Sterilizing nano-film detection method, device and equipment

Abstract

The invention discloses a bactericidal nano-film detection method, device and equipment, and belongs to the field of optical measurement, the detection method comprises the following steps: carrying out detection pretreatment on a vanadium dioxide nano-film to obtain a to-be-detected sample; scanning a to-be-detected sample in a normal temperature state and a phase change temperature state to obtain spectral data, and constructing a spectral database; extracting the transmissivity and the reflectivity of the vanadium dioxide nano-film from the spectrum database, calculating to obtain a refractive index and an extinction coefficient, and storing the calculated data into an optical constant database; fitting data in the spectrum database and the optical constant database to obtain a vanadium dioxide nano-film surface defect result. According to the method, accurate identification of the surface defects of the vanadium dioxide nano-film is realized through two times of scanning by utilizing the phase change characteristic of vanadium dioxide.

Description

Technical Field

[0001] The present invention relates to the field of optical measurement, and in particular to a method, device and equipment for detecting a bactericidal nano film. Background Art

[0002] Nanofilm refers to thin film materials with a thickness in the nanoscale range, and its properties are closely related to its surface and interface defects. Nanofilms have unique physical and chemical properties. At the same time, the latest research has found that two-dimensional ultra-thin vanadium dioxide has good broad-spectrum antibacterial properties. The new ultra-thin vanadium dioxide film provides a new strategy for treating infected wounds, greatly expanding the application range of nanofilms and extending the application of nanocatalytic drugs to the anti-infection field. However, surface defects are prone to occur during the production of nanofilms, and the presence of these surface defects will seriously affect their performance, especially for vanadium dioxide films that need to be used in the field of medical sterilization. Surface defects not only affect the mechanical properties, optical properties and electrical behavior of the film, but may also lead to a reduction in the sterilization effect of the material. Therefore, the detection of surface defects in nanofilms is particularly important.

[0003] At present, the most common method for detecting surface defects of nanofilms is to use atomic force microscopy, which is a high-resolution imaging technology that uses the interaction force between atoms to detect the surface morphology of samples. AFM can detect the surface roughness and defects of nanofilms with nanoscale resolution. However, its scanning speed is slow, and the surface state of the sample will affect the measurement results, resulting in inaccurate detection of subtle defects. Therefore, the development of efficient and accurate detection methods is crucial for the research and application of nanofilms. Summary of the invention

[0004] One of the purposes of the present invention is to provide a method for detecting bactericidal nanofilms and to solve the shortcomings of the prior art of slow nanofilm detection speed and low detection accuracy.

[0005] The present invention is achieved through the following technical scheme, a bactericidal nano film detection method, comprising, S100, performing detection pretreatment on the vanadium dioxide nano film to obtain a sample to be detected; S200, scanning the sample to be detected at room temperature and phase change temperature to obtain spectral data, and constructing a spectral database; S300, extracting the transmittance and reflectivity of the vanadium dioxide nano film from the spectral database, and calculating the refractive index and extinction coefficient, and storing the calculated data in an optical constant database; S400, fitting the data in the spectral database and the optical constant database to obtain the surface defect results of the vanadium dioxide nano film.

[0006] Furthermore, the sample to be tested is obtained by uniformly coating a vanadium dioxide nanofilm on a transparent substrate, and the transparent substrate is lead-free glass.

[0007] Furthermore, constructing a spectral database includes: using a Fourier transform infrared spectrometer to scan a sample to be detected at room temperature, scanning the detection sample from three wavelength ranges of near infrared, mid-infrared and far infrared by the Fourier transform infrared spectrometer to obtain first spectral data, and constructing a normal temperature spectral sub-database after noise reduction processing of the first spectral data; heating the same sample to be detected to 68°C, scanning the detection sample heated to 68°C from three wavelength ranges of near infrared, mid-infrared and far infrared by the Fourier transform infrared spectrometer to obtain second spectral data, and constructing a phase change spectral sub-database after noise reduction processing of the second spectral data; standardizing the data in the normal temperature spectral sub-database and the phase change spectral sub-database; then performing independent component analysis on the data in the spectral database to obtain independent components of the normal temperature spectrum and independent components of the phase change spectrum, comparing the independent components of the normal temperature spectrum and the phase change spectrum, and storing the comparison results in a comparison sub-database; the normal temperature spectral sub-database, the phase change spectral sub-database and the comparison sub-database together constitute the spectral database.

[0008] Furthermore, the wavelength of near infrared is 1µm, the wavelength of mid infrared is 10µm, and the wavelength of far infrared is 100µm.

[0009] Furthermore, the noise reduction process includes removing background noise of the spectral data by comparing it with a background spectrum.

[0010] Furthermore, the substrate spectrum includes a room temperature substrate spectrum and a phase change substrate spectrum; wherein, the room temperature substrate spectrum is obtained by scanning the transparent substrate at room temperature using near infrared light with a wavelength of 1µm, mid infrared light with a wavelength of 10µm, and far infrared light with a wavelength of 100µm, and the phase change substrate spectrum is obtained by heating the transparent substrate to the phase change temperature and scanning using near infrared light with a wavelength of 1µm, mid infrared light with a wavelength of 10µm, and far infrared light with a wavelength of 100µm.

[0011] Furthermore, the data in the room temperature spectrum sub-database and the phase change spectrum sub-database are standardized by using Z-score standardization. The Z-score standardization includes: , , ; Where Z is the data output after standardization, dimensionless; x is the data in the database, dimensionless; μ is the mean of all the data in the database, dimensionless; σ is the standard deviation of the data, dimensionless; M is the total number of data set samples in the database, dimensionless; x i is the data value of the i-th sample in the database, dimensionless.

[0012] Furthermore, independent component analysis includes performing the following operations on the room temperature spectrum sub-database and the phase change spectrum sub-database respectively: combining the three groups of spectrum data of near infrared, mid-infrared and far infrared into a data matrix, in which each row represents a sample and each column represents a wavelength point; calculating the covariance matrix and performing eigendecomposition; and finding independent components using the FastICA algorithm.

[0013] Furthermore, comparing the independent components of the room temperature spectrum and the phase change spectrum includes: using a fast Fourier transform (FFT) algorithm to perform Fourier transform on each independent component of the room temperature spectrum and the phase change spectrum, and converting the time domain signal into the frequency domain; drawing spectrum diagrams under room temperature and phase change states, and checking the changes in frequency components by comparing the frequency domain amplitude and phase information of the room temperature spectrum and the phase change spectrum; identifying abnormal changes in the spectrum as frequency components indicating changes in material properties or defects.

[0014] Further, calculating the transmittance and reflectance of the vanadium dioxide nanofilm includes obtaining the transmittance T and reflectance R at different wavelengths from a spectrum database, and calculating the refractive index n and the extinction coefficient k according to the transmittance T and the reflectance R; , , where R is the reflectivity, T is the transmittance, n is the refractive index, k is the extinction coefficient, α is the light absorption coefficient, λ is the wavelength of light, and d is the thickness of the film. The thickness of the film is 50 to 70 nm.

[0015] Furthermore, the fitting includes fitting the data in the comparison sub-database of the spectral database and the data in the optical constant database through the Lorentz model. First, the data in the two databases are preprocessed, and then the Lorentz model is used to fit the data in the comparison sub-database and the optical constant data to obtain the abnormal peak value of the spectrum, the abnormal change data of the refractive index and the extinction coefficient, thereby obtaining the surface defect results.

[0016] On the other hand, the present invention provides a bactericidal nanofilm detection device, which includes a preprocessing unit, a spectral database construction unit, an optical constant database construction unit and a fitting unit, wherein the preprocessing unit is configured to perform detection preprocessing on the vanadium dioxide nanofilm to obtain a sample to be detected; the spectral database construction unit is connected to the preprocessing unit, and is configured to scan the sample to be detected at room temperature and phase change temperature to obtain spectral data, and construct a spectral database; the optical constant database construction unit is connected to the spectral database construction unit, and is configured to extract the transmittance and reflectivity of the vanadium dioxide nanofilm from the spectral database, and calculate the refractive index and extinction coefficient, and store the calculated data in the optical constant database; the fitting unit is connected to the optical constant database construction unit, and is configured to fit the data in the spectral database and the optical constant database to obtain the surface defect results of the vanadium dioxide nanofilm.

[0017] In another aspect, the present invention provides a computer device, comprising: a processor; a memory storing a computer program, and when the computer program is executed by the processor, the above-mentioned bactericidal nano film detection method is implemented.

[0018] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0019] 1. The present invention scans the vanadium dioxide nanofilm twice by utilizing the phase change characteristics of vanadium dioxide, and compares the results of the two scans to achieve accurate identification of surface defects of the vanadium dioxide nanofilm.

[0020] 2. The present invention analyzes the optical properties of vanadium dioxide nanofilms, scans the vanadium dioxide nanofilms at two temperatures using three specific wavelengths of infrared rays, and conducts a comprehensive analysis based on the optical properties to obtain more accurate surface defect detection, thereby improving the overall detection accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0022] Figure 1 A method flow chart provided for exemplary embodiment 1 of the present invention. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0024] Embodiment 1:

[0025] Figure 1 The method flow chart of this embodiment is shown. This embodiment provides a method for detecting bactericidal nanofilms.

[0026] This embodiment includes the following steps:

[0027] Step 1: Right The nanofilm is subjected to detection pretreatment to obtain a sample to be detected.

[0028] Specifically, The nano film is evenly coated on a transparent substrate to obtain a sample to be tested, and the transparent substrate is lead-free glass.

[0029] Step 2: Scan the sample to be tested at room temperature and phase change temperature to obtain spectral data, and build a spectral database.

[0030] Specifically, the spectral database includes three sub-databases, namely, the room temperature spectral sub-database, the phase change spectral sub-database and the comparison sub-database.

[0031] The spectral data in the room temperature spectrum sub-database and the phase change spectrum sub-database are obtained by scanning the samples to be tested under different temperature environments using a Fourier transform infrared spectrometer. Specifically, at room temperature (25-30°C), the samples to be tested are scanned using near infrared light with a wavelength of 1000nm (1µm), mid infrared light with a wavelength of 10µm, and far infrared light with a wavelength of 100µm. The spectral data obtained by scanning these three infrared rays are compared with the base spectrum to remove the background noise of the spectral data and stored in the room temperature spectrum sub-database.

[0032] Heat the sample to be tested to The phase transition temperature of the nanofilm (68°C) is measured by scanning the heated sample with near infrared light of 1000nm (1µm), mid infrared light of 10µm, and far infrared light of 100µm. The spectral data obtained by scanning with these three infrared rays are compared with the base spectrum to remove the background noise of the spectral data and stored in the phase change spectrum sub-database.

[0033] The substrate spectrum data is obtained by scanning the transparent substrate, which is a lead-free glass plate in this embodiment, at room temperature in advance using near infrared light with a wavelength of 1000nm (1µm), mid infrared light with a wavelength of 10µm, and far infrared light with a wavelength of 100µm to obtain a normal temperature substrate spectrum, which is used to remove background noise from normal temperature spectrum data. Similarly, the transparent substrate is heated to the phase change temperature, and scanned using near infrared light with a wavelength of 1000nm (1µm), mid infrared light with a wavelength of 10µm, and far infrared light with a wavelength of 100µm to obtain a phase change substrate spectrum, which is used to remove background noise from phase change spectrum data.

[0034] Then, the data in the room temperature spectrum sub-database and the phase change spectrum sub-database are standardized by using Z-score standardization. The Z-score standardization includes:

[0035] ,

[0036] ,

[0037] ;

[0038] Among them, Z is the data output after standardization, dimensionless; x is the data in the database, dimensionless; μ is the mean of all the data in the database, dimensionless; σ is the standard deviation of the data, dimensionless; M is the total number of data set samples in the database, dimensionless; x i is the data value of the i-th sample in the database, dimensionless.

[0039] After completing the standardization process, the data in the room temperature spectrum sub-database and the phase change spectrum sub-database are subjected to independent component analysis. Specifically, the independent component analysis includes the following operations on the room temperature spectrum sub-database and the phase change spectrum sub-database: combining the three groups of near infrared, mid-infrared and far infrared spectrum data into a data matrix, where each row represents a sample and each column represents a wavelength point; calculating the covariance matrix and performing eigendecomposition; using the FastICA algorithm to find independent components.

[0040] It should be noted that for the three sets of spectral data (near infrared, mid-infrared and far-infrared spectral data), each set of data may contain some common signal components (such as flatness information). Through independent component analysis, these spectral data can be decomposed into independent components. For example, the data is divided into independent signals related to defect characteristics and independent signals related to flatness, so that the defect characteristics of the sample can be analyzed more clearly and intuitively. Then, the FastICA algorithm is used to separate independent components from the mixed spectral data, and the main features in the independent components are analyzed. This can better understand and analyze Spectral properties of nanofilms.

[0041] After obtaining the independent components of the room temperature spectrum and the independent components of the phase change spectrum, use the fast Fourier transform (FFT) algorithm to perform Fourier transform on each independent component of the room temperature spectrum and the phase change spectrum, and convert the time domain signal to the frequency domain; draw the spectrum diagram under the room temperature and phase change state, and check the change of frequency components by comparing the frequency domain amplitude and phase information of the room temperature spectrum and the phase change spectrum; identify the abnormal changes in the spectrum as frequency components indicating changes in material properties or defects, and save these abnormal change data in the comparison sub-database for backup.

[0042] It should be noted that large errors in the spectrum may indicate that the material has undergone physical or chemical changes during phase change. These large errors may lead to surface or structural defects in the film. Theoretically, detection can be achieved at this step. The purpose of detecting the surface defects of nanofilms is to detect the surface defects of nanofilms, but in fact this method still has errors. Therefore, in order to more accurately detect the surface defects of nanofilms, the present invention calculates the optical characteristics and then fits the comparison results with the optical characteristics, so as to more accurately determine the surface defects of nanofilms. The defects on the surface of nanofilm can effectively improve the accuracy of detection.

[0043] Step 3: Extract from the spectral database The transmittance and reflectivity of the nanofilm are calculated, and the refractive index and extinction coefficient are obtained, and the calculated data are stored in the optical constant database.

[0044] Specifically, calculation The transmittance and reflectance of the nanofilm include obtaining the transmittance T and reflectance R at different wavelengths from a spectrum database, and calculating the refractive index n and the extinction coefficient k based on the transmittance T and the reflectance R.

[0045] ,

[0046] ,

[0047] Among them, R is reflectivity, T is transmittance, n is refractive index, k is extinction coefficient, α is light absorption coefficient, λ is wavelength of light, d is thickness of film, and the thickness of film is generally 50-70nm.

[0048] Substitute the reflectivity R and transmittance T at a certain wavelength λ into the above refractive index formula to calculate the refractive index n. After calculating the refractive index n, use the known thickness d and transmittance T of the film to calculate the extinction coefficient k.

[0049] It should be noted that the spectral data at different wavelengths in the room temperature spectrum sub-database and the phase change spectrum sub-database need to be calculated separately, and the calculated results are stored in the optical constant database to facilitate the next fitting operation.

[0050] Step 4: Fit the data in the spectral database and the optical constant database to obtain Nanofilm surface defect results.

[0051] Specifically, the data in the comparison sub-database of the spectral database and the data in the optical constant database are fitted by the Lorentz model, including:

[0052] First, the data in the comparison sub-database and the optical constant database were preprocessed to remove missing values ​​and outliers, and then the data were standardized.

[0053] The purpose of eliminating missing values ​​and outliers is to ensure the integrity and accuracy of the data. The purpose of standardization is to facilitate effective comparison and analysis of fitting algorithms.

[0054] Then, the Lorentz model is used to fit the data in the comparison sub-database and the optical constant data to obtain the abnormal peak of the spectrum, the abnormal change data of the refractive index and the extinction coefficient, so as to obtain more accurate surface defect detection results.

[0055] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for detecting a bactericidal nanofilm, characterized in that: The method comprises, S100, performing detection pretreatment on the vanadium dioxide nanofilm to obtain a sample to be detected; S200, scanning the sample to be tested at room temperature and phase change temperature to obtain spectral data, and constructing a spectral database; S300, extracting transmittance data and reflectance data of the vanadium dioxide nanofilm from the spectrum database, calculating the refractive index and extinction coefficient, and storing the calculated data in the optical constant database; S400, fitting the data in the spectrum database and the optical constant database to obtain the surface defect results of the vanadium dioxide nanofilm.

2. The bactericidal nano film detection method according to claim 1, characterized in that: The sample to be tested is prepared by uniformly coating a vanadium dioxide nanofilm on a transparent substrate, wherein the transparent substrate is lead-free glass.

3. The bactericidal nano film detection method according to claim 1, characterized in that: The constructing of the spectrum database comprises: Use a Fourier transform infrared spectrometer to scan the sample to be tested at room temperature, scan the sample in three wavelength ranges of near infrared, mid infrared and far infrared by the Fourier transform infrared spectrometer to obtain first spectrum data, and construct a normal temperature spectrum sub-database after the first spectrum data is subjected to noise reduction processing; The same sample to be tested is heated to 68°C, and the sample heated to 68°C is scanned by a Fourier transform infrared spectrometer in three wavelength ranges of near infrared, mid-infrared and far infrared to obtain second spectrum data, and the second spectrum data is subjected to noise reduction processing to construct a phase change spectrum sub-database; Performing standardization processing on the data in the room temperature spectrum sub-database and the phase change spectrum sub-database; Then, independent component analysis is performed on the data in the spectrum database to obtain independent components of the normal temperature spectrum and independent components of the phase change spectrum, and the independent components of the normal temperature spectrum and the phase change spectrum are compared, and the comparison results are stored in a comparison sub-database; The normal temperature spectrum sub-database, phase change spectrum sub-database and comparison sub-database together constitute the spectrum database.

4. The method for detecting the bactericidal nano film according to claim 3, characterized in that: The wavelength of the near infrared is 1µm; the wavelength of the mid-infrared is 10µm; the wavelength of the far infrared is 100µm, and the noise reduction processing includes removing background noise of the spectral data by comparing with the base spectrum.

5. The method for detecting the bactericidal nano film according to claim 3, characterized in that: The independent component analysis includes: The following operations are performed on the normal temperature spectrum sub-database and the phase change spectrum sub-database respectively, and the three groups of spectrum data of near infrared, mid-infrared and far infrared are combined into a data matrix, in which each row represents a sample and each column represents a wavelength point; Calculate the covariance matrix and perform eigendecomposition; The FastICA algorithm was used to find independent components.

6. The method for detecting the bactericidal nano film according to claim 3, characterized in that: The independent components of the comparison of the room temperature spectrum and the phase change spectrum include: The fast Fourier transform (FFT) algorithm is used to perform Fourier transform on each independent component of the normal temperature spectrum and the phase change spectrum to convert the time domain signal into the frequency domain; Draw the spectrum at room temperature and phase change state, and check the change of frequency components by comparing the frequency domain amplitude and phase information of the room temperature spectrum and the phase change spectrum; Identify abnormal changes in the spectrum as frequency components that indicate changes in material properties or defects.

7. The method for detecting the bactericidal nano film according to claim 1, characterized in that: The calculation of the transmittance data and reflectance data of the vanadium dioxide nanofilm includes obtaining the transmittance T and reflectance R at different wavelengths from a spectrum database, and calculating the refractive index n and the extinction coefficient k according to the transmittance T and the reflectance R; ， ， Among them, R is reflectivity, T is transmittance, n is refractive index, k is extinction coefficient, α is light absorption coefficient, λ is wavelength of light, d is thickness of film, and the thickness of film is 50-70nm.

8. The method for detecting the bactericidal nano film according to claim 1, characterized in that: The fitting includes fitting the data in the comparison sub-database of the spectrum database and the data in the optical constant database by using the Lorentz model, First, the data in the two databases are preprocessed. Then, the Lorentz model is used to fit the data in the comparison sub-database and the optical constant data to obtain the abnormal peak of the spectrum, the abnormal change data of the refractive index and the extinction coefficient, and thus the surface defect results are obtained.

9. A bactericidal nanofilm detection device, comprising: A preprocessing unit, a spectrum database building unit, an optical constant database building unit and a fitting unit, wherein: The pretreatment unit is configured to perform detection pretreatment on the vanadium dioxide nanofilm to obtain a sample to be detected; The spectrum database construction unit is connected to the preprocessing unit and is configured to scan the sample to be detected at room temperature and phase change temperature to obtain spectrum data and construct a spectrum database; The optical constant database construction unit is connected to the spectrum database construction unit, and is configured to extract the transmittance data and reflectance data of the vanadium dioxide nanofilm from the spectrum database, calculate the refractive index and extinction coefficient, and store the calculated data in the optical constant database; The fitting unit is connected to the optical constant database construction unit and is configured to fit the data in the spectrum database and the optical constant database to obtain the surface defect results of the vanadium dioxide nanofilm.

10. A computer device, characterized in that: The device comprises: processor; The memory stores a computer program, and when the computer program is executed by the processor, the bactericidal nano film detection method according to any one of claims 1 to 8 is implemented.

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