scholarly journals TXM-Sandbox: an open-source software for transmission X-ray microscopy data analysis

2022 ◽  
Vol 29 (1) ◽  
Author(s):  
Xianghui Xiao ◽  
Zhengrui Xu ◽  
Feng Lin ◽  
Wah-Keat Lee

A transmission X-ray microscope (TXM) can investigate morphological and chemical information of a tens to hundred micrometre-thick specimen on a length scale of tens to hundreds of nanometres. It has broad applications in material sciences and battery research. TXM data processing is composed of multiple steps. A workflow software has been developed that integrates all the tools required for general TXM data processing and visualization. The software is written in Python and has a graphic user interface in Jupyter Notebook. Users have access to the intermediate analysis results within Jupyter Notebook and have options to insert extra data processing steps in addition to those that are integrated in the software. The software seamlessly integrates ImageJ as its primary image viewer, providing rich image visualization and processing routines. As a guide for users, several TXM specific data analysis issues and examples are also presented.

Proceedings ◽  
2020 ◽  
Vol 62 (1) ◽  
pp. 9
Author(s):  
Oriol Vallcorba ◽  
Jordi Rius

The d1Dplot and d2Dplot computer programs have been developed as user-friendly tools for the inspection and processing of 1D and 2D X-ray diffraction (XRD) data, respectively. d1Dplot provides general tools for data processing and includes the ability to generate comprehensive 2D plots of multiple patterns to easily follow transformation processes. d2Dplot is a full package for 2D XRD data. Besides general processing tools, it includes specific data analysis routines for the application of the through-the-substrate methodology [Rius et al. IUCrJ 2015, 2, 452–463]. Both programs allow the creation of a user compound database for the identification of crystalline phases. The software can be downloaded from the ALBA Synchrotron Light Source website and can be used free of charge for non-commercial and academic purposes.


2018 ◽  
Vol 955 ◽  
pp. 012005 ◽  
Author(s):  
Evgeny Pichkur ◽  
Timur Baimukhametov ◽  
Anton Teslyuk ◽  
Anton Orekhov ◽  
Roman Kamyshinsky ◽  
...  

Author(s):  
P. Ingram

It is well established that unique physiological information can be obtained by rapidly freezing cells in various functional states and analyzing the cell element content and distribution by electron probe x-ray microanalysis. (The other techniques of microanalysis that are amenable to imaging, such as electron energy loss spectroscopy, secondary ion mass spectroscopy, particle induced x-ray emission etc., are not addressed in this tutorial.) However, the usual processes of data acquisition are labor intensive and lengthy, requiring that x-ray counts be collected from individually selected regions of each cell in question and that data analysis be performed subsequent to data collection. A judicious combination of quantitative elemental maps and static raster probes adds not only an additional overall perception of what is occurring during a particular biological manipulation or event, but substantially increases data productivity. Recent advances in microcomputer instrumentation and software have made readily feasible the acquisition and processing of digital quantitative x-ray maps of one to several cells.


Author(s):  
Auclair Gilles ◽  
Benoit Danièle

During these last 10 years, high performance correction procedures have been developed for classical EPMA, and it is nowadays possible to obtain accurate quantitative analysis even for soft X-ray radiations. It is also possible to perform EPMA by adapting this accurate quantitative procedures to unusual applications such as the measurement of the segregation on wide areas in as-cast and sheet steel products.The main objection for analysis of segregation in steel by means of a line-scan mode is that it requires a very heavy sampling plan to make sure that the most significant points are analyzed. Moreover only local chemical information is obtained whereas mechanical properties are also dependant on the volume fraction and the spatial distribution of highly segregated zones. For these reasons we have chosen to systematically acquire X-ray calibrated mappings which give pictures similar to optical micrographs. Although mapping requires lengthy acquisition time there is a corresponding increase in the information given by image anlysis.


Author(s):  
G.E. Ice

The increasing availability of synchrotron x-ray sources has stimulated the development of advanced hard x-ray (E≥5 keV) microprobes. With new x-ray optics these microprobes can achieve micron and submicron spatial resolutions. The inherent elemental and crystallographic sensitivity of an x-ray microprobe and its inherently nondestructive and penetrating nature will have important applications to materials science. For example, x-ray fluorescent microanalysis of materials can reveal elemental distributions with greater sensitivity than alternative nondestructive probes. In materials, segregation and nonuniform distributions are the rule rather than the exception. Common interfaces to whichsegregation occurs are surfaces, grain and precipitate boundaries, dislocations, and surfaces formed by defects such as vacancy and interstitial configurations. In addition to chemical information, an x-ray diffraction microprobe can reveal the local structure of a material by detecting its phase, crystallographic orientation and strain.Demonstration experiments have already exploited the penetrating nature of an x-ray microprobe and its inherent elemental sensitivity to provide new information about elemental distributions in novel materials.


Author(s):  
Ernst Bauer

One of the major shortcomings of conventional PEEM and of LEEM is the lack of chemical information about the surface. Although the imaging of the LEED pattern in the back focal plane of the objective lens of a LEEM instrument allows chemical characterization via the crystalline structure derived from the LEED pattern, this method fails in the absence of a characteristic LEED pattern. Direct information about the atomic composition of the surface is then needed which can be best obtained from inner shell electrons either directly by x-ray-induced photoemission (XPEEM) or by x-ray- or electron-induced Auger electron emission (AEEM). These modes of excitation and imaging can be combined with conventional PEEM and LEEM in one instrument which is presently being developed. Thus a complete structural and chemical characterization becomes possible in one instrument, with parallel detection and high resolution.In contrast to LEEM, in which up to more than 50% of the incident intensity is available for image formation, the intensity of the emitted electrons is much lower in XPEEM and AEEM and the signal is much lower than the background in AEEM. Therefore, intensity I and resolution d have to be optimized simultaneously which is best done by maximizing Q = I/d2 with respect to maximum emission angle α and relative energy distribution ε = ΔVo/V accepted by the instrument. For a well-designed magnetic lens section of the cathode lens its aberrations are determined by the accelerating field F in front of the specimen. For a homogeneous accelerating field F and a cosine emission distribution one obtains for the optimum α and ε values αo,εo a radius of the minimum disc of confusion of


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Sven Lißner ◽  
Stefan Huber

Abstract Background GPS-based cycling data are increasingly available for traffic planning these days. However, the recorded data often contain more information than simply bicycle trips. GPS tracks resulting from tracking while using other modes of transport than bike or long periods at working locations while people are still tracking are only some examples. Thus, collected bicycle GPS data need to be processed adequately to use them for transportation planning. Results The article presents a multi-level approach towards bicycle-specific data processing. The data processing model contains different steps of processing (data filtering, smoothing, trip segmentation, transport mode recognition, driving mode detection) to finally obtain a correct data set that contains bicycle trips, only. The validation reveals a sound accuracy of the model at its’ current state (82–88%).


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