Electronic linearization of piezoelectric actuators and noise budget in scanning probe microscopy

The evolution of the profile of nanometer sized water drops on a mica surface has been studied through hydration scanning probe microscopy. A time range from a few seconds down to a fraction of millisecond after the formation of the drop has been explored. This high time resolution has been obtained by sampling a series of statistically equivalent drops. This approach also avoids any probe interference during the drop evolution process.

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“…27 Other details of the instrument are reported and discussed in Ref. 28. The probes were electrochemically etched from a tungsten wire.…”

Section: Methodsmentioning

confidence: 99%

Use of scanning probe microscopy to study the evolution of nanometer sized liquid structures

Aloisi

Bacci

Carlà

et al. 2011

Review of Scientific Instruments

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“…9 Therefore, scanning probes often have problems with interference from external noise sources, which can skew results and produce surface "features" that can be misperceived as real. 10 Knowledge of the frequency of these external noise sources is crucial for finding their origin in order to eliminate noise. 11 Spectrum analyzers are very useful for the measurement of both the magnitude and frequency of noise sources in SPM images, 12,13 but in general they tend to be relatively expensive.…”

Section: Introductionmentioning

confidence: 99%

Low-cost spectrum analyzer for trouble shooting noise sources in scanning probe microscopy

McQuillan

Larson

Sykes

2020

Journal of Vacuum Science &Amp; Technology A

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Scanning probe microscopes are notoriously sensitive to many types of external and internal interference including electrical, mechanical and acoustic noise. Sometimes noise can even be misinterpreted as real features in the images. Therefore, quantification of the frequency and magnitude of any noise is key to discovering the source and eliminating it from the system. While commercial spectrum analyzers are perfect for this task, they are rather expensive and not always available. We present a simple, cost effective solution in the form of an audio output from the instrument coupled to a smart phone spectrum analyzer application. Specifically, the scanning probe signal, e.g. the tunneling current of a scanning tunneling microscope is fed to the spectrum analyzer which Fourier transforms the time domain acoustic signal into the frequency domain. When the scanning probe is in contact with the sample, but not scanning, the output is a spectrum containing both the amplitude and frequency of any periodic noise affecting the microscope itself, enabling troubleshooting to begin.

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“…8 Others have implemented methods to correct distortion Yothers, Browder, & Bumm Real-Space Distortion Correction of STM Images 3 / 38 from the piezoelectric actuators in real time, e.g. by modifying the image raster scan in the controller frame using behavioral models for the piezoelectric actuators [11][12][13][14] and the linearization of long-range hysteresis with software, 15 or by hardware linearization of the piezoelectric actuator response using charge control instead of voltage control. 16,17 All have proven effective for reducing distortion, although they can introduce new problems.…”

Section: Introductionmentioning

confidence: 99%

Real-space post-processing correction of thermal drift and piezoelectric actuator nonlinearities in scanning tunneling microscope images

Yothers

Browder

Bumm

2017

Review of Scientific Instruments

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We have developed a real-space method to correct distortion due to thermal drift and piezoelectric actuator nonlinearities on scanning tunneling microscope images using Matlab. The method uses the known structures typically present in high-resolution atomic and molecularly-resolved images as an internal standard. Each image feature (atom or molecule) is first identified in the image. The locations of each feature's nearest neighbors (NNs) are used to measure the local distortion at that location. The local distortion map across the image is simultaneously fit to our distortion model, which includes thermal drift in addition to piezoelectric actuator hysteresis and creep. The image coordinates of the features and image pixels are corrected using an inverse transform from the distortion model. We call this technique the thermal-drift, hysteresis, and creep transform (DHCT).Performing the correction in real space allows defects, domain boundaries, and step edges to be excluded with a spatial mask. Additional real-space image analyses are now possible with these corrected images. Using graphite(0001) as model system, we show lattice fitting to the corrected image, averaged unit cell images, and symmetry-averaged unit cell images.Statistical analysis of the distribution of the image features around their best-fit lattice sites measures the aggregate noise in the image, which can be expressed as feature confidence ellipsoids.

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Electronic linearization of piezoelectric actuators and noise budget in scanning probe microscopy

Cited by 8 publications

References 9 publications

Use of scanning probe microscopy to study the evolution of nanometer sized liquid structures

Use of scanning probe microscopy to study the evolution of nanometer sized liquid structures

Low-cost spectrum analyzer for trouble shooting noise sources in scanning probe microscopy

Real-space post-processing correction of thermal drift and piezoelectric actuator nonlinearities in scanning tunneling microscope images

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