Integrated CO2 capture and conversion (ICCC) is a promising technology aiming at converting waste CO2 to fuels and high value-added chemicals. Herein, we described a proof-of-concept study of applying engineered natural ores (dolomite, magnesite, and limestone) to two different ICCC processes—intermediate-temperature ICCC for CH4 production (350–400°C) and high-temperature ICCC for syngas production

A predictive mathematical model for tablet dissolution was developed and implemented in an end-to-end integrated continuous manufacturing pilot plant. The tablets were produced for immediate release with a proprietary extrusion-molding-coating (EMC) unit operation. Besides the mass balance of API solute in the buffer solution, the model consisted of the dissolution, diffusion, and population balance

This work explores the use of thermodynamics-informed Gaussian processes (GPs) and active learning (AL) to model activity coefficients and construct phase diagrams. Relying on synthetic data generated from an excess Gibbs energy model, GPs were found to accurately describe the activity coefficients of several binary mixtures across large composition and temperature ranges. Moreover, GPs could estimate

The induction time for nucleation can differ based on the solutions used to conduct a crystallization, which can in turn impact the efficiency and economics of a crystallization process, the crystal size distribution, the morphology and ultimately functionality of the final product. Establishing a link between the nucleation pathway/solution structure and nucleation induction time is essential to achieve

Direct air capture of CO2 (DAC) has been increasingly recognized as a promising carbon-negative technology. The challenge in deploying energy-efficient DAC lies in effective sorbent materials. In this research, we comprehensively investigated the DAC behavior of LTA zeolites exchanged with different metal cations (Na+, K+, Mg2+, Ca2+, Mn2+, Co2+, Ni2+, Cu2+, Zn2+, Y3+, La3+, Ce3+, Eu3+, Tb3+, and Yb3+)

This study consists in the determination of two kinetic laws of urea oxidation (UO) and electrooxidation (UEO) in alkaline media on nickel(III). Two kinds of active sites were examined, the first one derived from a Ni(OH)2 powder and the second from a massive nickel electrode. Partial orders of nickel(III) (two for UO and five UEO) enable to conclude about (i) the urea adsorption on two nickel(III)

Model-based systems engineering (MBSE) is part of a long-term trend toward model-centric approaches adopted by many engineering disciplines. We establish the need of an MBSE approach by reviewing the importance, complexity, and vulnerability of the U.S. chemical supply chains. We discuss the origins, work processes, modeling approaches, and supporting tools of the systems engineering discipline (SE)

As key components of antifouling material surfaces, the design and screening of polymer molecules grafted on the substrate are critical. However, current experimental and computational models still retain an empirical flavor due to the complex structure of polymers. Here, we report a simple and general strategy that enables multiscale design and screening of easily synthesized functional polymer molecules

High tunability of both ionic liquids (ILs) and metal organic frameworks (MOFs) enables great opportunity in the rational designation of IL/MOF composites for physical adsorption and separation. Traditionally, cations and anions of ILs as an entirety are combined with MOFs either inside or outside the microchannels. Herein, organic cations of ILs were confined into Cu-BTC and the champion adsorbent

A new micro-kinetic model of the enzyme-catalyzed synthesis of fructo-oligosaccharides (FOS) was developed. A commercial enzyme mixture Pectinex® Ultra SP-L derived from Aspergillus aculeatus was used. A variety of initial enzyme concentrations (1–5 vol%) and sucrose concentrations (400–600 g/L) were experimentally investigated and included in kinetic modeling. Several variations of kinetic mechanisms

The constant molar overflow (CMO) framework, while useful for shortcut distillation models, assumes that all components have the same latent heats of vaporization. A simple transformation, from molar flows to latent-heat flows, allows shortcut models to retain the mathematical simplicity of the CMO framework while accounting for different latent heats, resulting in the constant heat transport (CHT)

The purpose of this work was to compare the performance of 7 meta-heuristics algorithms namely: Dragonfly (DA), Ant Lion (ALO), Grey Wolf (GWO), Artificial Bee Colony (ABC), Particle Swarm (PSO), Whale (WAO), and a hybrid Particle Swarm with Grey Wolf (HPSOGWO) optimizers in terms of fine-tuning hyper-parameters of a hybrid quantitative structure property relationships (QSPR)-support vector regression

We propose a framework that relies on machine learning techniques and statistical modeling to enhance industrial production planning. Supervised learning is employed to improve the production planning model, whereas unsupervised learning is used to achieve economic synchronization between the process control and production planning layers. Finally, an upgraded production planning decision-making structure

Intensified heat treatment, using direct contact condensation (DCC), is applied in the production of dairy products to ensure a high level of food safety. The key challenge with DCC is the fouling due to the protein reactions that limits operational efficiency and sustainability. Using a condensation regime map can improve operational decision-making. Pilot plant scale experiments were conducted for

Describing spatiotemporal evolution and characteristics of dispersed systems using the population balance equation (PBE), examples including sectional and moment methods are fraught with numerous issues. Hence, this study develops an accurate method by combining computational fluid dynamics and population balance-Monte Carlo method (CFD-PBMC) with a moderate computational cost. An efficient sub-model

Here, we propose a strategy for the global optimization of process flowsheets, a fundamental problem in process systems engineering, based on algebraic surrogates that are built from rigorous simulations via Bayesian symbolic regression. The applied method provides a closed-form expression that can be optimized to global optimality using state-of-the-art solvers, where BARON or ANTIGONE were the solvers

The construction of high-performance MOF-based hollow fiber composite membrane (HFCM) modules is a significant, yet challenging task for the biofuel production industry. In this study, a novel approach was taken to fabricate PDMS@ZIF-8/PVDF HFCMs in modules through a facile ZIF-8 self-crystallization synthesis followed by pressure-assisted PDMS infusion for pervaporation ethanol-water separation. The

As an important rate-determining step in the oxidation of methane, the catalytic behaviors of single-atom alloys (SAAs) on the CH activation reactions have not been fully understood. In this work, density functional theory calculations are performed to investigate the CH activation of methane on a series of SAAs with Cu(111/100) and Ag(111/100) as hosts. The reaction energies and the barriers for

The objective in this work is to propose a novel approach for solving inverse problems from the output space to the input space using automatic differentiation coupled with the implicit function theorem and a path integration scheme. A common way of solving inverse problems in process systems engineering (PSE) and in science, technology, engineering and mathematics (STEM) in general is using nonlinear

Precise simulation of the topology structure of low-density polyethylene (LDPE) chain is significant for product properties research. However, the chain structure symbolization methods in literature all rely on specially designed methods or temporary tricks, which are hard to understand and may induce some deviations in branch distribution prediction. To overcome this problem, a graph theory assisted

Petroleum catalytic pyrolysis to light olefin technology has received wide-ranging research interest in the refining industry. This work built a molecular kinetic model for the catalytic pyrolysis of a heavy gas oil from bitumen synthetic crude oil (SCO) to light olefins. A feedstock compositional model was constructed containing 1311 molecules using bulk properties information. A variety of reaction

We propose to fabricate a bifunctional photocatalyst for cooperative glycerol selective oxidation and H2 evolution. The key role of interface scale (nanometer, subnanometer, or atomic level) on tuning catalysis performance was revealed. Specifically, series Pt/defective TiO2 with tailored interface scale were constructed by loading Pt nanoparticle, cluster, and single atom on VTi-enriched TiO2. It

This study combines theoretical models with experiments to analyze the impurity migration mechanism and obtain the key factors of separation optimization for the design of layer melt crystallization. The fractal slice model was used to explore pore structure formation and calculate the heat properties of the crystal layer. It was found that the fractal characteristics approached the features of Euclidean

Process engineering applications such as heat transfer, reactions, and separations involve passing fluid through a porous medium. Historically, random-channel porous media have been used for these operations. Such systems do not represent optimal configurations for process performance because of poor flow distribution and high-pressure drop. It is now possible to fabricate porous monoliths with tailored

All-atom force fields are important for calculating interaction energies between growth units to predict crystal morphology. Our group at UCSB developed the ADDICT morphology design software to predict crystal morphology using mechanistic growth models driven by the generalized Amber force field (GAFF). In this study, the universal force field (UFF), the consistent force field (CFF), and the Coulomb-London-Pauli

In this work, we first solved the partial differential equation of the one-dimensional axial diffusion model in an open-source platform, that is, FEniCS, to explore the influence of the axial dispersion on the reaction yield-to-time profile. Then, we built an automatic platform, which included a photomicroreactor, a continuously controlled pump, a high-power UV-LED light source, an in-line visible-light

Accurately constructing membranes based on two-dimensional (2D) materials on commercial porous substrates remains a significant challenge for H2 purification. In this work, a series of tubular 2D MXene membranes are prepared on commercial porous stainless steel substrates via fast electrophoretic deposition. Compared with other methods, such as filtration or drop coating, and so on. such preparation

The experimental and simulation results indicate that the reverse Brazil nut effect (RBNE)-Brazil nut effect (BNE) segregation inversion happens faster in the circular-bottom container than that in the flat-bottom container. The starting location of the sinkage of heavier grains at the top layer is triggered with certain randomness in the latter, whereas it first occurs at either of the lateral edges

Petroleum molecular reconstruction method can be used to calculate molecular composition from limited analytical data, which is the basis of the molecular-level process modeling of petroleum refining. However, due to the problem of multiple solutions, it is difficult to obtain accurate and stable molecular compositional models. Therefore, based on the traditional bulk property constraints, composition

In recent years, cyber-security of networked control systems has become crucial, as these systems are vulnerable to targeted cyberattacks that compromise the stability, integrity, and safety of these systems. In this work, secure and private communication links are established between sensor–controller and controller–actuator elements using semi-homomorphic encryption to ensure cyber-security in model

The improvement of liquid dispersion by rotating wire mesh is one of the major causes for the mass transfer and micromixing intensification in rotating packed beds (RPBs). In particular, the initial dispersion region has been proved to have the greatest mass transfer and micromixing efficiency. However, the dispersion mechanism has not been revealed. This study investigated the dynamics of liquid dispersion

Accurate prediction of gas–liquid pressure drop is essential to microreactors design; however, the understanding of general rules of pressure drop in a wide gas–liquid flow ratio, especially smaller than 1.0, remains insufficient, Accordingly, this work systematically studies the pressure drop rule within the gas–liquid flow ratio of 0.2–2.0. The results show that, under a given gas velocity, the pressure

In this study, a three-dimensional coupled lattice Boltzmann model and cellular automata platform was developed to simulate biofilm growth and phenol biodegradation as an effective and sustainable way to remove phenolic contaminants in aquatic systems. Two three-dimensional bioreactors with cubic or spherical obstacles at varying inlet phenol concentrations and flow velocities were examined. The results

Mathematical modeling of mass transfer and absorption in the small intestine has been a challenging task. Systematic review and analysis of existing efforts indicate the need to pursue a reliable predictive model that is physically sound and computationally efficient. With the consideration of 3D intestinal inner wall structure, this work rigorously derives an absorption model that can be used as a

Enhancing the mass transfer performance just by modifying the channel structure without external energy input is one of the most important topics for microchemical technology development. This work reports the high-performance gas–liquid mass transfer in a novel step T-junction microchannel. The liquid-side mass transfer coefficient in the step T-junction has been significantly improved by one order

Biomass gasification combined with CO2 absorption-enhanced reforming (AER) in a bubbling fluidized bed (BFB) reactor is numerically studied via the multiphase particle-in-cell (MP-PIC) method featuring thermochemical and polydispersity sub-models. A novel bubble detection algorithm is proposed for efficiently characterizing bubble morphology. The effects of several crucial operating parameters on the

Organic synthesis facilitates the conversion of raw materials into high-value chemicals. Computer-assisted synthetic planning plays a vital role in designing synthetic pathways, which are usually evaluated by the reaction probability using deep learning models. However, this criterion is generally hard to describe real reaction behaviors such as reaction kinetics. Therefore, this article aims to establish

The use of machine learning in physicochemical properties modeling has great potential to accelerate the application of emerging materials. Deep eutectic solvents (DESs), an emerging class of solvents, are promising for applications as inexpensive “designer” solvents. Due to the unique structure of DESs, the hydrogen bond donor and hydrogen bond acceptor can be varied to create a mixture with specific

In this study, the mechanism of lithium extraction with β-diketones was investigated by resolving the reaction mechanism, thermodynamic property, and molecular interaction through density functional theory approach. Before the selective extraction of lithium, the β-diketones had tautomerism with the product of enol. The enol structure was unsteady in alkaline environment so that Li+ can be selectively

Separation and purification of light hydrocarbons have been the critical processes for producing basic chemicals and polymers in petrochemical industry. Adsorbents with high performance are highly demanded for the separation of light hydrocarbons. However, the adsorbents filling in the packed bed when evaluated will inevitably induce reduced performance and increased pressure drop that considerably

In chemical engineering, the Fischer–Speier esterification shows incredible value for biofuel production. However, the transformation suffers from challenges including necessary catalysts that cause corrosion issues in addition to a complex synthesis. Herein, we report a green acidic liquid, [N,N,N-tris(propanesulfonic)aniline][ethanol]3, which is induced by hydrogen bonding interactions between a

Metal oxide-based catalysts are widely studied in oxidative propane dehydrogenation (OPDH), but they usually suffered from the low olefin activity, which is believed to be related to the active centers of metal-oxygen species. Herein, we report an effective cation-exchange strategy towards the development of TiO2 nanosheets embedded isolated Fe species (Fe1TiO2) as a highly-active and stable catalyst

Classical molecular dynamics (MD) simulations were used to study the separation of carbon dioxide from methane by three formulations of the deep eutectic solvent (DES) ethaline (choline chloride: ethylene glycol at 1:2, 1:4, and 1:8 molar ratios), confined inside graphite and titania (rutile) slit pores of two different pore widths, 2 and 5 nm. In addition, equivalent DES systems in the bulk were studied

Granular materials exhibit unique secondary flow behaviors upon shearing. We demonstrate, using particle dynamics simulations, that the secondary flow patterns are controlled by a pressure exerted on particle bed. A threshold pressure, at which vortex flow transitions to disturbed or chaotic flow, depends on particle shape, that influences interparticle contacts and rheological performance. Our results

The authors have found some discrepancies in Tables 3, 4, and S3 in the original paper. These discrepancies arose due to human and systematic errors in the evaluation code. As a result, Tables 3, 4, and S3 are updated below to reflect the correct values. The evaluation functions and methods are reported in the original paper GitHub repository: https://urldefense.com/v3/__https://github.com/PEESEgr

Selective oxidation of alcohols to the carboxylic acid plays an important role in the production of valuable chemicals. Herein, NiCo hydroxide (NiCo(OOH)x) nanosheets with a thickness of ~4 nm were controllably fabricated in a facile way efficient for the electrooxidation of benzyl alcohol (BAL) to benzoic acid (BAD). Mechanistic studies confirmed the hydroxyl active intermediate (OH*) generated on

Cyclopropane derivates are appealing to synthesis of high-energy-density fuels because of the high strained energy of the three-numbered ring. The catalytic cyclopropanation of olefin with diazomethane is very effective to construct the carbocycle. The majority of the catalysts employed are nonrecyclable homogeneous compounds. Herein, we report cyclopropanation of polycyclic olefins catalyzed by heterogeneous

In the present work, a series of deep eutectic solvents (DESs) based on organic amine as hydrogen bond acceptors (HBAs), and ethylene glycol (EG) as hydrogen bond donor (HBD) were prepared for the H2S absorption. Thermal decomposition temperature, HBA mass ratios, alkalinity and structure effect on absorption behavior were systematically investigated. The reaction mechanism was demonstrated by FT-IR

Selective oxidation at low temperatures without alkali of biomass is a promising and sustainable avenue to manufacture glycolic acid (GA), a biodegradable functional material to protect the environment. However, producing glycolic acid with high selectivity and yield using the traditional research and development approach is time-consuming and labor-intensive. To this context, a hybrid deep learning

To realize highly efficient in situ release of hydrogen energy from methanol reforming at lower operation temperature, the introduction of solar energy can effectively activate the methanol and significantly reduce activation energy of reaction. Herein, the hierarchical integration of photoactive Cu2O/Cu7S4 core-shell nanospheres stabilized by MIL-101(Cr) support for H2 evolution from photothermal-driven

Ionic liquids (ILs) are promising solvents for the aromatic extraction process. An attractive characteristic is the existence of hundreds of ILs that exhibit different properties. To identify key properties of IL solvents for an energy-optimum aromatic extraction, we use process simulation to generate the process datasets for multivariate data analytics with partial least squares, and use science-guided

Selective acetylene hydrogenation is a strongly exothermic process, easy to cause coking and metal agglomeration, and thus leads to deactivation. In this work, Pd/TiO2 with different oxygen vacancies (Vo) were synthesized by controlling reduction temperature in 300–700°C, in which Pd/TiO2-HT300 (HT is reduction temperature) possessed the highest Vo content. It was found highly dispersed Pd nanoparticles

A robust aluminum-based metal–organic framework (Al-MOF) MIL-120Al with 1D rhombic ultra-microporous was reported. The nonpolar porous walls composed of para-benzene rings with a comparable pore size to the kinetic diameter of methane allow it to exhibit a novel thermodynamic-kinetic synergistic separation of CH4/N2 mixtures. The CH4 adsorption capacity was as high as 33.7 cm3/g (298 K, 1 bar), which

This work develops a transfer learning (TL) framework for modeling and predictive control of nonlinear systems using recurrent neural networks (RNNs) with the knowledge obtained in modeling one process transferred to another. Specifically, transfer learning uses a pretrained model developed based on a source domain as the starting point, and adapts the model to a target process with similar configurations

A facile and robust ultrasonic micromixer was developed to intensify antisolvent precipitation via ultrasonic cavitation. The gas supersaturation created from solvent–antisolvent mixing was found to be a novel driving force which facilitated the generation of cavitation bubbles (CBs). Instead of being attached on the channel wall, numerous CBs translated across the microchannel at a speed up to 1.7 m/s

Therapeutic monoclonal antibodies (mAbs) are typically manufactured using mammalian cell cultures in fed-batch bioreactors, with increasing emphasis on meeting productivity and product quality attribute targets that depend strongly on such process variables as nutrient feed rates and bioreactor operating conditions. In this article, we identify, categorize, and address the challenges of achieving both

The mesoporous carbon-supported metal catalysts are important materials in heterogeneous catalysis. From the standpoint of process intensification, the current synthesis methods still suffer from several issues, such as the excessive use of toxic solvents, the time-consuming self-assembly process, and the difficulty of continuous production. Herein, we report a solvent-free and continuous route to

In a simulated moving bed, the regeneration is accomplished by the introduction of a third species, the desorbent, which is later recovered by two downstream separations. As such, the choice of a proper adsorbent/desorbent pair is critical to ensure the effectiveness of the SMB process. While this can be done by comparing the separation region for each system, the computational effort required is extremely

We numerically study how rigid solid cylinders with a length over diameter aspect ratio of 10 settle through suspensions consisting of uniformly sized solid spheres and Newtonian liquid. We identify regimes with preference for horizontal settling and vertical settling of the cylinders dependent on the overall solids volume fraction (in the range of 0–0.58) and the Archimedes number of the cylinders

Modeling the uncertainty in partial least squares (PLS) is made difficult because of the nonlinear effect of the observed data on the latent space that the method finds. We present an approach, based on bootstrapping, that automatically accounts for these nonlinearities in the parameter uncertainty, allowing us to equally well represent confidence intervals for points lying close to or far away from