Showing papers in "Aiche Journal in 2017"
TL;DR: In this article, the current state-of-the-art with focus on enabling technologies for reaction and separation equipment is summarized and highlighted as promising applications of microreactor technology.
Abstract: Over the past two decades, microreaction technology has matured from early devices and concepts to encompass a wide range of commercial equipment and applications. This evolution has been aided by the confluence of microreactor development and adoption of continuous flow technology in organic chemistry. This Perspective summarizes the current state-of-the art with focus on enabling technologies for reaction and separation equipment. Automation and optimization are highlighted as promising applications of microreactor technology. The move towards continuous processing in pharmaceutical manufacturing underscores increasing industrial interest in the technology. As an example, end-to-end fabrication of pharmaceuticals in a compact reconfigurable system illustrates the development of on-demand manufacturing units based on microreactors. The final section provides an outlook for the technology, including implementation challenges and integration with computational tools. AIChE J, 2017 © 2016 American Institute of Chemical Engineers AIChE J, 63: 858–869, 2017
340 citations
TL;DR: A novel data-driven adaptive robust optimization framework that leverages big data in process industries is proposed and a Bayesian nonparametric model—the Dirichlet process mixture model—is adopted and combined with a variational inference algorithm to extract the information embedded within uncertainty data.
Abstract: A novel data-driven adaptive robust optimization framework that leverages big data in process industries is proposed. A Bayesian nonparametric model—the Dirichlet process mixture model—is adopted and combined with a variational inference algorithm to extract the information embedded within uncertainty data. Further a data-driven approach for defining uncertainty set is proposed. This machine-learning model is seamlessly integrated with adaptive robust optimization approach through a novel four-level optimization framework. This framework explicitly accounts for the correlation, asymmetry and multimode of uncertainty data, so it generates less conservative solutions. Additionally, the proposed framework is robust not only to parameter variations, but also to anomalous measurements. Because the resulting multilevel optimization problem cannot be solved directly by any off-the-shelf solvers, an efficient column-and-constraint generation algorithm is proposed to address the computational challenge. Two industrial applications on batch process scheduling and on process network planning are presented to demonstrate the advantages of the proposed modeling framework and effectiveness of the solution algorithm. © 2017 American Institute of Chemical Engineers AIChE J, 63: 3790–3817, 2017
130 citations
TL;DR: A rational design and synthesis of covalent organic frameworks (COFs) displaying efficient adsorption of surrogates for common organic pollutants is demonstrated in this article, where the top performing mesoporous triazine-functionalized polyimide COF exhibits superior adaption of the small dye molecule methylene blue, achieving a maximum adsoption capacity of ∼1691 mg g−1 (∼169 wt %), surpassing the performance of all previously reported nanoporous adsorbents.
Abstract: A rational design and synthesis of covalent organic frameworks (COFs) displaying efficient adsorption of surrogates for common organic pollutants is demonstrated herein. Significantly, the top performing mesoporous triazine-functionalized polyimide COF exhibits superior adsorption of the small dye molecule methylene blue, achieving a maximum adsorption capacity of ∼1691 mg g−1 (∼169 wt %), surpassing the performance of all previously reported nanoporous adsorbents. The experimental results and accompanying in silico simulations suggest that both the size of the organic dye molecules and the intrinsic pore-size effect of the COF material should be taken into account simultaneously for the construction of COF-based adsorbents with efficient dyes adsorption capacities. The structural diversity of COF materials along with the understanding of the encapsulation of organic dyes on COFs holds great promise for developing novel COF adsorbents for the efficient removal of organic pollutants from wastewater. © 2017 American Institute of Chemical Engineers AIChE J, 63: 3470–3478, 2017
117 citations
TL;DR: In this paper, the authors review several drivers for modular production, and evaluate modular production architectures based on the value density of feedstock resources and markets for the products of a process, and discuss the links between modularization and process intensification.
Abstract: Chemical companies are constantly seeking new, high-margin growth opportunities, the majority of which lie in high-grade, specialty chemicals, rather than in the bulk sector. In order to realize these opportunities, manufacturers are increasingly considering decentralized, flexible production facilities: large-scale production units are uneconomical for innovative products with a short lifespan and volatile markets. Small modular plants have low financial risks, are flexible and can respond rapidly to changes in demand. Logistics costs can be also reduced by moving production closer to customers and/or sources of raw materials. Moreover, stricter safety regulations can in many cases be more easily met using smaller distributed facilities.
Modularization of chemical production can thus have potentially significant economic and safety ben- efits. In this article, we review several drivers for modular production, and evaluate modular production architectures based on the value density of feedstock resources and markets for the products of a process. We also discuss the links between modularization and process intensification. We illustrate the discussion with an array of industrial examples, which we also use to motivate a summary of challenges and future directions for this area. This article is protected by copyright. All rights reserved.
116 citations
TL;DR: In this paper, a data-driven approach for optimization under uncertainty based on multistage adaptive robust optimization (ARO) and nonparametric kernel density M-estimation is proposed.
Abstract: A novel data-driven approach for optimization under uncertainty based on multistage adaptive robust optimization (ARO) and nonparametric kernel density M-estimation is proposed. Different from conventional robust optimization methods, the proposed framework incorporates distributional information to avoid over-conservatism. Robust kernel density estimation with Hampel loss function is employed to extract probability distributions from uncertainty data via a kernelized iteratively reweighted least squares algorithm. A data-driven uncertainty set is proposed, where bounds of uncertain parameters are defined by quantile functions, to organically integrate the multistage ARO framework with uncertainty data. Based on this uncertainty set, we further develop an exact robust counterpart in its general form for solving the resulting data-driven multistage ARO problem. To illustrate the applicability of the proposed framework, two typical applications in process operations are presented: The first one is on strategic planning of process networks, and the other one on short-term scheduling of multipurpose batch processes. The proposed approach returns 23.9% higher net present value and 31.5% more profits than the conventional robust optimization method in planning and scheduling applications, respectively. © 2017 American Institute of Chemical Engineers AIChE J, 63: 4343–4369, 2017
110 citations
TL;DR: In this paper, UiO-66-NH2 nanoparticles were surface modified with long alkyl chains and used in the preparation of TFN membranes with ultrathin MOF@polyamide layer.
Abstract: Preparation of defect-free and optimized thin film nanocomposite (TFN) membranes is an effective way to enhance the process of organic solvent nanofiltration. However, it still remains a great challenge due to poor filler particle dispersibility in organic phase and compatible issue between fillers and polymers. Aiming at these difficulties, UiO-66-NH2 nanoparticles were surface modified with long alkyl chains and used in the preparation of TFN membranes. As a result, defect-free TFN membranes with ultrathin MOF@polyamide layer were successfully prepared benefited from the improved particle dispersibility in n-hexane. Significant enhancement was found in methanol permeance after nanoparticle incorporation, without comprising the tetracycline rejection evidently. Especially, the novel TFN membrane prepared with organic phase solution containing 0.15% (w/v) modified UiO-66-NH2 nanoparticles showed a superior methanol permeance of 20 L·m−2·h−1·bar−1 and a tetracycline rejection of about 99%, which is appealing to the application in pharmaceutical industry for example. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1303–1312, 2017
101 citations
TL;DR: In this paper, a general and scalable fabrication of nanoparticles (NPs)@reduced graphene oxide (rGO) membranes with significantly expanded nanochannels meanwhile ordered laminar structures using in situ synthesized NPs@rGO nanosheets as building blocks is reported.
Abstract: Developing advanced membranes with high separation performance and robust mechanical properties is critical to the current water crisis. Herein, a general and scalable fabrication of nanoparticles (NPs)@reduced graphene oxide (rGO) membranes with significantly expanded nanochannels meanwhile ordered laminar structures using in situ synthesized NPs@rGO nanosheets as building blocks is reported. Size- and density-controllable NPs were uniformly grown on the regularly stacked rGO nanosheets through coordination, followed by filtration-deposition on inner surface of porous ceramic tubes. The NPs bonded rGO building blocks enabled the as-prepared membranes 1–2 orders of magnitudes higher water permeance than the counterparts while keeping excellent rejections for various organic matters and ions. Moreover, the industrially preferred GO-based tubular membrane exhibited an extraordinary structural stability under high-pressure and cross-flow process of water purification, which is considered as a notable step toward realizing scalable GO-based membranes. © 2017 American Institute of Chemical Engineers AIChE J, 2017
99 citations
TL;DR: In this article, a spatially-averaged two-fluid model (SA-TFM) is derived from ensemble averaging the kinetic-theory based TFM equations, and the residual correlation for the gas-solid drag, which appears due to averaging, is derived by employing a series expansion to the microscopic drag coefficient, while the Reynolds-stress-like contributions are closed similar to the Boussinesq-approximation.
Abstract: We present a spatially-averaged two-fluid model (SA-TFM), which is derived from ensemble averaging the kinetic-theory based TFM equations. The residual correlation for the gas-solid drag, which appears due to averaging, is derived by employing a series expansion to the microscopic drag coefficient, while the Reynolds-stress-like contributions are closed similar to the Boussinesq-approximation. The subsequent averaging of the linearized drag force reveals that averaged interphase momentum exchange is a function of the turbulent kinetic energies of both, the gas and solid phase, and the variance of the solids volume fraction. Closure models for these quantities are derived from first principles. The results show that these new constitutive relations show fairly good agreement with the fine grid data obtained for a wide range of particle properties. Finally, the SA-TFM model is applied to the coarse grid simulation of a bubbling fluidized bed revealing excellent agreement with the reference fine grid solution. © 2017 American Institute of Chemical Engineers AIChE J, 63: 3544–3562, 2017
93 citations
91 citations
TL;DR: In this paper, a reaction mechanism was proposed for hydrolytic dehydrogenation of ammonia borane on a Pt/CNT catalyst, where the main reaction was NH3BH3+4H2O→NH4++B(OH)4−+3H2↑, involving the B-H, B-N, and O-H bond cleavages.
Abstract: A reaction mechanism is proposed for hydrolytic dehydrogenation of ammonia borane on a Pt/CNT catalyst. A combination of thermodynamic analysis and FTIR measurement reveals that B-containing byproducts are mainly in the form of an NH4B(OH)4-B(OH)3 mixture rather than NH4BO2 reported previously. The revised main reaction is NH3BH3+4H2O→NH4++B(OH)4−+3H2↑, involving the B–H, B–N, and O–H bond cleavages. Isotopic experiments using D2O instead of H2O as reactant or introducing D2 into the reaction atmosphere suggest the O–H bond cleavage being in the rate-determining step, and an unfavorable occurrence of the chemisorbed H2O dissociation (i.e., the direct O–H bond cleavage), respectively. Different reaction pathways with indirect O–H bond cleavages are analyzed, and then NH3BH2*+H2O*→NH3BH2(OH)*+H* is suggested as the rate-determining step. Subsequently, a Langmuir–Hinshelwood kinetic model is developed, which fits well with the experimental data. © 2016 American Institute of Chemical Engineers AIChE J, 63: 60–65, 2017
88 citations
TL;DR: In this article, a two-dimensional model of a fixed-bed tube reactor for carbon dioxide methanation was developed based on the reaction scheme of the underlying exothermic Sabatier reaction mechanism.
Abstract: Utilizing volatile renewable energy sources (e.g., solar, wind) for chemical production systems requires a deeper understanding of their dynamic operation modes. Taking the example of a methanation reactor in the context of power-to-gas applications, a dynamic optimization approach is used to identify control trajectories for a time optimal reactor start-up avoiding distinct hot spot formation. For the optimization, we develop a dynamic, two-dimensional model of a fixed-bed tube reactor for carbon dioxide methanation which is based on the reaction scheme of the underlying exothermic Sabatier reaction mechanism. While controlling dynamic hot spot formation inside the catalyst bed, we prove the applicability of our methodology and investigate the feasibility of dynamic carbon dioxide methanation. © 2016 American Institute of Chemical Engineers AIChE J, 63: 23–31, 2017
TL;DR: This article introduces a novel moving horizon closed-loop scheduling approach that consists of periodic schedule updates that reflect updated price and demand forecasts, and event-driven updates that account for process and market disturbances.
Abstract: The economic circumstances that define the operation of chemical processes (e.g., product demand, feedstock and energy prices) are increasingly variable. To maximize profit, changes in production rate and product grade must be scheduled with increased frequency. To do so, process dynamics must be considered in production scheduling calculations, and schedules should be recomputed when updated economic information becomes available. In this article, this need is addressed by introducing a novel moving horizon closed-loop scheduling approach. Process dynamics are represented explicitly in the scheduling calculation via low-order models of the closed-loop dynamics of scheduling-relevant variables, and a feedback connection is built based on these variables using an observer structure to update model states. The feedback rescheduling mechanism consists of, (a) periodic schedule updates that reflect updated price and demand forecasts, and, (b) event-driven updates that account for process and market disturbances. The theoretical developments are demonstrated on the model of an industrial-scale air separation unit. © 2016 American Institute of Chemical Engineers AIChE J, 63: 639–651, 2017
TL;DR: This work develops design dependent multi-parametric model predictive controllers that are able to provide the optimal control actions as functions of the system state and the design of the process at hand via the recently introduced PAROC framework1.
Abstract: We present a framework for the application of design and control optimization via multiparametric programming through four case studies. We develop design dependent multi-parametric model predictive controllers that are able to provide the optimal control actions as functions of the system state and the design of the process at hand, via our recently introduced PAROC framework1. The process and the design dependent explicit controllers undergo a Mixed Integer Dynamic Optimization (MIDO) step for the determination of the optimal design. The result of the MIDO is the optimal design of the process under optimal operation. We demonstrate the framework through case studies of a tank, a continuously stirred tank reactor, a binary distillation column and a residential cogeneration unit. This article is protected by copyright. All rights reserved.
TL;DR: In this article, an extensive database of estimated Henry's law constants of twelve gases in more than ten thousand ILSs at 313.15 K is established using the COSMO-RS method.
Abstract: Ionic liquids (ILs) have attracted considerable attention in both the academic and industrial communities for absorbing and separating gases. However, a data-rich and well-structured systematic database has not yet been established, and screening for highly efficient ILs meeting various requirements remains a challenging task. In this study, an extensive database of estimated Henry's law constants of twelve gases in more than ten thousand ILs at 313.15 K is established using the COSMO-RS method. Based on the database, a new systematic and efficient screening method for IL selection for the absorption and separation of gases subject to important target properties is proposed. Application of the database and the screening method is highlighted through case studies involving two important gases separation problems (CO2 from CH4 and C2H2 from C2H4). The results demonstrate the effectiveness of using the screening method together with the database to explore and screen novel ILs meeting specific requirements for the absorption and separation of gases. VC 2017 American Institute of Chemical Engineers AIChE J, 63: 1353-1367, 2017
TL;DR: An optimal modulated hydrothermal (MHT) synthesis of a highly stable zirconium metal-organic framework (MOF) with an optimum aperture size of 3.93 A that is favorable for CO2 adsorption was reported in this paper.
Abstract: We herein report an optimal modulated hydrothermal (MHT) synthesis of a highly stable zirconium metal-organic framework (MOF) with an optimum aperture size of 3.93 A that is favorable for CO2 adsorption. It exhibits excellent CO2 uptake capacities of 2.50 and 5.63 mmol g−1 under 0.15 and 1 bar at 298 K, respectively, which are among the highest of all the pristine water-stable MOFs reported so far. In addition, we have designed a lab-scale breakthrough set-up to study its CO2 capture performance under both dry and wet conditions. The velocity at the exit of breakthrough column for mass balance accuracy is carefully measured using argon with a fixed flow rate as the internal reference. Other factors that may affect the breakthrough dynamics, such as pressure drop and its impact on the roll-up of the weaker component have been studied in details. © 2017 American Institute of Chemical Engineers AIChE J, 63: 4103–4114, 2017
TL;DR: The proposed local model order-reduction technique is applied to a hydraulic fracturing process described by a nonlinear parabolic PDE system with the time-dependent spatial domain and is shown to be more accurate and computationally efficient in approximating the original nonlinear system with fewer eigenfunctions.
Abstract: In this work, we present a temporally-local model order-reduction technique for nonlinear parabolic partial differential equation (PDE) systems with time-dependent spatial domains. In lieu of approximating the solution of interest using global (with respect to the time domain) empirical eigenfunctions, we derive low-dimensional models by constructing appropriate temporally-local eigenfunctions. Within this context, we partition the time domain into multiple clusters (i.e. subdomains) by using the framework known as global optimum search (GOS). This approach, a variant of Generalized Benders Decomposition (GBD), formulates clustering as a Mixed-Integer Nonlinear Programming problem and involves the iterative solution of a Linear Programming problem (primal problem) and a Mixed-Integer Linear Programming problem (master problem). Following the cluster generation, local (with respect to time) eigenfunctions are constructed by applying the proper orthogonal decomposition (POD) method to the snapshots contained within each cluster. Then, the Galerkin's projection method is employed to derive low-dimensional ordinary differential equation (ODE) systems for each cluster. The local ODE systems are subsequently used to compute approximate solutions to the original PDE system. The proposed local model order-reduction technique is applied to a hydraulic fracturing process described by a nonlinear parabolic PDE system with the time-dependent spatial domain. It is shown to be more accurate and computationally efficient in approximating the original nonlinear system with fewer eigenfunctions, compared to the model order-reduction technique with temporally-global eigenfunctions. This article is protected by copyright. All rights reserved.
TL;DR: In this article, a Rh1/TiO2 single-atom catalyst (SAC) with appreciable loading of 0.37 wt % exhibited an overall CO conversion of ∼95% but without any methanation at 300°C, even under CO2-and H2-rich WGS stream.
Abstract: Water-gas shift (WGS) reaction is an important process for industrial hydrogen production. The side reaction of methanation often causes unavoidable loss of H2 along with this reaction. Here, we report a Rh1/TiO2 single-atom catalyst (SAC) with appreciable loading of 0.37 wt %, which exhibited an overall CO conversion of ∼95% but without any methanation at 300°C, even under CO2- and H2-rich WGS stream. The specific activity of this SAC was around four times higher than that of cluster catalyst, which meanwhile suffered from unfavorable methanation. It was found that Rh single atoms promoted the formation of more oxygen vacancies on the TiO2 support to activate H2O to generate H2 and prohibited the dissociation of H2 compared with Rh clusters, leading to the enhanced activity and selectivity for WGS. © 2016 American Institute of Chemical Engineers AIChE J, 63: 2081–2088, 2017
TL;DR: In this paper, an ammonia-based energy storage system is proposed to achieve high round-trip efficiency, low cost, and considerable flexibility for integrating intermittent renewables on the utility scale.
Abstract: Chemicals-based energy storage is promising for integrating intermittent renewables on the utility scale. High round-trip efficiency, low cost, and considerable flexibility are desirable. To this end, an ammonia-based energy storage system is proposed. It utilizes a pressurized reversible solid-oxide fuel cell for power conversion, coupled with external ammonia synthesis and decomposition processes and a steam power cycle. A coupled refrigeration cycle is utilized to recycle nitrogen completely. Pure oxygen, produced as a side-product in electrochemical water splitting, is used to drive the fuel cell. A first-principle process model extended by detailed cost calculation is used for process optimization. In this work, the performance of a 100 MW system under time-invariant operation is studied. The system can achieve a round-trip efficiency as high as 72%. The lowest levelized cost of delivered energy is obtained at 0.24 $/kWh, which is comparable to that of pumped hydro and compressed air energy storage systems. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1620–1637, 2017
TL;DR: The potential of diesel particulate filters wash-coated with highly dispersed nano-metric ceria particles for continuous regeneration has been investigated in this article, where catalytic filters were prepared, soot-loaded (avoiding the formation of the cake layer), and regenerated under isothermal conditions.
Abstract: The potential of diesel particulate filters wash-coated with highly dispersed nano-metric ceria particles for continuous regeneration has been investigated. To this end, catalytic filters were prepared, soot-loaded (avoiding the formation of the cake layer), and regenerated—under isothermal conditions—at temperature ranging from 200–600°C. Results have shown that catalytic oxidation of soot starts from 300°C and, at all temperatures, the selectivity to CO2 is higher than 99%. 475°C is the minimum temperature at which the filter is regenerated via catalytic path. At this temperature, the catalytic filter maintains substantially the same performance over repeated cycles of soot loading and regeneration, indicating that the thermal stability of ceria is preserved. This has been further confirmed by comparison between the outcomes obtained from characterization (X-ray powder diffraction, N2 adsorption at 77 K, Hg intrusion porosimetry, and scanning electron microscope/energy dispersive X-ray analysis) of fresh filter and filter subjected to repeated regeneration tests. © 2017 American Institute of Chemical Engineers AIChE J, 63: 3442–3449, 2017
TL;DR: A hybrid meta-heuristic method is presented that was able to provide the lowest costs solutions reported so far to six cases well studied in the literature and was written in C++, which is free and faster when compared to many other languages.
Abstract: Heat Exchanger Network (HEN) synthesis is an important field of study in process engineering. However, obtaining optimal HEN design is a complex task. When mathematically formulated, it may require sophisticated methods to achieve good solutions. The complexity increases even more for large-scale HEN. In this work, a hybrid meta-heuristic method is presented. A rather simple Simulated Annealing approach is used for the combinatorial level, while a strategy named Rocket Fireworks Optimization is developed and applied to the continuous domain. An advantage over other approaches is that the algorithm was written in C++, which is free and faster when compared to many other languages. The developed method was able to provide the lowest costs solutions reported so far to six cases well studied in the literature. An important feature of the approach here proposed is that, differently from other approaches, it does not split HEN into smaller problems during the optimization. This article is protected by copyright. All rights reserved.
TL;DR: In this article, the enhancement of physical absorption of carbon dioxide by Fe3O4-water nanofluid under the influence of AC and DC magnetic fields was investigated, and a gas-liquid mass transfer model for single bubble systems was applied to predict mass transfer parameters.
Abstract: In this study, the enhancement of physical absorption of carbon dioxide by Fe3O4-water nanofluid under the influence of AC and DC magnetic fields was investigated. Furthermore, a gas-liquid mass transfer model for single bubble systems was applied to predict mass transfer parameters. The coated Fe3O4 nanoparticles were prepared using co-percipitation method. The results from characterization indicated that the nanoparticles surfaces were covered with hydroxyl groups and nanoparticles diameter were 10–13 nm. The findings showed that the mass transfer rate and solubility of carbon dioxide in magnetic nanofluid increased with an increase in the magnetic field strength. Results indicated that the enhancement of carbon dioxide solubility and average molar flux gas into liquid phase, particularly in the case of AC magnetic field. Moreover, results demonstrated that mass diffusivity of CO2 in nanofluid and renewal surface factor increased when the intensity of the field increased and consequently diffusion layer thickness decreased. © 2016 American Institute of Chemical Engineers AIChE J, 63: 2176–2186, 2017
TL;DR: In this article, the authors investigated the energy efficiency of domestic fabricated ultrasonic microreactors, where cavitation bubbles were generated under the ultrasonic field, which undergo vigorous translational motion and surface oscillation with different modes.
Abstract: Intensification of liquid mixing was investigated in domestic fabricated ultrasonic microreactors. Under the ultrasonic field, cavitation bubbles were generated, which undergo vigorous translational motion and surface oscillation with different modes (volume, shape oscillation, and transient collapse). These cavitation phenomena induce intensive convective mixing and reduce the mixing time from 24–32 s to 0.2–1.0 s. The mixing performance decreases with the channel size, due to the weaker cavitation activity in smaller channel. The energy efficiency is comparable to that of the conventional T-type and higher than the Y-type and Caterpillar microreactors. Residence time distribution was also measured by a stimulus-response experiment and analyzed with axial dispersion model. Axial dispersion was significantly reduced by the ultrasound-induced radial mixing, leading to the increasing of Bo number with ultrasound power. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1404–1418, 2017
TL;DR: In this article, the performance of five different catalysts (Pt-Bi/AC, PtBi/ZSM-5, Pt/MCM-41, Pt-Bi-doped-MCM/41, and Pt/Bi-Doped-MP-41) was investigated experimentally.
Abstract: It is important to utilize glycerol, the main by-product of biodiesel, to manufacture value-added chemicals such as 1,3-dihydroxyacetone (DHA). In the present work, the performance of five different catalysts (Pt-Bi/AC, Pt-Bi/ZSM-5, Pt/MCM-41, Pt-Bi/MCM-41, and Pt/Bi-doped-MCM-41) was investigated experimentally, where Pt-Bi/MCM-41 was found to exhibit the highest DHA yield. To better understand the experimental results and to obtain insight into the reaction mechanism, density functional theory (DFT) computations were conducted to provide energy barriers of elementary steps. Both experimental and calculated results show that for high DHA selectivity, Bi should be located in an adatom-like configuration Pt, rather than inside Pt. A favorable pathway and catalytic cycle of DHA formation were proposed based on the DFT results. A cooperative effect, between Pt as the primary component and Bi as a promoter, was identified for DHA formation. Both experimental and theoretical considerations demonstrate that Pt-Bi is efficient to convert glycerol to DHA selectively. © 2016 American Institute of Chemical Engineers AIChE J, 63: 705–715, 2017
TL;DR: In this article, the effect of bridged organoalkoxysilanes on network pore size and microporous structure was evaluated by examining the molecular size and temperature dependence of gas permeance across a wide range of temperatures.
Abstract: Organosilica membranes were fabricated using bridged organoalkoxysilanes (bis(triethoxysilyl)methane (BTESM), bis(triethoxysilyl)ethane (BTESE), bis(triethoxysilyl)propane (BTESP), bis(trimethoxysilyl)hexane (BTMSH), bis(triethoxysilyl)benzene (BTESB), and bis(triethoxysilyl)octane (BTESO)) to produce highly permeable molecular sieving membranes. The effect of the organoalkoxysilanes on network pore size and microporous structure was evaluated by examining the molecular size and temperature dependence of gas permeance across a wide range of temperatures. Organosilica membranes showed H2/N2 and H2/CH4 permeance ratios that ranged from 10 to 150, corresponding to network pore size, and both H2 selectivity decreased with an increase in the carbon number between 2 Si atoms. Organosilica membranes showed activated diffusion for He and H2, and a slope of temperature dependence that increased approximate to the increase in the carbon number between 2 Si atoms. The relationship between activation energy and He/H2 permeance ratio for SiO2 and organosilica membranes suggested that the molecular sieving can dominate He and H2 permeation properties via the rigid microporous structure, which was constructed by BTESM and BTESE. With increased in the carbon concentration in silica, polymer chain vibration in organic bridges, which is a kind of solution/diffusion mechanism, can dominate the permeation properties. © 2017 American Institute of Chemical Engineers AIChE J, 63: 4491–4498, 2017
TL;DR: In this paper, a comparative assessment of four cavitation devices (3 venturis and an orifice) in terms of cavitational yield is presented, viz CFD simulations of cavitating flow, simulations of individual cavitation bubble dynamics, high speed photographs of cavitation flow and model reaction of potassium iodide oxidation.
Abstract: This study presents comparative assessment of four cavitation devices (3 venturis and an orifice) in terms of cavitational yield A 4-fold approach was adopted for assessment, viz CFD simulations of cavitating flow, simulations of individual cavitation bubble dynamics, high speed photographs of cavitating flow and model reaction of potassium iodide oxidation Influence of design parameters of cavitation devices on nature of cavitation produced in the flow was studied Number density of cavitation bubbles in the flow and interactions among bubbles had critical influence on cavitation yield Orifice gave the highest cavitational yield per unit energy dissipation in flow (despite lower working inlet pressure) due to low density of cavitation bubbles in flow On contrary, occurrence of large cavitation bubble clouds in venturi flow had adverse effect on cavitational yield due to high interactions among cavitation bubbles resulting in inter-bubble coalescence and recombination of oxidizing radicals generated from cavitation bubbles This article is protected by copyright All rights reserved
TL;DR: In this article, a series of Pd/FeOx catalysts were detected for water gas shift reaction on supported noble metal catalysts is an essential process for upgrading hydrogen source industrially.
Abstract: Water gas shift reaction on supported noble metal catalysts is an essential process for upgrading hydrogen source industrially. Here a series of Pd/FeOx catalysts were detected for this reaction with Pd/Al2O3 as reference. It was found that Pd/FeOx exhibited higher CO conversion than Pd/Al2O3 with a good stability even in the presence of CO2 and H2. Along the loading decreasing, the turnover frequency of exposed Pd atoms increased with the dispersion from subnanometer (∼1 nm) to single atoms. Various characterizations suggested that Pd single atoms greatly enhanced the reducibility of FeOx and facilitated the formation of oxygen vacancies, which served as sites to promote the dissociation of H2O to form H2 and atomic O. The atomic O was ready to react with the linear adsorbed CO species on Pd single-atom sites through a redox mechanism, which resulted in low activation energy of ∼30 kJ mol−1. © 2017 American Institute of Chemical Engineers AIChE J, 63: 4022–4031, 2017
TL;DR: In this article, the effect of particle shape on pressure drop, heat transfer and reaction performance was analyzed in a cylindrical packed bed with tube to particle diameter ratio of 1.4, containing 10 particles.
Abstract: Numerical simulations of a cylindrical packed bed with tube to particle diameter ratio of 1.4, containing 10 particles, were performed to understand the effect of particle shape on pressure drop, heat transfer and reaction performance. Six particle shapes namely, cylinder as the reference, trilobe and daisy having external shaping, hollow cylinder, cylcut, and 7-hole cylinder including internal voids were chosen. Methane steam reforming reactions were considered for the heat transfer and reaction performance evaluation. The present study showed that the external shaping of particles offered lower pressure drop, but lower values of effectiveness factor indicating strong diffusion limitations. The internally shaped particles offered increased surface area, led to higher effectiveness factor and allowed to overcome the diffusion limitations. The effective heat transfer and effectiveness factor of the trilobe-shaped particle per unit pressure drop was found to be the best among the particle shapes considered in the present work. © 2016 American Institute of Chemical Engineers AIChE J, 63: 366–377, 2017
TL;DR: In this article, the adsorption process of iodine, a major volatile radionuclide in the off-gas streams of spent nuclear fuel reprocessing, on hydrogen-reduced silver-exchanged mordenite (Ag0Z) was studied at the micro-scale.
Abstract: The adsorption process of iodine, a major volatile radionuclide in the off-gas streams of spent nuclear fuel reprocessing, on hydrogen-reduced silver-exchanged mordenite (Ag0Z) was studied at the micro-scale. The gas-solid mass transfer and reaction involved in the adsorption process were investigated and evaluated with appropriate models. Optimal conditions for reducing the silver-exchanged mordenite (AgZ) in a hydrogen stream were determined. Kinetic and equilibrium data of iodine adsorption on Ag0Z were obtained by performing single-layer adsorption experiments with experimental systems of high precision at 373–473 K over various iodine concentrations. Results indicate approximately 91% to 97% of the iodine adsorption was through the silver-iodine reaction. The effect of temperature on the iodine loading capacity of Ag0Z was discussed. In conclusion, the Shrinking Core model describes the data well, and the primary rate controlling mechanisms were macro-pore diffusion and silver-iodine reaction. © 2016 American Institute of Chemical Engineers AIChE J, 2016