Twin screw granulation – review of current progress

Twin screw granulation (TSG) is a new process of interest to the pharmaceutical community that can continuously wet granulate powders, doing so at lower liquid concentrations and with better product consistency than found by a high shear batch mixer. A considerable body of research has evolved over the short time since this process was introduced but generally with little comparison of results. A certain degree of confidence has been developed through these studies related to how process variables and many attributes of machinery configuration will affect granulation but some major challenges still lay ahead related to scalability, variations in the processing regimes related to degree of channel fill and the impact of wetting and granulation of complex powder formulations. This review examines the current literature for wet granulation processes studied in twin screw extrusion machinery, summarizing the influences of operational and system parameters affecting granule properties as well as strives to provide some practical observations to newly interested users of the technique.     

Evolving an Accurate Decision Tree-Based Model for Predicting Carbon Dioxide Solubility in Polymers

Solubility is one of the most indispensable physicochemical properties determining the compatibility of components of a blending system. Research has been focused on the solubility of carbon dioxide in polymers as a significant application of green chemistry. To replace costly and time-consuming experiments, a novel solubility prediction model based on a decision tree, called the stochastic gradient boosting algorithm, was proposed to predict CO₂ solubility in 13 different polymers, based on 515 published experimental data lines. The results indicate that the proposed ensemble model is an effective method for predicting the CO₂ solubility in various polymers, with highly satisfactory performance and high efficiency. It produces more accurate outputs than other methods such as machine learning schemes and an equation of state approach.     

Effect of H2O2 concentration on electrochemical growth and properties of vertically oriented ZnO nanorods electrodeposited from chloride solutions

In this work, ZnO nanostructures are electrodeposited on a transparent conducting glass from chloride baths. The influence of H₂O₂ concentration on the electrochemical characteristics has been studied using cyclic voltammetry (CV) and chronoamperometry (CA) techniques. From the analysis of the current transients on the basis of the Scharifker–Hills model, it is found that nucleation mechanism is progressive with a typical three-dimensional (3D) nucleation and growth process; independently with the concentration of H₂O₂. However, the nucleation rate of the ZnO changes with the increase of H₂O₂ concentration. The Mott–Schottky measurements demonstrate an n-type semiconductor character for all samples with a carrier density varying between 5.14×10¹⁸ cm⁻³ and 1.47×10¹⁸ cm⁻³. Scanning electron microscopy (SEM) observations show arrays of vertically aligned ZnO nanorods (NRs) with good homogeneity. The X-ray diffraction (XRD) patterns show that the ZnO deposited crystallises according to a hexagonal Würtzite-type structure and with the c-axis perpendicular to the electrode surface. The directional growth along (002) crystallographic plane is very important for deposits obtained at 5 and 7 mM of H₂O₂. The high optical properties of the ZnO NRs with a low density of deep defects was checked by UV–vis transmittance analyses, the band gap energy of films varies between 3.23 and 3.31 eV with transparency around 80–90%.     

Validation of performance of real-time kinematic PPP. A possible tool for deformation monitoring

Structural failures (bridge or building collapses) and geohazards (landslides, ground subsidence or earthquakes) are worldwide problems that often lead to significant economic and loss of life. Monitoring the deformation of both natural phenomena and man-made structures is a major key to assessing structural dynamic responses. Actually, this monitoring process is under real-time demand for developing warning and alert systems.One of the most used techniques for real-time deformation monitoring is the Global Navigation Satellite System (GNSS) real-time procedure, where the relative positioning approach, using a well-known reference station, has been applied.This study was conducted to evaluate the actual quality of the real-time kinematic Precise Point Positioning (PPP) GNSS solution for deformation monitoring, where it can be concluded that a promise tool is under development and should be taken into account on actual and near future real-time deformation monitoring studies and applications.     

On recommendation problems beyond points of interest

Recommendation systems aim to recommend items or packages of items that are likely to be of interest to users. Previous work on recommendation systems has mostly focused on recommending points of interest (POI), to identify and suggest top-k items or packages that meet selection criteria and satisfy compatibility constraints on items in a package, where the (packages of) items are ranked by their usefulness to the users. As opposed to prior work, this paper investigates two issues beyond POI recommendation that are also important to recommendation systems. When there exist no sufficiently many POI that can be recommended, we propose (1) query relaxation recommendation to help users revise their selection criteria, or (2) adjustment recommendation to guide recommendation systems to modify their item collections, such that the users׳ requirements can be satisfied.We study two related problems, to decide (1) whether the query expressing the selection criteria can be relaxed to a limited extent, and (2) whether we can update a bounded number of items, such that the users can get desired recommendations. We establish the upper and lower bounds of these problems, all matching, for both combined and data complexity, when selection criteria and compatibility constraints are expressed in a variety of query languages, for both item recommendation and package recommendation. To understand where the complexity comes from, we also study the impact of variable sizes of packages, compatibility constraints and selection criteria on the analyses of these problems. Our results indicate that in most cases the complexity bounds of query relaxation and adjustment recommendation are comparable to their counterparts of the basic recommendation problem for testing whether a given set of (resp. packages of) items makes top-k items (resp. packages). In other words, extending recommendation systems with the query relaxation and adjustment recommendation functionalities typically does not incur extra overhead.     

Lagrangian relaxation hybrid with evolutionary algorithm for short-term generation scheduling

Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.     

Abrasive waterjet micro-machining of channels in metals: Comparison between machining in air and submerged in water

Abrasive water jet technology can be used for micro-milling using recently developed miniaturized nozzles. Abrasive water jet (AWJ) machining is often used with both the nozzle tip and workpiece submerged in water to reduce noise and contain debris. This paper compares the performance of submerged and unsubmerged abrasive water jet micro-milling of channels in 316L stainless steel and 6061-T6 aluminum at various nozzle angles and standoff distances. The effect of submergence on the diameter and effective footprint of AWJ erosion footprints was measured and compared. It was found that the centerline erosion rate decreased with channel depth due to the spreading of the jet as the effective standoff distance increased, and because of the growing effect of stagnation as the channel became deeper. The erosive jet spread over a larger effective footprint in air than in water, since particles on the jet periphery were slowed much more quickly in water due to increased drag. As a result, the width of a channel machined in air was wider than that in water. Moreover, it was observed that the instantaneous erosion rate decreased with channel depth, and that this decrease was a function only of the channel cross-sectional geometry, being independent of the type of metal, the jet angle, the standoff distance, and regardless of whether the jet was submerged or in air, in either the forward or backward directions. It is shown that submerged AWJM results in narrower features than those produced while machining in air, without a decrease in centerline etch rate.     

Effect of high pressure - low temperature processing on composition and colloidal stability of casein micelles and whey proteins

The aim of this study was to identify the impact of high pressure treatments at sub-zero temperatures (high pressure - low temperature; HPLT) on milk proteins. Whey protein solutions, micellar casein dispersions and two mixtures (micellar caseins:whey proteins, 80:20 and 20:80, w/w) were pressure treated (100–600 MPa) at pH 7.0 or 5.8 at −15 °C, −35 °C and ambient temperature. Solubility data showed that whey proteins could only be affected by HPLT treatments at pH 7.0 if caseins were present, while effects could be induced at pH 5.8 without the presence of caseins. The caseins formed on the one hand large aggregates (flocs) and on the other hand the solubility was increased by the creation of smaller micelles. The formation of flocs could only be observed for HPLT treated samples, which indicates the formation of different protein interactions in milk protein based samples compared with common HP treatments.     

A facile co-solvent strategy for preparation of graphene nanoplatelet powder: An industrially viable innovative approach

We report an industrially viable promising approach to produce micrometer-sized multilayer graphene nanoplatelet powder (MGNP) in a scalable quantity via microwave-assisted exfoliation of graphite (MEG) and fragmented into MGNP through liquid-phase exfoliation in the co-solvent mixture by kitchen mixer (KM). KM allows rapid delaminating MEG into MGNP by shear force dominated exfoliation. Majority of MGNPs are with a diameter of few micrometers and thickness is in nanometers. MGNP are crystalline with very limited defects was confirmed by Raman measurements and transmission electron microscopy. This process transforms, more than 86% of graphite flakes into MGNP. This advanced approach opens a new pathway to produce MGNP in bulk quantity as it is feasible, rapid, and cost-effective.