The crystallographic structures of disordered materials are typically analyzed using diffractometry techniques, such as x-ray diffraction (XRD), neutron diffraction (ND), and electron diffraction (ED). Here, we demonstrate a novel technique to analyze the local structure of disordered materials via scanning transmission electron microscopy (STEM) under a contrast variation scheme. Contrast variation is a scheme used for the analysis of bulk materials, which combines two different diffractometry techniques with discrete scattering factors, such as ND and XRD. The STEM image contrasts of annular dark-field (ADF) and annular bright-field (ABF) imaging, which are characterized by different atomic number dependences, are simultaneously utilized. Simulated STEM images of amorphous SiO2 are examined using Fourier transform and autocorrelation operations, revealing that the Fourier transforms of ADF and ABF images are consistent with the results of conventional XRD/ED and ND techniques, respectively. The autocorrelation of the ABF image indicates the short-range ordering of light elements, which cannot be accomplished using conventional TEM, ED, and XRD techniques. As such, employing the contrast variation scheme in STEM imaging paves the way for analyzing the local crystallographic structure of non-monoatomic materials.

Transformation of Land use Land cover is a dynamic process that takes place on the Earth’s surface and becomes a basic component in current strategies to manage natural resources and to monitor environmental changes. Remote sensing and GIS are important tools and techniques for monitoring and assessment of land use land cover change status, which can be helpful to decide the strategies for productive use of land for sustainable development. Therefore, it is important to detect the land use or land cover changes for sustaining growth and development of any region. The objective of this paper is to analyse the land use land cover changes over the last 24 years in Jodhpur district, Rajasthan, using multi season satellite data of 30 meter spatial resolution namely, Landsat-5 TM for 1993 and Landsat-8 OLI/TIRS for 2017. This paper has prepared the land use land cover status map on 1:50000 scale with the help of manual digitization technique for the years 1993 and 2017. Later, the change detection in land use land cover changes from 1993 to 2017 has been calculated using ArcGIS software. Land use land cover classes are classified into various categories such as built-up land, kharif crop, Rabi crop, double crop, fallow land, forest, scrub land, dunes, Barren/Rocky area, Quarrying, Lake/Reservoir/Tank, and others for the years of 1993 and 2017. The result of the study shows the expansion of agricultural land, built-up land, Quarrying and other manmade area during this time period and at the same time scrub land, dunes and barren rocky area are decreased. This has significant impact on the livelihood of the local community.

The distribution of electric fields in hexagonal boron nitride is mapped down to the atomic level inside a scanning transmission electron microscope by using the recently introduced technique of differential phase contrast imaging. The maps are calculated and displayed in real time, along with conventional annular dark-field images, through the use of custom-developed hardware and software. An increased electric field is observed around boron monovacancies and subsequently mapped and measured relative to the perfect lattice. The edges of extended defects feature enhanced electric fields, which can be used to trap diffusing adatoms. The magnitude of the electric field produced by the different types of edges is compared to monolayer areas, confirming previous predictions regarding their stability. These observations provide insight into the properties of this interesting material, serving as a suitable platform on which to test the limits of this technique, and encourage further work, such as dynamic experiments coupled with in situ techniques.

Although the possibility of locating single atom in three dimensions using the scanning transmission electron microscope (STEM) has been discussed with the advent of aberration correction technology, it is still a big challenge. In this report we have developed deconvolution routines based on maximum entropy method (MEM) and Richardson-Lucy algorithm (RLA), which are applicable to the STEM-annular dark-field (ADF) though-focus images to improve the depth resolution. The new three-dimensional (3D) deconvolution routines require a limited defocus-range of STEM-ADF images that covers a whole sample and some vacuum regions. Since the STEM-ADF probe is infinitely elongated along the optical axis, a 3D convolution is performed with a two-dimensional (2D) convolution over xy-plane using the 2D fast Fourier transform in reciprocal space, and a one-dimensional convolution along the z-direction in real space. Using our new deconvolution routines, we have processed simulated focal series of STEM-ADF images for single Ce dopants embedded in wurtzite-type AlN. Applying the MEM, the Ce peaks are clearly localized along the depth, and the peak width is reduced down to almost one half. We also applied the new deconvolution routines to experimental focal series of STEM-ADF images of a monolayer graphene. The RLA gives smooth and high-P/B ratio scattering distribution, and the graphene layer can be easily detected. Using our deconvolution algorithms, we can determine the depth locations of the heavy dopants and the graphene layer within the precision of 0.1 and 0.2 nm, respectively. Thus, the deconvolution must be extremely useful for the optical sectioning with 3D STEM-ADF images.

Journal Article Realtime Up-sampling Noise Filter: Paradigm Shift for Data Acquisition Get access Akimitsu Ishizuka, Akimitsu Ishizuka HREM Research Inc., Higashimatsuyama, Saitama, Japan Search for other works by this author on: Oxford Academic Google Scholar Koji Kimoto, Koji Kimoto National Institute for Materials Science, Tsukuba, Ibaraki, Japan Search for other works by this author on: Oxford Academic Google Scholar Kazuo Ishizuka Kazuo Ishizuka HREM Research Inc., Higashimatsuyama, Saitama, Japan Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 26, Issue S2, 1 August 2020, Pages 1936–1938, https://doi.org/10.1017/S143192762001987X Published: 01 August 2020

Journal Article Low Count Detection for EELS Spectrum by Reducing CCD Read-out Noise Get access Mitsutaka Haruta, Mitsutaka Haruta Kyoto University, Uji, Kyoto, Japan Search for other works by this author on: Oxford Academic Google Scholar Yoshifumi Fujiyoshi, Yoshifumi Fujiyoshi Kyoto University, Uji, Kyoto, Japan Search for other works by this author on: Oxford Academic Google Scholar Takashi Nemoto, Takashi Nemoto Kyoto University, Uji, Kyoto, Japan Search for other works by this author on: Oxford Academic Google Scholar Akimitsu Ishizuka, Akimitsu Ishizuka HREM Research Inc., Higashimatsuyama, Saitama, Japan Search for other works by this author on: Oxford Academic Google Scholar Kazuo Ishizuka, Kazuo Ishizuka HREM Research Inc., Higashimatsuyama, Saitama, Japan Search for other works by this author on: Oxford Academic Google Scholar Hiroki Kurata Hiroki Kurata Kyoto University, Uji, Kyoto, Japan Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 26, Issue S2, 1 August 2020, Pages 1202–1204, https://doi.org/10.1017/S1431927620017328 Published: 01 August 2020

Extremely low count detection for EELS spectrum imaging is required to overcome problems with electron irradiation and widen the range of available applications. We have made a systematic statistical study of the reduction of CCD noise for EELS. We propose a calculation method to estimate the properties of noise and a procedure to reduce it. Since the dominant noise is a practically random component, it can be reduced by subtracting the population mean of the dark reference and a summation over an appropriate number of spectra, depending on the standard deviation of the noise. A gain-averaging method can further improve the signal-to-noise (SN) ratio. It is thereby demonstrated that a high-SN spectrum can be obtained even for a single-count core-loss signal. The present method would be useful for measuring low signal spectrum such as monochromated spectra and for radiation sensitive materials.