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We investigated the single-electron spectrum of an InAs/GaAs quantum dot (QD) using an effective potential model developed in previous studies. Our objective was to explore the limits of applicability of this model. We conducted numerical simulations, introducing a piezoelectric potential as a perturbation to the effective potential. The profile of this additional potential was derived from theoretical numerical studies presented in the literature. We analyzed the impact of variations in this profile within the framework of the perturbation theory. Our findings indicate that within a variation range of 25%, the effective potential model remains applicable. 

Additive friction stir deposition (AFS-D) is considered a productive method of additive manufacturing (AM) due to its ability to produce dense mechanical parts at a faster deposition rate compared to other AM methods. Al6061 alloy finds extensive application in aerospace and nuclear engineering; nevertheless, exposure to radiation or high-energy particles over time tends to deteriorate their mechanical performance. However, the effect of radiation on the components manufactured using the AFS-D method is still unexamined. In this work, samples from the as-fabricated Al6061 alloy, by AFS-D, and the Al6061 feedstock rod were irradiated with He+ ions to 10 dpa at ambient temperature. The microstructural and mechanical changes induced by irradiation of He+ were examined using a scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDS), transmission electron microscopy (TEM), and nanoindentation. This study demonstrates that, at 10 dpa of irradiation damage, the feedstock Al6061 produced a bigger size of He bubbles than the AFS-D Al6061. Nanoindentation analysis revealed that both the feedstock Al6061 and AFS-D Al6061 samples have experienced radiation-induced hardening. These studies provide a valuable understanding of the microstructural and mechanical performance of AFS-D materials in radiation environments, offering essential data for the selection of materials and processing methods for potential application in aerospace and nuclear engineering. 

In this paper, we study the localization of an electron in a binary quantum system formed by a pair of quantum dots (QDs). The traditional theoretical consideration of such systems is limited to the symmetrical case when QDs in such double quantum dot (DQD) are assumed identical in all respects. In this paper, we model the effects of breaking QD similarities in a DQD by studying two-dimensional (2D) DQDs as a double quantum well (DQW). This is done by solving the Schrödinger equation, with parameters chosen to describe an InAs/GaAs heterostructure. We calculate the energy spectrum of the electron confinement and the spectral distribution of localized/delocalized spatial states. Both symmetric and asymmetric QW shapes are considered and their effects are compared. The effects of symmetry breaking are explained within the framework of the two-level system theory. We delineate the QW weak and strong coupling cases in DQW. In particular, we show that the coherence in ideal DQW is unstable in the case of a weak QW coupling. Within the framework of the proposed approach, a charge qubit realized on a DQD is discussed and, as an example, a qubit based on an almost ideal DQD is proposed. 

In this work, a dataset including structural and mechanical properties of refractory multicomponent alloys was developed by fusing computations of phase diagram (CALPHAD) and density functional theory (DFT). The refractory multicomponent alloys, also named refractory complex concentrated alloys (CCAs) which contain 2–5 types of refractory elements were constructed based on Special Quasi-random Structure (SQS). The phase of alloys was predicted using CALPHAD and the mechanical property of alloys with stable and single body-centered cubic (BCC) at high temperature (over 1,500°C) was investigated using DFT-based simulation. As a result, a dataset with 393 refractory alloys and 12 features, including volume, melting temperature, density, energy, elastic constants, mechanical moduli, and hardness, were produced. To test the capability of the dataset on supporting machine learning (ML) study to investigate the property of CCAs, CALPHAD, and DFT calculations were compared with principal components analysis (PCA) technique and rule of mixture (ROM), respectively. It is demonstrated that the CALPHAD and DFT results are more in line with experimental observations for the alloy phase, structural and mechanical properties. Furthermore, the data were utilized to train a verity of ML models to predict the performance of certain CCAs with advanced mechanical properties, highlighting the usefulness of the dataset for ML technique on CCA property prediction. 

The world energy crisis necessitated the cause of the research interest into new, renewable and alternative energy sources. From this point of view, there is research on phenomena and different synthetic methods and on structure and electronic property optimization expressed by important material and device advancement. Efficiency and electricity generation (batteries, fuel cells, hydrogen energy) are nowadays actual questions. Because of that research, innovations and applications require extended knowledge by fractal nature characterization. The electrochemical energy sources solutions, especially electrolytes, are in fractal nature science focus. Based on the research novelties, especially electronic materials, we presented an investigation on fractal structure influence in electrochemistry. We explore the activation energy and fundamental thermodynamic functions and values, also the electrode surface changed by complex fractal correction through fractal dimension of grains and pores, and Brownian motion of involved particles, as well. At the end, the electrochemical Arrhenius and Butler–Volmer equation fractalization is applied. All of these open new perspectives for electrochemical energy processes, within electrolyte bulk and related electrodes and more precise energy generation. This is important for semiconductor processing in solar cells and devices. So, we included the knowledge of fractal sciences advancement in this field for current–voltage equation.