An estimation of the penetration rate of rotary drills using the Specific Rock Mass Drillability index

The main purpose of the present study was to provide a practical,convenient drillability prediction model based on rock mass characteristics,geological sampling from blast holes,and drill operational f...     

Thermo-hydrolytic stability of swelling capacity of superabsorbing composite hydrogels based on AMPS and acrylamide

N,N′-Methylenebisacrylamide (MBA) is a conventional crosslinker most often used to produce hydrogels. We have previously shown that MBA-crosslinks were thermo-hydrolytically cleaved upon heating during oven-drying, particularly in hydrogels based on 2-acrylamido-2-methylpropane sulfonic acid (AMPS). The present paper deals with the effect of comonomer acrylamide (AM, ranged 0–100%) and an organomodified clay on swelling stability of MBA-crosslinked poly(AMPS–AM) superabsorbing composite hydrogels. It was found that either AM or the organoclay had constructive effects on thermo-hydrolytic stability of the network through delaying or stopping the undesirable swelling changes originated from the crosslink cleavage, de-crosslinking. The incorporated organomodified clay, however, exhibited fewer stabilizing effect rather than AM, when AM content was higher than 15%. The swelling of hydrogels was turned out to be stable during heating even at high temperature (200 °C) when they composed at least 15% AM. Based on rheometrical studies, swollen gel strength of heated composite hydrogel was typically shown to be significantly higher than that of the clay-free counterpart.     

Adaptive control of cold rolling system in electrical strips production system with online-offline predictors

One of the main concerns of strips producers is to measure strip thickness accurately as it is produced. Correct modelling of the sensitivity of output variables to input variables in a rolling mill model is one of the keys to obtaining more accurate data. An adaptive control system that uses an artificial neural network (ANN) creates a model of the process directly from measurement data. Using the model, the control system can predict how the process will react to control actions. The creation of the model and the computation of the control strategy are carried out automatically by the control system. The proportional–integral–derivative controller is used in this method to increase accuracy of final estimated variables and to increase accuracy of control of the system. To determine the correct tuning for thickness control, three control parameters are considered: the roll gap, and front and back tensions. A predictive model is used, based on the sensitivity equations of the process, where the sensitivity factors are computed by differentiating a previously trained neural network. Results of a case study in a real plant show that this online-offline model is effective in reducing thickness variations in produced strips.     

Liquid Metal Droplet and Graphene Co‐Fillers for Electrically Conductive Flexible Composites

Colloidal liquid metal alloys of gallium, with melting points below room temperature, are potential candidates for creating electrically conductive and flexible composites. However, inclusion of liquid metal micro‐ and nanodroplets into soft polymeric matrices requires a harsh auxiliary mechanical pressing to rupture the droplets to establish continuous pathways for high electrical conductivity. However, such a destructive strategy reduces the integrity of the composites. Here, this problem is solved by incorporating small loading of nonfunctionalized graphene flakes into the composites. The flakes introduce cavities that are filled with liquid metal after only relatively mild press‐rolling (<0.1 MPa) to form electrically conductive continuous pathways within the polymeric matrix, while maintaining the integrity and flexibility of the composites. The composites are characterized to show that even very low graphene loadings (≈0.6 wt%) can achieve high electrical conductivity. The electrical conductance remains nearly constant, with changes less than 0.5%, even under a relatively high applied pressure of >30 kPa. The composites are used for forming flexible electrically‐conductive tracks in electronic circuits with a self‐healing property. The demonstrated application of co‐fillers, together with liquid metal droplets, can be used for establishing electrically‐conductive printable‐composite tracks for future large‐area flexible electronics.     

Porous Superabsorbent Hydrogel Composites: Synthesis,Morphology and Swelling Rate

Summary: Novel porous hydrogel composites with very high swelling capacity and enhanced rate of water absorption were synthesized in aqueous media at room temperature under normal atmospheric conditions. The porosity was induced through either foaming conducted in the course of polymerization or non‐solvent dewatering of the as‐synthesized gels. Kaolin was incorporated as an inorganic component in the polymerization process. The foaming technique was used to form porosity using three systems of different porogens (porosity generators), i.e. sodium bicarbonate, acetone and their combination. The as‐synthesized gels were dried through oven drying and non‐solvent dewatering. Morphology and swelling rate of the superabsorbent hydrogel composites (SHCs) were studied versus either the porogen system or the drying method. It was found that the simultaneous polymerization‐foaming technique had great influence on the improvement of porosity, morphology of the porous structure and the rate of water absorption. It was also shown that the drying procedure had remarkable influence on preserving the preformed porosity. Methanol as a dewatering solvent produced SHCs with higher porosity and swelling rate in comparison with the porosity of the hydrogels dewatered in acetone. Our invented methodology including simultaneous polymerization and foam formation using dual‐porogen system and the subsequent methanol‐dewatering approach was found to be the most efficient, highly practical, and cost‐effective route for preparing improved superabsorbing hydrogel materials.

     

Ultrafast Acoustofluidic Exfoliation of Stratified Crystals

While the remarkable properties of 2D crystalline materials offer tremendous opportunities for their use in optics, electronics, energy systems, biotechnology, and catalysis, their practical implementation largely depends critically on the ability to exfoliate them from a 3D stratified bulk state. This goal nevertheless remains elusive, particularly in terms of a rapid processing method that facilitates high yield and dimension control. An ultrafast multiscale exfoliation method is reported which exploits the piezoelectricity of stratified materials that are noncentrosymmetric in nature to trigger electrically‐induced mechanical failure across weak grain boundaries associated with their crystal domain planes. In particular, it is demonstrated that microfluidic nebulization using high frequency acoustic waves exposes bulk 3D piezoelectric crystals such as molybdenum disulphide (MoS₂) and tungsten disulphide (WS₂) to a combination of extraordinarily large mechanical acceleration (≈10⁸ m s^?2) and electric field (≈10⁷ V m^?1). This results in the layered bulk material being rapidly cleaved into pristine quasi‐2D‐nanosheets that predominantly comprise single layers, thus constituting a rapid and high throughput chip‐scale method that opens new possibilities for scalable production and spray coating deposition.     

Scalable Feature Selection in High-Dimensional Data Based on GRASP

Feature selection in high-dimensional data is one of the active areas of research in pattern recognition. Most of the algorithms in this area try to select a subset of features in a way to maximize the accuracy of classification regardless of the number of selected features that affect classification time. In this article, a new method for feature selection algorithm in high-dimensional data is proposed that can control the trade-off between accuracy and classification time. This method is based on a greedy metaheuristic algorithm called greedy randomized adaptive search procedure (GRASP). It uses an extended version of a simulated annealing (SA) algorithm for local search. In this version of SA, new parameters are embedded that allow the algorithm to control the trade-off between accuracy and classification time. Experimental results show supremacy of the proposed method over previous versions of GRASP for feature selection. Also, they show how the trade-off between accuracy and classification time is controllable by the parameters introduced in the proposed method.     

Hepatitis disease diagnosis using a novel hybrid method based on support vector machine and simulated annealing (SVM-SA)

In this study, diagnosis of hepatitis disease, which is a very common and important disease, is conducted with a machine learning method. We have proposed a novel machine learning method that hybridizes support vector machine (SVM) and simulated annealing (SA). Simulated annealing is a stochastic method currently in wide use for difficult optimization problems. Intensively explored support vector machine due to its several unique advantages is successfully verified as a predicting method in recent years. We take the dataset used in our study from the UCI machine learning database. The classification accuracy is obtained via 10-fold cross validation. The obtained classification accuracy of our method is 96.25% and it is very promising with regard to the other classification methods in the literature for this problem.     

On-chip separation of Lactobacillus bacteria from yeasts using dielectrophoresis

Dielectrophoresis, the induced motion of dielectric particles in non-uniform electric fields, enables the separation of suspended bio-particles based on their dimensions or dielectric properties. This work presents a microfluidic system, which utilises a combination of dielectrophoretic (DEP) and hydrodynamic drag forces to separate Lactobacillus bacteria from a background of yeasts. The performance of the system is demonstrated at two operating frequencies of 10?MHz and 100?kHz. At 10?MHz, we are able to trap the yeasts and bacteria at different locations of the microelectrodes as they experience different magnitudes of DEP force. Alternatively, at 100?kHz we are able to trap the bacteria along the microelectrodes, while repelling the yeasts from the microelectrodes and washing them away by the drag force. These separation mechanisms might be applicable to automated lab-on-a-chip systems for the rapid and label-free separation of target bio-particles.