Packed bed microreactors offer a promising platform for intensifying heterogeneously catalyzed reactions. To understand hydrodynamics therein, N2 or water flow was investigated experimentally through microreactors packed with glass beads in this work, corresponding to a microreactor to particle diameter ratio (D/d) of 1.29–25.12. The porosity of a single pellet string microreactor (D/d < 1.866) agrees

Structured catalysts exhibit the advantages of high diffusion efficiency and low heat transfer resistance, which have attracted increasing attention to non‐adiabatic gas–solid process. However, the metal‐supported coating catalysts face the problems of weaker bond strength and severe sintering, especially under the conditions of large flow rate and high temperature. Herein, metal@Silicalite‐1 structured

Solar‐driven photocatalysis is a promising strategy for clean hydrogen (H2) generation cooperated with selective organic synthesis. Lignin, rich in aromatic units and functional groups, serves as an ideal hole sacrificial agent and substrate, facilitating H2 evolution and yielding high‐value chemicals/fuels. To boost overall photocatalytic redox efficiency, thermal catalysis was further combined to

Purifying ultra‐high purity propylene (>99.995%) with an energy‐efficient adsorptive separation method is a promising yet challenging technology that remains unfulfilled. Instead of solely considering the effect of adsorbents on guest molecules, we propose a synergistic adsorption mechanism for the deep removal of propane and propyne, utilizing supramolecular interactions in both “host‐guest” and “guest‐guest”

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Liquid holdup is a crucial factor in the study of hydrodynamic behaviors in the micro‐packed bed reactor (μPBR). In this work, the values of liquid holdup are studied with the weighing method with good accuracy. The packed bed is a tube made of stainless steel with a length of 20 cm and an inner diameter of 4 mm, packed with 177–250 μm or 350–500 μm microbeads. The gas and liquid flow rates vary from

The integrated design of the heat exchanger network (HEN) and organic Rankine cycle (ORC) system with new working fluids is a complex optimization problem. It involves navigating a vast design space across working fluid molecules, ORC processes, and networks. In this article, a new two‐stage reverse strategy is developed. The optimal HEN‐ORC configurations and operating conditions, and the thermodynamic

Despite the practical importance, 3D measurements of gas–solid distribution in fluidized beds calls for further breakthroughs. Here an approach combing a recently developed mobile electrical capacitance tomography (ECT) sensor with Fourier Neural Operator (FNO) is developed, in which the fluidized bed is divided into a series of cross‐sectional slices along axial direction. At any given instant, the

Conventional testing of novel contrast agents for magnetic resonance imaging (MRI) involves cell and animal studies. However, 2D cultures lack dynamic flow and in vivo MRI is limited by regulatory approval of long-term anesthesia use. Microfluidic tumor models (MTMs) offer a cost-effective, reproducible, and high throughput platform for bridging cell and animal models. Yet, MRI of microfluidic devices

Vapor–liquid phase equilibrium (VLE) plays a crucial role in chemical process design, process equipment control, and experimental process simulation. However, experimental acquisition of VLE data is a challenging and complex task. As an alternative to experimentation, VLE data prediction offers great convenience and utility. In this article, an artificial intelligence network is proposed to predict

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Nanoscale wettability, crucial for various disciplines in science and engineering, challenges traditional theory, particularly the Young's equation. This study proposes and validates a modified format of the Young's equation under nano‐confinement and, for the first time, the nano‐confined droplet morphological evolution and transition are investigated from thermodynamic theories and molecular dynamics

Chemical reactions between carbon dioxide (CO) and amine have been extensively characterized, however, their influence on the dynamics of polyamines remains largely unexplored. In this work, we compare the dynamics of polyethylenimine (PEI) before and after CO absorption through broadband dielectric spectroscopy (BDS). The molecular processes of bulk PEI are very different from those of thin film PEI

The study investigates effect of particle shape on gas bypassing and mixing of gas‐fluidized Geldart A particles. A shallow fluidized bed (FB), configured at benchscale, was used with digital image analysis (DIA) for the investigation. The extent of scatter of tracer particles throughout the bed was assessed from DIA images of defluidized powder. A novel method employing Jupyter notebook software,

This article demonstrates a parameter estimation technique for bioprocesses that utilizes measurement noise in experimental data to determine credible intervals on parameter estimates, with this information of potential use in prediction, robust control, and optimization. To determine these estimates, the work implements Bayesian inference using nested sampling, presenting an approach to develop neural

Process heat electrification offers the prospect of deep decarbonization of the chemical and allied industries. Replacing fossil fuel‐fired boilers with electric units can reduce carbon emissions if the power mix has a large share of renewables. For multinational firms with plants in multiple locations, the electrification decisions should be scheduled based on grid carbon intensity projections and

Although eutectic solvents (ESs) have garnered significant attention as promising solvents for carbon dioxide (CO2) capture, systematic studies on discovering novel ESs linking machine learning (ML) and experimental validation are scarce. For the reliable prediction of CO2‐in‐ES solubility, ensemble ML modeling based on random forest and extreme gradient boosting with inputs of COSMO‐RS derived molecular

An open research question lies in how machine learning (ML) can accelerate the design optimization of chemical processes which are at very early experimental development stage with limited data availability. As an example, this article investigates the design of an intensified microwave‐assisted ammonia production reactor with 46 experimental data. We present an integrated approach of neural networks

This study employed titanium catalysts to degrade low‐quality PET (polyethylene terephthalate) bottle flakes and subsequently re‐polymerized the degradation solution to investigate whether the titanium catalyst could restore the physical and chemical properties of the degraded PET bottle flakes. The reaction process of property restoration was characterized using GPC, DSC, ICP, NMR, and so forth. The

This study investigated the hydrodynamics of highly viscous liquid under vertical acoustic vibration, and examined the effects of vibration parameters and filling ratio on the strain rate, stretching index, and convective intensity of high‐viscosity liquid. A numerical simulation model of gas–liquid flows was developed using computational fluid dynamics method and validated through experiment. Under

The objective of this study is to develop ionic liquids (ILs) derived from organophosphorus acids, featuring thermomorphic phase behavior tailored for homogeneous liquid–liquid extraction applications, addressing the challenges posed by the high viscosity of ILs. The novelty of our work includes a logP‐based guideline for designing thermomorphic water/organophosphorus IL solvent systems and a proof‐of‐concept

In porous media, the transport and flow through the void phase are influenced by the internal pore network due to its complex morphology. In other words, the contributions of individual pores can vary due to their connectivity within the network and characteristics in physical phenomena. In this study, we propose a pore classification method according to geometries and physical behaviors to understand

Electrochemical nitrate reduction reaction (NO3RR) is considered a promising strategy for ammonia synthesis and nitrate removal, in which catalyst development is crucial. Herein, a series of bimetal (Co and Cu) anchoring porous MXene nanosheets (CoxCuy@PM) catalysts were prepared by combining etching and reduction strategy. On the one hand, Cu and Co bimetals provided tandem catalytic active sites

In modern chemical engineering production, numerous elastoplastic materials, often formed into agglomerates, frequently undergo plastic deformation and rupture. Understanding how these materials behave under different conditions is crucial for improving manufacturing processes and material design. In this work, an elastoplastic beam bond model for discrete element method (DEM) simulation was developed

As a significant industrial material, MgO is mainly obtained by the pyrolysis of magnesite (magnesium carbonate) under air conditions, producing large amounts of CO2 and contributing to global warming. In this work, the MgO was prepared using the hydrogenation reduction method. The reaction conditions led to CO2 emissions of <1% and an overall temperature decrease of ~80°C. The highly active MgO prepared

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The identification of highly productive cell lines is crucial in the development of bioprocesses for the production of therapeutic monoclonal antibodies (mAbs). Metabolomics data provide valuable information for cell line selection and allow the study of the relationship with mAb productivity and product quality attributes. We propose a novel robust machine learning procedure which, exploiting dynamic

Here, commercial carbon black (CB) grades are characterized in detail to determine the link between their physicochemical properties and solar steam generation performance. The CB nanoparticles used here have surface mean primary particle diameters of 11–406 nm resulting in specific surface areas of 8–300 m2/g. Thermogravimetric analysis, dynamic light scattering, Raman spectroscopy, and x-ray diffraction

The significance of easily detecting rare earth elements (REEs) has increased due to the growing demand for REEs. Addressing this need, we present an innovative electrochemical biosensor, focusing on cerium as a model REE. This biosensor utilizes a modified EF-hand loop peptide sequence, incorporating cysteine for covalent attachment to a gold working electrode and tyrosine as an electrochemically

Micromixing in chemical reactors can be characterized through test reactions that are sensitive to mixing. A new pair of parallel competitive reactions, including acid–base neutralization and diethyl oxalate hydrolysis, is proposed in this work. It has clear principles and high sensitivity to micromixing with quantitative accuracy and operational simplicity. The measurement results obtained from stopped‐flow

MXenes doped with non‐metallic and transition metal elements exhibit remarkable potential as catalysts in the hydrogen energy. Nonetheless, efficiently identifying viable materials from a vast array of candidates remains a formidable challenge. Here, we conducted density functional theory (DFT) calculations to obtain the hydrogen adsorption free energy () of 78 types of doped TiVCO2 MXene catalysts

We propose a methodological framework to quantify the relative abundance of key surface intermediates via analysis of the macroscopic intrinsic kinetic characteristics of gas-phase data. At the core of this approach is the development of analytical expressions, which link reaction orders and activation energies in macroscopic power law models to the fractional coverage of the non-observable intermediates

The design of monovalent cation selective membranes for precise separation requires a comprehensive understanding of the geometry and chemical environment of the transport channels. Here, a charged cation transfer channel with sub‐1‐nanometer is constructed by layer‐by‐layer self‐assembly of layered double hydroxides. To effectively improve the separation performance, the thickness of the membrane

Mesoscale bubble dynamics play a critical role in governing the overall performance of gas-liquid-solid systems. In this study, the volume of fluid method coupled with a discrete element method is utilized to scrutinize the mesoscale bubble dynamics within a gas-liquid-solid system featuring a dense particle bed. The results reveal that the squeezing effect of the particle bed induces a bubble pairs

CFD‐PBM numerical simulation is a powerful tool in the research of droplet swarm behavior. In this work, an artificial neural network (ANN) based droplet breakage frequency function is established based on the directly measured data from our previous studies. Then, the weights and biases of ANN are embedded into the CFD‐PBM code in the form of matrices and vectors. For the first time, a CFD‐PBM‐ANN

Optimizing charging protocols is critical for reducing battery charging time and decelerating battery degradation in applications such as electric vehicles. Recently, reinforcement learning (RL) methods have been adopted for such purposes. However, RL‐based methods may not ensure system (safety) constraints, which can cause irreversible damages to batteries and reduce their lifetime. To this end, this

Synergistic Pd–In2O3 catalysts are promising candidates for producing methanol via CO2 hydrogenation, and the metal phases in them can be tuned by thermal reduction treatment affecting the catalytic activity significantly. This work presents a comprehensive investigation to gain an insight into the effect of thermal reduction temperature on the variation and interaction of Pd and In2O3 phases supported

Many next-generation materials for Li-ion batteries are limited by material instabilities. To stabilize these materials, ultrathin, protective coatings are needed that conduct both lithium ions and electrons. Here, we demonstrate a hybrid chemistry combining molecular layer deposition (MLD) of trimethylaluminum (TMA) and p-hydroquinone (HQ) with oxidative molecular layer deposition (oMLD) of molybdenum

Excavating highly efficient and cost-effective non-noble metal single-atom catalysts for electrocatalytic CO2 reduction reaction (CO2RR) is of paramount significance. However, the general and universal strategy for designing atomically dispersed metals as accessible active sites is still in its infancy. Herein, we reported a general sol–gel pore-confined strategy for preparing a series of isolated

Exploring the molecular mechanisms underlying insulin analogs is important for protein engineering to design innovative drug proteins. Insulin aspart (IAsp) and insulin degludec (IDeg) are representative examples of insulin analogs with distinct release profiles synthesized by targeted mutagenesis in protein engineering. Despite their importance in diabetes treatment, there remains a gap in our understanding

The synthesis of large-scale integrated water networks is typically formulated as nonconvex mixed-integer quadratic constrained programming (MIQCP) or QCP problems. With the complexity arising from bilinear terms in modeling mass flows of contaminants and binary variables representing the presence of units or streams, numerous local optima exist, thus presenting a significant optimization challenge

Mixed matrix membranes (MMMs) combining functional fillers with polymer matrices hold promise for high-efficiency separation. However, it remains a great challenge to enhance the loading to fully harness the capabilities of the fillers. Herein, we introduced RUB-15 nanosheets as fillers for MMMs to approach parallel alignment of nanosheets within the matrix, thus achieving a high-loading rate of up

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The application of machine learning (ML) techniques in materials science has revolutionized the pace and scope of materials research and design. In the case of metal–organic frameworks (MOFs), a promising class of materials due to their tunable properties and versatile applications in gas adsorption and separation, ML has helped survey the vast material space. This study explores the integration of

A dispersed plug flow heterogeneous photocatalytic reactor is investigated. A two-dimensional (2D) model adapted to the media, a photocatalyst supported on a macroporous ceramic foam, was built. It is based on the couplings at the local scale between mass transfer, radiative transfer, and reaction kinetics. The simulations are compared to experimental results obtained in the case of the degradation

Chromatographic separation processes are described by nonlinear partial differential and algebraic equations, which may result in high computational cost, hindering further online applications. To decrease the computational burden, different data-driven modeling approaches can be implemented. In this work, we investigate different strategies of data-driven modeling for chromatographic processes, using

This study introduces an approach to enhance the Raman calibration model cross-scale prediction capabilities in cell cultures. Our investigation centers on the improvement of Raman calibration models along with the scaling-up of mammalian cell culture processes. Initially, we observed that integrating data from a 50 L run into the original dataset at lab-scale was an effective strategy for improving

The recent advancement in mechanically and chemically robust membranes has led to the capabilities of both reverse osmosis (RO) and pervaporation (PV) for separation of water/organic solvent and organic solvent mixtures. However, their performances are evaluated in different permeation formulas. To address this, we have conducted an analysis using a unified parameter: activity-based permeance. The

Optimal control over fast chemical processes hinges on the achievement of rapid and effective mixing. Impinging jet mixers are a unique class of passive mixing devices renowned for their exceptional ability to achieve rapid mixing at micro-length scales, whilst offering the possibility of a high throughput. Comprising of two co-linear jets flowing in opposite directions and colliding with each other

An optimal process plant layout needs to ensure that the associated piping and land costs are minimized, while the overall safety is maximized. Although various approaches to optimizing plant layout exists in the literature, none considers the essential need for simultaneous compliance with local risk regulations. Employing mixed-integer nonlinear programming, this article presents a methodology to

In vivo, migrating cells often encounter microenvironments that impose spatial constraints, leading to cell and nuclear deformation. As confinement-induced DNA damage has been linked to the accumulation of reactive oxygen species (ROS), we sought to investigate the impact of oxidative stress on cell behavior within confined spaces. Using microchannel devices that enable control of the degree and duration

This work reported the application of a twin-column recycling chromatography system for the separation of three minor impurities in crude aloe-emodin. The whole process went through three steps, each using a different mobile phase to separate corresponding impurity, which were integrated and automatically operated in a single device. Despite these impurities peaked closely in high-performance liquid

Numerous nonlinear distributed parameter systems (DPSs) operate within an extensive range due to process uncertainties. Their spatial distribution characteristic, combined with nonlinearity and uncertainty, poses challenges in optimal operation under two-step real-time optimization (RTO) and economic model predictive control (EMPC). Both methods necessitate substantial computational power for prompt

The flow distribution issue is of significance to the fuel cell stack performance and durability, which herein is studied from a theoretical and practical level. The manifold flow fundamentals are clarified and the pressure-reconstruction-based principle to regulate flow distribution is revealed. The prerequisite and corequisite lie in the ratio of pressure drop between headers and the entire manifold

Dual reflux pressure swing adsorption (DR-PSA) has been regarded as a state-of-the-art adsorption-based process which can simultaneously obtain two streams of pure product gases with a narrow pressure window. However, the DR-PSA has not yet been reported in industrial applications. Herein, a DR-PSA and a heavy-purge pressure vacuum swing adsorption (HP-PVSA) were numerically investigated for the enrichment

Direct CH4 to CH3OH conversion is a long-standing grand challenge in catalysis. We present one-step steam reforming of methane to methanol (OSRMtM) by combining an atmospheric pressure CH4/H2O/Ar plasma with a Cu/Mordenite (Cu/MOR) catalyst at 170°C, achieving 77% CH3OH selectivity with 3.0% CH4 conversion. Catalyst characterization and plasma diagnostics, as well as D2O and H218O-labeled isotope tracer

This study introduces two novel Reinforcement Learning (RL) agents for the design and optimization of chemical process flowsheets (CPFs): a discrete masked Proximal Policy Optimization (mPPO) and a hybrid masked Proximal Policy Optimization (mHPPO). The novelty of this work lies in the use of masking within the hybrid framework, i.e., the incorporation of expert input or design rules that allows the

The Fe-Pd bifunctional heterogeneous electro-Fenton catalyst is an attractive option for the degradation of phenol wastewater. However, the catalyst faces issues such as inadequate yield of H2O2 on the Pd species and poor durability. In this study, we developed a bifunctional Fe-Pd catalyst with Zn embedded into a mesh-type γ-Al2O3/Al support (ZnxFePd/γ-Al2O3/Al). The characterization results indicate

Micro-packed bed reactors, due to their high mass and heat transfer efficiency, and inherent safety, have significant advantages in processes such as hydrogenation reactions, debenzylation reactions, and catalyst screening. Despite extensive studies on gas–liquid two-phase flow in micro-packed beds, research on gas–liquid–liquid three-phase flow remains limited. This study investigates the mass transfer

Porous liquids (PLs) are a novel material that combines the advantages of porous solids and liquid fluidity. In this study, we propose an imprinted porous liquid (IPL) with imprinted polymers as the porous framework and a mixture of TOP + FeCl3 as sterically hindered solvents. Quantum chemical computations and characterization results demonstrate the presence of unoccupied pore structure in IPLs. The