We report mesoporous Co‐Al oxide nanosheets (CoxAl‐Ns, where x denotes the Co/Al ratio in the samples) prepared by calcination of CoAl‐hydrotalcite and subsequent alkaline treatment. X‐ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X‐ray photoelectron spectroscopy (XPS) measurements show that the prepared Co‐Al oxide nanosheets (CoxAl‐Ns) are very thin (10–15 nm) and exhibit high mesoporosity (3–5 nm). Catalytic CO oxidation tests reveal that the CoxAl‐Ns exhibit excellent catalytic performances at relatively low temperatures: for example, the Co2.5Al‐Ns catalyst could achieve 99% CO conversion at −98°C. Kinetic studies and experimental investigations indicate that the high activity of the Co2.5Al‐Ns sample is strongly related to the abundance of active sites associated with the large BET (Brunauer–Emmett–Teller) surface area. The Co2.5Al‐Ns catalyst also achieves full conversion of CO in tests performed with a gas mixture simulating automobile exhaust gas at 200°C. After loading the Co2.5Al‐Ns on a porous ceramic (PC) substrate, the obtained Co2.5Al‐Ns/PC shows high activity and stability in CO oxidation process. These features are potentially important for future industrial applications of these catalysts.

Metal sulfide catalysts for ultra‐deep hydrodesulfurization of diesel generally lose a fraction of their catalytically active sites during reactor startup. The underlying mechanisms are discussed. A laboratory diagnostic tool consisting of three probe molecules is developed for testing metal sulfide catalysts’ start‐of‐run (SOR) activity maintenance. It is found that a significant fraction of the active sites on a commercial supported catalyst are deactivated permanently, but this is not the case with a bulk metal sulfide catalyst. The SOR deactivation of the bulk catalyst is completely reversible, while that of the supported catalyst is partially reversible. The diagnostic tool may provide a basis for developing a high‐throughput approach for evaluating and enhancing catalyst SOR stability, thereby increasing plant productivity.

In 2016, we introduced the concept of model‐predictive safety (MPS) 1. MPS is a proposed innovation in functional safety systems to methodically account for process nonlinearities and variable interactions to enable predictive, prescriptive actions, while existing functional safety systems generally react when individual process variables exceed thresholds. MPS systematically utilizes a dynamic process model to detect imminent and potential future operation hazards in real time and to take optimal preventive and mitigative actions proactively. This work formulates two min‐max optimization problems, offline solutions of which are the optimal proactive preventive and mitigating actions that an MPS system should take online, in response to predicted process operation hazards. A nested particle swarm optimization (PSO) algorithm is proposed to solve the min‐max optimization problems. The application and performance of the min‐max optimization formulations, the PSO algorithm, and MPS, applied to two chemical process examples, are shown through numerical simulations.

Multimetallic nanocatalysts have attracted increasing attention for steam reforming owing to highly exposed active sites, but often suffering from severe sintering. Herein, we design subnanometric Ni‐Pt bimetal clusters (ca. 1.7 nm) encapsulated in Silicalite‐1 zeolite (2Ni0.5Pt@S‐1) through ligand‐stabilized method to prevent sintering by fixing the metal into microporous channels. In the steam reforming of n‐dodecane test, 2Ni0.5Pt@S‐1 gave an excellent activity and stability with a decrease of conversion only 4% at 600°C for 4 hr, which was about a quarter that of 2Ni0.5Pt/S‐1 synthesized by co‐impregnation method, ascribing to superior sinter‐resistance of encapsulation structure. Moreover, 2Ni0.5Pt@S‐1 exhibited a higher H2 selectivity up to 69.9% than that of 2Ni0.5Pt/S‐1 (64.4%), owing to suppressed methanation reaction based on subnanometric clusters. Shape‐selective steam reforming of n‐dodecane and ofm‐xylene was also observed, because of m‐xylene could hardly diffuse into the zeolite channels due to its bulky molecular size, further preventing potential deactivation by tars in reforming process.

Electrostatic potential in the multizone circulating fluidized bed (CFB) reactor for polypropylene is measured even larger than 1,000 V. In this article, electrostatic effects on hydrodynamics in the riser of CFBs were studied via experiment and computational fluid dynamic simulation. Experimental results showed electrostatics increased solids holdup in the riser for more than 20% in fast fluidization. Using measured charge densities as electrostatic model parameters, electrostatic effects were simulated by two‐fluid model coupled with electrostatics accurately. The relative deviation between measured and simulated solids holdup was 3.53% at 5.68 m/s, which was the first time that this mode was verified quantitatively. Further analysis of simulation results demonstrated the mechanism of electrostatic effects was that the electrostatic forces increased the radial particle velocity and induced particle accumulation near the wall, leading to the increase of solids holdup. These electrostatic effects are more significant in the dense‐phase region, which require special care.

The hydrodynamic cavitation multiphase reactor (HCMR) is emerging as a promising alternative for the intensification of liquid–liquid heterogeneous reactions, but research on HCMR modeling is lacking. In this article, an HCMR model was developed using Prileschajew epoxidation as the model system. First, based on experimental measurements of oil/water two‐phase flow downstream of hydrodynamic cavitation devices, semiempirical correlations were proposed to describe the droplet size and droplet size distribution (DSD) as functions of flow conditions and geometry parameters. Then, with boundary conditions calculated by the DSD correlation, a droplet dynamics simulation in a reaction tank was performed by computational fluid dynamics coupled with population balance model to obtain the two‐phase interfacial area. Finally, the acquired reactor model was substituted into an overall kinetic model, to simulate the epoxidation reaction in HCMR. Model predictions were verified by experimental results measured on an industrial scale HCMR.

This study provides an extension to previously published articles on measurements and computational fluid dynamic (CFD) modeling and simulations of airflow across “bottleneck‐type” structures in the Forchheimer regime to purely inertial‐neglected (Darcy regime) incompressible flowing fluid via tomography datasets. A linear‐dependent relationship between the CFD computed unit pressure drop developed across the samples and the superficial fluid inlet velocity was observed for all the samples for creeping fluid flow (0–7 × 10−03m·s−1). The permeability of the structures was observed to be dependent on the structural parameters of the porous medium and most importantly, its pore diameter openings. Linear graphical relations between permeability and pore‐structure related properties of these materials were observed and these could assist in minimizing the number of design iterations needed for the processing of self‐supporting porous metals.

Cells in a genetically homogeneous cell‐population exhibit a significant degree of heterogeneity in their responses to an external stimulus. To understand origins and importance of this heterogeneity, individual‐based population model (IBPM), where parameters follow probability density functions (PDF) instead of being constants, has been previously developed. However, parameter identification for an IBPM is challenging as estimating PDFs is computationally expensive. Also, because of experimental limitations and nonlinearity of models, not all parameters PDFs are identifiable. Motivated by the above considerations, a new methodology is proposed in this study. First, a subset of parameters whose PDFs is identifiable are determined through sensitivity analysis, and only these PDFs are estimated. Second, an artificial neural network model is developed to find an empirical relation between these parameter and output PDFs to reduce computational costs of the parameter identification. The proposed approach is validated by estimating PDFs of parameters of a TNFαsignaling model.

We propose a systematic approach for generating alternative production schedules to address two challenges in implementing optimization‐based scheduling techniques in industrial settings: (i) the limited scope of the scheduling models due to modeling simplifications, and (ii) the consideration of shop‐floor nervousness. We first introduce metrics to quantify specific characteristics of a schedule (e.g. number of batches and degree of nervousness). Next, we favor, at different degrees, such characteristics in each alternative schedule, by penalizing the metrics in the objective function. Through illustrative instances, we show that multiple alternative schedules, including the schedules with desired properties can readily be generated.

In this paper we developed a pore‐scale model of integrated lattice Boltzmann method and Cellular Automata (LBM‐CA) to investigate competitive growth of aerobic nitrite and ammonium oxidizers in a bioreactor. The results showed that inlet nutrient concentrations have significant effects on maximum biofilm concentration, ratio of microorganisms’ concentrations, growth pattern and time. The local availability of oxygen could control the competition, resulting in different growth patterns. The coexistence of ammonium and nitrite in same inlet zone increased not only the biofilm concentration (7%) but also the ratio of microorganisms’ concentrations (36%). Although this coexistence decreased the total biofilm concentration in some cases, it increased the growth rate about 25%. Changes of the maximum biomass concentration could change biofilm concentration of about 40% and microorganisms’ concentrations ratio of about 30%. This framework provides a powerful tool to improve our understanding of dynamic interdependency of many complex microbial consortia systems with environments.

A trust‐region approach is presented to address the simultaneous design and control of large‐scale systems under uncertainty. The key idea is to represent the system using power series expansions (PSEs) as piecewise models in an iterative manner while the validity of those expansions is certified in a trusted region. The mean of squared errors is used as a metric to quantify the accuracy of the PSE approximations. Identified search regions specify the boundaries of the decision variables for the PSE‐based optimization problems. The proposed algorithm shows a significant accomplishment in locating dynamically feasible and near‐optimal design and operating conditions. The proposed approach was tested in a wastewater treatment plant and the Tennessee Eastman (TE) process. The results indicate that the proposed methodology leads to more economically attractive and reliable designs while maintaining the dynamic operability of the system in the presence of disturbances and uncertainty.

This work deals with estimating the dominant size enlargement mechanism in spray fluidized beds. A new process model is presented, which consists of population balances and a heat and mass transfer model. New methods to incorporate the wet surface fraction and the Stokes criterion are proposed, which allow for the probability of wet collisions and the probability of successful wet collisions to be calculated. The product of these parameters, the probability of successful collisions, is linked to the dominant size enlargement mechanism. Simulation studies were performed to investigate the influence of inlet gas temperature, viscosity, droplet size, and contact angle on the probability of successful collisions. Further simulation results based on experiments available in literature suggest that exceeding a probability of successful collisions of 0.001 is sufficient for agglomeration to become dominant. Otherwise, layering will be the dominant size enlargement mechanism. Finally, regime maps of layering and agglomeration are constructed.

A binary mixture is mixed in a rotating drum composed by 19 rings with different inner diameters. It is found that the larger particles are concentrated in the rings with smaller inner diameters. The collection of the larger particles in these rings is due to the particle dynamic angle of repose. The transition from the particle segregation core pattern at the end wall to the good radial mixing rings is through a transient turning comet segregation pattern. This transition is closely related to the distance from the ring with the smallest inner diameter to the ring with the largest inner diameter. Having a higher fraction of larger particles in a ring requires both the collection ring having a smaller inner diameter and a smoother inner diameter transition to the neighboring rings.

Fast pyrolysis is a promising technology to convert biomass to renewable biofuels. In our prior work, hydrodeoxygenation kinetics of guaiacol, a well‐known model compound of bio‐oil, over Pt/AC (activated carbon) catalysts were investigated under integral operating conditions. It was found that the pseudo‐homogeneous plug‐flow model utilizing these kinetics describes the experimental observations well (with normalized RMS error = 7.6%). In the presen work, under differential operating conditions instead, we refine the kinetic model for the same reaction network over the same catalyst. The comparison between experimental and predicted values for both the prior and new sets of data is excellent and even better than our prior model (with reduced normalized RMS error = 4.2%). The present work demonstrates that kinetic expressions and parameters obtained from a gradientless differential reactor are more reliable.

Free surface granular flows in bounded axisymmetric geometries are poorly understood. Here, we consider the kinematics and segregation of size‐bidisperse flow in a rising conical heap by characterizing the flow of particles in a wedge‐shaped silo with frictional sidewalls using experiments and discrete‐element‐method simulations. We find that the streamwise velocity is largest at the wedge centerline and decreases near the sidewalls, and that velocity profiles in the depthwise and spanwise directions are self‐similar. For segregating size bidisperse mixtures, the boundary between small and large particles deposited on the heap is significantly further upstream at the sidewalls than at the centerline, indicating that measurements taken at transparent sidewalls of quasi‐2D or wedge‐shaped heaps are unrepresentative of an axisymmetric heap. The streamwise velocity and flowing layer depth locally satisfy the scaling relation of Jop et al (J Fluid Mech. 2005;541:167‐192) when modified to account for the wedge geometry, highlighting the influence of wall friction on the flow.

The key to many chemical and energy conversion processes is the choice of the right molecule, for example, used as working fluid. However, the choice of the molecule is inherently coupled to the choice of the right process flowsheet. In this work, we integrate superstructure‐based flowsheet design into the design of processes and molecules. The thermodynamic properties of the molecule are modeled by the PC‐SAFT equation of state. Computer‐aided molecular design enables considering the molecular structure as degree of freedom in the process optimization. To consider the process flowsheet as additional degree of freedom, a superstructure of the process is used. The method results in the optimal molecule, process, and flowsheet. We demonstrate the method for the design of an organic Rankine cycle considering flowsheet options for regeneration, reheating, and turbine bleeding. The presented method provides a user‐friendly tool to solve the integrated design problem of processes, molecules, and process flowsheets.

A linear stability analysis of a three‐dimensional shear‐imposed fluid flowing down an inclined plane is studied based on the evolution equations for normal velocity and normal vorticity components. Both modal and nonmodal stability analyses are carried out. The modal stability analysis demonstrates that shear‐imposed flow is more unstable to solo streamwise perturbation. On the contrary, the nonmodal stability analysis demonstrates that shear‐imposed flow is more unstable to solo spanwise perturbation. There is evidence of existing transient energy growth in the wavenumber space that intensifies in the presence of imposed shear stress. Further, the boundary for the zone of transient growth appears far ahead of the boundary for the zone of exponential growth. This fact indicates that the onset of instability for the shear mode may occur before than that predicted from the eigenvalue analysis. A new critical surface parameter involving imposed shear stress is determined, which in fact reveals the existence criterion of instability for the surface mode. Moreover, we have found three different regimes of surface mode instability, shear mode instability, and transient growth phenomenon in the wavenumber space. The unstable region for the surface mode reduces while the unstable region for the shear mode enhances in the wavenumber space with the increasing value of surface parameter, or equivalently, with the increasing value of imposed shear stress. Finally, the unstable region for the surface mode disappears from the wavenumber space as soon as the surface parameter exceeds its critical value; instead, the wavenumber space is occupied by the regime of transient energy growth. In addition, the incident of pseudoresonance takes place on the response curve to external harmonic forcing.

Nowadays, the droplet–particle collision characteristics in the gas‐phase ethylene polymerization process are still unclear. The high‐speed photography and a quasi‐circle imaging approach are employed to study the collision interaction characteristics between liquid droplets and polyethylene particles. The liquid film evolution is studied through variations of the film thickness on the particle north pole, the dynamic contact angle, center angle and film thickness at the maximum extension. Results have found that for n‐hexane the threshold temperature of the recoil happening increases with increasing initial Weber number, but for 1‐hexene it is stable. Over 70°C evaporation and splash occurs immediately. Under low Weber numbers, the water droplet stays for damping oscillations, the reference stable height of which is linearly related to temperatures. Moreover, three regimes of film thickness variation with time are identified and mathematically described, while Regime 3 characteristics are found strongly dependent on the liquid species, Weber number, and particle temperature.

This work presents a detector‐integrated two‐tier control architecture capable of identifying the presence of various types of cyber‐attacks, and ensuring closed‐loop system stability upon detection of the cyber‐attacks. Working with a general class of nonlinear systems, an upper‐tier Lyapunov‐based Model Predictive Controller (LMPC), using networked sensor measurements to improve closed‐loop performance, is coupled with lower‐tier cyber‐secure explicit feedback controllers to drive a nonlinear multivariable process to its steady state. Although the networked sensor measurements may be vulnerable to cyber‐attacks, the two‐tier control architecture ensures that the process will stay immune to destabilizing malicious cyber‐attacks. Data‐based attack detectors are developed using sensor measurements via machine‐learning methods, namely artificial neural networks (ANN), under nominal and noisy operating conditions, and applied online to a simulated reactor‐reactor‐separator process. Simulation results demonstrate the effectiveness of these detection algorithms in detecting and distinguishing between multiple classes of intelligent cyber‐attacks. Upon successful detection of cyber‐attacks, the two‐tier control architecture allows convenient reconfiguration of the control system to stabilize the process to its operating steady state.

The increasing penetration of unconventional gas and liquefied natural gas poses an operational challenge on existing regional gas networks for gas quality problems. A new dynamic model for natural gas pipeline network with multiple supplies is presented with a special emphasis on gas interchangeability control. Wobbe index serves as gas interchangeability indicator and is calculated by equations derived from rigorous composition‐based partial differential equations. Disjunctive formulation is applied to represent different modes of gas blending due to gas reversal, and the disjunctive model is then reformulated as a nonsmooth model with min/max and absolute value functions, which is solved by a gradient‐based nonlinear program solver after smooth approximation. Moreover, a heuristic algorithm is proposed to tune the penalty parameters in order to focus on different penalty terms while keeping the model well‐conditioned. The developed model and strategy are first tested with a small pipeline network model and then extended to a large model. The results show that the model can effectively manage gas interchangeability issues in pipeline networks within reasonable CPU time.

Local structural anisotropy prevails in gas–solid suspensions. It causes strong fluctuations in the drag on individual particles. In this work, the anisotropy of microstructures is quantified by a second‐order structure tensor, which is determined with a directionally dependent mean free path length. Direct numerical simulations of low‐Reynolds‐number flows past anisotropic and isotropic BCC, FCC, and random arrays of monodisperse spheres in sufficiently large domains are performed. The results show that, at the same solid volume fraction, the differences between the mean drag in principal directions of anisotropic arrays and that in isotropic arrays correlate well with functions of eigenvalues of the structure tensor for the anisotropic arrays. Anisotropic drag models for different arrays are proposed. Assessment of the model for random arrays shows that it well captures fluctuations in the mean drag at microscales of several sphere diameters, where the traditional model fails to give satisfactory predictions.

Model predictive control (MPC) is a de facto standard control algorithm across the process industries. There remain, however, applications where MPC is impractical because an optimization problem is solved at each time step. We present a link between explicit MPC formulations and manifold learning to enable facilitated prediction of the MPC policy. Our method uses a similarity measure informed by control policies and system state variables, to “learn” an intrinsic parametrization of the MPC controller using a diffusion maps algorithm, which will also discover a low‐dimensional control law when it exists as a smooth, nonlinear combination of the state variables. We use function approximation algorithms to project points from state space to the intrinsic space, and from the intrinsic space to policy space. The approach is illustrated first by “learning” the intrinsic variables for MPC control of constrained linear systems, and then by designing controllers for an unstable nonlinear reactor.

The mixing and drying behavior in a continuous fluidized bed dryer were investigated experimentally by characterizing the residence time distribution (RTD) and incorporating a micromixing model together with the drying kinetics obtained from batch drying. The RTD of the dryer was modeled using a tank‐in‐series model. It was found that a high initial material loading and a low material flow rate resulted in a reduced peak height and broaded peak width of the RTD curve. To predict the continuous dryer effluent moisture content, we combined: (a) the drying kinetics as determined in a batch fluidized bed dryer, (b) the RTD model, and (c) micromixing models—segregation and maximum mixedness models. It was found that the segregation model overpredicted the effluent moisture content by up to 5% for the cases we have studied while the maximum mixedness model gave a good prediction of the effluent moisture content.

Microcapsules filled with liquid solvents for CO2 absorption can be easily deformed due to their elastic polymer shells. We present a combination of experiments and model predictions to demonstrate that modest compressive forces can lead to significant capsule deformation and performance issues for this enabling technology. Contrary to expectations based on Raoult's law, capsules containing aqueous carbonate solution were found to lose water to flows of humidified nitrogen in centimeter‐scale packed beds. Water loss increased with gas velocity, suggesting compression was responsible for mass transfer, an interpretation supported by microscope images of deformed and broken capsules. A model for compression induced mass transfer under packed/fluidized bed operating conditions was developed and validated with the experimental data for a range of conditions (gas velocities, temperatures, humidities). Design criteria for future generations of microcapsules that will more effectively resist compression are evaluated.

Three types of self‐prepared chemical dust suppressants (CDSs) were investigated for their inhibitory effects on nitrocellulose (NC) cloud dust explosion. The results revealed that NC is extremely sensitive to electric sparks and has a high explosion intensity. CaCl2‐CDS effectively increased the particle size to control fly dust substantially inhibiting dust cloud explosions. However, both Na2SO4‐CDS and MgCl2‐CDS exhibited poor abilities and even promoted explosion. Therefore, neither Na2SO4‐CDS nor MgCl2‐CDS is recommended as a CDS for NC. Inappropriately using CDSs may engender severe explosions. Furthermore, a mechanism underlying NC dust cloud combustion and explosion was proposed. NC has three stages of heat release: autoxidation, thermal decomposition, and combustion. Thermal decomposition, combustion, and explosion were triggered depending on the energy provided from autoxidation. CaCl2‐CDS inhibited only combustion. This study reveals the mechanism underlying NC dust cloud explosions and provides useful information for the development of more optimized CDSs.

In this work, batch‐adsorption experiments and molecular simulations are employed to probe the adsorption of binary mixtures containing ethanol or a linear alkane‐1,n‐diol solvated in water or ethanol onto silicalite‐1. Since the batch‐adsorption experiments require an additional relationship to determine the amount of solute (and solvent) adsorbed, as only the bulk liquid reservoir can be probed directly, molecular simulations are used to provide a relationship between solute and solvent adsorption for input to the experimental bulk measurements. The combination of bulk experimental measurements and simulated solute–solvent relationship yields solvent and solute loadings that are self‐consistent with simulation alone, and allow for an assessment of the various assumptions made in the literature. At low solution concentrations, the solute loading calculated is independent of the assumption made. At high concentrations, a negligent choice of assumption can lead to systematic overestimation or underestimation of calculated solute loading.

Particle shape is one of the most important parameters in the design and optimization of fixed‐bed processes. To address the impact of particle shape on methanol partial oxidation to formaldehyde over molybdate catalyst, packings of spheres, cylinders, rings, and trilobes are numerically generated. The generated packings are used to carry out resolved particle Computational Fluid Dynamics (CFD) simulations under industrial conditions. Pressure drop, voidage and velocity profiles, radial heat transfer, and local and overall conversion and selectivity results are presented. Despite their lower particle surface area, lower particle effectiveness and more uneven flow distribution than trilobes, and lower overall heat transfer coefficient than cylinders, rings had the best conversion and selectivity due to their balance between the factors. Three longer tubes of rings, rings and cylinders, and rings and trilobes are simulated and show a small gain in selectivity for the rings and trilobes.

The dynamic 13C labelling experiment, as an emerging experimental technique, can be utilized to quantify intracellular fluxes of the cell culture under metabolic unsteady states conditions, for example, under fed batch mode. One main disadvantage of the current dynamic isotope experiment technique is that the intracellular metabolic pools have to be at pseudo steady state. Furthermore, to the best of our knowledge, the stability issue of dynamic isotope experiments is not addressed in the literature. In this work, if one assumes that concentrations of intracellular metabolites are non‐steady, it is shown that dynamic cumomer balance equations for any metabolic network are uniformly bounded‐input and bounded‐output stable regardless of the existence of traps. It is valid under very weak conditions. Specifically, it requires that the intracellular flux and the size of intracellular pool are finite and strictly greater than zero at any time. The new finding paves the way to utilize the dynamic isotope experiment to approximately quantify intracellular fluxes and sizes of intracellular pools under intracellular metabolic non‐steady state with piecewise affine fluxes.

This work aims at developing an efficient and feasible adsorption‐based separation process for the separation of vinyl chloride and nitrogen, on activated carbon, by employing a multitubular packed bed geometry, with adsorbent material inside the tubes. Using this geometry, a 2‐dimensional mathematical model of a temperature pressure swing adsorption process was used to developed a 6‐step three multitubular adsorbers system capable of separating and purifying an industrial scale gas stream of a 40:60% (v/v) vinyl chloride/nitrogen mixture into a 95% (v/v) vinyl chloride stream and a nitrogen stream with a vinyl chloride limit concentration of 8 ppm (w/w). The process reported energy consumption of 4.88 × 106 J/kgVCM and recovery capacity of 24.35 kgVCM/(m3unit h). The multitubular geometry enabled the use of lower adsorbent loads, shorter cycle times, and lower regeneration temperatures. An equivalent 1‐dimensional model has also shown to satisfactorily estimate the performance of the current equipment.

To improve the energy‐to‐CH4 efficiency and enhance renewable power utilization, we investigate direct Power‐to‐Methane at low inlet H2 content (25 vol%) in solid oxide electrolysis cell (SOEC). The synergy of the pressurized operation and the electricity input effectively enhances CH4 yield by one‐order of magnitude from 2.8% to 28.7% and the CO2‐to‐CH4 ratio from 4.4% to 39.5% in the H2‐reduced case, where the ratio of H2 consumption to total energy consumption decreases to 41% and the energy‐to‐CH4 efficiency increases to 53%. We develop a multiphysics tubular SOEC model to understand the intrinsic coupling between electrochemistry and heterogeneous catalytic chemistry. From the perspective of performance enhancement, geometry optimization, and thermal design, inhibiting CH4 production in the inlet gas‐controlled zone and promoting CH4 production synergistically in both the electrochemistry‐controlled zone and the temperature‐controlled zone is the key to improve the energy‐to‐CH4 efficiency.

This article addresses the sustainable design of organic Rankine cycle‐based geothermal binary power systems under economic and environmental criteria. A novel superstructure with multiple heat source temperatures, working fluids, and heat rejection systems is proposed. Based on the superstructure, a life cycle optimization model is formulated as a mixed‐integer nonlinear fractional program (MINFP) to determine the optimal design. The nonconvex MINFP is efficiently solved by a tailored global optimization algorithm. Two case studies are considered to demonstrate the proposed modeling framework and solution algorithm. One case is based on a geothermal energy system located in California, and the other one is in New York (NY) State. The results show that the geothermal energy system in California is much more economically competitive than that in NY State. The difference in life cycle environmental impacts is less pronounced because the environmental impacts are less sensitive to geological conditions than the capital investments.

A scaled‐up dielectric barrier discharge (DBD) reactor has been developed and demonstrated for the production of hydrogen from steam methane reforming (SMR) by catalytic nonthermal plasma (CNTP) technology. Compared to SMR, CNTP offers conversion at ambient pressure (101.325 kPa), low temperature with better efficiency, making it suitable for distributed hydrogen production with small footprint. There have been several lab‐scale DBD reactors reported in the literature. Dimension of the scaled‐up DBD reactor is about six times the lab‐scale version and can produce 0.9 kg H2/day. The scale‐up is, however, nonlinear; several technical innovations were required including spray nozzle for homogeneous introduction of steam, perforated tube central electrodes for generation of homogeneous plasma. Conversion efficiency of the scaled‐up DBD reactor is 70–80% at 550°C and 500 W. A continuous run of 8 hr was demonstrated with typical product gas composition of 69% H2, 6% CO2, 15% CO, 10% CH4.

In biomass processing fluidized beds are used to process granular materials where particles typically possess elongated shapes. However, for simplicity, in computer simulations particles are often considered spherical, even though elongated particles experience more complex particle–particle interactions as well as different hydrodynamic forces. The exact effect of these more complex interactions in dense fluidized suspensions is still not well understood. In this study we use the magnetic particle tracking technique to compare the fluidization behavior of spherical particles to that of elongated particles. We found a considerable difference between fluidization behavior of spherical versus elongated particles in the time‐averaged particle velocity field as well as in the time‐averaged particle rotational velocity profile. Moreover, we studied the effect of fluid velocity and the particle's aspect ratio on the particle's preferred orientation in different parts of the bed, which provides new insight in the fluidization behavior of elongated particles.

This contribution evaluates systematic but rigorous methodologies to characterize kinetics and heat transfer mechanisms and states statistical and phenomenological criteria to model an industrial‐scale wall‐cooled packed‐bed reactor for the oxidative dehydrogenation of ethane over a MoVTeNbO catalyst. A set of kinetic formalisms was submitted to regression analyses with the reparametrized form of the Arrhenius and van't Hoff equations. Heat transfer parameters (HTP) were determined by evaluating either the effect of hydrodynamics or the type of temperature measurements on reactor simulations. Eley–Rideal formalism led to the most proper approach to describe kinetics, presenting thermodynamic consistency and statistical confidence; whereas the HTP determined out of radial and axial measurements and accounting for hydrodynamics led to the determination of the most reliable transport parameters presenting phenomenological and statistical significance. These results stated criteria to model with confidence the performance of the studied technology, paving the way for its further rigorous design, optimization, or intensification.

The considerable performance enhancement of small molecule‐sieving nanofiltration membrane has been achieved by the functional combination between host–guest chemistry and interfacial polymerization (IP) for the first time in this work. First, the water‐insolubility of cucurbit[6]uril (CB6) was ameliorated by constructing host–guest complex (CB6‐PIP) with piperazine. Second, the incorporation of water‐soluble CB6‐PIP in the selective layer via IP leads to the generation of not only the enlarged conventional polyamide network tunnels but also rotaxane tunnels. Such enrichment of solvent transport tunnels contributes to an amazing pure water permeability of 15.5–25.4 Lm−2bar−1h−1, three times higher than that of traditional polyamide membranes, with a high R/MgSO4 of 99.5–92.5%, perfect SO42−/Cl− selectivity due to the electronegative contribution of CB6, as well as untapped potential in organic solvent nanofiltration. This work not only provides a fire‐new strategy to design new type of NF materials but also promotes the application of CBs in many other fields.

This study evaluated geochemistry between the Utica‐Point Pleasant shale and reservoir/hydraulic fracturing fluid mixtures under simulated reservoir conditions in a batch reactor system. Analytical techniques were utilized to monitor fluid composition with time along with pre‐ and post‐trial shale microscopy and phase identification analyses. Formation of iron‐based precipitate was evident through results from fluid and material analyses. Ferrous iron was the predominant iron form found in the aqueous phase, with oxidation to ferric iron and subsequent precipitate formation. Geochemical modeling further supported ferric iron was the favorable phase for precipitation.

We perform quantitative visualization experiments on the vertical (z‐direction) motion of a spherical solid particle being lifted off a horizontal flat bottom due to laminar fluid flow generated by a revolving impeller. Describing the observed motion of the particle in terms of a constant vertical hydrodynamic force overcoming gravity and the lubrication force has limited success. For this reason, we hypothesize that the hydrodynamic force on the particle quickly increases with its distance from the bottom. This hypothesis is supported by detailed numerical simulations of the flow around the particle. Integrating the equation of motion of the sphere with the vertical hydrodynamic force as a linear function of z derived from simulations provides an adequate description of the experimentally observed vertical motion of the particle.

In this study, a mathematic model is proposed for estimating the wax content of wax deposits. The proposed model was built based on the diffusion of wax molecules and counter‐diffusion of oil molecules and described using the Fick's second law, allowing for the stacking fraction and orientational order of precipitated wax crystals and the tortuosity of diffusion path of de‐waxed oil molecules during the counter‐diffusion. The calculated results were verified by comparing with the flow‐loop wax deposition experimental results. Dependence of radial position, deposition duration, bulk temperature, and wall temperature were investigated. These factors significantly affected the wax content during wax deposition. Good agreements were observed between the predictions and experimental results. The variation trends of wax content affected by various aspects are consistent with the existing studies.

Liquid–liquid mass transfer performance of a novel pore‐array intensified tube‐in‐tube microchannel (PA‐TMC) was investigated with the water‐benzoic acid‐kerosene system. Both mass transfer efficiency (E) and volumetric mass transfer coefficient (K La) are found to increase simultaneously with the flow rate, but decrease with total number of pores and rows. However, E increases but K La decreases with the annular length. In particular, the pore size shows an optimal value at 0.3 mm due to the interplay problem of the radial adjacent pores. Computational fluid dynamics simulations reveal that the high kinetic energy generated by the pore‐array section plays a significant role in mass transfer process. The artificial neural network model is established to correlate K La with the investigated parameters of PA‐TMC. The comparison of K La with other types of contactors indicates that PA‐TMC has superior mass transfer performance and high throughput for a broad industrial application.

Microbial electrocatalysis systems (MES) provide a cutting‐edge solution to global problems associated with the environment and energy, but practical applications are hindered by the expensive electrode materials. Although stainless steel (SS) has been proposed as a promising inexpensive candidate, poor cell/SS interaction results in a low performance for MES. Here, a new synthetic biology approach was established for reinforcing the cell/SS interaction. Hybridized curli nanofibers fused with a metal‐binding domain were heterogeneously expressed onto the cell surface, which realized efficient cell binding with the SS electrode. Consequently, it enabled a ~420‐fold improvement of the anodic power output and a substantial enhancement of the cathodic Coulombic efficiency (from 0.6 to 4% to over 80%) with an SS electrode. This work demonstrates low‐cost MES with an SS electrode and introduces a new avenue to engineer the cell/electrode interaction, which is promising for future practical applications of MES.

The waves of liquid film flow play an important role on the process intensification in spinning disk reactors (SDRs). However, the mechanism of wave formation was still unclear. In this work, a three‐dimensional large eddy simulation was developed to investigate the mechanism, as well as the characteristics of waves in the SDR. Agreed with the imaging results, different wave patterns were identified as: smooth film, concentric, and spiral waves in spreading direction; sine‐like and pulse‐like waves in fluctuating direction. The radial and tangential relative movements among the layers of liquid film were found to dominate the formation of different wave patterns. Local average film thickness (havg) and local wave amplitude (Δh) ranged from 0 to 500 μm and 0 to 200 μm, respectively. The waves can improve the turbulent intensity and enlarge the specific surface area, resulting in the intensification of transfer processes.

The addition of surfactants to modify the surface property of nanoparticles (NPs) from hydrophilic to hydrophobic also enhances their interfacial properties. Several approaches were previously proposed to calculate the surface tension/interfacial tension (IFT) for different systems in the presence of NPs, surfactants, and electrolytes. However, most of these approaches are indirect and require several measured parameters. Therefore, a mathematical model is developed here to calculate the surface tension/IFT for these systems. The developed model takes into account the cohesive energy due to the interaction of the surfactant CH2 groups, the electric double layer effect due to the interaction among the ions of NPs, surfactants, and electrolytes, and the dipole–dipole interaction of NPs and electrolytes. The developed model is compared and validated with the laboratory experimental data in literature. The results reveal further understanding of the mechanisms involved in stabilization of oil/water emulsion in the presence of NPs, surfactants, and electrolytes.

Gas–liquid bubble column reactors are often used in industry because of their favorable mass transfer characteristics. The bubble mass boundary layer in these systems is generally one order of magnitude thinner than the momentum boundary. To resolve it in simulations, a subgrid scale model will account for the sharp concentration variation in the vicinity of the interface. In this work, the subgrid scale model of Aboulhasanzadeh et al., Chem Eng Sci, 2012, 75:456–467 embedded in our in‐house front tracking framework, has been improved to prevent numerical mass transfer due to remeshing operations. Furthermore, two different approximations of the mass distribution in the boundary layer have been tested. The local and global predicted Sherwood number has been verified for mass transfer from bubbles in the creeping and potential flow regimes. In addition, the correct Sherwood number has been predicted for free rising bubbles at several Eötvös and Morton numbers with industrial relevant Schmidt numbers (103–105).

For better understanding and optimization of multiphase flow in miniaturized devices, micro‐computed tomography (μCT) is a promising visualization tool, as it is nondestructive, three‐dimensional, and offers a high spatial resolution. Today, computed tomography (CT) is a standard imaging technique. However, using CT in microfluidics is still challenging, since X‐ray related artifacts, low phase contrast, and limited spatial resolution complicate the exact localization of interfaces. We apply μCT for the characterization of stationary interfaces in thin capillaries. The entire workflow for imaging stationary interfaces in capillaries, from image acquisition to the analysis of interfaces, is presented. Special emphasis is given to an in‐house developed segmentation routine. For demonstration purposes, contact angles of water, liquid polydimethylsiloxane, and air in FEP, glass, and PMMA are determined and the influence of gravity on interface formation is discussed. This work comprises the first steps for a systematic 3D investigation of multiphase flows in capillaries using μCT.

In the present study, flow homogenization by distributors in chemical apparatus is studied as a process of flow control and its mechanism is reconsidered from the model of resistance to the model of radial flow. This process is composed of four consecutive behaviors: the generation, distribution, conversion of the radial flow and the momentum transfer of axial flow. Based on these flow behaviors, the novel distributor is designed as the combination of perforated plate in the center area and vertical guiding baffles around. Taking the wire‐screen catalytic reactor as a case study, numerical simulation is employed to optimize the structure of distributor and a CFD based design scheme called “flow field analysis scheme” is proposed. Numerical simulation is conducted in the apparatus with a diffuser (inlet D0=500mm, main part D1=3000mm) under the gas velocity of 3.6m/s (corresponding Re≈12000). The numerical results from optimized distributor show that compared with the traditional perforated plate, the flow field adjusted by the novel distributor can achieve a better flow uniformity with lower energy consumption. The theoretical analysis and numerical results are also validated and proved by the experimental results.

In flame spray pyrolysis (FSP), the evolution of metal oxide nanoparticles relies on quite a number of droplet (liquid) and vapor phase related physical mechanism as for instance precursor evaporation, oxidation, nucleation via gas‐to‐particle conversion mechanism, and subsequent particle (solid) growth mechanisms based on coagulation, sintering/coalescence, and agglomeration. The liquid precursor and dispersion oxygen feed rates are relevant control parameters of the FSP process for tailoring the nanoparticle size (diameter) and structure as well as the atomizer nozzle configuration. Sophisticated nonintrusive, laser‐based in situ and ex situ diagnostics with multiscale spatial resolution (micrometer to meter range) are applied for analyzing droplet formation and size, gas velocity, temperature, species concentration, as well as primary and agglomerate diameters along the flow direction. Computational fluid dynamics (CFD) are coupled with population balance modeling (PBM) to elucidate the nanoparticle dynamics within the reactive spray. It is found that the CFD‐PBM approach allows estimations of primary and agglomerate nanoparticle diameters within 80 and 75% accuracy compared to experimental data, suggesting that the methods presented could pave the way for designing next‐generations of flame reactors.

Drag plays a crucial role in hydrodynamic modeling and simulations of gas–solid flows, which is significantly affected by particle Reynolds number, solid volume fraction, heterogeneity, granular temperature, particle‐fluid density ratio, and so on. To clarify and quantify the multiscale effects of these factors, large‐scale particle‐resolved direct numerical simulations of gas–solid flows with up to 115,200 freely moving particles are conducted. Both domain‐averaged kinetic properties and local averaged dimensionless drag are sampled and analyzed. It is revealed that the complex scale‐dependence of drag is attributed to the multiscale effects of heterogeneous structures and particle fluctuating velocity. The granular temperature and the scalar variance of solid volume fraction are also found to be scale‐dependent. On account of these, a new drag correlation as the function of Froude number is proposed with consideration of scale‐dependence.

Due to the linear correlation between the subgrid drift velocity and the filtered drag force, modeling the drift velocity would be an alternative way to obtain the filtered drag force for coarse‐grid simulations. This work aims to improve the predictability of models for the drift velocity using a new effective marker, the filtered gas pressure gradient, which is identified by momentum balance analysis. New models are constructed based on conditional averaging of the results obtained from fine‐grid two‐fluid model simulations of three‐dimensional unbounded fluidized systems. A priori assessment is presented with the comparison between the proposed models and the best available Smagorinsky‐type model with dynamic adjustment technique proposed in the literature. Results show that the proposed models give satisfactory performance. More important, the proposed models are demonstrated to have a better adaptability for cases under various physical conditions than the Smagorinsky‐type model.

In the past decades, CO2 constituted nearly the 80% of anthropogenic greenhouse gases emissions therefore, global actions are needed to tackle the increase of carbon concentration in the atmosphere. CO2 (carbon) capture and storage has been highlighted among the most promising options to decarbonize the energy and industry sectors. Considering a large‐scale infrastructure at European level, economic cooperation has been highlighted as a key requirement to relieve single countries from too high risk and commitment. This article proposes an economic optimization for cooperative supply chains for CO2 capture and storage, by adopting policies that balance the spread of costs among countries, according to local characteristics in terms of population, CO2 emissions, and macroeconomic outcome. Results show that the additional European investment for cooperation (max. +2.6% with respect to a noncooperative network) should not constitute a barrier toward the installation and operation of such more effective network designs.

The discharge of granular media from hoppers plays a vital role in many solids handling operations. The dynamic flow of poly‐disperse nonspherical particles differs markedly from mono‐disperse spheres and highlights the need to rigorously account for particle shape effects. The multisphere discrete element method (MS‐DEM) was utilized here to examine the bulk packing fraction, discharge rate, collisional stress tensor, and order parameter of a bi‐disperse sphere‐rod mixture evacuating a hopper. A modified form of the Myers and Sellers correlation with variable shape factor is capable of replicating the MS‐DEM discharge data. The collisional stress tensor is observed to be highly symmetric for mono‐disperse spheres but becomes asymmetric when rod‐like particles are introduced. The order parameter within the hopper increases significantly during discharge and the rod‐like particles undergo shear induced alignment with their long dimensions orthogonal to the outflow plane.

The homogeneous phosphotungstic acid catalyzed N‐oxidation of alkylpyridines by hydrogen peroxide has important applications in pharmaceutical and fine chemical industries. Current industry practice is to employ a semibatch reactor with gradual dosing of hydrogen peroxide into an alkylpyridine/catalyst solution under isothermal conditions. However, due to lack of understanding of reaction mechanism and thermodynamic behavior, this system is subject to significant risk of flammability, fires and explosions due to hydrogen peroxide decomposition. In this study, we conducted semibatch N‐oxidation process in an isothermal reaction calorimeter (RC1) over a wide range of temperature, catalyst amount and oxidizer dosing rates. Reactor pressure, reaction heat generation rate and in situ FTIR spectra of liquid phase species were recorded in real‐time during experiments, and final product was quantified using HPLC and GC–MS analytical tools. We developed an integrated thermodynamic and kinetics model of homogeneous N‐oxidation reaction based on experimental results and past literature findings. More specifically, Wilson excess Gibbs model was employed to estimate activity coefficients of highly nonideal liquid mixture. We found ideal gas law was satisfactory in calculating incondensable oxygen pressure. First principle reaction mechanism and kinetics parameters of (a) catalytic N‐oxidation reaction; (b) catalytic hydrogen peroxide decomposition reaction; (c) noncatalytic N‐oxidation reaction; (d) noncatalytic hydrogen peroxide decomposition reaction was derived based on experimental findings of this study and past literature. The proposed integrated thermodynamic model and kinetics model successfully predicted highly nonlinear reactor pressure, species concentration and reaction enthalpy generation rate profile of homogenous catalytic N‐oxidation and H2O2 decomposition reaction. The optimal reactions conditions with maximum N‐oxide product yield and minimum reactor pressure and catalyst usage was theoretically identified and further verified by experiments. The obtained model can be used for inherently safer reactor design and applied to other homogeneous tungstic acid catalytic hydrogen peroxide oxidation processes.

Mixing of viscous non‐Newtonian fluids plays an important role in many industrial processes (wastewater treatment, methanization, etc.). In some cases, mixing by gas injection can be more interesting than mechanical mixing. The present study focuses on the gas injection in yield stress fluids. The influence of the air flow rate, fluid rheological properties, and geometrical configuration on an air jet impinging the bottom wall of a tank containing a yield stress fluid has been considered. Focus has been placed on the air cavity present at the injection point. The trends of two key parameters of the cavity have been characterized: its maximum diameter and frequency detachment. Correlations based on the characteristic dimensionless numbers governing the flow have been derived. These correlations show that the apparent viscosity has an effect on the cavity's frequency but a low influence on its diameter which is mainly governed by the air flow inertia.

Aerosol deposition with gas phase‐synthesized chain‐like nanoaggregates can yield dense coatings from the impaction of particles on a substrate; however, dense coating formation is not well understood. Here, we study coating consolidation at the single nanoaggregate level. Flame spray pyrolysis‐made tin oxide nanoaggregates are mobility (size) filtered, accelerated through a de Laval nozzle, and impacted on alumina substrates. TEM images obtained from low velocity collection and supersonic deposition are compared via quantitative image analysis, which reveals that upon supersonic impact nanoaggregates fragment into smaller aggregates. This suggests that fragmentation is a key step in producing coatings denser than the depositing nanoaggregates themselves. We supplement experiments with detailed particle trajectory calculations, which show that the impact energies per atom during nanoaggregate deposition are below 0.2 eV/molecule. These results suggest that fragmentation can only occur at locations where nanoaggregates bonded by van der Waals and capillary interactions.

Ternary mixture of fluoroethane (HFC‐161) + difluoromethane (HFC‐32) + N,N‐dimethylformamide (DMF) is a promising working fluid for absorption refrigeration system which is an important energy saving technology receiving more and more attention. Investigation on vapor–liquid equilibrium (VLE) is necessary for further study and the application in absorption system of the ternary mixture. Therefore, an experimental system with continuous vapor‐phase circulation is set up, measuring VLE data within temperature range of 283.15 to 323.15 K. The experimental data is correlated with Wilson and NRTL models, and BP‐ANN method, respectively. The calculating data of Wilson model has the largest relative deviation of 5.14% and average relative deviation of 2.65% for vapor pressure, being the best one. The deviation of molar fraction data obtained with BP‐ANN model has the best average relative deviation 3.07%. However, NRTL model provides a smooth predicted surface. The correlated parameters of the three models are given.

This article describes the design and synthesis of MgO‐modified Ni/CaO catalysts for sorption‐enhanced steam reforming of ethanol. The results show that the introduction of MgO effectively increases the dispersion of CaO via forming MgCa(CO3)2 precursor. In the prepared MgO‐modified Ni/CaO catalysts, metallic Ni exists around MgO supported on CaO. Both 100% ethanol conversion and >96% hydrogen purity can be stabilized in 10 cycles over the catalyst containing 20 wt% MgO. The interaction between metallic Ni and MgO enhances the sintering resistance of the catalyst. More importantly, reaction pathway studies have confirmed that the formation of CaCO3 hinders the activation of H2O on the Ni/CaO catalyst surface, and thus inhibits the conversion of the reaction intermediates including HCO* and CH x*. MgO can dissociate H2O to form hydroxyl groups which participate in the conversion of the reaction intermediates, thereby the MgO‐modified Ni/CaO catalysts have better catalytic performance and carbon deposition resistance.

We present a workflow for kinetic modeling of biocatalytic reactions which combines methods from Bayesian learning and uncertainty quantification for model calibration, model selection, evaluation, and model reduction in a consistent statistical framework. Our workflow is particularly tailored to sparse data settings in which a considerable variability of the parameters remains after the models have been adapted to available data, a ubiquitous problem in many real‐world applications. Our workflow is exemplified on an enzyme‐catalyzed two‐substrate reaction mechanism describing the symmetric carboligation of 3,5‐dimethoxy‐benzaldehyde to (R)‐3,3′,5,5′‐tetramethoxybenzoin catalyzed by benzaldehyde lyase from Pseudomonas fluorescens. Results indicate a substrate‐dependent inactivation of enzyme, which is in accordance with other recent studies.

Polysilicon is a key commodity required for both electronics and solar photovoltaic modules. The traditional route to produce polysilicon involves the Siemens reactor, an energy intensive batch process. A more efficient, but more complex alternative process is the fluidized bed reactor (FBR). In an FBR silane is pyrolysed producing chemical vapor deposition (CVD) and aerosols. Efficient FBR operation requires yield optimization together with continuous and stable operation of the reactor. Such optimization is not straightforward because the aerosol formation mechanisms and incorporation into the FBR beads are not completely understood. In this work, two model aerosols with different morphology were tested and their filtration efficiency between 20 and 800 nm was determined. Bead saturation at different times was determined for each morphology and the scavenging factor over time for each case is reported. Such information can be of interest for establishing bed recirculation needs in a silicon FBR.

We present a 3D metal printing showerhead mixer to blend effectively two reagent streams into a confined mixing volume. Each stream is predistributed to multiple channels to increase the contact area in the mixing zone, which enables high mixing performance with smaller pressure drop. The showerhead mixer shows excellent mixing performance owing to its ability to intersperse rapidly the two streams as characterized by the diazo coupling reactions and computational fluid dynamics (CFD) simulations. Experimental results demonstrate superior performance of the showerhead mixer compared to two common commercial micro T‐mixers, especially in low Reynolds number regime. CFD results are employed to (a) help understand the mixing mechanism, (b) reproduce the experimental observations, and (c) inform the design specifications for optimal performance. Good agreement between experiments and simulations is achieved. The final design includes multiple side‐fed inlets for improved mixing performance of the showerhead mixer, as suggested by the validated CFD models.

Group C+ particles, Group C particles after nano‐modulation, with extremely large specific surface area, have been shown to exhibit extraordinarily good fluidization quality with superiorly high bed expansion, significantly increasing gas holdup in the bed. As a first attempt, Group C+ particles were used as catalysts in a fluidized bed reactor (C‐plus FBR) to evaluate the reaction performance and were compared to that using Group A particles. C‐plus FBR could achieve a much higher reaction conversion, up to 235% of that using Group A particles. The contact efficiency for Group C+ particles is much higher, being 330% more than that for Group A particles. The greater contact efficiency is due to both larger specific surface area and higher bed expansion, providing larger gas–solid interfacial area and longer gas residence time. Conclusively, Group C+ particles with superior fluidization quality and reaction performance do have huge potential in gas‐phase catalytic reactions.