Chemical Process Industries Research Articles

Economic and Ecological Benefits of SHM Techniques in Chemical Process Industry

High-performance machine components are involved in a wide range of industrial production processes. They play an important role in the provision of chemical products, pharmaceuticals, and energy resources. They require monitoring because they can fail during production due to corrosion and/or wear, which often means an increased risk to people and the environment. Periodic inspections with on-site test personnel often require a shutdown of the chemical plant. Ideally, an ultrasonic structural health monitoring (SHM) system could be used to provide continuous data on the structural integrity of these components while reducing or eliminating plant downtime. A plant shutdown is not only a high economic or supply risk but can also be energy intensive. In our presentation, we would like to give an overview of the technical requirements for an SHM system to be used in the chemical industry. Finally, the presentation will highlight the economic benefits of SHM as well as its contribution to energy savings and reduction of CO2 emissions per ton of chemical product produced.

A Study of the Design of Lifting Trolley for the Suspending Agent Pouring Process in Chemical Industry

The raw material preparation process in the chemical industry is still done manually by pouring the suspending agent. Workers pour 20kg boxes with a frequency of 20-30 boxes every day. These activities have the potential to cause musculoskeletal injuries. The purpose of this study is to provide an assessment and design a lifter as a conveyance that has the potential to reduce the risk of musculoskeletal disorders. This study used the Nordic questionnaire to determine the prevalence of musculoskeletal complaints, REBA to assess work posture, and QFD as an approach in designing the lifter. Based on the results of the questionnaire, the most complaints were felt in the upper body. And based on the assessment with the QEC method, the average total exposure received by workers is 64.63%. This is evidenced by the results of the assessment of 60 work postures during the suspending agent pouring process which obtained the highest REBA mode value with a score of 8 (high risk). Based on the QFD method, this lifting trolley produces 11 target specifications. After simulating the design of the lifting trolley, the REBA score decreased to 3 (low risk). This shows that the designed trolley has the potential to be applied to reduce the risk of musculoskeletal disorders in workers in the chemical industry.

Anion Modulation of Ag-Imidazole Cuboctahedral Cage Microenvironments for Efficient Electrocatalytic CO2 Reduction.

How to achieve CO2 electroreduction in high efficiency is a current challenge with the mechanism not well understood yet. The metal-organic cages with multiple metal sites, tunable active centers, and well-defined microenvironments may provide a promising catalyst model. Here, we report self-assembly of Ag4L4 type cuboctahedral cages from coordination dynamic Ag+ ion and triangular imidazolyl ligand 1,3,5-tris(1-benzylbenzimidazol-2-yl) benzene (Ag-MOC-X, X=NO3, ClO4, BF4) via anion template effect. Notably, Ag-MOC-NO3 achieves the highest CO faradaic efficiency in pH-universal electrolytes of 86.1 % (acidic), 94.1 % (neutral) and 95.3 % (alkaline), much higher than those of Ag-MOC-ClO4 and Ag-MOC-BF4 with just different counter anions. In situ attenuated total reflection Fourier transform infrared spectroscopy observes formation of vital intermediate *COOH for CO2-to-CO conversion. The density functional theory calculations suggest that the adsorption of CO2 on unsaturated Ag-site is stabilized by C-H⋅⋅⋅O hydrogen-bonding of CO2 in a microenvironment surrounded by three benzimidazole rings, and the activation of CO2 is dependent on the coordination dynamics of Ag-centers modulated by the hosted anions through Ag⋅⋅⋅X interactions. This work offers a supramolecular electrocatalytic strategy based on Ag-coordination geometry and host-guest interaction regulation of MOCs as high-efficient electrocatalysts for CO2 reduction to CO which is a key intermediate in chemical industry process.

Anion Modulation of Ag‐Imidazole Cuboctahedral Cage Microenvironments for Efficient Electrocatalytic CO2 Reduction

AbstractHow to achieve CO2 electroreduction in high efficiency is a current challenge with the mechanism not well understood yet. The metal‐organic cages with multiple metal sites, tunable active centers, and well‐defined microenvironments may provide a promising catalyst model. Here, we report self‐assembly of Ag4L4 type cuboctahedral cages from coordination dynamic Ag+ ion and triangular imidazolyl ligand 1,3,5‐tris(1‐benzylbenzimidazol‐2‐yl) benzene (Ag‐MOC‐X, X=NO3, ClO4, BF4) via anion template effect. Notably, Ag‐MOC‐NO3 achieves the highest CO faradaic efficiency in pH‐universal electrolytes of 86.1 % (acidic), 94.1 % (neutral) and 95.3 % (alkaline), much higher than those of Ag‐MOC‐ClO4 and Ag‐MOC‐BF4 with just different counter anions. In situ attenuated total reflection Fourier transform infrared spectroscopy observes formation of vital intermediate *COOH for CO2‐to‐CO conversion. The density functional theory calculations suggest that the adsorption of CO2 on unsaturated Ag‐site is stabilized by C−H⋅⋅⋅O hydrogen‐bonding of CO2 in a microenvironment surrounded by three benzimidazole rings, and the activation of CO2 is dependent on the coordination dynamics of Ag‐centers modulated by the hosted anions through Ag⋅⋅⋅X interactions. This work offers a supramolecular electrocatalytic strategy based on Ag‐coordination geometry and host–guest interaction regulation of MOCs as high‐efficient electrocatalysts for CO2 reduction to CO which is a key intermediate in chemical industry process.

Causal Discovery for Topology Reconstruction in Industrial Chemical Processes

Causal Discovery for Topology Reconstruction in Industrial Chemical Processes

Influences of thermal stratification and chemical reaction on MHD free convective flow along an accelerated vertical plate with variable temperature and exponential mass diffusion in a porous medium

AbstractThis study examines the impacts of thermal stratification and chemical reaction on magnetohydrodynamic (MHD) free convective flow along an accelerated vertical plate with variable temperature and exponential mass diffusion, set within a porous medium. Analytical solutions, utilized, are obtained through the Laplace transform technique to accurately represent the flow's physical mechanism. The research employs advanced mathematical models to analyze the intricate interplay between MHD and convective processes under varying thermal and exponential mass diffusion conditions, offering insights into fluid dynamics that closely simulate real‐world conditions. The study draws a significant conclusion by contrasting the effects of thermal stratification with a nonstratified environment. It has been noted that when stratification is applied to the flow, the steady state is achieved more quickly. The study reveals that thermal stratification reduces fluid velocity and temperature but increases skin friction and the Nusselt number, diverging from nonstratified conditions. It also shows that parameters, like, , and significantly influence velocity, temperature, and concentration in fluid dynamics. This research could be driven by a need to enhance the understanding of fluid flow in various engineering and environmental contexts, where such conditions are prevalent, including geothermal energy extraction, thermal management, chemical processing industries, and environmental control technologies. This novel approach enhances understanding of flow processes in both natural and engineered porous environments.

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

AbstractIn 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.

Monodentate Phosphinoamine Nickel Complex Supported on a Metal-Organic Framework for High-Performance Ethylene Dimerization.

Ethylene dimerization is an efficient industrial chemical process to produce 1-butene, with demanding selectivity and activity requirements on new catalytic systems. Herein, a series of monodentate phosphinoamine-nickel complexes immobilized on UiO-66 are described for ethylene dimerization. These catalysts display extensive molecular tunability of the ligand similar to organometallic catalysis, while maintaining the high stability attributed to the metal-organic framework (MOF)scaffold. The highly flexible postsynthetic modification method enables this study to prepare MOFs functionalized with five different substituted phosphines and 3 N-containing ligands and identify the optimal catalyst UiO-66-L5-NiCl2 with isopropyl substituted nickel mono-phosphinoamine complex. This catalyst shows a remarkable activity and selectivity with a TOF of 29000 (molethyl/molNi/h) and 99% selectivity for 1-butene under ethylene pressure of 15bar. The catalyst is also applicable for continuous production in the packed column micro-reactor with a TON of 72000 (molethyl/molNi). The mechanistic insight for the ethylene oligomerization has been examined by density functional theory (DFT) calculations. The calculated energy profiles for homogeneous complexes and truncated MOF models reveal varying rate-determining step as β-hydrogen elimination and migratory insertion, respectively. The activation barrier of UiO-66-L5-NiCl2 is lower than other systems, possibly due to the restriction effect caused by clusters and ligands. A comprehensive analysis of the structural parameters of catalysts shows that the cone angle as steric descriptor and butene desorption energy as thermodynamic descriptor can be applied to estimate the reactivity turnover frequency (TOF) with the optimum for UiO-66-L5-NiCl2. This work represents the systematic optimization of ligand effect through combination of experimental and theoretical data and presents a proof-of-concept for ethylene dimerization catalyst through simple heterogenization of organometallic catalyst on MOF.

Construction of two New Second Order Rotatable Designs Using Trigonometric Functions

In this study, two new second order rotatable designs of thirty-five and forty-five points are constructed respectively using transformations of some trigonometric functions. The designs are s rotatable since they satisfy both the outlined moment conditions and the non-singularity conditions. Second-order rotatable designs are useful for optimizing these processes in chemical industries, agriculture and engineering by systematically varying the factors of interest and studying their combined effects on the response variables. This helps in identifying the optimal settings for maximum or minimum responses.

Physical methods for preparation of nanomaterials, their characterization and applications: a review

AbstractNanotechnology refers to nanomaterials of different dimensions, ranging in size from 1 to 100 nm. Shape and size, as well as properties of nanomaterials, depend on the materials based on their production. Nanomaterials are classified according to the type of substrate into carbon-based nanomaterials, metal-based nanomaterials, ceramic nanomaterials, lipid-based nanomaterials, semiconductor nanomaterials, and polymer nanomaterials. There are many physical methods that are widely used to produce nanomaterials, among these methods are inert gas condensation (IGC), physical evaporation, electric arc discharge, sputtering, and laser methods. Many characterization analysis techniques of nanomaterials, including ultraviolet–visible (UV–V) spectroscopy, XRD (X-ray diffraction), BET (Brunauere emmette teller), FESEM (Field emission scanning electron microscopy), FTIRS (Fourier transform infrared spectroscopy), TEM (Transmission electron microscopy) and Zeta size analysis. The unique properties that distinguish nanomaterials, allows them to penetrate many applications that directly serve the world. Nanomaterials have been utilized in various applications in the environment, agriculture, food industries, medical industries, chemical processing, and military industries.

Visualizing Dynamic Single Atom Catalysis.

Many industrial chemical processes, including for producing fuels, foods, pharmaceuticals, chemicals and environmental controls, employ heterogeneous solid state catalysts at elevated temperatures in gas or liquid environments. Dynamic reactions at the atomic level play a critical role in catalyst stability and functionality. In situ visualization and analysis of atomic-scale processes in real time under controlled reaction environments can provide important insights into practical frameworks to improve catalytic processes and materials. This review focuses on innovative real time in situ electron microscopy (EM)methods, including recent progress in analytical insitu environmental (scanning) transmission EM (E(STEM), incorporating environmental scanning TEM (ESTEM) and environmental transmission EM (ETEM), with single atom resolution for visualizing and analysing dynamic single atom catalysis under controlled flowing gas reaction environments. ESTEM studies of single atom dynamics of reactions, and of sintering deactivation, contribute to a better-informed understanding of the yield and stability of catalyst operations. Advances in in situ technologies, including gas and liquid sample holders, nanotomography, and higher voltages, as well as challenges and opportunities in tracking reacting atoms, are highlighted. The findings show that the understanding and application of fundamental processes in catalysis can be improved, with valuable economic, environmental, and societal benefits.

Hazard Identification and Risk Analysis of Liquid Effluent Treatment Plant Apply in Chemical Process Industry

The chemical process industry is one of the categories of highly polluting industries and generates strong wastewater of high COD along with hazardous waste which requires effective treatment and disposal/reuse of effluents. In this review, the various sources of wastewaters in the chemical industry are identified and the best available technologies to remove them are critically evaluated. The aim of the present research work was to determine the behavior of various parameters of the chemical wastewater. During the entire study evaluate, monitor, and check various environmental parameters whether they are complying with a given standard or not given by regulatory authority at chemical Industry,. The India based industry produced bulk drugs, fatty acids, fatty alcohol, food additives, personal care products, and others. The monitoring data of the effluent treatment plant will give information on the pollution control by the company and the management of waste. Overall analysis showed that there is no significant difference in pH, BOD, COD, and ammoniacal Nitrogen. The use of conventional treatment methods along with membrane reactors and advanced post-treatment methods resulting in a Coagulation wastewater treatment technology appears to be the best

Where Does Fouling Occur in Individual Random Packing Elements? A Simulative Investigation

AbstractFouling in columns is a persistent challenge in the chemical process industry, leading to decreased efficiency and increased operating costs. This paper presents an investigation into fouling behavior on individual random packing elements in packed columns using computational fluid dynamics (CFD) simulations. The study aims to gain a deeper understanding of how fouling grows and impacts the flow behavior, predicting areas susceptible to fouling and providing insights for improved design. The simulation results are validated against experimental results and show good agreement.

Improving Ammonia Emission Model of Urea Fertilizer Fluidized Bed Granulation System Using Particle Swarm Optimization for Sustainable Fertilizer Manufacturing Practice

Granulation is an important class of production processes in food, chemical and pharmaceutical manufacturing industries. In urea fertilizer manufacturing, fluidized beds are often used for the granulation system. However, the granulation processes release ammonia to the environment. Ammonia gas can contribute to eutrophication, which is an oversupply of nitrogen and acidification to the ecosystems. Eutrophication may cause major disruptions of aquatic ecosystems. It is estimated that global ammonia emissions from urea fertilizer processes are approximately at 10 to 12 Tg N/year, which represents 23% of overall ammonia released globally. Therefore, accurate modeling of the ammonia emission by the urea fertilizer fluidized bed granulation system is important. It allows for the system to be operated efficiently and within sustainable condition. This research attempts to optimize the model of the system using the particle swarm optimization (PSO) algorithm. The model takes pressure (Mpa), binder feed rate (rpm) and inlet temperature (°C) as the manipulated variables. The PSO searches for the model’s optimal coefficients. The accuracy of the model is measured using mean square error (MSE) between the model’s simulated value and the actual data of ammonia released which is collected from an experiment. The proposed method reduces the MSE to 0.09727, indicating that the model can accurately simulate the actual system.

Design of adaptive-PID-Smith control in the two-mixing tank series

ABSTRACT A control strategy must be developed to maintain the product composition of the two- or more-mixed-flow reactor series. In this research, a two-mixing tank series (TMTS) was utilized in the laboratory to approach the two-mixed flow reactors’ problems. Both tanks are designed to overflow so that the volume remains constant. The salt solution was directly fed to Tank 1, while the water was charged to both tanks as the mixing progressed. The output of Tank-1 flowed to Tank-2 through a rather long pipe, resulting in dead time in Tank-2. The Smith predictor was applied to overcome dead time. The PRC (process reaction curve) method was used to tune the PID (proportional-integral-derivative) parameters of Tank-1 and Tank-2. The novel composition controls, adaptive-PID (APID) and modified metaheuristic adaptive-PID (MMAPID), have been proposed and compared with conventional PID. The mathematical models were rigorously examined through XCOS simulations. The processing system is considered sensitive to changes in input disturbances since the process time constants of both tanks were quite low. The dead time of 0.5 minutes was found in Tank 2. The PID parameters produced by PRC experiments resulted in stable responses to changes in the disturbance system. As shown in the dynamic simulation study, both novel APID and MMAPID give almost the same results; their responses are faster than the conventional PID. Based on the integral absolute error (IAE) results, APID with scheduling PID parameters produced the smallest IAE and outperformed the conventional PID. The results of the study highlight APID and MMAPID potential in PID control applications for composition control in a TMTS. The combined APID-Smith and MMAPID-Smith were able to overcome the dead time well. This study creates opportunities for engineers and professionals to use cutting-edge control technologies, improving automation and chemical process industries.

A Comprehensive Review of Fine Chemical Production Using Metal-Modified and Acidic Microporous and Mesoporous Catalytic Materials

Fine chemicals are produced in small annual volume batch processes (often <10,000 tonnes per year), with a high associated price (usually >USD 10/kg). As a result of their usage in the production of speciality chemicals, in areas including agrochemicals, fragrances, and pharmaceuticals, the need for them will remain high for the foreseeable future. This review article assesses current methods used to produce fine chemicals with heterogeneous catalysts, including both well-established and newer experimental methods. A wide range of methods, utilising microporous and mesoporous catalysts, has been explored, including their preparation and modification before use in industry. Their potential drawbacks and benefits have been analysed, with their feasibility compared to newer, recently emerging catalysts. The field of heterogeneous catalysis for fine chemical production is a dynamic and ever-changing area of research. This deeper insight into catalytic behaviour and material properties will produce more efficient, selective, and sustainable processes in the fine chemical industry. The findings from this article will provide an excellent foundation for further exploration and a critical review in the field of fine chemical production using micro- and mesoporous heterogeneous catalysts.

An integrated approach to assess safety and security risks in chemical process industries

Chemical process industries (CPIs) face significant safety and security risks that are closely intertwined. However, previous research has predominantly examined these risks separately, lacking a comprehensive scientific approach to simultaneously analyze safety and security in critical systems. This research aims to propose an integrated approach to assess safety and security risks in CPIs. To achieve this, a taxonomy of safety and security risk factors consisting of four dimensions (i.e., occurrence probability, severity, vulnerability, and securing) and their respective twenty contributing factors has been developed. The validity and reliability of the taxonomy were assessed using the Delphi method, involving Subject Matter Experts (N = 25), and through statistical analysis. Subsequently, the Fuzzy Analytical Hierarchy Process (FAHP) was employed to determine the importance level of each contributing factor and dimension, thereby enabling the integration of safety and security risk levels. The proposed approach was validated through reality checks, and independent peer review. The findings of this study highlight the dimensions and contributing factors that have the most significant impact on the integrated safety and security risk level. Moreover, the approach provides insights into effectively assigning countermeasures to establish a safe and resilient operation in CPIs. By adopting this integrated assessment approach, CPIs can gain a deeper understanding of the interplay between safety and security risks, allowing for more informed decision-making and the implementation of targeted risk mitigation strategies.

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.

Investigation on The Effect of Low Frequency Ultrasound on The Crystallization of a Pharmaceutical Compound L+ Ascorbic Acid

One of the most crucial processes in the chemical processing industry is crystallization, which has the major challenge of producing solid products with the required purity and properties. The standard crystallization methods have various processing limitations; hence, research into alternative methods like ultrasonic-assisted crystallization has been at the forefront. The present work investigates the application of low-frequency ultrasound irradiation (40 kHz) for improving the cooling crystallization of ascorbic acid. The impact of ultrasonic irradiation on crystal size, shape, and induction time has been studied, and a comparison with the conventional method has been made. The standing time had a minor effect on particle size on average, while the initial temperature had a far more significant impact. Photographic analysis using image-analysis software indicated that when ultrasound was applied to the saturated solutions, the resulting crystals were smaller and more uniform in size and shape. The resultant crystal grows predominantly in a single direction, resembling thin prisms. The use of ultrasound was also shown to reduce the induction time significantly. This ultrasonic impact is stronger at lower initial temperatures. Indeed, the smallest induction time of 300 s was obtained for sonicated solutions at an initial temperature of 65°C and ultrasonic power of 250 w. When different levels of ultrasonic power dissipation were tested, it was established that the time required for the first nuclei to appear decreased as the power increased. There was, nevertheless, a marginal impact on average crystal size.

Continuous and controllable synthesis of MnO2 adsorbents for H2S removal at low temperature

H2S is an extremely noxious impurity generated from nature and chemical industrial processes. High performing H2S adsorbents are required for chemical industry and environmental engineering. Herein, α-, γ-, and δ-MnO2 adsorbents with high sulfur capacity were synthesized through a continuous-flow approach with a microreactor system, achieving much higher efficiency than hydrothermal methods. The relationship between crystal structure and synthesis conditions such as residence time, reaction temperature, concentration of K+ in solution and reactant ratio is discussed. According to the H2S breakthrough tests at 150 °C, continuously prepared α-, γ-, and δ-MnO2 exhibited sulfur capacities of 669.5, 193.8 and 607.6 mg S/g sorbent, respectively, which was at a high level among the reported adsorbents. Such enhanced performance is related to the large surface area and mesopore volume, high reducibility, and a large number of oxygen species with high reactivity and mobility. Manganese sulfide and elemental sulfur were formed after desulfurization, which indicated the reaction consisted of two steps: redox and sulfidation of the sorbents. This study provides an innovative design strategy for the construction of nanomaterials with high H2S adsorption performances.