A neuromorphic memristor based on thiophene organic polymer and a preparation method thereof

Abstract

The present invention discloses a neuromorphic memristor based on a thiophene organic polymer and a preparation method thereof, belonging to the field of preparation of organic diode memristive devices. The neuromorphic memristor includes a top electrode, an organic active layer, a bottom electrode and a substrate from top to bottom, and the organic active layer is prepared from a thiophene organic polymer poly(3-dodecylthiophene) PQT-12. The present invention uses PQT-12 as a key material to simulate the plasticity of biological synapses, realizes efficient information storage and processing. As the organic active layer, PQT-12 has excellent charge retention ability and low power consumption characteristics. The memristor prepared by the present invention exhibits excellent performance in terms of switching speed, stability and scalability, and has broad application prospects, especially in the fields of neuromorphic computing, low-power storage devices and artificial intelligence systems, etc.

Description

Technical Field

[0001] The present invention belongs to the field of preparation of organic diode memristive devices, and specifically relates to a neuromorphic memristor based on a thiophene organic polymer and a preparation method thereof. Background Art

[0002] With the continuous progress of technology, information technology and artificial intelligence (AI) technology have developed vigorously and have been widely applied in various fields, such as intelligent driving, AI translation, intelligent manufacturing, etc. However, the current computing of emerging technologies such as artificial intelligence that require processing a large amount of data adopts the traditional von Neumann architecture, which has an inherent energy efficiency bottleneck when performing neural computing. Its computing unit and storage unit are separated from each other, and a large amount of energy consumption and delay will be generated during data communication. This defect limits the development of emerging technologies and determines their upper limit. In contrast, the human brain can achieve efficient information perception, processing, and memory at extremely low power consumption. Therefore, developing devices that simulate the human brain or neural network for computing can break through the traditional von Neumann bottleneck and is a feasible method for efficient computing.

[0003] Previous studies have attempted to simulate human brain neurons and synapses based on complementary metal oxide semiconductors (CMOS). However, when the device is scaled down according to Moore's law, the leakage power consumption will become very large, thus limiting its operating frequency. In recent years, with the gradual failure of Moore's law, neuromorphic computing has gradually become a very promising technology. Its system has a high degree of interconnectivity and parallelism, can directly process data in memory, and at the same time maintains low energy consumption. The emerging artificial synaptic devices based on memristors, or called neuromorphic memristors, have attracted more and more research interest and attention in simulating the plasticity of brain synapses due to their advantages such as low power consumption, high data storage density, and fast operation. Internationally, the research on neuromorphic memristors mainly focuses on the selection of materials and the optimization of device performance. Among many memristor materials, polymer-based memristors are favored because of their excellent flexibility, processability, and relatively low production cost.

[0004] Thiophene organic polymers such as PQT-12 (poly(3-dodecylthiophene)) are widely used in organic electronic devices as an organic semiconductor material due to their good conductivity and thermal stability. The molecular structure of PQT-12 contains long-chain alkyl substituents, which not only enhance its solubility but also improve the charge mobility, making it have good prospects in the application of neuromorphic memristors. However, the current systematic research on thiophene organic polymers as neuromorphic memristor materials is still relatively scarce and has certain limitations and instabilities. Therefore, exploring the performance characteristics and application potential of thiophene organic polymer-based memristors has important theoretical value and practical significance. Summary of the Invention

[0005] The object of the present invention is to provide a thiophene-based organic polymer neuromorphic memristor and a preparation method thereof.

[0006] The thiophene-based organic polymer neuromorphic memristor provided by the present invention has a structure including a top electrode, an organic active layer, a bottom electrode and a substrate from top to bottom. The organic active layer is prepared from an organic polymer poly(3-dodecylthiophene) (PQT-12).

[0007] Further, the preparation method of the organic active layer is as follows:

[0008] Dissolve poly(3-dodecylthiophene) (PQT-12) in chloroform to prepare a poly(3-dodecylthiophene) solution. Using solution deposition technology, spin-coat the prepared solution into a film on a substrate with a bottom electrode.

[0009] Further, the concentration of the poly(3-dodecylthiophene) solution is 3 mg / ml, and the thickness of the organic active layer is 50 - 80 nm.

[0010] Further, the material of the bottom electrode is indium tin oxide. The bottom electrode is a layer of indium tin oxide grown on the surface of the substrate. The bottom electrode is the anode of the neuromorphic memristor, and the thickness of the bottom electrode is 130 - 150 nm.

[0011] Further, the material of the top electrode is aluminum. The top electrode is the cathode of the neuromorphic memristor, and the thickness of the top electrode is 90 - 120 nm.

[0012] Further, the material of the substrate is glass.

[0013] The present invention further includes a preparation method of the above thiophene-based organic polymer neuromorphic memristor, which is characterized by including the following steps:

[0014] Step 1: Grow a bottom electrode on the surface of the substrate. Ultrasonically clean the substrate with the bottom electrode in turn using ethanol, glass cleaner, and deionized water, and dry it with ordinary nitrogen, and then perform drying and ultraviolet ozone treatment;

[0015] Step 2: Dissolve poly(3-dodecylthiophene) in chloroform to prepare a poly(3-dodecylthiophene) solution. Spin-coat the poly(3-dodecylthiophene) solution evenly on the surface of the material treated in Step 2, and then put it into an oven for annealing treatment.

[0016] Step 3: Put the substrate with the organic active layer into a vacuum evaporation system, and obtain a top electrode on the organic active layer through evaporation treatment. After the top electrode is cooled, a thiophene-based organic polymer neuromorphic memristor is obtained.

[0017] Further, in the first step, the ultrasonic cleaning time of ethanol, glass cleaner, and ultrapure water is 25 - 30 min, the ultraviolet ozone treatment time is 10 - 15 minutes, and the drying temperature is set at 120°C.

[0018] Further, in the second step, the concentration of the poly(3-dodecylthiophene) solution is 3 mg / ml.

[0019] Further, in the second step, a pipette is used to spin-coat the poly(3-dodecylthiophene) solution onto the substrate with a bottom electrode processed in the first step to form a film, and then it is placed in an oven at 60°C for annealing for 30 minutes; the spin-coating process is as follows: first rotate at a low speed of 500 rpm for 9 s, and then rotate at a high speed of 3000 rpm for 30 s until an organic active layer with a set thickness is obtained, and the thickness of the organic active layer is 50 nm - 80 nm.

[0020] Further, in the third step, during the evaporation deposition process, the vacuum evaporation system is evacuated to a pressure in the chamber lower than 5×10 -4 Pa before starting to evaporate the top electrode. The evaporation rate of the top electrode is 1 - 3 Å / s, and a crystal oscillator is used to control the thickness of the top electrode. After the treatment is completed, the vacuum state is maintained until the top electrode cools to room temperature, and the cooling time of the top electrode is 20 - 30 minutes.

[0021] Compared with the prior art, the present invention has the following remarkable advantages:

[0022] 1) The memristor prepared by the present invention has the characteristics of low switching voltage and low power consumption, which makes it particularly advantageous in low-energy-consuming applications. Compared with some inorganic memristors, it can operate with a smaller voltage and current, reducing energy consumption and improving the long-term stability and reliability of the device.

[0023] 2) The memristor prepared by the present invention has the characteristics of simple structural design and easy operation, and can be processed by a solution deposition method (spin-coating), with low cost. This has an obvious cost advantage compared with the traditional preparation method of hard materials (such as vacuum evaporation), and can provide higher efficiency in large-area and high-throughput production.

[0024] 3) The memristor prepared by the present invention can simulate the behavior of neural synapses and has the ability of brain-like computing and neuromorphic processing. This makes it have application advantages in the fields of artificial intelligence, machine learning, etc. Compared with traditional electronic computing devices, it can efficiently execute neural network tasks and has a high parallel computing ability.

[0025] 4) PQT-12 in the organic active layer of the memristor prepared by the present invention is used as an organic material, which has good flexibility and is suitable for fields such as wearable devices and flexible electronic products. In addition, the thiophene organic polymer also has biocompatibility, making the memristor prepared by the present invention have potential in the fields of biomedicine and brain-like computing, etc. Description of the Drawings

[0026] Figure 1 Schematic structural diagram of the neuromorphic memristor based on thiophene polymer prepared by the present invention;

[0027] Figure 2 Schematic diagram of forward current-voltage of the neuromorphic memristor based on thiophene polymer prepared in Example 1 at room temperature;

[0028] Figure 3 Schematic diagram of reverse current-voltage of the neuromorphic memristor based on thiophene polymer prepared in Example 1 at room temperature;

[0029] Figure 4 Schematic diagram of forward conductance change of the neuromorphic memristor based on thiophene polymer prepared in Example 1 at room temperature;

[0030] Figure 5 Schematic diagram of reverse conductance change of the neuromorphic memristor based on thiophene polymer prepared in Example 1 at room temperature;

[0031] Figure 6 Schematic diagram of excitatory postsynaptic current (EPSC) synaptic function simulation of the neuromorphic memristor based on thiophene polymer prepared in Example 1;

[0032] Figure 7 Schematic diagram of paired-pulse facilitation synaptic function simulation of the neuromorphic memristor based on thiophene polymer prepared in Example 1;

[0033] Figure 8 Schematic diagram of paired-pulse inhibition synaptic function simulation of the neuromorphic memristor based on thiophene polymer prepared in Example 1;

[0034] Figure 9 Schematic diagram of post-tetanic potentiation synaptic function simulation of the neuromorphic memristor based on thiophene polymer prepared in Example 1;

[0035] Figure 10 Schematic diagram of potentiation and inhibition synaptic function simulation of the neuromorphic memristor based on thiophene polymer prepared in Example 1;

[0036] Figure 11 Schematic diagram of current response of the neuromorphic memristor based on thiophene polymer prepared in Example 1 to 10 different pulse amplitudes applied. Detailed Description of the Invention

[0037] The technical solution of the present invention will be described in detail below through embodiments, but the protection scope of the present invention is not limited to the described embodiments.

[0038] In the embodiment of the present invention, poly(3-dodecylthiophene) (PQT-12) was purchased from Sigma-Aldrich (Shanghai) Trading Co., Ltd.

[0039] The present invention provides a neuromorphic memristor based on a thiophene organic polymer and a preparation method thereof. The structure of the neuromorphic memristor is as Figure 1 shown, including a top electrode 1, an organic active layer 2, a bottom electrode 3, and a substrate 4 from top to bottom. As a whole, it is a vertical structure. Among them, the organic active layer is prepared from poly(3-dodecylthiophene).

[0040] The thiophene polymer poly(3-dodecylthiophene) PQT-12 has a good π-π conjugate structure, which can effectively improve the electron conduction performance. This enables it to perform better electron migration when used as an organic active layer in a memristor, enhancing the switching characteristics and response speed of the device. The advantage of using PQT-12 as the organic active layer compared to other thiophene-based organic polymers is that PQT-12 has a highly conjugated π-electron system, enhancing the charge transport ability, enabling more stable conductance regulation in the memristor device. Its thiophene conjugate main chain results in a higher electron mobility inside the material, reducing the scattering loss of electrons in the path, thereby enhancing the stability and response speed of the memristive effect. The long alkyl side chain (dodecyl) in the PQT-12 structure endows it with good solution processability and thin film forming ability, making it easy to form high-quality thin films by low-cost methods such as spin coating and spraying. The molecular structure of PQT-12 is conducive to the migration of ions / protons in the material, which is crucial for memristive devices. Compared with PEDOT, the memristive effect of PQT-12 is more stable and non-volatile, while the memristive effect of PEDOT mainly depends on ion doping / dedoping and is easily affected by the environment, resulting in poor information retention ability. In the present invention, PQT-12 regulates ion transition through an electric field and is suitable for fine synaptic function simulation, such as synaptic weight regulation, STDP (spike-timing-dependent plasticity), PPF (paired-pulse facilitation), etc. In addition, PQT-12 is compatible with organic semiconductor manufacturing processes and can be integrated with silicon-based CMOS, while the acidity of PEDOT will corrode metal electrodes and affect the lifespan of integrated circuits. Therefore, in the application of high-performance memristors and neuromorphic computing devices, the thiophene-based organic polymer PQT-12 has more advantages.

[0041] Example 1

[0042] (1) Select glass as the substrate, and deposit a layer of indium tin oxide on the glass as the bottom electrode with a thickness of 150 nm to form ITO conductive glass. Wash the ITO conductive glass successively with ethanol, glass cleaner, and ultrapure water for 30 min, then dry it with ordinary nitrogen and place it in an oven at 120 °C for 60 min to dry.

[0043] (2) Treat the dried ITO conductive glass with ultraviolet ozone for 15 min.

[0044] (3) Use a pipette to spin-coat a 3 mg / mL PQT-12 solution dissolved in chloroform on the ITO conductive glass, and anneal it in a drying oven at 60 °C for 30 minutes. The formed PQT-12 layer is the organic active layer. The spin-coating process is as follows: first rotate at a low speed of 500 rpm for 9 s, and then rotate at a high speed of 3000 rpm for 30 s until the thickness of the organic active layer reaches 60 nm.

[0045] (4) Place the prepared ITO conductive glass with the organic active layer into a vacuum evaporation equipment, control the pressure in the vacuum chamber to be 5×10 -4 Pa, and start evaporating the metal aluminum electrode as the top electrode with an evaporation rate of 1-3 Å / s and a thickness of 120 nm.

[0046] (5) After the evaporation experiment is completed, wait for the metal electrode to cool to room temperature in the vacuum chamber to obtain a neuromorphic memristor based on thiophene organic polymer. Then open the chamber and take out the neuromorphic memristor for relevant electrical performance tests.

[0047] (6) Performance test results:

[0048] Figure 2 and Figure 3 are the typical current-voltage (I-V) characteristic curves of the neuromorphic memristor under forward voltage scan and reverse voltage scan at room temperature, respectively. During the electrical test, the aluminum electrode (top electrode) is grounded, and an electrical signal is applied to the ITO electrode (bottom electrode). Under the positive voltage (0-6-0V) scan, the current corresponding to the neuromorphic memristor at 6V gradually increases, indicating that the overall conductive state of the neuromorphic memristor gradually increases; conversely, under the negative voltage (0--6-0V) scan, the current corresponding to the neuromorphic memristor at -6V gradually decreases, indicating that the overall conductive state of the neuromorphic memristor gradually decreases.

[0049] Figure 4 is the forward conductance change diagram of the neuromorphic memristor based on thiophene polymer prepared in Example 1 at room temperature, that is, the schematic diagram of the enhanced synaptic function simulation at room temperature. Figure 5Negative conductance change diagram of the thiophene polymer-based neuromorphic memristor prepared in Example 1 at room temperature, that is, the schematic diagram of simulating the inhibitory synaptic function at room temperature.

[0050] It can be clearly seen from Figure 3 and Figure 4 that under the test of periodic bipolar electrical signals, the neuromorphic memristor has a hysteretic non-characteristic curve in the electrical characteristics on the I-V plane, which is a typical feature of the memristor. The hysteresis phenomenon is essentially a manifestation of the memristor simulating the plasticity of neural synapses.

[0051] Figure 4 and Figure 5 Schematic diagram of the conductance change of the thiophene organic polymer-based neuromorphic memristor prepared in Example 1 at room temperature. In the memristor, the conductivity is similar to the synaptic weight. It can be seen from the figure that the change in conductivity is non-linear, which means that when a voltage is applied, the current does not simply change proportionally with the voltage. As a series of periodic electrical signals are applied to the neuromorphic memristor, the conductivity of the neuromorphic memristor changes, thus forming a memory effect in the neuromorphic memristor. This non-linear transmission characteristic enables the memristor to simulate the process of synaptic weight regulation.

[0052] Figure 6 Schematic diagram of simulating the excitatory postsynaptic current (EPSC) synaptic function of the thiophene organic polymer-based neuromorphic memristor prepared in Example 1. The generation of EPSC is usually a rapid transient process. Under the voltage stimulation of +6V, the current rises sharply and quickly reaches the peak, and then gradually decreases with time.

[0053] Figure 7 and Figure 8 Schematic diagrams of paired-pulse facilitation (PPF) and paired-pulse depression (PPD) synaptic function simulations of the thiophene organic polymer-based neuromorphic memristor prepared in Example 1. In neural synapses, paired-pulse facilitation (PPF) and paired-pulse depression (PPD) respectively represent the effects of two stimuli with short time intervals on synaptic transmission. When the time interval between the two pulses is short (6V, 100ms), the response caused by the second pulse is stronger than that of the first pulse, and this phenomenon is called facilitation. It usually represents the enhancement of the postsynaptic response, that is, the enhancement of synaptic weight, and this effect simulates the short-term potentiation (STP) process in neural synapses; on the contrary, paired-pulse depression means that when the time interval between the two pulses is short, the response of the second pulse is weaker than that of the first pulse, and this phenomenon reflects the inhibition of the postsynaptic response, simulating the short-term depression (STD) process in neural synapses.

[0054] Figure 9Schematic diagram of the neuromorphic memristor of the thiophene organic polymer prepared in Example 1 simulating post-tetanic potentiation (PTP) synaptic function. Similar to PPF, post-tetanic potentiation (PTP) refers to the continuous enhancement of the strength of synaptic weight after high-frequency stimulation. When a continuous positive voltage signal (6V, 100 ms) is applied to the neuromorphic memristor, the current continuously increases, forming an ascending curve.

[0055] Figure 10 Curve of the change in conductivity of the neuromorphic memristor of the thiophene organic polymer prepared in Example 1 under the application of continuous positive and negative pulses. Among them, (a) is the curve of the change in conductivity under the application of continuous positive pulses, and (b) is the curve of the change in conductivity under the application of continuous negative pulses. When a positive electrical signal (6V) is applied, the conductance gradually increases; when a negative electrical signal is applied, the conductance gradually decreases.

[0056] Figure 11 Schematic diagram of the current response of the neuromorphic memristor of the thiophene organic polymer prepared in Example 1 to the application of 10 different pulse amplitudes (6V, 7V, 8V, 9V). In the neuromorphic memristor, the change in the conductivity of the neuromorphic memristor is also affected by the change in pulse amplitude (voltage intensity). That is to say, the amplitude of the pulse determines the plasticity performance of the memristor, affecting the rise and fall of its conductivity. A series of pulse stimuli with different amplitudes (6V, 7V, 8V, 9V) are applied to the neuromorphic memristor. The results show that the larger the voltage amplitude, the larger the overall level of synaptic weight.

[0057] In summary, the present invention lays a foundation for exploring neuromorphic memristors based on thiophene organic polymers and promotes the research of neuromorphic memristors. The neuromorphic memristor prepared by the present invention is expected to be widely used in fields such as intelligent hardware, neuromorphic computers, autonomous driving, and robots, contributing to the development of future technologies.

[0058] As described above, although the present invention has been shown and described with reference to specific preferred embodiments, it should not be construed as a limitation of the present invention itself. Various changes can be made in its form and details without departing from the spirit and scope of the present invention.

Claims

1. A neuromorphic memristor based on thiophene organic polymer, characterized in that: The neuromorphic memristor realizes memristive characteristics based on electrical signals. The neuromorphic memristor includes a top electrode, an organic active layer, a bottom electrode and a substrate from top to bottom. The organic active layer is made of PQT-12. The preparation method of the organic active layer is as follows: PQT-12 is dissolved in chloroform to prepare a PQT-12 solution, and then the PQT-12 solution is spin-coated on a substrate with a bottom electrode, and after film formation, the solution is placed in an oven at 60° C. for annealing to form an organic active layer; The concentration of the PQT-12 solution is 3 mg / ml, and the thickness of the organic active layer is 50-80 nm.

2. The neuromorphic memristor according to claim 1, characterized in that The material of the top electrode is metal aluminum; the material of the bottom electrode is indium tin oxide; and the material of the substrate is glass.

3. The neuromorphic memristor according to claim 1, characterized in that The thickness of the top electrode is 90-120 nm; the thickness of the bottom electrode is 130-150 nm.

4. The method for preparing a neuromorphic memristor according to any one of claims 1 to 3, characterized in that: The steps include: Step 1: The substrate with the bottom electrode is cleaned with ethanol, glass cleaning agent, and deionized water ultrasonically in sequence, dried with nitrogen, and then dried and treated with ultraviolet ozone; Step 2: dissolving PQT-12 in chloroform to prepare a PQT-12 solution, and evenly spin-coating the PQT-12 solution on the substrate with the bottom electrode obtained in step 1, and then placing it in an oven for annealing to obtain a substrate with an organic active layer; Step 3: Place the substrate with the organic active layer into a vacuum evaporation system, obtain a top electrode on the organic active layer through evaporation treatment, and obtain a neuromorphic memristor based on thiophene organic polymer after the top electrode is cooled.

5. The preparation method according to claim 4, characterized in that: In the step 2, the PQT-12 solution is spin-coated on the substrate with the bottom electrode by means of a pipette gun to form a film, and then placed in an oven at 60° C. for annealing for 20 to 30 minutes.

6. The preparation method according to claim 4, characterized in that: In the step 2, the spin coating process is: firstly rotating at a low speed of 500 rpm for 9 s, and then rotating at a high speed of 3000 rpm for 30 s, until an organic active layer of a set thickness is obtained.

7. The preparation method according to claim 4, characterized in that: In the step 1, the ultrasonic cleaning time of ethanol, glass cleaning agent and ultrapure water is 25 to 30 minutes, and the ultraviolet ozone treatment time is 10 to 15 minutes.

8. The preparation method according to claim 4, characterized in that: In the step 3, during the evaporation process, the vacuum evaporation system is evacuated to a pressure in the chamber lower than 5×10 -4 Pa, the top electrode was deposited at a rate of 1-3 Å / s. A crystal oscillator was used to control the thickness of the top electrode. After the treatment, the vacuum state was maintained until the top electrode cooled to room temperature.

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