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.     

Thermomechanical stability and inelastic energy dissipation as durability criteria for fuel cell gas diffusion media with pre-assembly effects

In this article, pre-assembly hot-press pressure and thermal expansion effects in gas-diffusion layers (GDLs) are addressed to explore the practicalities of the constitutive model reported in the companion article. A facile technique is proposed to include deformation history dependent residual strain effects. The model is implemented in the numerical environment and compared with widely followed conventional models such as isotropic and orthotropic material models. With the normal and accelerated thermal expansion effects no significant variation in stresses or strains is reported with the compressible GDL model in contrast to the conventional incompressible form of the GDL model. The present work identifies the critical differences with advanced and extended variants of the model along with conventional GDL material models in terms of planar stress/strain distribution and the membrane response. Finally, the model is simulated for micro-cyclic stress loads of varying amplitudes that imitate the real working conditions of fuel cell. The inelastic energy dissipation in GDLs is predicted using the proposed model, which is utilized further to distinguish the safe (elastic) and unsafe (inelastic shakedown) operating limits. The inelastic collapse of GDLs is shown to be a active function of high amplitude micro-cyclic load with high initial clamping load.     

The decreasing effect of ammonia enrichment on the combustion emission of hydrogen,methane, and propane fuels

In the present study, non-premixed combustion and NOx emission of H₂, NH₃, C₃H₈, and CH₄ fuels have been studied in a combustion test unit under lean mixture conditions (λ = 4) at 8.6 kW thermal capacity. Furthermore, the combustion and NOx emission of the H₂, C₃H₈, and CH₄ fuels have been investigated for various NH₃ enrichment ratios (5, 10, 20, and 50%) and excess air coefficients (λ = 1.1, 2, 3, and 4) at the same thermal capacity. The obtained results have been compared for each fuel. Numerical simulation results show that H₂ emits intense energy through the reaction zone despite the lowest fuel consumption in mass, among others, due to its high calorific value. Therefore, it has a higher flame temperature than others. At the same time, C₃H₈ has the lowest flame temperature. Besides, NH₃ has the shortest flame length among others, while C₃H₈ has the most extended flame form. The highest level of NOx is released from the NH₃ flame in the combustion chamber, while the lowest NOx is released from the CH₄. However, the lowest NOx emission at the combustion chamber exit is obtained in NH₃ combustion, while the highest NOx emission is obtained with H₂ combustion. It results from the shortest flame length of NH₃, short residence time, and backward NOx reduction to N₂ for NH₃. As for H₂, high flame temperature and relatively long flame, and high residence time of the products trigger NOx formation and keep the NOx level high. On the other hand, excess air coefficient from 1.1 to 2 increases NOx for H₂, CH₄, and NH₃ due to their large flame diameters, unlike propane. Then, NOx emission levels decrease sharply as the excess air coefficient increases to 4 for each fuel. NH₃ fuel also emits minimum NOx in other excess air coefficients at the exit, while H₂ emits too much emission. With NH₃ enrichment, the NOx emissions of H₂, CH₄, and C₃H₈ fuels at the combustion chamber exit decrease gradually almost every excess air coefficient apart from λ = 1.1. As a general conclusion, like renewable fuels, H₂ appears to be a source of pollution in terms of NOx emissions in combustion applications. In contrast, NH₃ appears to be a relatively modest fuel with a low NOx level. In addition, the high amount of NOx emission released from H₂ and other fuels during the combustion can be remarkably reduced by NH₃ enrichment with an excess air combustion.     

Densification effects on the fracture in fused silica under Vickers indentation

This study investigates the effects of densification on the deformation and fracture in fused silica under Vickers indentation by both the finite element analysis (FEA) and experimental tests. A refined elliptical constitutive model was used, which enables us to investigate the effects of the evolution of yield stress under pure shear and elastic properties with densification. The densification distribution was predicted and compared with experiments. The plastic deformation and indentation stress fields were used to analyze the initiation and morphology of various crack types. The formation mechanism of borderline cracks was revealed for the first time. This study reveals that the asymmetry of the densification distribution and elastic-plastic boundary significantly influences the cracking behavior. Under the Vickers indentation, conical cracks have the largest penetration depth. When these cracks emerge from a region far from the impression, they extend with constant radii to form circles on the sample surface. Otherwise, they tend to be initiated at the centers of the indenter-material contact edges before propagating towards the impression corners with increasing radii. Therefore, the borderline cracks consisting of successive partial conical cracks can form at a low load and makes them the first type of crack to appear.     

Modulation of electrical transport in calcium cobaltite ceramics and thick films through microstructure control and doping

Ca₃Co₄O₉ is a promising p-type thermoelectric oxide material having intrinsically low thermal conductivity. With low cost and opportunities for automatic large scale production, thick film technologies offer considerable potential for a new generation of micro-sized thermoelectric coolers or generators. Here, based on the chemical composition optimized by traditional solid state reaction for bulk samples, we present a viable approach to modulating the electrical transport properties of screen-printed calcium cobaltite thick films through control of the microstructural evolution by optimized heat-treatment. XRD and TEM analysis confirmed the formation of high-quality calcium cobaltite grains. By creating 2.0 at% cobalt deficiency in Ca_2.7Bi_0.3Co₄O_9+δ, the pressureless sintered ceramics reached the highest power factor of 98.0 μWm^?1 K^-2 at 823 K, through enhancement of electrical conductivity by reduction of poorly conducting secondary phases. Subsequently, textured thick films of Ca_2.7Bi_0.3Co_3.92O_9+δ were efficiently tailored by controlling the sintering temperature and holding time. Optimized Ca_2.7Bi_0.3Co_3.92O_9+δ thick films sintered at 1203 K for 8 h exhibited the maximum power factor of 55.5 μWm^?1 K^-2 at 673 K through microstructure control.     

A review of hydrogen production processes by photocatalytic water splitting – From atomistic catalysis design to optimal reactor engineering

‘Renewable energy is an essential part of our strategy of decarbonization, decentralization, as well as digitalization of energy.’ – Isabelle Kocher.Current climate, health and economic condition of our globe demands the use of renewable energy and the development of novel materials for the efficient generation, storage and transportation of renewable energy. Hydrogen has been recognised as one of the most prominent carriers and green energy source with challenging storage, enabling decarbonization. Photocatalytic H₂ (green hydrogen) production processes are targeting the intensification of separated solar energy harvesting, storage and electrolysis, conventionally yielding O₂/H₂. While catalysis is being investigated extensively, little is done on bridging the gap, related to reactor unit design, optimisation and scaling, be it that of material or of operation. Herein, metals, oxides, perovskites, nitrides, carbides, sulphides, phosphides, 2D structures and heterojunctions are compared in terms of parameters, allowing for efficiency, thermodynamics or kinetics structure–activity relationships, such as the solar-to-hydrogen (STH). Moreover, prominent pilot systems are presented summarily.     

Machine learning algorithm selection for windage alteration fault diagnosis of mine ventilation system

Machine learning algorithms have been widely used in mine fault diagnosis. The correct selection of the suitable algorithms is the key factor that affects the fault diagnosis. However, the impact of machine learning algorithms on the prediction performance of mine fault diagnosis models has not been fully evaluated. In this study, the windage alteration faults (WAFs) diagnosis models, which are based on K-nearest neighbor algorithm (KNN), multi-layer perceptron (MLP), support vector machine (SVM), and decision tree (DT), are constructed. Furthermore, the applicability of these four algorithms in the WAFs diagnosis is explored by a T-type ventilation network simulation experiment and the field empirical application research of Jinchuan No. 2 mine. The accuracy of the fault location diagnosis for the four models in both networks was 100%. In the simulation experiment, the mean absolute percentage error (MAPE) between the predicted values and the real values of the fault volume of the four models was 0.59%, 97.26%, 123.61%, and 8.78%, respectively. The MAPE for the field empirical application was 3.94%, 52.40%, 25.25%, and 7.15%, respectively. The results of the comprehensive evaluation of the fault location and fault volume diagnosis tests showed that the KNN model is the most suitable algorithm for the WAFs diagnosis, whereas the prediction performance of the DT model was the second-best. This study realizes the intelligent diagnosis of WAFs, and provides technical support for the realization of intelligent ventilation.     

Digital twin-based analysis of volumetric error mapping procedures

The evaluation of the volumetric accuracy of a machine tool is an open challenge in the industry, and a wide variety of technical solutions are available in the market and at research level. All solutions have advantages and disadvantages concerning which errors can be measured, the achievable uncertainty, the ease of implementation, possibility of machine integration and automation, the equipment cost and the machine occupation time, and it is not always straightforward which option to choose for each application. The need to ensure accuracy during the whole lifetime of the machine and the availability of monitoring systems developed following the Industry 4.0 trend are pushing the development of measurement systems that can be integrated in the machine to perform semi-automatic verification procedures that can be performed frequently by the machine user to monitor the condition of the machine. Calibrated artefact based calibration and verification solutions have an advantage in this field over laser based solutions in terms of cost and feasibility of machine integration, but they need to be optimized for each machine and customer requirements to achieve the required calibration uncertainty and minimize machine occupation time.This paper introduces a digital twin-based methodology to simulate all relevant effects in an artefact-based machine tool calibration procedure, from the machine itself with its expected error ranges, to the artefact geometry and uncertainty, artefact positions in the workspace, probe uncertainty, compensation model, etc. By parameterizing all relevant variables in the design of the calibration procedure, this simulation methodology can be used to analyse the effect of each design variable on the error mapping uncertainty, which is of great help in adapting the procedure to each specific machine and user requirements. The simulation methodology and the analysis possibilities are illustrated by applying it on a 3-axis milling machine tool.     

Electrodeposition of the manganese-doped nickel-phosphorus catalyst with enhanced hydrogen evolution reaction activity and durability

Hydrogen technology is widely considered a novel clean energy source, and electrolysis is an effective method for hydrogen evolution. Therefore, efficient hydrogen evolution reaction (HER) catalysts are urgently needed to replace precious metal catalysts and meet ecological and environmental protection standards. Herein, Ni–Mn–P electrocatalysts are synthesized using facile electrodeposition technology. The influence of the Mn addition on the catalytic behavior is studied by the comprehensive analysis of catalytic performance and morphology of the catalysts. Among them, the Ni–Mn–P0.01 catalyst exhibits small coral-like structures, greatly improving the adsorption and desorption of hydrogen ions and reducing the overpotential hydrogen evolution. Consequently, overpotential at 10 mA cm^?2 electric current density is 113 mV, and the value of the Tafel slope achieves 74 mV/dec. Furthermore, the Ni–Mn–P catalyst shows long-time (20 h) stability at current densities of 10 and 60 mA/cm². The results confirm that the synergistic effect of Ni, Mn, and P accelerates the electrochemical reaction. Meanwhile, the addition of manganese element can change the micromorphology of the catalyst, thereby exposing more active sites to participate in the reaction, enhancing water ionization, improving the catalytic performance. This study opens a new way toward improving the activity of the catalyst by adjusting Mn concentration during the electrodeposition process.