Nonlinear model predictive control for dividing wall columns

Dividing wall columns (DWCs) are practical, effective, and promising among distillation process intensification technologies. Nonlinear model predictive control (NMPC) schemes are developed in this study to control the three-product DWCs. As these systems are intensely interactive and highly nonlinear, NMPC may be more suitable than the traditional PI control. The model is established based on Python and Pyomo platforms. As the original mathematical model of the column section is ill-posed, index reduction is used to avoid a high-index differential-algebraic equation (DAE) system. The well-posed index-1 system after index reduction is employed for the steady-state simulation and dynamic control in this study. Case studies with three DWC configurations to separate the mixture of ethanol (A), n-propanol (B), and n-butanol (C) show that the NMPC performs very well with small maximum deviations and short settling times. This demonstrates that the NMPC is a feasible and very effective scheme to control three-product DWCs.     

Advanced trust region optimization strategies for glass box/black box models

We present an improved trust region filter (TRF) method for optimization of combined glass box/black box systems. Glass box systems refer to models that are easily expressed in an algebraic modeling language, providing cheap and accurate derivative information. By contrast, black box systems may be computationally expensive and derivatives are unavailable. The TRF method, as first introduced in our previous work (Eason and Biegler, AIChE J. 2016; 62:3124–3136), is able to handle hybrid systems containing both glass and black box components, which can frequently arise in chemical engineering, for example, when a multiphase reactor model is included in a flow sheet optimization problem. We discuss several recent modifications in the algorithm such as the sampling region, which maintains the algorithm's global convergence properties without requiring the trust region to shrink to zero in the limit. To benchmark the development of this optimization method, a test set of problems is generated based on modified problems from the CUTEr and COPS sets. The modified algorithm demonstrates improved performance using the test problem set. Finally, the algorithm is implemented within the Pyomo environment and demonstrated on a rigorous process optimization case study for carbon capture. © 2018 American Institute of Chemical Engineers AIChE J, 64: 3934–3943, 2018     

Fabrication of Ti3SiC2-based pastes for screen printing on paper-derived Al2O3 substrates

This paper describes the development and fabrication of pastes suitable for screen printing process using Ti₃SiC₂ as the ceramic filler and ethyl cellulose as the binder. With the aim of obtaining high quality screen printed films, the influence of different amounts of Ti₃SiC₂ filler (20–40?vol%) and binder (0–5?vol%) on the rheological properties of the pastes was investigated. Samples with higher viscosity, such as pastes containing 30?vol% and 40?vol% Ti₃SiC₂ filler, regardless of the amount of ethyl cellulose, showed a higher printing quality compared to the samples with other compositions. The different paste compositions were screen printed onto paper-derived Al₂O₃ substrates containing 28.6 ± 4.8% open porosity and sintered for 1?h under an argon atmosphere at 1600?°C. X-ray diffraction (XRD) measurements and scanning electron microscopy (SEM) analysis showed that the sintered films contained TiC as a primary phase and Ti₃SiC₂ as a secondary phase. The partial decomposition of Ti₃SiC₂ after sintering can be attributed to residual carbon from the organic additives, which decreases the thermal stability of this material.     

Vaporization and Corrosion of Refractories in the Presence of Pressurized Pulverized Coal Combustion Slag

The corrosion and vaporization behavior of eight commercial refractories containing Cr₂O₃ were investigated under simulated pressurized pulverized coal combustion (PPCC) conditions at 1723 K in the presence of liquid slag. The corrosion resistance of the refractory materials decreased with increased content of free Cr₂O₃, because bursting (reaction of Fe₃O₄ with Cr₂O₃) occurred. Refractories containing MgCr₂O₄ with dissolved Al₂O₃ showed the highest corrosion resistance. Thermodynamic calculations showed that CrO₃ and CrO₂(OH)₂ were the most volatile species in air and in PPCC flue gas, whereas additions of A₂O (A = Na and K, minor slag component) increased the chromium vaporization significantly because of A₂CrO₄ formation. Knudsen effusion mass spectrometry measurements showed that the chromium vaporization of refractories was directly correlated to the Cr₂O₃ content of the material. In contrast, refractories containing MgCr₂O₄ showed a significant decrease in chromium vaporization.     

Simple N‐Heterocyclic Carbenes as Ligands in Ullmann‐Type Ether and Thioether Formations

A simple N‐heterocyclic carbene (NHC) derived from 1‐methyl‐3‐ethylimidazolium tetrafluoroborate was found to be an efficient ligand for a range of copper‐catalyzed cross‐coupling reactions, leading to the formation of aromatic ethers and thioethers.

     

Multilevel surrogate modeling of an amine scrubbing process for CO2capture

Surrogate models provide a powerful method for simplifying calculations within complex simulations. While surrogate models are broadly applied within chemical engineering, little research exists investigating the level of surrogacy's impact on a simplified process model. In this work, artificial neural networks (ANN) and Kriging models are used as surrogate models at the process, process unit, and thermodynamic levels for a CO₂ amine scrubbing process. The surrogated models are evaluated against an Aspen Plus simulation for accuracy, convergence behavior, computational cost, and ability to extrapolate. The thermodynamic and process unit models can better handle discontinuous, non-smooth behavior, and convergence issues in the surrogated truth model, but poor conditioning in the final system of equations results in a lower accuracy and convergence rate than the process level surrogate. Beyond model accuracy, availability of diverse data, intended re-usability, and the desired outputs must be considered when selecting a level of abstraction.     

CNT Based Elastomer‐Hybrid‐Nanocomposites with Promising Mechanical and Electrical Properties

CNT based elastomer‐hybrid‐nanocomposites prepared by melt mixing have been investigated showing promising results in technologically relevant electrical, mechanical, and fracture‐mechanical properties. It is demonstrated that the incorporation of CNT in silica‐filled natural rubber results in a good dispersion of the CNT. The materials show an enhanced mechanical stiffness and tensile strength, an increased modulus, and a high electrical conductivity with quite low amounts of CNT, though the tear resistance under dynamical loading is slightly reduced. Using DMA and dielectric spectra, a better understanding of the conduction mechanism, the polymer/tube interaction, and the filler networking in CNT nanocomposites is achieved.

     

Metformin Preserves β-Cell Compensation in Insulin Secretion and Mass Expansion in Prediabetic Nile Rats

Prediabetes is a high-risk condition for type 2 diabetes (T2D). Pancreatic β-cells adapt to impaired glucose regulation in prediabetes by increasing insulin secretion and β-cell mass expansion. In people with prediabetes, metformin has been shown to prevent prediabetes conversion to diabetes. However, emerging evidence indicates that metformin has negative effects on β-cell function and survival. Our previous study established the Nile rat (NR) as a model for prediabetes, recapitulating characteristics of human β-cell compensation in function and mass expansion. In this study, we investigated the action of metformin on β-cells in vivo and in vitro. A 7-week metformin treatment improved glucose tolerance by reducing hepatic glucose output and enhancing insulin secretion. Although high-dose metformin inhibited β-cell glucose-stimulated insulin secretion in vitro, stimulation of β-cell insulin secretion was preserved in metformin-treated NRs via an indirect mechanism. Moreover, β-cells in NRs receiving metformin exhibited increased endoplasmic reticulum (ER) chaperones and alleviated apoptotic unfold protein response (UPR) without changes in the expression of cell identity genes. Additionally, metformin did not suppress β-cell mass compensation or proliferation. Taken together, despite the conflicting role indicated by in vitro studies, administration of metformin does not exert a negative effect on β-cell function or cell mass and, instead, early metformin treatment may help protect β-cells from exhaustion and decompensation.