Scanning Kelvin Force Microscopy For Characterizing Nanostructures in Atmosphere
Author(s) -
Joseph J. Kopanski,
Muhammad Y. Afridi,
Stoyan Jeliazkov,
Wencai Jiang,
Tony R. Walker,
David G. Seiler,
Alain C. Diebold,
Robert McDonald,
C. Michael Garner,
Dan Herr,
Rajinder P. Khosla,
Erik M. Secula
Publication year - 2007
Publication title -
aip conference proceedings
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.177
H-Index - 75
eISSN - 1551-7616
pISSN - 0094-243X
DOI - 10.1063/1.2799430
Subject(s) - kelvin probe force microscope , signal (programming language) , microscope , materials science , nanowire , work function , nanostructure , microscopy , image resolution , scanning probe microscopy , work (physics) , electric field , near field scanning optical microscope , resolution (logic) , nanotechnology , optics , optoelectronics , optical microscope , physics , scanning electron microscope , atomic force microscopy , computer science , layer (electronics) , quantum mechanics , artificial intelligence , thermodynamics , programming language
The Electrostatic Force Microscope (EFM) and the related Scanning Kelvin Force Microscope (SKFM) are of interest for the measurement of potential distributions within nanostructures and for work function measurements of gate metals for next generation CMOS. EFM phase mode has better spatial resolution than SKFM because its signal depends on the electric field gradient, while the SKFM's signal depends on the electric field directly. We have determined the effect of data acquisition conditions on spatial resolution and accuracy of CPD measured with SKFM in atmosphere by using various commercially available tips and a specially designed test chip containing up to four different metal layers. The test chip contains structures intended to simulate nanoparticles and nanowires in various combinations of metals. By comparison to measurements on the test structures using tips with known work functions, the effective work functions of tips with unknown work functions can be estimated. A simple computer model was de...
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