scholarly journals Characterization of diffusion processes: Normal and anomalous regimes

2016 ◽  
Vol 447 ◽  
pp. 392-401 ◽  
Author(s):  
Samuel B. Alves ◽  
Gilson F. de Oliveira ◽  
Luimar C. de Oliveira ◽  
Thierry Passerat de Silans ◽  
Martine Chevrollier ◽  
...  
Keyword(s):  
Diffusion Processes

scholarly journals A Brief Review of Generalized Entropies

Entropy ◽  
2018 ◽  
Vol 20 (11) ◽  
pp. 813 ◽  
Author(s):  
José Amigó ◽  
Sámuel Balogh ◽  
Sergio Hernández
Keyword(s):  
Diffusion Processes ◽  
Complex Dynamics ◽  
Probability Distributions ◽  
Point Of View ◽  
Scaling Exponent ◽  
Scaling Exponents ◽  
Physical Systems ◽  
New Phenomena ◽  
Generalized Entropies

Entropy appears in many contexts (thermodynamics, statistical mechanics, information theory, measure-preserving dynamical systems, topological dynamics, etc.) as a measure of different properties (energy that cannot produce work, disorder, uncertainty, randomness, complexity, etc.). In this review, we focus on the so-called generalized entropies, which from a mathematical point of view are nonnegative functions defined on probability distributions that satisfy the first three Shannon–Khinchin axioms: continuity, maximality and expansibility. While these three axioms are expected to be satisfied by all macroscopic physical systems, the fourth axiom (separability or strong additivity) is in general violated by non-ergodic systems with long range forces, this having been the main reason for exploring weaker axiomatic settings. Currently, non-additive generalized entropies are being used also to study new phenomena in complex dynamics (multifractality), quantum systems (entanglement), soft sciences, and more. Besides going through the axiomatic framework, we review the characterization of generalized entropies via two scaling exponents introduced by Hanel and Thurner. In turn, the first of these exponents is related to the diffusion scaling exponent of diffusion processes, as we also discuss. Applications are addressed as the description of the main generalized entropies advances.

Ultra Shallow Depth Profiling with SIMS

2008 ◽  
Vol 573-574 ◽  
pp. 197-205 ◽  
Author(s):  
H. Ulrich Ehrke
Keyword(s):  
Mass Spectrometry ◽  
Thin Films ◽  
Secondary Ion Mass Spectrometry ◽  
Diffusion Processes ◽  
Depth Profiling ◽  
Semiconductor Technology ◽  
Technology Standard ◽  
Secondary Ion ◽  
Analytical Requirements

Secondary Ion Mass Spectrometry (SIMS) is frequently used in the characterization of thin films, coatings, diffusion processes, materials composition and in the analysis of implants. The SIMS technique has been continuously developed for more than 30 years. One of the main drivers was semiconductor technology. Standard implants in Si like B, As and P, implanted with a few keV to MeV energy are routinely measured with high precision. But nowadays with implant energies of 500 eV and below, when ultra shallow structures are examined, the desired information is in the first few nm to some tens of nm. This has a great impact on the analytical requirements and quantification procedures. Some of these aspects will be examined in this contribution.

Structural Characterization of the Chromium-Iron Alloy Formed by Thermal Diffusion Processes

2013 ◽  
Vol 651 ◽  
pp. 284-288 ◽  
Author(s):  
Roberto Baca Arroyo
Keyword(s):  
Thermal Diffusion ◽  
Diffusion Processes ◽  
Iron Alloy ◽  
Magnetic Coupling ◽  
Magnetic Ordering ◽  
X Ray Diffraction ◽  
Lattice Constants ◽  
Air Atmosphere ◽  
Direct Band

We have investigated the chromium-iron alloy and compared it to the oxides α-Fe2O3 (Eg = 4.8eV) and α-Cr2O3 (Eg = 2.1eV). It is known that α-Cr2O3 and α-Fe2O3 both adopt a corundum-type structure, but display differences in the lattice constants, direct band gap, and magnetic ordering of the cations. The chromium-iron alloy was synthesized by thermal diffusion processes of both chromium and iron thin-films in air atmosphere conditions. We have studied the elastic distortions related to nature of the relative strains as well as magnetic coupling between Fe and Cr from the X-ray diffraction studies.

scholarly journals Asteroseismic inference of subgiant evolutionary parameters with deep learning

2020 ◽  
Vol 499 (2) ◽  
pp. 2445-2461
Author(s):  
Marc Hon ◽  
Earl P Bellinger ◽  
Saskia Hekker ◽  
Dennis Stello ◽  
James S Kuszlewicz
Keyword(s):  
Deep Learning ◽  
Diffusion Processes ◽  
Physical Parameters ◽  
Fundamental Parameters ◽  
Fundamental Properties ◽  
Wide Range ◽  
Modelling Techniques ◽  
Subgiant Stars ◽  
Good Agreement

ABSTRACT With the observations of an unprecedented number of oscillating subgiant stars expected from NASA’s TESS mission, the asteroseismic characterization of subgiant stars will be a vital task for stellar population studies and for testing our theories of stellar evolution. To determine the fundamental properties of a large sample of subgiant stars efficiently, we developed a deep learning method that estimates distributions of fundamental parameters like age and mass over a wide range of input physics by learning from a grid of stellar models varied in eight physical parameters. We applied our method to four Kepler subgiant stars and compare our results with previously determined estimates. Our results show good agreement with previous estimates for three of them (KIC 11026764, KIC 10920273, KIC 11395018). With the ability to explore a vast range of stellar parameters, we determine that the remaining star, KIC 10005473, is likely to have an age 1 Gyr younger than its previously determined estimate. Our method also estimates the efficiency of overshooting, undershooting, and microscopic diffusion processes, from which we determined that the parameters governing such processes are generally poorly constrained in subgiant models. We further demonstrate our method’s utility for ensemble asteroseismology by characterizing a sample of 30 Kepler subgiant stars, where we find a majority of our age, mass, and radius estimates agree within uncertainties from more computationally expensive grid-based modelling techniques.

scholarly journals Characterization of Influences of Steel-Aluminum Dissimilar Joints with Intermediate Zinc Layer

Metals ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 442 ◽  
Author(s):  
Tobias Bick ◽  
Verena Heuler ◽  
Kai Treutler ◽  
Volker Wesling
Keyword(s):  
Diffusion Processes ◽  
Intermetallic Phases ◽  
Dissimilar Joints ◽  
Solution Approach ◽  
Small Areas ◽  
Joint Properties ◽  
Zinc Interlayer ◽  
Edx Analyses ◽  
Strength And Ductility

Brittle intermetallic phases are formed when steel and aluminum are joined. Therefore, it is difficult to use this combination of materials when applying the multimaterial design in the construction of load-adapted and weight-adapted structures. In order to largely avoid the formation of these brittle phases, joining processes based on diffusion processes, such as composite forging, depict a good solution approach. The materials are joined in a solid state. Furthermore, zinc additives are used to create the joint. Zinc forms a compound with both steel and aluminum without the formation of brittle phases. By combining the composite forging process with zinc additives, strength values of 26 N/mm2 can be reached. This is higher, in comparison to former investigations of resistance spot welded and clinched joints. The joint properties depend on the composition of the zinc interlayer. Small amounts of magnesium in the zinc interlayer affected the strength and ductility values. While the strength decreased by about 30% in contrast to the zinc layer without magnesium, the ductility increased by 60%. This effect was probably due to the metallurgical impact of the alloying elements on phase formation, as could be shown by energy dispersive X-ray spectroscopy (EDX) analyses of the joint zones. Thereby, it was shown that the brittle intermetallic phases are located only in small areas.

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