Influence of earth gravity on reaction engineering of tubular reactor for high concentration tungsten ion-exchange

The influence of gravity on the reaction engineering of tubular reactor is studied by analyzing the residence time distribution curves.The results show that upflow-feeding mode is more beneficial compared with downflow-feeding mode,since the flow pattern of the fluid in the reactor is closer to plug flow.The result of dynamic experiment conducted in ion-exchange of tungsten metallurgy is as good as that in reaction engineering of ion-exchange column.Whether downflow-feeding or upflow-feeding mode is adopted,breakthrough time decreases when solution concentration increases.Upflow-feeding mode has longer breakthrough time and greater improvement in adsorption capacity especially with high WO3 concentration in ion-exchange.

AN ENGINEERING MODEL FOR MULTICOMPONENT REVERSIBLE REACTION NETWORK

The treatment of a multicomponent reversible reaction network is extremely complicated because largenumber of rate constants must be precisely determined and because the calculation based on these rateconstants is tedious.In order to reduce the degrees of freedom of the process,the authors propose a methodin which the reactor and the separator are regarded as a whole.Based on this approach,an N-componentreversible reaction system can be dealt with as a two—component system.Consequently,a simple and ac-cessible way of the apparent rate determination is suggested.For fiist-order reactions,an explicit,simplifiedexpression has been derived for both lumped and distributed parameter reaction systems.

Synthesis methods and powder quality of titanium monocarbide

Titanium monocarbide(TiC),which is the most stable titanium-based carbide,has attracted considerable interest in the fields of energy,catalysis,and structural materials due to its excellent properties.Synthesis of high-quality TiC powders with low cost and high efficiency is crucial for industrial applications;however major challenges face its realization.Herein,the methods for synthesizing TiC powders based on a reaction system are reviewed.This analysis is focused on the underlying mechanisms by which synthesis methods affect the quality of powders.Notably,strategies for improving the synthesis of highquality powders are analyzed from the perspective of enhancing heat and mass transfer processes.Furthermore,the critical issues,challenges,and development trends of the synthesis technology and application of high-quality TiC powder are discussed.

Highly dispersed MgInCe-mixed metal oxides catalyzed direct carbonylation of glycerol and CO_(2)into glycerol carbonate

Glycerol carbonate,an important glycerol value-added product,has been widely used as an active intermediate and inert solvent in the synthesis of cosmetics,detergents,chemical intermediates,polymers,and so on.The direct carbonylation from glycerol with CO_(2)is considered a promising route,but still tough work due to the thermodynamic stability and the kinetic inertness of CO_(2).In this work,highlyselective direct carbonylation of glycerol and CO_(2)into glycerol carbonate has been achieved over highly dispersed MgInCe-mixed metal oxides(MgInCe-MMO),which were prepared through the topological transformation derived from the MgInCe-layered double hydroxides(MgInCe-LDHs).By precisely modulating the surface basic-acidic properties and the oxygen vacancies,an efficient carbonylation of glycerol with CO_(2)has been achieved with a selectivity of up to>99%to glycerol carbonate.Deep investigation into the synergistic catalysis of base-acid sites and oxygen vacancies has been clarified.

Machine Learning in Chemical Engineering:Strengths,Weaknesses,Opportunities,and Threats

Chemical engineers rely on models for design,research,and daily decision-making,often with potentially large financial and safety implications.Previous efforts a few decades ago to combine artificial intelligence and chemical engineering for modeling were unable to fulfill the expectations.In the last five years,the increasing availability of data and computational resources has led to a resurgence in machine learning-based research.Many recent efforts have facilitated the roll-out of machine learning techniques in the research field by developing large databases,benchmarks,and representations for chemical applications and new machine learning frameworks.Machine learning has significant advantages over traditional modeling techniques,including flexibility,accuracy,and execution speed.These strengths also come with weaknesses,such as the lack of interpretability of these black-box models.The greatest opportunities involve using machine learning in time-limited applications such as real-time optimization and planning that require high accuracy and that can build on models with a self-learning ability to recognize patterns,learn from data,and become more intelligent over time.The greatest threat in artificial intelligence research today is inappropriate use because most chemical engineers have had limited training in computer science and data analysis.Nevertheless,machine learning will definitely become a trustworthy element in the modeling toolbox of chemical engineers.

Effects of zinc on χ-Fe_(5)C_(2) for carbon dioxide hydrogenation to olefins:Insights from experimental and density function theory calculations

Production of light olefins from CO_(2), the primary greenhouse gases, is of great importance to mitigate the adverse effects of CO_(2) emission on environment and to supply the value-added products from nonpetroleum resource. However, development of robust catalyst with controllable selectivity and stability remains a challenge. Herein, we report that Zn-promoted Fe catalyst can boost the stable and selective production of light olefins from CO_(2). Specifically, the Zn-promoted Fe exhibits a highly stable activity and olefin selectivity over 200 h time-on-stream compared to the unpromoted Fe catalyst, primarily owing to the preservation of active χ-Fe_(5)C_(2) phase. Structural characterizations of the spent catalysts suggest that Zn substantially regulates the content of iron carbide on the surface and suppresses the reoxidation of bulk iron carbide during the reaction. DFT calculations confirm that adsorption of surface carbon atoms and graphene-like carbonaceous species are not thermochemically favored on Zn-promoted Fe catalyst. Carbon deposition by CAC coupling reactions of two surface carbon atoms and dehydrogenation of CH intermediate are also inhibited. Furthermore, the effects of Zn on antioxidation of iron carbide were also investigated. Zn favored the hydrogenation of surface adsorbed oxygen atoms to H_(2)O and the desorption of H_(2)O, which reduces the possibility of surface carbide being oxidized by the chemisorbed oxygen.

Multivariable Nonlinear Proportional-Integral-Derivative Decoupling Control Based on Recurrent Neural Networks

A nonlinear proportional-integral-derivative (PID) controller is constructed based on recurrent neural networks. In the control process of nonlinear multivariable systems, several nonlinear PID controllers have been adopted in parallel. Under the decoupling cost function, a decoupling control strategy is proposed. Then the stability condition of the controller is presented based on the Lyapunov theory. Simulation examples are given to show effectiveness of the proposed decoupling control.

Research on Ce-Zr compounds on modifying γ-alumina washcoat on FeCrAl foils

Ce-Zr compounds such as Cc0.68Zr0.3202 solid solution, Ce/Zr nitrate and CeO2/ZrO2 were added into γ-alumina-based slurries, which were then loaded on FeCrAl foils pretreated at 950℃ and 1100℃. The microstructures and adhesion performance between the substrates and the washcoats were measured by SEM, BET surface area, ultrasonic vibration and thermal shock test. The results show that the addition of Ce0.68Zr0.32O2 solid solution, Ce/Zr nitrate and CeO2/ZrO2 into the slurries can improve γ-Al2O3-based washcoat adhesion on FeCrAl foils. Furthermore, ceria-zirconia solid solution increases the adhesion of the washcoat on the surface of an FeCrAl foil than the two others. The specific surface area of this washcoat remains about 4345 m^2/g and the weight loss is below 4.0% even after aging test of 10% steam-containing air at 1050℃ for 20 h.

A micro-sphere catalyst complex with nano CaCO_3 precursor for hydrogen production used in ReSER process

This paper describes the preparation and evaluation of a micro-sphere catalytic complex for the hydrogen production in a Reactive Sorption Enhanced Reforming （ReSER） process. The catalytic complex made by a spray technique has a dual function containing Ni as a catalytic material and CaO as an adsorption material used in the ReSER process. The attrition characteristics of the catalytic complex are acceptable for the commercial used. The nano GaCO3 material used as a precursor of CaO showed a desirable durability with a CO2 sorption capacity of 0.6 mol CO2/kg after 10 repeating cycles under the carbonation temperature of 600 ℃, a CO2 partial pressure of 0.02 MPa, and a calcination temperature of 750 ℃ in N2 measured by a thermal gravimetric analyzer. The testing of the catalytic complex for ReSER showed a hydrogen yield of over 95 % （v/v） in the laboratory fixed fluidized bed reactor. The catalytic system has an attractive prospect in the ReSER process for hydrogen production, especially in the fluidized mode where reactor and regenerator combined in a cycling process.

Numerical simulation and combination optimization of aluminum holding furnace linings based on simulated annealing

To reduce heat loss and save cost, a combination decision model of reverb aluminum holding furnace linings in aluminum casting industry was established based on economic thickness method, and was resolved using simulated annealing. Meanwhile, a three-dimensional mathematical model of aluminum holding furnace linings was developed and integrated with user-defined heat load distribution regime model. The optimal combination was as follows: side wall with 80 mm alumino-silicate fiber felts, 232 mm diatomite brick and 116 mm chamotte brick; top wall with 50 mm clay castables, 110 mm alumino-silicate fiber felts and 200 mm refractory concrete;and bottom wall with 232 mm high-alumina brick, 60 mm clay castables and 68 mm diatomite brick. Lining temperature from high to low was successively bottom wall, side wall, and top wall. Lining temperature gradient in increasing order of magnitude was refractory layer and insulation layer. It was indicated that the results of combination optimization of aluminum holding furnace linings were valid and feasible, and its thermo-physical mechanism and cost characteristics were reasonably revealed.

Modeling and Control of Nonlinear Discrete-time Systems Based on Compound Neural Networks

An adaptive inverse controller for nonliear discrete-time system is proposed in this paper. A compound neural network is constructed to identify the nonlinear system, which includes a linear part to approximate the nonlinear system and a recurrent neural network to minimize the difference between the linear model and the real nonlinear system. Because the current control input is not included in the input vector of recurrent neural network (RNN), the inverse control law can be calculated directly. This scheme can be used in real-time nonlinear single-input single-output (SISO) and multi-input multi-output (MIMO) system control with less computation work. Simulation studies have shown that this scheme is simple and affects good control accuracy and robustness.

Mass transfer coefficients in metallurgical reactors

An overview on the application and achievements of physico-mathematicalmodeling of metallurgical processes in China is briefly declared. The important role of coefficientsin model formulation is shown from our experience. The mass transfer coefficients of the slag-metalreactions and the gas-metal reactions are discussed referring to the flow conditions near theinterface. The influence of the surface-active species on the mass transfer and the interfacialreaction is also discussed briefly.

Preliminary Exploration of the Reactor Configuration for Hydroformylation of 1-Dodecene Catalyzed by Water Soluble Rhodium Complex

Hydroformylation of 1-dodecene was studied in a biphasic systemusing water-soluble rhodium complex [RhCl(CO)(TPPTS)_2] as catalystin the presence of cetyl trimethyl ammonium bromide as surfactant toenhance the reaction rate. Efforts were devoted to improve theperformance of hydroformylation by exploring reactor configurationwhich enhanced the mixing, dispersion and interphase mass transfer.Experiments were carried out in a 0.5 L autoclave at the totalpressure of 1.1 Mpa and temperature from 363 K to 373 K.

A perspective of the engineering applications of carbon-based selenium-containing materials

Carbon-based selenium-containing materials are novel materials just being invented recently.Owing to the low cost and bio-compatible features of carbon and selenium,these materials are practical.The unique chemical-and bio-activities of selenium endow them wide range of applications in catalysis,environment-protection,fertilizer and biocide development etc.Recent progresses in this field are summarized and prospected from the engineering application viewpoint in this mini-review.

CFD modeling using heterogeneous reaction kinetics for catalytic dehydrogenation syngas reactions in a fixed-bed reactor

A comprehensive 2D computational fluid dynamics （CFD） model was developed to simulate the flow behavior and catalytic dehydrogenation reaction of syngas in a heterogenous fixed-bed reactor （FBR）. The model combined the porous medium CFD model with a reaction kinetics model. To acquire an accu- rate reaction kinetics model, a comprehensive reaction mechanism was studied for the heterogeneous catalytic dehydrogenation reaction ofsyngas over a supported metal catalyst. Based on the reaction mech- anism and a statistical test, a reliable kinetics model was proposed. The CFD model combined with the above kinetics model was validated with one set of experimental data. The CFD model was also used to predict key reaction variable distributions such as the temperature and the component concentrations in the reactor.

Issues and strategies of cathode materials for mild aqueous static zinc-ion batteries

Researchers prefer mild aqueous static zinc-ion batteries(ASZIBs)for their distinct benefits of excellent safety,abundant zinc resources,low cost,and high energy density.However,at the moment there are some issues with the cathode materials of mild ASZIBs,including dissolution,by-products,poor conductivity,and a contentious energy storage system.Consequently,there are numerous difficulties in the development of high-performance mild ASZIBs cathode materials.This overview examines the mechanisms for storing energy and the de-velopments in inorganic,organic,and other novel cathode materials that have emerged in recent years.At the same time,three solutions—structural engineering,interface engineering,and reaction pathway engineering—as well as the difficulties now faced by the cathode materials of mild ASZIBs are forcefully introduced.Finally,a prospect is made regarding the evolution of cathode materials in the future.

Numerical investigation of droplet pre-dispersion in a monodisperse droplet spray dryer

Monodisperse droplet spray dryers have great advantages in particle formation through spray drying because of their ability to produce uniform sized particles. Experimental analyses of this system have shown that droplets atomized through the piezoceramic nozzle need to be sufficiently well dispersed before entering the drying chamber to achieve sufficiently dried particles. However, the dispersion dynamics cannot be readily observed because of experimental limitations, and key factors influencing the dispersion state currently remain unclear. This study carried out numerical simulations for droplet dispersions in the dispersion chamber, which allow this important process to be visualized. The system- atic and quantitative analyses on the dispersion states provide valuable data for improving the design of the dispersion chamber, and optimizing the spray drying operation.

A spatially distributed,deterministic approach to modeling Typha domingensis(cattail)in an Everglades wetland

Introduction:The emergent wetland species Typha domingensis(cattail)is a native Florida Everglades monocotyledonous macrophyte.It has become invasive due to anthropogenic disturbances and is out-competing other vegetation in the region,especially in areas historically dominated by Cladium jamaicense(sawgrass).There is a need for a quantitative,deterministic model in order to accurately simulate the regional-scale cattail dynamics in the Everglades.Methods:The Regional Simulation Model(RSM),combined with the Transport and Reaction Simulation Engine(TARSE),was adapted to simulate ecology.This provides a framework for user-defineable equations and relationships and enables multiple theories with different levels of complexity to be tested simultaneously.Five models,or levels,of increasing complexity were used to simulate cattail dynamics across Water Conservation Area 2A(WCA2A),which is located just south of Lake Okeechobee,in Florida,USA.These levels of complexity were formulated to correspond with five hypotheses regarding the growth and spread of cattail.The first level of complexity assumed a logistic growth pattern to test whether cattail growth is density dependent.The second level of complexity built on the first and included a Habitat Suitability Index(HSI)factor influenced by water depth to test whether this might be an important factor for cattail expansion.The third level of complexity built on the second and included an HSI factor influenced by soil phosphorus concentration to test whether this is a contributing factor for cattail expansion.The fourth level of complexity built on the third and included an HSI factor influenced by(a level 1–simulated)sawgrass density to determine whether sawgrass density impacted the rate of cattail expansion.The fifth level of complexity built on the fourth and included a feedback mechanism whereby the cattail densities influenced the sawgrass densities to determine the impact of inter-species interactions on the cattail dynamics.Results:All the simulation results from the different levels of complexity were compared to observed data for the years 1995 and 2003.Their performance was analyzed using a number of different statistics that each represent a different perspective on the ecological dynamics of the system.These statistics include box-plots,abundance-area curves,Moran’s I,and classified difference.The statistics were summarized using the Nash-Sutcliffe coefficient.The results from all of these comparisons indicate that the more complex level 4 and level 5 models were able to simulate the observed data with a reasonable degree of accuracy.Conclusions:A user-defineable,quantitative,deterministic modeling framework was introduced and tested against various hypotheses.It was determined that the more complex models(levels 4 and 5)were able to adequately simulate the observed patterns of cattail densities within the WCA2A region.These models require testing for uncertainty and sensitivity of their various parameters in order to better understand them but could eventually be used to provide insight for management decisions concerning the WCA2A region and the Everglades in general.