Amorpheus: a Python-based software for the treatment of X-ray scattering data of amorphous and liquid systems

Boccato, Silvia; Garino, Y.; Morard, Guillaume; Zhao, Bin; Xu, Fang; Sanloup, C.; King, Andrew; Guignot, Nicolas; Clark, A. N.; Garbarino, Gastón; Morand, Marc; Antonangeli, Daniele

doi:10.1080/08957959.2022.2032032

Cited by 9 publications

(4 citation statements)

References 73 publications

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“…These data have been converted to S(Q) and g(r) with the Amorpheus software package (Boccato et al, 2021), using two different values of Q max , 7.3 and 9.2 A ˚À1 . The resultant profiles are shown in Fig.…”

Section: Resultsmentioning

confidence: 99%

Combined angular and energy dispersive diffraction: optimized data acquisition, normalization and reduction

King¹,

Guignot²,

Henry³

et al. 2022

J Appl Crystallogr

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Combined angular and energy dispersive diffraction is particularly well suited to experiments at high pressures in large-volume presses, and to the study of liquid or amorphous systems. This work describes the data acquisition, correction and reduction approach developed at the PSICHE beamline of the SOLEIL synchrotron. The measured data were normalized for both the scattering volume and the effective incident energy spectrum. By optimizing the acquisition strategy, the measurement time and radiation dose are greatly reduced. The correction and reduction protocol outputs normalized scattering profiles that are suitable for pair distribution function or liquid structure analysis. These processes are demostrated with examples from a number of real experimental data sets.

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Section: Resultsmentioning

confidence: 99%

Combined angular and energy dispersive diffraction: optimized data acquisition, normalization and reduction

King¹,

Guignot²,

Henry³

et al. 2022

J Appl Crystallogr

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“…For the calculation of S ( Q ) and g ( r ), we used the Python‐based software (Amorpheus) developed by Boccato et al. (2022). Because the 2 θ angle was too small to calculate g ( r ) for the direction perpendicular to the deformation, the calculation was performed only for the data parallel to the deformation.…”

Section: Methodsmentioning

confidence: 99%

“…Then, the structural factor S(Q) and radial distribution function g(r) were calculated from typical XRD data obtained during tension and compression (Figures 1b and 1c). For the calculation of S(Q) and g(r), we used the Python-based software (Amorpheus) developed by Boccato et al (2022). Because the 2θ angle was too small to calculate g(r) for the direction perpendicular to the deformation, the calculation was performed only for the data parallel to the deformation.…”

Section: Methodsmentioning

confidence: 99%

A Molecular‐Scale Origin of Shear Thinning and Brittle Failure of Silicate Melt

Okumura,

Uesugi,

Goto

et al. 2023

Geophysical Research Letters

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Shear thinning and brittle failure of silicate melt control the dynamics of volcanic eruptions, but their molecular‐scale origin is still unclear. Here, we conducted tension and compression experiments on silicate melts, using time‐resolved X‐ray diffraction. Our experiments revealed that the intermediate‐range ordering of silicate structures, that is, the ring size formed by the SiO4 tetrahedra, demonstrated elastic and anisotropic dilation under tension and shrinkage under compression in the non‐Newtonian regime. In contrast, there were no significant changes in short‐range ordering, such as Si–O and Si–Si distances. Based on these findings, we inferred that shear thinning observed under high stress originates from the formation of anisotropically deformed large and small rings in silicate structures that are energetically unfavorable and unstable. Brittle failure occurred under high‐stress conditions, in both tension and compression. We propose a stress criterion as a necessary and sufficient condition for magma failure, rather than a strain rate criterion.

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“…The CAESAR data were analyzed on the basis of the methodology developed by Eggert et al (2002) and Morard et al (2014) implemented into the software AMORPHEUS (Boccato et al, 2022) to study the local structure and density of the liquids. In particular, the pair distribution function g(r) and distribution function F(r) (also referred to as reduced distribution function) are obtained from the collected S(Q) by a Fourier transformation.…”

Section: High-pressure In Situ X-ray Diffraction Experimentsmentioning

confidence: 99%

Local Structure and Density of Liquid Fe‐C‐S Alloys at Moon's Core Conditions

et al. 2023

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The local structure and density of ternary Fe‐C‐S liquid alloys have been studied using a combination of in situ X‐ray diffraction and absorption experiments between 1 and 5 GPa and 1600–1900 K. The addition of up to 12 at% of carbon (C) to Fe‐S liquid alloys does not significantly modify the structure, which is largely controlled by the perturbation to the Fe‐Fe network induced by S atoms. The liquid density determined from diffraction and/or absorption techniques allows us to build a non‐ideal ternary mixing model as a function of pressure, temperature, and composition in terms of the content of alloying light elements. The composition of the Moon's core is addressed based on this thermodynamic model. Under the assumption of a homogeneous liquid core proposed by two recent Moon models, the sulfur content would be 27–36 wt% or 12–23 wt%, respectively, while the carbon content is mainly limited by the Fe‐C‐S miscibility gap, with an upper bound of 4.3 wt%. On the other hand, if the core is partially molten, the core temperature is necessarily lower than 1850 K estimated in the text, and the composition of both the inner and outer core would be controlled by aspects of the Fe‐C‐S phase diagram not yet sufficiently constrained.

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Amorpheus: a Python-based software for the treatment of X-ray scattering data of amorphous and liquid systems

Cited by 9 publications

References 73 publications

Combined angular and energy dispersive diffraction: optimized data acquisition, normalization and reduction

Combined angular and energy dispersive diffraction: optimized data acquisition, normalization and reduction

A Molecular‐Scale Origin of Shear Thinning and Brittle Failure of Silicate Melt

Local Structure and Density of Liquid Fe‐C‐S Alloys at Moon's Core Conditions

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