Chemical Engineering Design Research Articles

(Keynote) Soft Microfluidic Analysis Systems for the Skin

Recent advances in materials science, chemical engineering and mechanics design establish the foundations for high performance classes of microfluidic lab-on-a-chip technologies that have physical properties matched those of the human skin. The resulting devices can integrate with the surface of the skin in a water-tight yet physically imperceptible fashion, to provide real-time measurements of sweat rate and total sweat loss, along with continuous, clinical-quality biochemical information on physiological status using a combination of colorimetric and electrochemical techniques. This talk summarizes the key ideas and presents application examples in sports performance, worker safety, medical diagnostics and nutritional monitoring.

Scaling-up a Photo-Electrocatalytic Reactor for CO2 Capture and Conversion to Syngas

The most challenging deal we face today is the need to lower greenhouse gas (GHG) emissions and tackle climate change. Though calls to reduce them are growing louder yearly, emissions remain unsustainably high. CO2 is the key contributor to global climate change in the atmosphere. Electrochemical CO2 reduction (EC CO2R) into chemicals or fuels holds great research interest as a promising approach to mitigate CO2 emissions and reach a carbon-neutral future.1 In this regard, an extraordinary effort has been made to discover new efficient and sustainable catalysts at the laboratory level over recent years. High-performance electrocatalysts in aqueous electrolytes often rely on noble metals, which may hinder their industrial applications. Herein, we successfully synthesized core-shell Cu2O/SnO2 nanoparticles2–4 functionalized with a silane group, using a simple and versatile methodology based on a three-step scalable synthesis method involving wet precipitation followed by salinization and, finally, a rhenium-based complex has been assembled by electro-polymerization.5 The carbon paper-supported Cu2O/SnO2-Re electrocatalyst was characterized at 10 cm2 scale achieving a CO:H2 ratio from 3 to 9, and demonstrating an stable syngas production up to 24 hours at -20 mA·cm-2. To translate those developments from the laboratory level to a higher TRL towards the practical application of CO2 capture and utilization6, an additional chamber was added to the system for the continuous CO2 capture and electrochemical conversion, increasing the electrode area from 10 cm2 to 100 cm2. Captured CO2 co-electrolysis to syngas (H2:CO ratio of 5) in one step was demonstrated with a high CO2 conversion at a current up to -2 A, indicating the scale-up potential of this intensified system. The technology is currently under validation in a TRL4 reactor composed of an array of 5 modules (i.e., 4 x 5 cells x 100 cm2) with a total active area of or 0.2m2 for direct CO2 conversion from simulated anthropogenic sources. The design integrates low-cost photovoltaic (PV) cells to provide any required additional bias to drive the reaction, thus, Perovskite PV panels with a cost of up to 5 times lower (10 €/m2) than Si PV cells were used. The TRL5 demonstration of the developed technology will be done with real flue gas emissions the first semester of 2024. Acknowledgements The financial support of the SUNCOCHEM project (Grant Agreement No 862192) of the European Union’s Horizon 2020 Research and Innovation Action programme is acknowledged. References Guzmán, H., Russo, N. & Hernández, S. CO2 valorisation towards alcohols by Cu-based electrocatalysts: challenges and perspectives. Green Chemistry vol. 23 1896–1920 Preprint at https://doi.org/10.1039/d0gc03334k (2021).Cuatto, G. et al. Standardization of Cu2O nanocubes synthesis: Role of precipitation process parameters on physico-chemical and photo-electrocatalytic properties. Chemical Engineering Research and Design 199, 384–398 (2023).Zoli, M., Guzmán, H., Sacco, A., Russo, N. & Hernández, S. Cu2O/SnO2 Heterostructures: Role of the Synthesis Procedure on PEC CO2 Conversion. Materials 16, (2023).Zoli, M. et al. Facile and scalable synthesis of Cu2O-SnO2 catalyst for the photoelectrochemical CO2 conversion. Catal Today 413–415, 113985 (2023).Miró, R. et al. Solar-driven CO2 reduction catalysed by hybrid supramolecular photocathodes and enhanced by ionic liquids. Catal Sci Technol 13, 1708–1717 (2023).Sullivan, I. et al. Coupling electrochemical CO2 conversion with CO2 capture. Nat Catal 4, 952–958 (2021). Figure 1

Process design in chemical engineering CFD symposium

Process design in chemical engineering <scp>CFD</scp> symposium

Using senior undergraduate students as coaches in an introductory chemical engineering design course

Senior undergraduate students were hired as Teaching Assistants (TAs) in CHBE 221, an introductory bioprocess design course offered in the Department of Chemical and Biological Engineering at University of British Columbia, and the roles were recast from traditional course support, to being coaches and mentors to a small number of teams working on term-spanning design projects. This was done as a means to provide more personalized support to students working on realistic design problems early in their training, leverage the benefits of peer learning strategies, and provide professional and leadership development opportunities to the TAs ahead of graduation. At the end of the course in which this was implemented, surveys were sent to students asking them to comment on their experience with this mentorship model, and the TAs of the course were interviewed to better understand theirs. This paper presents the results of these surveys and interviews, highlights the benefits and challenges of this approach, and provides recommendations for future implementations of this student support model

Data-driven molecular design and simulation in modern chemical engineering

Data-driven molecular design and simulation in modern chemical engineering

Designing biomimetic two-dimensional channels for uranium separation from seawater.

Efficient separation of uranium from seawater stands as a pivotal challenge. This study unveils an approach focusing on the ingenious design of biomimetic two-dimensional (2D) membranes tailored explicitly for this purpose. Leveraging the unique interplay of DNA strands housing U aptamers, pH-responsive i-motifs, and poly A(10) segments ingeniously embedded within graphene oxide membranes, a distinctive biomimetic 2D channel is engineered. The strategic integration of these bio-inspired elements enables dynamic adjustment of interlayer spacing, augmenting both the permeability of the membrane and the selectivity of the aptamer for uranyl ions. During the separation process, the encounter between uranyl ions and the enhanced aptamer within the interlayers initiates a crucial interaction, triggering a specific concentration polarization mechanism. This mechanism stands as the cornerstone for achieving a highly selective separation of uranyl ions from the vast and complex matrix of seawater. The membrane exhibits excellent performance in real seawater, with a rejection rate of uranyl ions of ≈100% and sustained selectivity of uranyl ions over ten cycles. Importantly, the selectivity of uranium and vanadium can reach 14.66. The significance of this research lies not only in the effective separation of uranyl ions but also in showcasing the broader applicability of 2D membrane design in chemical engineering.

Extended Definition of Conversion and Reaction Extent for a Systematic Development of the Design Equations for Reactor Networks

The aim of this work is to present in a systematic way a novel general methodology to develop the design equations (heat and mass balances) for networks of ideal reactors, that is, Plug-Flow Reactors (PFRs) and Continuous Stirred Tank Reactors (CSTRs). In particular, after introducing the general definition of conversion to be used for reactor networks, several case studies of interest in chemical engineering are presented as topic-examples of application: (i) adiabatic-stage reactors with recycle, (ii) adiabatic-stage reactors with split, (iii) adiabatic-stage reactors intercooled by reactants and (iv) adiabatic-stage reactors with interstage distributed feed. More generally, the presented methodology can also be applied to develop the design equations for complex networks of interconnected reactors, not restricted to those considered in the present work. The motivation behind the present study lies in the fact that, to the best of our knowledge, a systematic development of the design equations of single reactors in reactor networks is currently missing in the open literature as well as in the reference textbooks of chemical reaction engineering and reactor design.

Improving the precision of solids velocity measurement in gas-solid fluidized beds with a hybrid machine learning model

Accurate measurement of solids velocity is crucial for fluidized bed reactor design, optimization, and scaling in chemical engineering. However, the cross-correlation calculation of dual-channel particle concentration signals has limitations in dense-phase fluidized systems. To address this, we propose a data-driven approach using machine learning algorithms in numerical simulations. Four popular algorithms (linear regression, random forest, support vector machine, and neural network) are evaluated. Individual models show poor generalization with a determinable coefficient below 0.2. To overcome this, a hybrid model combining a neural network and random forest is developed, improving data prediction and generalization. The determinable coefficient increases to 0.90, and the relative error in average particle velocity prediction reduces to less than 0.01. This hybrid machine learning model has the potential to overcome limitations of cross-correlation-based particle velocimetry, expanding its applications in multiphase flow systems. It offers a promising solution for accurate solids velocity measurement in fluidized beds.

Exploring Performance and Cost Trade-Offs in Electrochemical CO2 Separation Processes

Increasing global energy demand coupled with a continued reliance on carbon-intensive fuels has contributed to the rise in anthropogenic greenhouse gas emissions that are adversely impacting the global climate.1,2 While the expansion of low-cost renewable electricity (often coupled with energy storage) offsets fossil-fuel-based generation, complete mitigation of carbon emissions will likely require the capture, utilization, and/or storage of carbon dioxide (CO2) at scale. Today’s state-of-the-art separation technologies rely on thermochemical processes to extract CO2 from industrial waste streams, post-combustion flue gases, or directly from the atmosphere. Such approaches are energetically intensive and typically rely on fossil-fuel-derived heat to release CO2 and regenerate the sorbent, ultimately limiting process effectiveness.3 Electrochemical approaches to CO2 capture and concentration are increasingly seen as a viable pathway to reducing carbon emissions, as these processes enable several advantages including direct integration with renewables, modular deployment, operation near ambient conditions, and high energetic efficiencies.4 Despite this promise, these concepts are at an early-stage and the relationships between cost and performance are not well-understood at the molecular-, cell-, or system-level.In this presentation, we will discuss how techno-economic modeling can be used to inform design criteria for cost-competitive electrochemical CO2 separation systems. We will specifically focus on a 4-stage system with soluble redox-active species for direct binding / debinding with CO2. First, we describe and integrate all process units (i.e., electrochemical reactor, absorber, desorber) via thermodynamic, chemical, and electrochemical relationships and then estimate capital, fixed, and variable costs via a levelized cost of capture model. Second, we investigate key scaling correlations and cost sensitivities for the 4-stage system, including the role of resistive losses in the electrochemical reactor and binding affinity in the absorption column. Third and finally, we connect system-level performance and cost targets to molecular / system properties and operating envelopes. While our focus is on a particular system, the framework is generalizable and can be extended to different electrochemical and thermochemical approaches to CO2 separation, potentially enabling technology comparisons on a common basis. Acknowledgements This work was supported by the Alfred P. Sloan Foundation. K.M.R. gratefully acknowledges the support of the National Defense Science and Engineering Graduate (NDSEG) Fellowship. References Ritchie, H., Roser, M. & Rosado, P. CO2 and Greenhouse Gas Emissions. Our World in Data (2020). Annual Energy Outlook 2021. U.S. Energy Information Administration (2021).Khan, F. M., Krishnamoorthi, V. & Mahmud, T. Modelling reactive absorption of CO2 in packed columns for post-combustion carbon capture applications. Chemical Engineering Research and Design 89, 9, 1600–1608 (2011).Renfrew, S. E., Starr, D. E. & Strasser, P. Electrochemical Approaches toward CO2 Capture and Concentration. ACS Catal. 10, 21, 13058–13074 (2020).

An interactive graph resource for chemical engineering teaching

Instructors teaching chemical engineering topics have traditionally used graphical methods to explain core concepts and design unit operations. However, with the shift towards online and blended/flexible learning, there is a need to adapt these graphical methods for online use. This paper presents a set of interactive graphs that can be used for fluid flow, separation process, and reaction process unit operations and aims to investigate students' opinions of the interactive graphs and their motivations for using them in their studies. The digital resource developed in the paper is a set of slim single-page applications written in HTML5 & CSS3 with the numerical calculations undertaken in JavaScript (JS). The interactive graphs are embedded into the virtual learning environment (VLE) system Blackboard for two courses, and a paper survey is used to measure students' perceptions towards the interactive graphs and their use of them. The UTAUT2 model is used to analyse the student use of these resources. It is demonstrated that the use of online interactive graphs is popular with the students and the main driving factors are the performance expectancy and the hedonic motivation. Short scaffold questions to help students interact with the graphs are key to their usefulness. Some guidance on the use of interactive graphs is also provided. The interactive graphical resource can be found and used at the Graphical Chemical Engineering Design weblink: https://www.ce.manchester.ac.uk/gced.

Review on Chemical Engineering Capstone Design Teaching Model to Drive Continuous Improvement and Achieving Program Outcomes

Project-based Learning (PjBL) is a well-known paradigm for engineering design education, with numerous case studies published in the literature. Capstone is intended to provide students with an opportunity to demonstrate their readiness for professional practice. Consequently, this paper suggests a teaching and learning model as a new paradigm for capstone design projects in an effort to perpetually enhance engineering education, particularly in chemical engineering design courses. Rigorously assessing students’ knowledge of the design process is essential for understanding how to best create learning environments to facilitate the development of such knowledge. Such assessment is also quite difficult and hence there is a lack of assessment tools capable of measuring the design process knowledge of every student. The model also intends to assess whether students can explain their tasks through PBL. Besides, it provides such a structure for aligning course learning outcomes, methods of teaching including teaching strategy and learning activity, and methods for assessing students’ performance. Instead of prioritizing student outcomes and mapping them to direct metrics related to curriculum, the model is also used to highlight areas of engineering education where significant opportunities exist for improving the preparedness of our students for capstone and ultimately for professional practice. This paper also addresses an early stage of a study to seek the challenges in incorporating complex engineering problems during designing a capstone design model.

Hydrodynamic and mass transfer correlations for SiC ceramic foam monolithic trays used in distillation column

AbstractBACKGROUNDCellular foam materials are excellent engineering materials for many applications in chemical engineering, especially process intensification of chemical conversions and separation. Recently, a silicon carbide (SiC) ceramic foam monolithic tray was developed as an excellent mass transfer tool to improve distillation and it showed an improved operational flexibility. Previous studies have revealed the effects of open cell diameter and tray thickness on the hydraulic performance and mass transfer efficiency of SiC foam monolithic trays, but relevant correlations are still missing, limiting their practical uses.RESULTSIn this study, based on the published experimental data, empirical correlations were developed to predict the hydrodynamic performance and mass transfer efficiency of SiC ceramic foam monolithic trays. The new correlations include the influence of the tray structure parameters, such as open cell (or pore) diameter and tray thickness, and of the operation conditions (such as the liquid and vapor volumetric flow rates), and the data obtained agree well with the experimental results.CONCLUSIONThe availability of such empirical correlations can be beneficial for the chemical engineering design of practical distillation processes based on SiC foam monolithic trays. © 2023 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley &amp; Sons Ltd on behalf of Society of Chemical Industry (SCI).

Analyzing drop coalescence in microfluidic devices with a deep learning generative model.

Predicting drop coalescence based on process parameters is crucial for experimental design in chemical engineering. However, predictive models can suffer from the lack of training data and more importantly, the label imbalance problem. In this study, we propose the use of deep learning generative models to tackle this bottleneck by training the predictive models using generated synthetic data. A novel generative model, named double space conditional variational autoencoder (DSCVAE) is developed for labelled tabular data. By introducing label constraints in both the latent and the original space, DSCVAE is capable of generating consistent and realistic samples compared to the standard conditional variational autoencoder (CVAE). Two predictive models, namely random forest and gradient boosting classifiers, are enhanced on synthetic data and their performances are evaluated based on real experimental data. Numerical results show that a considerable improvement in prediction accuracy can be achieved by using synthetic data and the proposed DSCVAE clearly outperforms the standard CVAE. This research clearly provides more insights into handling imbalanced data for classification problems, especially in chemical engineering.

A coupled reinforcement learning and IDAES process modeling framework for automated conceptual design of energy and chemical systems

This study introduces an advanced automated system for designing diverse chemical or electrochemical systems, requiring minimal user expertise, and enabling designing and optimization from scratch.

Virtual Reality Broken Plant Tutorial for Capstone Design

Providing student capstone teams with an opportunity to demonstrate their design competency and complete a team challenge inside a full-scale chemical processing plant provides a novel learning opportunity. A full-scale virtual reality (VR) chemical processing plant was built as an immersive learning application for the Chemical Engineering and Engineering Chemistry capstone design course at Queen’s University in Kingston. During their capstone design course, student teams are required to work on the design of an ampicillin processing facility and the VR application was designed to provide a high-fidelity representation of an operating plant, including a piping and instrumentation diagram (P&amp;ID). To examine the impact of this new VR learning tool, a broken plant exercise was designed to examine the efficacy of the application. The student cohort was divided into two groups for the exercise; paper-based, and web VR based. Each group completed several surveys and a tutorial problem. Initial quantitative results comparing the survey responses from both groups will be presented.

The Chemical Engineering Design of a Commercial Citrus Evaporator for the Production of 6,539.86 kg/hr Orange Juice Concentrate in Lagos, Nigeria, West Africa

Chemical engineers are high in importunity by industries in a wide range of sectors for the following impetus: Based on nominally defined problem statements, such as a client need or a set of experimental ramifications, chemical engineers can devise and gain a profound understanding of fundamental physical science relevant to the enigma, and harness this apprehension to excogitate a comprehensive action plan and a set of detailed specifications that, if implemented, will lead to forecasted financial dividends. In this treatise, as chemical engineers, apply our scientific and mathematical knowledge, specifically chemistry, applied mathematics, and engineering concepts, to translate experimental or conceptual ideas into value-added products in a lucrative, safe (environmentally friendly), and industry-leading manner. Citrus sinensis is the scientific name for orange, a savory and aromatic fruit from the Rutaceae family. The annual global citrus production increased dramatically over the last few decades, from around 30 million metric tonnes in the late 1960s to an estimated total of more than 105 million metric tonnes from 2000 to 2004, with oranges accounting for more than half of total global citrus production. Evaporation is a principle habituated in the processing industry to concentrate aqueous liquid streams by vaporizing the quantity of water content in a solution. The curtailment of energy consumption for evaporation reckoned on multitudinous components, such as evaporation capacity, number of effects, operation efficiency, and annual operation hours. We emphasized burgeoning efficient strategies to curtail the energy consumption of evaporators and alluded that monitoring the rate of energy dissipation guarantee the sustainability of an industrial enterprise. We betokened the heat transfer area was the indispensable criterion in the design of an evaporator and delineated correlations for estimating the size of the tube bundle. Ideally, a well-designed evaporator should be able to transfer heat adeptly at a high flow rate, have the minimum valuation of installation, operation, and maintenance, be able to bifurcate vapors from liquid concentrates, meet the conditions required by the product under treatment, produce a product of a quality required, and, if possible, be energy efficient. The peculiar grade of evaporator adopted was the 5-effect, 8-stage Thermally Accelerated Short Time Evaporator. We embraced the genre of evaporators after investigating their benefits relative to other evaporators used in food processing. In addition, it is fundamental to institute governance to identify benchmarks for optimal distribution based on results obtained by all segments of the production chains and orange juice exporters. This input will benefit the collective national interest and is pivotal for the orange juice industry.

Redox-Mediated Electrodialysis for Resource Recovery and Energy-Efficient Desalination

In the chemical and biochemical manufacturing industry, separation processes are amongst the most energy-demanding processes. Electrochemical separations have been growing in interest as promising candidates for both downstream processing for resource recovery and producing clean water due to their energy-efficient, environmentally benign, and modular features.1 Leveraging a sustainable redox reaction, we developed a redox-mediated electrodialysis system for energy-efficient desalination coupled with resource recovery of valuable resources such as lithium, and even biomolecules.2, 3 Our proposed redox-mediated electrodialysis system utilizes a reversible redox reaction as a driving force of salt removal at a much lower voltage than a water-splitting reaction (>1.2 V). As the redox materials are reduced or oxidized, all charged species migrate across the membranes to balance the charge in the electrolyte compartment. As the redox materials circulate in the cathode and anode compartments, they sustainably regenerated without additional regeneration steps, one of the major bottlenecks for industrializing the electrosorption system. We demonstrated the redox-mediated electrochemical system for resource recoveries such as simultaneous lithium recovery from brine3 and valorization of whey proteins and lactose from whey waste.2 Especially for the valorization of whey waste, our system treated 99% of salt from the whey solution within a single step and recovered > 98% of various whey proteins (e.g., valuable protein contents such as beta-lactoglobulin, alpha-lactalbumin, and lactose). The preliminary techno-economic analysis confirmed the economic potential of redox-mediated ED with 51−73% lower energy consumption compared to conventional ED. Overall. we envision the system can become a breakthrough in tackling the environmental challenges coupled with the limited resources. Kim, N.; Jeon, J.; Chen, R.; Su, X., Electrochemical separation of organic acids and proteins for food and biomanufacturing. Chemical Engineering Research and Design 2022, 178, 267-288.Kim, N.; Jeon, J.; Elbert, J.; Kim, C.; Su, X., Redox-mediated electrochemical desalination for waste valorization in dairy production. Chemical Engineering Journal 2022, 428, 131082.Kim, N.; Su, X.; Kim, C., Electrochemical lithium recovery system through the simultaneous lithium enrichment via sustainable redox reaction. Chemical Engineering Journal 2021, 420, 127715.

Artificial neural networks modeling ethanol oxidation reaction kinetics catalyzed by polyaniline-manganese ferrite supported platinum-ruthenium nanohybrid electrocatalyst

The electrochemical and physicochemical properties of the anode catalyst used in alcohol fuel cells affect the efficiency of the fuel cell due to both its effect on the cell potential and its direct relationship with the reaction stoichiometry. It is possible to determine these parameters from polarization curves (current vs. cell potential) of the cells. At low potentials, Tafel plots offer kinetic information, whereas currents at high potentials reveal the average number of electrons released per ethanol molecule and their potential dependency. Herein, bearing the chemical engineering research and design aspects, it was aimed to model the kinetics of ethanol electrooxidation reaction catalyzed by PANI-MnFe2O4/Pt/Ru nanocomposite by an artificial neural network (ANN) approach, specifically by Differential Evolution (DE) algorithm for the first time. The different parts of the Tafel plots were condensed into a single and efficient model to illustrate the generalization potential of ANN. The findings demonstrated that the best model with a single hidden layer with 18 neurons offered the highest correlation metrics of 0.997476, and the lowest mean-square-error value of 0.000428 at the testing phase. Furthermore, the average absolute error was calculated, with 0.773% in the training phase and 0.66% in the testing phase. These outstanding results indicated that the best model is capable of accurately capturing the dynamics of all instances analyzed.

Crustacean waste biorefinery as a sustainable cost-effective business model

Marine-derived food wastes mainly include seafood, fish and feed production resources. From the crustaceans traded annually, 6 to 8 million tonnes of valuable shrimp, lobster and/or crab shells waste are produced worldwide. In this systemic work, the researchers with complementary technical expertise, covering the fields of chemical engineering design, chemistry, materials, predictive environmental sciences and economy, worked together to develop a sustainable multiproduct pipeline for the biorefinery of unwanted by-products. All process bio-products from the shells waste were recovered, separated, and purified. Only harmless solvents, namely water, the protonating acetic acid under mild functional conditions and buffers, conjugated with solid–liquid extraction, centrifugation, and membrane ultrafiltration technologies were applied. Here, a success business model is shown after its standardised evaluation in terms of purification performance, economic impact, and life cycle assessment has been performed, driving this sector towards a sustainable ocean-based economy.

An overview of the effect of stirrer design on the mechanical properties of Aluminium Alloy Matrix Composites fabricated by stir casting

An overview of the effect of stirrer design on the mechanical properties of Aluminium Alloy Matrix Composites fabricated by stir casting