scholarly journals PCA-Based Analysis Applied to Germanium-On-Nothing: Revealing Buried Sub-Surface Structures and Analyzing Defects From Nanoscale Surface Topography

2021 ◽  
Author(s):  
Jaewoo Jeong ◽  
Taeyeong Kim ◽  
Bong Jae Lee ◽  
Jungchul Lee
Keyword(s):  
Surface Topography ◽  
Surface Analysis ◽  
Self Assembly ◽  
Surface Defects ◽  
Principal Component ◽  
Empty Space ◽  
Surface Structures ◽  
Buried Structures ◽  
Characterization Methods ◽  
Non Destructive

Abstract Empty Space in Germanium (ESG) or Germanium-on-Nothing (GON) are unique self-assembled germanium structures with multiscale cavities of various morphologies. Due to their simple fabrication process and high-quality crystallinity after self-assembly, they can be applied in various fields including micro-/nanoelectronics, optoelectronics, and precision sensors, to name a few. In contrast to their simple fabrication, inspection is intrinsically difficult due to buried structures. Today, ultrasonic atomic force microscopy and interferometry are some prevalent non-destructive 3-D imaging methods that are used to inspect the underlying ESG structures. However, these non-destructive characterization methods suffer from low throughput due to slow measurement speed and limited measurable thickness. To overcome these limitations, this work proposes a new methodology to construct a principal-component-analysis based database that correlates surface images with empirically determined sub-surface structures by interpolating the surface topography from the database and determining the buried sub-surface structure. Since the acquisition rate of a single nanoscale surface micrograph is up to a few orders faster than a thorough 3D sub-surface analysis, the proposed methodology would provide an exploitable and decisive advantage over the currently prevalent methods. Also, an empirical destructive test essentially resolves the measurable thickness limitation. We also demonstrate the practicality of the proposed methodology by applying it to GON devices to selectively detect and quantitatively analyze surface defects. Compared to state-of-the-art deep learning-based defect detection schemes, our method is much effortlessly finetunable for specific applications. In terms of sub-surface analysis, this work proposes a fast, robust, and high-resolution methodology which could potentially replace the conventional exhaustive sub-surface inspection schemes.

Улучшение качества ИК-термографического контроля подповерхностных дефектов методом выделения границ

2021 ◽  
Vol 7 ◽  
pp. 57-66
Author(s):  
П. Багавач ◽  
Л. Крстулович-Опара ◽  
Ж. Домазет
Keyword(s):  
Edge Detection ◽  
Surface Defects ◽  
Signal Reconstruction ◽  
Principal Component ◽  
Detection Algorithm ◽  
Fast Fourier Transformation ◽  
Detection Techniques ◽  
Thermal Signal ◽  
Novel Method ◽  
Non Destructive

This paper presents a novel method for separating sub-surface defects in cured pre-impregnated carbon fiber reinforced polimer specimens on thermal images based on edge detection. Every specimen was recorded by means of infrared thermography in reflective configuration and raw data was processed by several algorithms: Thermal Signal Reconstruction, Fast Fourier Transformation and Principal Component Analysis. Images were processed to determine damaged and non-damaged areas. Algorithm for determining area of discontinuity is based on edge detection techniques. Edge detection enables both simulated damages and boundaries between specimen and the background in the thermal image to be detected. Proposed algorithm is emphasizing edges within Sobel filter. Edges are defined as transition zone between damaged and non-damaged material. In this article edge detection algorithm is used as decision assistance for non-destructive evaluation.

scholarly journals Biodegradable and Compostable Shopping Bags under Investigation by FTIR Spectroscopy

2021 ◽  
Vol 11 (2) ◽  
pp. 621
Author(s):  
Silvana Alfei ◽  
Anna Maria Schito ◽  
Guendalina Zuccari
Keyword(s):  
Principal Component Analysis ◽  
Ftir Spectroscopy ◽  
Principal Component ◽  
Poly Lactic Acid ◽  
Chemometric Methods ◽  
Industrial Sectors ◽  
Fresh Food ◽  
Extruded Films ◽  
Productive Process ◽  
Non Destructive

In the recent years, plastic-based shopping bags have become irregular and progressively replaced by compostable ones. To be marketed, these “new plastics” must possess suitable requirements verified by specific bodies, which grant the conformity mark, and the approved physicochemical properties are periodically verified. The fast, inexpensive, non-destructive, easy to use, and reproducible Fourier-Transform infrared (FTIR) spectroscopy is a technique routinely applied to perform analysis in various industrial sectors. To get reliable information from spectral data, chemometric methods, such as Principal Component Analysis (PCA), are commonly suggested. In this context, PCA was herein performed on 4, 5, and 21 × 3251 matrices, collecting the FTIR data from regular and irregular shopping bags, including three freshly extruded films from the Italian industry MecPlast, to predict their compliance with legislation. The results allowed us to unequivocally achieve such information and to classify the bags as suitable for containing fresh food in bulk or only for transport. A self-validated linear model was developed capable to estimate, by acquiring a single FTIR spectrum if, after the productive process, the content of renewable poly-lactic-acid (PLA) in a new produced film respect the expectations. Surprisingly, our findings established that among the grocery bags available on the market, irregular plastic-based shopping bags continue to survive.

scholarly journals Spectroscopy as a useful tool for the identification of changes with time in post-mortem vitreous humor for forensic toxicology purposes

2021 ◽  
Author(s):  
Anna Wójtowicz ◽  
Agata Mitura ◽  
Renata Wietecha-Posłuszny ◽  
Rafał Kurczab ◽  
Marcin Zawadzki
Keyword(s):  
Ir Spectra ◽  
Forensic Toxicology ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Vitreous Humor ◽  
Attenuated Total Reflection ◽  
Glass Slides ◽  
Added Benefit ◽  
Ft Ir ◽  
Non Destructive

AbstractVitreous humor (VH) is an alternative biological matrix with a great advantage of longer availability for analysis due to the lack of many enzymes. The use of VH in forensic toxicology may have an added benefit, however, this application requires rapid, simple, non-destructive, and relatively portable analytical analysis methods. These requirements may be met by Fourier transform infrared spectroscopy technique (FT-IR) equipped with attenuated total reflection accessory (ATR). FT-IR spectra of vitreous humor samples, deposited on glass slides, were collected and subsequent chemometric data analysis by means of Hierarchical Cluster Analysis and Principal Component Analysis was conducted. Differences between animal and human VH samples and human VH samples stored for diverse periods of time were detected. A kinetic study of changes in the VH composition up to 2 weeks showed the distinction of FT-IR spectra collected on the 1st and 14th day of storage. In addition, data obtained for the most recent human vitreous humor samples—collected 3 and 2 years before the study, presented successful discrimination of all time points studied. The method introduced was unable to detect mephedrone addition to VH in the concentration of 10 µg/cm3. Graphic abstract

scholarly journals An Automated Pipeline for Dynamic Detection of Sub-Surface Metal Loss Defects across Cold Thermography Images

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4811
Author(s):  
Siavash Doshvarpassand ◽  
Xiangyu Wang
Keyword(s):  
Test Piece ◽  
Surface Defects ◽  
Principal Component ◽  
Specific Area ◽  
Gaussian Mixture ◽  
Metal Loss ◽  
Test Surface ◽  
Thermal Excitation ◽  
Cold Stimulation ◽  
Surface Metal

Utilising cooling stimulation as a thermal excitation means has demonstrated profound capabilities of detecting sub-surface metal loss using thermography. Previously, a prototype mechanism was introduced which accommodates a thermal camera and cooling source and operates in a reciprocating motion scanning the test piece while cold stimulation is in operation. Immediately after that, the camera registers the thermal evolution. However, thermal reflections, non-uniform stimulation and lateral heat diffusions will remain as undesirable phenomena preventing the effective observation of sub-surface defects. This becomes more challenging when there is no prior knowledge of the non-defective area in order to effectively distinguish between defective and non-defective areas. In this work, the previously automated acquisition and processing pipeline is re-designed and optimised for two purposes: 1—Through the previous work, the mentioned pipeline was used to analyse a specific area of the test piece surface in order to reconstruct the reference area and identify defects. In order to expand the application of this device over the entire test area, regardless of its extension, the pipeline is improved in which the final surface image is reconstructed by taking into account multiple segments of the test surface. The previously introduced pre-processing method of Dynamic Reference Reconstruction (DRR) is enhanced by using a more rigorous thresholding procedure. Principal Component Analysis (PCA) is then used in order for feature (DRR images) reduction. 2—The results of PCA on multiple segment images of the test surface revealed different ranges of intensities across each segment image. This potentially could cause mistaken interpretation of the defective and non-defective areas. An automated segmentation method based on Gaussian Mixture Model (GMM) is used to assist the expert user in more effective detection of the defective areas when the non-defective areas are uniformly characterised as background. The final results of GMM have shown not only the capability of accurately detecting subsurface metal loss as low as 37.5% but also the successful detection of defects that were either unidentifiable or invisible in either the original thermal images or their PCA transformed results.

Self-assembly mode and supramolecular framework of cyclopentanocucurbit[6]uril and aromatic amines

2021 ◽  
Vol 25 ◽  
Author(s):  
Jun Zheng ◽  
Yan Mei Jin ◽  
Xi Nan Yang ◽  
Lin Zhang ◽  
Dao Fa Jiang ◽  
...  
Keyword(s):  
Self Assembly ◽  
Functional Materials ◽  
Supramolecular Interactions ◽  
X Ray Diffraction ◽  
Guest Molecules ◽  
Characterization Methods ◽  
Potential Applications ◽  
Non Covalent Interactions ◽  
Multi Level ◽  
Covalent Interactions

: Single-crystal X-ray diffraction analysis, nuclear magnetic resonance (NMR), and other characterization methods are used to characterize the complexes formed by cyclopentano-cucurbit[6]uril (abbreviated as CyP6Q[6]) as a host interacting with p-aminobenzenesulfonamide (G1), 4,4'-diaminobiphenyl (G2), and (E)-4,4'-diamino-1,2-diphenylethene (G3) as guests, respectively. The experimental results show that these three aromatic amine molecules have the same interaction mode with CyP6Q[6], interacting with its negatively electric potential portals. The supramolecular interactions include non-covalent interactions of hydrogen bonding and ion-dipole between host and guest molecules. CdCl2 acts as a structureinducing agent to form self-assemblies of multi-dimensional and multi-level supramolecular frameworks that may have potential applications in various functional materials.

Review on Non-Destructive Testing Technique of Eddy Current Pulsed Thermography

2015 ◽  
Vol 742 ◽  
pp. 128-131 ◽  
Author(s):  
Jian Min Zhou ◽  
Jun Yang ◽  
Qi Wan
Keyword(s):  
Eddy Current ◽  
Signal Reconstruction ◽  
Infrared Image ◽  
Principal Component ◽  
Research Progress ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Pulsed Thermography ◽  
Pulsed Phase Thermography ◽  
Non Destructive

This paper introduces the theory of eddy current pulsed thermography and expounds the research status of eddy current pulsed thermography in application and information extraction. Thermographic signal reconstruction, pulsed phase thermography, principal component analysis were introuduced in this paper and listed some fusion multiple methods to acquire information from infrared image. At last, it summarizes research progress, existing problem and deelopment of eddy current pulsed thermography.

scholarly journals Vis/NIR hyperspectral imaging for detection of hidden bruises on kiwifruits

2011 ◽  
Vol 29 (No. 6) ◽  
pp. 595-602 ◽  
Author(s):  
Q. Lü ◽  
M.-j. Tang ◽  
J.-r. Cai ◽  
J.-w. Zhao ◽  
S. Vittayapadung
Keyword(s):  
Hyperspectral Imaging ◽  
Hyperspectral Image ◽  
Detection System ◽  
Image Data ◽  
Principal Component ◽  
Quality Analysis ◽  
Economic Losses ◽  
Hyperspectral Image Data ◽  
Multispectral Detection ◽  
Non Destructive

It is necessary to develop a non-destructive technique for kiwifruit quality analysis because the machine injury could lower the quality of fruit and incur economic losses. Bruises are not visible externally owing to the special physical properties of kiwifruit peel.We proposed the hyperspectral imaging technique to inspect the hidden bruises on kiwifruit. The Vis/NIR (408–1117 nm) hyperspectral image data was collected. Multiple optimal wavelength (682, 723, 744, 810, and 852 nm) images were obtained using principal component analysis on the high dimension spectral image data (wavelength range from 600 nm to 900 nm). The bruise regions were extracted from the component images of the five waveband images using RBF-SVM classification. The experimental results showed that the error of hidden bruises detection on fruits by means of hyperspectral imaging was 12.5%. It was concluded that the multiple optimal waveband images could be used to constructs a multispectral detection system for hidden bruises on kiwifruits.

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