Liquid-phase adsorption has hardly been established in micro-flow, although this constitutes an industrially vital method for product separation. A micro-flow UV-photo isomerization process converts cis-cyclooctene partly into trans-cyclooctene, leaving an isomeric mixture. Trans-cyclooctene adsorption and thus separation was achieved in a fixed-bed micro-flow reactor, packed with AgNO3/SiO2 powder, while the cis-isomer stays in the flow. The closed-loop recycling-flow has been presented as systemic approach to enrich the trans-cyclooctene from its cis-isomer. In-flow adsorption in recycling-mode has hardly been reported so that a full theoretical study has been conducted. This insight is used to evaluate three process design options to reach an optimum yield of trans-cyclooctene. These differ firstly in the variation of the individual residence times in the reactor and separator, the additional process option of refreshing the adsorption column under use, and the periodicity of the recycle flow.
During the course of a pressure relief discharge from a vessel containing a multicomponent liquid mixture, composition changes occur that affect the properties vessel contents. In this work, a model of the dynamic relief process for ternary, non-ideal, homogeneous mixtures is developed, under the assumption of vapour-only venting. Opening/re-closing of the relief valve introduces state-events which require re-initialization of the model at each state transition. The relationship between the pressure relief model and the concept of residue curves, which describe simple-distillation processes, is demonstrated. It is known that the presence of azeotropes and distillation boundaries in mixtures restricts the composition trajectories of simple-distillation processes, as well as continuous distillation columns at total reflux. In this work, the residue-curve analogy is extended to vapour-only pressure-relief, where vapour composition changes directly affect the operation of the pressure-relief device. Examples of dynamic relief processes are developed for ternary mixtures with varying non-ideality.
Techniques such as micro-tomography (µCT) and nuclear magnetic resonance (NMR) methods have been used to characterize porous media for decades. Magnetic Resonance Imaging (MRI) offers direct visualization of pore architecture through a vast number of pulse sequences. In this work, we tested the MRI pulse sequence Zero Echo Time (ZTE) in the study of sandstone and carbonate. ZTE has been used previously to image highly porous geological material with relative success. In this research, ZTE was used to study porous systems tighter than those previously reported. We show that ZTE can resolve not only pore systems, but also a combination of fractures and pores simultaneously. Additionally, Pore Cluster Analysis (PCA), combined with ZTE, can be used to analyze connectivity of relatively large volume core plugs. By combining Time-Domain NMR pore-size analysis and PCA, we show that careful selection of resolution is necessary to understand transport in porous media.
Diverse engineering fields request flash calculations like isothermal flash, isenthalpic flash, and isentropic flash. They can be cast as minimization of a thermodynamic state-function and solved by Michelsen’s Q-function approach. Flash calculations for open systems, i.e. systems where chemical potentials are specified instead of the mole numbers for some components, also belong to this scope. By analyzing the construction of Q-functions through Legendre transforms, we extend this approach to the flash for open systems in the absence or presence of chemical reactions, resulting in general formulations for various specifications. For systems without reactions, the classical framework using mole numbers as independent variables is employed; for those with reactions, the modified-RAND framework is employed. We present examples for open systems at constant temperature and pressure. Using the Q-function minimization, we can solve multicomponent non-reactive or reactive systems at a specified chemical potential with quadratic convergence over a wide range of conditions.
As the hydrodesulfurization (HDS) of diesel achieves ultra-deepness, our understanding of its kinetics is still far from in-depth. Therefore, herein, two lumped kinetic models for the ultra-deep hydrodesulfurization (UHDS) and hydrodenitrogenation (HDN) are established based on experiments under a wide range of operating conditions. Meanwhile, a four-lump kinetic model of the aromatic hydrosaturation (AHS) is erected. Our kinetic models disclose thermodynamic decisiveness in UHDS, which is unreachable beyond a temperature upper limit or a pressure lower limit. We also reveals the unexpected temperature dependence of nitrogen inhibition to HDS, for less than 300℃ the nitrogen inhibition becomes even more potent despite nitrogen removal by HDN reactions. Subsequently, the HDS kinetics of total sulfur are deciphered as multi stages exist in the whole reaction coordinate. Accordingly, a four-stage conceptual model involving mechanism and rate laws is proposed to offer a better understanding of nitrogen inhibition, thermodynamics and kinetics in UHDS.
Synthetic biology is the engineering approach to edit or write the genome aiming to design the biological devices (promoters, transcription factors, TFBS, terminators etc.) of an organism to achieve the improved properties, while, metabolic engineering aiming to engineer the microbes to produce metabolites on industrial scale through recombinant DNA technologies. Recently, both synthetic biology and metabolic engineering fields are growing quickly and are used to produce metabolites of interest. The main theme of Synthetic Biology – Metabolic Engineering book is to review the tools and techniques used in synthetic biology and metabolic engineering to design and engineer the microbes to produce value-added metabolites and its application in industrial biotechnology. The book is written by the world-renowned metabolic engineers and synthetic biologists in series of Advances in Biochemical Engineering/Biotechnology and primarily elaborates the synergy between metabolic engineering and synthetic biology.
Modeling and analysis of the materials universe is an emerging area of research with many important applications in materials science. The main goal is to create a map of materials which allows not only to visualize and navigate the materials space, but also reveal complex relationships and “connections” among materials and potentially find clusters of materials with similar properties. In this paper, we consider the problem of mapping and exploring the materials universe using network science tools and concepts. The networks are based on the open-source materials data repository AFLOW.org where each material is represented as a node, and each pair of nodes is connected by a link if the respective materials exhibit a high level of similarity between their Density of States (DOS) functions. We discuss the importance of similarity measure selection, investigate basic structural properties of the resulting networks, and demonstrate advantages and limitations of the proposed approaches.
Membranes with asymmetric wettability-Janus membranes-have recently received considerable attention for a variety of critical applications. Nonetheless, the current methods for making such membranes are still challenging. Here, we report on a simple approach to introduce asymmetric wettability into hydrophilic porous domains. Our approach is based on the physicochemical-selective deposition of polytetrafluoroethylene (PTFE) on hydrophilic polymeric substrates. The physicochemical inhibition was achieved through prefilling the substrates with glycerol, containing a known amount of free radical inhibitors. We showed that the glycerol/inhibitor mixture hinders the deposition of PTFE within the membrane pores. As a result, the surface of the substrates remains open and porous. The fabricated Janus membranes show stable wetting-resistant properties, evaluated through sessile drop contact angle measurements and direct contact membrane distillation (DCMD).
Most cell penetrating peptides (CPPs) are unstructured and susceptible to proteolytic degradation. One alternative is to incorporate D-chirality amino acids into unstructured CPPs to allow for enhanced uptake and intracellular stability. This work investigates CPP internalization using a series of time, concentration, temperature, and energy dependent studies, resulting in a three-fold increase in uptake and 50-fold increase in stability of D-chirality peptides over L-chirality counterparts. CPP internalization occurred via a combination of direct penetration and endocytosis, with a percentage of internalized CPP expelling from cells in a time-dependent manner. Mechanistic studies identified that cells exported the intact internalized D-chirality CPPs via an exocytosis independent pathway, analogous to a direct penetration method out of the cells. These findings highlight the potential of D-chirality CPPs as bio-vectors in therapeutic and biosensing applications, but also identify a new expulsion method suggesting a relationship between uptake kinetics, intracellular stability, and export kinetics
The manuscript describes a computational study that provides molecular-level insight into shale gas adsorption and transport in shale rocks, which are composed of organic and inorganic matter. Atomistic simulations were used to generate realistic models of the organic matter structures with both micro- and mesoporosity, and correspond to mature and overmature type-II kerogens. These porous material models are unique to most other previous kerogen models since they contain other components (asphaltene/resin, hydrocarbons and carbon dioxide/water fractions) that are typically not modeled. The inclusion of these additional components significantly influences the resulting porous structure characteristics. The adsorption and diffusion behavior of methane (as a shale gas proxy) and methane/carbon dioxide mixtures were simulated in the model structures. Several key industrial-relevant findings are described in the manuscript.
Drop breakup experiments were carried out in a stirred tank using the high-speed online camera. Breakup behaviors of drop breakup time, multiple breakage, and breakup rate were investigated. Experimental results show that the drop breakup time is mainly controlled by the interfacial tension and drop diameter, while is almost independent of the rotating speed. Besides, the dispersed phase viscosity has a slight influence on the breakup time. An empirical correlation for the breakup time is proposed and is further verified by comparing with the results of Solsvik and Jakobsen (Chem. Eng. Sci., 2015, 131: 219-234). The percentage of multiple breakage comparing to binary breakup was statistically counted. The results indicated that the dimensionless drop diameter η = d / dmax can be adopted to characterize the proportion of binary breakup. Finally, the breakup rate was experimentally measured and the breakup probability was calculated using the inverse method.
Spherical agglomeration (SA) is a process intensification (PI) strategy, which can reduce the number of unit operations in pharmaceutical manufacturing. SA merges drug substance crystallization with drug product wet granulation, reducing capital and operating costs. However, SA is a highly nonlinear process, thus for its efficient operation model-based design and control strategies are beneficial. These require the development of a high-fidelity process model with appropriately estimated parameters. There are two major problems associated with the development of a high-fidelity process models – (i) selection of the appropriate model corresponding to the underlying process mechanisms, and (ii) accurate estimation of the parameters. This work focuses on the identification of the best fitting model that correlates with experimental observations using cross-validation experiments. Further, an Iterative Model Based Experimental Design (IMED) strategy is developed, which uses D-optimal experimental design criterion to minimize the number of experiments necessary to obtain accurate parameter estimates.
Zeolite belongs to one of the most important families of solid acid catalysts in chemical industries. It is however severely constrained by the diffusion limitation for bulky molecules, the lack of multi-functionality for sequential reactions and pore adaptability towards specific adsorbates, due to the small micropore size and simple aluminosilicate framework. Introducing mesopores into the zeolitic framework towards hierarchical zeolites is prevailing, but usually suffers from compromised crystallinity as well as insufficient interconnectivity and openness of mesopores. Herein, a novel of acid-redox co-functionalized single-crystalline zeolite with highly open and interconnected mesopores is designed and fabricated. As a proof-of-concept study, we integrate the solid acid and Fe-oxy redox sites in a hierarchical MEL zeolite with well characterized microporosity and mesoporosity. It exhibits superior activity and stability towards the alkylation between mesitylene with benzyl alcohol, arising from greatly facilitated intracrystalline molecular diffusion, mitigated metal leaching and optimized adsorbate-pore wall interactions.
Sequential model-based design of experiments (MBDoE) uses information from previous experiments to select run conditions for new experiments. Computation of the objective functions for popular MBDoE can be impossible due to a non-invertible Fisher Information Matrix (FIM). Previously, we evaluated a leave-out (LO) approach that design experiments by removing problematic model parameters from the design process. However, the LO approach can be computationally expensive due to its iterative nature and some model parameters are ignored. In this study, we propose a simple Bayesian approach that makes the FIM invertible by accounting for prior parameter information. We compare the proposed Bayesian approach to the LO approach for designing sequential A-optimal experiments. Results from a pharmaceutical case study show that the Bayesian approach is superior, on average, to the LO approach for design of experiments. However, for subsequent parameter estimation, a subset-selection-based LO approach gives better parameter values than the Bayesian approach.
Experimental results on pressure drop and flow patterns for gas-liquid flow through packed beds obtained in the International Space Station with two types of packing are presented and analyzed. It is found that the pressure drop depends on the packing wettability in the viscous-capillary (V-C) regime and this dependence is compared with previously published results developed using short duration low-gravity aircraft tests. Within the V-C regime, the capillary contribution is the dominant force contributing to the pressure drop for the wetting case (glass) versus the viscous contribution dominating for the non-wetting case (Teflon). Outside of the V-C regime, it is also found that hysteresis effects that are often strong in normal gravity gas-liquid flows are greatly diminished in microgravity and pressure drop is nearly independent of packing wettability. A flow pattern transition map from bubble to pulse flow is also compared with the earlier aircraft data.
In this investigation, CO2 capture performance of zeolite 13X monoliths with 600 and 800 cpsi in presence of SO2/NO impurities under dry and humid conditions were evaluated and compared with that of 13X beads. Dynamic breakthrough tests demonstrated a drastic reduction in CO2 capture capacity and deterioration of kinetics under dry-clean conditions, whereas, upon switching the feed from a clean gas to contaminated gas which contained SO2 and NO, different adsorption performance was observed. Specifically, in dry-contaminated mode, the adsorbents retained their capture capacities with comparable kinetics to that of dry-clean feed conditions, however, in humid-contaminated mode, the adsorbents experienced improved CO2 uptake and CO2/N2 selectivity, albeit at the expense of deteriorated kinetics. These findings indicate that the presence of SO2 and NO contaminants, especially SO2 contaminants, lead to dramatic changes in the adsorption performance of zeolite 13X monoliths, indicating the importance of evaluating adsorbent materials under realistic conditions.
In Rodriguez et al.1 an analytical expression was deduced to predict the slip ratio in dispersed oil-water flow. Although the quantitative agreement was quite good, the expression systematically underestimated the slip ratio. New experimental data of similar flows were collected in two different experimental facilities in pipes of different materials and diameters (26 mm and 82.8 mm i.d.). Oil-water flow data collected within a range of mixture Reynolds numbers from 1∙10^5 to 20∙10^6 in glass, acrylic and steel pipes with oil viscosities varying from 7 to 220 mPa.s were used to deduce a more generic correlation for slip ratio as a function of the mixture Froud number (5 < Fr < 70). The underestimation of the slip ratio was corrected. The new slip-ratio correlation can be used to significantly improve the prediction of volumetric fraction in flow situations where turbulent dispersion of oil in water occurs.
We introduce a straightforward method for the preparation of novel starch-based ultramicroporous carbons (SCs) that demonstrate high CH4 uptake and excellent CH4/N2 selectivity. These SCs are derived from a combination of starch and 1-6 wt. % of acrylic acid, and the resulting materials are amenable to surface cation exchangeability as demonstrated by the formation of highly dispersed K+ in carbon precursors. Following activation, these SCs contain ultramicropores with narrow pore-size distributions of <0.7 nm, leading to porous carbon-rich materials that exhibit CH4 uptake values as high as 1.86 mmol/g at 100 kPa and 298 K, the highest uptake value for CH4 to date, with the IAST-predicted CH4/N2 selectivity up to 5.7. Both the potential mechanism for the formation of narrow pores and the origin of the favorable CH4 adsorption properties are discussed and examined. This work may potentially guide future designs for carbon-rich materials with excellent gas adsorption properties.