scholarly journals A review on the modeling and simulations of solid-state diffusional phase transformations in metals and alloys

2018 ◽  
Vol 5 ◽  
pp. 10 ◽  
Author(s):  
Xueyan Liu ◽  
Hongwei Li ◽  
Mei Zhan
Keyword(s):  
Solid State ◽  
Phase Transformations ◽  
Numerical Technique ◽  
Metals And Alloys ◽  
Analytical Models ◽  
Theoretical Research ◽  
Current Status ◽  
Advantages And Disadvantages ◽  
Simulation Techniques ◽  
Molecular Dynamics Methods

Solid-state diffusional phase transformations are vital approaches for controlling of the material microstructure and thus tailoring the properties of metals and alloys. To exploit this mean to a full extent, much effort is paid on the reliable and efficient modeling and simulation of the phase transformations. This work gives an overview of the developments in theoretical research of solid-state diffusional phase transformations and the current status of various numerical simulation techniques such as empirical and analytical models, phase field, cellular automaton methods, Monte Carlo models and molecular dynamics methods. In terms of underlying assumptions, physical relevance, implementation and computational efficiency for the simulation of phase transformations, the advantages and disadvantages of each numerical technique are discussed. Finally, trends or future directions of the quantitative simulation of solid-state diffusional phase transformation are provided.

Current Status of Solid-State X-Ray Systems

1985 ◽  
Vol 43 ◽  
pp. 158-161
Author(s):  
Martin Peckerar ◽  
Anastasios Tousimis
Keyword(s):  
Solid State ◽  
Electric Fields ◽  
Spectral Lines ◽  
Current Status ◽  
Mobile Charge ◽  
Electron Hole ◽  
X Ray ◽  
Sensing Systems ◽  
Transmission Electron ◽  
Electron Microscopes

Solid state x-ray sensing systems have been used for many years in conjunction with scanning and transmission electron microscopes. Such systems conveniently provide users with elemental area maps and quantitative chemical analyses of samples. Improvements on these tools are currently sought in the following areas: sensitivity at longer and shorter x-ray wavelengths and minimization of noise-broadening of spectral lines. In this paper, we review basic limitations and recent advances in each of these areas. Throughout the review, we emphasize the systems nature of the problem. That is. limitations exist not only in the sensor elements but also in the preamplifier/amplifier chain and in the interfaces between these components.Solid state x-ray sensors usually function by way of incident photons creating electron-hole pairs in semiconductor material. This radiation-produced mobile charge is swept into external circuitry by electric fields in the semiconductor bulk.

The use of high-resolution FESEM to study solid-state phase transformations and reactions

1994 ◽  
Vol 52 ◽  
pp. 1028-1029
Author(s):  
P. G. Kotula ◽  
D. D. Erickson ◽  
C. B. Carter
Keyword(s):  
Solid State ◽  
High Resolution ◽  
Phase Transformations ◽  
High Efficiency ◽  
Sol Gel ◽  
Quantitative Information ◽  
Solid State Reactions ◽  
Critical Dimensions ◽  
Backscattered Electrons ◽  
Backscattered Electron

High-resolution field-emission-gun scanning electron microscopy (FESEM) has recently emerged as an extremely powerful method for characterizing the micro- or nanostructure of materials. The development of high efficiency backscattered-electron detectors has increased the resolution attainable with backscattered-electrons to almost that attainable with secondary-electrons. This increased resolution allows backscattered-electron imaging to be utilized to study materials once possible only by TEM. In addition to providing quantitative information, such as critical dimensions, SEM is more statistically representative. That is, the amount of material that can be sampled with SEM for a given measurement is many orders of magnitude greater than that with TEM.In the present work, a Hitachi S-900 FESEM (operating at 5kV) equipped with a high-resolution backscattered electron detector, has been used to study the α-Fe2O3 enhanced or seeded solid-state phase transformations of sol-gel alumina and solid-state reactions in the NiO/α-Al2O3 system. In both cases, a thin-film cross-section approach has been developed to facilitate the investigation. Specifically, the FESEM allows transformed- or reaction-layer thicknesses along interfaces that are millimeters in length to be measured with a resolution of better than 10nm.

Research Situation Analysis of On-line Detection Technology for Power Transformer Winding Deformation

2020 ◽  
Vol 13 (6) ◽  
pp. 823-832
Author(s):  
Zhenhua Li ◽  
Weihui Jiang ◽  
Li Qiu ◽  
Zhenxing Li ◽  
Yanchun Xu
Keyword(s):  
Detection Method ◽  
Theoretical Research ◽  
Line Detection ◽  
Response Analysis ◽  
Advantages And Disadvantages ◽  
Detection Technology ◽  
The Future ◽  
Transformer Winding ◽  
On Line ◽  
Winding Deformation

Background: Winding deformation is one of the most common faults in power transformers, which seriously threatens the safe operation of transformers. In order to discover the hidden trouble of transformer in time, it is of great significance to actively carry out the research of transformer winding deformation detection technology. Methods: In this paper, several methods of winding deformation detection with on-line detection prospects are summarized. The principles and characteristics of each method are analyzed, and the advantages and disadvantages of each method as well as the future research directions are expounded. Finally, aiming at the existing problems, the development direction of detection method for winding deformation in the future is prospected. Results: The on-line frequency response analysis method is still immature, and the vibration detection method is still in the theoretical research stage. Conclusion: The ΔV − I1 locus method provides a new direction for on-line detection of transformer winding deformation faults, which has certain application prospects and practical engineering value.

scholarly journals Machine Learning Quantitation of Cardiovascular and Cerebrovascular Disease: A Systematic Review of Clinical Applications

Diagnostics ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 551
Author(s):  
Chris Boyd ◽  
Greg Brown ◽  
Timothy Kleinig ◽  
Joseph Dawson ◽  
Mark D. McDonnell ◽  
...  
Keyword(s):  
Machine Learning ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Model Comparison ◽  
Disease Risk ◽  
Imaging Modalities ◽  
Current Status ◽  
Advantages And Disadvantages ◽  
Body Regions ◽  
Artery Disease

Research into machine learning (ML) for clinical vascular analysis, such as those useful for stroke and coronary artery disease, varies greatly between imaging modalities and vascular regions. Limited accessibility to large diverse patient imaging datasets, as well as a lack of transparency in specific methods, are obstacles to further development. This paper reviews the current status of quantitative vascular ML, identifying advantages and disadvantages common to all imaging modalities. Literature from the past 8 years was systematically collected from MEDLINE® and Scopus database searches in January 2021. Papers satisfying all search criteria, including a minimum of 50 patients, were further analysed and extracted of relevant data, for a total of 47 publications. Current ML image segmentation, disease risk prediction, and pathology quantitation methods have shown sensitivities and specificities over 70%, compared to expert manual analysis or invasive quantitation. Despite this, inconsistencies in methodology and the reporting of results have prevented inter-model comparison, impeding the identification of approaches with the greatest potential. The clinical potential of this technology has been well demonstrated in Computed Tomography of coronary artery disease, but remains practically limited in other modalities and body regions, particularly due to a lack of routine invasive reference measurements and patient datasets.

MicroRNA annotation in plants: current status and challenges

2021 ◽  
Author(s):  
Yongxin Zhao ◽  
Zheng Kuang ◽  
Ying Wang ◽  
Lei Li ◽  
Xiaozeng Yang
Keyword(s):  
Small Rna ◽  
Signal To Noise Ratio ◽  
Current Status ◽  
Mirna Biogenesis ◽  
Plant Mirnas ◽  
Signal To Noise ◽  
Advantages And Disadvantages ◽  
Plant Mirna ◽  
History Of ◽  
Mirna Biogenesis Pathway

Abstract Last two decades, the studies on microRNAs (miRNAs) and the numbers of annotated miRNAs in plants and animals have surged. Herein, we reviewed the current progress and challenges of miRNA annotation in plants. Via the comparison of plant and animal miRNAs, we pinpointed out the difficulties on plant miRNA annotation and proposed potential solutions. In terms of recalling the history of methods and criteria in plant miRNA annotation, we detailed how the major progresses made and evolved. By collecting and categorizing bioinformatics tools for plant miRNA annotation, we surveyed their advantages and disadvantages, especially for ones with the principle of mimicking the miRNA biogenesis pathway by parsing deeply sequenced small RNA (sRNA) libraries. In addition, we summarized all available databases hosting plant miRNAs, and posted the potential optimization solutions such as how to increase the signal-to-noise ratio (SNR) in these databases. Finally, we discussed the challenges and perspectives of plant miRNA annotations, and indicated the possibilities offered by an all-in-one tool and platform according to the integration of artificial intelligence.

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