The Structure of Liquid Copper-Magnesium Alloys

1973 ◽  
Vol 28 (2) ◽  
pp. 297-304
Author(s):  
W.E. Lukens ◽  
C.N.J. Wagner

X-rays (MoKα) have been used as a radiation probe to evaluate the interference functions I(K) (or structure factors) of liquid Cu, Mg and Cu-Mg alloys with 49, 66, and 86 at. % Mg at temperatures about 50°C above the liquidus. Employing the transmission technique, I(K) has been determined in the range of K = 4π sin Θ/λ between 0.8 A-1 and 12.5 A-1. All I(K) of the alloys exhibit a premaximum at K = 1.5 A-1.The partial interference functions Iij(K) have been determined, and it was found that the assumption of concentration independence of Iij(K) yielded reduced partial distribution functions Gij(r), the weighted sum of which were only in fair agreement with G(r), the Fourier transform of F(K) = K[I(K)-1].The positions, r, of the first peak in G(r) and the coordination number, η, determined from the radial distribution function 4π r2 ρ(r) = r G(r) + 4πr2 ρo, where ρo is the average atomic density of the alloy, show a negative deviation from a straight line when plotted as a function of concentration, which might be considered as evidence for the existence of short-range order in the liquid. Art. 2288

1975 ◽  
Vol 30 (2) ◽  
pp. 242-249 ◽  
Author(s):  
W. E. Lukens ◽  
C. N. J. Wagner

Abstract Mo-Kα X-rays have been used as a radiation probe to evaluate the interference functions l(K) (also called structure factors) of liquid Ag, Cu and Ag-Cu alloys with 16.5, 28, 37, 50, 57, 71 and 85 at.% Cu at temperatures about 50 °C above the liquidus. Employing the transmission technique, I(K) has been determined in the range of K = 4 π sin θ/λ between 0.8 and 12.5 Å-1. The partial interference functions Iij(K) have been calculated, and it was found that the assumption of concentration independence of Iij(K) yielded reduced partial distribution functions Gij(r), the weighted sum of which were in excellent agreement with G(r), the Fourier transform of F(K) =K[l(K)-1]. The position of the first peak in G(r) and the coordination number η show a positive deviation from a straight line when plotted as a function of concentration.


2011 ◽  
Vol 312-315 ◽  
pp. 149-153
Author(s):  
E.A. Pastukhov ◽  
N.I. Sidorov ◽  
A.A. Vostrjakov ◽  
V.P. Chentsov

Amorphous alloys Ni64Zr36 and Ni36Zr64 structure and hydrogen mobility are researched by the molecular dynamics method. The analysis of structure factors and partial distribution functions of atoms revealed hydrogen affects the short order parameters of the disordered systems. Diffusion coefficients of hydrogen are shown to depend on its concentration.


Author(s):  
W. Chiu ◽  
M.F. Schmid ◽  
T.-W. Jeng

Cryo-electron microscopy has been developed to the point where one can image thin protein crystals to 3.5 Å resolution. In our study of the crotoxin complex crystal, we can confirm this structural resolution from optical diffractograms of the low dose images. To retrieve high resolution phases from images, we have to include as many unit cells as possible in order to detect the weak signals in the Fourier transforms of the image. Hayward and Stroud proposed to superimpose multiple image areas by combining phase probability distribution functions for each reflection. The reliability of their phase determination was evaluated in terms of a crystallographic “figure of merit”. Grant and co-workers used a different procedure to enhance the signals from multiple image areas by vector summation of the complex structure factors in reciprocal space.


2020 ◽  
Vol 640 ◽  
pp. A66 ◽  
Author(s):  
S. Freund ◽  
J. Robrade ◽  
P. C. Schneider ◽  
J. H. M. M. Schmitt

Aims. We revisit the X-ray properties of the main sequence Hyades members and the relation between X-ray emission and stellar rotation. Methods. As an input catalog for Hyades members, we combined three recent Hyades membership lists derived from Gaia DR2 data that include the Hyades core and its tidal tails. We searched for X-ray detections of the main sequence Hyades members in the ROSAT all-sky survey, and pointings from ROSAT, the Chandra X-Ray Observatory, and XMM-Newton. Furthermore, we adopted rotation periods derived from Kepler’s K2 mission and other resources. Results. We find an X-ray detection for 281 of 1066 bona fide main sequence Hyades members and provide statistical upper limits for the undetected sources. The majority of the X-ray detected stars are located in the Hyades core because of its generally smaller distance to the Sun. F- and G-type stars have the highest detection fraction (72%), while K- and M-type dwarfs have lower detection rates (22%). The X-ray luminosities of the detected members range from ∼2 × 1027 erg s−1 for late M-type dwarfs to ∼2 × 1030 erg s−1 for active binaries. The X-ray luminosity distribution functions formally differ for the members in the core and tidal tails, which is likely caused by a larger fraction of field stars in our Hyades tails sample. Compared to previous studies, our sample is slightly fainter in X-rays due to differences in the Hyades membership list used; furthermore, we extend the X-ray luminosity distribution to fainter luminosities. The X-ray activity of F- and G-type stars is well defined at FX/Fbol ≈ 10−5. The fractional X-ray luminosity and its spread increases to later spectral types reaching the saturation limit (FX/Fbol ≈ 10−3) for members later than spectral type M3. Confirming previous results, the X-ray flux varies by less than a factor of three between epochs for the 104 Hyades members with multiple epoch data, significantly less than expected from solar-like activity cycles. Rotation periods are found for 204 Hyades members, with about half of them being detected in X-rays. The activity-rotation relation derived for the coeval Hyades members has properties very similar to those obtained by other authors investigating stars of different ages.


Author(s):  
Carmelo Giacovazzo

The title of this chapter may seem a little strange; it relates Fourier syntheses, an algebraic method for calculating electron densities, to the joint probability distribution functions of structure factors, which are devoted to the probabilistic estimate of s.i.s and s.s.s. We will see that the two topics are strictly related, and that optimization of the Fourier syntheses requires previous knowledge and the use of joint probability distributions. The distributions used in Chapters 4 to 6 are able to estimate s.i. or s.s. by exploiting the information contained in the experimental diffraction moduli of the target structure (the structure one wants to phase). An important tool for such distributions are the theories of neighbourhoods and of representations, which allow us to arrange, for each invariant or seminvariant Φ, the set of amplitudes in a sequence of shells, each contained within the subsequent shell, with the property that any s.i. or s.s. may be estimated via the magnitudes constituting any shell. The resulting conditional distributions were of the type, . . . P(Φ| {R}), (7.1) . . . where {R} represents the chosen phasing shell for the observed magnitudes. The more information contained within the set of observed moduli {R}, the better will be the Φ estimate. By definition, conditional distributions (7.1) cannot change during the phasing process because prior information (i.e. the observed moduli) does not change; equation (7.1) maintains the same identical algebraic form. However, during any phasing process, various model structures progressively become available, with different degrees of correlation with the target structure. Such models are a source of supplementary information (e.g. the current model phases) which, in principle, can be exploited during the phasing procedure. If this observation is accepted, the method of joint probability distribution, as described so far, should be suitably modified. In a symbolic way, we should look for deriving conditional distributions . . . P (Φ| {R}, {Rp}) , (7.2) . . . rather than (7.1), where {Rp} represents a suitable subset of the amplitudes of the model structure factors. Such an approach modifies the traditional phasing strategy described in the preceding chapters; indeed, the set {Rp} will change during the phasing process in conjunction with the model changes, which will continuously modify the probabilities (7.2).


Author(s):  
Timma O Uwah ◽  
Ekaete I Akpabio ◽  
Daniel E Ekpa ◽  
Akwaowo E. Akpabio ◽  
Jacob Godwin

Objective: This work focused on evaluating the micromeritic and compressional properties of pregelatinized African water yam (Discorea alata) starch and its modified forms with comparison to pregelatinized corn starch and microcrystalline cellulose.Methods: Two modifications of the water yam starch were prepared; acetone dehydrated pregelatinized form (DSA) and an admixture of DSA and pregelatinized corn starch (CDSA). A third form of starch is the acetone dehydrated pregelatinized corn starch (CSA). These were used to form batches compacted as tablets using diclofenac sodium as the active moiety. Physicochemical and flow characteristics of the starch powders were elucidated, and the drug starch compatibility studies done using the Fourier transform Infra-red (FTIR) technique. Compaction studies were investigated on tablets formed at different compression pressures and Heckel plots were prepared.Results: The slope of the straight line (K) of 0.8959 was greatest for F1 while yield pressure (Py) value of 10.965 was highest for F3. These values from the Heckel plot suggest that while the tablets of control batch of microcrystalline cellulose (F4) and a batch of pregelatinized corn starch (F2) formed harder compacts, less likely deformed plastically, the Discorea alata batch (F1) and the admixed batch (F3) were likely to deform plastically. Also, the binding efficiency of the compact was significantly high (47.81%Kgscm-1) for F4 at 56.5Kpas compaction pressure, higher than that obtainable for any of the other formulations at the compaction pressures under consideration. All starches formed had similar moisture content (of 10%) despite the different sources but the interaction between the water molecule and pregelatinized water yam starch improved as revealed by viscosity(7.18mPas), hydration capacity(3.27%) and swelling index (250%) of CDSA.Conclusion: It could be concluded that pregelatinized water yam starch could be used as a substitute for corn starch or microcrystalline cellulose as a pharmaceutical excipient (binder/filler) in tablets formulation.


1971 ◽  
Vol 11 (01) ◽  
pp. 23-37 ◽  
Author(s):  
C. Petrauskas ◽  
P.M. Aagaard

Abstract An improved method is presented for selecting offshore structure design waves by extrapolating historical storm data to obtain extreme value statistics. The method permits flexibility in choice of distribution functions through use of computerized procedures, estimates extrapolated wave-height procedures, estimates extrapolated wave-height uncertainty due to small sample size, and includes criteria for judging whether or not given wave-height values can be represented by one or more of the distributions implemented in the method. The relevance of uncertainty to selection of design-wave heights is discussed and illustrated. Introduction The problem of selecting design-wave heights for offshore platforms has many facets, ranging from the development of oceanographic data to the selection of the prudent level of engineering risk for a particular installation. This paper deals only with part of the problem; it describes an improved method for using the small available amount of wave-height information to estimate the extreme value statistics and associated uncertainties for the large storm waves that have a very low probability of occurrence. probability of occurrence. Hindcast wave-height information for design-wave studies usually covers a period of historical record that is shorter than the return period selected for acceptable engineering risk. Return periods commonly used for selection design waves are 100 years or more, but good meteorological data, on Which the calculated wave heights are based, can rarely be obtained for periods covering more than 50 to 60 years. As a consequence, extrapolations to longer return periods are necessary. Present methods for making the extrapolation employ probablistic models through the use of special probability graph papers on which a family of distribution functions plot as straight lines. The wave heights are plotted vs their "plotting-position" return period, and a straight line fitted to the plotted data is extended beyond the data to estimate extreme wave heights for return periods of interest. The methods are described in periods of interest. The methods are described in numerous technical papers and books; Refs. 1 through 5 are examples. The shortcomings of the present commonly used methods are:the straight line drawn through the data is in most cases visually fit to the data, thus is subject to error; andno information is available on the uncertainty of the resulting extrapolation. These shortcomings have been discussed by many authors and many of their concepts influenced this study. The improved method presented in this paper offers:greater flexibility in the choice of distributions through computerized procedures,guidelines for picking the "best" distribution from several implemented in the method, andprocedures for estimating the uncertainty of procedures for estimating the uncertainty of extrapolated wave heights. CONDENSED CONCLUSIONS Procedures described in this paper for extrapolating hindcast storm-wave heights and estimating uncertainty intervals to the extrapolated values are recommended as aids in selecting the design-wave height. The results of the extrapolating procedure and related uncertainty considerations procedure and related uncertainty considerations are only aids to help the engineer assess the risks associated with his design. The actual selection of the design-wave height is a matter of engineering judgment. The choice is subjective and will vary according to the risk chosen for the design. Further consideration of ways to decrease the span of be uncertainty intervals is warranted. Increasing the number of years represented in the sample along with the number of storms is a direct way to decrease the span. In the areas of the world having poor weather records the sample size will be marginal for many years to come. SPEJ P. 23


2010 ◽  
Vol 43 (3) ◽  
pp. 635-638 ◽  
Author(s):  
Caroline Wurden ◽  
Katharine Page ◽  
Anna Llobet ◽  
Claire E. White ◽  
Thomas Proffen

Differently weighted experimental scattering data have been used to extract partial or differential structure factors or pair distribution functions in studying many materials. However, this is not done routinely partly because of the lack of user-friendly software. This paper presentsMIXSCAT, a new member of theDISCUSprogram package.MIXSCATallows one to combine neutron and X-ray pair distribution functions and extract their respective differential functions.


1989 ◽  
Vol 33 ◽  
pp. 397-402 ◽  
Author(s):  
Shin'ichi Ohya ◽  
Yasuo Yoshioka

When an x-ray diffraction profile Is measured for stress analysis or profile analysis by the use of a linear (straight line) position sensitive proportional counter (PSPC) , a convex-type background line is obtained because of the geometrical problem and the absorption of x-rays. Such phenomenon is remarkable when a wide angular range is set on a linear PSPC and it is, in particular, necessary to correct with a straight background for accurate measurement of diffraction angle or half-value breadth of the broadened diffraction profile.


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