Modern chemical processes need to be operated around different operating conditions to optimize plant economy, in response to dynamic supply chains. As such, the process control system needs to handle a wide range of operating conditions whilst optimizing system performance and ensuring stability during transitions. This article presents a reference-flexible nonlinear model predictive control approach using contraction based constraints. Firstly, a contraction condition that ensures convergence to any feasible state trajectories or setpoints is constructed. This condition is then imposed as a constraint on the optimization problem for model predictive control with a general (typically economic) cost function, utilizing Riemannian weighted graphs and shortest path techniques. The result is a reference flexible and fast optimal controller that can trade-off between the rate of target trajectory convergence and economic benefit (away from the desired process objective). The proposed approach is illustrated by a simulation study on a CSTR control problem.

This work considers a seeded fesoterodine fumarate (FF) cooling crystallization and presents the methodology and implementation of a real-time machine learning modeling-based predictive controller to handle batch-to-batch (B2B) parametric drift. Specifically, an autoencoder recurrent neural network-based model predictive controller (AERNN-MPC) is developed to optimize product yield, crystal size, and energy consumption while accounting for the physical constraints on cooling jacket temperature. Deviations in the kinetic parameters are considered in the closed-loop simulations to account for the B2B parametric drift, and two error-triggered online update mechanisms are proposed to address issues pertaining to the availability of real-time crystal property measurements and are incorporated into the AERNN-MPC to improve the model prediction accuracy. Closed-loop simulation results demonstrate that the proposed AERNN-MPC with online update, irrespective of the accessibility to real-time crystal property data, achieves a desired closed-loop performance in terms of maximizing product yield and minimizing energy consumption.

To validate the experimental results of Part-1, we conducted a two-phase flow simulation of imbibition of a wetting liquid through 2D microstructures made of ellipses of varying aspect ratios. The flow simulation in the particulate microstructures, characterized by low (ellipse) aspect ratio, produced somewhat even micro-fronts, thus replicating the sharp fronts at the visual (macroscopic) scale observed in Part-1. Whereas simulations in the fibrous microstructures produced highly uneven micro-fronts, suggesting the formation of semi-sharp or diffuse visual fronts. Increasing the porosity from 50% to 70% resulted in solid-phase clustering and led to further increase in the unevenness of micro-fronts, pointing to purely diffuse visual fronts. The evolution of the saturation plots along the flow direction, obtained from area-averaging of fluid-distribution plots, pointed to diffusing of sharp fronts with time. The predictions matched our previous experimental observations, i.e., the particulate media create sharp fronts while the fibrous media create semi-sharp/diffuse fronts.

The dynamics and breakup of bubbles in swirl-venturi bubble generator (SVBG) are explored in this work. The three-dimensional movement process and breakup phenomena of bubbles are captured by one high-speed camera system with two cameras while the distribution of swirling flow field are recorded through Particle Image Velocimetry technology. It is revealed that bubbles have two motion trajectories, which are deeply related to bubble breakup. One trajectory is that mother bubble moves upward in an axial direction of the SVBG to the diverging section, and the other trajectory is that mother bubble rotates obliquely upward to another side-wall along the radial direction. Meanwhile, binary breakup, shear-off-induced breakup, static erosive breakup and dynamic erosive breakup are observed. For relatively high liquid Reynolds number, vortex flow regions are extended and the bubble size is reduced. Furthermore, it is worth noting that the number of microbubbles increases significantly for intensive swirling flow.

The strong core base in chemical engineering during the latter half of the 20th century enabled chemical engineers to contribute extensively to many areas outside of the traditional. The depth of such involvement has led researchers to confront questions much more engaging to the field of application, thus adopting and cultivating expertise more native to it than to secure chemical engineering as a discipline. The progress of knowledge in science and engineering must leave a strong trail of fundamental understanding through developed methodologies that can assist in continuing progress. If this tenet is acknowledged, this article yields considerable scope for discussion on whether chemical engineering research is continuing to provide for a growing core that has endowed chemical engineers with the ability to formulate and solve important societal problems in which material systems undergo changes in composition and energy. We discuss opportunities for hopefully serving the issues of concern.

The state estimation and sensor placement for a continuous pulp digester with delayed measurements are investigated. The underlying model of interest is heat transfer in a pulp digester modeled by two coupled hyperbolic partial differential equations and an ordinary differential equation. Output measurements are considered with delay due to the possible low sampling rate. The Cayley-Tustin transformation is utilized to realize model time discretization in a late lumping manner which does not account for any type of spatial approximation or model reduction. The discrete Kalman filter is applied to estimate the system states using the delayed measurements. The selection of sensor location is addressed along with estimator design accounting for the delayed measurements and investigated by minimizing the variance of estimation error. The performance of the state estimator is evaluated, and the sensor placement is analyzed through simulation studies, which provide guidance for sensor location selection in industrial applications.

Single-atom catalysts with optimal atom utilization and outstanding activity have penetrated the frontier of heterogeneous catalysis. However, the large-scale synthesis of this class of catalysts is still a bottleneck for their industrialization. Herein, we suggest a two-stage micro-dispersion approach to synthesize mesoporous MgAl2O4-supported atomically dispersed Rh, which is more competitive than the batch method for boosting the uniform dispersion of Rh. By increasing the Rh loading, single-atom catalysts (SACs, < 0.05wt%), single-atom catalysts + nanoparticle catalysts (0.05–0.17 wt%), and nanoparticle catalyst (NPCs, 0.17–1.10 wt%) were obtained. For n-octane steam reforming, the turnover frequency of the SAC (0.01 wt%) was approximately 30 times that of the NPC (1.10 wt%), while the Rh amount of the SAC was only 3% that of the NPC for the same fuel conversion. Under a high-temperature (750 ℃) steam atmosphere for 15 h, the hydrogen formation rate only declined from 25.1 to 23.8 mol/mol-C8H18.

A high-throughput (105.5 g/h) passive four-stage asymmetric oscillating feedback microreactor using chaotic mixing mechanism was developed to prepare aggregated BaSO4 particles of high primary nanoparticle size uniformity. Three-dimensional unsteady simulations showed that chaotic mixing could be induced by three unique secondary flows (i.e., vortex, recirculation, and oscillation), and the fluid oscillation mechanism was examined in detail. Simulations and Villermaux-Dushman experiments indicate that almost complete mixing down to molecular level can be achieved and the prepared BaSO4 nanoparticles were with narrow primary particle size distribution (PSD) having geometric standard deviation, σg, less than 1.43 when the total volumetric flow rate Qtotal was larger than 10 mL/min. By selecting Qtotal and reactant concentrations, average primary particle size can be controlled from 23 to 109 nm as determined by microscopy. An average size of 26 nm with narrow primary PSD (σg = 1.22) could be achieved at Qtotal of 160 mL/min.

In this study, a new electrolyte system consisting of tetrabutylphosphonium 4-(methoxycarbonyl) phenol ([P4444][4-MF-PhO]) ionic liquid and acetonitrile (AcN) was developed as CO2 electroreduction electrolyte to produce oxalate, and the mechanism was studied. The results showed that using the new ionic liquid-based electrolyte, the reduction system exhibits 93.8% Faradaic efficiency and 12.6 mA cm-2 partial current density of oxalate at -2.6 V (vs. Ag/Ag+). The formation rate of oxalate is 234.4 μmol cm-2 h-1, which is better than that reported in the literature. The mechanism study using density functional theory (DFT) calculation revealed for the first time that [P4444][4-MF-PhO] IL can effectively activate CO2 molecules through ester and phenoxy double active sites, stabilize the reaction intermediate. The potential barriers of the key intermediates *CO2- and *C2O42- formation by induced electric-field was reduced in the phosphonium-based ionic environment, which greatly facilitates the activation and conversion of CO2 molecules to oxalate.

A two-step integrated MOF and pressure/vacuum swing adsorption (P/VSA) process design has been recently established for gas separation. In the first step, selected MOF descriptors and process operating conditions are simultaneously optimized to maximize the process performance. Based on the obtained results, the second step (i.e., MOF matching) is addressed and exemplified by propene/propane separation in this work. Computational MOF synthesis and screening are carried out to find new advanced material candidates for enhancing the separation process efficiency. First, model-based property-performance relationships are developed for fast MOF screening. Then, MOF building blocks are extracted from 471 CoRE MOFs. With these building blocks, 45472 hypothetical MOFs are created. After model-based and molecular simulation-based screening, six candidates are left and sent to P/VSA process optimization. Finally, three candidates are found to meet the pre-defined separation specifications and one candidate shows a better process performance than the best out of the 471 MOFs.

Surface pattern is a promising approach to enhance membrane performance while contradictory results have been reported on concentration polarization of patterned membranes. Here, we provide an experimental and modeling study of the concentration polarization on patterned membranes by varying pattern size, solute size, surface hydrophilicity and membrane orientation. Interesting trends were observed when comparing different membrane orientation, where relative concentration polarization degree (CPD) was found to be dependent on molecular weight. Salts and small organic molecules encountered more severe CPD in the transverse mode, while molecules larger than a threshold value showed a different trend. Such threshold molecular weight increased at larger pattern size. Simulation results were consistent with experimental observations, and revealed the critical role of diffusivity on such phenomena. Results also showed more severe concentration polarization on patterned membranes in both parallel and transverse modes in most cases, compared to smooth membrane.

Intercalated laminar membrane with controllable interlayer spacing (d-spacing) is one of the most effective membranes for fast molecule separation. In this work, we demonstrate a versatile strategy to create nanosheet-templated water channels in laminar graphene oxide (GO) membranes. The 1.2 nm-thick nickel hydroxide nanosheets as sacrificed intercalators provide a chance to control the d-spacing and simultaneously retain hydrophilicity. The resultant membranes have controllable channels and exhibit over 6 times higher water permeance than the unintercalated membrane. The 880 nm-thick nanosheet-templated GO (NST-GO) membrane has accurate d-spacing of about 1.14 nm and shows high water permeance of 120.3 L m−2 h−1 bar−1 and good molecule separation property, reflecting in high rejection for larger dyes (90.1% for erythrosine b (EB)), while low rejection for smaller dyes (58.3% for methylene blue (MB)). Furthermore, this strategy of intercalating and sacrificing nanosheets has higher potential than traditional intercalation in controlling d-spacing of laminar membranes.

Exploring highly active and stable electrocatalyst for oxygen evolution reaction is important for the development of water splitting and rechargeable metal-air batteries. Herein, a hybrid electrocatalyst of CoFe alloy and CoxN heterojunction encapsulated and embedded in N-doped carbon support (CoFe-CoxN@NC) was in situ coupling via a pyrolysis process of a novel coordination polymer from lignin biomacromolecule. CoFe-CoxN@NC exhibited an excellent OER activity with a low overpotential of 270 mV at 10 mA•cm−2 and stability with increment of 20 mV, comparable to commercial Ir/C. DFT calculations revealed that CoxN and N-doped grapheme encapsulation can reduce the binding strength between *O and CoFe alloy, prevent metals leaching and agglomeration, and improve electron transfer efficiency, thereby, remarkably enhancing the OER activity and stability. In situ coupling strategy of alloy and nitride heterojunction on N-doped lignin-derived carbon provided a promising and universal catalyst design for the development of renewable energy conversion technologies.

As a new type of gas-liquid microreactors, the gas-liquid mini-bubble column have potential applications. However, few studies on the flow fields in the mini-bubble column can be found at present. In this work, Particle Image Velocimetry (PIV) was first used to visually study the velocity fields, vorticity fields and bubble dynamics in the gas-liquid mini-bubble columns with column inner diameters of 1to 3 mm and mini-bubble diameters ranged from 0.7 to 1.3 mm. It is found that with the increase of superficial liquid velocity, bubbles rose from almost straight line to Z-shaped or S-shaped trajectory, and the bubble trajectory changed from 1-D to 3-D; when the bubble velocity changed, the bubble size and gas holdup decreased; bubble terminal velocity was controlled by bubble buoyancy and flow resistance, and increased slightly with bubble coalescence. These findings may provide basic reference for the design and scale-up of such mini-bubble column reactor.

Error-in-variables model (EVM) methods require information about input and output measurement variances when estimating model parameters. In EVM, using replicate experiments for estimating output measurement variances is complicated, because true values of inputs may be different when multiple attempts are made to repeat an experiment. To address this issue, we categorize attempted replicate experiments as: i) true replicates (TRs) when uncertain inputs are the same in replicated runs and ii) pseudo-replicates (PRs) when measured inputs are the same, but unknown true values of inputs are different. We propose methodologies to obtain output measurement variance estimates and associated parameter estimates for both situations. We also propose bootstrap methods for obtaining joint-confidence information for the resulting parameter estimates. A copolymerization case study is used to illustrate the proposed techniques. We show that different assumptions noticeably affect the uncertainties in the resulting reactivity-ratio estimates.

In this work, based on mathematical model inspired by transition state theory, the group contribution (GC) method is used to predict the viscosity of DESs. The model is constrained by Eyring rate theory and hard sphere free volume theory. A dataset of 2229 experimental measurements of the viscosity of 183 DESs from literature is used for determining the model parameters and subsequent verification of the model. The rules introduced by this model are simple and easy to understand. The results show that the proposed model is able to predict the DESs viscosity with very high accuracy, i.e., with an average absolute relative deviation of 8.12% over the training set and 8.64% over the test set, using only temperature and composition as inputs. The maximum absolute relative deviation is 34.63%. Therefore, the as-proposed model can be considered a highly reliable tool for predicting DESs viscosity when experimental data are absent.

Droplet breakup in micro-constrictions is an important phenomenon in industrial applications. This work aimed to investigate the droplet breakup in the square microchannel with a short square constriction to generate the slug flow, which drew little attention before. Mechanism analysis indicated that this breakup process included the shear-force-dominated, squeezing-force-dominated, and pinch-off stages. Non-uniform daughter droplets were generated in the constriction with their interface restricted in the horizontal and perpendicular directions by the microchannel walls. The average relative deviation of the daughter droplet size was < 30%, much lower than that for the breakup with the daughter droplet restricted only in one direction. An empirical equation with a deviation of < 20% was provided to show the dependence of the daughter droplet size on the operation conditions. The comparison results suggested that the different restriction effects of microchannel wall on daughter droplets led to the different breakup mechanisms in different constrictions.

Reactive polymer blending is basically a flow/mixing-driven process of interfacial generation, interfacial reaction for copolymer formation and morphology development. This work shows two antagonistic effects of mixing on this process: while mixing promotes copolymer formation by creating interfaces and enhancing collisions between reactive groups at the interfaces, excessive mixing may pull the in-situ formed copolymer out of the interfaces to one of the two polymer components of the blend, especially when the copolymer becomes highly asymmetrical. As such, the copolymer may loss its compatibilization efficiency. The mixing-driven copolymer pull-out from the interfaces is a catastrophic process (less than a minute), despite the high viscosity of the polymer blend. It depends on the molecular architecture of the reactive compatibilizer, polymer blend composition, mixing intensity and annealing. These findings are obtained using the concept of reactive tracer-compatibilizer and a model reactive polymer blend.