Method for preparing solid nanopores through automatic controllable breakdown

Abstract

The invention discloses a method for preparing a solid nanopore through automatic controllable breakdown, and relates to the technical field of nanopore processing, and the method comprises the steps of S1, preprocessing and chip assembly, S2, parameter initialization, S3, dynamic voltage gradient control, S4, multi-parameter real-time monitoring, S5, pore diameter prediction and feedback termination, and S6, post-processing and verification. A breakdown basis is established through surface functionalization processing and intelligent parameter initialization, a dynamic voltage gradient algorithm is adopted to adaptively adjust the electric field intensity according to the real-time current change rate, and noise features are synchronously monitored to recognize the breakdown stage; the method comprises the following steps: dynamically predicting pore diameter growth by combining a charge accumulation effect and a thermodynamic model, accurately controlling pore diameter formation through a multi-level termination condition, and finally verifying nanopore parameters by utilizing electrical property analysis and in-situ calibration, and the process is integrated with a dynamic algorithm and a multi-physics field feedback mechanism. And the aperture control precision and the process stability are improved while the machining efficiency is guaranteed.

Description

Technical Field

[0001] The present invention belongs to the technical field of nanopore processing, and particularly relates to a method for automatically and controllably breaking through to prepare solid-state nanopores. Background Art

[0002] With the development of nanoscience and technology, nanopore single-molecule technology has become one of the most powerful tools for applied research in the field of life sciences. Solid-state nanopores have been applied by many researchers in experiments such as DNA sequencing, RNA sequencing, and protein structure testing due to their stable performance and controllable pore size. The preparation materials are mainly two-dimensional thin film materials.

[0003] In the process of preparing solid-state nanopores, traditional methods rely on empirical voltage regulation and manual intervention, resulting in large discreteness of nanopore sizes and high edge roughness, making it difficult to meet the stringent requirements for pore size uniformity in single-molecule detection. Especially at the sub-10 nanometer scale, the random breakdown characteristics of traditional processes are prone to over-breakdown or pore size deviation from the target value. In view of the above problems, the following solutions are proposed. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for automatically and controllably breaking through to prepare solid-state nanopores. Through a dynamic feedback algorithm and a multi-parameter fusion prediction model, it is possible to accurately identify the transient physical changes during the breakdown process without relying on manual experience, and solve the problems of large discreteness of nanopore sizes and high edge roughness in existing methods.

[0005] To solve the above technical problems, the present invention is realized through the following technical solutions:

[0006] The present invention is a method for automatically and controllably breaking through to prepare solid-state nanopores, including:

[0007] Step S1, pretreatment and chip assembly: Immerse the silicon nitride thin film chip in a polyethyleneimine solution to form a uniform positive charge layer through electrostatic adsorption. After rinsing with deionized water and drying with nitrogen, install the chip into the flow cell;

[0008] Step S2, parameter initialization: Measure the initial leakage current at a low voltage, verify the integrity of the membrane, and calculate the initial voltage range;

[0009] Step S3, dynamic voltage gradient control: Adopt an adaptive voltage regulation model based on the current change rate, adjust the voltage according to the current change, and trigger a voltage step-down protection when the threshold is exceeded;

[0010] Step S4, multi-parameter real-time monitoring: Extract the noise spectrum characteristics, synchronously collect the current signal and calculate the power spectral density. When the proportion of 1 / f noise exceeds the threshold, it is determined as the surface defect formation stage;

[0011] Step S5, Aperture Prediction and Feedback Termination: Predict the aperture based on the double-parameter model. Stop breakdown when the aperture is close to the target value, the current slope changes abruptly, or the cumulative charge exceeds the limit. Specifically, stop breakdown when any of the following conditions is met:

[0012] D predict ≥D target ×9500,

[0013] Abrupt change in current slope (▽ 2 I > 10 6 pA / s 2 ),

[0014] Cumulative charge Q > 50 nC;

[0015] Step S6, Post-processing and Verification: Perform in-situ impedance calibration on the prepared nanopore, apply an AC signal with a frequency of 10 - 100 kHz, and calculate the aperture correction value by fitting the Nyquist curve;

[0016] In the above Step S3, the formula of the adaptive voltage regulation model in the dynamic voltage gradient control is:

[0017]

[0018] In the formula, ΔV is the voltage regulation amount (the voltage step dynamically adjusted according to the real-time current change rate, which determines the voltage increase or decrease amplitude in the next stage), k is the material attenuation coefficient (reflecting the response characteristics of the membrane material to the electric field change, calibrated through experiments, used to suppress the overshoot voltage), is the current change rate (characterizing the change speed of the current with time, used as a feedback signal to drive the voltage regulation), n is the non-linear regulation index (amplifying the regulation weight in the stage of high current change rate, accelerating the response to dangerous working conditions), V offset is the voltage reference offset (providing basic voltage compensation, preventing the regulation amount from approaching zero at low current change rate, ensuring the continuous progress of the breakdown process).

[0019] Furthermore, in the above Step S2, the parameter initialization specifically includes the following steps:

[0020] Step S21: Measure the initial leakage current at a low voltage to verify the integrity of the membrane. When the leakage current is abnormal, reprocess or replace the chip;

[0021] Step S22: Dynamically calculate the breakdown starting voltage threshold through material characteristics and surface modification parameters, and initiate the controllable breakdown process.

[0022] Furthermore, in the above Step S22, the formula for calculating the breakdown starting voltage threshold is:

[0023]

[0024] Wherein, V init is the breakdown starting voltage threshold (initial breakdown voltage, preventing instantaneous breakdown of the film material caused by excessive voltage), E breakdown is the breakdown field strength of the material (characterizing the breakdown resistance ability of the silicon nitride thin film under the action of an electric field, related to the material purity and the density of lattice defects), t SiNx is the thickness of the silicon nitride film (directly affecting the voltage threshold required for breakdown, the greater the film thickness, the higher the breakdown voltage), C surface is the capacitance of the surface modification layer (the interface capacitance formed by the PEI coating, reducing the distortion of the surface electric field), C bulk is the bulk capacitance (reflecting the capacitance characteristics of the unmodified SiNx film itself, related to the film thickness and the dielectric constant).

[0025] Furthermore, in the step S5, the two-parameter model formula in pore size prediction and feedback termination is:

[0026]

[0027] Wherein, D predict is the predicted pore size, α is the charge accumulation coefficient, I(τ) is the real-time current value, ∫I(τ)dτ is the current-time integral, β is the thermal effect coupling coefficient, V rms is the root mean square voltage value, t is the duration of the breakdown process, σ ion is the ionic conductivity of the solution.

[0028] Furthermore, in the step S6, the formula for calculating the pore size correction value in post-processing and verification is:

[0029]

[0030] Wherein, D final is the final pore size of the modified nanopore (eliminating the systematic error of the prediction model through impedance calibration and improving the accuracy of pore size measurement), D predict is the predicted pore size value, Z real is the real part of the nanopore impedance, Z ideal is the theoretical impedance of an ideal cylindrical nanopore.

[0031] Furthermore, the calculation formula for the theoretical impedance Z ideal of the ideal cylindrical nanopore is:

[0032]

[0033] Wherein, L is the film thickness, D predict is the predicted pore size, σ ion is the solution conductivity.

[0034] The present invention has the following beneficial effects:

[0035] 1. The present invention establishes a breakdown basis through surface functionalization treatment and intelligent parameter initialization, adopts a dynamic voltage gradient algorithm to adaptively adjust the electric field strength according to the real-time current change rate, and synchronously monitors the noise characteristics to identify the breakdown stage; combines the charge accumulation effect and the thermodynamic model to dynamically predict the pore size growth, precisely controls the pore size formation through multi-level termination conditions, and finally verifies the nanopore parameters by electrical property analysis and in-situ calibration. This process integrates a dynamic algorithm and a multi-physical field feedback mechanism, improving the pore size control accuracy and process stability while ensuring the processing efficiency.

[0036] 2. With the aid of a dynamic feedback algorithm and a multi-parameter fusion prediction model, the present invention can accurately identify the transient physical changes during the breakdown process. When preparing solid-state nanopores, traditional methods rely on experience and manual intervention and it is difficult to control the pore size. The present invention can monitor in real time and dynamically adjust according to multiple parameters. For example, by real-time monitoring of the current signal and noise spectrum characteristics, the voltage change is precisely controlled at different stages to avoid over-breakdown and deviation of the pore size from the target value, improving the accuracy of the pore size during nanopore preparation and making the prepared nanopore size closer to the target value.

[0037] 3. The system of the present invention synchronously monitors the higher-order derivative of the current, the local temperature field, and the dielectric stress distribution, constructs a breakdown risk prediction model through a machine learning algorithm, can trigger a protection program before abnormal expansion of the pore size, and the dynamic impedance matching technology further optimizes the electric field energy distribution, effectively suppressing the edge breakdown effect caused by fluctuations in the solution ion concentration. Under complex electrolyte environments or high-curvature membrane structure conditions, stable processing quality can still be maintained.

[0038] 4. Through the combination of real-time current signal feedback and a dynamic voltage regulation algorithm, the present invention realizes the closed-loop control of the nanopore formation process. The system can automatically identify the defect nucleation stage at the initial stage of breakdown, the pore size expansion stage in the middle, and the structural stability stage at the later stage, and dynamically optimize the electric field parameters for different stages. This design can effectively ensure that the pore edge is smooth and the size is uniform.

[0039] Of course, it is not necessary for any product implementing the present invention to achieve all the above advantages simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0041] Figure 1 It is a schematic flowchart of the present invention. Detailed implementation manners

[0042] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0043] Please refer to Figure 1 As shown, the present invention is a method for automatically controllable breakdown to prepare solid-state nanopores, including:

[0044] Step S1, pretreatment and chip assembly: Immerse the silicon nitride thin film chip in the polyethyleneimine solution to form a uniform positive charge layer through electrostatic adsorption. After rinsing with deionized water and drying with nitrogen, install the chip into the flow cell;

[0045] Step S2, parameter initialization: Measure the initial leakage current at a low voltage, verify the integrity of the membrane, and calculate the initial voltage range;

[0046] Step S3, dynamic voltage gradient control: Adopt an adaptive voltage regulation model based on the current change rate, adjust the voltage according to the current change, and trigger voltage reduction protection when the threshold is exceeded;

[0047] Step S4, multi-parameter real-time monitoring: Extract the noise spectrum characteristics, synchronously collect the current signal and calculate the power spectral density. When the proportion of 1 / f noise exceeds the threshold, it is determined as the surface defect formation stage;

[0048] Step S5, pore size prediction and feedback termination: Predict the pore size based on the double-parameter model, and stop breakdown when the pore size is close to the target value, the current slope changes suddenly, or the cumulative charge amount exceeds the limit. Specifically, stop breakdown when any of the following is satisfied:

[0049] D predict ≥D target ×9500,

[0050] Sudden change in current slope (▽ 2 I>10 6 pA / s 2 ),

[0051] Cumulative charge amount Q>50nC;

[0052] Step S6, post-treatment and verification: Perform in-situ impedance calibration on the prepared nanopores, apply an AC signal with a frequency of 10 - 100 kHz, and calculate the pore size correction value by fitting the Nyquist curve;

[0053] Step S3, the adaptive voltage regulation model formula in dynamic voltage gradient control is as follows:

[0054]

[0055] In the formula, ΔV is the voltage regulation amount (the voltage step dynamically adjusted according to the real-time current change rate, which determines the voltage increase or decrease amplitude in the next stage), k is the material attenuation coefficient (reflecting the response characteristics of the membrane material to the electric field change, calibrated through experiments, used to suppress overshoot voltage), is the current change rate (characterizing the change speed of the current over time, serving as a feedback signal to drive voltage regulation), n is the non-linear regulation index (amplifying the regulation weight in the stage of high current change rate, accelerating the response to dangerous working conditions), V offset is the voltage reference offset (providing basic voltage compensation, preventing the regulation amount from approaching zero at low current change rate, ensuring the continuous progress of the breakdown process).

[0056] Step S2, the parameter initialization specifically includes the following steps:

[0057] Step S21: Measure the initial leakage current at low voltage to verify the integrity of the membrane. When the leakage current is abnormal, reprocess or replace the chip;

[0058] Step S22: Dynamically calculate the breakdown starting voltage threshold through material characteristics and surface modification parameters, and initiate the controllable breakdown process.

[0059] In Step S22, the calculation formula for the breakdown starting voltage threshold is:

[0060]

[0061] In the formula, V init is the breakdown starting voltage threshold (the initial breakdown voltage, preventing the membrane material from instantaneous breakdown caused by too high voltage), E breakdown is the material breakdown field strength (characterizing the breakdown resistance ability of the silicon nitride thin film under the action of the electric field, related to the material purity and lattice defect density), t SiNx is the thickness of the silicon nitride film (directly affecting the voltage threshold required for breakdown, the greater the film thickness, the higher the breakdown voltage), C surface is the surface modification layer capacitance (the interface capacitance formed by the PEI coating, reducing the surface electric field distortion), C bulk is the bulk capacitance (reflecting the capacitance characteristics of the unmodified SiNx film itself, related to the film thickness and dielectric constant).

[0062] Step S5, the two-parameter model formula in pore size prediction and feedback termination is:

[0063]

[0064] In the formula, Dpredict is the predicted pore diameter, α is the charge accumulation coefficient, I(τ) is the real-time current value, ∫I(τ)dτ is the current-time integral, β is the thermal effect coupling coefficient, V rms is the root mean square voltage value, t is the duration of the breakdown process, σ ion is the ionic conductivity of the solution.

[0065] In step S6, the formula for calculating the pore diameter correction value in post-processing and verification is:

[0066]

[0067] In the formula, D final is the final pore diameter of the modified nanopore (the systematic error of the prediction model is eliminated through impedance calibration to improve the accuracy of pore diameter measurement), D predict is the predicted pore diameter value, Z real is the real part of the nanopore impedance, Z ideal is the theoretical impedance of an ideal cylindrical nanopore.

[0068] The theoretical impedance Z of an ideal cylindrical nanopore ideal is calculated by the formula:

[0069]

[0070] In the formula, L is the membrane thickness, D predict is the predicted pore diameter, σ ion is the solution conductivity.

[0071] A specific application of this embodiment is:

[0072] Experimental materials and equipment

[0073] Chip: Silicon nitride (SiNx) thin film chip (thickness 20 nm, window size 50×50 μm 2 );

[0074] Electrolyte: 1M KCl solution (containing 1 mM Tris-EDTA buffer, pH 7.0);

[0075] Instruments: High-bandwidth current amplifier (bandwidth 200 kHz, input noise <1 pA / √Hz); Dual-channel programmable voltage source (resolution 0.1 mV); Multichannel data acquisition card (sampling rate 2 MS / s); PDMS microfluidic chamber (integrated Ag / AgCl electrode);

[0076] Implementation steps

[0077] 1. Chip pretreatment: Immerse the SiNx chip in 0.1% polyethyleneimine (PEI) solution for 10 minutes, take it out, rinse it 3 times with ultrapure water, dry it with nitrogen, and then assemble it into the PDMS chamber;

[0078] Inject the electrolyte and let it stand for 5 minutes to fully wet the membrane surface;

[0079] 2. Baseline parameter calibration: Apply a test voltage of 50 mV and measure the baseline current I0 = 0.3 nA to verify the membrane integrity;

[0080] Calculate the initial breakdown voltage range V based on the formula init = 5.2 V;

[0081] 3. Dynamic voltage regulation:

[0082] Start the adaptive voltage regulation algorithm: Initially apply a voltage V = 4.5 V. When the current slope reaches 3×10 3 pA / s, trigger the non - linear regulation mode;

[0083] Dynamically adjust the voltage increment according to the current change rate and gradually increase it to 6.8 V within 12 seconds;

[0084] 4. Noise spectrum assisted diagnosis:

[0085] Real - time calculate the power spectral density (PSD) of the current signal: At the breakdown start stage (t = 8 s), it is detected that the proportion of 1 / f noise rises to 65%, and it is determined to enter the surface defect expansion stage;

[0086] Trigger the voltage drop protection (ΔV = - 0.5 V) to prevent non - uniform breakdown;

[0087] 5. Aperture prediction and termination:

[0088] Real - time predict the aperture through a two - parameter model: When D predict = 4.7 nm (94% of the target aperture of 5 nm), activate the termination condition;

[0089] Detect that the cumulative charge Q = 42 nC, which does not exceed the safety threshold (50 nC), and normally terminate the breakdown;

[0090] 6. In - situ impedance calibration:

[0091] Apply an AC signal of 10 - 100 kHz and collect the Nyquist curve: Fit to obtain the impedance phase angle θ = - 72°, and calculate the corrected aperture D final = 4.9 nm;

[0092] Performance verification

[0093] 1. Morphology characterization: Transmission electron microscopy (TEM) imaging shows that the aperture is 5.1 ± 0.3 nm and the edge roughness < 0.5 nm;

[0094] 2. Electrical Test: The steady-state current I = 1.2 nA was measured under a bias voltage of 100 mV, with a deviation of <8% from the theoretical value (1.3 nA).

[0095] 3. Function Verification: λ-DNA (48.5 kbp) was injected into the chamber, and a characteristic blocking current signal was captured under a bias voltage of 120 mV:

[0096] The event duration τ = 1.2 ± 0.3 ms, which is consistent with the theoretical prediction for a 5-nm pore size;

[0097] The signal baseline noise level σ = 0.8 pA, meeting the requirements for single-molecule detection.

[0098] In the description of this specification, the descriptions referring to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials, or characteristics described in connection with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0099] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the present invention, so that those skilled in the art in the relevant technical field can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A method for preparing solid-state nanopores by automated controllable breakdown, characterized in that, Including the following steps: Step S1, Pretreatment and Chip Assembly: Immerse the silicon nitride thin film chip in a polyethyleneimine solution to form a uniform positive charge layer through electrostatic adsorption. After rinsing with deionized water and drying with nitrogen, load the chip into the flow cell; Step S2, Parameter Initialization: Measure the initial leakage current at a low voltage, verify the integrity of the membrane, and calculate the initial voltage range; Step S3, Dynamic Voltage Gradient Control: Adopt an adaptive voltage regulation model based on the current change rate, adjust the voltage according to the current change, and trigger a voltage step-down protection when the threshold is exceeded; Step S4, Multi-parameter Real-time Monitoring: Extract the noise spectrum characteristics, synchronously collect the current signal and calculate the power spectral density. When the proportion of 1 / f noise exceeds the threshold, it is determined as the surface defect formation stage; Step S5, Aperture Prediction and Feedback Termination: Predict the aperture based on a two-parameter model, and stop breakdown when the aperture is close to the target value, the current slope changes suddenly, or the cumulative charge amount exceeds the limit; Step S6, Post-treatment and Verification: Conduct in-situ impedance calibration on the prepared nanopores, apply an AC signal with a frequency of 10 - 100 kHz, and calculate the aperture correction value by fitting the Nyquist curve; In the said step S3, the formula of the adaptive voltage regulation model in dynamic voltage gradient control is: Where ΔV is the voltage regulation amount, k is the material attenuation coefficient, is the current change rate, n is the non-linear regulation index, and V offset is the voltage reference offset.

2. A method for automatically controllable breakdown preparation of solid-state nanopores according to claim 1, It is characterized in that In the said step S2, parameter initialization specifically includes the following steps: Step S21: Measure the initial leakage current at a low voltage, verify the integrity of the membrane. When the leakage current is abnormal, reprocess or replace the chip; Step S22: Dynamically calculate the breakdown starting voltage threshold through material characteristics and surface modification parameters, and start the controllable breakdown process.

3. The method for preparing a solid-state nanopore by automated controllable breakdown according to claim 2, wherein In the said step S22, the calculation formula of the breakdown starting voltage threshold is: Wherein, V init is the breakdown starting voltage threshold, E breakdown is the material breakdown field strength, t SiNx is the thickness of the silicon nitride film, C surface is the capacitance of the surface modification layer, C bulk is the bulk capacitance.

4. The method for preparing a solid-state nanopore by automated controllable breakdown according to claim 1, wherein In the said step S5, the formula of the two-parameter model in aperture prediction and feedback termination is: Where D predict is the predicted aperture, α is the charge accumulation coefficient, I(τ) is the real-time current value, ∫I(τ)dτ is the current-time integral, β is the thermal effect coupling coefficient, V rms is the root mean square voltage value, t is the duration of the breakdown process, σ ion is the ionic conductivity of the solution.

5. A method for preparing solid-state nanopores by automated controllable breakdown according to claim 1, characterized in that In the said step S6, the formula for calculating the aperture correction value in post-treatment and verification is: where D final is the final pore diameter of the corrected nanopore, D predict is the predicted pore diameter value, Z real is the real part of the nanopore impedance, and Z ideal is the theoretical impedance of an ideal cylindrical nanopore.

6. The method for preparing a solid-state nanopore by automated controllable breakdown according to claim 5, wherein The theoretical impedance Z of the ideal cylindrical nanopore ideal is calculated by the formula: where L is the film thickness, D predict is the predicted pore size, and σ ion is the solution conductivity.

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