CN109449286B - Phase-change nanoparticle-embedded nitride memristor and preparation method thereof - Google Patents

Phase-change nanoparticle-embedded nitride memristor and preparation method thereof Download PDF

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CN109449286B
CN109449286B CN201811175304.6A CN201811175304A CN109449286B CN 109449286 B CN109449286 B CN 109449286B CN 201811175304 A CN201811175304 A CN 201811175304A CN 109449286 B CN109449286 B CN 109449286B
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曾飞
万钦
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Tsinghua University
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Abstract

The invention discloses a phase-change nanoparticle-embedded nitride memristor and a preparation method thereof. The preparation method comprises the following steps: depositing an inert metal on the substrate as a bottom electrode; depositing a layer of nitride or oxynitride film on the bottom electrode, and simultaneously depositing a small amount of transition metal into the nitride or oxynitride film; adding a mask plate on the medium layer, depositing inert metal on the mask plate to be used as a top electrode, and removing the mask plate; and negative bias is adopted between the top electrode and the bottom electrode, so that phase-change nano-particles which penetrate through the dielectric layer and are gathered into bundles are formed in the dielectric layer. The memristor has a coding function under the action of the periodic strong input pulse, has memory and learning functions after the strong input pulse is finished, and can well simulate the calculation and learning functions of the neural synapse.

Description

Phase-change nanoparticle-embedded nitride memristor and preparation method thereof
Technical Field
The invention relates to a phase-change nanoparticle-embedded nitride memristor and a preparation method thereof, and belongs to the technical field of information electronic materials.
Background
The adoption of memristors to simulate the plasticity of the nerve synapses and the realization of brain-like computation is a common concern of scientists and engineers in the fields of information, materials, computers and neuroscience. Many memristors, such as various metal oxides, have been invented to be able to mimic synaptic plasticity and learning functions. However, these devices have properties far different from those of real biological synapses, such as unclear working medium and unclear mechanism, and the working mode is still far different from that of real synapses. For example, phase change memristors (Kuzum, d., Jeyasingh, r.g.d., Lee, B. & Wong, h.s.p. nanoelectronic programmable metals based on phase change materials for broad-embedded computing. Nano let.12, 2179-2186(2012)) reported and widely cited on Nano Letters, employ phase change materials whose resistance gradually changes under external pulse stimulation, similar to the synaptic plasticity changes observed in neuroscience. However, such materials and structures mimic neurosynaptic plasticity in terms of electrical response, but do not reflect the kinetic processes of ion flow, neurotransmitter release, and gated ion channels within the biological synapse. This is only a physical but not a physical one, and the computational function of the real synapse is not reflected.
Therefore, there is an urgent need to find materials and devices with behavior, efficiency and dynamics processes closer to the biological synapse properties, so as to really advance towards brain-like computing.
Disclosure of Invention
The invention aims to provide a phase-change nanoparticle-embedded nitride memristor and a preparation method thereof, wherein the memristor has the functions of coding and learning, can convert a periodically input stimulation signal into another periodically input signal to be output without any external modulation circuit, and the overall conductivity (resistivity) of a device is changed for a long time after stimulation, namely the long-term memory and learning effects.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides a phase-change nanoparticle-embedded nitride memristor, which comprises a bottom electrode, a dielectric layer and a top electrode which are sequentially arranged on a substrate, and is characterized in that: the dielectric layer is a nitride or oxynitride film which is doped with transition metal and is arranged on one surface of the bottom electrode; applying continuous negative bias with the amplitude of 2-6V between the bottom electrode and the top electrode to convert the doped transition metal into phase-change nano particles embedded in the nitride or oxynitride film in a pulse impact or continuous scanning mode;
the nitride comprises gallium nitride, aluminum nitride, silicon nitride, boron nitride and indium nitride; the nitrogen oxides comprise gallium oxynitride, aluminum oxynitride, silicon oxynitride, boron oxynitride and indium oxynitride.
Further, the phase-change nanoparticles are gathered into bundles and penetrate through the nitride or oxynitride film, and the width of the phase-change nanoparticle bundles is 20-100 nm.
The invention also provides a preparation method of the nitride memristor, which comprises the following steps:
1) depositing a layer of inert metal on any substrate by adopting an electron beam evaporation method, a thermal evaporation method, a magnetron sputtering method or an ion sputtering method to form the bottom electrode;
2) magnetron sputtering is adopted on the top surface of the formed bottom electrodeDepositing the nitride or oxynitride film by using a method of ion sputtering, chemical vapor deposition or atomic layer deposition, wherein a deposition rate a is adopted; depositing any one of transition metal elements including vanadium, chromium, tantalum, molybdenum, yttrium, hafnium, tungsten and niobium by adopting a magnetron sputtering method, an ion sputtering method, a chemical vapor deposition method or an atomic layer deposition method while depositing the nitride or oxynitride film, wherein the deposition rate b is adopted; controlling the atomic percentage A of the transition metal element and the metal ion element in the nitride or oxynitride film by adjusting the relative sizes of a and brateUniformly dispersing the transition metal elements in the nitride or oxynitride film in a ratio of 1:100 to 1: 10;
3) adding a mask plate on the top surface of the formed nitride or oxynitride film, depositing a layer of inert metal on the mask plate by adopting an electron beam evaporation method, a thermal evaporation method, a magnetron sputtering method or an ion sputtering method, and removing the mask plate after the top electrode is formed;
4) and applying a negative pulse bias voltage with the amplitude of 2-6V between the top electrode and the bottom electrode, and forming phase change nano particles which penetrate through and are gathered into bundles in the nitride or oxynitride film after 20-200 continuous pulse impacts.
The invention has the following characteristics:
the memristor of the present invention has signal encoding and learning functions, including but not limited to:
1) for a periodic pulse input signal with the voltage amplitude higher than 2V, modulating and outputting the periodic signal again, wherein the waveform, the amplitude and the frequency of the output signal are changed and are changed along with the change of the input frequency; the peak value of the output signal is periodically oscillated along with the number of the input signals, and the oscillation waveform, the amplitude and the frequency are changed along with the frequency of the input signals;
2) for a periodic pulse input signal with the voltage amplitude lower than 1V, the output signal and the input signal have no obvious difference;
3) for a periodic pulse input signal with the voltage amplitude of 1V-2V, the change of an output signal is between the two, and the change regularity of the output signal is not strong;
4) firstly inputting a pulse signal with the voltage amplitude lower than 1V, reading the initial state of the system, which is represented by the conductivity or the resistivity, then inputting a group of periodic pulse input signals with the voltage amplitude higher than 2V, then inputting a pulse signal with the voltage amplitude lower than 1V, and reading the final state of the system, which is represented by the conductivity or the resistivity; calculating the ratio of the two low-voltage impulse responses to obtain the weight change or long-term change of the memristor, wherein the weight ratio is expressed in percentage, and the learned state and result; a weight value greater than 100, called enhanced plasticity, indicates memory and learning formation; a weight value less than 100 is called inhibitory plasticity, indicating forgetfulness.
The invention has the following advantages:
1) because the nitride or oxynitride film is used as a substrate, and the phase-change nanoparticles are oxides, the size of the phase-change nanoparticles is limited to be between 2 nanometers and 10 nanometers, and the phase-change nanoparticles are not easy to grow up, and the nanoparticles can be inhibited from being communicated to form a whole; each nanoparticle may work alone or in conjunction with other nanoparticles.
2) Under the action of an external voltage, the phase-change nano particles are gathered into bundles and penetrate through the nitride film to form a conductive channel. The phase-change nano-particles are not dispersed in the nitride or oxynitride film, so that the current flows along the channels gathered into bundles, but randomly passes through a certain position of the film, and the directional transmission of neurotransmitters and electric signals from a certain position of an anterior synapse to the next position of a posterior synaptic is simulated.
3) Under the action of a strong input signal, the peak value of an output signal is in periodic oscillation, and the method is suitable for researching signal processing of the memristor by adopting Fourier transform. A plurality of information such as frequency, amplitude, components and the like of the signals can be obtained from Fourier change, and the signals can be analyzed by using a classical signal processing principle to obtain a calculation rule or rule of the memristor.
4) After the action of the strong input signal, the state (such as conductance and resistance) of the memristor can be permanently changed, the states before and after the strong input signal can be read by using the weak input signal (without changing the state of the memristor), and the weight change, namely the effective learning strength, can be calculated. By permanent changes, memory is formed, so that its learning process can be analyzed. The memristor can well simulate the calculation and learning functions of the nerve synapse.
5) The response of a memristor, whether for a strong input or a weak input signal, is input frequency dependent, being a learning mode of frequency dependent plasticity. The frequency dependent mode can analyze the learning and memorizing process by applying the theory of signal processing.
Drawings
FIG. 1 is a cross-sectional view of an overall structure of a memristor in an embodiment of the present invention.
FIG. 2 is a top view of a memristor of an embodiment of the present disclosure.
FIG. 3 is a schematic diagram of the distribution of the nitride thin film layer and the phase-change nanoparticles of the present invention.
FIG. 4 is a typical voltage-current cycling scan plot of a memristor under a forward bias condition in accordance with an embodiment of the present disclosure.
FIG. 5 is a typical voltage-current cycling scan plot of a memristor under a negative bias condition in accordance with embodiments of the present disclosure.
Fig. 6 is a current response curve plotted at points a and B in fig. 4 or fig. 5, respectively, after 100 consecutive voltage-current cycle scans of the memristor according to the embodiments of the present invention.
FIG. 7 is a graph showing the response of a strong input (high voltage amplitude) pulse typical of an embodiment of the present invention, wherein the impulse responses at frequencies of 1Hz, 5Hz, 10Hz, and 20Hz are shown in a, and the impulse responses at frequencies of 40Hz, 60Hz, and 80Hz are shown in b.
FIG. 8 is a long-term response that embodies the memristor learning functional characteristics of embodiments of the present invention.
Detailed Description
The experimental procedures used in the following examples are all conventional procedures unless otherwise specified.
Materials, reagents and the like used in the following examples are commercially available unless otherwise specified.
The present invention is further described with reference to the following drawings and specific embodiments, but the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
The invention provides a phase-change nanoparticle-embedded nitride memristor, which comprises a bottom electrode, a dielectric layer and a top electrode, wherein the bottom electrode, the dielectric layer and the top electrode are sequentially arranged on a substrate; the dielectric layer is a nitride or oxynitride film which is doped with transition metal and is arranged on one surface of the bottom electrode; and applying continuous negative bias with the amplitude of 2-6V between the bottom electrode and the top electrode to convert the doped transition metal into phase-change nano particles embedded in the nitride or oxynitride film in a pulse impact or continuous scanning mode.
The nitride includes gallium nitride, aluminum nitride, silicon nitride, boron nitride, and indium nitride; the nitrogen oxides include gallium oxynitride, aluminum oxynitride, silicon oxynitride, boron oxynitride, and indium oxynitride. Further, the nitride or oxynitride film may have a thickness of 50 to 150 nm.
The bottom electrode and the top electrode are respectively made of platinum, gold or palladium; the top electrode is used as a signal input end, and the bottom electrode is used as a signal output end.
The material of the phase-change nano particles comprises oxides of several transition metals of vanadium, chromium, tantalum, molybdenum, yttrium, hafnium, tungsten and niobium.
Further, the average size of the phase-change nano-particles is between 2nm and 10nm, and the phase-change nano-particles can be converted between an amorphous phase and any one of crystalline phases.
Furthermore, the phase-change nanoparticles are gathered into bundles and penetrate through the nitride or oxynitride film, and the width of the phase-change nanoparticles is 20-100 nm.
Further, the thickness of each of the bottom electrode and the top electrode is 50-300 nm.
The invention also provides a preparation method of the memristor, which comprises the following steps:
1) depositing a layer of inert metal (including Au, Pt or Pd) on any substrate (preferably an insulating substrate) by adopting an electron beam evaporation method, a thermal evaporation method, a magnetron sputtering method or an ion sputtering method to form the bottom electrode;
2) depositing the nitride or oxynitride film on the top surface of the formed bottom electrode by adopting a magnetron sputtering, ion sputtering, chemical vapor deposition or atomic layer deposition method, wherein the deposition rate is a; depositing any one of transition metal elements including vanadium, chromium, tantalum, molybdenum, yttrium, hafnium, tungsten and niobium by adopting a magnetron sputtering method, an ion sputtering method, a chemical vapor deposition method or an atomic layer deposition method while depositing the nitride or oxynitride film, wherein the deposition rate is b; controlling the atomic percentage A of the transition metal elements (comprising vanadium, chromium, tantalum, molybdenum, yttrium, hafnium, tungsten and niobium) and the metal ion elements (comprising gallium, aluminum, silicon, boron and indium) in the nitride or oxynitride film by adjusting the relative sizes of a and brateThe ratio of the transition metal element to the nitrogen oxide film is 1:100 to 1:10, so that the transition metal element is uniformly dispersed in the nitride or nitrogen oxide film;
3) adding a mask plate on the top surface of the formed nitride or oxynitride film, depositing a layer of inert metal (including Au, Pt or Pd) on the mask plate by adopting an electron beam evaporation method, a thermal evaporation method, a magnetron sputtering method or an ion sputtering method to form the top electrode, and then removing the mask plate;
4) and applying a negative pulse bias voltage with the amplitude of 2-6V between the top electrode and the bottom electrode, and forming phase change nano particles which penetrate through and are gathered into bundles in the nitride or oxynitride film after 20-200 continuous pulse impacts.
Further, in the step 4), the pulse width of the applied negative pulse bias is 20 mus to 100ms, the pulse frequency is controlled to be 0.1Hz to 1000Hz, the width of the phase-change nanoparticle beam is increased along with the increase of the pulse frequency, and the number of the phase-change nanoparticle beam is increased along with the increase of the pulse frequency.
Further, the mask plate is a metal plate provided with a circular hole pattern, a straight line pattern, an arc line pattern or a line pattern, the metal plate is made of stainless steel or chromium, and when the mask plate is the metal plate provided with the circular hole pattern, the diameter of the circular hole is 100 nm-0.5 mm.
The following are examples of the present invention: Pd/Nb-doped AlNO/Pd memristor and preparation method thereof
The overall structure of the memristor provided by the embodiment of the invention is shown in the figures 1 and 2, and the memristor comprises a structure with SiO on the surface2The Si substrate is sequentially provided with a Pd bottom electrode, a Nb-doped AlNO film and a Pd bottom electrode; by applying a continuous negative pulse bias voltage with an amplitude larger than 2V (the specific voltage amplitude adopted in the embodiment is 4V) between the Pd bottom electrode and the Pd top electrode, the doped Nb is converted into phase-change nanoparticles embedded in the AlNO thin film. The thicknesses of the Pd bottom electrode, the Nb-doped AlNO thin film, and the Pd bottom electrode in this example are 150nm, 100nm, and 150nm, respectively.
The preparation method of the memristor comprises the following steps:
1) bringing a commercially available surface with SiO2The Si substrate is sequentially cleaned by acetone, alcohol and deionized water for 4-8 minutes in an ultrasonic way and is dried by nitrogen. And putting the Si substrate into a vacuum chamber substrate table, and depositing a layer of 150nm Pd on the substrate by methods such as electron beam evaporation, thermal evaporation, magnetron sputtering or ion sputtering to form a Pd bottom electrode.
2) Depositing a 100nm aluminum oxynitride film on one surface of the Pd bottom electrode by adopting a magnetron sputtering, ion sputtering, chemical vapor deposition or atomic layer deposition method, wherein the deposition rate is a; and depositing the Nb transition metal element by adopting a magnetron sputtering, ion sputtering, chemical vapor deposition or atomic layer deposition method while depositing the aluminum oxynitride film, wherein the deposition rate b is adopted. The relative sizes of a and b are adjusted to control the atomic percent of Al/Nb to be between 1:100 and 1:10 (1: 80 in the embodiment). The Nb-doped AlNO thin film is formed by this step.
3) And adding a metal mask plate with a circular hole pattern (the diameter is 0.25mm) on one surface of the formed Nb-doped AlNO thin film, then depositing 150nm Pd of the top electrode by adopting methods such as electron beam evaporation, thermal evaporation, magnetron sputtering or ion sputtering, and removing the mask plate to obtain the initial state of the memristor. As shown in fig. 1 and 2.
4) Applying a negative pulse bias with an amplitude of 2V-6V (the specific amplitude used in this embodiment is 4V) between the top electrode and the bottom electrode (the pulse width is 20 mus-100 ms, the pulse frequency is 0.1 Hz-1000 Hz, such as 10ms and 100Hz, for example), after 20-200 (such as 100) pulses impact, forming phase-change nanoparticles niobium oxide, and the niobium oxide nanoparticles are gathered into a bundle and Nb is doped with AlNO thin film, as shown in FIG. 3, the ellipses with different sizes are nanoparticles, and when a continuous negative bias is applied, many phase-change nanoparticles gradually appear, and extend from the bottom electrode to the top electrode, forming a conductive filament gathered into a bundle by the phase-change nanoparticles.
Or the step 4) can be replaced by the following steps:
after about 4 scans between the top and bottom electrodes with a negative bias of 2V to 6V (the specific amplitude of 4V used in this example), phase-change nano-particles niobium oxide were formed and the niobium oxide nano-particles aggregated into bundles and Nb-doped AlNO thin film, as shown in fig. 3.
The validity of the embodiment of the invention is verified as follows:
to verify the electrical properties of an embodiment of the present invention, pulse signals of different amplitudes, frequencies and widths were applied to the bottom and top electrodes, and the correspondence of the present memristor to the input pulse signals was observed, including but not limited to the following points:
property 1, negative differential resistance occurs on the dc voltage current curve, whether biased positively or negatively. As shown in fig. 4 and 5, the graphs of the typical voltage-current cycle scanning are as follows: whether biased positively or negatively, the peak of the current appears at point a, which is a voltage less than the maximum scan voltage; the current value at point B is the maximum scan voltage current value.
Property 2, the maximum current value of each scanning can be extracted from the voltage-current curve obtained after continuous scanning, and each maximum current value oscillates regularly along with the change of the scanning times. As shown in fig. 6, is a typical variation of the peak value of the scan current: after continuous 100 times of voltage and current cyclic scanning, respectively taking current response curves drawn by points A and B in fig. 4 or 5; wherein point A is in a sine oscillation rising mode, point B is in a trend of descending first and then gradually rising, and in figure 6, variable IVIs each time the scanning voltage is maximumCurrent value of ground voltage, IPIs the maximum current value in each scan.
Property 3, the present memristor has a signal encoding function. In the response of a typical strong input pulse (-4V square wave), also called short-time range plasticity, the weight calculation method is:
Figure BDA0001823553990000061
wherein IAIs the peak value of each pulse, N represents the nth pulse, and-4V is the amplitude of the input pulse. It can be seen that the weight (as indicated by the ordinate) is a function of the frequency f and the number of pulses N (as indicated by the abscissa) and that the output response is very regular, with a periodic variation curve. As shown in a and b in FIG. 7, the memristor is proved to have a good signal coding function.
Property 4, the present memristor has a typical learning function. This memristor state was read with a small voltage pulse (-1.5V square wave pulse) before the strong input of fig. 7, then stimulated to act on the memristor with a set of strong pulses as used in fig. 7, and then read again with a small voltage pulse. The weight calculation method comprises the following steps: wN(I(-1.5V))＝IN(-1.5V)/I0(-1.5V). Where N refers to the Nth strong pulse and-1.5V is the amplitude of the read pulse. The weights calculated from the peaks (squares as shown in fig. 8) have typical frequency selectivity, i.e., the characteristic of low frequency (frequency of 10Hz) suppression (weight less than 100), high frequency (frequency greater than 50Hz) enhancement (weight greater than 100), conforming to the typical frequency-dependent plasticity (spike-rate-dependent plasticity) learning mode of neuroscience.
In addition, for a periodic pulse input signal with a voltage amplitude lower than 1V, the output signal of the memristor is not obviously different from the input signal. For a periodic pulse input signal with the voltage amplitude of 1V-2V, the change of the output signal of the memristor is between the two, and the change regularity of the output signal is not strong.
In summary, the memristor provided by the invention has the following characteristics:
1) for a periodic pulse input signal with a voltage amplitude higher than 2V, the periodic signal is remodulated and output, as described in property 3, i.e. a signal coding function is provided. The waveform, amplitude and frequency of the output signal vary and vary with the input frequency. The peak value of the output signal is periodically oscillated along with the number of the input signals, and the oscillation waveform, the amplitude and the frequency are changed along with the frequency of the input signals.
2) For a periodic pulse input signal with the voltage amplitude lower than 1V, the output signal has no obvious difference from the input signal.
3) For a periodic pulse input signal with the voltage amplitude of 1V-2V, the change of an output signal is between the two, and the change regularity of the output signal is not strong.
4) Firstly inputting a pulse signal with the voltage amplitude lower than 1V, reading the initial state of the system, which is represented by the conductivity or the resistivity, then inputting a group of periodic pulse input signals with the voltage amplitude higher than 2V, then inputting a pulse signal with the voltage amplitude lower than 1V, and reading the final state of the system, which is represented by the conductivity or the resistivity. And calculating the ratio of the two low-voltage impulse responses before and after the low-voltage impulse response to obtain the change or long-term change of the weight of the system, wherein the weight ratio is expressed in percentage, and the state and the result after learning. The weight value is more than 100, which is called enhanced plasticity; a weight value less than 100 is called suppressed plasticity. As described in property 4.

Claims (10)

1. The utility model provides a nitride memristor that phase transition nanoparticle inlayed, is including being located bottom electrode, dielectric layer and the top electrode that sets gradually on the basement, its characterized in that: the dielectric layer is a nitride or oxynitride film which is doped with transition metal and is arranged on one surface of the bottom electrode; applying continuous negative bias with the amplitude of 2-6V between the bottom electrode and the top electrode in a pulse impact or continuous scanning mode to convert the doped transition metal into phase-change nanoparticles embedded in the nitride or oxynitride film;
the nitride is selected from gallium nitride, aluminum nitride, silicon nitride, boron nitride or indium nitride; the nitrogen oxide is selected from gallium oxynitride, aluminum oxynitride, silicon oxynitride, boron oxynitride or indium oxynitride.
2. The nitride memristor according to claim 1, wherein the phase-change nanoparticle material is selected from oxides of any of the above transition metals of vanadium, chromium, tantalum, molybdenum, yttrium, hafnium, tungsten, or niobium.
3. The nitride memristor according to claim 1, wherein the thickness of the nitride or oxynitride thin film is 50-150 nm.
4. The nitride memristor according to claim 1, wherein the average size of the phase-change nanoparticles is 2-10 nm, and the phase-change nanoparticles can be converted between an amorphous phase and any one of crystalline phases.
5. The nitride memristor of claim 1, wherein the bottom electrode and the top electrode are each made of an inert metal comprising platinum, gold, or palladium.
6. The nitride memristor according to claim 1, wherein the phase-change nanoparticles are gathered into a bundle, and the width of the bundle of phase-change nanoparticles is between 20 nm and 100nm throughout the nitride or oxynitride thin film.
7. A method of fabricating the nitride memristor according to any one of claims 1 to 6, comprising the steps of:
1) depositing a layer of inert metal on any substrate by adopting an electron beam evaporation method, a thermal evaporation method or an ion sputtering method to form the bottom electrode;
2) depositing the nitride or oxynitride film on the top surface of the formed bottom electrode by ion sputtering, chemical vapor deposition or atomic layer deposition at a deposition rate a; depositing any one of transition metal elements including vanadium, chromium, tantalum, molybdenum, yttrium, hafnium, titanium,Tungsten and niobium, with a deposition rate b; controlling the atomic percentage A of the transition metal element and the metal ion element in the nitride or oxynitride film by adjusting the relative sizes of a and brateUniformly dispersing the transition metal elements in the nitride or oxynitride film in a ratio of 1:100 to 1: 10;
3) adding a mask plate on the top surface of the formed nitride or oxynitride film, depositing a layer of inert metal on the mask plate by adopting an electron beam evaporation method, a thermal evaporation method or an ion sputtering method, and removing the mask plate after the top electrode is formed;
4) and applying a negative pulse bias voltage with the amplitude of 2-6V between the top electrode and the bottom electrode, and forming phase change nano particles which penetrate through and are gathered into bundles in the nitride or oxynitride film after 20-200 continuous pulse impacts.
8. The method according to claim 7, wherein the step 4) is replaced by the following steps:
and after negative bias with the amplitude of 2-6V is applied between the top electrode and the bottom electrode for continuous scanning, phase change nano particles penetrating and gathering into bundles are formed in the nitride or oxynitride film.
9. The preparation method according to claim 7, wherein in the step 3), the mask plate is a metal plate provided with a circular hole pattern, a straight line pattern, an arc pattern or a line pattern, and the metal plate is made of stainless steel or chromium; when the mask plate is a metal plate provided with a circular hole pattern, the diameter of the circular hole is 100 nm-0.5 mm.
10. The method according to claim 7, wherein the negative pulse bias voltage is applied in step 4) with a pulse width of 20 μ s to 100ms and a pulse frequency of 0.1Hz to 1000 Hz.
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