scholarly journals Influence of the elastic deformations on the form factor of polyhedral nanocrystals: the illustrative example of the pseudomorphic inclusion

2019 ◽  
Vol 52 (2) ◽  
pp. 387-393
Author(s):  
Bernard Croset
Keyword(s):  
Form Factor ◽  
Control Parameter ◽  
Crystal Shape ◽  
Total Amplitude ◽  
Elastic Deformations ◽  
Complex Density ◽  
Asymptotic Behaviours ◽  
Strong Contrast

Using an analytically tractable example, the pseudomorphic inclusion, this article examines the influence of elastic deformations on the form factor of polyhedral nanocrystals. A control parameter, the total amplitude of the variation of the complex density phase, is identified and it is shown that for low enough deformations the characteristic asymptotic behaviours as a function of the scattering vector associated with the polyhedral crystal shape are preserved, leading to a strong contrast in the dependence of the form factor on orientation. Using the sections method, it is explained why these results can be generalized to more realistic elastic situations.

The effect of temperature on high-resolution TEM image contrast

1995 ◽  
Vol 53 ◽  
pp. 640-641
Author(s):  
T. Geipel ◽  
W. Mader ◽  
P. Pirouz
Keyword(s):  
Form Factor ◽  
Inelastic Scattering ◽  
Accurate Method ◽  
Waller Factor ◽  
Effect Of Temperature ◽  
Specimen Thickness ◽  
Influence Of Temperature ◽  
Debye Waller Factor ◽  
Influence Of Temperature On ◽  
Atomic Form Factor

Temperature affects both elastic and inelastic scattering of electrons in a crystal. The Debye-Waller factor, B, describes the influence of temperature on the elastic scattering of electrons, whereas the imaginary part of the (complex) atomic form factor, fc = fr + ifi, describes the influence of temperature on the inelastic scattering of electrons (i.e. absorption). In HRTEM simulations, two possible ways to include absorption are: (i) an approximate method in which absorption is described by a phenomenological constant, μ, i.e. fi; - μfr, with the real part of the atomic form factor, fr, obtained from Hartree-Fock calculations, (ii) a more accurate method in which the absorptive components, fi of the atomic form factor are explicitly calculated. In this contribution, the inclusion of both the Debye-Waller factor and absorption on HRTEM images of a (Oll)-oriented GaAs crystal are presented (using the EMS software.Fig. 1 shows the the amplitudes and phases of the dominant 111 beams as a function of the specimen thickness, t, for the cases when μ = 0 (i.e. no absorption, solid line) and μ = 0.1 (with absorption, dashed line).

Crystal Shape, Size Distinguish Types of Gout

2007 ◽  
Vol 37 (20) ◽  
pp. 39
Author(s):  
DIANA MAHONEY
Keyword(s):  
Crystal Shape

Cu-AI based single crystal shape memory actuators and drives

2003 ◽  
Vol 112 ◽  
pp. 1181-1184 ◽  
Author(s):  
I. Vahhi ◽  
S. Pulnev ◽  
A. Priadko
Keyword(s):  
Single Crystal ◽  
Shape Memory ◽  
Crystal Shape ◽  
Shape Memory Actuators

MAGNETIC FORM FACTOR MEASUREMENTS IN CERIUM HEXABORIDE

1982 ◽  
Vol 43 (C7) ◽  
pp. C7-273-C7-278 ◽  
Author(s):  
P. Burlet ◽  
J. X. Boucherle ◽  
J. Rossat-Mignod ◽  
J. W. Cable ◽  
W. C. Koehler ◽  
...  
Keyword(s):  
Form Factor ◽  
Magnetic Form Factor

FORM FACTOR MEASUREMENTS IN CeTe

1982 ◽  
Vol 43 (C7) ◽  
pp. C7-263-C7-271 ◽  
Author(s):  
J. X. Boucherle ◽  
D. Ravot ◽  
J. Schweizer
Keyword(s):  
Form Factor

FORM FACTOR MEASUREMENT IN FERROMAGNETIC COBALT ORTHOVANADATE

1982 ◽  
Vol 43 (C7) ◽  
pp. C7-253-C7-256
Author(s):  
H. Fuess ◽  
R. Müller ◽  
D. Schwabe ◽  
F. Tasset
Keyword(s):  
Form Factor ◽  
Factor Measurement ◽  
Ferromagnetic Cobalt

Interference mitigation in point to point wireless sensor networks using LSP protocol and time division multiplexing approach

2020 ◽  
Vol 39 (4) ◽  
pp. 5449-5458
Author(s):  
A. Arokiaraj Jovith ◽  
S.V. Kasmir Raja ◽  
A. Razia Sulthana
Keyword(s):  
Energy Consumption ◽  
Large Scale ◽  
Control Parameter ◽  
Interference Mitigation ◽  
Wireless Sensor ◽  
Point To Point ◽  
A Minor ◽  
Two Stages ◽  
Time Division ◽  
And Control

Interference in Wireless Sensor Network (WSN) predominantly affects the performance of the WSN. Energy consumption in WSN is one of the greatest concerns in the current generation. This work presents an approach for interference measurement and interference mitigation in point to point network. The nodes are distributed in the network and interference is measured by grouping the nodes in the region of a specific diameter. Hence this approach is scalable and isextended to large scale WSN. Interference is measured in two stages. In the first stage, interference is overcome by allocating time slots to the node stations in Time Division Multiple Access (TDMA) fashion. The node area is split into larger regions and smaller regions. The time slots are allocated to smaller regions in TDMA fashion. A TDMA based time slot allocation algorithm is proposed in this paper to enable reuse of timeslots with minimal interference between smaller regions. In the second stage, the network density and control parameter is introduced to reduce interference in a minor level within smaller node regions. The algorithm issimulated and the system is tested with varying control parameter. The node-level interference and the energy dissipation at nodes are captured by varying the node density of the network. The results indicate that the proposed approach measures the interference and mitigates with minimal energy consumption at nodes and with less overhead transmission.

Effects of Process Parameters on Surface Roughness and MRR in the hard turning of EN 36 steel

2018 ◽  
pp. 102-110
Author(s):  
Amritpal Singh ◽  
Rakesh Kumar
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Hard Turning ◽  
Control Parameter ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Dry Cutting

In the present study, Experimental investigation of the effects of various cutting parameters on the response parameters in the hard turning of EN36 steel under the dry cutting condition is done. The input control parameters selected for the present work was the cutting speed, feed and depth of cut. The objective of the present work is to minimize the surface roughness to obtain better surface finish and maximization of material removal rate for better productivity. The design of experiments was done with the help of Taguchi L9 orthogonal array. Analysis of variance (ANOVA) was used to find out the significance of the input parameters on the response parameters. Percentage contribution for each control parameter was calculated using ANOVA with 95 % confidence value. From results, it was observed that feed is the most significant factor for surface roughness and the depth of cut is the most significant control parameter for Material removal rate.

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