Estudio de un magnetrón utilizando el método de elementos finitos

Magnetron sputtering system is a technique that consists in extracting atoms from a target material by collisions of energetic ions of an inert gas. It is widely used in semiconductor industries and materials processing research for developing thin films by deposition. During this process a low temperature capacitively coupled plasma is generated near the cathode and several variations of the properties of this plasma can affect the thin film deposition process and quality. An approach to study these types of systems is by computational modeling. The use of robust computational codes that can handle complicated geometries and can solve complex systems of differential equations. In this present project we aim to model numerically a system of magnetrons developed at the Materials Science and Renewable Energies (MatER) laboratory. Using the geometry measurements and the material properties of each component taken in the laboratory, a CAD geometry was developed. Furthermore, the electric and magnetic fields are solved for the geometry configuration and, by implementing a Monte Carlo simulation, the electron trajectories and velocity distributions in the system are calculated. Finally, we use a multi-fluid model to solve a simplified system of a 1 dimensional capacitively coupled plasma and recover the system properties. The method to solve the respective system of equations is the finite element method implemented in the software COMSOL Multiphysics.Trabajo de investigació

First-principles study of point defects at semicoherent interface

Modeling semicoherent metal-metal interfaces has so far been performed using atomistic simulations based on semiempirical interatomic potentials. We demonstrate through more precise ab-initio calculations that key conclusions drawn from previous studies do not conform with the new results which show that single point defects do not delocalize near the interfacial plane, but remain compact. We give a simple qualitative explanation for the difference in predicted results that can be traced back to shortcomings in potential fitting

A scalable parallel Monte Carlo algorithm for atomistic simulations of precipitation in alloys

We present an extension of the semi-grandcanonical (SGC) ensemble that we refer to as the variance-constrained semi-grandcanonical (VC-SGC) ensemble. It allows for transmutation Monte Carlo simulations of multicomponent systems in multiphase regions of the phase diagram and lends itself to scalable simulations on massively parallel platforms. By combining transmutation moves with molecular dynamics steps structural relaxations and thermal vibrations in realistic alloys can be taken into account. In this way, we construct a robust and efficient simulation technique that is ideally suited for large-scale simulations of precipitation in multicomponent systems in the presence of structural disorder. To illustrate the algorithm introduced in this work, we study the precipitation of Cu in nanocrystalline Fe.Comment: 12 pages; 10 figure

New simulations to qualify eutectic lithium-lead as breeder material

Pb17Li is today a reference breeder material in diverse fusion R&D programs worldwide. One of the main issues is the problem of liquid metals breeder blanket behavior. The knowledge of eutectic properties like optimal composition, physical and thermodynamic behavior or diffusion coefficients of Tritium are extremely necessary for current designs. In particular, the knowledge of the function linking the tritium concentration dissolved in liquid materials with the tritium partial pressure at a liquid/gas interface in equilibrium, CT =f(PT ), is of basic importance because it directly impacts all functional properties of a blanket determining: tritium inventory, tritium permeation rate and tritium extraction efficiency. Nowadays, understanding the structure and behavior of this compound is a real goal in fusion engineering and materials science. Atomistic simulations of liquids can provide much information; not only supplementing experimental data, but providing new tests of theories and ideas, making specific predictions that require experimental tests, and ultimately helping to a deeper understandin

Chemotherapy-induced alopecia management: Clinical experience and practical advice

Background: Chemotherapy-induced alopecia (CIA) is probably one of the most shocking aspects for oncological patients and underestimated by physicians. Among hair loss risk factors, there are treatment-related aspects such as drug dose, admin- istration regimen, and exposure to X-rays, but also patient-related characteristics. To the best of our knowledge, no guidelines are available about CIA management. Aims and methods: With this study, based on literature background and our clinical experience, we would like to propose a list of actions in order to estimate the risk of hair loss before starting chemotherapy and to manage this condition before, dur- ing, and after drug administration and to create a sort of practical guide for derma- tologists and oncologists. Results and conclusion: There is an urgent need for prospective studies to clarify the mechanistic basis of alopecia associated with these drugs and consequently to design evidence-based management strategies

Multi-therapies in androgenetic alopecia: review and clinical experiences.

Androgenetic alopecia (AGA) is a genetically determined progressive hair-loss condition which represents the most common cause of hair loss in men. The use of the medical term androgenetic alopecia reflects current knowledge about the important role of androgens and genetic factors in its etiology. In addition to androgen-dependent changes in the hair cycle, sustained microscopic follicular inflammation contributes to its onset. Furthermore, Prostaglandins have been demonstrated to have the ability in modulating hair follicle cycle; in particular, PGD2 inhibits hair growth while PGE2/F2a promote growth. Due to the progressive nature of AGA, the treatment should be started early and continued indefinitely, since the benefit will not be maintained upon ceasing therapy. To date, only two therapeutic agents have been approved by the Food and Drug Administration and European Medicines Agency for the treatment of AGA: topical minoxidil and oral finasteride. Considering the many pathogenetic mechanisms involved in AGA, various treatment options are available: topical and systemic drugs may be used and the choice depends on various factors including grading of AGA, patients’ pathological conditions, practicability, costs and risks. So, the treatment for AGA should be based on personalized therapy and targeted at the different pathophysiological aspects of AG

Are there stable long-range ordered Fe(1-x)Cr(x) compounds?

The heat of formation of Fe-Cr alloys undergoes an anomalous change of sign at small Cr concentrations. This observation raises the question whether there are intermetallic phases present in this composition range. Here we report the discovery of several long-range ordered structures that represent ground state phases at zero Kelvin. In particular we have identified a structure at 3.7% Cr with an embedding energy which is 49 meV/Cr atom below the solid solution. This implies there is an effective long-range attractive interaction between Cr atoms. We propose that the structures found in this study complete the low temperature-low Cr region of the phase diagram.Comment: 3 pages, 2 figure

a markov chain based model for wind power prediction in congested electrical grids

The large penetration of wind generators in existing electrical grids induces critical issues that are pushing the system operators to improve several critical operation functions, such as the security analysis and the spinning reserve assessment, with the purpose of mitigating the effects induced by the injected power profiles, which are ruled by the intermittent and not-programmable wind dynamics. Although numerous forecasting tools have been proposed in the literature to predict the generated power profiles in function of the estimated wind speed, further and more complex phenomena need to be investigated in order to take into account the effects of the forecasting uncertainty on power system operation. In order to deal with this issue, this paper proposes a probabilistic model based on Markov chains, which predicts the wind power profiles injected into the grid, considering the real generator model and the effects of the power curtailments imposed by the grid operator. Experimental results obtained on a real case study are presented and discussed in order to prove the effectiveness of the proposed method

Androgenetic alopecia: a review

Purpose Androgenetic alopecia, commonly known as male pattern baldness, is the most common type of progressive hair loss disorder in men. The aim of this paper is to review recent advances in understanding the pathophysiology and molecular mechanism of androgenetic alopecia. Methods Using the PubMed database, we conducted a systematic review of the literature, selecting studies pub- lished from 1916 to 2016. Results The occurrence and development of androgenetic alopecia depends on the interaction of endocrine factors and genetic predisposition. Androgenetic alopecia is character- ized by progressive hair follicular miniaturization, caused by the actions of androgens on the epithelial cells of genetically susceptible hair follicles in androgen-dependent areas. Although the exact pathogenesis of androgenetic alopecia remains to be clari fi ed, research has shown that it is a polygenetic condition. Numerous studies have unequi- vocally identi fi ed two major genetic risk loci for androge- netic alopecia, on the X-chromosome AR ⁄ EDA2R locus and the chromosome 20p11 locus. Conclusions Candidate gene and genome-wide association studies have reported that single-nucleotide polymorphisms at different genomic loci are associated with androgenetic alopecia development. A number of genes determine the predisposition for androgenetic alopecia in a polygenic fashion. However, further studies are needed before the specific genetic factors of this polygenic condition can be fully explaine

Data-driven Models to Anticipate Critical Voltage Events in Power Systems

This paper explores the effectiveness of data-driven models to predict voltage excursion events in power systems using simple categorical labels. By treating the prediction as a categorical classification task, the workflow is characterized by a low computational and data burden. A proof-of-concept case study on a real portion of the Italian 150 kV sub-transmission network, which hosts a significant amount of wind power generation, demonstrates the general validity of the proposal and offers insight into the strengths and weaknesses of several widely utilized prediction models for this application.Comment: In proceedings of the 11th Bulk Power Systems Dynamics and Control Symposium (IREP 2022), July 25-30, 2022, Banff, Canad