Polarization-insensitive terahertz metasurface biosensor and applications thereof

Abstract

The application discloses a polarization-insensitive terahertz metasurface biosensor and application thereof, and the sensor comprises a substrate layer and a resonance layer arranged on the substrate layer; the resonance layer is an array of unit structures composed of a ring-shaped loop dipole and a four-way central rotationally symmetrical open resonant ring, and the array of unit structures is arranged in a square period; wherein the internal current of the ring-shaped loop dipole presents a ring-shaped flow feature, and the consistency of electromagnetic field distribution can be maintained for any polarized direction of incident electric field; the four-way central rotationally symmetrical open resonant ring enables different electromagnetic modes to be coupled at the same frequency point, and forms a symmetrical response performance, so that the polarization-insensitive characteristic is realized. The application utilizes the fact that the ring-shaped loop dipole and the electric dipole moment have similar contributions in the far field, so that the scattering loss is inhibited; while the local field effect is enhanced, the stable response to the change of the incident angle is realized, and the sensitivity of the traditional sensor to the polarization direction is effectively overcome.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of terahertz and biosensing, and particularly relates to a polarization-insensitive terahertz metasurface biosensor and application thereof. BACKGROUND

[0002] Due to the characteristics of label-free, non-ionizing, high temporal resolution, and the ability to penetrate many non-metallic and non-aqueous molecular materials, terahertz waves exhibit unique sensing capabilities for biological tissues and biomolecules, making them an ideal tool for sensing the internal structure and dynamic changes of biological cells.

[0003] The terahertz wave band is located between the microwave and infrared light, with non-ionizing and low photon energy characteristics, which will not cause harm to biological tissues, and has wide application potential in the field of biomedicine, especially for detecting the vibration mode and structural changes of biomolecules. However, due to the small absorption cross-section of biomolecules in the terahertz wave band, the signal change is weak, which increases the detection difficulty. In order to overcome this challenge, researchers have developed various terahertz sensors based on metasurfaces, which can enhance electromagnetic field resonance and thus improve detection sensitivity. However, existing terahertz metasurface biosensors still face many technical bottlenecks. First, traditional metasurface structures usually rely on electric and magnetic multipole resonance modes, but these resonance modes have large losses in high-frequency transmission, resulting in a decrease in overall sensing sensitivity. In addition, many terahertz metasurfaces are highly sensitive to the polarization angle, which means that the polarization direction of the incident light needs to be precisely controlled during the detection process, thereby increasing the complexity and difficulty of measurement. This polarization dependence severely limits the versatility and flexibility of the sensor in practical biosensing applications. In addition, for early cancer diagnosis and treatment monitoring in practical applications, high sensitivity and high specificity detection of circulating tumor cells (CTCs) in patients or cancer cells in tissue biopsy samples is crucial. However, clinical samples often exhibit high heterogeneity, including various normal cell types and other potential interfering substances in addition to target cancer cells, which increases the detection difficulty. Therefore, it is necessary to design a terahertz metasurface biosensing method for two or more mixed cells.

[0004] Traditional terahertz metasurface biosensors are sensitive to the polarization direction of incident electromagnetic waves, which means that the signal response will differ under different polarization states, which not only reduces the consistency and reliability of the sensor, but also limits its applicability in various application scenarios. At the same time, when dealing with complex mixed samples, such as clinical samples containing multiple cell types, the presence of non-target components will increase background noise, reduce the detection limit and accuracy, and thus affect the reliability and specificity of the detection results. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a polarization-insensitive terahertz metasurface biosensor and an application thereof.

[0006] In a first aspect of the embodiment of the present application, a polarization-insensitive terahertz metasurface biosensor is provided, comprising:

[0007] a substrate layer,

[0008] and a resonant layer arranged on the substrate layer;

[0009] The resonant layer is an array of unit structures composed of annular loop dipoles and four-way central rotational symmetrical open resonant rings, and the array of unit structures is arranged in a square period.

[0010] The internal current of the annular loop dipole presents a ring flow feature, and the four-way central rotational symmetrical open resonant ring enables different electromagnetic modes to be coupled at the same frequency point, forming a symmetrical response performance, thereby realizing the polarization-insensitive characteristic.

[0011] In a second aspect of the embodiment of the present application, an application of the polarization-insensitive terahertz metasurface biosensor in biological detection is provided, and a biological detection method based on the polarization-insensitive terahertz metasurface biosensor comprises:

[0012] Normal cell samples and tumor cell samples under different cell concentrations are configured, and the normal cell samples and the tumor cell samples with the same cell concentration are mixed in different proportions to form a plurality of groups of biological cell suspensions;

[0013] A terahertz wave is incident, and a terahertz transmission spectrum corresponding to each biological cell suspension is obtained through the biological cell suspension and the polarization-insensitive terahertz metasurface biosensor;

[0014] A partial least squares regression method is used to extract features from the terahertz transmission spectrum;

[0015] The features are input into a support vector regression model for optimization to obtain a nonlinear relationship between the cell concentration and the cell type; and a biological cell sample to be detected is detected through the optimized support vector regression model to obtain the cell concentration in the biological cell sample to be detected and the proportion of the tumor cell sample.

[0016] In a third aspect of the embodiment of the present application, an electronic device is provided, comprising a memory and a processor, wherein the memory is coupled to the processor; the memory is used to store program data, and the processor is used to execute the program data to realize the biological detection method based on the polarization-insensitive terahertz metasurface biosensor.

[0017] The fourth aspect of the embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the program is executed by a processor to realize the biological detection method based on the polarization-insensitive terahertz metasurface biosensor.

[0018] Compared with the prior art, the present application has the following advantages:

[0019] The present application provides a polarization-insensitive terahertz metasurface biosensor, which comprises a substrate layer and a resonant layer arranged on the substrate layer; the resonant layer is an array of unit structures composed of a ring-shaped loop dipole and a four-way central rotationally symmetric open resonant ring, and the array of unit structures is arranged in a square period; wherein the internal current of the ring-shaped loop dipole presents a ring-shaped flow feature, and can maintain the consistency of electromagnetic field distribution for any polarized direction of incident electric field, and the four-way central rotationally symmetric open resonant ring enables different electromagnetic modes to be coupled at the same frequency point, forming a symmetric response performance, thereby realizing the polarization-insensitive characteristic. The present application utilizes the similar contribution of the ring-shaped loop dipole and the electric dipole moment in the far field, thereby suppressing scattering loss, realizing high-quality factor and high-sensitivity biosensing; while enhancing the local field effect, a stable response to the change of incident angle is realized, effectively overcoming the sensitivity of the traditional sensor to the polarization direction.

[0020] Meanwhile, the present application provides an application of the polarization-insensitive terahertz metasurface biosensor in biological detection, which can obtain the cell concentration in the biological cell sample to be detected and the proportion of tumor cell samples. The present application can solve the problems of low sensitivity and polarization dependence of the terahertz metasurface, and considering the complex mixed sample situation faced in actual tumor cell detection application, introduces the partial least squares-support vector regression method, extracts the feature information related to the target cell from the complex frequency domain signal, and then establishes a high-precision prediction model. The scheme provided by the present application can not only accurately distinguish and quantify the target cancer cells, but also shows excellent stability and reliability when facing complex backgrounds. The technology is suitable for cancer cell detection in complex mixed samples, and can be widely applied in the fields of biomedical research, clinical diagnosis and personalized medicine, etc., and provides a new tool and technical means for early screening and treatment monitoring of cancer. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0022] Figure 1is a schematic diagram of a polarization-insensitive terahertz metasurface biosensor;

[0023] Figure 2 is a size diagram of a polarization-insensitive terahertz metasurface biosensor unit structure;

[0024] Figure 3 is a polarization-insensitive terahertz metasurface biosensing method provided by the present application;

[0025] Figure 4 is a polarization-insensitive terahertz metasurface transmission diagram and transmission coefficient under different polarization angles;

[0026] Figure 5 is a current distribution diagram of a loop dipole and an open resonant loop under mode 1 and mode 2;

[0027] Figure 6 is a sensitivity simulation diagram of a polarization-insensitive terahertz metasurface;

[0028] Figure 7 is a transmission spectrum diagram and a sensitivity simulation diagram of a polarization-insensitive terahertz metasurface under different sample thicknesses;

[0029] Figure 8 is a transmission coefficient diagram of biological cells under different concentrations in the embodiment;

[0030] Figure 9 is a quantitative analysis and SVR parameter optimization diagram of biological cells under different mixing ratios in the embodiment. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0032] It should be noted that the features in the following embodiments and implementation manners can be combined with each other without conflict.

[0033] As shown in Figure 1 and Figure 2 , the present application provides a polarization-insensitive terahertz metasurface biosensor, comprising:

[0034] a substrate layer,

[0035] and a resonant layer arranged on the substrate layer;

[0036] The resonant layer is an array of unit structures composed of annular loop dipoles and four-way central rotationally symmetrical open resonant rings, and the array of unit structures is arranged in a square period;

[0037] The annular loop dipoles have the characteristic of annular flow of internal current, and can keep consistency of electromagnetic field distribution for incident electric fields of any polarization direction, and the four-way central rotationally symmetrical open resonant rings enable different electromagnetic modes to be coupled at the same frequency point, forming symmetrical response performance, thereby realizing polarization-insensitive characteristics.

[0038] It should be noted that the present application realizes uniform and consistent response under any polarization incident angle through the annular and four-way central rotationally symmetrical structure, and maintains consistent high-performance sensing under different polarization angles; the annular loop dipoles and electric dipole moments have similar contributions in the far field, thereby suppressing scattering loss, realizing high-quality factor and high-sensitivity biosensing; while enhancing the local field effect, stable response to incident angle changes is realized, and the sensitivity to polarization direction of the traditional sensor is effectively overcome.

[0039] Further, the annular loop dipole has an outer radius R1 of 23 μm, the open resonant ring has an outer radius R2 of 7 μm, the ring width W is 4 μm, the spacing g of the center of the open resonant ring is 17 μm, and the opening size s is 4 μm.

[0040] Further, the substrate layer adopts a 75 μm thick polyimide substrate, and the resonant layer adopts 0.2 μm thick gold; a 10 nm thick titanium is further arranged between the substrate layer and the resonant layer as an adhesive; and the cross section of each unit structure array element in the resonant layer is a square with a side length of 50 μm.

[0041] Further, the resonance frequency point caused by the annular loop dipole is near 1.52 THz, the quality factor is 40.67, and the sensitivity is 342 GHz / RIU; when the annular loop dipole is subjected to incident electromagnetic wave radiation, a loop current is induced in the loop, the current in the loop presents symmetrical distribution under the lowest order resonance mode, and a dipole radiation field is formed around the loop; the resonance frequency point generated by the four-way central rotationally symmetrical open resonant ring is near 3.00 THz, the quality factor is 46.39, and the sensitivity is 721 GHz / RIU.

[0042] Further, the terahertz metasurface biosensor exhibits consistent and stable transmission performance within an incident polarization angle range of -45° to 45°; and the terahertz metasurface biosensor maintains consistent and stable transmission performance within a thickness range of 10 μm to 50 μm of the biological cell suspension.

[0043] It should be noted that the polarization-insensitive terahertz metasurface biosensor based on the ring dipole shows consistent and stable transmission performance in the range of -45° to 45° (or equivalent 0° to 90°) of the incident polarization angle. The structure has a four-way central rotational symmetry, which makes it have a polarization-insensitive characteristic of 0-360° in practical application.

[0044] Figure 4 (a) in FIG. 1 shows the transmission characteristics of the sensor between 0.5 THz and 3.2 THz, and generates resonance frequency points f1 and f2 of mode 1 and mode 2 at 1.52 THz and 3.00 THz, Figure 4 (b) in FIG. 1 shows that the sensor maintains good transmission performance in the range of -45° to 45° of the incident polarization angle; Figure 5 (a) in FIG. 1 and Figure 5 (b) in FIG. 1 shows the current distribution of the ring dipole and the open resonant ring under mode 1 and mode 2, which reveals the principle of the ring dipole. When electromagnetic waves are incident on the ring structure, a ring current is induced in the ring. In the lowest order resonance mode, the current in the ring is symmetrically distributed, and a dipole radiation field is formed around the ring. Figure 6 (a) in FIG. 1 shows the change of the transmission coefficient of different refractive indexes (corresponding to different types of biological cells, different mixed proportions of cells), Figure 6 (b) in FIG. 1 shows the linear fitting results corresponding to the resonance frequency points f1 and f2, which shows that the sensor has a sensitivity of 342 GHz / RIU and 721 GHz / RIU under mode 1 and mode 2; Figure 7 (a) in FIG. 1 shows the transmission map of the biological sample with a thickness of 10-50 μm between 0.5 THz and 3.5 THz, Figure 7 (a) in FIG. 1 shows the sensitivity of the sensor for biological samples with a thickness of 10-50 μm, which shows consistent and stable transmission performance.

[0045] On the other hand, as shown in Figure 3 , the present application provides a polarization-insensitive terahertz metasurface biosensor for biological detection; specifically, the biological detection method based on the polarization-insensitive terahertz metasurface biosensor comprises:

[0046] Step S1, configure normal cell samples and tumor cell samples under different cell concentrations, and mix normal cell samples and tumor cell samples with the same cell concentration at different proportions to form several groups of biological cell suspensions.

[0047] Step S2, incident terahertz waves, and obtain the terahertz transmission spectrum corresponding to each biological cell suspension through the biological cell suspension and the polarization-insensitive terahertz metasurface biosensor.

[0048] Step S3, the characteristic extraction of the terahertz transmission spectrum is carried out by using a partial least squares regression (PLS) method, the number of components in the dimension reduction process is optimized, and the main characteristic components related to the concentration change of the target sample are extracted. Moreover, a nonlinear characteristic enhancement module is introduced into the PLS model, so as to further improve the analysis ability of the model for complex mixed ratio samples, and make the model better capture the complex data structure.

[0049] Step S4, the characteristics are input into a support vector regression model based on a radial basis kernel function for optimization, so as to obtain the nonlinear relationship between the cell concentration and the cell type; the biological cell sample to be detected is detected by using the optimized support vector regression model, so as to obtain the cell concentration in the biological cell sample to be detected and the proportion of the tumor cell sample.

[0050] Further, the process of optimizing the support vector regression model comprises:

[0051] Initializing the parameters of the support vector regression model: according to the set logarithmic range, a parameter grid containing all combinations of the penalty coefficient γ and the kernel function parameter C is generated;

[0052] For each group (γ, C), the support vector regression model is trained using the cross-validation technique and the corresponding mean square error is recorded;

[0053] The mean square errors of all combinations are compared, and the (γ, C) combination corresponding to the minimum mean square error is selected as the final optimal parameter of the support vector regression model.

[0054] Step S5, model error analysis is carried out in combination with the experimental results, including signal-to-noise ratio (SNR) evaluation and comparative analysis, so as to verify the detection sensitivity and prediction ability of the sensor, and evaluate the performance stability and applicability of the sensor in actual biological sensing applications.

[0055] Embodiment 1

[0056] In this embodiment, two kinds of biological cell suspensions, Miha and HepG2, are used as examples for high-sensitivity sensing and quantitative detection. Miha and HepG2 are human normal liver cells and liver cancer tumor cells, respectively. The cell concentrations configured in this embodiment are 5×10 3 cells / mL, 2.5×10 4 cells / mL, 5×10 4 cells / mL, 2.5×10 5 cells / mL, 5×10 5 cells / mL, and the measured transmission spectrum results are as follows Figure 8The sensitivity of the polarization-insensitive terahertz metasurface biosensor to Miha and HepG2 cells is 380 kHz / (cell mL -1 ) and 1000 kHz / (cell mL -1 ), respectively, as measured by experiments.

[0057] This embodiment performs accurate identification and quantitative analysis of the target component content of the two different proportions of mixed Miha and HepG2 biological cells described above, with the proportions of Miha and HepG2 being 0:10, 1:9, 2:8, 3:7, 4:6, 5:5, 6:4, 7:3, 8:2, 9:1, and 10:0. The partial least squares model is used to extract features, and the optimal principal component is selected. The square term and the cubic term of the principal component are added to increase the nonlinearity of the model, and the support vector regression model is input for quantitative analysis. In order to obtain better consistency and accuracy, multiple experiments are performed on different types and different concentration gradients of cells. This embodiment performs 156 experiments on each group of mixed biological cells, and a total of 1716 groups of frequency domain transmission spectrum data are obtained. 80% of the data set is used as the training set, and 20% is used as the test set. The average square error is used as an index to optimize the kernel size and box constraint parameters of the support vector regression, and the optimal kernel size parameter is 0.1 and the box constraint parameter is 10. The final average square error is 0.083, Figure 9 (a) in FIG. 8 shows the results of quantitative prediction, Figure 9 (b) in FIG. 8 shows the optimization diagram of the kernel size parameter.

[0058] Those skilled in the art will understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0059] The present application is described with reference to flowcharts and / or block diagrams according to the methods, devices (systems), and computer program products of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce a machine that implements the flowcharts and / or block diagrams. Figure 1One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0060] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0061] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0062] The above embodiments are only used to illustrate the design concept and features of the present invention, and their purpose is to enable those skilled in the art to understand the content of the present invention and implement it accordingly. The protection scope of the present invention is not limited to the above embodiments. Therefore, all equivalent changes or modifications made based on the principles and design ideas disclosed in the present invention are within the protection scope of the present invention.

Claims

1. A polarization-insensitive terahertz metasurface biosensor, characterized in that, include: basal layer And a resonant layer disposed on the substrate; The resonant layer is a unit structure array composed of a ring-shaped ring dipole and a four-way centrally rotationally symmetric open resonant ring, and the unit structure array is arranged in a square periodic pattern. Among them, the internal current of the ring dipole exhibits the characteristics of ring flow, and can maintain the consistency of electromagnetic field distribution for incident electric fields in any polarization direction. The four-way central rotationally symmetrical open resonant ring enables different electromagnetic modes to couple at the same frequency point, forming a symmetrical response performance, thereby achieving polarization insensitivity. The outer radius of the annular ring dipole is R1=23μm, the outer radius of the open resonant ring is R2=7μm, the ring width is W=4μm, the spacing between the centers of the open resonant ring is g=17μm, and the opening size is s=4μm. The resonant frequency caused by the ring dipole is around 1.52 THz, the quality factor is 40.67, and the sensitivity is 342 GHz / RIU. The resonant frequency generated by the four-way centrally rotationally symmetrical open resonant ring is around 3.00 THz, with a quality factor of 46.39 and a sensitivity of 721 GHz / RIU.

2. The polarization-insensitive terahertz metasurface biosensor according to claim 1, characterized in that, The terahertz metasurface biosensor exhibits consistent and stable transmission performance within the incident polarization angle range of -45° to 45°. The terahertz metasurface biosensor maintains stable transmission performance within a thickness range of 10~50μm in biological cell suspensions.

3. The polarization-insensitive terahertz metasurface biosensor according to claim 1, characterized in that, The base layer is made of 75μm thick polyimide, and the resonant layer is made of 0.2μm thick gold; a 10nm thick titanium layer is also provided between the base layer and the resonant layer as an adhesive. Each unit structure element in the resonant layer has a square cross-section with a side length of 50 μm.

4. The application of a polarization-insensitive terahertz metasurface biosensor according to any one of claims 1-3 in biological detection.

5. The application according to claim 4, characterized in that, Biosensor-based biological detection methods using polarization-insensitive terahertz metasurface biosensors include: Prepare normal cell samples and tumor cell samples at different cell concentrations, and mix normal cell samples and tumor cell samples of the same cell concentration in different proportions to form several groups of biological cell suspensions; The incident terahertz wave passes through a biological cell suspension and a polarization-insensitive terahertz metasurface biosensor to obtain the terahertz transmission spectrum corresponding to each biological cell suspension. Feature extraction of terahertz transmission spectra was performed using partial least squares regression. The features are input into the support vector regression model for optimization. The optimized support vector regression model is then used to detect the cell samples of the biological organism to be tested, and the cell concentration and the proportion of tumor cells in the cell samples are obtained.

6. The application according to claim 5, characterized in that, The process of optimizing a support vector regression model includes: Initialize the parameters of the support vector regression model: Generate a parameter grid containing all combinations of penalty coefficients γ and kernel function parameters C, based on the set logarithmic range; For each group (γ, C), a support vector regression model is trained using cross-validation and the corresponding mean squared error is recorded. Compare the mean squared errors under all combinations, and select the (γ,C) combination corresponding to the minimum mean squared error as the parameters of the final optimal support vector regression model.

7. An electronic device comprising a memory and a processor, characterized in that, The memory is coupled to the processor; wherein the memory is used to store program data, and the processor is used to execute the program data to implement the biological detection method based on the polarization-insensitive terahertz metasurface biosensor as described in any one of claims 5-6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the biological detection method based on a polarization-insensitive terahertz metasurface biosensor as described in any of claims 5-6.

Images