scholarly journals Effect of processing variables and bulk composition on the surface composition of spray dried powders of a model food system

2013 ◽  
Vol 118 (1) ◽  
pp. 19-30 ◽  
Author(s):  
Jim R. Jones ◽  
Dominic Prime ◽  
Mark C. Leaper ◽  
David J. Richardson ◽  
Chris D. Rielly ◽  
...  
2011 ◽  
Vol 127 (2) ◽  
pp. 669-675 ◽  
Author(s):  
Linda Monaci ◽  
Marcel Brohée ◽  
Virginie Tregoat ◽  
Arjon van Hengel

Author(s):  
Changqing Liu ◽  
David A. Hutt ◽  
Dezhi Li ◽  
Paul P. Conway

This paper aims to gain an insight into the correlation between the microstructure and surface composition of electroless Ni-P and its behaviour during soldering with Pb free alloys including Sn-3.8Ag-0.7Cu, Sn-3.5Ag and Sn-0.7Cu. Ni-P coatings with different P contents were produced through an industrial process on copper metal substrates. The surface morphology of these coatings was observed by Scanning Electron Microscopy (SEM) and the bulk composition was analyzed by means of Energy Dispersive X-ray analysis (EDX). The mechanical properties of the coatings were evaluated by nano-indentation testing under different maximum loads. However, to understand the behaviour of P in Ni-P coatings and deterioration of the coating surfaces during exposure to air, the surfaces of the coatings were also characterised by X-ray Photoelectron Spectroscopy (XPS) for storage at different temperatures. The dependence of the solderability of Ni-P coatings on the storage time and temperature was investigated by wetting balance testing, using an inactive or active flux with or without an inert N2 atmosphere. Finally, the solderability of Ni-P coatings to Pb free solders is correlated with their composition and microstructure (e.g. surface characteristics).


1998 ◽  
Vol 61 (4) ◽  
pp. 521-524 ◽  
Author(s):  
Jennifer M Ames ◽  
Aklile B Defaye ◽  
Richard G Bailey ◽  
Lisa Bates

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2182
Author(s):  
Damilola Ologunagba ◽  
Shyam Kattel

Surface chemical composition of bimetallic catalysts can differ from the bulk composition because of the segregation of the alloy components. Thus, it is very useful to know how the different components are arranged on the surface of catalysts to gain a fundamental understanding of the catalysis occurring on bimetallic surfaces. First-principles density functional theory (DFT) calculations can provide deeper insight into the surface segregation behavior and help understand the surface composition on bimetallic surfaces. However, the DFT calculations are computationally demanding and require large computing platforms. In this regard, statistical/machine learning methods provide a quick and alternative approach to study materials properties. Here, we trained previously reported surface segregation energies on low index surfaces of bimetallic catalysts using various linear and non-linear statistical methods to find a correlation between surface segregation energies and elemental properties. The results revealed that the surface segregation energies on low index bimetallic surfaces can be predicted using fundamental elemental properties.


2016 ◽  
Vol 140 ◽  
pp. 460-471 ◽  
Author(s):  
Martin Foerster ◽  
Thomas Gengenbach ◽  
Meng Wai Woo ◽  
Cordelia Selomulya

Sign in / Sign up

Export Citation Format

Share Document