Transient liquid phase sintering of high-purity mullite for high-temperature structural ceramics

High-purity mullite ceramics, promising engineering ceramics for high-temperature applications, were fabricated using transient liquid phase sintering to improve their high-temperature mechanical properties. Small amounts of ultrafine alumina or silica powders were uniformly mixed with the mullite precursor depending on the silica-alumina ratio of the resulting ceramics to allow for the formation of a transient liquid phase during sintering, thus, enhancing densification at the early stage of sintering and mullite formation by the reaction between additional alumina and the residual glassy phase (mullitization) at the final stage of sintering. The addition of alumina powder to the silica-rich mullite precursor resulted in a reaction between the glassy silica and alumina phases during sintering, thereby forming a mullite phase without inhibiting densification. The addition of fine silica powder to the mullite single-phase precursor led to densification with an abnormal grain growth of mullite, whereas some of the added silica remained as a glassy phase after sintering. The resulting mullite ceramics prepared using different powder compositions showed different sintering behaviors, depending on the amount of alumina added. Upon selecting an optimum process and the amount of alumina to be added, the pure mullite ceramics obtained via transient liquid phase sintering exhibited high density (approximately 99%) and excellent high-temperature flexural strength (approximately 320 MPa) at 1500 °C in air. These results clearly demonstrate that pure mullite ceramics fabricated via transient liquid phase sintering with compositions close to those of stoichiometric mullite could be a promising process for the fabrication of high-temperature structural ceramics used in an ambient atmosphere. The transient liquid phase sintering process proposed in this study could be a powerful processing tool that allows for the preparation of superior high-temperature structural ceramics used in the ambient processing atmosphere.     

Multi-criteria analysis for screening of reversible metal hydrides in hydrogen gas storage and high pressure delivery applications

Metals and alloys forming reversible hydrides with hydrogen gas are potential building blocks for compact, solid state hydrogen storage systems. Based on the materials’ thermodynamic characteristics, their use as temperature-swing gas compression and delivery systems in the hydrogen economy is also possible. Given the wide variety of materials developed and tested at laboratory and pilot scales, a harmonized method of selecting the feasible material(s) for a particular real-life application is required. This study proposes a system selection framework based on a normalized, multi-criteria metric. Using calculated values of multi-criteria metric, multi-criteria screening and ranking of potential materials has been demonstrated for a particular use case. It is found that the alloy TiMn_1.52 having value of additive metric between 0.25 and 0.35 represents the best material for a single stage system. The alloy pair CaNi₅–Ti_1.5CrMn represents the best alternative for a two-stage system with additive metric values between 0.63 and 0.82. Energy and economic characteristics of the metal hydride gas compression and delivery systems are evaluated and compared with an equivalent mechanical compression system producing the same final effect (i.e., delivery of a given quantity of gas at a defined pressure).     

Optimization of hydrogen enrichment via palladium membrane in vacuum environments using Taguchi method and normalized regression analysis

In this study, the separation of hydrogen from gas mixtures using a palladium membrane coupled with a vacuum environment on the permeate side was studied experimentally. The gas mixtures composed of H₂, N₂, and CO₂ were used as the feed. Hydrogen permeation fluxes were measured with membrane operating temperature in the range of 320–380 °C, pressures on the retentate side in the range of 2–5 atm, and vacuum pressures on the permeate side in the range of 15–51 kPa. The Taguchi method was used to design the operating conditions for the experiments based on an orthogonal array. Using the measured H₂ permeation fluxes from the Taguchi approach, the stepwise regression analysis was also employed for establishing the prediction models of H₂ permeation flux, followed by the analysis of variance (ANOVA) to identify the significance and suitability of operating conditions. Based on both the Taguchi approach and ANOVA, the H₂ permeation flux was mostly affected by the gas mixture composition, followed by the retentate side pressure, the vacuum degree, and the membrane temperature. The predicted optimal operating conditions were the gas mixture with 75% H₂ and 25% N₂, the membrane temperature of 320 °C, the retentate side pressure of 5 atm, and the vacuum degree of 51 kPa. Under these conditions, the H₂ permeation flux was 0.185 mol s^?1 m^?2. A second-order normalized regression model with a relative error of less than 7% was obtained based on the measured H₂ permeation flux.     

Co2FeO4@rGO composite: Towards trifunctional water splitting in alkaline media

Development of efficient, low cost and multifunctional electrocatalysts for water splitting to harvest hydrogen fuels is a challenging task, but the combination of carbon materials with transition metal-based compounds is providing a unique and attractive strategy. Herein, composite systems based on cobalt ferrite oxide-reduced graphene oxide (Co₂FeO₄) @(rGO) using simultaneous hydrothermal and chemical reduction methods have been prepared. The proposed study eliminates one step associated with the conversion of GO into rGO as it uses direct GO during the synthesis of cobalt ferrite oxide, consequently rGO based hybrid system is achieved in-situ significantly, the optimized Co₂FeO₄@rGO composite has revealed an outstanding multifunctional applications related to both oxygen evolution reaction (OER) and hydrogen counterpart (HER). Various metal oxidation states and oxygen vacancies at the surface of Co₂FeO₄@rGO composites guided the multifunctional surface properties. The optimized Co₂FeO₄@rGO composite presents excellent multifunctional properties with onset potential of 0.60 V for ORR, an overpotential of 240 mV at a 20 mAcm^?2 for OER and 320 mV at a 10 mAcm^?2 for HER respectively. Results revealed that these multifunctional properties of the optimized Co₂FeO₄@ rGO composite are associated with high electrical conductivity, high density of active sites, crystal defects, oxygen vacancies, and favorable electronic structure arisinng from the substitution of Fe for Co atoms in binary spinel oxide phase. These surface features synergistically uplifted the electrocatalytic properties of Co₂FeO₄@rGO composites. The multifunctional properties of the Co₂FeO₄@ rGO composite could be of high interest for its use in a wide range of applications in sustainable and renewable energy fields.     

Effect of micro-cracks on the in-plane electronic conductivity of proton exchange membrane fuel cell catalyst layers based on lattice Boltzmann method

Micro-cracks commonly occur on the catalyst layers (CLs) during the manufacturing of catalyst coated membranes (CCMs). However, the crack shape parameters effect on CLs in-plane (IP) electronic conductivity λ_s is not clear. In this work, the relationship between crack parameters and the λ_s is obtained based on the two-dimensional (2D) multiple-relaxation time (MRT) lattice Boltzmann method (LBM). The LBM numerical model is validated by the normalized λ_s experiment applied on three different home-made cracked CLs, and the parameter study focus on crack width, length, quantity and phase angle are carried out. The results show that the decrease of λ_s has different sensitivity |k| to the parameters above. The crack width has little effect on λ_s decrease, and the |k_w| is 0.038. However, crack arm length and quantity show more significant impact, which |k_l| and |k_N| are 0.753 and 0.725, respectively. The CLs with different crack propagation directions show significant anisotropy on λ_s, and a 53.53% decrease in λ_s is observed between 0° and 90° crack phase angle change. To manufacture a high electronic conductivity CL, crack initiation and migration mitigation are highly encouraged.     

Formation of acrylamide in microwave-roasted sorghum and associated dietary risk

The effect of microwave roasting parameters (300, 450 and 600 W; 5, 10 and 15 min) on acrylamide content in sorghum grain was determined using High Pressure Liquid Chromatography (HPLC)-photo diode array (PDA) detector coupled with C-18 column. Samples roasted at 300 and 450 W did not possess acrylamide, whereas 600 W (15 min) favoured formation of 2740.19 µg/kg of acrylamide, levels far exceeding the defined European Union (EU) limits. The chronic daily intake (CDI) for acrylamide through consumption of such grain flour was 3.25–9.5-fold higher to Joint FAO/WHO Expert Committee on Food Additives (JECFA) defined high exposure limits. The margin of exposure (MOE) values ranged from 4.3 to 12.76 and from 11.07 to 32.27 for neoplastic and neurological effects, respectively, demonstrating high exposure and serious health concerns associated with dietary intake of this toxicant. This study assesses the risk for the Indian population and highlights the importance of optimising process parameters for food product to minimise such exposure risks.     

Tabular data: Deep learning is not all you need

A key element in solving real-life data science problems is selecting the types of models to use. Tree ensemble models (such as XGBoost) are usually recommended for classification and regression problems with tabular data. However, several deep learning models for tabular data have recently been proposed, claiming to outperform XGBoost for some use cases. This paper explores whether these deep models should be a recommended option for tabular data by rigorously comparing the new deep models to XGBoost on various datasets. In addition to systematically comparing their performance, we consider the tuning and computation they require. Our study shows that XGBoost outperforms these deep models across the datasets, including the datasets used in the papers that proposed the deep models. We also demonstrate that XGBoost requires much less tuning. On the positive side, we show that an ensemble of deep models and XGBoost performs better on these datasets than XGBoost alone.     

Magnetic properties,phase evolution,hollow structure and biomedical application of hematite (α-Fe2O3) and QUAIPH

We investigate synthesis, phase evolution, hollow and porous structure and magnetic properties of quasi-amorphous intermediate phase (QUAIPH) and hematite (α-Fe₂O₃) nanostructure synthesized by annealing of akaganeite (β-FeOOH) nanorods. It is found that the annealing temperature determines the phase composition of the products, the crystal structure/size dictates the magnetic properties whereas the final nanorod morphology is determined by the starting material. Annealing of β-FeOOH at ～300 °C resulted in the formation of hollow QUAIPH nanorods. The synthesized material shows low-cytotoxicity, superparamagnetism and good transverse relaxivity, which is rarely reported for QUAIPH. The QUAIPH nanorods started to transform to porous hematite nanostructures at ～350 °C and phase transformation was completed at 600 °C. During the annealing, the crystal structure changed from monoclinic (akaganeite) to quasi-amorphous and rhombohedral (hematite). Unusually, the crystallite size first decreased (akaganeite → QUAIPH) and then increased (QUAIPH → hematite) during annealing whereas the nanorods retained particle shape. The magnetic properties of the samples changed from antiferromagnetic (akaganeite) to superparamagnetic with blocking temperature T_B = 84 K (QUAIPH) and finally to weak-ferromagnetic with the Morin transition at T_M = 244 K and high coercivity H_C = 1652 Oe (hematite). The low-cytotoxicity and MRI relaxivity (r₂ = 5.80 mM^?1 s^?1 (akaganeite), r₂ = 4.31 mM^?1 s^?1 (QUAIPH) and r₂ = 5.17 mM^?1 s^?1 (hematite)) reveal potential for biomedical applications.     

Simulation of hydrogen and coal gas fueled flat-tubular solid oxide fuel cell (FT-SOFC)

Solid oxide fuel cells (SOFCs) are considered an important technology in terms of high efficiency and clean energy generation. Flat-tubular solid oxide fuel cell (FT-SOFC) which is a combination of tubular and planar cell geometries stands out with its performance values and low costs. In this study, the performance of an FT-SOFC is analyzed numerically by using finite element method-based design as a result of changing parameters by using different fuels which are pure hydrogen and coal gas with various proportions of CO. In addition, cell performance values for different temperatures were analyzed and interpreted. Analyzes have been performed by using COMSOL Multiphysics software. The rates of CO composition used are 10%, 20%, and 40%, respectively. In addition, the air was used as the oxidizer in all cases. The cell voltage and average cell power of the FT-SOFC were examined under the 800 °C operating condition. The maximum power value and current density value were obtained as 710 W/m² and 1420 A/m² for the flat-tubular cell, respectively. As a result of the study, it was observed that the maximum cell power densities increased with increasing temperature. Analysis results showed that FT-SOFCs have suitable properties for different fuel usage and different operating temperatures. High-performance values and design features in different operating conditions are expected to make FT-SOFC the focus of many studies in the future.     

LinkingPark: An automatic semantic table interpretation system

In this paper, we present LinkingPark, an automatic semantic annotation system for tabular data to knowledge graph matching. LinkingPark is designed as a modular framework which can handle Cell-Entity Annotation (CEA), Column-Type Annotation (CTA), and Columns-Property Annotation (CPA) altogether. It is built upon our previous SemTab 2020 system, which won the 2nd prize among 28 different teams after four rounds of evaluations. Moreover, the system is unsupervised, stand-alone, and flexible for multilingual support. Its backend offers an efficient RESTful API for programmatic access, as well as an Excel Add-in for ease of use. Users can interact with LinkingPark in near real-time, further demonstrating its efficiency.