Recent developments in catalyst synthesis using DBD plasma for reforming applications

The catalyst has a significant role in gas processing applications such as reforming technologies for H₂ and syngas production. The stable catalyst is requisite for any industrial catalysis application to make it commercially viable. Several methods are employed to synthesize the catalysts. However, there is still a challenge to achieve a controlled morphology and pure catalyst which majorly influences the catalytic activity in reforming applications. The conventional methods are expansive, and the removal of the impurities are major challenges. Nevertheless, it is not straightforward to achieve the desired structure and stability. Therefore, significant interest has been developed on the advanced techniques to take control of the physicochemical properties of the catalyst through non-thermal plasma (NTP) techniques. In this review, the systematic evolution of the catalyst synthesis using NTP technique is elucidated. The emerging DBD plasma to synthesized and effective surface treatment is reviewed. DBD plasma synthesized catalyst performance in reforming application for H₂ and syngas production is summarised. Furthermore, the status of DBD plasma for catalyst synthesis and proposed future avenues to design environmentally suitable and cost-effective synthesis techniques are discussed.     

Forecasting hydrogen production potential in islamabad from solar energy using water electrolysis

The focus of this study is the use of Machine Learning methods to forecast Solar Hydrogen production potential for the Islamabad region of Pakistan. For this purpose, we chose a Photovoltaic-Electrolytic (PV-E) system to forecast electricity and, hence, hydrogen production. The weather data used for forecasting and simulation were recorded with precise meteorological instruments stationed in Islamabad, over the course of 13 and a half months. Out of the three tested algorithms, Prophet performs the best with Mean Absolute Percentage Error of 3.7%, forecasting a daily average Hydrogen production of 93.3 × 10³ kg/Km². Although, the forecast in this study is made for the month of August and September, during which the local season moves towards winter, this study demonstrates solar hydrogen production, as a green energy source, has a tremendous potential in this region.     

A computer-aided diagnostic system for liver tumor detection using modified U-Net architecture

The Journal of Supercomputing - A multimedia-based medical decision-making system is an ultimate requirement in the medical imaging domain. In the healthcare sector, achieving quick and efficient...     

A multi‐objective evolutionary optimization of fuzzy controller for energy conservation in air conditioning systems

This paper presents the use of evolutionary optimization approach to design and tune smart fuzzy controllers for heating, ventilation, and air conditioning systems or HVAC. The objective is to optimize energy consumption while accounting for user comfort requirements. The problem of energy conservation in air conditioning systems becomes a multi‐objective optimization constrained problem, which enlarges the solution search space. To solve this problem, a multi‐objective evolutionary optimization technique based on genetic algorithm (GA) is proposed. A physical experimental setup is constructed for data collection and formulation of mathematical model. A fuzzy controller is initially designed through expert knowledge, and GA is then used to tune the rules and membership functions of the fuzzy controller in order to optimize multiple objectives. Simulations and real experiments are compared to determine the effectiveness of the proposed strategy. As compared to the controller present in the real experimental air conditioner, approximately 15% energy is successfully saved with no increase in average individual dissatisfaction or discomfort index. Also, a decrease in peak individual dissatisfaction or discomfort index from 91% to 62% is observed. Copyright © 2013 John Wiley & Sons, Ltd.     

Foliar Application of Silicon Enhances Growth,Flower Yield,Quality and Postharvest Life of Tuberose (Polianthes tuberosa L.) under Saline Conditions by Improving Antioxidant Defense Mechanism

Silicon - Tuberose is native to Mexico and then reached Europe and spread other parts of the world. In Pakistan, tuberose stalks come in the market during late summer and autumn when only few...     

Performance enhancement and energy reduction using hybrid cryogenic distillation networks for purification of natural gas with high CO2 content

A novel concept of hybrid cryogenic distillation network has been explored which maximizes the benefits of both desublimation or solid-vapor based separation as well as distillation or vapor-liquid equilibrium based separation during the separation of carbon dioxide from methane or natural gas. Process network synthesis has been performed for four case studies with high carbon dioxide (72 mole%) and medium carbon dioxide (50 mole%) natural gas feed streams. The benefits of optimal locations for cryogenic packed beds were investigated. A conventional cryogenic network consisting of multiple distillation columns with butane as additive for extractive distillation was also studied and presented in this paper. Process modeling of cryogenic distillation network with MESH equations was attempted using an integrated dual loop (C+3) convergence and the results were compared with Aspen Plus simulator for benchmarking. The prediction of solidification region was employed using experimental data from literature to avoid solidification regions in the column. The proposed hybrid cryogenic distillation network showed promising potential for energy and size reduction.     

Structural and magnetic properties of erbium doped nanocrystalline Li–Ni ferrites

A series of nanocrystalline Li_0.25Ni_0.5Fe_2.25−xEr_xO₄ (x=0.00, 0.02, 0.06, 0.08, and 0.10) ferrite powders, having a cubic spinel crystal structure and a low value of coercivity, was synthesized by the sol–gel auto-combustion route. The structure, morphology and magnetic properties of the prepared nanoferrites were characterized by powder X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and the magnetic property measurement system (MPMS). A well-defined single phase spinel structure is confirmed in all the samples by X-ray diffraction analysis. The lattice parameters of the samples increase slightly with increasing the erbium content. The crystallite size of the Er-doped samples is smaller than that of pure Li–Ni ferrite, and decrease regularly in the range of 36.0–14.5 nm. It has been observed that the magnetic properties of these ferrites are strongly influenced by the added erbium content. The magnetic measurements indicate that saturation magnetization (M_s) and coercivity (H_c) decrease gradually with the increase of Er content in the lattice.     

Iron oxide supported sulfated TiO2 nanotube catalysts for NO reduction with propane

Sulfated TiO₂ nanotubes and a series of iron oxide loaded sulfated TiO₂ nanotubes catalysts with different iron oxide loadings (1 wt%, 3 wt%, 5 wt% and 7 wt%) were prepared and calcined at 400 °C. The physico-chemical properties of the catalysts were studied by using XRD, N₂-physisorption, Raman spectroscopy, SEM-EDX, TEM, XPS, and pyridine adsorption using FTIR and H₂-TPR techniques. It was observed that iron oxide was highly dispersed on the sulfated TiO₂ nanotube support due to its strong interaction. The activity of these catalysts in the catalytic removal of NO with propane was also studied in the temperature range of 300–500 °C. Highest activity (90% NO conversion) was observed with 5 wt% iron oxide supported on sulfated TiO₂ catalyst at 450 °C. Selective catalytic reduction of NO activity of the catalysts was correlated with iron oxide loading, reducibility, and the Brönsted and Lewis acid sites of the catalysts. The catalyst also showed good stability under studied reaction conditions that no deactivation was observed during the 50 h of reaction.