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Just posted a new Appplication Note on Dimension FastScan

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Stephen Minne Posted: Fri, Jul 8 2011 5:02 PM

Download from: AN134-RevA0-Survey_Screening-Dynamics_HighSpeed_Atomic_Force_Microscopy-AppNote (LoRes).pdf

Abstract:

When compared to other common microscopy techniques (optical, SEM, TEM), the atomic force microscope’s (AFM’s) broad potential for nanoscale imaging and characterization of numerous physical surface properties has been somewhat offset by its slow imaging speed. Thus, the AFM has sometimes been seen as a powerful “specialty tool” to use when other suitable techniques are not available.


The AFM community has spent considerable effort over the last decade looking for ways to address the speed limitation of AFMs, and through this research many of the fundamental technological challenges have been addressed on an academic scale. Driven by the researcher’s quest for discovery, many of these efforts were aimed at improving the time-resolution of the AFM in order to view dynamic processes on the nanoscale; while some also anticipated the need for the versatility and productivity of a fast general-purpose AFM.


Bruker’s Dimension FastScan™ development team worked with many AFM leaders to understand their research objectives and related enabling technologies, iteratively exploring various design considerations in the pursuit of bringing together the best of all these solutions into one tool. The ultimate result is the creation of an AFM that ideally marries high-resolution performance with rapid imaging. This application note details how the Dimension FastScan AFM accomplishes this ideal.

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Dear Stephen, thank you for good introduction to the subject. 

I have a feeling however that a confusion is still there and would appreciate more comments from you and other colleagues SPMers.

The confusion is probably coming from the word “speed”. Speed may mean rate (like in acquisition, frame or line frequency) or it may also mean velocity of a probe. Rates are related more to the XY scanner resonance frequencies while the tip velocity is defined by full system transfer function (FSTF). Rate and velocity are also interrelated through the spatial resolution defined by capability of a probe to track the profiles with required accuracy. That should probably mean that all the edge artifacts like probe “jumping”, “ringing” or “flying off” are confined within one pixel of image in the ideal case.

Would you probably agree that a term “productivity” or a similar term could describe the problem of “high-speed” AFM better? End users are probably interested in overall data acquisition rates (distribution of roughness, conductivity, dynamics of feature shapes and positions among other parameters in time, space and through a group of samples) at required accuracy (Niquest rates) in comparison to alternative techniques like SEM, TEM, LM. Remembering Niquest-Shannon sampling principles applied to the planning experiments themselves (for example, the roughness sampling can be performed on a fraction of an image, on a line in ideal case) could significantly increase the data acquisition rate too.

Automation of measurement of groups of samples is another interesting aspect where quick automatic engage of the probe to the surface from few mm distance can be performed in seconds. To my memory, this approach has been first shown on the year 2003-2004 by a group of Hans Danzebrink from PTB, Braunschweig, Germany and was based not only on acoustic but also laser confocal sensors of surfaces of unknown topology. I am missing this absolutely fabulous feature of FastScan at my present work with NanoScope E, NanoSurf and Asylum Research.

There is a number of topics that could be discussed here in application to increase of acquisition rate of AFM. Naming a few like adaptive Quality factor (applied to the whole system, not only cantilever) control, adaptive non-linear velocity scanning, fuzzy logics control and many other. May be too many to be discussed within the topic of “High-Speed AFM” and requiring cross-linking to another threads of discussions.

Thank you,

Dmitry Sokolov

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