In this paper, aluminium-vanadium master alloys AlVx (x = 55, 65, 85) were prepared by the aluminothermic reduction method. The thermodynamic characteristics of the reaction and the microstructures of the alloys were systematically analysed. The aluminothermic reaction was confirmed to proceed spontaneously with intense exothermic characteristics, exhibiting a specific heat release of up to 4988 J/g. For the AlV55 alloy, the grains displayed a granular morphology with a relatively finer grain size, and its fracture exhibited an intergranular fracture mode. For the AlV65 and AlV85 alloys, the grains exhibited a columnar morphology with a coarser grain size. These two alloys (AlV65 and AlV85) exhibited a relatively bright metallic lustre, and their fractures presented a cleavage fracture mode. The Al8V5 phase accounted for a large proportion in the AlV55 alloy; the AlV3 phase accounted for a large proportion in the AlV65 alloy; and only the AlV3 phase was detected in the AlV85 alloy. The AlV85 alloy exhibited the highest chemical composition homogeneity, whereas the AlV55 alloy showed the lowest. This phenomenon was mainly attributed to the solidification temperature range, as well as the phase proportion and distribution characteristics associated with the specific alloy composition.
This paper explores how experiments influence the reception of interpretations of quantum mechanics, and also other relations between experiments and interpretations in that field. We start by surveying the struggle of different schools of philosophy of science in the 19th and early 20th centuries to adapt to the scientific advances, and then give a brief overview of realist and antirealist interpretations in quantum mechanics. Eight different types of relations between interpretations and experiments are then examined, with case studies from the history of quantum mechanics. (1) Many interpretations agree with all of the predictions of the instrumentalist interpretation, which is a good strategy for survival. (2) Some interpretations make different predictions that are not testable. (3) Other interpretations constitute 'a different theory' and are testable, although sometimes this is not anticipated by the interpretation. (4) Some interpretations have generated many variations, by adjustment of parameters or hypotheses, and part of these variations have been tested and ruled out by experiment. (5) At times experiments reinforce an interpretation. (6) Some experiments lead to a refinement of the interpretation. (7) There are experiments that suggest the creation of an interpretation. (8) And there are cases in which experiments are suggested by an interpretation, while not affecting its rivals.
The monocrystalline Cr2AlC MAX phase has been studied and characterised by Transmission Electron Microscopy (TEM) after spherical nanoindentation tests. Observations have shown, for the first time, the existence of a helical dislocation in these materials. The characteristics and parameters of the cited dislocation have been deduced via the extinction criteria, and the formation mechanism has been discussed in relation to the literature. These findings suggest that the formation of such a defect is related to the synthesis method (high-temperature solution growth) rather than the mechanical test.
Impact toughness is a crucial mechanical property of hot work die steel that is significantly influenced by tempering temperature. Conventional Charpy impact testing provides only a single toughness value without quantifying the energy distribution between crack formation and extension, while the relationship between different notch types remains unclear. This study examines the dynamic fracture behaviour of H13 steel with unnotched, U-notched, and V-notched specimens tempered at 520-600 using oscillometric impact tests. Results demonstrate that unnotched specimens provide richer eigenvalues in oscillometric curves, better characterising the complete fracture process. Their substantially higher crack formation energy ratio reflects a balanced strength-toughness combination, effectively evaluating both crack initiation and arrest under elastic-plastic conditions. In contrast, notched specimens concentrate impact energy on crack extension due to prefabricated notches, primarily revealing crack sensitivity and plastic toughness while overlooking strength contributions. Notably, V-notched specimens show increasing linear-elastic fracture toughness with rising tempering temperature, governed by enhanced plasticity, while unnotched specimens exhibit decreasing elastic-plastic fracture toughness under the same conditions, dominated by strength reduction. These findings highlight the complementary roles of different notch configurations in material evaluation and provide valuable insights for optimising tempering processes in industrial applications.
The present study emphasises the critical phenomena and characterisation of DC magnetisation and AC susceptibility measurements in La0.7Bi0.3MnO3 perovskite manganite. The compound has been synthesised using a conventional solid-state reaction method. Rietveld analysis of powder X-ray diffraction (PXRD) patterns shows that the compound exhibits rhombohedral crystal structure indexed to the R$\bar{3}$3 & strns;c space group. The DC magnetisation versus temperature exhibits a high-temperature paramagnetic (PM) to low-temperature frustrated ferromagnetic (FM) transition. Using Bloch's law, the existence of critical inhomogeneous FM agglomerates around blocking temperature (TK) has been confirmed. Further, the critical fluctuations at low temperatures have been understood using the Kouvel-Fisher (KF) method, which indicates the existence of the critical phenomena. By using the critical scaling analysis and KF method, the obtained values of beta, gamma and delta are comparable with the 3D Heisenberg-type spin interactions. The Langevin fit to the DC magnetisation versus magnetic field confirms the short-range interactions with inhomogeneities in the randomly dispersed magnetic spins. Hence, indicating temperature-dependent distortions in the magnetisation ordering. This type of investigation on critical phenomena and the results of ${ m L}{ m a}_{0.7}{ m B}{ m i}_{0.3}{ m Mn}{ m O}_3{ m \; }$La0.7Bi0.3MnO3discussed in this paper finds importance in devising advanced sensors useful for automotive and chemical catalytic degradation industries.
A model is presented to calculate the mean time of diffusion-reaction controlled loading of and the unloading from bodies with the application-relevant geometry of a rectangular-shaped column with infinite height. This volume-averaged mean time, covering cases with initial homogeneous concentration of diffusing species, is relevant for a wide variety of processes, e.g. in bioscience for drug delivery and in materials science for hydrogen or battery loading. Despite the two-dimensional nature of the diffusion-reaction problem, a single-sum expression could be deduced for this characteristic mean time. The variation of the mean time with the shape of the rectangular column (side length ratio and cross section area) and the characteristic coefficients (diffusion coefficient and surface reaction rate) are discussed and compared with existing results as for example the cylindrical column or plates of a certain width. The various special cases of entirely diffusion- or reaction-limitation in both directions as well as in a single direction are outlined. For the entirely reaction-controlled case, the mean loading/unloading time is determined in a general fashion by the ratio of cross-section and perimeter. The approximation of the mean time either by the one-dimensional limits or by the entirely diffusion- and reaction-controlled limits is quantitatively considered, where the latter one turns out as particularly appropriate. Finally, the specific results for the rectangular-shaped column are put in context with the general theory for bodies of arbitrary shape, which is based on the concept of the so-called mean first reaction-time.
In this paper, authors present a physics-informed neural networks (PINN) approach for solving the optimal control problem (OCP) of the stochastic Schr & ouml;dinger equation (SSE), with an emphasis on applications in quantum optics. The SSE models quantum systems under uncertainty, a scenario often encountered in open quantum systems where environmental interactions introduce randomness into the system dynamics. These stochastic dynamics are particularly relevant in quantum optics, where precise control over quantum states is crucial for applications such as quantum computing, secure communication, and measurement protocols. Traditional numerical methods for solving such problems face limitations due to high computational costs and the complexity associated with stochastic partial differential equations. The proposed approach utilises PINN, a type of deep learning model that integrates physical laws directly into the learning process by incorporating loss functions based on governing equations, initial and boundary conditions. The fidelity-based objective function is constructed to achieve the desired quantum state so as to develop an OCP solving algorithm. The proposed work is distinguished between deterministic drift-based training and post-training stochastic validation. Extensive numerical experiments are demonstrated near-unity deterministic fidelity. Further, a systematic architecture study validated that a moderately deep network yielded optimal performance with reduced computational cost. Fidelity dissipation analysis confirmed that the method maintained accuracy even under strong damping. These findings established the PINN as an efficient and physically consistent framework for quantum optimal control in open systems.
EBSD orientation data are widely employed to evaluate the crystal curvature (orientation gradient) and, consequently, derive Nye's tensor indicative of geometrically necessary dislocations (GND). These defects attract a vivid interest because of their contributions to the strain-induced microstructure and the work hardening. The GND density is usually derived from either the measured Nye's tensor itself or its appropriate scalar measures scaled by the Burgers vector magnitude of lattice dislocations. Besides, the net Burgers vector of GND crossing a unit area of the specimen section can be employed to assess a lower bound for the GND density. Based on various presumptions, these approaches differ in their advantages and limitations, which should be kept in mind in specific applications. Along with estimates for distributions and average densities of GND, the paper particularly focuses on a method to identify by EBSD their constituent Burgers vectors. This research makes use of EBSD data on dissimilar states of copper with allowance for important issues that have not attracted due regard so far. They are dependences of results on the step size and a way to differentiate discrete orientation data.
