Chemical Engineering Literature Research Articles

ACS members honored with AIChE awards

Members of the American Chemical Society were recognized by the American Institute of Chemical Engineers (AIChE) at its 2022 annual meeting. Liang-Shih Fan , a Distinguished University Professor, C. John Easton Professor in Engineering, and professor of chemical and biomolecular engineering at the Ohio State University, received the Warren K. Lewis Award for Chemical Engineering Education. Timothy J. Hebrink , a senior staff scientist at 3M, received the Energy and Sustainability Award. Cato T. Laurencin , the University Professor and Albert and Wilda Van Dusen Distinguished Endowed Professor of Orthopaedic Surgery at the University of Connecticut, received AIChE’s highest honor, the Founders Award for Outstanding Contributions to the Field of Chemical Engineering. Eleftherios “Terry” Papoutsakis , the Unidel Eugene du Pont Professor at the University of Delaware, received the William H. Walker Award for Excellence in Contributions to Chemical Engineering Literature. Christopher J. Pope , an independent chemical engineering researcher

Global Solution of Semi-infinite Programs with Existence Constraints

We consider what we term existence-constrained semi-infinite programs. They contain a finite number of (upper-level) variables, a regular objective, and semi-infinite existence constraints. These constraints assert that for all (medial-level) variable values from a set of infinite cardinality, there must exist (lower-level) variable values from a second set that satisfy an inequality. Existence-constrained semi-infinite programs are a generalization of regular semi-infinite programs, possess three rather than two levels, and are found in a number of applications. Building on our previous work on the global solution of semi-infinite programs (Djelassi and Mitsos in J Glob Optim 68(2):227–253, 2017), we propose (for the first time) an algorithm for the global solution of existence-constrained semi-infinite programs absent any convexity or concavity assumptions. The algorithm is guaranteed to terminate with a globally optimal solution with guaranteed feasibility under assumptions that are similar to the ones made in the regular semi-infinite case. In particular, it is assumed that host sets are compact, defining functions are continuous, an appropriate global nonlinear programming subsolver is used, and that there exists a Slater point with respect to the semi-infinite existence constraints. A proof of finite termination is provided. Numerical results are provided for the solution of an adjustable robust design problem from the chemical engineering literature.

Experimental methods in chemical engineering: Electron paramagnetic resonance spectroscopy‐EPR/ESR

SummaryElectron paramagnetic resonance (EPR) spectroscopy, also known as electron spin resonance spectroscopy (ESR), utilizes absorption of microwave radiation by unpaired electrons in a magnetic field. The interaction between the unpaired electron(s) and nearby magnetic nuclei helps identify paramagnetic species and can provide information about the motion of the molecule and the local polarity, pH, viscosity, concentration, and accessibility to other paramagnetic species. This mini‐review discusses the fundamental underpinnings of EPR needed to correctly interpret EPR spectra. We describe various types of EPR spectra encountered by chemical engineers, and use application examples drawn from the chemical engineering literature to illustrate the information available from the technique. Few chemical engineering departments or even chemistry departments have EPR instruments, which contributes to the significant barrier that prevents this being adopted as a routine measurement technique. However, in 2016 and 2017, Web of Science indexed 7000 articles that applied EPR spectroscopy. A bibliometric map categorized the keywords in four categories based on co‐occurrences: magnetic properties, films, and luminescence; crystal structure, complexes, and ligands; nanoparticles, oxidation, and degradation; and, systems, radicals, and H2O2.

A simultaneous approach for singular optimal control based on partial moving grid

AbstractSingular optimal control plays an important role in process engineering, including optimal operation of batch and semi‐batch reactions. However, for many practical applications, accurate solution of singular optimal control profiles is still an open issue. In particular, numerical optimization must deal with an ill‐conditioned problem that often leads to very slow convergence or failure. Starting from the nested approach in our previous work in 2016, this study develops a more efficient strategy for singular control through a heuristic approach for the outer problem. The approach includes three stages. Starting from a coarse distribution of finite elements, sufficiently many finite elements are inserted where control profiles are steep and fixed gridpoints are inserted on the basis of error estimation of state profiles. Then, moving gridpoints are inserted where the modified switching function is violated. Initial junctions are obtained by moving the latest inserted gridpoints. Moreover, further mesh refinements are considered based on switching point detection and a moving grid point update strategy, until modified switching conditions are satisfied over the whole‐time span. A key feature of this approach is that only a subset of finite elements needs to move during optimization. Complexity of the optimization formulation is considerably decreased compared to our previous work. This approach is demonstrated on eight classical singular control problems with known solutions, as well as six complex singular control problems drawn from the chemical engineering literature.

A microscopic computer vision algorithm for autonomous bubble detection in aerated complex liquids

The size distribution of bubbles in cake batters is often determined from optical microscopic imaging, considering the lesser availability and non-affordability of sophisticated techniques such as light scattering, and acoustic methods. We present an automated bubble detection and counting method from microscopic images that presents flexibility and robustness over existing manual approaches. The method is able to successfully resolve connected bubbles and recognise far many bubbles in an image than would be possible by naked eye or hitherto reported methods in chemical and food engineering literature. Furthermore, the size data obtained for the bubbles can easily be used for routine statistical analysis. We demonstrate the application of our method for studying the influence of two different mixer geometries and three different speeds on bubble size.

Identifying “best bets” for searching in chemical engineering

PurposePerforming efficient literature searches and subscribing to the most comprehensive databases for interdisciplinary fields can be challenging since the literature is typically indexed in numerous databases to different extents. Comparing databases will help information professionals make appropriate choices when teaching, literature searching, creating online subject guides, and deciding which databases to renew when faced with fiscal challenges. The purpose of this paper is to compare databases for searching the chemical engineering literature.Design/methodology/approachThis paper compares journal indexing and search recall across seven databases that cover the chemical engineering literature in order to determine which database and database pair provide the most comprehensive coverage in this area. It also summarizes published, database comparison methods to aid information professionals in undertaking their own comparative assessments.FindingsSciFinder, Scopus, and Web of Science, listed alphabetically, were the leading databases for searching the chemical engineering literature. SciFinder-Scopus and SciFinder-Web of Science were the top two database pairs. No single database or pair provided 100 percent complete coverage of the literature examined. Searching a second database increased the recall of results by an average of 17.6 percent.Practical implicationsThe findings are useful since they identify “best bets” for performing an efficient search of the chemical engineering literature. Information professionals can also use the methods discussed to compare databases for any discipline or search topic.Originality/valueThis paper builds on the previous literature by using a dual approach to compare the coverage of the chemical engineering literature across multiple databases. To the author’s knowledge, comparing databases in the field of chemical engineering has not been reported in the literature thus far.

Exploring Citations in Chemical Engineering Literature Review

Citation is considered as an essential part in any academic writing whereby it is one way for writers to support any claims or arguments made in their study with literature from previous research. Literature review is known as a chapter which provides background for research described in a thesis. However, relatively not many studies are done on literature review chapter of thesis which may be due to the extensive nature of the text. Writing academic texts such as a thesis requires an author to acknowledge other researchers’ work through proper use of citations. Learning the appropriate way to cite is important in any kinds of academic writing especially among research students who are writing their theses. Therefore, the main aim of this study is to investigate the citation practices in doctoral theses of Chemical Engineering. The purpose of this study is two folds; i) to identify the types of citations used in the corpus (using Swale's 1990 categorization) and ii) to examine the functions related to the citations used (using Thompson's 2001 framework). Three literature review chapters were analysed first to identify the types of citations used in the mini corpus and the functions related to the citations. The results of the study show that engineering student writers mostly used Non-integral citations as compared to Integral. The study concludes with a discussion on the skills of citing the literature which should be given more attention to raise the awareness level among students.

Application and Analysis of Methods for Selecting an Optimal Solution from the Pareto-Optimal Front obtained by Multiobjective Optimization

Process optimization often has two or more objectives which are conflicting. For such situations, multiobjective optimization (MOO) provides many optimal solutions, which are equally good from the perspective of the given objectives. These solutions, known as Pareto-optimal front and as nondominated solutions, provide deeper insights into the trade-off among the objectives and many choices for implementation. In the past 20 years, researchers have applied MOO to numerous applications in chemical engineering. However, selection of an optimal solution from the set of nondominated solutions has not received much attention in the chemical engineering literature. In the present study, 10 methods for selecting an optimal solution from the Pareto-optimal front are carefully chosen and implemented in an MS Excel-based program. Then, they are applied to the selection of an optimal solution in many benchmark or mathematical problems and chemical engineering applications, and their effectiveness and similarities are...

An adaptive parallel tempering method for the dynamic data‐driven parameter estimation of nonlinear models

An adaptive parallel tempering algorithm is developed in a user‐friendly fashion that efficiently and robustly generates near‐optimum solutions. Using adaptive, implicit, time‐integration methods, the method allows fitting model parameters to dynamic data. The proposed approach is relatively insensitive to the initial guess and requires minimal fine‐tuning: most of the algorithm parameters can be determined adaptively based on the analysis of few model simulations, while default values are proposed for the few remaining ones, the exact values of which do not sensitively affect the solution. The method is extensively validated through its application to a number of algebraic and dynamic global optimization problems from Chemical Engineering literature. We then apply it to a multi‐parameter, highly nonlinear, model of the rheology of a thixotropic system where we show how the present approach can be used to robustly determine model parameters by fitting to dynamic, large amplitude, oscillatory stress vs. shear rate, data. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1937–1958, 2017

Introduction to a Special Issue on Molecular Computer Simulations of Clays and Clay-Water Interfaces: Recent Progress, Challenges, and Opportunities

Over recent years, a steady increase has been noted in the publication of research articles in Clays and Clay Minerals which have included the use of molecular simulation methods. Based on a keyword search of Web of Science , the number of molecular simulation papers has increased from zero during the first four decades of the journal to five during the late 1990s, to 14 in the 2000s, to 36 so far in the 2010s including those published in this special issue. Most research papers using computational molecular modeling approaches to study the properties of clays and clay-related systems and their practical applications are published in the broader materials science and chemical engineering literature. The clay-minerals community has taken quite a long time to embrace the technical insights associated with using a molecular modeling approach. Not only does a molecular basis help to develop and test crystallographic models of clay structures, it provides critical insight into understanding the fundamental mechanisms that control many physical and chemical properties, thermodynamics, kinetic processes, and reactivity. Molecular simulations help in the interpretation of spectroscopies and microscopies, and in many other critical issues associated with the behavior and dynamics of clay mineral systems. Though clearly not a panacea for all technical challenges in clay mineralogy, molecular models and simulations provide a solid theoretical context to enable us to delve deeper into the fundamental …

A review of the statistical turbulence theory required extending the population balance closure models to the entire spectrum of turbulence

The models for fluid particle breakage and coalescence due to turbulence are generally limited to the inertial subrange of isotropic turbulence and infinite Reynolds numbers. A rigorous procedure for extending the fluid particle breakage and coalescence closures to the entire spectrum of isotropic turbulence and for a wider range of Reynolds numbers can be established based on statistical turbulence theory. The modeling procedure consists of a three‐dimensional (3‐D) literature model energy spectrum for the dissipation, inertial, and energy containing subranges of isotropic turbulence, and an exact literature integral relation for determining the second‐order longitudinal structure function from the 3‐D energy spectrum. A review of the requisite statistical turbulence theory and the use of the model energy spectrum is provided, because the necessary details are not easily accessible in the chemical engineering literature and misconceptions are found in the publications of the previous modeling attempts. © 2016 American Institute of Chemical Engineers AIChE J, 62: 1795–1820, 2016

Phase Stability Analysis and Phase Equilibrium Calculations in Reactive and Nonreactive Systems Using Charged System Search Algorithms

Stochastic global optimization algorithms have shown promise in providing reliable and efficient solutions for phase stability and phase equilibrium problems in reactive and nonreactive systems. A special class of stochastic methods is Swarm Intelligence, in which search agents are allowed to interact with each other and with their environment and benefit from their peers in their collective pursuit for the global minimum, resulting in an intelligent behavior unknown to the individual agents. Of special interest are swarm intelligence methods with less tunable algorithm parameters, which allow for easy and user-friendly implementation. In particular, this study introduces the Charged System Search, a novel swarm intelligence method, as a global optimization tool to the Chemical Engineering literature via implementing it, for the first time, in solving phase stability and equilibrium problems. Two Charged System Search variants have been employed, namely, the Magnetic Charged System Search and the hybrid version with Particle Swarm Optimization. This hybrid method is coupled with chaotic maps to overcome the local optimum entrapment and to aid its exploration capability. Results indicate that these two variants generally outperformed the Charged System Search, especially the hybrid chaotic algorithm. Results of this study were also compared to those reported for other swarm intelligence methods applied in phase equilibrium calculations. In summary, this study introduces novel swarm intelligence methods for performing phase stability and equilibrium calculations in both reactive and nonreactive systems.

A bilevel NLP sensitivity‐based decomposition for dynamic optimization with moving finite elements

Optimal control has guided numerous applications in chemical engineering, and exact determination of optimal profiles is essential for operation of separation and reactive processes, and operating strategies and recipe generation for batch processes. Here, a simultaneous collocation formulation based on moving finite elements is developed for the solution of a class of optimal control problems. Novel features of the algorithm include the direct location of breakpoints for control profiles and a termination criterion based on a constant Hamiltonian profile. The algorithm is stabilized and performance is significantly improved by decomposing the overall nonlinear programming (NLP) formulation into an inner problem, which solves a fixed element simultaneous collocation problem, and an outer problem, which adjusts the finite elements based on several error criteria. This bilevel formulation is aided by a NLP solver (the interior point optimizer) for both problems as well as an NLP sensitivity component, which provides derivative information from the inner problem to the outer problem. This approach is demonstrated on 11 dynamic optimization problems drawn from the optimal control and chemical engineering literature. © 2014 American Institute of Chemical Engineers AIChE J, 60: 966–979, 2014

A new model for bubbling fluidized bed reactors

Various mathematical models have been proposed in the past for estimating the conversions of reactant gases in fluidized bed reactors. A new mathematical model is being proposed in this paper that gives relatively better results compared to the prevailing models for bubbling fluidized bed reactors utilizing Geldart B particles. The new model is named as JSR (Jain, Sathiyamoorthy, Rao) model and it is a modified version of bubble assemblage model of Kato and Wen (1969). This paper discusses the development of JSR model and its verification by using data from chemical engineering literature on fluidization and also experimental data from hydrochlorination of silicon in a fluidized bed reactor. The new model is tested for five processes having operating temperatures from 130°C to 450°C, operating velocities from 0.019ms−1 to 0.19ms−1 and solid particle sizes from 65 to 325 mesh.

ChemInform Abstract: Development and Evaluation of Porous Materials for Carbon Dioxide Separation and Capture

AbstractReview: 92 refs.

Development and Evaluation of Porous Materials for Carbon Dioxide Separation and Capture

The development of new microporous materials for adsorption separation processes is a rapidly growing field because of potential applications such as carbon capture and sequestration (CCS) and purification of clean-burning natural gas. In particular, new metal-organic frameworks (MOFs) and other porous coordination polymers are being generated at a rapid and growing pace. Herein, we address the question of how this large number of materials can be quickly evaluated for their practical application in carbon dioxide separation processes. Five adsorbent evaluation criteria from the chemical engineering literature are described and used to assess over 40 MOFs for their potential in CO(2) separation processes for natural gas purification, landfill gas separation, and capture of CO(2) from power-plant flue gas. Comparisons with other materials such as zeolites are made, and the relationships between MOF properties and CO(2) separation potential are investigated from the large data set. In addition, strategies for tailoring and designing MOFs to enhance CO(2) adsorption are briefly reviewed.

Solid–solid reaction in a fluidized bed

AbstractSolid–solid reactions, although of considerable industrial importance, have not received significant attention in the chemical engineering literature. In conventional method of manufacturing products using reactants in solid phase, the rate of heat transfer and rate of diffusion are very slow. In order to overcome these problems, an attempt is made to investigate these reactions employing a stirred fluidized bed. The addition reaction of phthalic anhydride and p‐nitro aniline system that takes place between 80 and 120 °C, forming phthaloyl derivative of p‐nitro aniline is selected for the investigations. The reaction is conducted in a stainless steel column of 0.1 m diameter and 1‐m height. The variables considered are reaction temperature, stirrer speed, flow rate of fluidizing medium, and static bed height. Experiments are performed using statistically designed factorial experiments. Data are used to find the model suitable to the mechanism of the reaction. Mathematical equations relating reaction parameters viz., steady state conversion, time for steady state conversion, reaction rate constant, and activation energy with operating variables are developed and activation energy is reduced from 14 kcal/mol reported in literature to less than 5.3 kcal/mol depending on operating conditions. The concept could be adopted for the manufacture of cement, and other materials with required modifications of experimental setup. Copyright © 2010 Curtin University of Technology and John Wiley & Sons, Ltd.

Review of Life Cycle Assessment in Agro-Chemical Processes

Life Cycle Assessment (LCA) is a method used to evaluate the potential impacts on the environment of a product, process, or activity throughout its life cycle. Today’s LCA users are a mixture of individuals with skills in different disciplines who want to evaluate their products, processes, or activities in a life cycle context. This study attempts to present some of the LCA studies on agro-chemical processes, recent advances in LCA and their application on food products and non-food products. Due to the recent development of LCA methodologies and dissemination programs by international and local bodies, use of LCA is rapidly increasing in agricultural and industrial products. The literatures suggest that LCA coupled with other environmental approaches provides much more reliable and comprehensive information to environmentally conscious policy makers, producers, and consumers in selecting sustainable products and production processes. For this purpose, a field study of LCA of biodiesel from Jatropha curcas has been taken as an example in the study. In the past, LCA has been applied primarily to products but recent literature suggests that it has also the potential as an analysis and design tool for processes and services. In general, all primary industries use energy and water resources and emit pollutants gases. LCA is a method to report on and analyze these resource issues across the life cycle of agro-chemical processes. This review has the importance as a first part of a research project to develop a life cycle assessment methodology for agro-chemical industries. It presents the findings of a literature review that focuses on LCA of agriculture and chemical engineering literature.

The continuum mechanical theory of multicomponent diffusion in fluid mixtures

The continuum mechanical approach for deriving the generalized equations of multicomponent diffusion in fluids is described here in detail, which is based on application of the principle of linear momentum balance to a species in a mixture, resulting in the complete set of diffusion driving forces. When combined with the usual constitutive equations including the continuum friction treatment of diffusion, the result is a very complete and clear exposition of multicomponent diffusion that unifies previous work and includes all of the various possible driving forces as well as the generalized Maxwell–Stefan form of the constitutive equations, with reciprocal diffusion coefficients resulting from Newton’s third law applied to individual molecular encounters. This intuitively appealing and rigorous approach, first proposed over 50 years ago, has been virtually ignored in the chemical engineering literature, although it has a considerable following in the mechanical engineering literature, where the focus, naturally, has been physical properties of multiphase fluid and solid mixtures. The described approach has the advantages of transparency over the conventional approach of non-equilibrium thermodynamics and of simplicity over those based on statistical mechanical or kinetic theory of gases or liquids. We provide the general derivation along with some new results in order to call attention of chemical engineers to this comprehensive, attractive, and accessible theory of multicomponent diffusion in fluids.

Hydrate formation and re-formation in nucleating THF/water mixtures show no evidence to support a “memory” effect

There are many reports in the chemical engineering literature citing a ‘memory’ effect in association with nucleation of clathrate hydrates. Some researchers appeal to this memory effect in order to explain the apparent reduction in induction time for hydrates formed repetitively from supercooled solutions. It is suggested that for various species of clathrate in liquid–liquid or gas–liquid systems, such as THF/water, CO 2/water and hydrocarbon gas/water, the ‘memory’ effect results from water which is obtained from melted hydrates possessing a “modified” structure which allows easier hydrate re-formation. We provide here data from several series of measurements of the stochastic nature of THF–water hydrate formation using an automatic lag time apparatus. Our data supports the existing molecular understanding of nucleation and does not require any appeal to a memory effect.