CN106855389A - The AFM system mechanical drift compensation method of view-based access control model sensing - Google Patents

Abstract

The invention belongs to field of precision measurement, it is related to a kind of AFM system mechanical drift compensation method of view-based access control model sensing, the method on the basis of microballoon position, sets up a kind of AFM system drift compensation algorithm under by image procossing position finding microscope.Influence due to factors such as mechanical oscillation and noise jammings to AFM system, the variable quantity of distance is the cumulative of AFM system drift between cantilevered distal end microballoon and sample surfaces microballoon, according to the distance change amount of measurement, the actuator voltage of platform is so as to adjust microballoon position where adjustment microballoon, distance between cantilevered distal end microballoon and sample surfaces microballoon is set to remain constant, so as to realize compensating AFM system drift value.Compared with current existing AFM system drift compensation method, the method has the advantage for not transforming AFM system hardware, non-cpntact measurement, can in real time compensate AFM system drift.

Description

Mechanical drift compensation method of AFM system based on visual sensing

technical field

The invention belongs to the field of precision measurement, and in particular relates to a method for compensating mechanical drift of an AFM system based on vision sensing.

Background technique

AFM (Atomic Force Microscope, Atomic Force Microscope) conducts morphology detection and micro-nano manufacturing and processing by detecting the force between the probe and the surface atoms of the sample. It is now widely used in the research fields of semiconductors, nano-functional materials, biology, and chemical engineering. middle. During the long-term working process of AFM, environmental temperature changes, mechanical vibration, electromagnetic interference and other factors lead to serious drift of the system, causing distortion of the image of the object to be measured and position measurement errors.

At present, the research direction of AFM system drift can be divided into two categories: one is to suppress drift in hardware design, and the other is to correct drift from an algorithm. There are additional sensors in the hardware design, optimizing the scanning platform and establishing a double cantilever model. The additional sensor is an auxiliary sensor added to the atomic force system, which can be used to measure vertical drift or interference. The optimization of the scanning platform increases the stiffness of the scanning platform and reduces the coupling to reduce the drift during the measurement process. The dual cantilever model is established and the reference probe is used as a position reference. The above drift compensation methods are limited by the composition structure of the AFM system. In terms of software algorithm compensation drift, for XY direction drift, continuous AFM image sequences are used for offline correction, and the position of features or structures tracked in real time is compensated by atomic tracking combined with feedforward control. For the drift in the vertical direction, the researchers proposed to reduce the thermal drift of the AFM system by controlling the ambient temperature. The above compensation schemes for AFM system drift all improve the system drift. The method of hardware transformation is costly and limited by the structure of the AFM system, and the offline correction of software algorithms is not real-time, which limits its popularization and application.

Contents of the invention

The technical solution problem of the present invention is: to overcome the deficiencies of the existing AFM system drift compensation method, propose a new AFM system drift compensation method, under the condition of non-contact mode and no modification of hardware, real-time high-precision for AFM system drift compensate.

The technical solution of the present invention is to provide a method for compensating mechanical drift of an AFM system based on visual sensing, wherein the visual sensing part includes a microsphere at the end of an AFM cantilever and a microsphere on the surface of a sample. Sensing technology measures the distance between the microspheres at the end of the AFM cantilever and the microspheres on the sample surface, and calculates the drift of the AFM system, including the following steps:

Step 1. Calculate the position of the microsphere at the end of the AFM cantilever and the microsphere on the sample surface based on the visual sensing technology;

Step 2. According to the position of the microsphere at the end of the cantilever and the position of the microsphere on the sample surface, the distance change between the two is calculated, so as to obtain the drift of the AFM system;

Step 3. According to the drift calculated in step 2, adjust the driving voltage of the scanning platform where the microsphere at the end of the AFM cantilever is located, so that the distance between the microsphere at the end of the AFM cantilever and the microsphere on the sample surface is within the threshold range.

Further, before the first step, a distance threshold between the microspheres at the end of the AFM cantilever and the microspheres on the sample surface is set.

In the second step, the calculation of the distance change between the microsphere at the end of the cantilever and the microsphere on the sample surface is to make a difference between the position change of the microsphere at the end of the cantilever and the microsphere on the sample surface, specifically,

d _drift ＝d′-d＝d _{cant, drift} -d _{subs, drift}

Among them, d is the initial distance between the microsphere at the end of the AFM cantilever and the microsphere on the sample surface in the AFM system, d' is the distance after the drift between the microsphere at the end of the AFM cantilever and the microsphere on the sample surface, d _cant,drift is the end of the AFM cantilever Microsphere drift, d _{subs, drift} is the microsphere drift on the sample surface.

The drift d _cant,drift of the microsphere at the end of the AFM cantilever is characterized in that d _cant,drift is obtained by measuring the change in the position of the microsphere at the end of the AFM cantilever.

The sample surface microsphere drift d _subs,drift is characterized in that, d _subs,drift is the amount of position change of the sample surface microsphere.

In the third step, the driving voltage of the AFM cantilever piezoelectric platform is adjusted according to the drift amount through PID closed-loop control, thereby controlling the position of the microsphere at the end of the AFM cantilever, so that the distance between the microsphere at the end of the cantilever and the microsphere on the sample surface is within a threshold value.

The measurement of the distance between the microspheres at the end of the AFM cantilever and the microspheres on the sample surface by the visual sensing technology comprises the following steps:

Step 1. Collect a series of microsphere images at known positions, convert the extracted features of the microsphere images at each position into radial vectors, and establish a microsphere image calibration model for the position information of the microspheres;

Step 2: collecting microsphere images within the range of the calibration position and comparing with the calibration model in step 1 to obtain the position of the microsphere.

Further, the microsphere image extraction feature in the step 1 is characterized in that the center position of the microsphere is determined according to the gray value intensity center of gravity in the image, the image is regarded as a series of rings with the center position as the center, and each The average value of the gray value on the ring, the average value of the gray value on a series of rings is combined into a radial vector in sequence.

The second step is characterized in that the collected microsphere image is converted into a radial vector, compared with the calibration model of position information, and the position of the microsphere is located according to the non-linear least square method.

The mechanical drift compensation method of the AFM system based on visual sensing in the present invention measures the drift of the AFM system by measuring the position of the microsphere at the end of the cantilever and the microsphere on the sample surface based on the visual sensing technology, and directly measures the AFM cantilever and the sample without modifying the original AFM system. Drift between surfaces can solve the drift problem in real time during the scanning process. This method can effectively adapt to drift correction in long-term scanning, and has the advantages of being able to adapt to ordinary samples, automatic, and real-time correction.

Description of drawings

Figure 1 is a schematic diagram of the microspheres at the end of the AFM cantilever and the microspheres on the sample surface.

In Fig. 1, (1) is the sample substrate glass slide, (2) is the microsphere on the sample surface, (3) is the microsphere at the end of the AFM cantilever, (4) is the microcantilever, (5) is the piezoelectric driver, (6) is the cantilever supporting piece, and the dotted line is the schematic position after drifting.

Fig. 2 is a flow chart of AFM system mechanical drift compensation based on visual sensing positioning.

Figure 3 is a flow chart of the microsphere positioning process. Fig. 4 is a flow chart of drift compensation according to the position of the microsphere.

detailed description

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The specific embodiments described here are only used to explain the present invention, not to limit the present invention.

The method of the invention adopts the visual sensing technology to measure and compensate the drift of the AFM system in real time in a non-contact manner without modifying the hardware of the AFM system. The mechanical drift compensation method of the AFM system based on visual sensing is characterized in that the visual sensing part includes a microsphere at the end of the AFM cantilever and a microsphere on the surface of the sample, and the microsphere is a microsphere with a diameter of 10 μm-50 μm. Sensing technology measures the distance between the microspheres at the end of the AFM cantilever and the microspheres on the sample surface, and calculates the drift of the AFM system.

The described AFM system mechanical drift compensation method based on visual sensing specifically includes the following steps:

Step 1. Calculate the position of the microsphere at the end of the AFM cantilever and the microsphere on the sample surface based on the visual sensing technology;

Step 2. According to the position of the microsphere at the end of the cantilever and the position of the microsphere on the sample surface, the distance change between the two is calculated, so as to obtain the drift of the AFM system;

Step 3. According to the drift calculated in step 2, adjust the driving voltage of the scanning platform where the microsphere at the end of the AFM cantilever is located, so that the distance between the microsphere at the end of the AFM cantilever and the microsphere on the sample surface is within the threshold range.

Further, before the first step, a distance threshold between the microspheres at the end of the AFM cantilever and the microspheres on the sample surface is set.

In said step one, the measurement of the distance between the microspheres at the end of the AFM cantilever and the microspheres on the sample surface by visual sensing technology includes the following steps:

Step 1. Collect a series of microsphere images at known positions, convert the extracted features of the microsphere images at each position into radial vectors, and establish a microsphere image calibration model for the position information of the microspheres;

Step 2: collecting microsphere images within the range of the calibration position and comparing with the calibration model in step 1 to obtain the position of the microsphere.

The microsphere image extraction feature is characterized in that the central position of the microsphere is determined according to the gray value intensity center of gravity in the image, the image is regarded as a series of rings with the center position as the center, and the gray level on each ring is calculated. The average value of the value, the average value of the gray value on a series of rings is combined into a radial vector in sequence.

The microsphere image within the scope of the collected calibration position is compared with the calibration model, which is characterized in that the collected microsphere image is converted into a radial vector, compared with the calibration model about the position information, and the microsphere is positioned according to the non-linear least squares method. ball position.

In the second step, the calculation of the distance change between the microsphere at the end of the cantilever and the microsphere on the sample surface is to make a difference between the position change of the microsphere at the end of the cantilever and the microsphere on the sample surface, specifically, d _drift = d'-d ＝d _{cant, drift} -d _{subs, drift}

Among them, d is the initial distance between the microsphere at the end of the AFM cantilever and the microsphere on the sample surface in the AFM system, d' is the distance after the drift between the microsphere at the end of the AFM cantilever and the microsphere on the sample surface, d _cant,drift is the end of the AFM cantilever Microsphere drift, d _{subs, drift} is the microsphere drift on the sample surface.

In the conventional AFM system shape detection, the theory of the sample deformation detected by the microsphere at the end of the AFM cantilever is, δ _ideal = d _{piezo, drive} -d _def

Among them, d _{piezo, drive} is the displacement of the microsphere at the end of the AFM cantilever driven by the piezoelectric driver, and d _def is the displacement caused by the interaction force between the sample and the probe.

Due to the influence of AFM system drift, the actual sample deformation is,

δ _real ＝d _piezo,drive +d _cant,drift -d _subs,drift -d _def

Among them, the sample surface drift can be obtained by measuring the position of the microsphere on the sample surface d _bead2 , and the cantilever drift d _cant,drift can be obtained by measuring the position of the microsphere at the end of the AFM cantilever d _bead1 , specifically,

d _bead1 = d _piezo,drive +d _cant,drift -d _def

d _{cant, drift} = d _bead1 -d _{piezo, drive} +d _def

The piezoelectric driver drives the displacement d _piezo,drive of the microsphere at the end of the AFM cantilever, and the displacement d _def caused by the interaction force between the sample and the probe can be directly measured from the AFM system.

In the third step, the drift amount is compensated in real time according to the measured position of the microsphere. Through the PID closed-loop control, the driving voltage of the piezoelectric platform of the AFM cantilever is adjusted according to the drift, so as to control the position of the microsphere at the end of the AFM cantilever, so that the distance between the microsphere at the end of the cantilever and the microsphere on the sample surface is within the threshold range.

Claims (10)

1. A method for compensating mechanical drift of an AFM system based on visual sensing, wherein the visual sensing part includes an AFM cantilever end microsphere and a sample surface microsphere, and the AFM cantilever end microsphere is controlled by visual sensing technology. The measurement of the distance between the ball and the microsphere on the sample surface, and the calculation of the drift of the AFM system, include the following steps: Step 1. Calculate the position of the microsphere at the end of the AFM cantilever and the microsphere on the sample surface based on the visual sensing technology; Step 2. According to the position of the microsphere at the end of the cantilever and the position of the microsphere on the sample surface, the distance change between the two is calculated, so as to obtain the drift of the AFM system; Step 3. According to the drift calculated in step 2, adjust the driving voltage of the scanning platform where the microsphere at the end of the AFM cantilever is located, so that the distance between the microsphere at the end of the AFM cantilever and the microsphere on the sample surface is within the threshold range. 2. A kind of AFM system mechanical drift compensation method based on visual sensing according to claim 1, characterized in that, before the step 1, the distance threshold between the microsphere at the end of the AFM cantilever and the microsphere on the sample surface is set . 3. a kind of AFM system mechanical drift compensation method based on visual sensing according to claim 1, it is characterized in that, in described step 2, calculate the amount of distance variation between the microsphere at the end of the cantilever and the position of the microsphere on the sample surface is the difference between the position change of the microsphere at the end of the cantilever and the microsphere on the sample surface, specifically, d _drift ＝d′-d＝d _{cant, drift} -d _{subs, drift} Among them, d is the initial distance between the microsphere at the end of the AFM cantilever and the microsphere on the sample surface in the AFM system, d' is the distance after the drift between the microsphere at the end of the AFM cantilever and the microsphere on the sample surface, d _cant,drift is the end of the AFM cantilever Microsphere drift, d _{subs, drift} is the microsphere drift on the sample surface. 4. The microsphere drift d _cant,drift at the end of the AFM cantilever according to claim 3, characterized in that d _cant,drift is obtained by measuring the change in the position of the microsphere at the end of the AFM cantilever. 5. The microsphere drift d _subs,drift on the surface of the sample according to claim 3, characterized in that, d _subs,drift is the position change of the microsphere on the sample surface. 6. A kind of AFM system mechanical drift compensation method based on visual sensing according to claim 1, characterized in that, said step 3, through PID closed-loop control, adjusts the drive voltage of the AFM cantilever piezoelectric platform according to the drift amount, Therefore, the position of the microsphere at the end of the AFM cantilever is controlled, so that the distance between the microsphere at the end of the cantilever and the microsphere on the sample surface is within the threshold range. 7. The control of the position of the microsphere at the end of the AFM cantilever according to claim 6, wherein the position of the microsphere at the end of the AFM cantilever is controlled so that the distance between the microsphere at the end of the AFM cantilever and the microsphere on the sample surface is within a threshold range. 8. a kind of AFM system mechanical drift compensation method based on visual sensing according to claim 1, is characterized in that, described distance between the microspheres at the end of the AFM cantilever and the sample surface microspheres by visual sensing technology measurement, including the following steps: Step 1. Collect a series of microsphere images at known positions, convert the extracted features of the microsphere images at each position into radial vectors, and establish a microsphere image calibration model for the position information of the microspheres; Step 2: collecting microsphere images within the range of the calibration position and comparing with the calibration model in step 1 to obtain the position of the microsphere. 9. According to the feature of microsphere image extraction in step 1 described in claim 8, it is characterized in that, according to the center of gravity of the gray value intensity in the image, the center position of the microsphere is determined, and the image is regarded as a series of circles with the center position as the center Ring, calculate the average value of the gray value on each ring, and the average value of the gray value on a series of rings is combined into a radial vector in sequence. 10. according to the described step 2 of claim 8, it is characterized in that, the microsphere image that collects is converted into radial vector, compares with the calibration model about position information, locates microsphere position according to non-linear least square method.