Characterization of Tribological and Mechanical Properties of the Si3N4 Coating Fabricated by Duplex Surface Treatment of Pack Siliconizing and Plasma Nitriding on AISI D2 Tool Steel

Silicon nitride (Si₃N₄) coating was deposited on AISI D2 tool steel through employing duplex surface treatments—pack siliconizing followed by plasma nitriding. Pack cementation was performed at 650 °C, 800 °C, and 950 °C for 2 and 3 hours by using various mixtures to realize the silicon coating. X-ray diffraction analyses and scanning electron microscopy observations were employed for demonstrating the optimal process conditions leading to high coating adhesion, uniform thickness, and composition. The optimized conditions belonging to siliconizing were employed to produce samples to be further processed via plasma nitriding. This treatment was performed with a gas mixture of 75 pct H₂-25 pct N₂, at the temperature of 550 °C for 7 hours. The results showed that different nitride phases such as Si₃N₄-β, Si₃N₄-γ, Fe₄N, and Fe₃N can be recognized as coatings reinforcements. It was demonstrated that the described composite coating procedure allowed to obtain a remarkable increase in hardness (80 pct higher with respect to the substrate) and wear resistance (30 pct decrease of weight loss) of the tool steel.

     

Chemically crosslinked polyvinyl alcohol for water shut-off and conformance control treatments during oil production: The effect of silica nanoparticles

Polyvinyl alcohol (PVA) is a synthetic commercial polymer with the inherent hydrophilicity, thermal and chemical resistance, ecofriendly, and a high anti-fouling potential making it an attractive choice for water treatment applications, but has been less studied for oil and gas industry applications. On the other hands, nowadays nanotechnology has gained an important space within most core areas in upstream oil and gas operations. The present work, first PVA at various concentrations, was added to 5 wt% NaCl solution and then, crosslinked by formaldehyde 37% at two different concentration ratios. To compare, a nanocomposite hydrogel was fabricated in the same way with 1 wt% silica nanoparticles (NPs). Contact angle and filtration test were performed to confirm the ability of PVA hydrogel and nanocomposite hydrogel for oil and water adsorption. Following this, a rheology measurement was made to realize the gelation time of samples and their performance for water shutoff applications. Finally, an experimental flooding setup was designed to inject the fluids into carbonate plugs in order to estimate of oil and water effective permeability, and oil recovery factor (RF) before and after the PVA hydrogel and nanocomposite hydrogel injection. Both samples wettability tests showed a super-hydrophilic state for brine droplets and neutral state for synthetic oil droplets by using nanocomposite hydrogel. The flooding tests revealed that the PVA hydrogel was clogged the plug with blocking efficiency of 32.83% for water effective permeability and 14.60% for oil effective permeability. This value was calculated to be 50.37% for water effective permeability and 31.36% for oil effective permeability in the case of nanocomposite hydrogel injection. Oil RF was also reported to be 64.58% after injecting PVA hydrogel which was higher than nanocomposite hydrogel injection with RF of 52.08%.     

CO2 capture by benzene-based hypercrosslinked polymer adsorbent: Artificial neural network and response surface methodology

In this research, porous benzene-based hypercrosslinked polymeric adsorbents with different morphological properties were synthesized through Friedel–Crafts alkylation reaction. The resulting samples were applied for CO₂ capture at different operational conditions. Two modelling approaches, including artificial neural network (radial basis function [RBF] and multi layer perceptron [MLP]) and response surface methodology (RSM), were employed to investigate the effect of independent parameters on adsorption capacity. A semi-empirical quadratic model for adsorption capacity was presented based on RSM-central composite design technique. Additionally, the optimal structure of RBF was determined with 200 neurons, and the optimal structure of MLP was determined with three hidden layers and 10, 8, and 7 neurons. The modelling results demonstrate the better prediction of MLP and RBF approaches than the RSM method with correlation coefficient values of 0.999, 0.989, and 0.931, respectively. Finally, process optimization was carried out using RSM optimization module and the optimized values of synthesis time, crosslinker ratio (formaldehyde dimethyl acetal [FDA]/benzene), adsorption time, pressure, and temperature were obtained at 10.11 h, 1, 220 s, 9 bar, and 55°C, respectively. The optimum value of CO₂ uptake capacity was obtained around 167 (mg/g).     

A domain adaptation method by incorporating belief function in twin quarter-sphere SVM

Knowledge and Information Systems - Domain adaptation is a representative problem in transfer learning, which aims to tackle the problem of insufficient labeled data in a target domain by...     

High-Throughput Exploration of Triple-Cation Perovskites via All-in-One Compositionally-Graded Films

Many devices heavily rely on combinatorial material optimization. However, new material alloys are classically developed by studying only a fraction of giant chemical space, while many intermediate compositions remain unmade in light of the lack of methods to synthesize gapless material libraries. Here report a high-throughput all-in-one material platform to obtain and study compositionally-tunable alloys from solution is reported. This strategy is applied to make all Cs_xMA_yFA_zPbI₃ perovskite alloys (MA and FA stand for methylammonium and formamidinium, respectively), in less than 10 min, on a single film, on which 520 unique alloys are then studied. Through stability mapping of all these alloys in air supersaturated with moisture, a range of targeted perovskites are found, which are then chosen to make efficient and stable solar cells in relaxed fabrication conditions, in ambient air. This all-in-one platform provides access to an unprecedented library of compositional space with no unmade alloys, and hence aids in a comprehensive accelerated discovery of efficient energy materials.     

Silicon Nanoparticles and Methyl Jasmonate Improve Physiological Response and Increase Expression of Stress-related Genes in Strawberry cv. Paros Under Salinity Stress

Silicon - Salinity is one of the most crucial abiotic stresses, which is the consequence of an increase in the concentration of NaCl ions, influencing the plant’s growth, development, and...     

Fragility assessment of an outrigger structure system based on energy method

Fragility curves development in structures has always been a focus of research interest among structural and earthquake engineers for which the maximum story drift is usually considered as the engineering demand parameter (EDP) known as the conventional approach. This paper aims at calculating the fragility curves of a tall building with outrigger braced system by considering the plastic strain energy as the EDP and compare it with the conventional approach. In addition, the effect of optimizing the position of outriggers on the exceedance probability of the structure under near- and far-fault seismic loadings is investigated in this paper. Fragility curves of this structure in four performance levels including immediate occupancy (IO), life safety (LS), collapse prevention (CP), and instability is extracted based on the conventional method. The fragility curves for the aforementioned performance levels are also extracted based on the plastic strain energy and compared with the conventional approach. The results have demonstrated that optimizing the location of the bracing system would lower the exceedance probability of the structure. Moreover, the exceedance probability of the investigated building with outrigger braced system under far-fault records in various levels is more than that of near-fault records. It is also concluded that the conventional approach would lead to more conservative results compared with the energy approach.     

Global modeling of nonlinear circuits using the finite‐difference Laguerre time‐domain/alternative direction implicit finite‐difference time‐domain method with stability investigation

This paper describes a new unconditionally stable numerical method for the full‐wave physical modeling of semiconductor devices by a combination of the finite‐difference Laguerre time‐domain (FDLTD) and alternative direction implicit finite‐difference time‐domain (ADI‐FDTD) approaches. The unconditionally stable method by using FDLTD scheme for the electromagnetic model and semi‐implicit ADI‐FDTD approach for the active model leads to a significant decrease in the full‐wave simulation time. Numerical simulations of an example transistor and a power amplifier show the efficiency of presented method for the full‐wave simulation of mm‐wave active circuits. Copyright © 2012 John Wiley & Sons, Ltd.     

Capillary pumping between droplets on superhydrophobic surfaces

The famous two-balloon experiment involves two identical balloons filled up with air and connected via a hollow tube, and upon onsetting the experiment one of the balloons shrinks and the other expands. Here, we present the liquid version of that experiment. We use superhydrophobic (SHP) substrates to form spherical droplets and connect them with a capillary channel. Different droplet sizes, substrates of different hydrophobicities, and various channel pathways are investigated, and morphometric parameters of the droplets are measured through image processing. In the case of SHP substrates, the pumping is from the smaller droplet to the larger one, similar to the two-balloon experiment. However, if one or both of the droplets are positioned on a normal substrate the curvature radius will indicate the direction of pumping. We interpret the results by considering the Laplace pressures and the surface tension applied by the channel at the connecting points.