CO2 methanation over mesoporous silica based catalyst: a comprehensive study

The abundance presence of CO2 released into the atmosphere has gained numerous consideration for an effective method to mitigate the CO2 build up and recycling the carbon resource. Among the catalytic reactions, the methanation of CO2 has been an indispensable reaction to transform toxic CO2 into methane which can be use as energy carrier or valuable chemical. The application of heterogeneous catalyst in CO2 methanation plays a significant role due to its effectiveness and stability which led to lower costs for large scale production. This article discussed the recent developments of silica based catalyst for CO2 methanation with emphasized on its physicochemical properties and catalytic performance. In summary, the nature of silica support material such as morphology, textural properties and nature of basicity has a great influence on its catalytic performance towards CO2 methanation

Perfectly normal type-2 fuzzy interpolation B-spline curve

In this paper, we proposed another new form of type-2 fuzzy data points(T2FDPs) that is perfectly normal type-2 data points(PNT2FDPs). These kinds of brand-new data were defined by using the existing type-2 fuzzy set theory(T2FST) and type-2 fuzzy number(T2FN) concept since we dealt with the problem of defining complex uncertainty data. Along with this restructuring, we included the fuzzification(alpha-cut operation), type-reduction and defuzzification processes against PNT2FDPs. In addition, we used interpolation B-soline curve function to demonstrate the PNT2FDPs.Comment: arXiv admin note: substantial text overlap with arXiv:1304.786

Distribution power loss minimization via distributed generation, capacitor and network reconfiguration

This paper presents a solution to solve the network reconfiguration, DG coordination (location and size) and capacitor coordination (location and size), simultaneously. The proposed solution will be determined by using Artificial Bee Colony (ABC). Various case studies are presented to see the impact on the test system, in term of power loss reduction and also voltage profiles. The proposed approach is applied to a 33-bus test system and simulate by using MATLAB programming. The simulation results show that combination of DG, capacitor and network reconfiguration gives a positive impact on total power losses minimization as well as voltage profile improvement compared to other case studies

Shape selective alkylation of benzene with methanol over different zeolite catalysts

Benzene methylation is an important process for removing excess benzene in petrochemical industries to produce value-added products such as toluene and xylene. In this study, the performance of three types of zeolites, which is ZSM-5 (HZ), zeolite Y (HY) and zeolite β (Hβ) were investigated as catalyst in the benzene methylation reaction. The catalysts were characterized by N2 adsorption-desorption and FTIR. The N2 adsorption-desorption verified that the mesopores volume of the catalysts was in the following order: HB > HY > HZ. While, the FTIR-lutidine revealed that the HB possessed the highest amount of Brönsted acid sites followed by HZ and HY. The catalytic testing at 573 K showed that HZ gave good performance in benzene methylation with 55.2% and 22.1% yield of toluene and xylene, respectively. It is suggested that HZ catalyst with moderate amount of Brönsted acid sites and smallest mesopores volume appear to be effective for shape selective synthesis of toluene and xylene. In addition, pore structure of HZ also contributed to the high catalytic activity of benzene methylation

Toluene side chain alkylation with methanol over silica catalyst

MSN and SiO2 catalyst were investigated on side chain toluene alkylation with methanol reaction. Characterization of the catalyst were carried out by XRD, N2 physisorption analysis, FTIR spectroscopy. A pyrrole adsorption FTIR study reveals shifting of perturbed NH stretching increasing slightly in MSN compared to SiO2 catalyst revealed that MSN possessed higher basic sites than SiO2. N2 adsorption desorption isotherm analysis showed that MSN possessed higher surface area than SiO2 as well as increased the amount of mesopores in catalyst. The catalytic side chain toluene alkylation with methanol reaction was conducted in the range of 523K-673K under atmospheric pressure. MSN exhibits the highest catalytic performance compared to SiO2 catalyst

Effect of Different S AC Based Nanoparticles Types on the Reflow Soldering Process of Miniaturized Component using Discrete Phase Model Simulation

The wetting formation and nanoparticles dispersion on adding nanoparticles to the lead free solder Sn-3.0Ag-0.5Cu (SAC305) is methodically investigated using Discrete Phase Model (DPM) simulation and applied on a 01005 capacitor component. Different types of nanoparticles, namely titanium dioxide (TiO2), nickle oxide (NiO) and Iron (III) oxide (Fe2O3) with varying weight percentages, 0.01wt%, 0.05wt% and 0.15wt% that is doped in SAC305 are used. The study of two-way interactions between multiphase volume of fluid (VOF) and discrete phase model (DPM) shows excellent capability in tracking the dispersed nanoparticles immersed in the wetted molten solder. In this study, real reflow profile temperature setup will be used to mimic the conventional reflow process. Based on the findings, the fillet height managed to achieve the minimum required height set by IPC standards. As the concentration of the nanoparticles doped in the molten solder increases, higher time is required for the wetting process. In general, the doped NiO nanoparticles at 0.05wt% has the lowest wetting time compared to other cases. The study of the instantaneous nanoparticles trajectory tracking was also conducted on a 3D model and 2D cross sectional view to identify the exact movement of the particles. Additionally, it was also observed that the velocity and pressure distribution increases as the weight percentage of the nanoparticles increases

The prognostic association of SPAG5 gene expression in breast cancer patients with systematic therapy

Background: Despite much effort on the treatment of breast cancer over the decades, a great uncertainty regarding the appropriate molecular biomarkers and optimal therapeutic strategy still exists. This research was performed to analyze the association of SPAG5 gene expression with clinicopathological factors and survival outcomes. Methods: We used a breast cancer database including 5667 patients with a mean follow-up of 69 months. Kaplan-Meier survival analyses for relapse free survival (RFS), overall survival (OS), and distant metastasis-free survival (DMFS) were performed. In addition, ROC analysis was performed to validate SPAG5 as a prognostic candidate gene. Results: Mean SPAG5 expression value was significantly higher with some clinicopathological factors that resulted in tumor promotion and progression, including poor differentiated type, HER2 positive or TP53 mutated breast cancer. Based on ROC-analysis SPAG 5 is a suitable prognostic marker of poor survival. In patients who received chemotherapy alone, SPAG5 had only a moderate and not significant predictive impact on survival outcomes. However, in hormonal therapy, high SPAG5 expression could strongly predict prognosis with detrimental RFS (HR = 1.57, 95% CI 1.2-2.06, p = 0.001), OS (HR = 2, 95% CI 1.05-3.8, p = 0.03) and DMFS (HR = 2.36, 95% CI 1.57-3.54, p < 0.001), respectively. In addition, SPAG5 could only serve as a survival predictor in ER+, but not ER- breast cancer patients. Patients might also be at an increased risk of relapse despite being diagnosed with a lower grade cancer (well differentiated type). Conclusions: SPAG5 could be used as an independent prognostic and predictive biomarker that might have clinical utility, especially in ER+ breast cancer patients who received hormonal therapy. © 2019 The Author(s)