A continuous control mode with improved imaging rate for scanning ion conductance microscope (SICM)

doi:10.1016/j.ultramic.2018.04.009

Ultramicroscopy

Volume 190, July 2018, Pages 66-76

https://doi.org/10.1016/j.ultramic.2018.04.009 Get rights and content

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Highlights

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A continuous control mode of scanning ion conductance microscope (SICM) is developed.
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Surfaces of PDMS, metal grating samples and cardiac fibroblasts were comparably scanned by SICM with the continuous control mode and the stepwise control mode.
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The approach speed of pipette in the continuous control mode can reach at 300 nm/ms.
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The continuous control mode can perform a faster imaging rate and reconstruct the sample topography more accurately than the stepwise control mode.

Abstract

Scanning ion conductance microscopy (SICM), one kind of scanning probe microscopy technique, featuring the advantage of non-contact imaging of sample surfaces in three dimensions with high resolution, has been widely applied in characterizations of sample topography, especially for soft materials. However, the time consuming imaging process of SICM restricts its further applications, such as in characterization of dynamic change of sample surface. In this work, a fast control mode of SICM, named as a continuous control mode, has been developed. In this mode, the SICM probe (i.e., pipette) is controlled by speed instructions in the axial direction of pipette (Z axis), and the pipette position is determined by the position sensor. Compared to the conventional piezo control mode of SICM (i.e., the stepwise control mode), in which the pipette is controlled by the position instructions and moves step by step, the continuous control mode can perform the continuous movement of the pipette in Z axis and overcome the time consuming problem caused by the repeated acceleration and deceleration of the pipette during the stepwise mode. Moreover, the imaging resolution in Z axis is not restricted by the pipette movement step and the imaging rate in the continuous control mode can be significantly enhanced without losing imaging quality. The approach speed of pipette in the continuous control mode can reach at 300 nm/ms, which is much faster than that in the stepwise mode. The surfaces of the soft polydimethylsiloxane (PDMS) samples with three different patterns, the hard metal grating sample and the cardiac fibroblasts as the biological sample demo were comparably scanned by SICM using the continuous control mode and the stepwise approach mode, respectively. The obtained SICM images of the sample topography prove that the continuous control mode can not only reduce the imaging deviation, but also efficiently improve the scanning rate of SICM. Furthermore, the continuous control mode can reconstruct the sample topography more stably compared to the stepwise control mode. The continuous control mode developed in this work can provide an efficient and reliable control strategy for improving the imaging performance of SICM system, and therefore can be potentially applied in dynamic characterizations of various samples in material science, biology and chemistry fields.

Keywords

Scanning ion conductance microscope (SICM)

Continuous control mode

Stepwise approach mode

Imaging rate

Pixel detection frequency

Mean square error (MSE)

1. Introduction

Scanning ion conductance microscope (SICM) [1], one member of scanning probe microscope (SPM), is especially designed for non-contact characterizations of sample surfaces in three dimensions (3D) with high resolution. When a SICM probe (micropipette or nanopipette) approaches to a sample surface, by keeping the conductance of the ion current flow across the pipette tip constant, a constant distance between the SICM probe over sample surface can be performed in a non-contact way, from which the topography information of the sample surface can be obtained. Compared with atomic force microscope (AFM), SICM can better maintain the original features and fit the actual dimension of samples, especially for scanning soft materials in a noncontact way [2], [3]. Moreover, through combining with other techniques (e.g., patch clamp [4], [5], [6], laser scanning confocal microscope [7], [8] and scanning electrochemical microscope [9], [10], [11]), SICM can be further extended to characterize biological samples (e.g., cells) and study biological processes across cell surfaces. Therefore, as a powerful tool for characterization of sample topography, SICM has been widely utilized in material science, biology and chemistry fields in recent years [12], [13], [14], [15], [16], [17]. However, because the sample topography information obtained by SICM is by controlling the pipette to traverse on the sample surface, the imaging rate of SICM is relatively low, restricting its measurement efficiency and time resolution during scanning. Therefore, the imaging rate is one of the critical factors in the development of SICM system [18], [19].

Approach retract scanning (ARS) modes (including the backstep, hopping and standing approach modes [20], [21], [22]) with the adaptability to arbitrarily complex samples are the mostly employed scanning modes of SICM. But the ARS modes have a relative long scanning trajectory compared with the raster scanning mode [8], [23], [24], [25], which leads to the time-consuming scanning process. Two approaches have been developed to facilitate the imaging rates of ARS modes. One is to shorten the scanning track and the other is to enhance the scanning speed of the pipette. For the first approach, one way is to adjust the scanning algorithm of SICM through shortening unnecessary scanning track according to the approximate topography obtained by the pre-scan step [21], [26]. While in this way, the bump structures of samples may be ignored during the pre-scan step, leaving hidden troubles of collisions between pipette and sample for the following scanning. The other way to shorten the scanning track is called the hybrid scanning mode (fSICM) [27], which is by calculating the sample topography using ion current and can dramatically decrease the scanning time. But it is only suitable for rapidly scanning flat sample surfaces in a small region and cannot guarantee the imaging quality. Compared with the approach of shortening scanning track, the method of increasing the scanning speed of pipette is more direct and fundamental. From the aspect of mechanical structure of SICM system, using the faster actuator to control the pipette movement in Z axis is a main method to improve the scan speed of the pipette [28], [29]. However, in the traditional piezo control mode of SICM, i.e., stepwise control mode, there is still a demand to further improve the scan speed of the pipette in the control strategy because the movement of the pipette is generally composed of many steps and each step needs a response time, which results in the repeated acceleration and deceleration processes and thus limits the scanning speed. Moreover, the resolution in Z axis is also limited by the step size [18], [30].

In this work, to overcome the time consuming issue caused by the repeated acceleration and deceleration of the pipette in the stepwise control mode, we developed a fast control mode, named as the continuous control mode, in which the SICM probe is controlled by speed instructions in the axial direction of pipette (Z axis) and the sample height is determined by actuator sensor. The imaging rate of SICM measurements is facilitated using the continuous control mode. The soft polydimethylsiloxane (PDMS) samples with three different patterns, the hard metal grating sample and the cardiac fibroblasts were imaged by the continuous control mode and the stepwise control mode, respectively. The imaging rate, imaging quality and the topography details of the samples using the two control modes were compared from the obtained SICM results, which prove that the continuous control mode can more stably reconstruct the sample topography with higher efficiency than the stepwise control mode.

2. Materials and methods

2.1. Samples

PDMS, metal grating samples and cardiac fibroblasts were used for SICM imaging in this work. The PDMS samples with three different patterns (i.e., microarray cylinder, groove and gear patterns) on their surfaces were fabricated by the imprinting technique using silicon molds (Fig. 1(a–c)). The surface of the metal grating sample was fabricated by polishing and the dark bands of the grating were made by chemical etching with period of 20 µm (Fig. 1(d)). Cardiac fibroblasts were isolated from the hearts of neonatal Sprague–Dawley rats (2-day old), cultured on petri dish on day 4 and fixed using 4% paraformaldehyde. All the samples were placed on the bottom of petri dish with solution during scanning.

2.2. Pipettes and solutions

The SICM probes (i.e., pipettes) made of glass capillaries (BF100-58-10, Sutter Instrument) were fabricated through a laser puller (P-2000, Sutter Instrument) using the following pulling parameters (Heat 280, Fil 2, Vel 55, Del 250, Pul 150). The resistances of the pipettes were measured about 25 MΩ. The inner radius of the pipette tip was estimated at approximately 200 nm with 4% error based on the previous method [31]. Before SICM experiments, the pipette was filled with sample solution (0.1 M KCl aqueous solution for PDMS and metal samples, phosphate buffered saline (PBS) for cardiac fibroblasts) by a syringe. Two Ag/AgCl wires as the electrodes were inserted into the pipette and the sample solution, respectively. Both the pipette and the samples were soaked in the sample solution during SICM measurements.

2.3. Instrumentation and operation modes of SICM system

The block diagram of the hardware used to control the SICM probe is displayed in Fig. 2(a), in which the SICM system consists of a scanning module, a piezo servo-controller, an amplifier, a FPGA control unit, a preamplifier and a host computer. Fig. 2(b) is the photograph of the self-built SICM system. The scanning module is composed of the XYZ piezo-stages (Physik Instrument), which are driven by the actuator controller (E-509, Physik Instrument) with the amplifier (E-503, Physik Instrument) and employed to precisely control the relative position between pipette and sample. The XYZ piezo-stages include a Z piezo-stage (P621.ZCL, Physik Instrument) to control the pipette movement in the vertical direction, and a XY piezo-stage (P621.2CL, Physik Instrument) to control the sample movement in the horizontal direction. The preamplifier (SR570, Stanford Research System) is applied to amplify the ion current and send the feedback signal to the FPGA control unit to regulate the pipette-sample distance. The FPGA chip (Spartan6-XC6S2X25, Xilinx), which is programmed by a high-speed integrated circuit hardware description language (VHDL), is used to control the scanning process by sending the instructions to the piezo servo-controller through a D/A converter (AD5754R, 16 bit) and monitor the signals from the preamplifier and the position senor through the A/D converter (AD7656, 16 bit). The XYZ micro-translation stages (M-111.1DG, Physik Instrument), with maximum travel range of 15 mm in each axis and driven by a motor controller (C-863, Physik Instrument), are used to position the pipette close to the sample surface from a long pipette-to-sample distance. The host computer, as the medium of the man-machine interaction, is responsible for sending scanning commands, receiving and displaying scanning data.

Two control modes of SICM, i.e., the stepwise control mode and the continuous control mode, were employed in this study. The flow charts of the control processes in the two modes are shown in Fig. 3(a) and (b). In each cycle of the stepwise control mode, the reference ion current (I₀) is first recorded away from the sample surface. Then the control unit sends consecutive position instructions to the piezo servo-controller to drive the pipette approach to the sample in the Z axis direction. The difference between the adjacent position instructions is step interval. During each step, the piezo stage needs a stabilization time to let the pipette gradually move to the target position according to the feedback from the stage sensor. After each step movement, the ion current (I) is detected. If the ion current reaches the feedback threshold (I ≤ aI₀, a is the feedback threshold of the ion current), the stepwise movement will stop, and the relative height of the measurement point is determined by the last position instruction. The pipette then retracts away from the sample surface. If all the points are measured, the scan finishes. Otherwise, the pipette will horizontally move to above the next measurement point and begin a new detection cycle. In the continuous control mode developed in this work, the control unit sends velocity instructions (continuous position instructions with a slope) to the piezo servo-controller to drive the piezo-stage to approach to the sample surface at a constant speed. The ion current (I) is monitored during the pipette movement all the time. If the ion current reaches the feedback threshold (I ≤ aI₀), the control unit records the signal from the position sensor as the relative height of the measurement point. That is the reason why a signal line from the position sensor to the FPGA control unit (dotted line in Fig. 2(a)) is added into the SICM system. At the same time of the ion current reaching the feedback threshold, the control unit sends instruction to retract the pipette away from the sample surface.

To clearly show the movement features of the two control modes, Fig. 3(c) and (d) are the schematic diagrams of the position-speed–time curves in one detection cycle of the stepwise control mode and the continuous control mode, respectively. The black and blue lines represent the pipette position and velocity, respectively. In the stepwise control mode, the pipette gradually approaches to the sample with an increment of step interval. The precise stepwise movement adjusted by the piezo controller needs a stabilization time in each step. Thus, the repeated accelerated and decelerated movements can be seen from the velocity curve in Fig. 3(c). Whereas, in the continuous control mode, the pipette approaches to the sample with a more smooth motion, thus no repeated accelerated and decelerated movement caused by the redundant positioning processes is obtained.

2.4. Parameters of SICM imaging

Considering the PDMS samples containing steep slopes on their surfaces, the ARS mode with a retract distance of 3 µm was used and the feedback point of ion current was set to 99% during SICM measurements. The SICM imaging sizes were set to be 12.8 × 12.8 µm (pixels: 64 × 64), 25.6 × 25.6 µm (pixels: 128 × 128) and 51.2 × 51.2 µm (pixels: 256 × 256) for the PDMS samples with cylinder, groove and gear patterns, respectively. The imaging size of the metal grating sample was set to be 51.2 × 51.2 µm (pixels: 256 × 256). The imaging size of the cardiac fibroblasts was set to be 100 × 100 µm (pixels: 100 × 100). A bias voltage of 1.0 V was applied between the two Ag/AgCl electrodes to generate the ion current flowing through the pipette tip during SICM measurements. The topography images of the samples were reconstructed, rendered and demonstrated by Matlab. The subscript M-file was firstly applied to load raw data and reconstruct the topography of the sample in the figure window of Matlab. Then the color and background of the topography images were adjusted. In general, to obtain more actual topography of sample, the raw data recorded by SICM need to be further processed, such as by convolution and filtering algorithm. To compare the features of the original data obtained by the two control modes more clearly, all the topography images of samples presented in this work are the raw data without interpolation or filtered.

In the continuous control mode, the pipette moves continuously at a constant speed. Considering the existence of the Z piezo-stage response time, the pipette inevitably overshoots the feedback position when the pipette approaches to the sample surface. To select a proper speed to avoid the contact between pipette and sample, the maximum approaching speed during scanning the bottom of petri dish was tested first. Then the reliable approach speed was selected according to the minimum of the ion current [32]. Fig. 4 shows the normalized ion current during the processes of the pipette scanning over the bottom of the petri dish in the continuous control mode and the stepwise control mode, respectively. The retract height was 3 µm and the feedback threshold was 0.99. During testing the continuous control mode, 10 nm/ms was the increment of the approach speed. Fig. 4(a) presents the test results when the approach speeds of pipette were set to 100 nm/ms, 200 nm/ms, 300 nm/ms and 400 nm/ms, respectively. It can be seen from the figure that with the increase of the approach speed, the ion current in the downward peak gradually decreases, which means the overshoot of the pipette gradually increases. When the approach speed enhances to 300 nm/ms, the reduction of the ion current reaches ∼2%, and the pipette could scan the sample surface in a stably and non-invasive way [32]. As the approach speed continuously increases, the reduction of the ion current is over the non-invasive threshold of 2%, which can be seen from the forth figure in Fig. 4(a), resulting in a probable contact between pipette and sample surface during measurement. Thus, to scan sample surface as quickly as possible and also to maintain a stable scan, the maximum approaching speed of 300 nm/ms was used. In the stepwise control mode, for balancing the imaging rate and the imaging resolution [22], the pipette step size in Z axis was set to 40 nm. Fig. 4(b) shows the normalized ion current when the pipette scans over the bottom of the petri dish at the approach steps of 40 nm and 200 nm. No obvious overshoot in the stepwise mode at different approach steps is observed. Even the approach step of 200 nm cannot be used stably for scanning real sample, the detection frequency in the stepwise control mode is still longer than that in the continuous control mode at the relatively low approach speed of 100 nm/ms. The above results indicate that the continuous control mode is a relatively more efficient control method than the stepwise control mode.

2.5. Performance indexes

The two control modes were employed to consecutively measure PDMS and metal grating samples for twenty times. Two performance indexes, i.e., the pixels detection frequency (fr) and the mean square error (MSE) of the images, were obtained through statistical analysis of the experimental data. The pixels detection frequency of each image, which as the unified imaging rate index, is calculated by (1)

f r = (M \times N) / t

where M is the row number of the pixels, N is the column number of the pixels, and t is imaging time. A higher frequency corresponds to a faster imaging rate.

The MSE, representing the imaging deviation, is used as an imaging quality index. A lower MSE indicates a better imaging quality. The MSE is given by (2)

M S E = \sum_{j = 1}^{N} \sum_{i = 1}^{M} {[f (i, j) - \bar{f} (i, j)]}^{2} / (M \times N)

where f(i, j) is the sample height at the pixel coordinates of (i, j).

\bar{f} (i, j)

is the average sample height at the pixel coordinates of (i, j), which can be calculated by (3)

\bar{f} (i, j) = \sum_{k = 1}^{n} f_{k} (i, j) / n

where n is the number of imaging in the same area, and f_k(i, j) represents the sample height at the pixel coordinates of (i, j) in the kth image.

3. Results and discussion

The self-built SICM system with both the continuous control mode and the stepwise control mode were utilized to image the “soft” PDMS and the “hard” grating metal samples first. The obtained 3D topographic images of the samples are shown in Fig. 5(a–d). In each subfigure, upper and lower images are acquired in the two control modes. The color on the sample surface represents the relative sample height in Z axis, as displayed in the color bar. And due to the different height ranges of the metal grating and the PDMS patterns, different color bars were used for the two samples in the figure. It can be observed from Fig. 5(a–c) that the round shape of cylinder with ca. 6.5 µm in diameter and height of ca. 2.5 µm, the groove pattern with the grooves width of ca. 20 µm and depth of ca. 2.5 µm, and the gear pattern with the outer diameter of ca. 48 µm, inner diameter of ca. 40 µm and the height of ca. 2.5 µm. For the metal grating sample shown in Fig. 5(d), the grating fringe spacing of ca. 20 µm is observed. These imaging results recorded by the two control modes are consistent with the dimensions of samples displayed in Fig. 1. Although from the SICM results, the sample topography acquired in the two modes are the same overall, the imaging rate, the imaging quality and the sample topography details are significantly different. The detailed comparisons of the two control modes are analyzed as below.

The statistic results of the PDMS and the grating metal samples repeatedly scanned using the two control modes for twenty times are summarized in Fig. 5(e) and (f). Considering that the SICM probe scans the sample topography point by point, the average pixel detection frequency was utilized to evaluate the imaging rate. As shown in Fig. 5(e), the pixel average detection frequencies of the four samples scanned using the stepwise control mode and the continuous control mode are ca. 3.2 Hz and 41.9 Hz, respectively. It indicates that the continuous control mode has a much faster imaging rate than that of the stepwise control mode. During SICM imaging process, the pipette approach speed in Z axis mainly determines the detection time of each measurement point. According to the step size of pipette (40 nm) and the stabilization time of each step (4 ms), the pipette approach speed in the stepwise control mode was calculated to be equivalent to 10 nm/ms, which is much slower than the pipette approach speed of 300 nm/ms in the continuous control mode. It suggests that the maximum imaging rate of the continuous control mode is about fourteen times faster than that of the stepwise control mode with optimal detection parameters, i.e., the continuous control mode is a more efficient control strategy than the stepwise control mode for the SICM measurements. The efficient improvement of the pipette detection speed is based on the specific Z piezo actuator, which is a commonly used type and balances the response time and travel range. Recently, adopting the higher-speed customized or commercial piezo actuator is a main strategy to improve the detection speed of the pipette. However, simply pursuing the high-speed piezo structure will cause the severe decay of movement range. For example, in a previous work [33], the resonance frequency of the Z displacement reaches ∼100 kHz, which makes the pipette detection speed reaches 400 nm/ms. But the too small scan range of ∼6 µm limits it further application in SICM scanning on various samples with tens of micrometers size. Therefore, adopting the faster control strategy and developing the high-speed actuator with large travel range are the two approaches for improving the imaging speed of SICM.

To evaluate the imaging stability of the two modes, the average MSE values of the sample images scanned using the two control modes were calculated. As shown in Fig. 5(f), the average MSE values of the four samples using the continuous control mode are 209, 164, 148 and 155 nm², which are lower than the corresponding values of 312, 312, 240 and 283 nm² obtained by the stepwise control mode. It indicates that the image deviation of the continuous control mode is lower than that of the stepwise control mode. The main reason is analyzed as follows. MSE is mainly determined by the positioning error of the piezo actuator, noise of the ion current and data recording method. In this case, since the positioning error of the piezo actuator and the ion current noise are constant during measurement, the difference of MSE is mainly caused by the data recording methods in the two control modes. From the statistic results of MSE, a relative more stable imaging deviation is obtained through using the position sensor to determine the sample topography in the continuous control mode than using the position instruction to determine the sample topography in the stepwise control mode. It demonstrates that during the consecutive scanning of the same sample surface, the continuous control mode proposed herein can obtain topography information with more stable quality than the stepwise control mode.

To clearly compare the details of sample topography obtained using the two control modes, the cross sections of single scan line of the PDMS sample with cylinder pattern by the two control modes extracted from Fig. 6(a) and (d) are presented in Fig. 6(b) and (e). The detailed difference of the scanning results of the sample surfaces is further shown in the local section profiles in Fig. 6(c) and (f). In the stepwise control mode, since the pipette moves step by step and the position of the Z piezo-stage is determined according to the control instructions, the imaging resolution is restricted by the pipette step size in Z axis, leading to the layered situation of the measured points in Fig. 6(c). Even decreasing the step size can reduce the distance between the adjacent layers and increase the imaging resolution in Z axis, the sever decay of the imaging speed will occur [22], [26], [30]. However, the scan profile obtained by the continuous control mode in Fig. 6(f) is smoother than that in Fig. 6(c). It is because the pipette moves continuously and the pipette position is recorded by the position feedbacks from the piezo sensor, the contradiction between the pipette speed and the density of the detection point is largely alleviated.

The detailed improvements of sample topography using the continuous control mode compared to the stepwise control mode can be further observed from the SICM images of the metal grating sample with hard surface in Fig. 7. The traces of the machining processes on the grating surface can be clearly seen in Fig. 7(a) and (b). The cross sections of the single scan line marked by the black lines in Fig. 7(a) and (b) are shown in Fig. 7(c) and (d). Fig. 7(e) and (f) are the local section profiles in the black dotted boxes marked in Fig. 7(c) and (d). From Fig. 7(c–f), the surface of the grooves on the metal grating shows a depth of ca. 400 nm. In the stepwise control mode, the resolution in Z axis is 40 nm (Fig. 7(e)), which will cause 10% error of the measured depth. Thus, the smaller height range of the metal grating (<1 µm) will cause the bigger measurement error compared with that of the PDMS samples (40 nm/2500 nm = 1.6%). While, in the continuous control mode, the section profile of the sample is not limited by the step size, which can provide the SICM system with the ability of efficiently obtaining more accurate topography of samples.

To further demonstrate the advantage of our self-built SICM system with the continuous control mode for scanning biological sample, cardiac fibroblasts were imaged by SICM using the continuous control mode and the stepwise control mode with different feedback thresholds. Fig. 8(a) and (c) show the topography of the cardiac fibroblasts obtained by the continuous control mode with the feedback threshold of 99.5% and 99.0%, respectively. Fig. 8(e) demonstrates the profiles marked by the yellow lines in Fig. 8(a) and (c), respectively. Fig. 8(b) and (d) show the topography of the same sample area obtained by the stepwise control mode with the feedback threshold of 99.5% and 99.0%, respectively. Fig. 8(f) displays the profiles marked by the yellow lines in Fig. 8(b) and (d), respectively. During scanning, both the thresholds of 99.5% and 99% could be stably used for imaging. But the cell imaging time in the continuous control mode and the stepwise control mode are 244 and 3125 s, respectively, which further validates the higher efficiency of the continuous control mode than the stepwise control mode. From Fig. 8(e) and (f), the expansion of the sample profile about 330 nm happens in both the two control modes when the feedback threshold was set from 99.0% to 99.5%. Thus, the larger feedback threshold will cause the larger measurement deviation of real sample topography, which decreases the SICM imaging accuracy. However, on the other hand, the larger feedback threshold (99.5%) can provide more room between the pipette and sample, which could make the scanning process more reliable and the maximum detection speed of pipette faster. Therefore, the selection of the feedback threshold in SICM imaging needs consider the performance requirement both from efficiency and accuracy.

Based on the quantitative comparison results of the imaging performances of the two control modes displayed in Table 1, the continuous control mode is proved to be more accurately reconstruct the sample topography with lower error fluctuation and can perform at a faster imaging rate compared to the stepwise control mode. In this work, definition of the resolution in Z axis is related to the SICM measurement principle, but not attributes to the external interference, such as the noise in ion current. In the stepwise control mode, the topography data is recorded by the control instruction, the sample height is therefore multiple of the step size (40 nm). In the continuous control mode, the topography data is recorded by the piezo sensor and sampled by the AD converter. Thus, the minimal height difference is limited by the travel range of Z piezo stage and bit width of the AD converter. The minimal height difference depends on the travel range of the piezo stage (100 µm) and bit width of the AD converter (16 bits). Therefore, in our configuration, the resolution in Z axis is 100/2¹⁶ = 1.5 nm, which is consistent with the raw data obtained from the continuous control mode. In the SICM systems, if the positioning accuracy influenced by the thermal noise in piezo controller is larger than the aforementioned theory resolution, the thermal noise will become the main influence factor of SICM scanning resolution. Therefore, to further improve the SICM scanning resolution, some methods can be used in the future, such as using the higher-resolution AD converter, adopting some refined technique for converter resolution and reducing thermal noise in the hardware circuit. Moreover, average MSE of the images reflects the measurement deviation caused by the different control strategies. The height errors are ∼17 and ∼13 nm (square root of the average MSE value) in the stepwise control mode and continuous control mode, respectively. It can be concluded from the above results that the continuous control mode is more efficient and stable for SICM scans on biological samples, such as characterizations of cell volume [34], ion channel structure [35] and surface protein on cell membrane [36]. Furthermore, although the continuous control mode proposed herein can be a technical reference for further improving the measurement rates of other SPM techniques [37], [38], [39].

Table 1. Comparisons of the imaging rate (pixel detection frequency), imaging stability (MSE) and theory Z-resolution of the two modes in our SICM system.

Performance index	Pipette approaching speed	Average pixel detection frequency	Average MSE of the images	Theory resolution in Z axis
Stepwise control mode	10 nm/ms	3.2 Hz	287 nm²	40 nm
Continuous control mode	300 nm/ms	41.9 Hz	169 nm²	1.5 nm

Note: The theory Z axis resolution in the continuous control mode is calculated by the travel range of Z piezo stage (100 µm) and 16 bits of A/D converter (100,000/2¹⁶ nm).

4. Conclusions

A continuous control mode of SICM imaging is developed in this work. Compared with the stepwise control mode, in which the pipette movement is controlled by the position instruction, the continuous control mode controls the pipette position in Z axis by speed instructions. It can eliminate the repeated acceleration and deceleration processes during the step by step movement occurred in the stepwise control mode, thus facilitate the pipette imaging speed during scanning. The maximum approaching speed of the pipette of the continuous control mode can reach 300 nm/ms, which enhances imaging rate about fourteen times higher than that of the stepwise control mode. In addition, the continuous control mode adopts the position sensor to determine the sample topography in Z axis, which can overcome the imaging resolution restricted by the step size in the stepwise control mode. The obtained SICM imaging results of the PDMS, the metal grating samples and the cardiac fibroblasts prove that the continuous control mode can more rapidly reconstruct the sample topography with lower error fluctuation compared to the stepwise control mode. Therefore, the SICM with the continuous control mode shows the application potential in dynamical observation of the topography change of sample surface and study of the relationship between sample topography and function, such as the dynamic topography change of living cells and the pathogenic mechanism of biological samples in the future.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (51375363, 21775117), the Research of Engine Fault Diagnosis Method Based on SECM-SICM Image of Debris, the International Science and Technology Cooperation and Exchange Program of Shaanxi Province of China (2016KW-064), the General Financial Grant from the China Postdoctoral Science Foundation (2016M592773) and the Fundamental Research Funds for the Central Universities of China (0109-1191320016).

Appendix. Supplementary materials

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Proc. Natl. Acad. Sci. U.S.A., 99 (2002), pp. 16018-16023
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Imaging the elastic modulus of human platelets during thrombin-induced activation using scanning ion conductance microscopy
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A.V. Glukhov, M. Balycheva, J.L. Sanchez-Alonso, Z. Ilkan, A. Alvarez-Laviada, N. Bhogal, I. Diakonov, S. Schobesberger, M.B. Sikkel, A. Bhargava, G. Faggian, P.P. Punjabi, S.R. Houser, J. Gorelik
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Adv. Mater., 47 (2011), pp. 5613-5617
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T. Ji, Z. Liang, X. Zhu, L. Wang, S. Liu, Y. Shao
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Phys. Chem. Chem. Phys., 34 (2010), pp. 10012-10017
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P. Novak, C. Li, A.I. Shevchuk, R. Stepanyan, M. Caldwell, S. Hughes, T.G. Smart, J. Gorelik, V.P. Ostanin, M.J. Lab, G.W.J. Moss, G.I. Frolenkov, D. Klenerman, Y.E. Korchev
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J. Nanobiotech., 7 (2009), p. 7
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[23]
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Scanning ion conductance microscopy of living cells
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J. Microsc., 188 (1997), pp. 17-23
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Ultramicroscopy, 90 (2001), pp. 13-19
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Monitoring cell movements and volume changes with pulse-mode scanning ion conductance microscopy
J. Microsc., 212 (2003), pp. 144-151
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[27]
A. Zhukov, O. Richards, V. Ostanin, Y. Korchev, D. Klenerman
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Ultramicroscopy, 121 (2012), pp. 1-7
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R. Guo, J. Zhuang, L. Ma, F. Li, D. Yu
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Use of scanning ion conductance microscopy to guide and redirect neuronal growth cones
Neurosci. Res., 64 (2009), pp. 290-296
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[33]
S. Watanabe, T. Ando
High-speed XYZ-nanopositioner for scanning ion conductance microscopy
Appl. Phys. Lett., 111 (2017), Article 113106
View in Scopus Google Scholar
[34]
Y.E. Korchev, J. Gorelik, M.J. Lab, E.V. Sviderskaya, C.L. Johnston, C.R. Coombes, I. Vodyanoy, C.R. Edwards
Cell volume measurement using scanning ion conductance microscopy
Biophys. J., 78 (2000), pp. 451-457
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[35]
P. Novak, J. Gorelik, U. Vivekananda, A.I. Shevchuk, Y.S. Ermolyuk, R.J. Bailey, A.J. Bushby, G.W.J. Moss, D.A. Rusakov, D. Klenerman, D.M. Kullmann
Nanoscale-targeted patch-clamp recordings of functional presynaptic ion channels
Neuron, 79 (2013), pp. 1067-1077
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[36]
Y. Nashimoto, Y. Takahashi, H. Ida, Y. Matsumae, K. Ino, H. Shiku, T. Matsue
Nanoscale imaging of an unlabeled secretory protein in living cells using scanning ion conductance microscopy
Anal. Chem., 87 (2015), pp. 2542-2545
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[37]
Y.R. Teo, Y.K. Yong, A.J. Fleming
A review of scanning methods and control implications for scanning probe microscopy
American Control Conference (2016), pp. 7377-7383
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[38]
K.Y. Yuen, A. Bazaei, S.O.R. Moheimani
Video-rate lissajous-scan atomic force microscopy
IEEE Trans. Nanotech., 13 (2014), pp. 85-93
Google Scholar
[39]
A.J. Fleming, B.J. Kenton, K.K. Leang
Bridging the gap between conventional and video-speed scanning probe microscopes
Ultramicroscopy, 110 (2010), pp. 1205-1214
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Cited by (13)

Hierarchical spiral-scan trajectory for efficient scanning ion conductance microscopy
2019, Micron
Citation Excerpt :
To further enhance the imaging capability and stability, research groups have developed hopping/backstep (Novak et al., 2009; Happel and Dietzel, 2009), standing approach modes (Takahashi et al., 2010), etc. The scanning speed of those modes (typically hopping mode) in SICM is impacted by several factors, including approach rate (Novak et al., 2014; Jung et al., 2015; Zhuang et al., 2018a; Watanabe and Ando, 2017), retract distance (determined by the complexity of the surface) (Zhukov et al., 2012; Ida et al., 2017; Zhuang et al., 2017), imaging pixels, etc. The retract distance of probe in the z-direction considerably depends on the sample height and steepness.
Scanning Ion Conductance Microscopy
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Research on the Adaptive Sensitivity Scanning Method for Ion Conductance Microscopy with High Efficiency and Reliability
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A fuzzy control for high-speed and low-overshoot hopping probe ion conductance microscopy
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2019, ACS Applied Materials and Interfaces
A fast scanning ion conductance microscopy imaging method using compressive sensing and low-discrepancy sequences
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View Abstract

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Imaging the elastic modulus of human platelets during thrombin-induced activation using scanning ion conductance microscopy
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View at publisher
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Direct evidence for microdomain-specific localization and remodeling of functional L-type calcium channels in rat and human atrial myocytes
Circulation, 132 (2015), pp. 2372-2384
View in Scopus Google Scholar

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Nanoscale in situ characterization of Li-ion battery electrochemistry via scanning ion conductance microscopy
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Scanning ion conductance microscopy for studying biological samples
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Scanning ion conductance microscopy
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Topographic imaging of convoluted surface of live cells by scanning ion conductance microscopy in a standing approach mode
Phys. Chem. Chem. Phys., 34 (2010), pp. 10012-10017
View at publisherCrossref View in Scopus Google Scholar

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P. Novak, C. Li, A.I. Shevchuk, R. Stepanyan, M. Caldwell, S. Hughes, T.G. Smart, J. Gorelik, V.P. Ostanin, M.J. Lab, G.W.J. Moss, G.I. Frolenkov, D. Klenerman, Y.E. Korchev
Nanoscale live-cell imaging using hopping probe ion conductance microscopy
Nat. Methods, 6 (2009), pp. 279-281
View at publisher
Crossref View in Scopus Google Scholar

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Backstep scanning ion conductance microscopy as a tool for long term investigation of single living cells
J. Nanobiotech., 7 (2009), p. 7
View at publisher
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View PDF View article Google Scholar

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Specialized scanning ion-conductance microscope for imaging of living cells
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View at publisher
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Characterization of AC mode scanning ion-conductance microscopy
Ultramicroscopy, 90 (2001), pp. 13-19
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P. Happel, G. Hoffmann, S.A. Mann, I.D. Dietzel
Monitoring cell movements and volume changes with pulse-mode scanning ion conductance microscopy
J. Microsc., 212 (2003), pp. 144-151
View in Scopus Google Scholar

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A. Zhukov, O. Richards, V. Ostanin, Y. Korchev, D. Klenerman
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Ultramicroscopy, 121 (2012), pp. 1-7
View PDF View article View in Scopus Google Scholar

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Imaging single nanoparticle interactions with human lung cells using fast ion conductance microscopy
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View at publisher
Crossref View in Scopus Google Scholar

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Multi-objective optimal design of high frequency probe for scanning ion conductance microscopy
Chin. J. Mech. Eng., 29 (2016), pp. 195-203
View in Scopus Google Scholar

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Nanophysiology: bridging synapse ultrastructure, biology, and physiology using scanning ion conductance microscopy
Synapse, 69 (2015), pp. 233-241
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Characterization of tip size and geometry of the pipettes used in scanning ion conductance microscopy
Micron, 83 (2016), pp. 11-18
View PDF View article View in Scopus Google Scholar

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M. Pellegrino, P. Orsini, F. De Gregorio
Use of scanning ion conductance microscopy to guide and redirect neuronal growth cones
Neurosci. Res., 64 (2009), pp. 290-296
View PDF View article View in Scopus Google Scholar

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S. Watanabe, T. Ando
High-speed XYZ-nanopositioner for scanning ion conductance microscopy
Appl. Phys. Lett., 111 (2017), Article 113106
View in Scopus Google Scholar

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Y.E. Korchev, J. Gorelik, M.J. Lab, E.V. Sviderskaya, C.L. Johnston, C.R. Coombes, I. Vodyanoy, C.R. Edwards
Cell volume measurement using scanning ion conductance microscopy
Biophys. J., 78 (2000), pp. 451-457
View PDF View article View in Scopus Google Scholar

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P. Novak, J. Gorelik, U. Vivekananda, A.I. Shevchuk, Y.S. Ermolyuk, R.J. Bailey, A.J. Bushby, G.W.J. Moss, D.A. Rusakov, D. Klenerman, D.M. Kullmann
Nanoscale-targeted patch-clamp recordings of functional presynaptic ion channels
Neuron, 79 (2013), pp. 1067-1077
View PDF View article View in Scopus Google Scholar

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Y. Nashimoto, Y. Takahashi, H. Ida, Y. Matsumae, K. Ino, H. Shiku, T. Matsue
Nanoscale imaging of an unlabeled secretory protein in living cells using scanning ion conductance microscopy
Anal. Chem., 87 (2015), pp. 2542-2545
Crossref View in Scopus Google Scholar

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A review of scanning methods and control implications for scanning probe microscopy
American Control Conference (2016), pp. 7377-7383
Crossref View in Scopus Google Scholar

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K.Y. Yuen, A. Bazaei, S.O.R. Moheimani
Video-rate lissajous-scan atomic force microscopy
IEEE Trans. Nanotech., 13 (2014), pp. 85-93
Google Scholar

[39] [39]
A.J. Fleming, B.J. Kenton, K.K. Leang
Bridging the gap between conventional and video-speed scanning probe microscopes
Ultramicroscopy, 110 (2010), pp. 1205-1214
View PDF View article View in Scopus Google Scholar