and effective means of estimating effective parameters, thus catalyzing their implementation in real-world scenarios. In this study, the predictive accuracy of six different machine learning models, including Natural Gradient-based Boosting (NGBoost), Adaptive Boosting (AdaBoost), Categorical Boosting (CatBoost), Support vector regression (SVR), Gaussian Process Regression (GPR), and Extremely Randomized Tree (ERT) was evaluated for modelling the parameter of permeate flow as a key element in system efficiency, energy consumption, and water quality using six various input combinations of feed water salt concentration, condenser inlet temperature, feed flow rate, and evaporator inlet temperature. The next phase of this research employed the SHAP interpretability method to illustrate the impact of individual variables on the model's output. Moreover, the predictive performance of the developed frameworks was evaluated using a set of five dependable statistical measures: RMSE, NS, MAE, MAPE and R 2. These indicators were utilized to provide a robust means of gauging the precision of the model's forecasts. A comparative analysis of the outcomes, as measured by the RMSE criteria, revealed that the SVR technique (RMSE = 0.125 L/(h·m2)) exhibited superior performance compared to NGBoost (RMSE = 0.163 L/(h·m2)), AdaBoost (RMSE = 0.219 L/(h·m2)), CatBoost (RMSE = 0.149 L/(h·m2)), GPR (RMSE = 0.156 L/(h·m2)), and ERT (RMSE = 0.167 L/(h·m2)) methodologies in predicting permeate flow rates. The modelling outcomes obtained during the evaluation stage demonstrated the efficacy of the SVR algorithm in enhancing the precision of permeate flow forecasts, utilizing relevant input variables.

Techno-economic feasibility study of ammonia recovery from sewage sludge digestate in wastewater treatment plants

Wastewater treatment plants play a vital role in resource recovery, particularly through biogas production, a key renewable energy source. Beyond biogas, the digestate from anaerobic digestion is rich in nutrients like ammonia. This study explored the feasibility of recovering ammonia from sewage sludge digestate using air stripping. The process was modeled using Aspen Plus® software, utilizing real data from As-Samra WWTP in Jordan. Various operational parameters, such as digestate feed flow, air flow rate, temperature, and pressure, were analyzed to optimize ammonia recovery. The results showed that with a feed flow rate between 10,000 and 30,000 kg/hr, ammonia recovery reached 85%, with production exceeding 100 kg/hr, where the effect of the flow rate appears mostly at elevated feeding temperatures. Increased air flow rates significantly boosted recovery, achieving 90% efficiency at 60 °C with 50,000 kg/h as air flow. Flashing pressure peaked at 1.5 bar, with 85% efficiency at 95 °C, while higher pressures yielded diminishing returns, stabilizing production around 106 kg/hr. The NaOH feed rate also influenced output, rising from 100 kg/hr at a 50 kg/hr feed rate to 107 kg/hr at 750 kg/hr, with recovery efficiency exceeding 85%. The economic analysis showed that the project had a payback period of 6.07 years, reflecting a reasonable recovery of the initial investment. The net present value was 122,924 USD over 15 years, with 8% amortization rate, indicating that the project created value beyond the initial cost. The internal rate of return was 14.23%, surpassing the discount rate and highlighting the project's financial attractiveness.

Unraveling the impact of operational parameters and environmental conditions on the quality of viable bacterial aerosols.

Viable pathogen-laden droplets of consistent quality are essential for reliably assessing the protection offered by facemasks against airborne infections. We identified a significant gap in guidance within standardized tests for evaluating the filtration efficiencies of facemask materials using viable bacteria-laden aerosol droplets. An aerosol platform, built according to the American Society for Testing and Materials standard F2101-19, was used to validate and standardize facemask filtration test procedures. We utilized this platform to investigate the impact of varying five operating parameters, namely suspension media composition, relative humidity, pathogen concentration, and atomizer airflow and feed flow rates, on the aerosol quality of viable bacteria-laden aerosols. We achieved consistent generation of 1,700 to 3,000 viable bacteria-laden droplets sized between 2.7 and 3.3 µm under the following optimized test conditions: 1.5% w/v peptone water concentration, ≥80% relative humidity at 24 ± 2 °C, 1 × 105 CFU/mL bacterial concentration, 1.5 L/min atomizer airflow rate, and 170 μL/min feed flow rate. We also explored the consequence of deviating from these optimized test parameters on viable bacteria-laden aerosol quality. These results highlight the importance of controlling these parameters when studying airborne transmission and control.

Phosphate pre-concentration from wastewater by a continuous flow bench-scale forward osmosis membrane: A circular economy approach on nutrient recovery

Phosphate is a vital element necessary for the growth and development of plants, making it a crucial element in agricultural fertilizers. Extracting phosphate from wastewater for recovery aligns with the principles of a circular economy by closing the loop on nutrient cycles. Instead of viewing wastewater as a waste product, treating it as a resource for recovering valuable nutrients like phosphate promotes a more sustainable and efficient use of resources. In this study, the phosphate from synthetic wastewater was pre-concentrated by a continuous flow forward osmosis membrane system to facilitate effective precipitation. The pre-concentration feasibility of forward osmosis was studied by changing the draw concentration, feed concentration, feed pH, and flow rate of the feed solution. With the optimum operational parameters in batch mode such as pH of 7, the draw solute concentration of 0.4 M MgSO4, the feed and draw flowrate of 0.7 L/min and 0.3 L/min, the phosphate concentration was increased from 30 mg/L to 525 mg/L after 60 min, the average osmotic flux and reverse solute flux was 2.7 L/m2/h and 0.43 g/m2/h, respectively. As operated with continuous mode, the final phosphate concentration was increased four times, the average osmotic flux was higher with 8.1 L/m2/h and the reverse solute flux was 0.86 g/m2/h, which could improve the efficiency of calcium phosphate crystallization in precipitation/ crystallization reactors. This integrated system, which includes forward osmosis as a pretreatment method followed by a precipitation process, is technically possible for application on a larger scale as a circular economy approach.

The design and control of heat-integrated EDWC processes for the separation of THF/IPA/water

Extractive dividing wall columns (EDWC) and heat integration are effective process intensification strategies for separating azeotropes. In this study, the steady-state and dynamic control for the separation of tetrahydrofuran/isopropanol/water using a combination of EDWC and heat integration with intermediate reboilers are systematically investigated. The feasibility of the extractive distillation process is evaluated by analyzing the thermodynamic characteristics of the mixture through phase diagrams, and the three-column extractive distillation (TCED) process is established as the basic process. To enhance the energy and economic efficiencies, as well as environmental sustainability, three improved processes are proposed. Compared with TCED, the optimal process (E-EDWC-HI2) reduces the total annual costs, energy consumption, and CO2 emissions by 22.35 %, 41.77 %, and 26.28 %, respectively. In addition, a dynamic control structure is proposed for the E-EDWC-HI2, which exhibits robustness against disturbances in the feed flow rate and composition. This study provides guidance for the design and dynamic control of complex distillation processes.

Enhanced continuous lithium extraction using self-designed porous nanosorbent fibers in a fixed-bed system: Optimization and mechanistic insights

This study introduced a novel lithium/aluminum layered double hydroxide (Li/Al-LDH) nanosorbent fiber (Li-PNF) engineered for continuous lithium extraction from brine using a fixed-bed system. These fibers featured a three-dimensional interconnected mesh structure and were distinctively encapsulated with needle-like Li/Al-LDH, exhibiting a layer-by-layer configuration. Compared to conventional Li/Al-LDH, Li-PNFs demonstrated abundant mesoporous structure and larger average pore size, facilitating the mass transfer and molecular diffusion of Li+ ions. Li-PNFs possessed a static lithium adsorption capacity of approximately 13.0 mg/g, with notable selectivity against Na+ and K+. Additionally, the Li+ binding energy across three distinct sites within the atomic structure of Li-PNFs proved advantageous, particularly at the Triangle-site-Al-overlapping-O3, which reached −5.72 eV. Fixed-bed adsorption experiments confirmed that lower feed flow rates, higher initial lithium concentrations, and increased bed heights significantly enhanced the Li+ capture efficiency, achieving up to 23.83 % in a single fixed-bed experiment. Based on the prediction of adsorption penetration curves using four empirical models, it was found that the Clark and Thomas models could accurately predict the behavior of Li+ penetration through the bed. Fixed-bed desorption results indicated that optimal lithium recovery was achieved at lower feed rates, reduced lithium concentrations in the desorption solution, and elevated temperatures. Finally, the excellent cyclic adsorption/desorption performance and low preparation cost of Li-PNF further highlighted its potential for real industrial applications, offering a significant advancement in the field of lithium extraction technology.

Machine learning‐aided process design using limited experimental data: A microwave‐assisted ammonia synthesis case study

AbstractAn open research question lies in how machine learning (ML) can accelerate the design optimization of chemical processes which are at very early experimental development stage with limited data availability. As an example, this article investigates the design of an intensified microwave‐assisted ammonia production reactor with 46 experimental data. We present an integrated approach of neural networks and synthetic minority oversampling technique to quantify the nonlinear input‐output relationships of this process. For ammonia concentration predictions at discrete operating conditions, the approach demonstrates 96.1% average accuracy over other ML methods (e.g., support vector regression 84.2%). The approach has also been applied for continuous optimization, identifying the optimal synthesis conditions at 597.37 K, 0.55MPa with feed flow rate of 1.67 ×10−3 m3/s kg and hydrogen to nitrogen ratio of 1 which is consistent with experimental observations. The data‐driven model enables to integrate this reactor with existing ammonia production infrastructure and benchmark with conventional techniques.

A perspective on alignment between steady‐state design and control for a distillation system in the context of flexibility analysis

AbstractThis perspective paper discusses the alignment between steady‐state design and control (dynamic) simulation in the context of flexibility analysis for distillation systems. Operational variations, such as fluctuations in feed composition or flowrate, can stem from external factors like raw material quality or temperature variations. These disturbances need to be mitigated to ensure optimal industrial performance. Traditionally, these process uncertainties are usually considered in a sequential manner, where the steady‐state flowsheet is established first, and control performance is analyzed afterwards. However, recent studies have started integrating flexibility index into the design phase to account for process uncertainties. While this integration has improved design strategies, aligning steady‐state and dynamic control simulations for comprehensive flexibility analysis remains underexplored. In this paper, we wish to share new perspectives and insights we have observed by analyzing the existing literature. We highlight some points not immediately apparent in our previous studies, hoping these insights will serve as guidelines for future research in this direction. We believe that validating results between steady‐state and control simulations is a long‐term endeavor that cannot be conclusively addressed soon. However, we hope this paper will be valuable to future researchers, contributing to advancing this field and reaching those who will appreciate and build upon these insights. © 2024 Society of Chemical Industry (SCI). Published by John Wiley &amp; Sons Ltd

An innovative quick-decision strategy for evaluating the applicability of extractive distillation process with a preconcentration column in separating high-concentration organic waste liquid

In the face of the high energy consumption challenge in separating high-concentration organic waste liquid through extractive distillation (ED), the concept of preconcentration provides a new strategic direction. Therefore, it has become crucial to determine the suitability of the ED process with a preconcentration column for processing such complex mixture. Taking this into consideration, the study proposes an innovative quick-decision method that utilizes thermodynamic analysis of ternary phase diagram to determine the ratio of theoretical product flowrate at the bottom of the preconcentration column to the feed flowrate, which serves as the basis for deciding whether to choose the ED process with a preconcentration column for handling such separation tasks. Three azeotropic systems with different thermodynamic characteristics are chosen as case studies: cyclohexane/ethyl acetate/ethanol (Case 1), ethyl acetate/ethanol/water (Case 2), and n-hexane/ethyl acetate/acetonitrile (Case 3). The task of separating the above three systems is accomplished through the application of both three-column extractive distillation configuration (TCED), and four-column extractive distillation configuration (FCED). The objective functions for multi-objective optimization of all separation configurations include the minimum total annual cost (TAC), the minimum entropy generation and the minimum CO2 emissions. The research findings indicate that when the ratio of theoretical product flowrate at the bottom of the preconcentration column to the feed flowrate is not less than 0.56, or when there is a significant concentration difference among the components in the feed stream, the FCED configuration exhibits clear advantages over the TCED configuration in terms of economic, environmental, and thermodynamic aspects.

Kinetic investigation of dry reforming of methane reaction over Ni–Rh/ZrO2–Al2O3 catalyst using Langmuir-Freundlich isotherm

The study involved conducting kinetic measurements for the dry reforming of methane (DRM) over a Ni–Rh/Al2O3 (85%)-ZrO2(15%) catalyst under a wide range of operating conditions (temperature: 500–900 °C, total flow rate of the inlet feed: 50–100 mL/min). The support material was prepared using the sol-gel method, followed by impregnation of Ni–Rh catalyst on the incipient wetness of the Al2O3–ZrO2 support. The calcined, reduced and spent samples were characterized by X-ray diffraction (XRD), thermal gravimetric analysis (TGA), inductively coupled plasma atomic emission spectrometer (ICP-AES), N2 adsorption/desorption and CHNS analyzer, and tested for activity, yield and stability in DRM reaction. Furthermore, kinetic behavior of Ni–Rh/Al2O3–ZrO2 catalyst in DRM process was investigated by assuming DRM and reverse water-gas shift (RWGS) reactions take place on two kinds of different active sites. Experimental data were fitted using rate expressions based on the Langmuir-Freundlich (LF) isotherm for DRM and RWGS reactions. The activation energy for the DRM reaction was optimized at 43.62 kJ/mol, falling within the reported literature range of 24.73–108.9 kJ/mol. Statistical indices indicated that the kinetic model accurately predicted CO2 conversion compared to other responses, with an error of 12.054%. The computed and experimental trends for CH4 and CO2 conversions, H2 and Co yield in terms of temperature were similar with each other and the difference between the calculated and experimental trends was lower for conversions compared to yields.

Formulation of synbiotic buttermilk powder with higher viability of probiotic cells

The present study focused on the use of trehalose (TRE), whey protein concentrate (WPC), pullulan (PUL), and calcium lactate gluconate (CAL) as a protectant in the formulation of synbiotic buttermilk powder by application of spray drying. The spray drying of the solution mixture was carried out at an inlet temperature of 150 °C, a feed flow rate of 15mL/min, and compressed air at 3 kg/cm2 while keeping the outlet temperature constant at 70 ± 5 °C. TRE4 + CAL0.5 showed good results with the viability of Bifidobacterium bifidum as 6.04 ± 0.13 after 16 weeks followed by TRE2 + CAL0.5, TRE4, CAL0.5, WPC6, PUL4, and Control. The addition of protectants and Fructooligosaccharide (FOS) as a prebiotic did not affect the powder properties. The moisture content, water activity, bulk density, hygroscopicity, solubility, particle size, and scanning electron microscopy (SEM) of SBMP were better than the control sample for 17 weeks. SEM results showed spherical shapes without any cracks for SBMP containing TRE4 + CAL0.5. The present work demonstrated that the formulation containing TRE4 + CAL0.5 showed excellent results in terms of the viability of probiotic cells and also physicochemical properties of powder during storage for 16 weeks at 4 ± 1 °C.

Reaction ignition during the oxidative coupling of methane over Mn–Na2WO4/SiO2

The present study investigates the oxidative coupling of methane (OCM) as a viable solution for CH4 upgrading with the benchmark Mn–Na2WO4/SiO2 catalyst. The effects of space velocity on catalytic performance and ignition responses were evaluated. Experimental catalytic tests revealed a complex relationship between space velocity and C2+ product yields and a self-igniting behavior when the reaction temperature reached about 700 °C. The results indicated that the temperature difference (∆T) between the catalyst bed and the flowing gas increased with the feed flow rate and decreased with dilution of the catalyst bed (increasing with catalyst loading), which can allow the reaction ignition at lower temperatures. The present study sheds light on the interplay between reaction conditions and the ignition behavior, providing valuable insights for optimization of OCM processes and catalyst development.

Engineering Optimization of Producing High-Purity Dichlorosilane in a Fixed-Bed Reactor by Trichlorosilane Decomposition.

High-purity dichlorosilane (DCS) is an important raw material for thin film deposition in the semiconductor industry, such as epitaxial silicon, which is mainly produced by trichlorosilane (TCS) catalytic decomposition in a fixed-bed reactor. The productivity of DCS is strongly dependent on the controlling of the TCS decomposition reaction process, associated with the cost in practical application. In this study, we have performed computational fluid dynamics (CFD) simulation on the TCS decomposition reaction kinetics in a cylindrical fixed-bed reactor, in which the effects of catalyst bed height, feed temperature, and feed flow rate are stressed to predict the conversion rate of TCS and the generation rate of DCS. This indicates that the increase of bed height helps the reaction to proceed adequately, but too large a bed height does not improve the DCS generation rate. Meanwhile, the feed temperature and reactor temperature have important effects on the DCS generation rate. However, it is found that changing the feed flow rate and L/D ratio cannot effectively improve the DCS generation rate while the bed volume remains constant. Furthermore, we have designed a fixed-bed reactor to verify the simulation results, which are in good agreement with each other. These results are of significance for the practical industrial production of high-purity DCS in a fixed-bed reactor.