Introduction

Since 1950s, information technology revolutions have greatly changed human life. The rapid development of the semiconductor technology boosts calculation speed and memory capacity of computer, as a result the computer has exceeded human brain in many aspects such as chess playing arithmetic calculation and information broadcasting1,2,3. However, a classical computer based on Von Neumann architecture usually processes the information in a sequential procedure and accompanies a lot of data exchange and communication between central processing unit (CPU) and data storage modules. These will complex the information processing and decrease the data processing efficiency compared to the brain4,5. Additionally, the traditional semiconductor technology is approaching its physical limits with the continuous scaling down, which would accordingly limit further improvement of devices' characteristics6,7. Therefore, it will be very hard to realize similar learning ability as human brain by the traditional complementary metal–oxide–semiconductor (CMOS) technology. To break this bottleneck and further improve the computing ability of computers, neuromorphic systems imitating human neural network have been explored8. Meanwhile, to simplify the architecture of neuromorphic systems and realize functions like the human brain, various synaptic devices have been also proposed9,10. Nevertheless, either large operation power consumption or low speed makes them difficult to approach the human brain. Recently, transition metal oxide based resistive random access memory (ReRAM), as a promising candidate for next generation nonvolatile memory (NVM) application, has been widely studied11,12. It shows great characteristics such as fast operation speed, low power, high reliability, multilevel data storage and high density integration13,14,15. More interestingly, some of ReRAM cells show an adaptation response to pulse stimulation, which is quite similar to synapse's behaviors as reported in literature16,17,18. All these characteristics suggest a great potential to realize electronically neuromorphic systems by using ReRAM-based cells19. On the other hand, there are still some problems for the ReRAM's application as a synaptic device, considering its lager operation current/power consumption20 and switching variation, as well as cross-talk with adjacent cells. To address these, a transistor as a selector has been serially connected with the ReRAM cell. However, due to poor high density integration ability with large footprint of 8F2 ~ 12F2 (F is the feature size of the process), the traditional planar transistor is not an ideal candidate for neuromorphic system application. Therefore, a more proper selector is required to implement not only good switching behaviors but also small footprint so as to realize stable synaptic behaviors and large array size20,21, which are subsequently critical for realizing complex functions like human brains in neuromorphic system.

In this study, we develop a novel synaptic cell by using CMOS compatible nano-fabrication technology22,23. It consists of one vertical gate-all-around (GAA) Si nano-pillar transistor (1T) as the selector and one transition metal-oxide based resistive switching device (1R), stacked directly on top of the transistor. Thanks to good selector's performances of the vertical transistor and extremely high-density integration capacity of the vertical 1T1R architecture, all the above-mentioned problems have been solved. Correspondingly, neuromorphic systems have also been implemented by 1T1R arrays with this highly compact 1T1R cell (4F2), showing superior electrical characteristics such as ultra-low operation current (<2 nA) and power (<10 fJ), fast switching speed (<10 ns), multilevel data storage and controllable synaptic behaviors.

The architecture of a 1T1R cell-based 4x4 array is illustrated in Figure 1a,b and the corresponding single 1T1R cell structure is shown in Figure 1c–e. By employing the vertical GAA Si nano-pillar MOSFET as the selection device of a ReRAM cell24, a much smaller cell footprint (4F2) compared with traditionally planar 1T1R cell (8F2) can be achieved with good controllability on the ON/OFF current. The source of the MOSFET at the bottom terminal of the nano-pillar is connected to the common ground and its gate is connected by α-Si in a row as word line (WL) of the memory. Additionally, to simplify the fabrication process, the drain of the MOSFET is directly used as the bottom electrode (BE) of ReRAM. Combining with the HfOx resistive switching (RS) layer and the Ni/TiN top electrode (TE), a Si/HfOx/Ni/TiN structured ReRAM is formed directly at the top of the nano-pillar. Finally, the top electrode of ReRAM cell is connected with metal bit line (BL) so that any cell can be accurately selected by a certain BL and a certain WL. Figure 1b shows the Defect Review Scanning Electron Microscope (DRSEM) image of the fabricated 1T1R array. Moreover, as shown in schematic view (Figure 1c,d) and TEM image (Figure 1e) of the 1T1R cell, a vertical n-MOSFET controlled ReRAM is fabricated on the Si substrate, where the diameter of the Si nano-pillar is about 37 nm and the ReRAM cell is composed by 4 nm HfOx RS layer and Ni/TiN TE on top of the drain of the transistor. The process flow to fabricate this 4×4 nano-pillar based 1T1R array and some corresponding DRSEM photos are illustrated in Figure 2a–i*, which is compatible with today's CMOS technology.

Figure 1
figure 1

(a) Schematic view of architecture of the nano-pillar based 1T1R array, (b) DRSEM image of fabricated 4×4 1T1R array (c) Schematic view of single 1T1R cell (d) Cross-sectional view of single 1T1R cell (e) TEM image of single 1T1R cell.

Figure 2
figure 2

(a)–(i) Schematic view of process flow of the fabricated 4×4 nano-pillar based 1T1R array (a*)–(i*) Corresponding steps' DRSEM images of 4×4 nano-pillar based 1T1R array.

The resistive switching occurred in TMO-based ReRAM is believed to be associated with electrical field induced formation and rupture of conductive filament (CF), which is most probably constructed by oxygen vacancies (Vo)25. In SET process, oxygen ions (O2−) would be generated under a large enough electrical field and drift to the active electrode (TE in our device). As a result, the left oxygen vacancies in the RS layer could construct a CF, leading to low resistance state (LRS) of the ReRAM. While, in RESET process, O2− drift out from the active electrode and recombine with positively charged Vo induced by the locally and critically negative electrical field in the RS layer, then the CF would be ruptured and LRS would switch back to high resistance state (HRS) accordingly. Afterwards, functional cells switch reversibly in between HRS and LRS alternately. Thus, it can be realized that this reversible switching happened in the RS layer is more like a dielectric “breakdown” and “recovery” process, wherein a well controlled “breakdown” or Vo generation in SET process is very critical26. Therefore, a selector who can provide a current compliance in SET process would be needed, such as diode or MOSFET. In this work, the vertical Si nano-pillar MOSFET is employed owing to its excellent gate controllability and less than 0.1 nA leakage current, as shown in Figure 3a,b. In addition, I–V characteristics of single ReRAM device without a nano-pillar MOSFET as the selector are illustrated in Figure 3c, showing that RESET current is larger than SET current compliance. This confirms that the SET process of a single ReRAM device is usually uncontrollable. In contrast to this, the 1T1R cell shows well controlled switching behaviors with smaller RESET current than SET current limitation and larger HRS/LRS ratio than 1R cell (Figure 3d), suggesting that the switching characteristics of the ReRAM device can be controlled by the nano-pillar MOSFET-based selector.

Figure 3
figure 3

(a) Transfer characteristic curve and (b) Output characteristics curve of nano-pillar MOSFET (c) I–V characteristics of single ReRAM cell without control MOSFET, SET current compliance is 1 μA (d) I–V characteristics of fabricated 1T1R cell when VG = −0.3 V.

Moreover, good transistor's characteristics shown in Figure 3a,b also suggest that SET current through the 1T1R cell can be effectively controlled by the gate voltage and various functions might be achieved from the 1T1R array by using different gate voltages. In this experiment, we applied a 2 V gate voltage to turn on the MOSFET in the RESET process because of its good voltage response. Figure 4a shows the switching I–V curves of the ReRAM under −0.8 V gate voltage in SET process, demonstrating very low switching current (<2 nA). Such low current is absolutely beneficial to reduce the power consumption down to 10 fJ, a key specification for a synaptic device of a neuromorphic system20,27. Furthermore, eight resistance states of the 1T1R cell can be achieved by controlling the gate voltage, as shown in Figure 4b. Additionally, the ultra fast response speed of the 1T1R cell is demonstrated by using 8 ns 4 V SET voltage pulse and 8 ns −2 V RESET voltage pulse (Figure 4c). All these characteristics pave the way for the 1T1R cells to imitate information storage and synaptic connection in a neural network8. Excitingly, the gate voltage controlled synaptic switching behavior is also demonstrated in this 1T1R cell, as shown in Figure 4d. Using a 1 μs 2.5 V voltage pulse to stimulate the device, its resistance will rapidly switch to LRS at 0.3 V gate voltage. On the other hand, its resistance will slowly switch to another LRS at −0.3 V gate voltage, with a relatively higher resistance. In other words, a larger gate voltage will enhance both the saturation synaptic weight and the stimulation intensity of the 1T1R cell in the neuromorphic systems. These behaviors can be also understood by the above-mentioned Vo related switching model, the resistance of the transistor tends to reduce at a higher gate voltage, as a result Vo accumulation would be accelerated due to the enhanced voltage stress applied on the ReRAM device. Thanks for the gate voltage controlled resistance state and synaptic switching behavior, the connection strength of the synaptic devices in some critical nodes can be adjusted to accelerate training process in neuromorphic system. In addition some complex functions in neuromorphic system such as the “winner-take-all” system architecture28, can be easily realized by applying feedback signal on the gate of the transistor in the 1T1R cell. Compared with 1R arrays, the 1T1R array shows much lower operation power higher integration density and gate controlled switching behaviors, which benefits realization of complex functions in the 1T1R array based system.

Figure 4
figure 4

(a) Ultra-low current switching characteristics of the 1T1R cell when VG = −0.8 V in SET process (b) Using different VG to get multilevel data storage characteristics in the 1T1R cell (c) Resistance distribution of the 1T1R cell's response to fast voltage pulse stimulation (d) Gate voltage controlled synaptic switching behavior of the 1T1R cell. (e) Schematic view of the electrical neuromorphic system constituted by 1T1R array by imitating the interconnection in a neural network.

With these excellent characteristics, this 1T1R array shows great potential to build up high speed and low power electronics neuromorphic systems as illustrated in Figure 4e. By controlling the gate voltage of the 1T1R cell, both multilevel data storage and weights adjustable synapse like functions can be realized. Furthermore, by simply adding some external control units such as integrator, comparator and spike circuits to this 1T1R array, the logical operations and human visual imitation can be expected, as reported in references27,29. Additionally, the developed cell can imitate the behavior of a synapse, by connecting one 1T1R cell to neuron-inspired devices. Also, electronics neuromorphic systems can be realized by connecting these neuron-inspired devices in the 1T1R based array properly.

In conclusion, we successfully demonstrate a nano-pillar transistor controlled ReRAM 1T1R cell with 37 nm cell dimension and compact 4F2 footprint by using a CMOS compatible process flow. Meanwhile, ultra low switching current (<2 nA) and power (10<fJ) as well as fast switching time (<10 ns) are achieved. In addition, multilevel date storage and processing performance can also be realized in the cell. Furthermore, the 1T1R cell shows a controllable synaptic behavior under electric stimulation. More promisingly, the demonstrated switching characteristics and functions of the 1T1R cell can be switched flexibly by adjusting applied gate voltages and pulses. All these characteristics suggest great potential of the 1T1R array in electronics neuromorphic systems for future computer application.

Experimental Section

Device fabrication: Firstly, a nitride hard mask (SiN) was deposited and patterned on 8 inch bulk Si wafers (p-type, ~1015 cm−3) by using a 248 nm KrF scanner. This was followed by photo resist trimming, SiN hard mask open and 400 nm Si etch using deep reactive-ion etching (RIE). Then, thermal oxidation at 1000°C and dilute hydrofluoric acid (DHF) etch-back were done to smooth the wire surface and to reduce the diameter of the formed nano-pillar down to about 37 nm (Figure 2a,a*). Secondly, a vertical As implant and activation was done to dope the substrate and the bottom of the nano-pillar to n+. Then, nonconformal high-density plasma (HDP) oxide deposition followed by DHF etch-back was performed to cover the bottom of the nano-pillar only (up to the n+-p junction, as shown in Figure 2b). Thirdly, a 4.5 nm gate oxide was thermally grown before α-Si deposition and gate shallow implantation with phosphorus (Figure 2c). Then, HDP oxide layer was deposited and etched back again to form etch mask of α-Si exposed from nano-pillar tip, followed by α-Si wet etch, top angle As implantation and activation (Figure 2d,d*). After that, a nitride spacer was formed to protect the nano-pillar tips and MOSFET part was completed by the following oxide strip, gate litho and etching (Figure 2e,e*). Fourthly, the nano-pillars were fully capped by a thick HDP oxide layer, followed by CMP, oxide wet etch back and nitride removal. Consequently, n+ Si nano-pillar tip, as BE of the ReRAM, was exposed (Figure 2f,f*), showing about 37 nm diameter as indicated by DRSEM images and confirmed by TEM images (Figure 1e). Then, after second nitride hard mask formation, physical vapor deposited (PVD) HfOx, Ni and TiN films were stacked and patterned at the pillar tips by using the same nano-pillar form mask (Figure 2g,g*). Finally, the vertical 1T1R structure was defined after ReRAM cell etch (Figure 2h,h*) and the corresponding 4×4 array fabrication was completed after PMD deposition, contact formation and Al metallization (Figure 2i,i*).

TEM and DRSEM characterization: The TEM sample was prepared using the in situ Focused Ion Beam (FIB) lift out technique on a FEI Helios 450S Dual Beam FIB. The sample was coated with a protective platinum layer prior to FIB milling. The sample was imaged with a FEI Titan TEM operated at 200 kV in bright-field (BF) mode, high-resolution (HR) mode and high-angle annular dark-field (HAADF) STEM mode.

The DRSEM inspection was performed without destructive damage on device region by using an in-line SEM Vision G4 setup, which can provide high resolution images at both 0 degree and 45 degree tilt. Also, to provide the best review image quality, it's equipped with anti-charging mechanisms inside the setup.

Electrical measurements: Electrical measurements are performed using a Keithley 4200 semiconductor parameter analyzer, an Agilent 4156C semiconductor parameter analyzer and an Agilent 33250A pulse generator. The voltage is applied on the Ni/TiN top electrode and the poly-Si gate electrode of the nano-pillar transistor, the Si bottem electrode is grounded as a reference.