Industrial Processes Research Articles

Tailoring the Structure-Property Relationship of Ring-Opened Metathesis Copolymers for CO2-Selective Membranes.

In this work, we explore the use of ring-opening metathesis polymerization (ROMP) facilitated by a second-generation Grubbs catalyst (G2) for the development of advanced polymer membranes aimed at CO2 separation. By employing a novel copolymer blend incorporating 4,4'-oxidianiline (ODA), 1,6-hexanediamine (HDA), 1-adamantylamine (AA), and 3,6,9-trioxaundecylamine (TA), along with a CO2-selective poly(ethylene glycol)/poly(propylene glycol) copolymer (Jeffamine2003) and polydimethylsiloxane (PDMS) units, we have synthesized membranes under ambient conditions with exceptional CO2 separation capabilities. The strategic inclusion of PDMS, up to a 20% composition within the PEG/PPG matrix, has resulted in copolymer membranes that not only surpass the 2008 upper limit for CO2/N2 separation but also meet the commercial targets for CO2/H2 separation. Comprehensive analysis reveals that these membranes adhere to the mixing rule and exhibit percolation behavior across the entire range of compositions (0-100%), maintaining robust antiplasticization performance even under pressures up to 20 atm. Our findings underscore the potential of ROMP in creating precisely engineered membranes for efficient CO2 separation, paving the way for their application in large-scale environmental and industrial processes.

On Inter‐bubble Hydrodynamics and Cluster Formation in Non‐Newtonian Bubbly Columns: A Review

AbstractA comprehensive understanding of the inter‐bubble dynamics and the cluster formations in non‐Newtonian fluids is pivotal for chemical and biomedical engineering applications. In this review, we summarize current research efforts to provide a fundamental understanding and engineering principles of the interactions between bubbles and the dynamics of bubble clusters in non‐Newtonian fluids. Although the majority of research is still predominantly conducted through experimentation, the significance of computational fluid dynamics in elucidating interaction mechanisms has become increasingly prominent in recent years. Moreover, the gas‐liquid systems reviewed in this paper are driven by gravity, which is closer to the actual industrial processes. We indicate the effects of non‐Newtonian fluid special rheological properties (especially viscoelasticity and shear‐dependent viscosity) on the interaction between multiple bubbles and the formation of clusters. We summarize the main empirical correlations in related research, which are useful for the optimization of industry. Ultimately, we address the current trends, limitations, and future directions in this research field.

Promoter Impact on 5Ni/SAPO-5 Catalyst for H2 Production via Methane Partial Oxidation

Compared to steam reforming techniques, partial oxidation of methane (POM) is a promising technology to improve the efficiency of synthesizing syngas, which is a mixture of CO and H2. In this study, partial oxidation of methane (POM) was used to create syngas, a combination of CO and H2, using the SAPO-5-supported Ni catalysts. Using the wetness impregnation process, laboratory-synthesized Ni promoted with Sr, Ce, and Cu was used to modify the SAPO-5 support. The characterization results demonstrated that Ni is appropriate for the POM due to its crystalline structure, improved metal support contact, and increased thermal stability with Sr, Ce, and Cu promoters. During POM at 600 °C, the synthesized 5Ni+1Sr/SAPO-5 catalyst sustained stability for 240 min on stream. While keeping the reactants stoichiometric ratio of (CH4:O2 = 2:1), the addition of Sr promoter and active metal Ni to the SAPO-5 increased the CH4 conversion from 41.13% to 49.11% and improved the H2/CO ratio of 3.33. SAPO-5-supported 5Ni+1Sr catalysts have great potential for industrial catalysis owing to their unique combination of several oxides. This composition not only boosts the catalyst’s activity but also promotes favorable physiochemical properties, resulting in improved production of syngas. Syngas is a valuable intermediate in various industrial processes.

Modeling of a Solar Thermal Plant to Produce Hot Water and Steam for a Brewery Factory

The environmental impact caused by the intensive exploitation of fossil fuels to generate heat and electricity has already reached a critical level. Also, as the industrial sector is the largest energy consumer, mainly in the form of heat, it has then become compulsive to implement the use of renewable solar heat in industrial processes, such as those found in the food processing and beverages industries, which do not require high temperatures. Consequently, this study examines the viability of supplying heat as hot water at 80 °C and saturated steam at 160 °C to a medium-sized brewery factory through a hybrid solar plant composed of flat plate and parabolic trough collectors and sensible thermal energy storage. The study was conducted numerically using the meteorological conditions of a city different from that where the factory is located because it benefits from higher insolation levels. The mean annual solar fractions achieved were 49.9% for hot water production and 37.3% for steam generation, at a levelized cost of heat of 0.032 USD/kWh, which can be considered competitive if compared against the values reported in other similar solar projects. Also, the decrease in fossil fuel consumption allowed an annual reduction of 252 tons of carbon dioxide emissions.

Catalysts with Trimetallic Sites on Graphene-like C2N for Electrocatalytic Nitrogen Reduction Reaction: A Theoretical Investigation.

Electrocatalytic nitrogen reduction reaction (NRR) is a green and highly efficient way to replace the industrial Haber-Bosch process. Herein, clusters consisting of three transition metal atoms loaded on C2N as NRR electrocatalysts are investigated using density functional theory (DFT). Meanwhile, Ca was introduced as a promoter and the role of Ca in NRR was investigated. It was found that Ca anchored to the catalyst can act as an electron donor and effectively promote the activation of N2 on M3. In both M3@C2N and M3Ca@C2N (M = Fe, Co, Ni), the limiting potential (UL) is less negative than that of the Ru(0001) surface and has the ability to suppress the competitive hydrogen evolution reaction (HER). Among them, Fe3@C2N is suggested to be the most promising candidate for NRR with high thermal stability, strong N2 adsorption ability, low limiting potential, and good NRR selectivity. The concepts of trimetallic sites and alkaline earth metal promoters in this work provide theoretical guidance for the rational design of atomically active sites in electrocatalytic NRR.

Measurement insights and error analysis of electronic parameters for ultrasonic transducers

Abstract Piezoelectric ultrasonic transducers with the function of energy conversation, as well as their numerous advantages, such as high-power density, quick response, flexible design, and service reliability, are involved in wide applications of industrial processing, precision driving, smart sensing, and medical services. The electromechanical equivalent circuit and Kirchhoff’s law indicate that mechatronics parameters are essential for performance evaluation, reliability analysis, and fault diagnosis of ultrasonic transducers. Importantly, the ultrasonic transducer is a time variant system, data of one single parameter collected from a certain test can’t match with the data of another single parameter acquired from a different test. So, a synchronous and precise online measurement of electronic parameters is encouraged for performance evaluation and optimization design of ultrasonic transducers. With the combination of virtual instrument technology, an asynchronous measurement system of electrical excitation parameters for the ultrasonic transducers of linear driving motors was established in this study. Furthermore, the systematic measurement methods and error theory, including the calculation methods and measuring circuits of electric signals, were illustrated. Experimental results proved that the proposed system and methods for measuring the input electronic power of ultrasonic transducer (e.g., effective value method for voltage and current, energy moment method for frequency, and spectrum analysis method for phase difference) are highly precise, quick responsive, robust, and reliable for ultrasonic transducers. The findings of this study provide valuable references and suggestions for efficient, accurate, and online performance evaluation of ultrasonic transducers, particularly for piezoelectric transducers utilizing ultrasonic high-voltage exciting signals.

New analytical thermodynamic models developed for pure H2, CH4, CO2 and H2 containing mixtures based on molecular simulations

Pressure-volume-temperature-composition (PVTX) properties of gas mixtures are important to model and predict flow and compression performance in a range of industrial processes. It is time consuming and sometimes impractical to obtain these properties from experiments. Here, molecular dynamics (MD) simulations were conducted to compute the thermodynamic volumetric properties of pure H2, CH4, CO2, and binary mixtures of H2/CH4 and H2/CO2 at temperatures of 310.9–470 K, pressures up to 172 MPa. MD simulation results were used to develop five analytical equations explicit in pressure as a function of density or volume, temperature, and composition, for the pure gases and mixtures. Our simulated results matched very well with the predictions from the established GERG-2008 equation and data published by NIST. The simplified equations of state (EOS) developed in this work will be more computationally efficient than other EOS for mixed systems. This can be significant in reservoir simulations.

Polyvinyl Alcohol/Zr-based Metal Organic Framework Mixed-matrix Membranes Synthesis and Application for Hydrogen Separation

AbstractMembrane gas separation is an environmentally friendly and economical method used to separate valuable gases, industrial process gas wastes, and carbon dioxide from mixed gases. The most important part of this method is the membranes. Gas separation membranes are expected to have high separation and permeability performance, high mechanical strength, easy and fast production capability, and low prices. Polymer-based membranes are mostly preferred depending on the ease of modification capability. In this study, a zirconium-based metal organic framework (Zr-MOF, MIL-140 A) was synthesized and used as a filler within polyvinyl alcohol (PVA) matrix for the selective separation of hydrogen (H2) from carbon dioxide (CO2). The effect of MIL-140 A addition on the mechanical, structural, and morphological properties of PVA was evaluated. The MIL-140 A significantly improved the mechanical strength of the membrane. According to the gas separation results, the increasing concentration of MIL-140 A increased the selective separation performance of the nanocomposite membrane. The highest mechanical strength (43.1 MPa) and best film-forming ability were obtained with 3 wt% MIL-140 A loaded membrane. The ideal H2/CO2 selectivity and hydrogen permeability were obtained as 5.6 and 944 Barrer, respectively at 2 bar feed pressure and room temperature. The highest ideal H2/CO2 selectivity was obtained as 6.3 with the H2 permeability of 959 Barrer when the MIL-140 A ratio was 4 wt%.

A fast, reliable, low‐cost, and efficient xylan extraction for xylooligosaccharides production

AbstractA fast, reliable, low‐cost, and efficient method for the recovery of xylan from agro‐residue materials is needed to improve the use of xylan in industrial processes. Xylan was extracted from two agrowastes (corncobs and wheat bran) using a cost‐effective alkali extraction method. The characteristic band patterns and bending vibrations associated with hemicellulose and beta glycoside linkage could be seen in the corncob‐extracted xylan (CCEx) and wheatbran‐extracted xylan (WBEx). Scanning electron microscopy (SEM) analysis showed that the extracted xylans consisted of aggregated and nonaggregated particles with irregular morphology and rough surfaces. Particle‐size analysis displayed average sizes of 205.6, 210.8, and 794.2 nm for commercial beechwood xylan (Bx), CCEx, and WBEx, respectively. Alkali extraction was performed with different concentrations of NaOH, from 5% to 20%, with a solid–liquid ratio of 1:20. It was found that 82.90 and 76.77% of xylan were extracted from corncob and wheat bran, respectively, which represents a higher yield obtained in a shorter duration in comparison with studies in the literature. The enzymatic hydrolysis of wheat bran and corncob that used 250 IU/mL of Enterobacter hormaechie KS1 xylanase yielded 334.38 and 162.35 mg/g of xylooligosaccharides. Their properties were studied and were found to be very similar to those of commercial xylan. They could reduce costs if applied in industry.

Dimensionality reducing Gaussian mixture‐based reconstruction for fault detection in multimode processes

AbstractModern industrial processes increasingly prioritize demands for safety and reliability, spurring substantial research on process monitoring models. Among existing research subjects, concurrent multimode operating conditions are vital for effective process monitoring. This work proposes an efficient dimensionality‐reducing Gaussian mixture‐based reconstruction approach for multimode industrial process monitoring. The t‐SNE method is first employed to transform high‐dimensional data into a lower‐dimensional space that retains critical operational information. Using these reduced dimensions, a robust Gaussian mixture model is established to partition the operation data into different modes. Furthermore, the original data are assigned to the corresponding operating modes, and local variational autoencoder (VAE) reconstruction models are established, respectively. For each VAE model, two statistics are designed, termed and , to detect abnormalities. The proposed method is applied to a three‐phase flow facility, and the superiority over the comparison methods is proved.

Unsteady MHD flow analysis of hybrid nanofluid over a shrinking surface with porous media and heat generation: Computational study on entropy generation and Bejan number

The use of hybrid nanofluids in real-world situations is essential for enhancing the efficiency of heat transmission, especially in cooling semiconductor technology and industrial processes. The entropy generation on unsteady Al2O3-Cu/H2O hybrid nanofluid flow over a three-dimensional shrinking sheet is addressed numerically in this study, taking into account the effects of magnetohydrodynamic (MHD), nonlinear thermal radiation, porous media, heat generation, viscous dissipation, joule heating, and convective conditions. Using well-known non-similarity transformations, the model is carefully converted from partial differential equations (PDEs) to ordinary differential equations (ODEs). Afterwards, the behaviors of critical physical characteristics are uncovered across different parameter configurations by a numerical solution using the finite difference technique in bvp4c MATLAB. The velocity profiles of hybrid nanofluid grow proportionately with increases in the values of ϕ2,M,A,K and λ parameters. As Rd,θw,Ec,Bi,H and ϕ2 increase, the temperature of the hybrid nanofluid rises, but as M and A increase, the temperature falls. The local skin friction in both the x and y- directions is increased by enhancing the unsteadiness A, nanoparticle volume fraction ϕ2, magnetic M, porous media K, and the ratio of strain rate λ parameter on the shrinking surface. The local Nusselt number is improved by cumulative the unsteadiness A, nanoparticle volume fraction ϕ2, magnetic M, and Biot number Bi parameter in the direction of a shrinking surface, while the Nusselt number decreases when Eckert number Ec, thermal radiation Rd, heat production H, and temperature ratio θw are improved. An upsurge in the magnetic parameter leads to the development of entropy generation. Increasing levels of the magnetic parameters led to a reduction in the Bejan number. At a nanoparticle volume fraction of 1 % and a nonlinearity radiation scenario, where the unsteadiness values are 0.5, the Nusselt number for hybrid nanofluid shows an estimated improvement of 10.55 % compared to regular nanofluid.

Synergistic Catalysis of SO42–/TiO2–CNT for the CO2 Desorption Process with Low Energy Consumption

Synergistic Catalysis of SO₄^2–/TiO₂–CNT for the CO₂ Desorption Process with Low Energy Consumption

Deflagration characteristics of N2 diluted propanal/air mixtures at elevated pressures

Hydrocarbon fuels, in addition to being direct sources of energy, also serve as crucial raw materials for numerous industrial processes. In this study, the oxidation of propanal to propionic acid under elevated pressures has garnered our attention due to the substantial heat release during the mixing of propanal and oxidants, posing considerable hazards to production. Fortunately, the introduction of N2 effectively mitigates these risks by reducing the laminar burning speed (SL) and peak deflagration pressure (Pm), and even preventing the ignition of mixtures. On this basis, the deflagration characteristics of propanal/N2/air mixtures were investigated in a 20 L spherical vessel at 348 K under various equivalent ratios (φ, 0.5 - 2.0), dilution rates (D, 0 - 0.5) and initial pressures (P0, 0.1 - 1.0 MPa). The combustion characteristics of propanal/N2/air were also analyzed through the 1-D laminar flame speed model, and the sensitivity analysis was performed to elucidate the effect of φ, D and P0 on the combustion of propanal. Results reveal that the addition of N2 stabilizes the flame propagation, and the Pm of propanal/N2/air mixtures decreases with the increasing D, with a sudden drop observed at a certain D level. However, the reduction of SL does not undergo an abrupt decrease across the entire dilution rate range. Furthermore, Pm exhibits a linear relationship with P0 at lower D, but this linear trend disappears once D approaches the critical suppression concentration. Interestingly, the critical suppression concentration of N2 increases with P0 at fuel-rich conditions, yet remains unaffected by P0 at fuel-lean conditions. Near the critical suppression concentration, a limiting burning speed (Slim) emerges, below which the flame is incapable of spontaneous propagation. Notably, Slim is not a fixed value, but varies according to the composition and initial state of the mixture. For a given gas component, an increase in P0 leads to a decline in Slim, while for gases with varying components, Slim is observed to be lower under fuel-rich conditions compared to fuel-lean scenarios. Also, both the addition of N2 and the augmentation of P0 significantly reduce the SL. When SL is comparable to the gas rise speed due to natural convection, the flame propagation becomes vulnerable to buoyancy instability. Meanwhile, the flame propagation may also be influenced by thermal diffusion instability and hydrodynamic instability. Under the combined effect of these instabilities, the flame is prone to be unstable. More importantly, when the flame contacting the upper wall of the is in a critical state where it can or cannot propagate downward, the irregularity of the disturbed flame may introduces uncertainty into the subsequent propagation, resulting in markedly different Pm even among mixtures with identical compositions.

Electro‐Oxidation of Alkenes: A Green Approach Towards Functionalized Oxygenates

In chemical industrial process, conversion of alkenes to functional oxygenates plays a key role in bridging between the feedstock and downstream application. Traditionally, the oxidation required highly‐active oxygen sources or molecular oxygen under high temperature and pressure. This poses challenges to the green and safe production of oxygenates. To circumvent the issues of massive consumption of fossil fuel and serious CO2 footprints, approaches of electro‐oxidation are developed under ambient conditions, adopting O2 and H2O as oxygen source. Utilizing electricity from renewable resources and the involved electron transfer, the performance is closely related to the interface characteristics of electrodes and electrolytes. This review presents the progress in catalysts design, electrolytes optimization, cells integration to effectively regulate the microenvironment of the interfaces. Further discussion of the mechanism analysis and potential issues are emphasized, based on the in‐situ characterization techniques, isotopic experiments and quenching tests. We hope this review can provide an outline for green approaches to oxidation of alkenes via electrocatalytic pathways.

Fault detection using machine learning based dynamic ICA-distributed CCA: Application to industrial chemical process

Unexpected accidents and events in industrial chemical processes have resulted in a considerable number of causalities and property damage. Safety process management in industrial chemical processes is critical to avoid and ensure casualties and property damage. However, due to the immense scope and high complexity of current industrial chemical processes, the traditional safety process management approaches cannot address these challenges to attain adequate fault detection accuracy. To address this issue, an innovative machine learning-based distributed canonical correlation analysis-dynamic independent component analysis (DICA-DCCA) approach is needed to improve the fault detection effectiveness of complicated systems. The (DICA-DCCA) model could potentially detect anomalies and faults in industrial chemical data by utilizing three essential statistics:Id2,Ie2and squared prediction error (SPE). The practical effectiveness of the proposed frameworks is evaluated and compared using a continuous stirred tank reactor (CSTR) framework as a standard benchmark study. The research findings present that the suggested (DICA-DCCA) approach is more resilient and effective in detecting abnormalities and faults than the ICA and DICA approaches with FDR 100 % and FAR 0 %. The implied research approach is robust, operational, and productive.

Gas viscosities from a semiconductor-manufacturing mass-flow controller

We obtain gas viscosities with a pressure-based mass-flow controller used for semi-conductor manufacturing, a rate-of-change approach, and a physics-based calculation. The novelty of this method is that it is used in an industrial process whose main goal is not to measure viscosities. In this way, for pressures of the order of 10 kPa and 25 ∘C and 35 ∘C, we obtain for seven gases viscosities with mean absolute errors with respect to reference viscosities of less than 1%. Using this method, we report viscosities for two semiconductor-manufacturing gases not available in the open literature: hexafluoroisobutene (CAS # 382-10-5) and 1,1,3,3,3-pentafluoropropene (690-27-7).

Response mechanisms of different Saccharomyces cerevisiae strains to succinic acid

BackgroundThe production of succinic acid (SA) from biomass has attracted worldwide interest. Saccharomyces cerevisiae is preferred for SA production due to its strong tolerance to low pH conditions, ease of genetic manipulation, and extensive application in industrial processes. However, when compared with bacterial producers, the SA titers and productivities achieved by engineered S. cerevisiae strains were relatively low. To develop efficient SA-producing strains, it’s necessary to clearly understand how S. cerevisiae cells respond to SA.ResultsIn this study, we cultivated five S. cerevisiae strains with different genetic backgrounds under different concentrations of SA. Among them, KF7 and NBRC1958 demonstrated high tolerance to SA, whereas NBRC2018 displayed the least tolerance. Therefore, these three strains were chosen to study how S. cerevisiae responds to SA. Under a concentration of 20 g/L SA, only a few differentially expressed genes were observed in three strains. At the higher concentration of 60 g/L SA, the response mechanisms of the three strains diverged notably. For KF7, genes involved in the glyoxylate cycle were significantly downregulated, whereas genes involved in gluconeogenesis, the pentose phosphate pathway, protein folding, and meiosis were significantly upregulated. For NBRC1958, genes related to the biosynthesis of vitamin B6, thiamin, and purine were significantly downregulated, whereas genes related to protein folding, toxin efflux, and cell wall remodeling were significantly upregulated. For NBRC2018, there was a significant upregulation of genes connected to the pentose phosphate pathway, gluconeogenesis, fatty acid utilization, and protein folding, except for the small heat shock protein gene HSP26. Overexpression of HSP26 and HSP42 notably enhanced the cell growth of NBRC1958 both in the presence and absence of SA.ConclusionsThe inherent activities of small heat shock proteins, the levels of acetyl-CoA and the strains’ potential capacity to consume SA all seem to affect the responses and tolerances of S. cerevisiae strains to SA. These factors should be taken into consideration when choosing host strains for SA production. This study provides a theoretical basis and identifies potential host strains for the development of robust and efficient SA-producing strains.

Understanding Fouling in an Industrial Biorefinery Membrane Separation Process by Feature-Oriented Data-Driven Modeling

Understanding Fouling in an Industrial Biorefinery Membrane Separation Process by Feature-Oriented Data-Driven Modeling

Parabolic trough concentrator design, characterization, and application: solar wastewater purification targeting textile industry dyes and pharmaceuticals—techno-economic study

AbstractSolar energy, along with other renewable resources, has the potential to be a major contributor to solving environmental issues in the future, as illustrated by the most recent advancements in solar photocatalytic technology. Indeed, wastewater treatment using a parabolic solar collector for industrial processes is gaining ground owing to improved system performance and economic benefits. The fabricated parabolic trough collector (PTC) incorporates reflective, parabolic panels that focus solar energy onto a transparent tube positioned along the parabolic focal line, where solar-powered photochemical reactions occur. This study investigated the design, implementation, and effectiveness of a concentrated sunlight system for removing industrial dyes and emerging large-use pharmaceutical contaminants in the presence of H2O2 at a small demonstrator scale (10 L/h). A spectrophotometric assessment revealed that subjecting Remazol Brilliant Blue (RBB, 60 ppm) and ciprofloxacin (CIP, 10 ppm) to irradiation in the presence of 0.1 M H2O2 (RBB) or 0.01 M H2O2 (CIP) for 3 h resulted in a degradation rate exceeding 60% and 80%, respectively. Furthermore, the total organic content (TOC) analysis indicates a very high total removal yield for RBB. On these bases, a techno-economic analysis is produced, and economic viability is discussed. The data reveal that the annual costs for water treatment, considering investment, electricity, and catalyst expenses over a 12-month period are significantly lower for our PTC-based prototype than for a comparable artificial UV-based equipment.

Unsupervised Feature-Construction-Based Motor Fault Diagnosis

Any bearing faults are a leading cause of motor damage and bring economic losses. Fast and accurate identification of bearing faults is valuable for preventing damaging the whole equipment and continuously running industrial processes without interruption. Vibration signals from a running motor can be utilized to diagnose a bearing health condition. This study proposes a detection method for bearing faults based on two types of neural networks from motor vibration data. The proposed method uses an autoencoder neural network for constructing a new motor vibration feature and a feed-forward neural network for the final detection. The constructed signal feature enhances the prediction performance by focusing more on a fault type that is difficult to detect. We conducted experiments on the CWRU bearing datasets. The experimental study shows that the proposed method improves the performance of the feed-forward neural network and outperforms the other machine learning algorithms.