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The central assumption is that adsorption at the aluminosilicate surface is mainly related to the presence of extra-framework cations and, as a consequence, the activation barrier for cation displacement, measured from DRS, identifies the surface energy landscape.
Recently, we showed that the GNM identifies the surface residues that are suitable binding sites [30], [31], [32].
Second, there is no high-coverage dataset available that identifies the surface proteins that are dysregulated and are involved in type 1 and type 2 diabetes.
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They were used to identify the surface damage evolution.
The colour spectrum of RGB format was applied to identify the surface images of the parts.
For bottom gate devices we identify the surface energy of the gate dielectric to predominantly dictate the device mobility.
Our approach of identifying the surface location of residues is relevant to other planar supramolecular protein assemblies.
Microstructure observation was performed using an atomic force microscope (AFM) to identify the surface roughness related to the adhesion properties.
X-ray photoelectron spectroscopy analysis was applied to identify the surface chemical changes due to the reduction processes.
The XPS spectra of Ni12P5 samples were measured to identify the surface chemical composition and valence states.
A library of polymeric SPE materials with different surface functionalities was screened for PEth extraction in order to identify the surface characteristics that control PEth retention and recovery.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com