Quantitative analysis of grain size in bimodal powders by x-ray diffraction and transmission electron microscopy

He, Jianhong; Ye, J.; Lavernia, Enrique J.; Matejczyk, D. E.; Bampton, C.C.; Schoenung, Julie M.

doi:10.1023/b:jmsc.0000047538.95825.ad

Cited by 29 publications

(33 citation statements)

References 10 publications

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“…Klug and Alexander have reported that this approximation well represents the intrinsic broadening [16]. Furthermore, suppose that the grain size and micro-strain broadening were described by using Cauchy-Gaussian (CG) relationship, He et al and Zang et al reported that the CG approximation is the most appropriate method for the linear fitting for grain size and micro-strain [17,18]; the following equation can be derived:…”

Section: Methodsmentioning

confidence: 99%

Electrical conductivity of ceria nanoparticles under high pressure

et al. 2008

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This paper describes the electrical conductivity of ceria nanoparticles under high pressure ranging from 2 to 6 GPa. The samples used were pure and acceptor-doped ceria nanoparticles with a grain size of approximately 2 nm prepared by mixing hexamethylenetramine and metal nitrate solutions. The size of ceria nanoparticles was controlled to be 2 to 15 nm by varying heat-treatment conditions. The in-situ electrical conductivity measurements under high pressure were conducted by using an ac-impedance spectroscopy. By applying a pressure of 6 GPa at 300 • C, the green compact of 6 mol % Sm-doped ceria nanoparticles was densified; a relative density of 93% was achieved. The sample showed an electrical conductivity of 3× 10 −3 S/cm at 300 • C under 6 GPa. The enhancement of electrical conductivity under high pressure seems to be related to ionic conduction in the vicinity of grain boundaries.

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Section: Methodsmentioning

confidence: 99%

Electrical conductivity of ceria nanoparticles under high pressure

et al. 2008

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“…The results reported by several investigators [17,[30][31][32] indicated that the measurements obtained from both methods were comparable. However, recent studies [33][34][35] have demonstrated that grain size measurements from XRD lead to underestimation when deviations in narrow grain size distributions occurred.…”

Section: A Microstructure Characterizationmentioning

confidence: 99%

Effect of Annealing on Hardness and the Modulus of Elasticity in Bulk Nanocrystalline Nickel

Torrents

Yang

Mohamed

2010

Metall Mater Trans A

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“…A major difference between these two functions is that Lorentzian profile has flatter tails (extends for a greater deviation away from the Bragg peak) than a Gaussian distribution exhibiting an equal FWHM. The application of both the Lorentzian and Gaussian diffraction profiles is based on the experimental usefulness [22,26,27] of both these functions in describing peak broadening and not a fundamental first principles relationship with either domain size or microstrain. To improve the fitting of either (or both) the Gaussian or Lorentzian profile to peak broadening, a combination of the two profiles can be used in a Voigt function [22,25,27] (i.e., broadening due to both domain size and microstrain strain contains both a Lorentzian and Gaussian component [16,25].…”

Section: Profile Functionsmentioning

confidence: 99%

Characterization of Precipitates in a Microalloyed Steel Using Quantitative X-ray Diffraction

Wiskel

Lü²,

Omotoso

et al. 2016

Metals

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Quantitative X-ray diffraction (QXRD) (also known as the Rietveld method) was used to analyze the precipitates present in Grade 100 microalloyed steel. The precipitates were extracted from the steel using electrolytic dissolution and the residue from the dissolution was analyzed using XRD. The XRD pattern exhibited three (3) distinct diffraction peaks, and significant broadening of a fourth peak corresponding to the <10 nm size precipitates. QXRD analysis was applied to the XRD pattern to obtain precipitate size, composition, and weight fraction data for each of the four diffraction peaks observed. The predicted mean precipitate diameter and average atomic composition of the nano-size (<10 nm) precipitates was 4.7 nm and (Nb 0.50 Ti 0.32 Mo 0.18 )(C 0.59 N 0.41 ), respectively. The predicted precipitate size correlates well with the average size of precipitates measured in previous work by the authors using both transmission electron microscopy (TEM) and small angle neutron scattering (SANS). The average atomic composition correlates well with the composition measured in this work using energy dispersive X-ray (EDX) analysis of individual nano-sized precipitates. The calculated weight fraction of the nano-size precipitates in the extracted residue was 42.2 wt. %. The calculated atomic compositions of the other three diffraction peaks were TiN, (Ti 0.87 Nb 0.13 )N, and (Nb 0.82 Ti 0.18 )(C 0.87 N 0.13 ) with weight fraction values of 12.9 wt. %, 31.7 wt. %, and 13.1 wt. %, respectively. The sizes of both the (Ti 0.87 Nb 0.13 )N and the (Nb 0.82 Ti 0.18 )(C 0.87 N 0.13 ) groups of precipitates were directly measured and were observed to range from 150 nm to 570 nm and from 90 nm to 475 nm, respectively. QXRD was unable to determine a reasonable mean precipitate size for either of these two groups of precipitates. The wide compositional range (i.e., varying levels of Nb and Ti) of these precipitates (as measured by EDX) resulted in XRD peak broadening that was erroneously interpreted as a size broadening effect.

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Quantitative analysis of grain size in bimodal powders by x-ray diffraction and transmission electron microscopy

Cited by 29 publications

References 10 publications

Electrical conductivity of ceria nanoparticles under high pressure

Electrical conductivity of ceria nanoparticles under high pressure

Effect of Annealing on Hardness and the Modulus of Elasticity in Bulk Nanocrystalline Nickel

Characterization of Precipitates in a Microalloyed Steel Using Quantitative X-ray Diffraction

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