Evaluation of hydrogen effect on the fatigue crack growth behavior of medium-Mn steels via in-situ hydrogen plasma charging in an environmental scanning electron microscope

Fatigue crack growth(FCG)tests were conducted on a medium-Mn steel annealed at two intercritical annealing temperatures,resulting in different austenite(γ)to ferrite(α)phase fractions and different γ(meta-)stabilities.Novel in-situ hydrogen plasma charging was combined with in-situ cyclic loading in an environmental scanning electron microscope(ESEM).The in-situ hydrogen plasma charging increased the fatigue crack growth rate(FCGR)by up to two times in comparison with the reference tests in vacuum.Fractographic investigations showed a brittle-like crack growth or boundary cracking manner in the hydrogen environment while a ductile transgranular manner in vacuum.For both materials,the plastic deformation zone showed a reduced size along the hydrogen-influenced fracture path in comparison with that in vacuum.The difference in the hydrogen-assisted FCG of the medium-Mn steel with different microstructures was explained in terms of phase fraction,phase stability,yielding strength and hydrogen distribution.This refined study can help to understand the FCG mechanism without or with hydrogen under in-situ hydrogen charging conditions and can provide some insights from the applications point of view.     

Rate and microstructure influence on the fracture behavior of cemented carbides WC-Co and WC-Ni

Tungsten carbide has both industrial and military applications, from high strength end mill dies and geological drilling, to kinetic energy penetrators. In these extreme environments, an understanding of the dynamic fracture properties and the potential influence of grade microstructure is necessary. The present work investigates fracture behavior of cobalt and nickel cemented tungsten carbide with varying grain size and binder content. Notched hardmetal WC-Co and WC-Ni samples are impacted under mode-I (opening) fracture conditions, and the dynamic stress intensity factor is determined from digital image correlation using ultra high-speed imaging, and compared with quasi-static values. In both grain size and binder content variants examined, the dynamic fracture toughness increased from the quasi-static by a factor of 1.51–2.44. In addition, a 7% increase in cobalt binder content (while maintaining nominally identical average grain size) resulted in a 20% increase in quasi-static fracture toughness, from 8.62 to 10.38 MPa\(\sqrt{\text {m}}\); while the same binder increase resulted in a 34% decrease in critical SIF from 21.07 to 15.72 MPa\(\sqrt{\text {m}}\). The 6% nickel binder WC was found to have a 4.5% higher quasi-static fracture toughness than the 6% cobalt binder WC of the same grain size, but a statistically insignificant difference under dynamic loading. Overall, there is a 28% increase in the quasi-static fracture toughness of tungsten carbide samples with an increase of average grain size from 1 to 3 \(\upmu \)m, and under dynamic loading the larger grain WC shows a nominally identical increase in fracture toughness. These findings are discussed within the theory of classical dynamic fracture mechanics, the implications of the experimental configurations pursued, and the microstructural features are examined using fractography.     

Synthesis of undoped and Fe nanoparticles doped SnO<Subscript>2</Subscript> nanostructure: study of structural,optical and electrocatalytic properties

In this study, undoped and nano Fe doped SnO₂ nanostructures were synthesized by hydrothermal method. Characterization of the synthesized nanostructures was performed by X-ray diffraction and scanning electron microscopy. For investigation of optical properties, photo luminescence and UV–Vis spectrum were taken. The electrochemical response of the carbon paste electrode modified with synthesized nanostructures toward levodopa (L-Dopa) was studied. Cyclic voltammetry studies using prepared modified electrodes showed outstanding electrocatalytic properties towards electro-oxidation of L-Dopa and a significant reduction was observed in anodic over voltage compared to the bare electrode. Obtained results indicated the effective role of the employed dopant. Best response in terms of the current enhancement, overvoltage reduction, and reversibility improvement of the L-Dopa oxidation reaction under experimental conditions was obtained by modified electrode with Fe doped SnO₂ nanoparticles.     

Estimation of homogenisation time for superalloys based on a new diffusional model

The inter-diffusion of segregating elements (Nb, Mo, and Ti) in the cast ingot of Inconel 718 superalloy during homogenisation at elevated temperature was studied by a new model based on the characteristic diffusion length. The proposed simple method was used for obtaining the homogenisation time required for back-diffusion of each element. Therefore, the developed model can be used for both studying the diffusion of alloying elements and estimation of homogenisation time, where the latter is important from the industrial standpoint.     

Influence of heat treatment and aging on microstructure and mechanical properties of Mg‐1.8Zn‐0.7Si‐0.4Ca alloy

In order to optimize the aging treatment of Mg‐1.8Zn‐0.7Si‐0.4Ca alloy, different times and temperatures of solid solution and age hardening were applied to the alloy specimens. Microstructures and mechanical properties of the specimens were investigated using the optical microscopy, field emission scanning electron microscopy equipped with an energy dispersive x‐ray spectrometer, x‐ray diffraction, hardness, and shear punch tests. The lowest hardness and strength were achieved by solution treating of the alloy at 500 °C for 8 h, presenting the optimal condition for solution treatment of the alloy. The microstructural examinations revealed three different precipitates consisting of CaMgSi, Ca₂Mg₆Zn₃, and Mg₂Si in the solid solution specimens. It was found that the highest peak hardness and strength are obtained by aging the alloy at 150 °C for 16 h. This condition was confirmed by differential scanning calorimetry (DSC) tests performed on the solid solution and aged specimens.     

Incremental one-class classifier based on convex–concave hull

Pattern Analysis and Applications - One subject that has been considered less is a binary classification on data streams with concept drifting in which only information of one class (target class)...     

Wideband Frequency-Reconfigurable Antenna for Airborne Applications

Wireless Personal Communications - One of the important objectives of underwater acoustic sensor network is to extend the lifespan of a network which depends on the topology control mechanisms....     

A joint correlation noise estimation and decoding algorithm for distributed video coding

Multimedia Tools and Applications - Distributed video coding is relatively a novel video coding paradigm that enables a lower complex video encoding compared to conventional video coding schemes,...     

Partial fingerprint identification for large databases

Nowadays, most fingerprint sensors capture partial fingerprint images. Incomplete, fragmentary, or partial fingerprint identification in large databases is an attractive research topic and is remained as an important and challenging problem. Accordingly, conventional fingerprint identification systems are not capable of providing convincing results. To overcome this problem, we need a fast and accurate identification strategy. In this context, fingerprint indexing is commonly used to speed up the identification process. This paper proposes a robust and fast identification system that combines two indexing algorithms. One of the indexing algorithms uses minutiae triplets, and the other uses orientation field (OF) to index and retrieve fingerprints. Furthermore, the proposal uses some partial fingerprint matching methods on final candidate list obtained from the indexing stage. The proposal is evaluated over two national institutes of standards and technology (NIST) datasets and four fingerprint verification competition (FVC) datasets leading to low identification times with no accuracy loss.