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Active Control of Acoustics-caused Nano-Vibration in Atomic Force Microscope Imaging
Abstract
In this paper, we propose a finite-impulse-response (FIR)-based feedforward control approach to mitigate the acoustic-caused probe vibration during atomic force microscope (AFM) imaging. Compensation for the acoustic-caused probe vibration is important, as environmental disturbances including acoustic noise induce nano-scale probe vibration, directly affecting the AFM performance in applications such as imaging, nanomechanical characterization, and nanomanipulation. Although conventional passive noise cancellation apparatus has been employed, limitation exists, and residual noise still persists. Thus, a FIR-based active feedforward control approach is developed, by exploring a data-driven approach to account for the vibrational dynamics of the probe caused by the environmental acoustic noise in the controller design. An experimental implementation in AFM imaging application is presented and discussed to illustrate the proposed technique. Experimental results show that the FIR-based feedforward control is promising to not only complement, but also alleviate the limitations of passive noise control in AFM operations.
... However, glitch noise is more difficult to remove than slope noise because the former requires nonrigid registration for correction. Yi et al. [18] developed a finite impulse responsebased feedforward control approach to mitigate acoustic-caused probe vibration during AFM imaging. Jones et al. [14] presented a nonrigid registration method based on the gradient descent technique. ...
... Based on the WT, Mallat [24] proposed a multiresolution analysis, presented in [18], where a scaling function φ(x) was introduced. Fast calculation and visualization of discrete dyadic wavelet decomposition were achieved. ...
In advanced integrated circuit manufacturing processes, the quality of chemical mechanical flattening is a key factor affecting chip performance and yield. Therefore, it has become increasingly important to develop an accurate predictive model for the chip surface topography after chemical mechanical flattening. In the modeling process, the noise problem of atomic force microscopy measurement data is relatively serious. To solve this problem, the noise characteristics of atomic force microscope measurement data for chip surface topography in this field are studied and discussed in this paper. It is found that the noise present in such problems is mainly triggered by the vibration and tilt of the probe. Two types of noise, low-frequency and high-frequency, are presented in the time domain. In order to solve the noise problem in this modeling data, this paper analyzes the spectral characteristics of the measurement data using Fourier transform, and a wavelet-Fourier transform composite noise reduction process is proposed. The algorithm is applied to the noise reduction of the chip surface data of 32 nm copper interconnect process. The noise reduction results were compared with scanning electron microscope photographs to verify the effectiveness of the noise reduction.
... However, in the cases where knowledge of the interference origin can be determined, feedforward methods can be used to counteract their effects. Inversion methods can be used on models of the disturbance phenomena, such as coupling in multi-axis applications (Tien et al. 2005) or acoustic sources (Yi et al. 2018). The feedforward effort can be precomputed for repetitive errors, such as through ILC (Wu et al. 2009), or implemented in real time with finite impulse response representations. ...
This chapter discusses mechanical design techniques and control approaches that can be used to achieve high speed and fine precision control of micro-and nanoscale positioning systems. By carefully using these design considerations, undesirable effects such as thermal drift, mechanical resonances, and off-axis motion can be minimized. Additionally, control systems can be designed to improve the positioning capabilities in open-loop and closed-loop configurations, allowing for high-bandwidth motion control while minimizing nonlinearities, such as hysteresis, and detrimental external disturbances.
... On the other hand, it is feasible to design advanced algorithms, including strong robust controllers, optimized scanning strategies and improved imaging algorithms, to compensate for vertical drift in real time to achieve high quality imaging. For instance, Yi et al. (2018) proposes a finite-impulse-response-based feedforward control approach to mitigate acoustic-caused probe vibration during AFM imaging. Moreover, Marinello et al. (2007) designs a surface correction algorithm based on two topographies taken with mutually orthogonal scanning directions to construct accurate AFM images of three-dimensional surface topographies. ...
The atomic force microscope (AFM) has become a powerful tool in many fields. However, environmental noise and other disturbances are very likely to cause the AFM probe to vibrate, which lead to vertical drift in AFM imaging and limit its further application. Therefore, to correct image distortion caused by vertical drift, a morphology prediction based image correction algorithm is proposed in this paper. Specifically, a Gaussian–Hann filter is first designed for distorted AFM images, based on which, an adaptive image binarization algorithm is developed to achieve accurate object detection and background extraction. Furthermore, an advanced morphology prediction algorithm, consisting of morphological approximation prediction and morphological detail prediction, is proposed to correct image distortion by using the extracted substrate of a sample image. Approximate morphology is generated by an improved weighted fusion autoregressive model, and morphological detail is obtained by energy analysis based on discrete wavelet transform. Experimental and application results are presented to illustrate that the proposed algorithm is able to effectively eliminate vertical drift of AFM images.
... The nanometer scale displacement has several applications including nano-positioning, microsystems technology, semiconductors, microscopes and precision machining [1][2][3][4][5]. Although the embedded sensor is recognized as a common way to increase the accuracy of nano-displacement, it is impossible to select a miniaturized sensor with fast response rate resistance to environmental vibration noise [6]. ...
Self-sensing feature allows an actuator to be used as a sensor. Magnetoelectric (ME) composites consist of piezoelectric and magnetostrictive layers. ME composite is a proper candidate for the self-sensing feature in a wireless actuator due to its concurrent magnetic-charge order. In this study, the self-sensing feature of a nano-displacement ME actuator is investigated. The ME structure design, as well as the effect of geometric parameter and resonance frequency on the ME signal, is evaluated using a numerical modeling. The Metglas/PMN-PT/Metglas composite was fabricated as an ME actuator. The displacement measurement was conducted using a laser Doppler. The effect of bias field and excitation frequency on sensitivity, linearity, resolution and signal stability of actuator/sensor feature were evaluated by a magnetoelectric measurement setup. The experimental results revealed that the maximum sensitivity of actuator was achieved at the resonance frequency of about 60.7 kHz. Compared to the ME voltage, the phase angle was more reliable for application in the self-sensing feature. The actuator/sensor sensitivity was estimated at about 5.2 nm/mA and 0.64 mV/mA, respectively. Also, the output range of the sensoric feature was measured at 58–272 mV. The fatigue test revealed that the ME signal at the first resonance frequency was more stable than the second mode. The results also confirmed that the magnetoelectric signal could be promising candidate for the self-sensing feature in the ultrasonic nano-displacement actuator.
... applications [10]. One solution to these challenges (even in the single-actuator case) is to incorporate a control strategy that is robust to these nonlinearities and external disturbances [6], [11]. ...
This paper presents an imaging mode of atomic force microscope (AFM) that is robust to the environmental acoustic noise. AFM operations are sensitive to external disturbances including acoustic noise, as disturbances to the probe-sample interaction directly results in distortions in the sample images obtained. Although conventionally passive noise cancellation has been employed, the passive-noise apparatus limits the function of AFM and its use in emerging applications. Moreover, residual noise still persists. In this work, we propose a noise rejection mode (NRM) of AFM imaging to avoid and eliminate the acoustic-caused disturbance to the imaging process. Contrary to other existing AFM imaging modes, in the proposed NRM approach, the set-point of the feedback loop for tracking the sample topography is adjusted online such that the AFM system is insensitive and thereby, robust to the environmental noise. Then, a feedforward controller is augmented to counter act the noise-caused vibration in the feedback loop. Both the set-point adjustment and the feedforward noise cancellation are implemented through finite-impulse-response (FIR) filters. Experimental examples are presented and discussed to illustrate the proposed technique.
In this paper, we present a hybrid adaptive feedforward and feedback controller with hysteresis compensator on a magnetostrictive-actuated multi degree of freedom (DOF) positioning and vibration isolation integrated system (PVIIS). The PVIIS is custom-developed and based on “cubic” Stewart configuration. It is challenging to develop an effective controller to systematically address the issues of cross-coupling, strut hysteresis and dynamics for the PVIIS. Magnetostrictive asymmetric hysteresis leads to the loss of closed-loop output performance with conventional linear controller. To this end, a novel comprehensive controller is proposed in this paper. With the inverse kinematics analysis, the spatial motion of the mobile plate of the PVIIS is decoupled into the independent motions of six actuator struts. As for controlling the single strut of the PVIIS, the hybrid adaptive feedforward (AFF) and proportional–integral–derivative (PID) feedback controller with asymmetric hysteresis compensator (HC) is constructed. Among them, the AFF sub-controller is characterized by an adaptive finite impulse response (FIR) filter whose coefficients are updated by normalized least-mean squares (NLMS) algorithm. The PID feedback sub-controller is introduced to enhance the ability of positioning and vibration isolation. The arctangent-polynomial modified Prandtl–Ishlinskii (APMPI) model is used to build the inversion-based asymmetric hysteresis compensator. The experimental set-up is built. The positioning and vibration isolation experiments are conducted. Experimental studies show that the output performances are best with the proposed controller compared against sole AFF, hybrid AFF and PID controllers. With the proposed controller, the relative positioning error can maintain around 2.83% when the PVIIS performs 2-DOF rotation in the presence of 0.5 Hz disturbance.
This paper presents a post-filtering approach to eliminate distortions of atomic force microscope (AFM) images caused by acoustic noise from an unknown location. AFM operations are sensitive to external disturbances including acoustic noise as disturbances to the probe-sample interaction directly results in distortions in the sample images obtained. Although conventional passive noise cancellation has been employed, limitation exists and residual noise still persists. Advanced online control techniques face difficulty in capturing the complex noise dynamic and limited system bandwidth imposed by the robustness requirement. In this work, we propose a dynamics-based optimal filtering technique to remove the acoustic-caused distortions in AFM images. A dictionary-approach is integrated with time-delay measurement to localize the noise source and estimate the corresponding acoustic dynamics. Then a noise-to-image coherence minimization approach is proposed to minimize the acoustic-caused image distortion via a gradient-based optimization to seek an optimal modulator to the acoustic dynamics. Finally, the filter is obtained as the finite-impulse response of the optimized acoustic dynamics. Experimental implementation is presented and discussed to illustrate the proposed technique.
Thanks to the ability to perform imaging and manipulation at the nanoscale, atomic force microscopy (AFM) has been widely used in biology, materials, chemistry, and other fields. However, as common error sources, vertical drift and illusory slope severely impair AFM imaging quality. To address this issue, this paper proposes a robust algorithm to synchronously correct the image distortion caused by vertical drift and slope, thus achieving accurate morphology characterization. Specifically, to eliminate the damage of abnormal points and feature areas on the correction accuracy, the laser spot voltage error acquired in the AFM scanning process is first utilized to preprocess the morphology height data of the sample, so as to obtain the refined alternative data suitable for line fitting. Subsequently, this paper proposes a novel line fitting algorithm based on sparse sample consensus, which accurately simulates vertical drift and slope in the cross-sectional profile of the topographic image, thereby achieving effective correction of the image distortion. In the experiments and applications, a nanoscale optical grating sample and a biological cell sample are adopted to perform topography imaging and distortion correction, so as to verify the ability of the proposed algorithm to promote AFM imaging quality.
To shorten the scanning time by focusing on the local scanning for such specimens as cells, this paper proposes an advanced scanning strategy based on autonomous exploration, so as to detect the specimen in real time and achieve fast imaging for an atomic force microscopy (AFM). More specifically, fast raster scanning is first performed to locate the initial boundary point of the specimen. On this basis, a boundary tracking algorithm is proposed to construct the internal boundary of the specimen online through the autonomous exploration of the probe. Afterwards, the boundary is expanded according to the internal boundary tracking direction, based on which a convex hull of the specimen is further constructed for the local scanning. Furthermore, the local slow scanning is performed for the specimen according to the generated scanning trajectory. Subsequently, unscanned areas in the sample can also be scanned by this autonomous method. Experimental results verify that the proposed method can achieve fast scanning while ensuring high-quality imaging.
An atomic force microscopy (AFM) generally relies on a raster scanning method to obtain the sample morphology, which limits its scanning speed and application prospect. To solve this issue, this paper proposes an optimized scanning based fast imaging method to improve the scanning speed of the AFM system. More precisely, a class of novel tracking signals is constructed to achieve smooth scanning, for which the effect of the parameters is analyzed to provide a basis for trajectory optimization. The scanning performance of the proposed method is evaluated from such aspects as scanning uniformity, scanning coverage, scanning/imaging time, and imaging quality, wherein, the scanning uniformity is analyzed with Hopkins statistic, while the scanning coverage is studied with the logistic regression. Based on these evaluation indexes, the scanning performance is investigated to determine the scanning parameters and generate the optimized trajectory. Moreover, a 3-nearest neighbor interpolation method is proposed to deal with the difficulty involved with nonlinear sampling imaging, which facilitates to reconstruct images with satisfactory quality. Finally, multiple convincing experiments and applications are implemented to further verify the good performance of the proposed method.
For high-resolution imaging without bulky external vibration isolation, this paper presents an atomic force microscope (AFM) capable of vibration isolation with its internal Z-axis (vertical) actuators moving the AFM probe. Lorentz actuators (voice coil actuators) are used for the Z-axis actuation, and flexures guiding the motion are designed to have a low stiffness between the mover and the base. The low stiffness enables a large Z-axis actuation of more than 700 um and mechanically isolates the probe from floor vibrations at high frequencies. To reject the residual vibrations, the probe tracks the sample by using a displacement sensor for feedback control. Unlike conventional AFMs, the Z-axis actuation attains a closed-loop control bandwidth that is 35 times higher than the first mechanical resonant frequency. The closed-loop AFM system has robustness against the flexures' nonlinearity and uses the first resonance for better sample tracking. For further improvement, feedforward control with a vibration sensor is combined, and the resulting system rejects 98.4% of vibrations by turning on the controllers. The AFM system is demonstrated by successful AFM imaging in a vibrational environment.
Structural vibrations is a major cause for noise problems, discomfort and mechanical failures in aerospace, automotive and marine systems, which are mainly composed of plate-like structures. In order to reduce structural vibrations on these structures, active vibration control (AVC) is an effective approach. Adaptive filtering methodologies are preferred in AVC due to their ability to adjust themselves for varying dynamics of the structure during the operation. The filtered-X LMS (FXLMS) algorithm is a simple adaptive filtering algorithm widely implemented in active control applications. Proper implementation of FXLMS requires availability of a reference signal to mimic the disturbance and model of the dynamics between the control actuator and the error sensor, namely the secondary path. However, the controller output could interfere with the reference signal and the secondary path dynamics may change during the operation. This interference problem can be resolved by using an infinite impulse response (IIR) filter which considers feedback of the one or more previous control signals to the controller output and the changing secondary path dynamics can be updated using an online modeling technique. In this paper, IIR filtering based filtered-U LMS (FULMS) controller is combined with online secondary path modeling algorithm to suppress the vibrations of a plate-like structure. The results are validated through numerical and experimental studies. The results show that the FULMS with online secondary path modeling approach has more vibration rejection capabilities with higher convergence rate than the FXLMS counterpart.
This article studies dynamic characteristics of the optical table vibration isolation system with quazi – zero stiffness isolators. A numerical model of honeycomb optical table is developed and its deflections subjected to point load are calculated as well as eigenmodes and eigenfrequencies. Modal analysis is performed by means of MSC Patran/Nastran. Numerical model of the optical table is verified by comparing the frequency of its free oscillations and full-scale models. Dynamic analysis is performed due to the base kinematic excitation of different origin and the amplitudes of forced oscillations of the surface of the table with the equipment placed are determined. Amplitudes of forced oscillations are then compared to the regulatory values given by vibration criteria for precision equipment.
For a piezoelectric tube scanner (PTS), this paper proposes an improved direct inverse tracking control algorithm and apply it to an atomic force microscope (AFM) to accomplish high-speed scanning tasks. That is, to enhance the high-speed tracking control performance of a PTS, an improved direct inverse rate-dependent Prandtl-Ishlinskii (P-I) model is firstly constructed, which includes a polynomial module to eliminate the structure nonlinearity. Based on the model, a practical feedforward control law is then designed to implement high-speed tracking control for a high-frequency trajectory with strong robustness, which presents the advantages of high-speed response, simple structure and convenient implementation. Subsequently, the designed feedforward law is combined with a feedback component, and the combined control strategy is employed in an AFM to accomplish fast imaging tasks. Numerous experimental results are then collected, which convincingly demonstrate the superior performance of the proposed practical model/control scheme.
In this paper, an imaging mode (called the adaptive multiloop mode) of atomic force microscope (AFM) is proposed to substantially increase the speed of tapping mode (TM) imaging while preserving the advantages of TM imaging over contact mode (CM) imaging. Due to its superior image quality and less sample disturbances over CM imaging, particularly for soft materials such as polymers, TM imaging is currently the most widely used imaging technique. The speed of TM imaging, however, is substantially (over an order of magnitude) lower than that of CM imaging, becoming the major bottleneck of this technique. Increasing the speed of TM imaging is challenging as a stable probe tapping on the sample surface must be maintained to preserve the image quality, whereas the probe tapping is rather sensitive to the sample topography variation. As a result, the increase of imaging speed can quickly lead to loss of the probe-sample contact and/or annihilation of the probe tapping, resulting in image distortion and/or sample deformation. The proposed adaptive multiloop mode (AMLM) imaging overcomes these limitations of TM imaging through the following three efforts integrated together: First, it is proposed to account for the variation of the TM deflection when quantifying the sample topography; second, an inner-outer feedback control loop to regulate the TM deflection is added on top of the tapping-feedback control loop to improve the sample topography tracking; and, third, an online iterative feedforward controller is augmented to the whole control system to further enhance the topography tracking, where the next-line sample topography is predicted and utilized to reduce the tracking error. The added feedback regulation of the TM deflection ensures the probe-sample interaction force remains near the minimum for maintaining a stable probe-sample interaction. The proposed AMLM imaging is tested and demonstrated by imaging a poly(tert-butyl acrylate) sample in experiments. The experimental results demonstrate that the image quality achieved by using the proposed AMLM imaging at a scan rate of 25 Hz and over a large-size imaging (50 μm×25 μm) is at the same level of that obtained using TM imaging at 1 Hz, while the probe-sample interaction force is noticeably reduced from that achieved using TM imaging at 2.5 Hz.
In this paper, an adaptive contact-mode imaging approach is proposed to replace the traditional contact-mode imaging by addressing the major concerns in both the speed and the force exerted to the sample. The speed of the traditional contact-mode imaging is largely limited by the need to maintain precision tracking of the sample topography over the entire imaged sample surface, while large image distortion and excessive probe-sample interaction force occur during high-speed imaging. In this work, first, the image distortion caused by the topography tracking error is accounted for in the topography quantification. Second, the quantified sample topography is utilized in a gradient-based optimization method to adjust the cantilever deflection set-point for each scanline closely around the minimal level needed for maintaining stable probe-sample contact, and a data-driven iterative feedforward control that utilizes a prediction of the next-line topography is integrated to the topography feeedback loop to enhance the sample topography tracking. The proposed approach is demonstrated and evaluated through imaging a calibration sample of square pitches at both high speeds (e.g., scan rate of 75 Hz and 130 Hz) and large sizes (e.g., scan size of 30 μm and 80 μm). The experimental results show that compared to the traditional constant-force contact-mode imaging, the imaging speed can be increased by over 30 folds (with the scanning speed at 13 mm/s), and the probe-sample interaction force can be reduced by more than 15% while maintaining the same image quality.
This paper presents a control-based approach to accurately quantify the indentation in broadband nanomechanical property measurements using scanning probe microscope (SPM). Accurate indentation measurement is essential to probe-based material property characterization as the force exerted and the indentation generated are the two most important physical variables measured in the process. Large measurement errors, however, occur when the measurement frequency range becomes large (i.e., broadband). Such errors result from the inability of the conventional method to account for the difference between the SPM z-axis piezo actuator displacement and the vertical displacement of the cantilever at its fixed end, and the lateral-vertical coupling-caused cantilever motion when the measurement frequency range increases. A control-based approach is presented to address these limits of the conventional method. The proposed approach is demonstrated through experiments to measure the viscoelastic properties of a Polydimethylsiloxane (PDMS) sample over a broad-frequency range.
In this paper, a control-based approach to replace the conventional method to achieve accurate indentation quantification is proposed for nanomechanical measurement of live cells using atomic force microscope. Accurate indentation quantification is central to probe-based nanomechanical property measurement. The conventional method for in-liquid nanomechanical measurement of live cells, however, fails to accurately quantify the indentation as effects of the relative probe acceleration and the hydrodynamic force are not addressed. As a result, significant errors and uncertainties are induced in the nanomechanical properties measured. In this paper, a control-based approach is proposed to account for these adverse effects by tracking the same excitation force profile on both a live cell and a hard reference sample through the use of an advanced control technique, and by quantifying the indentation from the difference of the cantilever base displacement in these two measurements. The proposed control-based approach not only eliminates the relative probe acceleration effect with no need to calibrate the parameters involved, but it also reduces the hydrodynamic force effect significantly when the force load rate becomes high. We further hypothesize that, by using the proposed control-based approach, the rate-dependent elastic modulus of live human epithelial cells under different stress conditions can be reliably quantified to predict the elasticity evolution of cell membranes, and hence can be used to predict cellular behaviors. By implementing the proposed approach, the elastic modulus of HeLa cells before and after the stress process were quantified as the force load rate was changed over three orders of magnitude from 0.1 to 100 Hz, where the amplitude of the applied force and the indentation were at 0.4-2 nN and 250-450 nm, respectively. The measured elastic modulus of HeLa cells showed a clear power-law dependence on the load rate, both before and after the stress process. Moreover, the elastic modulus of HeLa cells was substantially reduced by two to five times due to the stress process. Thus, our measurements demonstrate that the control-based protocol is effective in quantifying and characterizing the evolution of nanomechanical properties during the stress process of live cells.
In this paper, we present a high-speed direct pattern fabrication on hard materials (e.g., a tungsten-coated quartz substrate) via mechanical plowing. Compared to other probe-based nanolithography techniques based on chemical- and/or physical-reactions (e.g., the Dip-pen technique), mechanical plowing is meritorious for its low cost, ease of process control, and capability of working with a wide variety of materials beyond conductive and/or soft materials. However, direct patterning on hard material faces two daunting challenges. First, the patterning throughput is ultimately hindered by the "writing" (plowing) speed, which, in turn, is limited by the adverse effects that can be excited/induced during high-speed, and/or large-range plowing, including the vibrational dynamics of the actuation system (the piezoelectric actuator, the cantilever, and the mechanical fixture connecting the cantilever to the actuator), the dynamic cross-axis coupling between different axes of motion, and the hysteresis and the drift effects related to the piezoelectric actuators. Secondly, it is very challenging to directly pattern on ultra-hard materials via plowing. Even with a diamond probe, the line depth of the pattern via continuous plowing on ultra-hard materials such as tungsten, is still rather small (<0.5 nm), particularly when the "writing" speed becomes high. To overcome these two challenges, we propose to utilize a novel iterative learning control technique to achieve precision tracking of the desired pattern during high-speed, large-range plowing, and introduce ultrasonic vibration of the probe in the normal (vertical) direction during the plowing process to enable direct patterning on ultra hard materials. The proposed approach was implemented to directly fabricate patterns on a mask with tungsten coating and quartz substrate. The experimental results demonstrated that a large-size pattern of four grooves (20 μm in length with 300 nm spacing between lines) can be fabricated at a high speed of ∼5 mm/s, with the line width and the line depth at ∼95 nm and 2 nm, respectively. A fine pattern of the word "NANO" is also fabricated at the speed of ∼5 mm/s.
A control-based approach to achieve accurate indentation and broadband nanomechanical quantification using atomic force microscope is proposed and utilized to measure four different polymers. For broadband nanomechanical measurement, conventional method is limited by its inability to account for the dynamics effect of the piezoelectric actuator and the cantilever fixture, and the lateral-vertical coupling effect on the cantilever deflection. The proposed approach substantially improved the accuracy of indentation and nanomechanical measurements by utilizing control technique to compensate for these adverse effects. A polydimethylsiloxane sample and three low-density polyethylene samples with different densities were measured by using this approach. The results showed that the viscoelasticity of these four polymer samples can be consistently measured over a large frequency range (100 Hz to 6 kHz) with merely 1 sec. measurement time.
A novel approach to nanoscale broadband viscoelastic spectroscopy is presented. The proposed approach utilizes the recently developed modeling-free inversion-based iterative control (MIIC) technique to achieve accurate measurement of the material response to the applied excitation force over a broad frequency band. Scanning probe microscope (SPM) and nanoindenter have become enabling tools to quantitatively measure the mechanical properties of a wide variety of materials at nanoscale. Current nanomechanical measurement, however, is limited by the slow measurement speed: the nanomechanical measurement is slow and narrow-banded and thus not capable of measuring rate-dependent phenomena of materials. As a result, large measurement (temporal) errors are generated when material is undergoing dynamic evolution during the measurement. The low-speed operation of SPM is due to the inability of current approaches to (1) rapidly excite the broadband nanomechanical behavior of materials, and (2) compensate for the convolution of the hardware adverse effects with the material response during high-speed measurements. These adverse effects include the hysteresis of the piezo actuator (used to position the probe relative to the sample); the vibrational dynamics of the piezo actuator and the cantilever along with the related mechanical mounting; and the dynamics uncertainties caused by the probe variation and the operation condition. In the proposed approach, an input force signal with frequency characteristics of band-limited white-noise is utilized to rapidly excite the nanomechanical response of materials over a broad frequency range. The MIIC technique is used to compensate for the hardware adverse effects, thereby allowing the precise application of such an excitation force and measurement of the material response (to the applied force). The proposed approach is illustrated by implementing it to measure the frequency-dependent plane-strain modulus of poly(dimethylsiloxane) (PDMS) over a broad frequency range extending over 3 orders of magnitude (~1 Hz to 4.5 kHz).
This article presents an iterative-based feedforward-feedback control approach to achieve high-speed atomic force microscope (AFM) imaging. AFM-imaging requires precision positioning of the probe relative to the sample in all x-y-z axes directions. Particularly, this article is focused on the vertical z-axis positioning. Recently, a currentcycle-feedback iterative-learning-control (CCF-ILC) approach has been developed for precision tracking of a given desired trajectory (even when the desired trajectory is unknown), which can be applied to achieve precision tracking of sample profile on one scanline. In this article, we extend this CCF-ILC approach to imaging of entire sample area. The main contribution of this article is the convergence analysis and the use of the CCF-ILC approach for output tracking in the presence of desired trajectory varation between iterations-the sample topography variations between adjacent scanlines. For general case where the desired trajectory variation occurs between any two successive iterations, the convergence (stability) of the CCF-ILC system is addressed and the allowable size of desired trajectory variation is quantified. The performance improvement achieved by using the CCF-ILC approach is discussed by comparing the tracking error of using the CCF-ILC technique to that of using feedback control alone. The efficacy of the proposed CCF-ILC control approach is illustrated by implementing it to the z-axis control during AFM-imaging. Experimental results are presented to show that the AFMimaging speed can be substantially increased.
The convolution of tip shape on sample topography can introduce significant inaccuracy in an AFM image, when the tip radius is comparable to the typical dimension of the sample features to be observed. The blind estimation method allows one to obtain information on the AFM tip through an unknown characterizer sample and thus to perform the deconvolution of the tip shape from an image. When applying the blind estimation method to determine the AFM tip shape, some apparently trivial issues relating to the experimental operating parameters must be taken into account. In this paper, the effects of the operating parameters, e.g., sampling intervals (resolution) and instrumental noise, have been taken into account for the practical use of blind estimation and the result is that instrumental noise tends to provide a smaller estimation of the tip size, while larger sampling intervals provide a larger value of it. This paper presents guidelines to those effects in AFM and appropriate experimental conditions for applying the blind estimation method to obtain more reliable data on tip radius and therefore on sample topography.
Control can enable high-bandwidth nanopositioning needed to increase the operating speed of scanning probe microscopes (SPMs). High-speed SPMs can substantially impact the throughput of a wide range of emerging nanosciences and nanotechnologies. In particular, inversion-based control can find the feedforward input needed to account for the positioning dynamics and, thus, achieve the required precision and bandwidth. This article reviews inversion-based feedforward approaches used for high-speed SPMs such as optimal inversion that accounts for model uncertainty and inversion-based iterative control for repetitive applications. The article establishes connections to other existing methods such as zero-phase-error-tracking feedforward and robust feedforward. Addi-tionally, the article reviews the use of feedforward in emerging applications such as SPM-based nanoscale combinatorial-science studies, image-based control for subnanometer-scale studies, and imaging of large soft biosamples with SPMs.
The atomic force microscope (AFM) has been widely used to manipulate nanoparticles, nanowires, and nanotubes for applications such as nanostructure building, nanocharacterization, and biomanipulation. However, conventional AFM-based nanomanipulation is inefficient because of the serial scan-manipulation-scan process involved. In this paper, high-efficiency automated nanomanipulation with a parallel imaging/manipulation force microscope (PIMM) is presented. With the PIMM, image scan and nanomanipulation can be performed in parallel through the collaboration between two cantilevers: one cantilever acts as an imaging sensor and the other is used as a manipulating tool. Two automated manipulation schemes were introduced for normal- and high-speed image scanning, respectively. An automated parallel manipulation task is managed by system control software with multithread through a procedure of dynamic image processing, task planning, two-tip collaboration, and a controlled pushing manipulation with amplitude feedback from the cantilevers. The efficiency of automated parallel nanomanipulation with normal-speed image scanning was validated by building nanoparticle patterns.
In this paper, an inversion-based feedforward control approach for achieving high-speed, large-range probe-based nanofabrication is proposed. Probe-based nanofabrication has attracted great interest recently. This technique, however, is still limited by its low throughput, due to the challenges in compensating for the existing adverse effects. These adverse effects include the nonlinear hysteresis as well as the vibrational dynamics of piezoactuators used to position the probe in 3D axes, and the dynamic coupling in multi-axis motion during high-speed nanofabrication. The main contribution of this paper is the utilization of the recently developed model-less inversion-based iterative control technique to overcome these challenges in scanning probe microscope-based nanofabrication. By using this advanced control technique, precision position control of the probe can be achieved during high-speed, large-range multi-axis nanofabrication. The proposed approach is demonstrated in experiments by implementing it to fabricate large-size ( approximately 50 microm) pentagram patterns via mechanical scratching on a gold-coated silicon sample surface at high speed ( approximately 4.5 mm s(-1)).
In this paper, an integrated approach to achieve high-speed atomic force microscope (AFM) imaging of large-size samples is proposed, which combines the enhanced inversion-based iterative control technique to drive the piezotube actuator control for lateral x-y axis positioning with the use of a dual-stage piezoactuator for vertical z-axis positioning. High-speed, large-size AFM imaging is challenging because in high-speed lateral scanning of the AFM imaging at large size, large positioning error of the AFM probe relative to the sample can be generated due to the adverse effects--the nonlinear hysteresis and the vibrational dynamics of the piezotube actuator. In addition, vertical precision positioning of the AFM probe is even more challenging (than the lateral scanning) because the desired trajectory (i.e., the sample topography profile) is unknown in general, and the probe positioning is also effected by and sensitive to the probe-sample interaction. The main contribution of this article is the development of an integrated approach that combines advanced control algorithm with an advanced hardware platform. The proposed approach is demonstrated in experiments by imaging a large-size (50 microm) calibration sample at high-speed (50 Hz scan rate).
The noise power spectrum of the thermally activated motion of an AFM cantilever has been analyzed with respect to viscoelastic and hydrodynamic coupling between the cantilever and a substrate surface. Spheres with radii between 5 and 25 microm were glued to the cantilever to provide a well-defined geometry. The cantilever is modeled as a harmonic resonator with a frequency-dependent complex drag coefficient xi(omega). The variation of the drag coefficient xi(omega) with the tip-sample distance, D, and the sphere radius, R, can be expressed as a function of the single dimensionless parameter D/ R. However, this scaling breaks down close to the surface. There are two sources of a frequency dependence of xi(omega), which are viscoelastic memory and hydrodynamics. Viscoelastic relaxation is observed when the surface is covered with a soft polymer layer. In the absence of such a soft layer one still finds a frequency dependence of xi(omega) which is caused by hydrodynamics. At large substrate-cantilever distances, the drag coefficient increases with frequency because of inertial effects. At small distances, on the other hand, the drag coefficient decreases with increasing frequency, which is explained by the reflection of shear waves from the substrate surface. In liquids, inertial effects can be important when performing dynamic AFM experiments.
In this paper, we present design and real-time implementation of a single-channel adaptive feedback active noise control (AFANC) headset for audio and communication applications. Several important design and implementation considerations, such as the ideal position of error microphone, training signal used, selection of adaptive algorithms and structures will be addressed in this paper. Real-time measurements and comparisons are also carried out with the latest commercial headset to evaluate its performance. In addition, several new extensions to the AFANC headset are described and evaluated.
Active noise control (ANC) is achieved by introducing a cancelling
“antinoise” wave through an appropriate array of secondary
sources. These secondary sources are interconnected through an
electronic system using a specific signal processing algorithm for the
particular cancellation scheme. ANC has application to a wide variety of
problems in manufacturing, industrial operations, and consumer products.
The emphasis of this paper is on the practical aspects of ANC systems in
terms of adaptive signal processing and digital signal processing (DSP)
implementation for real-world applications. In this paper, the basic
adaptive algorithm for ANC is developed and analyzed based on
single-channel broad-band feedforward control. This algorithm is then
modified for narrow-band feedforward and adaptive feedback control. In
turn, these single-channel ANC algorithms are expanded to
multiple-channel cases. Various online secondary-path modeling
techniques and special adaptive algorithms, such as lattice,
frequency-domain, subband, and recursive-least-squares, are also
introduced. Applications of these techniques to actual problems are
highlighted by several examples
This paper proposes an improved adaptive filtered-x normalized least-mean-square (FxNLMS) algorithm to achieve active microvibration isolation. Physically, microvibration disturbance is attenuated by a custom-developed magnetostrictive-actuated device. Whereas, magnetostrictive materials characterize hysteresis. Particularly, when the amplitude of the input current is large, the hysteresis loop describes strong asymmetry and nonlinearity. To avoid this phenomenon, in some studies, the actuators are limited to move over a small range, and thus the potential range of the isolated microvibration is restrictive. Then Jiles-Atherton model and Bouc-Wen model are utilized to compensate hysteresis, however these models are non-analytical with certain approximation. In order to compensate hysteresis more accurately, Preisach model, a popular operator-based model, is presented. However, due to the double integrals in this model, the hysteresis identification and inversion process is complicated. Therefore, we reduce hysteresis based on a modified Prandtl-Ishlinskii (PI) model which is more simple but effective. This model utilizes the polynomial operators to describe hysteresis asymmetry and nonlinearity. The inverse hysteresis is then applied to compensate the magnetostrictive-induced hysteresis and to alleviate microvibration combining with the conventional FxNLMS algorithm. An experimental setup is fabricated and some experimental investigations are conducted. Experimental results show that the improved FxNLMS algorithm enhances the performance of microvibration isolation effectively—in the presence of single-tone (4 Hz at amplitude of 250 μm) and double tone (2 Hz mixed with 6 Hz at amplitude of 250 μm) excited microvibration, the isolation ratios of the improved FxNLMS controller are 20.79 dB and 15.32 dB respectively, while those of the conventional FxNLMS controller are 13.83 dB and 10.65 dB respectively.
In this paper, an adaptive-scanning mode (ASM) of atomic force microscope (AFM) with near-minimum sample deformation is proposed for imaging live biological samples in liquid. Conventional contact mode (CM) imaging of live cells is rather slow (scan rate < 0.2 Hz), and as the imaging speed increases, significant deformation of the soft and highly corrugated cell membrane is induced. Such a low speed CM imaging of live biological samples is not only time consuming, but also incapable of capturing dynamic biological evolutions occurring in seconds to minutes. The proposed ASM approach aims to address these issues through two synergetic efforts integrated together. First, an adaptive-scanning technique is proposed to optimally adjust the lateral scanning speed to accommodate the sample topography variation and the probe-sample interaction force, so that the scanning-caused sample deformation is maintained below the threshold value while the overall imaging time is minimized. Secondly, a data-driven iterative feedforward control is integrated to the vertical feedback loop along with a gradient-based optimization of the deflection set-point to substantially improve the tracking of the sample topography while maintaining the vertical sample deformation around the minimal. The ASM technique is experimentally validated through imaging live human prostate cancer cells on AFM. The experimental results demonstrate that compared to the conventional CM imaging, the imaging speed is increased over eight times without loss of tracking the topography details of the live cell membrane, and the probe-sample interaction force is substantially reduced.
In this paper, we propose a finite-impulse-response (FIR)-based feedforward control approach to mitigate the acoustic-caused probe vibration during atomic force microscope (AFM) imaging. Compensation for the extraneous probe vibration is needed to avoid the adverse effects of environmental disturbances such as acoustic noise on AFM imaging, nanomechanical characterization, and nanomanipulation. Particularly, residual noise still exists even though conventional passive noise cancellation apparatus has been employed. The proposed technique exploits a data-driven approach to capture both the noise propagation dynamics and the noise cancellation dynamics in the controller design, and is illustrated through the experimental implementation in AFM imaging application.
This paper presents a vibration isolation system integrated with the internal actuators of an atomic force microscope (AFM) to vertically move the probe. For the motion, voice coil actuators (Lorentz actuators) are guided by low-stiffness flexures. Due to the low stiffness, the vibrations from the floor to the probe are decoupled at high frequencies. To reject the residual vibrations, the AFM probe tracks the AFM sample by using a displacement sensor. By mechanical and control design specifically for Lorentz actuators, the vertical motion has a control bandwidth that is 24 times higher than the first mechanical resonance to reject vibrations. As a demonstration of the vibration isolation performance, pits and tracks of a CD-ROM are successfully imaged without an external vibration isolator.
High-speed atomic force microscopy (HS-AFM) has been established and used, which can visualize biomolecules in dynamic action at high spatiotemporal resolution without disturbing their function. Various studies conducted in the past few years have demonstrated that the dynamic structure and action of biomolecules revealed with HS-AFM can provide greater insights than ever before into how the molecules function. However, this microscopy has still limitations in some regards. Recently, efforts have been carried out to overcome some of the limitations. As a result, it has now become possible to visualize dynamic processes occurring even on live cells and perform simultaneous observations of topographic and fluorescent images at a high rate. In this review, we focus on technical developments for expanding the range of objects and phenomena observable by HS-AFM as well as for granting multiple functionalities to HS-AFM.
This article discusses a number of cleanroom qualification parameters in terms of their proper specification. A critical analysis reveals that the useful operating range of some parameters is not appropriately considered by some early standards and guidelines, which are still used by regulatory authorities (the US Food and Drug Administration (FDA) and the European Union (EU)) and industry professionals. In practice, the windows of safely controlled cleanroom operation prove to be considerably larger than anticipated by existing regulations, especially with regard to unidirectional airflow velocity, pressure difference, and other parameters. Many measuring techniques, such as installed HEPA filter integrity testing and recovery time testing, are also regulated more strictly than necessary. Modern cleanroom testing requires more carefully defined targets and more flexibility in using advanced test procedures.
This paper investigates the effect of ultrasonic tip-sample vibration in regulating the fabricated feature depth and reducing machining force in ultrasonic vibration-assisted nanomachining with an atomic force microscope (AFM). Nanopatterns on aluminum and polymethyl methacrylate (PMMA) substrates are fabricated by the ultrasonic vibration-assisted nanomachining approach. It is demonstrated that using a small set-point force and the same vibration amplitude for machining PMMA and aluminum, nearly the same feature depth is achieved. The fabrication depth is mainly controlled by the amplitude of the tip-sample z-vibration, and is insensitive to sample materials. A theoretical analysis of the sample contact stiffness and dynamic stiffness of the cantilever is used to explain the observed material-insensitive depth regulation by ultrasonic tip-sample vibration. The ultrasonic vibration also effectively reduces the normal force and friction during nanomachining. On both PMMA and aluminum samples, experimental results demonstrate significant reduction in set-point force and lateral friction force in ultrasonic vibration-assisted nanomachining compared with nanomachining without ultrasonic z-vibration. Smaller tip wear is observed in ultrasonic vibration-assisted nanomachining for the fabrication of PMMA samples.
When the vibrating microcantilever in an atomic force microscope (AFM) is close to the sample surface, the nonlinear tip-sample interaction will greatly influence the dynamics of the cantilever. In this paper, the effect of the bounded noise parametric excitation on the nonlinear dynamic behavior of dynamic AFM system is investigated. The microcantilever is modeled by a single-lumped-mode approximation and the interactions between the microcantilever and sample are described by the Lennard-Jones (LJ) potential. Numerical simulations are carried out to study the coupled nonlinear dynamic system in terms of bifurcation diagram, Poincaré maps, largest Lyapunov exponent, phase portraits, and time histories in detail. Effects of the density of the random disturbance with bounded noise, material property, and contact angle of the meniscus force are analyzed and discussed. The results indicate that periodic and chaotic motions occur in the dynamic AFM system. It is demonstrated that the coupled dynamic system goes through a complex nonlinear behavior as the system parameters change and the effect of bounded noise cannot be ignored in the further design of an AFM.
This paper deals with local as well as global active noise control (ANC) using a parametric array loudspeaker (PAL) possessing intriguing properties: sharp directivity, low sound pressure decay by distance, capability of steering directivity, etc. After briefing some properties of a PAL necessary for ANC, this paper presents pinpoint control using a PAL for suppressing the sound pressure at a designated location, hence local control. It is shown that unlike conventional ANC in which a voice coil loudspeaker is used, the pinpoint control may achieve the sound pressure suppression without causing spillover. Using the same sound control source, PAL, this paper then refers to global control, termed trivial control in the art, enabling one to generate a global zone of quiet. The trivial control strategy falls into a category of acoustic power control based on a trivial condition requiring the collocation of a primary source and a control source. The trivial condition formerly avoided because of literally trivial may be implemented due to the property of a PAL, thereby enhancing the control effect, theoretically infinity. Two kinds of control strategy are then demonstrated with a view to fulfilling the trivial condition for global control.
The atomic force microscope (AFM) is not only a tool to image the topography of solid surfaces at high resolution. It can also be used to measure force-versus-distance curves. Such curves, briefly called force curves, provide valuable information on local material properties such as elasticity, hardness, Hamaker constant, adhesion and surface charge densities. For this reason the measurement of force curves has become essential in different fields of research such as surface science, materials engineering, and biology.
In this paper, we address the problems associated with the identification and compensation of adverse dynamic effects (magnitude and phase distortions) that limit the operating speed in currently available scanning tunnelling microscopes (STMs). To minimize errors caused by dynamic effects, current STM systems are operated at relatively low speeds (scan frequencies) when compared to the first resonant frequency of the system. Low operating speed limits the temporal resolution of STMs, which in turn limits the STM's ability to observe fast surface phenomena, and reduces the throughput of STM-based applications such as nanofabrication. Our main contribution is the development of an image-based approach that exploits the extant imaging capabilities of the STM to identify and compensate for errors caused by unwanted dynamic effects, thereby enabling high-speed STM operation. The proposed image-based method is illustrated by applying it to an experimental STM.
Infinite impulse response filters have not been used extensively in active noise and vibration control applications. The problems are mainly due to the multimodal error surface and instability of adaptive IIR filters used in such applications. Considering these, in this paper a new adaptive recursive RLS-based fast-array IIR filter for active noise and vibration control applications is proposed. At first an RLS-based adaptive IIR filter with computational complexity of order O(n2) is derived, and a sufficient condition for its stability is proposed by applying passivity theorem on the equivalent feedback representation of this adaptive algorithm. In the second step, to reduce the computational complexity of the algorithm to the order of O(n) as well as to improve its numerical stability, a fast array implementation of this adaptive IIR filter is derived. This is accomplished by extending the existing results of fast-array implementation of adaptive FIR filters to adaptive IIR filters. Comparison of the performance of the fast-array algorithm with that of Erikson’s FuLMS and SHARF algorithms confirms that the proposed algorithm has faster convergence rate and ability to reach a lower minimum mean square error which is of great importance in active noise and vibration control applications.
System inversion provides a nature avenue to utilize the priori knowledge of system dynamics in iterative learning control, resulting in rapid convergence and exact tracking (for nonminimum-phase systems). The benefits of system inversion, however, are not fully exploited in the time-domain ILC approach due to the lack of uncertainty quantification. This critical limit was alleviated in the frequency-domain formulated inversion-based iterative control (IIC) techniques. The existing IIC techniques, however, are for single-input–single-output (SISO) systems only, and the time-domain properties of the IIC techniques are unclear. The contributions of the proposed multi-axis inversion-based iterative control (MAIIC) approach are twofold: First, the IIC technique is extended from SISO systems to multi-input–multi-output systems and is easy to implement in practice. The iterative control law is optimized by using the quantification of the system uncertainty. Secondly, the time-domain properties of the MAIIC law are discussed. The proposed MAIIC technique is illustrated through 3D nanopositioning experiments using piezoelectric actuators. The experimental results clearly demonstrated that by using the proposed technique, precision tracking in all 3D axes can be achieved in the presence of a pronounced cross-axis dynamics coupling effect.
We introduce a method that exploits the "active" nature of the force-sensing integrated readout and active tip (FIRAT), a recently introduced atomic force microscopy (AFM) probe, to control the interaction forces during individual tapping events in tapping mode (TM) AFM. In this method the probe tip is actively retracted if the tip-sample interaction force exceeds a user-specified force threshold during a single tap while the tip is still in contact with the surface. The active tip control (ATC) circuitry designed for this method makes it possible to control the repulsive forces and indentation into soft samples, limiting the repulsive forces during the scan while avoiding instability due to attractive forces. We demonstrate the accurate topographical imaging capability of this method on suitable samples that possess both soft and stiff features.
Piezoelectric tube scanners have emerged as the most widely used nanopositioning technology in modern scanning probe microscopes. Despite their impressive properties, their fast and accurate operations are hindered due to complications such as scan induced mechanical vibrations, hysteresis nonlinearity, creep, and thermal drift. This paper presents an overview of emerging innovative solutions inspired from recent advances in fields such as smart structures, feedback control, and advanced estimation aimed at maximizing positioning precision and bandwidth of piezoelectric tube scanners. The paper presents a thorough survey of the related literature and contains suggestions for future research prospects.
Force-distance curve measurements using atomic force microscope (AFM) has been widely used in a broad range of areas. However, currently force-curve measurements are hampered the its low speed of AFM. In this article, a novel inversion-based iterative control technique is proposed to dramatically increase the speed of force-curve measurements. Experimental results are presented to show that by using the proposed control technique, the speed of force-curve measurements can be increased by over 80 times--with no loss of spatial resolution--on a commercial AFM platform and with a standard cantilever. High-speed force curve measurements using this control technique are utilized to quantitatively study the time-dependent elastic modulus of poly(dimethylsiloxane) (PDMS). The force-curves employ a broad spectrum of push-in (load) rates, spanning two-order differences. The elastic modulus measured at low-speed compares well with the value obtained from dynamic mechanical analysis (DMA) test, and the value of the elastic modulus increases as the push-in rate increases, signifying that a faster external deformation rate transitions the viscoelastic response of PDMS from that of a rubbery material toward a glassy one.
The atomic force microscope (AFM) is one of the foremost tools for imaging, measuring and manipulating matter at the nanoscale. This brief presents a review of the systems and control approach to analyzing the challenging dynamic-mode operation of the AFM. A Lure system perspective of the AFM dynamics facilitates the application of powerful tools from systems theory for the analysis. The harmonic balance method provides significant insights into the steady-state behavior as well as a framework for identifying the tip-sample interaction force. A simple piecewise-linear tip-sample interaction model and its identification using the harmonic balance method is presented. The dominant first harmonic is analyzed using multivalued frequency responses and the corresponding stability conditions. The ability of the simple tip-sample interaction model to capture the intricate nonlinear behavior of the first harmonic is demonstrated. This also points to the importance of studying the higher harmonics to obtain finer details of the tip-sample interaction. The suitability of the Lure system perspective for the analysis of the higher harmonics is demonstrated.
Controlling tipsample proposed FIR-based controller, along with the ratio of the deflection fluctuation in (b) to that in (a), and (c) the control input applied, and (d) the induced white acoustic noise
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(d) the induced white acoustic noise, respectively.
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Ultramicroscopy 195 (2018) 101-110
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