Particularities of metallographic preparation for the analysis of thin layers and coatings. Foundry production and metallurgy

Litiyo i Metallurgiya (FOUNDRY PRODUCTION AND METALLURGY) ◽

10.21122/1683-6065-2020-2-59-62 ◽

2020 ◽

pp. 59-62

Author(s):

A. G. Anisovich

Keyword(s):

Image Processing ◽

Sample Preparation ◽

Titanium Nitride ◽

Layer Thickness ◽

Thin Layers ◽

Optimal Method ◽

Metallographic Preparation ◽

Processing Program ◽

Nitride Layers

The article deals with the issues of determining the thickness of layers and coatings for various purposes in metallographic research. The role of the material for filling metallographic sections in determining the layer thickness is demonstrated. It is shown that when filling the sample with plastic masses, the error in determining the layer thickness can be 0.2...0.4 microns, which is significant for thin layers. Sample preparation options for determining the thickness of titanium nitride layers with a thickness of 1 microns or less are considered. It is shown that with the optimal method of sample preparation, it is possible to visualize a layer less than 1 microns thick, and also determine its thickness in the image processing program.

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Structure, Adhesion Strength and Corrosion Resistance of Vacuum Arc Multi-Period NbN/Cu Coatings

Journal of Metallic Material Research ◽

10.30564/jmmr.v3i1.1364 ◽

2020 ◽

Vol 3 (1) ◽

Author(s):

Hanna Oleksandrivna Postelnyk

Keyword(s):

Corrosion Resistance ◽

Crystal Lattice ◽

Layer Thickness ◽

Adhesive Strength ◽

Nitrogen Atmosphere ◽

Niobium Nitride ◽

Chloride Ions ◽

Thin Layers ◽

Vacuum Arc ◽

Nitride Layers

The influence of deposition modes on the phase-structural state, corrosion resistance, and adhesive strength of vacuum-arc multi-period NbN/Cu coatings is studied. It was found that in thin layers (about 8 nm, in a constant rotation mode), regardless of the change in the pressure of the nitrogen atmosphere, a metastable δ - NbN phase forms (cubic crystal lattice of the NaCl type). At a layer thickness of ~ 40 nm or more, a phase composition changes from the metastable δ - NbN to the equilibrium ε - NbN phase with a hexagonal crystal lattice. In the presence of the ε - NbN phase in the niobium nitride layers, the highest adhesive strength is achieved with a value of LС5 = 96.5 N. Corrosion resistance tests have shown that for all the studied samples the corrosion process has mainly an anodic reaction. The highest corrosion resistance was shown by coatings obtained at a pressure of 7·10-4 Torr, with the smallest bias potential of -50 V and the smallest layer thickness; with a thickness of such a coating of about 10 microns, its service life in the environment of the formation of chloride ions is about a year.

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The Constantly Evolving Role of Medical Image Processing in Oncology: From Traditional Medical Image Processing to Imaging Biomarkers and Radiomics

Journal of Imaging ◽

10.3390/jimaging7080124 ◽

2021 ◽

Vol 7 (8) ◽

pp. 124

Author(s):

Kostas Marias

Keyword(s):

Image Processing ◽

Image Analysis ◽

Medical Image ◽

Biomarker Discovery ◽

Medical Image Processing ◽

Machine Learning Techniques ◽

Imaging Biomarker ◽

Imaging Biomarkers ◽

Precision Oncology

The role of medical image computing in oncology is growing stronger, not least due to the unprecedented advancement of computational AI techniques, providing a technological bridge between radiology and oncology, which could significantly accelerate the advancement of precision medicine throughout the cancer care continuum. Medical image processing has been an active field of research for more than three decades, focusing initially on traditional image analysis tasks such as registration segmentation, fusion, and contrast optimization. However, with the advancement of model-based medical image processing, the field of imaging biomarker discovery has focused on transforming functional imaging data into meaningful biomarkers that are able to provide insight into a tumor’s pathophysiology. More recently, the advancement of high-performance computing, in conjunction with the availability of large medical imaging datasets, has enabled the deployment of sophisticated machine learning techniques in the context of radiomics and deep learning modeling. This paper reviews and discusses the evolving role of image analysis and processing through the lens of the abovementioned developments, which hold promise for accelerating precision oncology, in the sense of improved diagnosis, prognosis, and treatment planning of cancer.

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Image Processing Using Local Regularization: The Role of Optimization

IEICE ESS FUNDAMENTALS REVIEW ◽

10.1587/essfr.11.1_40 ◽

2017 ◽

Vol 11 (1) ◽

pp. 40-53

Author(s):

Keiichiro SHIRAI ◽

Tatsuya BABA ◽

Shunsuke ONO ◽

Masahiro OKUDA

Keyword(s):

Image Processing ◽

Local Regularization

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The role of graphite addition on spark plasma sintered titanium nitride

Journal of Materials Research and Technology ◽

10.1016/j.jmrt.2020.03.040 ◽

2020 ◽

Vol 9 (3) ◽

pp. 6268-6277 ◽

Cited By ~ 2

Author(s):

O.J. Akinribide ◽

B.A. Obadele ◽

O.O. Ayeleru ◽

S.O. Akinwamide ◽

K. Nomoto ◽

...

Keyword(s):

Titanium Nitride ◽

Sintered Titanium ◽

Spark Plasma

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Investigation of titanium—nitride layers for solar-cell contacts

IEEE Transactions on Electron Devices ◽

10.1109/t-ed.1980.19949 ◽

1980 ◽

Vol 27 (4) ◽

pp. 873-876 ◽

Cited By ~ 67

Author(s):

H. von Seefeld ◽

N.W. Cheung ◽

M. Maenpaa ◽

M.-A. Nicolet

Keyword(s):

Solar Cell ◽

Titanium Nitride ◽

Cell Contacts ◽

Nitride Layers

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Spreadability Testing of Powder for Additive Manufacturing

BHM Berg- und Hüttenmännische Monatshefte ◽

10.1007/s00501-020-01069-9 ◽

2021 ◽

Vol 166 (1) ◽

pp. 9-13

Author(s):

Christopher Neil Hulme-Smith ◽

Vignesh Hari ◽

Pelle Mellin

Keyword(s):

Additive Manufacturing ◽

Layer Thickness ◽

Measurement Procedure ◽

Quantitative Information ◽

Thin Layers ◽

Spreading Speed ◽

Powder Bed ◽

Critical Step ◽

Robust Image

AbstractThe spreading of powders into thin layers is a critical step in powder bed additive manufacturing, but there is no accepted technique to test it. There is not even a metric that can be used to describe spreading behaviour. A robust, image-based measurement procedure has been developed and can be implemented at modest cost and with minimal training. The analysis is automated to derive quantitative information about the characteristics of the spread layer. The technique has been demonstrated for three powders to quantify their spreading behaviour as a function of layer thickness and spreading speed.

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Preferred Orientations for Sol-Gel Derived Plzt Thin Layers

MRS Proceedings ◽

10.1557/proc-310-269 ◽

1993 ◽

Vol 310 ◽

Cited By ~ 107

Author(s):

Toshihiko Tani ◽

Zhengkui Xu ◽

David A. Payne

Keyword(s):

Heat Treatment ◽

Surface Energy ◽

Sol Gel ◽

Nucleation And Growth ◽

Thin Layers ◽

Energy Conditions ◽

Chemical Characteristics ◽

Interfacial Chemistry ◽

Si Substrates

AbstractPLZT thin layers were deposited onto various substrates by sol-gel methods, and crystallized under different conditions and substrate treatments. Relationships are given for the chemical characteristics of the substrate's surface and the preferred orientations which develop on heat treatment. A preferred (111) orientation always developed for perovskite crystallized on Pt layers which contained Ti on the surface. This was attributed to the formation of Pt3Ti and the role of heteroepitaxial nucleation and growth sites. In addition, a preferred (100) orientation was also obtained on unannealed Pt/Ti/SiO2/Si substrates which were free of Ti on the surface. This was attributed to self-textured growth with flat faces striving for minimum surface energy conditions. The results are discussed in terms of the importance of interfacial chemistry on the control of texture for crystallization of PLZT thin layers on coated substrates.

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