Chemical Engineering Unit Operations Research Articles

Crystallisation: Solving crystal nucleation problem in the chemical engineering classroom based on the research grade experiments deployed in virtual mode

Crystallization via nucleation can isolate active pharmaceutical ingredients from their crudes. While chemical engineering textbooks provide theoretical knowledge on crystallization and nucleation theories, they often fall short in providing provide practical insights on the nucleation mechanism. To bridge this gap, we introduced a virtual experiment on nucleation in second-year chemical engineering classrooms. The main goal is to educate students on crystallization procedures in research and process industries, teaching them how to analyse and manage collected data while integrating theoretical knowledge. This includes conveying the kind of information that can be obtained from a crystallisation process and instructing students on how to analyse and manage the data collected in the light of the theories learned. We devised an original chemical engineering problem on nucleation, derived directly from the raw data collected in the classroom from virtual experiments. This method differs from the conventional approach of solving standard textbook problems. The textbook problems, regrettably often lack crucial information on how nucleation rate or surface free energy are directly obtained from raw data. By the conclusion of the virtual experiment, students have acquired a comprehensive understanding encompassing both practical and theoretical aspects of crystallization, with a particular focus on nucleation. The methodologies elucidated in this study can be applied across a spectrum of chemical engineering modules, including process engineering, unit operations in chemical engineering, mass transfer, and can even be integrated into specialized courses dedicated to crystallization.

Machine learning for rapid discovery of laminar flow channel wall modifications that enhance heat transfer

Numerical simulation of fluid flow plays an essential role in modeling many physical phenomena, which enables technological advancements, contributes to sustainable practices, and expands our understanding of various natural and engineered systems. The calculation of heat transfer in fluid flow in simple flat channels is a relatively easy task for various simulation methods. However, once the channel geometry becomes more complex, numerical simulations become a bottleneck in optimizing wall geometries. We present a combination of accurate numerical simulations of arbitrary, flat, and non-flat channels as well as machine learning models trained on simulated data to predict the drag coefficient and Stanton number. We show that convolutional neural networks (CNNs) can accurately predict target properties at a fraction of the computational cost of numerical simulations. We use CNN models in a virtual high-throughput screening approach to explore a large number of possible, randomly generated wall architectures. Data augmentation techniques are incorporated to enforce physical invariances toward shifting and flipping, contributing to precise prediction for fluid flow and heat transfer characteristics. Moreover, we approach the interpretation of the trained model to better understand relevant channel structures and their influence on heat transfer. The general approach is not only applicable to simple flow setups as presented here but can be extended to more complex tasks, such as multiphase or even reactive unit operations in chemical engineering.

A Review on the Adsorption Isotherms and Design Calculations for the Optimization of Adsorbent Mass and Contact Time.

Adsorption is a widely used chemical engineering unit operation for the separation and purification of fluid streams. Typical uses of adsorption include the removal of targeted pollutants like antibiotics, dyes, heavy metals, and other small to large molecules from aqueous solutions or wastewater. To date several adsorbents that vary in terms of their physicochemical properties and costs have been tested for their efficacy to remove these pollutants from wastewater. Irrespective of the type of adsorbent, nature of the pollutant, or experimental conditions, the overall cost of adsorption depends directly on the adsorption contact time and the cost of the adsorbent materials. Thus, it is essential to minimize the amount of adsorbent and the contact time required. We carefully reviewed the attempts made by several researchers to minimize these two parameters using theoretical adsorption kinetics and isotherms. We also clearly explained the theoretical methods and the calculation procedures involved during the optimization of the adsorbent mass and the contact time. To complement the theoretical calculation procedures, we also made a detailed review on the theoretical adsorption isotherms that are commonly used to model experimental equilibrium data that can be used to optimize the adsorbent mass.

Augmented Reality: An Emergent Technology for Students’ Learning Motivation for Chemical Engineering Laboratories during the COVID-19 Pandemic

In higher education, the learning of Unit Operations in Chemical Engineering and the development of practical activities became a real challenge. Therefore, the use of emerging technologies became necessary to develop practical laboratory activities of the Unit Operations due to the inaccessibility to the equipment infrastructure. In this study, Project-Based Learning methodology was assisted with the Augmented Reality (AR) technology for the development of subjects. The development of a real educational experiment for the application of a basic topic of the course as a project for each subject was proposed. The results were presented using the Zappar application, and a unique rubric was used for the evaluation of project. The evaluation of students’ motivation for learning was measured using Keller’s Attention, Relevance, Confidence and Satisfaction (ARCS) model of motivation by Instructional Materials Motivation Survey (IMMS). The attention, confidence and satisfaction demonstrate an acceptable reliability in comparison to relevance, which was considered as moderate reliability. Above 96% of students considered that the activities, materials, and organization of information used for the AR project caught their attention and encouraged their interest towards the fundamentals applied in the project. Around 80% of students expressed concern about the ease of AR technology use, and understood the learning aim of the project. Above 85% of students recognized the relevance of activities and their usefulness, and considered AR as a meaningful educational tool. 90% of students considered that AR technology helped them to develop the subject competencies. Cronbach’s Alpha was used to indicate an acceptable reliability of IMMS instrument. Regarding IMMS, values were superior to 0.7, which could be considered acceptable. For the individual ARCS dimensions, values of Cronbach’s alpha reached values of 0.94.

Towards responsive gas-solid operations: Oscillating and vortex flows

Working towards a circular economy requires the ability to introduce clean energy sources, new vectors and storage methods into classic process infrastructure. An efficient contact between gases and solids is at the core of this task across manufacturing, environmental and energy sectors. New integrated processes start to move away from the use of the classic unit operations in chemical engineering into more flexible, multifunctional units, but intensified contact chambers are often too specialised. New design concepts must focus not only on the efficiency of a device, but in creating robust, flexible solutions that can adapt to changing targets and perform multiple functions to widen the scope of advanced optimization and control strategies. In this work, I briefly discuss the role of responsive devices in the design of sustainable processes involving gas-solid flows, and I provide a quick overview of the role of structured fluidization paying special attention to two promising pathways: dynamically structured oscillating fluidised beds that deliver homogeneous, responsive, and scalable solid mixing at low velocity, and the potential evolution of emerging vortex devices into rotational “moving” beds working at high interfacial velocity.

Brewing Beer from Malt Extract as University Laboratory Experiment to Enhance Chemical Engineering Learning Outcomes Understanding

Brewing beer is one of the most popular food processes in the current society, and it has been widely used as a learning course at many universities. However, most laboratory experiences take a very long time for development. In this work, we discuss the brewing process from malt extract as an intelligent way to reduce the timing for implementation by simplifying some of its stages, such as malting or mashing, but remaining the same core process. During brewing with malt extract, the students deal with this multidisciplinary process, enhancing primary learning outcomes related to the unit operations of chemical engineering applied to the food industry. At the university level, the addition of brewing as a laboratory experiment might directly affect the productive fabric of the area through the development of new beer-related businesses.

Designing interactive augmented reality application for student's directed learning of continuous distillation process

Continuous distillation is an important separation process in chemical engineering curriculum. Conventionally, it is often taught as black box diagrams that lack user visibility, thus preventing students from developing a deeper understanding and comprehension. This paper presents the technical development of the mobile AR application and its implementation in the curriculum of Chemical Engineering Unit Operations at Nanyang Technological University Singapore. The mobile AR application is to provide interactive visualization and real-time numerical simulation to promote students’ active learning in the classroom. The results of the pre-test and post-test indicated that the AR application helped students gain a better understanding of the principle and fundamental concepts of the distillation process. The evaluation survey with 6-point likert scale questions shows that students had a positive experience using the mobile AR application and it has enhanced their learning experience, as suggested by a mean evaluation score of 5.18 out of 6.0.

Neural Network Technique in the Study of Selected Chemical Engineering Unit Operations Data using MATLAB

Neural Network Technique in the Study of Selected Chemical Engineering Unit Operations Data using MATLAB

Flow Chemistry: A Sustainable Voyage Through the Chemical Universe en Route to Smart Manufacturing.

Microfluidic devices and systems have entered many areas of chemical engineering, and the rate of their adoption is only increasing. As we approach and adapt to the critical global challenges we face in the near future, it is important to consider the capabilities of flow chemistry and its applications in next-generation technologies for sustainability, energy production, and tailor-made specialty chemicals. We present the introduction of microfluidics into the fundamental unit operations of chemical engineering. We discuss the traits and advantages of microfluidic approaches to different reactive systems, both well-established and emerging, with a focus on the integration of modular microfluidic devices into high-efficiency experimental platforms for accelerated process optimization and intensified continuous manufacturing. Finally, we discuss the current state and new horizons in self-driven experimentation in flow chemistry for both intelligent exploration through the chemical universe and distributed manufacturing.

A Roadmap for Designing Extended Reality Tools to Teach Unit Operations in Chemical Engineering: Learning Theories & Shifting Pedagogies

A Roadmap for Designing Extended Reality Tools to Teach Unit Operations in Chemical Engineering: Learning Theories & Shifting Pedagogies

Ultrasound-assisted Solid-liquid Extraction Devices - Harnessing Active Ingredients from Plant materials – Overview and Analysis

Background: In the growing environmental concern use of natural products, efficient processes and devices are necessary. Solid-Liquid extraction of active Ingredients from Plant materials is one of the important unit operations in Chemical Engineering and need to be enhanced. Objectives: Since, these active ingredients are firmly bound to the plant cell wall membrane, which pose mass-transfer resistance and need to get detached through the use of suitable process intensification tools such as ultrasound and suitable devices. Therefore, detailed analysis and review is essential on development made in this area through Publications and Patents. Hence, the present paper illustrates the development of ultrasound assisted device for solid-liquid extraction are presented in this paper. Methods: Advantages such as % Yield, Reduction in extraction time, use of ambient conditions, better process control, avoidance or minimizing multi stage extraction could be achieved due to the use of ultrasound in extraction as compared to conventional processes. Conclusions: Use of ultrasound to provide significant improvements in the extraction of Vegetable tannins, Natural dyes for application in Leather processing has been demonstrated and reported earlier. These enhancement could be possible through various effects of ultrasound such as better flow of solvents through micro-jet formation, mass transfer enhancement due to rupture of plant cell wall membranes through acoustic cavitation, better leaching due to micro-mixing and acoustic streaming effects. This approach would minimize material wastage; thereby, leading to eco-conservation of plant materials, which is very much essential for better environment. Hence, various methods and design for application of ultrasound assisted solid-liquid extractor device are necessary.

An improved batch fluidized drying experimental design based on digital sensors and a minicomputer

AbstractIn most undergraduate programs of chemical engineering in Chinese universities, the batch fluidized bed drying (BFBD) experiment is commonly adopted as a part of the experimental course of chemical engineering unit operation. In those BFBD experiments, the students should dry the material in a dryer, repeatedly sample and measure it outside to get its moisture content. In most cases, each sampling and measuring operation needs more than 5 min. The BFBD drying experiment conducted in that manner cannot obtain adequate, accurate data, making it difficult for the student to perform proper calculation and data analysis. In this article, the authors build a small BFBD prototype equipment and mount a set of digital temperature/humidity sensors. Then they use a Raspberry Pi 3, a kind of mini‐computer, to automatically measure and record the process parameters values online. Aided by those modern information process methods, the data accuracy and amount are all enhanced. Based on the gotten big data set, the student can get much more accurate results and do a more thorough analysis. The data analysis based on the old BFBD equipment is too straightforward and simple because it only needs the mass balance calculations. On the contrary, although the new BFBD equipment adopts an indirect way to measure the drying process, it obtains much more accurate results than before. The students must also apply more theories to get the results, such as mass transmission, the thermal balance, which makes the experiment more comprehensive. That is meaningful and helps to achieve the objectives of the chemical engineering experiments.

Integrating Hands-on Battery Design into a Chemical Engineering Unit Operations Laboratory

Though electrochemistry and electrochemical engineering play significant roles in the behavior of many engineered systems – either through their fundamental operation (i.e. batteries) or secondary effects (i.e. corrosion) – engineering undergraduates typically do not graduate with appreciable fundamental knowledge in these area. It is important for our community to reach out to these students and develop coursework modules that build both fundamental and applied knowledge related to electrochemical systems. In this talk, integration of electrochemical science and engineering principles into a Junior Laboratory course will be discussed. The battery module in this course was offered for over a two-year period. In this laboratory, teams of four students are provided with a problem statement: Design a battery pack that can seamlessly REPLACE the AA batteries in a child’s toy. Students are allowed to choose their own platform. They must determine the power requirements for the toy under various operational conditions. Of course, on day 1, undergraduates do not know almost anything about how to design a battery. Therefore, the students systematically step them through a series of tasks and lectures to build their knowledge and competency – covering thermodynamics, polarization (kinetics and mass transfer), cell design, etc. These lectures and iteration of their battery design occurs over the course of an entire semester. The details around these will be discussed in the talk. The lab culminates with a demonstration day where teams show off their home-made batteries, operating a wide range of toys.

Quantitative visualization of fluid mixing in slug flow for arbitrary wall-shaped microchannel using Shannon entropy

Micro-reactors based on slug flow are among the most promising developments for improving the efficiencies of chemical reactions and unit operations in chemical engineering. Quantitative understanding of the local and global fluid dynamics and their effects on fluid mixing is required for designing effective slug flow micro-reactors. This paper proposes a new method for quantitative two-dimensional assessment of fluid mixing in slug flow. Pixel-wise calculation of local entropy inside a slug is discussed. The proposed method is based on two-phase simulation using the volume of fraction (VOF) algorithm and is thus applicable to the flow pattern in arbitrary wall-shaped micro-reactors. The method consists of three steps. (1) Flow analysis using two-phase VOF algorithm: A series of two-dimensional velocity fields inside the slug along time is obtained for a certain duration. (2) Backward particle tracking from the target image to the initial image: The slug in the initial image is divided into small regions, and each region is assigned a different label. Accumulation of backward particle tracking results reveals a two-dimensional distribution of labels in the target image. (3) Pixel-wise calculation of entropy on the obtained distribution of labels: The resulting image is a quantitative two-dimensional mixing pattern inside the slug. The proposed method was applied to three types of microchannels with different bumps on the walls. The results could quantitatively distinguish the differences in fluid mixing capability among the systems.

Supply chain design network model for biofuels and chemicals from waste cooking oil

Supply chain is an effective coordination and integration of all activities performed by several business lines with the aid of their infrastructures. Supply chain managing and designing teams should adopt the latest most effective scientific methods to locate facilities. Waste cooking oil (WCO) is dumped in swears and municipal drainages, causing a lot of problems. One of the most important uses of WCO is converting it to biodiesel. In Egypt case, a lot of barriers were found to initiate a plant producing biodiesel from WCO, as there is no collection supply chain system designed. Lack of public awareness led to the drawback of dumping WCO in municipal drains, causing sewer damage and water pollution. Only 35 % of wastewater in Egypt is purified before being dumped into the Nile River. This research generates a supply chain design model of three layered medium mixed integer linear programme for an application of biodiesel production from WCO. MATLAB Software with a Graphical User Interface programmed by the C SHARP C# programming software and EXCEL solver tools were used. CAPCOST tool was used to generate economic feasibility study. Scenarios are examined to price out and compare trade-offs potential solutions. Optimizing the operations are focused on chemical engineering unit operations, production process facilities as well as the entire supply chain.

SEPARATION OF COPPER FROM A LEACHING SOLUTION OF PRINTED CIRCUIT BOARDS BY USING SOLVENT EXTRACTION WITH D2EHPA

Abstract Global generation of waste electrical and electronic equipment (WEEE) is increasing quickly. Metals from WEEE can be recovered by using unit operations of chemical engineering. This paper describes a combined hydrometallurgical route (sulfuric oxidant leaching + solvent extraction) to recover copper from printed circuit boards (PCBs). A non-magnetic fraction from comminuted PCBs was used to perform leaching tests at 75oC for 6 hours in an oxidizing media (sulfuric acid + hydrogen peroxide). In order to separate zinc, aluminum, and copper from the leaching liquor, solvent extraction tests were carried out using D2EHPA. Parameters that influence the process, such as pH, extractant concentration, and the aqueous/organic (A/O) ratio were investigated. Solvent extraction experiments were carried out in two stages: i) separation of zinc, aluminum, and residual iron, and ii) copper separation. The results showed that the leaching obtained around 60% aluminum, 94% copper, 76% zinc, 50% nickel and residual iron from the non-magnetic fraction of PCBs. With the solvent experiments, in the first stage, 100 wt.% zinc, iron and aluminum were extracted at pH 3.5, 2:1 A/O, 10 % (v/v) D2EHPA, while, in the second stage 100% of the copper was extracted at pH 3.5, 1:1 A/O, 20 % (v/v) D2EHPA.

The progress of quantitatively description of membrane process based on the mechanism of nanoconfined mass transfer

As a novel chemical engineering unit operation, membrane separation has many advantages such as high efficiency and energy saving. Recently, at nanoscale, the increasingly anomalous phenomena of ultra-fast flux and breaking the tradeoff between flux and selectivity are found in membrane separations (such as pervaporation, reverse osmosis, nano-filtration, etc.), which promote considerable attentions. However, traditional models or mechanisms fail to explain these phenomena or to predict the behavior. The main reason of this is that when the size of systems shrinks to nanoscale, the intermolecular forces between the fluids and membrane pore wall (including primarily steric interactions/hydration, van der Waals interactions and electrostatic interactions) have become the most prominent ones in nanoconfined systems, which make significant contributions to mass-transfer and engender unique performance. The relevant mass-transfer theories especially under nanoconfinement lacks common mass-transfer mechanism and controlling methods for these abnormal phenomena on its mass-transfer, severely restricting the design and development of related membrane materials. To quantitatively describe the nanoconfined membrane process, a universal theoretical framework for nanoconfined mass-transfer is needed and then the contributions of various influencing factors at nanoscale to the flux and selectivity should be illustrated quantitatively. In this review, we first analyzed the challenges of classical mass-transfer models in the confinement conditions, such as solution-diffusion model to dense membrane. The main problem can be attributed to that these models in essence describe an equilibrium state plus a dynamic process, which not includes the interfacial influence. Secondly, we explored the application of non-equilibrium thermodynamics linearization method in establishing the mass-transfer model under nanoconfinement. We simplified the interfacial phenomenon to assume that system located at a distance close to interface can be regarded as a microelement and its deviation from equilibrium remained in the linear region. We established a model to describe nano- and micro-interfacial transfer confined in a complex structure, using CO2 separation by ionic liquids as an example, assuming that the transfer in phase interface comprised two steps (surface reaction and diffusion) in the same phase. The mass-transfer model on the basis of linear non-equilibrium thermodynamics was proven to decouple reaction and transfer more effectively for achieving process intensification by adjusting easy-to-control factors, compared with the classical solution-diffusion model. Thirdly, the factors affecting the behavior of the confined fluid molecules were so complex that it was difficult to do single-factor analysis and to determine controlling factors. Related advances on the analysis of the influencing factor for nanoconfined mass-transfer were further explored. We evaluated the effects of the influencing factors for water molecules transfer in various nanochannels or nanotubes, including pore size, pore wall hydrophilicity, pore geometrical shape and pore mouth modification, based on the numerous results derived from molecular simulation and experimental method. Finally, we had a brief conclusion and summarized the development directions. (1) Linear non-equilibrium thermodynamics method has great potential in the modeling of mass-transfer at nanoscale. (2) Experimentally synthesizing ordered nanochannel material should be encouraged to build a platform for comparison of the factor analysis results from molecular simulation and experiment. (3) The original experimental characterization methods are expected to be developed to probe the intermolecular interactions quantitatively.

Investigation of the Pressure Drop of Random Packed Bed Adsorbers

Adsorption is one of the most often used unit operations in chemical engineering. However, due to computational limitations and time constraints simulations of adsorption processes are commonly done only with black box models or simplified porous media structures. In a new project an OpenFOAM® based CFD solver adsorpFoam, the required grid generation work flow using DEM methods for random packings and also post processing tools were created to carry out extended analyses of adsorption columns. Fully resolved packed beds were simulated to get more detailed information on gas side inhomogeneous distribution, bypass streams and near-wall effects (all these factors contribute to the total pressure drop of the packing), as well as fluid residence time distributions of random packings in columns.The current work will summarize the first results of adsorpFoam with respect to the validation using gas flow in laboratory scale random packings: The code and the procedure have been tested for spheres, mono- dispersed cylinders and cylindrical particles with size distribution. In all cases, a good agreement of the experimental results and the CFD simulations has been achieved.In a next stage of the project multi-component adsorption kinetics will be investigated, which are influenced by the local flow and temperature profile. Compared to common porous media CFD approaches a more realistic and reasonable residence time distribution can be achieved with this method.

An optimization based algorithm for solving design problems of counter-current multistage batch solid–liquid extractors for complex systems: Application to vanilla extract

Solid–liquid extraction is one of the aged unit operations in chemical engineering. However the process design models, universally included in textbooks, continue considering infinite dilution of extractable material and single component solvent. Extraction processes of bioactive compounds with composite solvents (ethanol–water) from plants or foods products require a better understanding of equilibrium between phases of bioactive compounds and their role in the process design. Then, a general mathematical model of counter-current ideal multi-stages batch solid–liquid extractors was developed. The model considers composite solvents and the two equilibrium relations required for the total description of a solid–liquid extraction system. An optimization based algorithm was proposed for solving the design problems. Experimental equilibrium relations were obtained for vanilla–ethanol–water system and used as example of model application. Additionally, the prediction of a particular component (vanillin) concentration in extract was included and experimentally validated.

Industrial Automation in Unit Operations Labs

Chemical engineering unit operation labsdo an excellent job of integrating the whole curriculumand exposing students to pilot-scale systems. Where theyare often lacking, though, is the exposure to and use ofreal-life industrial automation by the future graduates. Aunit operation lab that has been automated usingindustrial level paradigms and equipment is the focus ofthis paper. A partnership with a global automationmanufacturer (Emerson) was established and the lab wasretrofitted using industrial sensors and actuators, aDistributed Control System (DeltaV DCS), industrialnetworks (FOUNDATION Fieldbus and AS-i), HumanMachine Interface (HMI) screens, and systemredundancy. The details of the automation along with itsuse through the lab curriculum will be discussed. Thiscross-curricular approach benefits students as, throughthe regular unit operation labs, they become familiar withkey elements of an automated set-up, understand the needfor it and its limitations, see control loops in action,communicate to the units through the HMI, and use theHMI to recover historical data on the processes. The labis a meso-scale of a processing facility and preparesstudents for field work after graduation. At the sametime, the traditional exposure to “manually operated”sensors and final elements is maintained as some of theunits have not been converted to fully automated systems