Correlation methods in optical metrology with state-of-the-art x-ray mirrors

2018 ◽  
Author(s):  
Valeriy V. Yashchuk ◽  
Gary Centers ◽  
Gevork S. Gevorkyan ◽  
Ian Lacey ◽  
Brian V. Smith
Keyword(s):  
State Of The Art ◽  
Optical Metrology ◽  
X Ray ◽  
Correlation Methods

scholarly journals Long, elliptically bent, active X-ray mirrors with slope errors <200 nrad

2017 ◽  
Vol 24 (3) ◽  
pp. 615-621 ◽  
Author(s):  
Ioana T. Nistea ◽  
Simon G. Alcock ◽  
Paw Kristiansen ◽  
Adam Young
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Free Electron Laser ◽  
State Of The Art ◽  
Optical Metrology ◽  
Optical Surface ◽  
High Quality ◽  
Element Analysis ◽  
Bending Performance ◽  
X Ray

Actively bent X-ray mirrors are important components of many synchrotron and X-ray free-electron laser beamlines. A high-quality optical surface and good bending performance are essential to ensure that the X-ray beam is accurately focused. Two elliptically bent X-ray mirror systems from FMB Oxford were characterized in the optical metrology laboratory at Diamond Light Source. A comparison of Diamond-NOM slope profilometry and finite-element analysis is presented to investigate how the 900 mm-long mirrors sag under gravity, and how this deformation can be adequately compensated using a single, spring-loaded compensator. It is shown that two independent mechanical actuators can accurately bend the trapezoidal substrates to a range of elliptical profiles. State-of-the-art residual slope errors of <200 nrad r.m.s. are achieved over the entire elliptical bending range. High levels of bending repeatability (ΔR/R = 0.085% and 0.156% r.m.s. for the two bending directions) and stability over 24 h (ΔR/R = 0.07% r.m.s.) provide reliable beamline performance.

Revisiting the High-Pressure Properties of the Metal-Organic Frameworks ZIF-8 and ZIF-67

2020 ◽  
Author(s):  
Pia Vervoorts ◽  
Stefan Burger ◽  
Karina Hemmer ◽  
Gregor Kieslich
Keyword(s):  
High Pressure ◽  
State Of The Art ◽  
Energy Landscape ◽  
Structural Flexibility ◽  
Zeolitic Imidazolate Frameworks ◽  
Stimuli Responsive ◽  
X Ray Diffraction ◽  
X Ray ◽  
Open Questions ◽  
Metal Organic

The zeolitic imidazolate frameworks ZIF-8 and ZIF-67 harbour a series of fascinating stimuli responsive properties. Looking at their responsitivity to hydrostatic pressure as stimulus, open questions exist regarding the isotropic compression with non-penetrating pressure transmitting media. By applying a state-of-the-art high-pressure powder X-ray diffraction setup, we revisit the high-pressure behaviour of ZIF-8 and ZIF-67 up to <i>p</i> = 0.4 GPa in small pressure increments. We observe a drastic, reversible change of high-pressure powder X-ray diffraction data at <i>p</i> = 0.3 GPa, discovering large volume structural flexibility in ZIF-8 and ZIF-67. Our results imply a shallow underlying energy landscape in ZIF-8 and ZIF-67, an observation that might point at rich polymorphism of ZIF-8 and ZIF-67, similar to ZIF-4(Zn).<br>

Revisiting the High-Pressure Properties of the Metal-Organic Frameworks ZIF-8 and ZIF-67

2020 ◽  
Author(s):  
Pia Vervoorts ◽  
Stefan Burger ◽  
Karina Hemmer ◽  
Gregor Kieslich
Keyword(s):  
High Pressure ◽  
State Of The Art ◽  
Energy Landscape ◽  
Structural Flexibility ◽  
Zeolitic Imidazolate Frameworks ◽  
Stimuli Responsive ◽  
X Ray Diffraction ◽  
X Ray ◽  
Open Questions ◽  
Metal Organic

The zeolitic imidazolate frameworks ZIF-8 and ZIF-67 harbour a series of fascinating stimuli responsive properties. Looking at their responsitivity to hydrostatic pressure as stimulus, open questions exist regarding the isotropic compression with non-penetrating pressure transmitting media. By applying a state-of-the-art high-pressure powder X-ray diffraction setup, we revisit the high-pressure behaviour of ZIF-8 and ZIF-67 up to <i>p</i> = 0.4 GPa in small pressure increments. We observe a drastic, reversible change of high-pressure powder X-ray diffraction data at <i>p</i> = 0.3 GPa, discovering large volume structural flexibility in ZIF-8 and ZIF-67. Our results imply a shallow underlying energy landscape in ZIF-8 and ZIF-67, an observation that might point at rich polymorphism of ZIF-8 and ZIF-67, similar to ZIF-4(Zn).<br>

Infra-Red Reflectance Microscopy (IRRM) for Daisy Chain Flip Chip Device Failure Analysis

2004 ◽  
Author(s):  
Carlo Grilletto ◽  
Steve Hsiung ◽  
Andrew Komrowski ◽  
John Soopikian ◽  
Daniel J.D. Sullivan ◽  
...  
Keyword(s):  
Failure Analysis ◽  
Flip Chip ◽  
State Of The Art ◽  
Failure Mechanisms ◽  
Simple Metal ◽  
X Ray ◽  
Infra Red ◽  
Cause Of Failure ◽  
Reflectance Microscopy ◽  
Ir Emission

Abstract This paper describes a method to "non-destructively" inspect the bump side of an assembled flip-chip test die. The method is used in conjunction with a simple metal-connecting "modified daisy chain" die and makes use of the fact that polished silicon is transparent to infra-red (IR) light. The paper describes the technique, scope of detection and examples of failure mechanisms successfully identified. It includes an example of a shorting anomaly that was not detectable with the state of the art X-ray equipment, but was detected by an IR emission microscope. The anomalies, in many cases, have shown to be the cause of failure. Once this has been accomplished, then a reasonable deprocessing plan can be instituted to proceed with the failure analysis.

scholarly journals COVID-19 infection map generation and detection from chest X-ray images

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Aysen Degerli ◽  
Mete Ahishali ◽  
Mehmet Yamac ◽  
Serkan Kiranyaz ◽  
Muhammad E. H. Chowdhury ◽  
...  
Keyword(s):  
State Of The Art ◽  
Ground Truth ◽  
Clinical Use ◽  
X Ray ◽  
Learning Techniques ◽  
Map Generation ◽  
Severity Grading ◽  
Chest X Ray ◽  
Novel Method ◽  
Aided Diagnosis

AbstractComputer-aided diagnosis has become a necessity for accurate and immediate coronavirus disease 2019 (COVID-19) detection to aid treatment and prevent the spread of the virus. Numerous studies have proposed to use Deep Learning techniques for COVID-19 diagnosis. However, they have used very limited chest X-ray (CXR) image repositories for evaluation with a small number, a few hundreds, of COVID-19 samples. Moreover, these methods can neither localize nor grade the severity of COVID-19 infection. For this purpose, recent studies proposed to explore the activation maps of deep networks. However, they remain inaccurate for localizing the actual infestation making them unreliable for clinical use. This study proposes a novel method for the joint localization, severity grading, and detection of COVID-19 from CXR images by generating the so-called infection maps. To accomplish this, we have compiled the largest dataset with 119,316 CXR images including 2951 COVID-19 samples, where the annotation of the ground-truth segmentation masks is performed on CXRs by a novel collaborative human–machine approach. Furthermore, we publicly release the first CXR dataset with the ground-truth segmentation masks of the COVID-19 infected regions. A detailed set of experiments show that state-of-the-art segmentation networks can learn to localize COVID-19 infection with an F1-score of 83.20%, which is significantly superior to the activation maps created by the previous methods. Finally, the proposed approach achieved a COVID-19 detection performance with 94.96% sensitivity and 99.88% specificity.

scholarly journals The Degree of Oxidation of Graphene Oxide

Nanomaterials ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 560
Author(s):  
Alexandra Carvalho ◽  
Mariana C. F. Costa ◽  
Valeria S. Marangoni ◽  
Pei Rou Ng ◽  
Thi Le Hang Nguyen ◽  
...  
Keyword(s):  
Graphene Oxide ◽  
Ab Initio ◽  
State Of The Art ◽  
High Accuracy ◽  
Precise Determination ◽  
Photoemission Spectroscopy ◽  
Pristine Graphene ◽  
X Ray ◽  
Degree Of Oxidation

We show that the degree of oxidation of graphene oxide (GO) can be obtained by using a combination of state-of-the-art ab initio computational modeling and X-ray photoemission spectroscopy (XPS). We show that the shift of the XPS C1s peak relative to pristine graphene, ΔEC1s, can be described with high accuracy by ΔEC1s=A(cO−cl)2+E0, where c0 is the oxygen concentration, A=52.3 eV, cl=0.122, and E0=1.22 eV. Our results demonstrate a precise determination of the oxygen content of GO samples.

scholarly journals On the relation between mini-halos and AGN feedback in clusters of galaxies

2020 ◽  
Vol 499 (2) ◽  
pp. 2934-2958
Author(s):  
A Richard-Laferrière ◽  
J Hlavacek-Larrondo ◽  
R S Nemmen ◽  
C L Rhea ◽  
G B Taylor ◽  
...  
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Vital Role ◽  
Clusters Of Galaxies ◽  
Relativistic Jets ◽  
X Ray ◽  
Core Cluster ◽  
Central Galaxy ◽  
Central Regions ◽  
Radio Power

ABSTRACT A variety of large-scale diffuse radio structures have been identified in many clusters with the advent of new state-of-the-art facilities in radio astronomy. Among these diffuse radio structures, radio mini-halos are found in the central regions of cool core clusters. Their origin is still unknown and they are challenging to discover; less than 30 have been published to date. Based on new VLA observations, we confirmed the mini-halo in the massive strong cool core cluster PKS 0745−191 (z = 0.1028) and discovered one in the massive cool core cluster MACS J1447.4+0827 (z = 0.3755). Furthermore, using a detailed analysis of all known mini-halos, we explore the relation between mini-halos and active galactic nucleus (AGN) feedback processes from the central galaxy. We find evidence of strong, previously unknown correlations between mini-halo radio power and X-ray cavity power, and between mini-halo and the central galaxy radio power related to the relativistic jets when spectrally decomposing the AGN radio emission into a component for past outbursts and one for ongoing accretion. Overall, our study indicates that mini-halos are directly connected to the central AGN in clusters, following previous suppositions. We hypothesize that AGN feedback may be one of the dominant mechanisms giving rise to mini-halos by injecting energy into the intra-cluster medium and reaccelerating an old population of particles, while sloshing motion may drive the overall shape of mini-halos inside cold fronts. AGN feedback may therefore not only play a vital role in offsetting cooling in cool core clusters, but may also play a fundamental role in re-energizing non-thermal particles in clusters.

A robust framework for shoulder implant X-ray image classification

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Minh Thanh Vo ◽  
Anh H. Vo ◽  
Tuong Le
Keyword(s):  
Image Classification ◽  
Performance Metrics ◽  
State Of The Art ◽  
Area Under The Curve ◽  
Predictive Performance ◽  
Extraction Process ◽  
Content Type ◽  
X Ray ◽  
Robust Model ◽  
Input Dataset

PurposeMedical images are increasingly popular; therefore, the analysis of these images based on deep learning helps diagnose diseases become more and more essential and necessary. Recently, the shoulder implant X-ray image classification (SIXIC) dataset that includes X-ray images of implanted shoulder prostheses produced by four manufacturers was released. The implant's model detection helps to select the correct equipment and procedures in the upcoming surgery.Design/methodology/approachThis study proposes a robust model named X-Net to improve the predictability for shoulder implants X-ray image classification in the SIXIC dataset. The X-Net model utilizes the Squeeze and Excitation (SE) block integrated into Residual Network (ResNet) module. The SE module aims to weigh each feature map extracted from ResNet, which aids in improving the performance. The feature extraction process of X-Net model is performed by both modules: ResNet and SE modules. The final feature is obtained by incorporating the extracted features from the above steps, which brings more important characteristics of X-ray images in the input dataset. Next, X-Net uses this fine-grained feature to classify the input images into four classes (Cofield, Depuy, Zimmer and Tornier) in the SIXIC dataset.FindingsExperiments are conducted to show the proposed approach's effectiveness compared with other state-of-the-art methods for SIXIC. The experimental results indicate that the approach outperforms the various experimental methods in terms of several performance metrics. In addition, the proposed approach provides the new state of the art results in all performance metrics, such as accuracy, precision, recall, F1-score and area under the curve (AUC), for the experimental dataset.Originality/valueThe proposed method with high predictive performance can be used to assist in the treatment of injured shoulder joints.

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