CN-121830721-B - S-SNOM subsurface defect fine imaging method and system based on polarized laser scattering guidance

CN121830721BCN 121830721 BCN121830721 BCN 121830721BCN-121830721-B

Abstract

An s-SNOM subsurface defect fine imaging method and system based on polarized laser scattering guidance, which belongs to the technical field of optical nondestructive testing, is realized based on a laser, a polarizer, a polarization modulator, a sample to be tested, a beam splitter array, an analyzer array and a detector which are sequentially arranged along the laser propagation direction, wherein the sample to be tested contains subsurface defects. Firstly, carrying out polarization scattering rapid detection on a sample to be detected to obtain polarization scattering data, secondly, carrying out quantitative analysis and risk assessment on subsurface structure non-uniformity to obtain an interested region, thirdly, carrying out interested region extraction and detection task scheduling on a high-risk region, and finally, carrying out high-resolution near-field scanning imaging on the interested region. On the basis of maintaining the advantages of the s-SNOM high-resolution imaging, the cross-scale coordination between the polarization scattering information and the near-field imaging can be realized by introducing a rapid and effective priori guiding mechanism, and efficiency and precision are both considered in large-area sample detection.

Inventors

YAN YING
Bai qian
FAN JIALIN
FANG ZIKENG
LIU CHENXI

Assignees

大连理工大学

Dates

Publication Date: 20260508
Application Date: 20260313

Claims (10)

1. The s-SNOM subsurface defect fine imaging method based on polarized laser scattering guidance is characterized by being realized based on an s-SNOM subsurface defect fine imaging system and comprising a laser (1), a polarizer (2), a polarization modulator (3), a sample to be detected (4), a beam splitter array (6), a beam splitter array (7) and a detector (8) which are sequentially arranged along the laser propagation direction, wherein the sample to be detected (4) comprises subsurface defects (5), the subsurface defects (5) cause polarization characteristic changes of scattered light under the irradiation of polarized laser, and the s-SNOM subsurface defect fine imaging method comprises the following steps: firstly, constructing a physical detection layer through an s-SNOM subsurface defect fine imaging system, and performing polarization scattering rapid detection on a sample (4) to be detected to obtain polarization scattering data; The method comprises the steps of obtaining a polarized scattering data set, constructing a polarized characteristic and risk assessment layer based on the polarized scattering data set obtained in the first step, and quantitatively analyzing and carrying out risk assessment on subsurface structure non-uniformity of a sample (4) to be tested to obtain a region of interest, wherein the polarized characteristic and risk assessment layer comprises a polarized parameter calculation unit, a space reconstruction unit, a risk map generation unit and a parameter configuration and threshold management unit; thirdly, constructing a decision and scheduling layer based on the two-dimensional subsurface defect risk map generated in the second step, and extracting a region of interest and scheduling detection tasks for the high-risk region, wherein the decision and scheduling layer comprises an ROI extraction unit and an ROI screening and priority evaluation unit; Fourth, constructing a cross-system coordinate mapping and control layer to realize coordinate unification and scanning control between the polarized laser scattering detection system and the s-SNOM imaging system, wherein the cross-system coordinate mapping and control layer comprises a reference mark identification unit, a coordinate transformation calculation unit and a scanning instruction generation unit; And fifthly, constructing an s-SNOM fine imaging layer, and performing high-resolution near-field scanning imaging on the region of interest determined in the third step, wherein the s-SNOM fine imaging layer comprises a probe, a near-field excitation unit, an adaptive scanning control unit and a near-field signal acquisition unit.
2. The s-SNOM subsurface defect fine imaging method based on polarized laser light scattering guidance according to claim 1, wherein the first step is specifically: The laser (1), the polarizer (2) and the polarization modulator (3) form a laser and polarization modulation unit, and the laser and polarization modulation unit is used for generating laser with controllable polarization state and realizing modulation of the polarization state of incident light, and the polarization-controllable laser irradiates the surface of a sample (4) to be measured; scanning detection of the surface of the sample (4) to be detected is realized under the driving of a scanning mechanism, in the scanning process, the sample (4) to be detected generates scattered light signals for incident laser, the scattered light signals are received by a scattered signal acquisition unit, the scattered light after splitting is respectively subjected to polarization detection and synchronous acquisition in different polarization directions, scattered response information under each polarization component is extracted and corresponds to scanning position information, polarized scattered data simultaneously containing spatial position information and polarized information is obtained, and a polarized scattered data set for rapidly distinguishing abnormal characteristics of the subsurface of the sample (4) to be detected is formed; The polarization scattering data comprise scattering response information under different polarization states and are used for reflecting disturbance characteristics of subsurface structures of the sample (4) to be detected on the polarization state of incident light.
3. The s-SNOM subsurface defect fine imaging method based on polarized laser light scattering guidance according to claim 2, wherein the second step is specifically: Analyzing the polarized scattering data acquired at different spatial positions by a polarized parameter calculation unit, and calculating normalization, difference, ratio or statistical combination among the scattered light intensities of different polarized components to obtain polarized characteristic parameters for representing subsurface structure non-uniformity; The polarization characteristic parameters are in one-to-one correspondence with the space position information recorded in the scanning process through a space reconstruction unit, and are reconstructed in a two-dimensional plane according to the scanning path and the sampling sequence to form a polarization characteristic distribution matrix consistent with the surface coordinate system of the sample (4) to be detected; the risk map generating unit is used for classifying or mapping the polarization characteristic parameters at each spatial position based on the polarization characteristic distribution matrix and combining parameter configuration with risk criteria preset or adaptively updated in the threshold management unit to generate a two-dimensional subsurface defect risk map reflecting the risk degree of the potential subsurface defect (5) in different areas of the surface of the sample (4) to be detected; finally, quick coarse screening type risk assessment on a large-area of the sample (4) to be detected is realized, and the quick coarse screening type risk assessment is used for identifying a high-risk area possibly with subsurface defects (5) and providing priori guidance for subsequent high-resolution fine detection.
4. A polarized laser light scattering guide-based s-SNOM subsurface defect fine imaging method according to claim 3, wherein the polarization characteristic parameter in the second step comprises depolarization rate, polarization degree, anisotropy parameter or a combination index thereof.
5. The s-SNOM subsurface defect fine imaging method based on polarized laser light scattering guidance according to claim 3, wherein the third step is specifically: Analyzing the two-dimensional subsurface defect risk map through the ROI extraction unit, identifying continuous or discrete areas with risk values higher than a preset threshold according to the risk value distribution condition, and extracting the continuous or discrete areas as one or more areas of interest; The ROI screening and priority evaluation unit is used for combining the spatial position, the region size and the risk level information of the region of interest to schedule and sort the subsequent high-resolution detection tasks, and a detection priority list is generated to realize the centralized allocation of detection resources.
6. The s-SNOM subsurface defect fine imaging method based on polarized laser scattering guidance, which is characterized in that the risk value in the third step is determined based on comprehensive evaluation indexes obtained through calculation of polarization characteristic parameters, the determination mode comprises the steps of carrying out normalization processing on different polarization characteristic parameters, carrying out weighted fusion according to preset weights or adaptive weights to obtain risk scores representing the abnormality degree of subsurface structures, and carrying out corresponding division on risk grade information according to the risk scores and preset or dynamically adjusted risk grade intervals to form a grading risk criterion used for guiding detection decisions.
7. The s-SNOM subsurface defect fine imaging method based on polarized laser light scattering guidance according to claim 5, wherein the fourth step is specifically: Setting one or more reference marks on the surface of the sample (4) to be detected or on a carrying platform of the sample (4) to be detected, wherein the reference marks are used for establishing a space mapping relation among a polarized laser scattering detection coordinate system, the carrying platform coordinate system of the sample (4) to be detected and an s-SNOM imaging coordinate system; The method comprises the steps of acquiring position information of a reference mark under different detection systems through a reference mark identification unit, calculating conversion parameters among different coordinate systems based on corresponding relations of the reference mark in the coordinate systems by a coordinate transformation calculation unit, converting the spatial position information of a region of interest obtained in the third step into scanning coordinates identifiable by an s-SNOM imaging system according to the coordinate conversion relations by a scanning instruction generation unit, generating corresponding scanning instructions, and ensuring that accurate connection is realized between a fast coarse screen and a fine imaging.
8. The s-SNOM subsurface defect fine imaging method based on polarized laser light scattering guide according to claim 6, wherein the fifth step is specifically: According to the spatial position information of the region of interest and the corresponding risk level, which are obtained in the third step, s-SNOM scanning imaging is only carried out on the region of interest, the probe and the near field excitation unit are used for generating local near field excitation on the surface of the sample (4) to be detected and generating near field interaction with the sample (4) to be detected, the near field signal acquisition unit is used for acquiring near field amplitude signals and near field phase signals formed by scattering of the probe, the scanning parameters are dynamically adjusted through the self-adaptive scanning control unit according to the risk level of the region of interest, and finally a near field amplitude image and a near field phase image of the corresponding region of interest are obtained and are used for carrying out fine characterization and analysis on subsurface defects (5).
9. The s-SNOM subsurface defect fine imaging method based on polarized laser scattering guidance according to claim 6, wherein in the fifth step, the scanning parameters comprise scanning steps, scanning density or scanning paths, and the dynamic adjustment is that when the risk level of the region of interest is high, fine scanning of the region is achieved by using small scanning steps or high scanning density, and when the risk level of the region of interest is low, rapid scanning is achieved by using relatively large scanning steps or low scanning density.
10. The s-SNOM subsurface defect fine imaging system based on polarized laser scattering guidance is characterized in that the s-SNOM subsurface defect fine imaging system is used for realizing the s-SNOM subsurface defect fine imaging method based on polarized laser scattering guidance, which is described in any one of claims 1-9, and comprises a laser (1), a polarizer (2), a polarization modulator (3), a sample to be detected (4), a beam splitter array (6), a polarization analyzer array (7) and a detector (8); the polarizer (2) limits the polarization state of the laser output by the laser (1); The polarization modulator (3) is adjustable in angle and is used for modulating the polarization state of laser incident to the sample (4) to be detected, wherein the interior or near-surface area of the sample (4) to be detected contains subsurface defects (5); the beam splitter array (6) is arranged on a scattered light propagation path of the sample (4) to be detected and is used for carrying out beam splitting treatment on scattered light from the sample (4) to be detected to form a plurality of paths of scattered light signals; Each analyzer in the analyzer array (7) corresponds to different polarization analysis directions respectively and is used for extracting scattered light components in the corresponding polarization directions, and a plurality of groups of polarization-related scattered data are obtained through the detector (8), so that the positioning and characterization of subsurface defects (5) or densification features are finally realized; The detector (8) analyzes the polarization response of the scattered light component based on the relative change relation between the light intensities of different polarization components to construct polarization response parameters reflecting the local optical anisotropy and scattering characteristics of the material, and realizes the positioning and characterization of subsurface defects (5) or densification characteristics by analyzing the spatial distribution characteristics of the polarization response parameters and provides priori guidance for subsequent high-resolution near-field scanning.

Description

S-SNOM subsurface defect fine imaging method and system based on polarized laser scattering guidance Technical Field The invention belongs to the technical field of optical nondestructive testing, and relates to an s-SNOM subsurface defect fine imaging method and system based on polarized laser scattering guidance. Background With the rapid development of high-power laser systems, precision optical elements and semiconductor devices, the requirements on the internal structural integrity and the optical performance stability of materials are increasingly increasing. Particularly in hard and brittle materials such as fused quartz, optical glass, crystalline materials, semiconductor substrates and the like, subsurface regions often introduce defects such as microcracks, densified layers, holes/pores, inclusions and the like during processing, polishing or service. Although the scale of the subsurface defect is tiny, the local refractive index, scattering property and energy deposition behavior of the material can be obviously changed, so that the laser damage threshold (LIDT), optical uniformity and long-term reliability of the device are reduced, and the subsurface defect becomes an important factor for restricting the manufacture and application of high-performance photoelectric devices. Aiming at the detection and characterization requirements of subsurface defects, near-field scanning optical microscopy (s-SNOM) is receiving attention because of breaking through diffraction limit and having nanoscale spatial resolution. The technology can carry out fine imaging on the optical response of the material surface layer and the near-surface area, and provides a powerful means for high-resolution characterization of subsurface microstructures. However, the near field scanning optical microscopy generally adopts a point-by-point scanning mode, the single effective imaging area is limited, the scanning efficiency is low, and under the condition of lacking prior information, blind scanning is often required to be carried out on a large-area sample, so that the detection efficiency and the engineering practicability are difficult to be combined. On the other hand, the polarization laser scattering technology can rapidly acquire scattering characteristic information of subsurface defects in a larger scale range by virtue of the sensitive response characteristics of the polarization laser scattering technology to the anisotropy, stress concentration and microstructure disturbance in the material, and has the advantages of high detection speed and large coverage area. However, the method mainly depends on far-field scattering signals, has limited spatial resolution, is difficult to accurately distinguish the fine morphology, scale and type of the defects, is generally only applicable to qualitative or semi-quantitative evaluation, and cannot meet the requirements of fine imaging and quantitative analysis of subsurface defects. In the prior art, a near field scanning optical microscopy technology and a polarized laser scattering method are used in an independent mode, and an effective cross-scale cooperative detection mechanism is not formed yet. On one hand, the technical scheme for uniformly associating large-scale scattering information with a nanoscale near-field imaging result is lacking, and on the other hand, the coordinate systems among different detection modules are independent, so that accurate mapping and automatic directional scanning of a defect area are difficult to realize. In addition, the existing detection flow generally depends on manual experience to select a scanning area, lacks an adaptive scanning strategy based on physical feature guidance, and is difficult to obviously improve detection efficiency while guaranteeing imaging precision. The Chinese patent CN119619553A discloses a hard and brittle material densification detection method based on near-field optical amplitude and phase analysis, and the inventor obtains near-field amplitude or phase information of the surface of a sample by using a scanning near-field optical microscope system and establishes a corresponding relation between near-field optical response and material densification rate, thereby realizing high-precision and nondestructive detection of densification degrees of different positions. However, the method still mainly depends on a point-by-point scanning imaging mechanism of a near-field scanning optical microscope system, the single detection area is limited, and the overall detection efficiency is obviously limited by the scanning speed and the scanning range. When facing large-size optical elements or large-area samples of hard and brittle materials, long-time and large-scale area-by-area scanning is still required, and the requirements of rapid screening and high-throughput detection in engineering applications are difficult to meet. Meanwhile, the method takes the direct mapping relation between the near-field optical si