A General-Purpose Debye-Scherrer Camera and its Application to Work at Low Temperatures

Hume‐Rothery, W.; Strawbridge, Dick

doi:10.1088/0950-7671/24/4/302

Cited by 16 publications

(6 citation statements)

References 4 publications

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“…The optimised parameters for equation 1 are listed here to 15 significant figures to prevent rounding errors when evaluating the equation (rounding errors can make this otherwise monotonic function nonmonotonic at T<20K): m = 5.46215569838344x10 -4 , n=86.0150000000000, p0 = 1.80595722249783x10 31 , p1 = 2.96317351342354x10 30 , p2 = 2.25855016769900x10 29 , p3 = 1.06004494945302x10 28 , p4 = 3.42305759706082x10 26 , p5 = 8.04609813573980x10 24 , p6 = 1.41998402393052x10 23 , p7 = 1.91189157411850x10 21 , p8 = 1.97428843905832x10 19 , p9 = 1.55692828415459x10 17 , p10 = 9.23827056204128x10 14 , p11 = 4.00527886712625x10 12 , p12 = 1.20273329860717x10 10 , p13 = 2.25714359192389x10 7 , p14 = 2.06989439078737x10 4 , p15 = 1.00000000000000, q0 = 2.04335860741967x10 30 , q1 = 3.32581764853519x10 29 , q2 = 2.51326102603950x10 28 , q3 = 1.16875476418741x10 27 , q4 = 3.73664547057534x10 25 , q5 = 8.68835777614448x10 23 , q6 = 1.51514697020481x10 22 , q7 = 2.01313321790028x10 20 , q8 = 2.04788881667471x10 18 , q9 = 1.58723386748412x10 16 , q10 = 9.22649460840626x10 13 , q11 = 3.90058588445197x10 11 , q12 = 1.13369350824041x10 9 , q13 = 2.02772058226054x10 6 , q14 = 1.68385961108157x10 3 .…”

Section: Introductionmentioning

confidence: 99%

“…The optimised parameters for fitting equation 2 to the experimental data points are: s0 = 8.55692806695981x10 18 , s1 = 1.09556645819752x10 24 , s2 = 1.78316852655619x10 23 , s3 = 2.04804545623587x10 22 , s4 = 1.60396172331341x10 21 , s5 = 2.36491757661617x10 20 , s6 = 2.07873881554774x10 19 , s7 = 9.19266228575283x10 17 , s8 = 2.20725652279774x10 16 , s9 = 2.93361641840158x10 14 , s10 = 2.08150841393624x10 12 , s11 = 8.47737173962446x10 9 , s12 = 5.09073073293741x10 7 , s13 = 3.26718741801178x10 5 , s14 = -3.93634611081583x10 2 , s15 = 1.00000000000000, and parameters n, pi and qi are the same as for equation 1. Again, all parameters have been listed to 15 significant figures to avoid problems associated with rounding errors.…”

Section: Introductionmentioning

confidence: 99%

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The Crystallography of Aluminum and Its Alloys

Nakashima

2019

Encyclopedia of Aluminum and Its Alloys

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This article begins with pure aluminum and a discussion of the form of the crystal structure and different unit cells that can be used to describe it. Measurements of the face-centered cubic lattice parameter and thermal expansion coefficient in pure aluminum are reviewed and parametrizations are given which allow the reader to evaluate them across the full range of temperatures where aluminum is a solid. A new concept called the “vacancy triangle” is introduced and demonstrated as an effective means for determining vacancy concentrations near the melting point of aluminum. The Debye–Waller factor, quantifying the thermal vibration of aluminum atoms in pure aluminum, is reviewed and parametrized over the full range of temperatures where aluminum is a solid. The nature of interatomic bonding and the history of its characterization in pure aluminum are reviewed with the unequivocal conclusion that it is purely tetrahedral in nature. The crystallography of aluminum alloys is then discussed in terms of all of the concepts covered for pure aluminum, using prominent alloy examples. The electron density domain theory of solid-state nucleation and precipitate growth is introduced and discussed as a new means of rationalizing phase transformations in alloys from a crystallographic point of view.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Crystallography of Aluminum and Its Alloys

Nakashima

2019

Encyclopedia of Aluminum and Its Alloys

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“…In a few cases [Glover, 1954;Gott, 1942;Smith, 1954] appreciable differences in thermal expansion by the two methods have been found, amounting to over 10 percent at the worst. However, others have found no difference exceeding experimental error except near the melting point [Austin, Saini, Weigle, and Pierce, 1940;Berry, 1953;Connell and Martin, 1951; van Duijn and van Galen, 1957;Feder and Nowick, 1958; Hume-Rothery and Andrews, 1942; Hume-Rothery and Boultbee, 1949; Hume-Rothery and Strawbridge, 1947;Baluffi, 1 1959, 1960;Wagner and Beyer, 1936]. Such differences, if real, would require high concentrations of vacancies or nonuniform distribution of lattice defects.…”

Section: Introductionmentioning

confidence: 98%

Thermal expansion of technical solids at low temperatures; a compilation from the literature

Corruccini¹,

Gniewek²

1961

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“…ReaxFF percent differences (%Δ) were computed with respect to PBE-D3 values. Experimental room temperature densities, α-alumina cell parameters, 83 and aluminum cell parameters 84 are provided for comparison. Optimized values for the model parameters were obtained by a least-squares fit and are collected in Table 2.…”

Section: ■ Resultsmentioning

confidence: 99%

Model for Humidity-Mediated Diffusion on Aluminum Surfaces and Its Role in Accelerating Atmospheric Aluminum Corrosion

Scher

Weitzner

Hao

et al. 2023

ACS Appl. Mater. Interfaces

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Bare aluminum metal surfaces are highly reactive, which leads to the spontaneous formation of a protective oxide surface layer. Because many subsequent corrosive processes are mediated by water, the structure and dynamics of water at the oxide interface are anticipated to influence corrosion kinetics. Using molecular dynamics simulations with a reactive force field, we model the behavior of aqueous aluminum metal ions in water adsorbed onto aluminum oxide surfaces across a range of ion concentrations and water film thicknesses corresponding to increasing relative humidity. We find that the structure and diffusivity of both the water and the metal ions depend strongly on the humidity of the environment and the relative height within the adsorbed water film. Aqueous aluminum ion diffusion rates in water films corresponding to a typical indoor relative humidity of 30% are found to be more than 2 orders of magnitude slower than self-diffusion of water in the bulk limit. Connections between metal ion diffusivity and corrosion reaction kinetics are assessed parametrically with a reductionist model based on a 1D continuum reaction−diffusion equation. Our results highlight the importance of incorporating the properties specific to interfacial water in predictive models of aluminum corrosion.

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A General-Purpose Debye-Scherrer Camera and its Application to Work at Low Temperatures

Cited by 16 publications

References 4 publications

The Crystallography of Aluminum and Its Alloys

The Crystallography of Aluminum and Its Alloys

Thermal expansion of technical solids at low temperatures; a compilation from the literature

Model for Humidity-Mediated Diffusion on Aluminum Surfaces and Its Role in Accelerating Atmospheric Aluminum Corrosion

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