Results 21 to 30 of about 637,903 (236)

Structural studies of the brass ingots from the Shcherbet historical complex of the Lower Kama region: neutron diffraction and tomography studies

Eurasian Journal of Physics and Functional Materials, 2022
The structural characteristics and phase composition of several ancient brass ingots obtained in the archeological Shcherbet complex has been studied using neutron diffraction and tomography methods.
A.Zh. Zhomartova, E.F. Shaykhutdinova, B.A. Bakirov, S.E. Kichanov, D.P. Kozlenko, A.G. Sitdikov   +5 more
doaj   +1 more source

Neutron diffraction study of the Cr84.7Re15.3 alloy

AIP Advances, 2021
Measurements of the temperature dependence of electrical resistance (R) and neutron powder diffraction (NPD) of a Cr84.7Re15.3 alloy is reported. The magnetism originates from the formation of a spin-density-wave (SDW) as a result of nesting between the ...
B. S. Jacobs, A. R. E. Prinsloo, A. M. Venter, Z. N. Sentsho, A. J. Studer, C. J. Sheppard   +5 more
doaj   +1 more source

The neutron diffraction experiments under high pressure and high temperature on FENGHUANG diffractometer at CMRR

Nuclear Analysis, 2022
FENGHUANG diffractometer at CMRR, a high-intensity multi-section neutron powder diffractometer, has been constructed to in situ studies of materials under high pressure high temperature conditions.
Leiming Fang, Xiping Chen, Lei Xie, Guangai Sun, Bo Chen, Shuming Peng   +5 more
doaj   +1 more source

The Wiener-Hopf-Hilbert technique applied to problems in diffraction [PDF]

, 1999
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A number of diffraction problems which have practical applications are examined using the Wiener-Hopf-Hilbert technique.
Barton, P.G., Barton, Peter
core   +7 more sources

Fast and Accurate Pixel Calibration of Tof Neutron Diffractometers with Machine Learning

Quantum Beam Science
At a spallation neutron source, neutron pulses of varying energies are generated, and the detection of neutrons by instrument detectors is recorded as time-of-flight from the emission of the neutron pulse to its arrival at specific detector pixels with ...
Albert P. Song, Ke An
doaj   +1 more source

Magnetic ordering in Gd5Ir2Bi and Gd5Ir2Sb

AIP Advances, 2016
155Gd Mössbauer spectroscopy and neutron powder diffraction have been used to study magnetic ordering in Gd5Ir2Bi and Gd5Ir2Sb. Despite the hyperfine fields (Bhf) at the two Gd sites differing by more than a factor of two for both compounds, the moments ...
D. H. Ryan, Nadejda Mas, Rasa Rejali, T. Miller, Birgit Gerke, Birgit Heying, Rainer Pöttgen, Roxana Flacau   +7 more
doaj   +1 more source

Neutron Diffraction Measurements of Residual Stresses for Ferritic Steel Specimens over 80 mm Thick

Metals
The maximum thickness for ferritic steel specimens’ residual stress measurements using neutron diffraction is known to be about 80 mm. This paper proposes a new neutron diffraction configuration of residual stress measurements for cases that are over 80 ...
Vyacheslav Em, Karpov Ivan, Wanchuck Woo, Pavol Mikula   +3 more
doaj   +1 more source

X-ray powder diffraction analysis of methionine sulfoxide

, 2001
Powder X-ray diffraction data for methionine sulfoxide, C5H11NO3S, obtained from the commercial amino acid, are presented in this work. Monoclinic cell parameters are: a = 15.500 Angstrom; b = 3.820 Angstrom; c = 13.490 Angstrom; 8=97.300 degrees.
Melnikov, P., Massabni, Antonio Carlos, Corbi, P. P., Massabni, Antonio Carlos [UNESP]   +3 more
core   +1 more source

Study on Texture Recognition Capability and Anti-noise Performance of Convolutional Neural Networks

Yuanzineng kexue jishu
Neutron diffraction has been recognized as an ideal analytical technique for investigating material properties and functions through the characterization of phase composition, structural features, and microstructural characteristics.
ZHAO Bokai1, 2, HOU Yuhan1, 2, LIU Xiaolong1, 2, LI Yuqing1, 2, LIU Danmin3, LI Meijuan1, 2, , CHEN Dongfeng1, 2, , ZHANG Yingxun1,
doaj   +1 more source

Automated multiphase identification and refinement in powder diffraction using mismatch-tolerant machine learning [PDF]

APL Machine Learning
Powder diffraction is a primary structural characterization tool in materials science, yet automated phase identification remains a major bottleneck for autonomous discovery.
Lalit Yadav, Yongqiang Cheng, Mathieu Doucet   +2 more
doaj   +1 more source