Skip to main content

Synaptic Behaviors in Ferroelectric-Like Field-Effect Transistors with Ultrathin Amorphous HfO2 Film

Abstract

We demonstrate a non-volatile field-effect transistor (NVFET) with a 3-nm amorphous HfO2 dielectric that can simulate the synaptic functions under the difference and repetition of gate voltage (VG) pulses. Under 100 ns write/erase (W/E) pulse, a memory window greater than 0.56 V and cycling endurance above 106 are obtained. The storied information as short-term plasticity (STP) in the device has a spiking post-synaptic drain current (ID) that is a response to the VG input pulse and spontaneous decay of ID. A refractory period after the stimuli is observed, during which the ID hardly varies with the VG well-emulating the bio-synapse behavior. Short-term memory to long-term memory transition, paired-pulse facilitation, and post-tetanic potentiation are realized by adjusting the VG pulse waveform and number. The experimental results indicate that the amorphous HfO2 NVFET is a potential candidate for artificial bio-synapse applications.

Background

The need for high density, high performance, and low power consumption has necessitated the development of novel memory devices. Because of their compact structure, non-destructive read-out operation, and multi-bit storage, non-volatile transistors such as ferroelectric field-effect transistors (FeFETs), floating-gate transistors, and IGZO memristors have attracted much attention for embedded memories, computing-in memory, and neuromorphic synapse applications [1,2,3,4,5]. The stimulus is applied to the gate electrode of the transistors for synaptic operation, and the drain side current is the post-synapse current [6, 7].

Recently, non-volatile field-effect transistors (NVFETs) utilizing amorphous Al2O3 and ZrO2 gate insulators were experimentally realized, which was attributed to the switchable polarization (P) induced by the voltage-modulation of the oxygen vacancy (\({V}_{\mathrm{O}}^{+}\))-related dipoles [8,9,10,11]. The mechanism of voltage-modulation of \({V}_{\mathrm{O}}^{+}\) in ferroelectric tunnel junctions was also demonstrated, which improved the tunneling electroresistance ratio of the device [12]. Compared to the polycrystalline doped-HfO2 FeFETs, NVFETs with amorphous dielectrics exhibited significantly lower operation voltage and better linearity for multi-threshold voltage operation [9]. These characteristics make them a promising candidate for low-power neuromorphic devices that closely mimic biological behaviors, which are not to be investigated yet.

In this work, biological synapse behaviors such as short-term plasticity (STP), long-term potentiation (LTP), the transition from short-term memory (STM) to long-term memory (LTM), and spike-timing-dependent plasticity (STDP) are emulated based on the single amorphous HfO2 NVFET, without using additional circuit elements.

Methods

The process flow in [9] was used to fabricate the NVFETs with an amorphous HfO2 gate insulator on 4-inch n-type Ge(001). After the pre-gate cleaning, the substrate was loaded into an atomic layer deposition (ALD) chamber to deposit the HfO2 at 300 °C. Then, a 100-nm-thick TaN gate electrode was deposited by the reactive sputtering. After the gate electrode patterning and etching, the source/drain (S/D) regions were implanted by BF2+. 20-nm thick nickel (Ni) S/D metal electrodes were formed by a lift-off process. Finally, the repaid thermal annealing (RTA) at 350 °C was carried out to improve the interface quality and form the Ni germanium silicide S/D contacts.

The schematic of the fabricated NVFET is shown in Fig. 1a. Figure 1b shows a 3-nm-thick amorphous HfO2 imaged with high-resolution transmission electron microscopy (HRTEM). Figure 1c depicts the measured ferroelectric-like P vs. voltage (V) behavior in the amorphous HfO2 capacitor at a frequency of 1 kHz. The underlying mechanism for the ferroelectric-like behaviors in this amorphous HfO2 devices is similar to that for those devices in Refs. [8, 9]. The extracted evolution of the remnant P (Pr) and coercive voltage (Vc) for the device during the endurance test is shown in Fig. 1d. No wake-up or imprint is observed over 106 cycles. A positive-up and negative-down (PUND) test is used to extract the switching current component of the device by isolating the non-switching charge (Fig. 1e), demonstrating the true P.

Fig. 1
figure 1

a Schematic of the NVFET with amorphous HfO2 gate insulator. b HRTEM image shows the 3-nm-thick amorphous HfO2. c Measured P–V curves for TaN/HfO2/Ge capacitor. d Pr and Vc vs. the number of sweeping cycles for amorphous HfO2 capacitors. e PUND test of HfO2 capacitor exhibiting the switching current component by isolating the non-switching charge

Results and Discussion

In contrast to the trapping/detrapping process [13,14,15], a ferroelectric-like clockwise hysteresis loop is observed for the DC sweeping of the drain current (ID) as a function of gate voltage (VG) curves for the transistor with the amorphous HfO2 gate insulator, as shown in Fig. 2a. The non-volatile memory function is induced by the ferroelectric-like P switching in the gate stack. Figure 2b shows the initial IDVG curve for the device and those underwent with 100 ns, 1 μs, 10 μs, 100 μs, and 1 ms write/erase (W/E) pules at ± 3 V voltage providing a non-volatile memory function, respectively. The device has a gate length (LG) of 3 μm and a gate width (W) of 80 μm. The write (erase) operation is achieved by applying positive (negative) voltage pulses to the gate of the HfO2 FET, to raise (lower) its threshold voltage (VTH).

Fig. 2
figure 2

a Dual-direction sweeping of ID-VG curves of the amorphous HfO2 NVFET. b Measured ID-VG curves of the device with ± 3 V W/E pulses, and the pulse width varies from 100 ns to 1 ms. c MW for the amorphous HfO2 NVFET with various pulse width. d Stable MW maintains after 106 W/E cycles underwent ± 3 V, 100 ns W/E pulses. e Several hundred seconds retention time was maintained of the amorphous HfO2 device

Figure 2c plots the MW values for different W/E pulse widths. As the pulse width increases from 100 ns to 10 μs, the MW increases to 1.2 V; but when the W/E pulse width further increases, the MW decreases. Trapping/detrapping process is thought to cause the degradation of MW under the 100 μs to 1 ms W/E pulses. Here, MW is the VTH difference between the two states, and VTH is defined as VG at ID = 100 nAW/LG.

As shown in Fig. 2d, a stable MW is maintained over 106 W/E cycles. Figure 2e shows that a stable MW of the amorphous HfO2 device can be maintained over several hundred seconds. The limitation retention time of the device is mainly due to the smaller Pr and large depolarization field. Recent studies have shown that the non-volatile devices with limited retention time can be alternative candidates for high-density and lower power DRAM architectures [16, 17].

Synapse is a basic unit of the human neural network to realize the information transmission from the pre-synaptic neuron to the post-synaptic neuron. The STP is a key factor that affects the biographic performance of the NVFET synapse in the neural system [18]. Figure 3 shows the STP characteristics of a HfO2 NVFET under the single VG pulse with a fixed pulse magnitude of -3 V. The VG pulse width varies from 1 μs to 10 ms and the base voltage varies from 0.5 V to − 1.5 V. As a three-terminal device, the STP performance can be modulated by changing the base voltage, magnitude, and width of the VG pulses. Underwent an applied VG stimulus, the post-synaptic ID of the device increases to a high ID state and decays to a low ID state when the VG pulse ended. For all the measurements, the devices are in the same relaxed pre-state.

Fig. 3
figure 3

Base voltage varies from 0.5 to -1.5 V. The widths of VG pulses in ad are 1 μs, 100 μs, 1 ms, and 10 ms, respectively

As shown in Fig. 3a, underwent a 1 μs VG pulse, the device exhibits a lower post-synaptic ID under the base voltage of − 1.5 V and − 1.0 V compared to the cases under 0 V and − 0.5 V VG base. It is speculated that this could be due to the smaller difference between base and pulse VG voltages. As the VG pulse is widened to ms, the post-synaptic ID no longer depends on the base voltage (Fig. 3c, d). In general, the post-synaptic ID of the device is improved with widening the stimulus VG pulse.

According to Fig. 3, there is a refractory period after the VG pulse. The ID barely varies with the VG, which accurately simulates the bio-synapse with the external stimulating signal. The refractory period of the NVFET synapse is approximately 10–100 μs, which does not depend on the VG pulse width or magnitude. Figure 4 depicts the post-synaptic ID of the transistor that underwent multiple VG input pulses within the refractory period. During this period, ID is excitable by the VG pulse, but its value is less than that for the initial pulse firing. After the refractory period, the post-synaptic ID increases with time to a saturate state, and values of post-synaptic ID in saturation increase with the decrease in the base voltage.

Fig. 4
figure 4

Post-synaptic ID of the device underwent multiple VG input pulses within the relative refractory period

Besides the width and magnitude of the pulse, the stimulation rate also influences the memory formation of the device. To examine the effects of the stimulation rate on the transistor, the ten cycles (N = 10) of stimuli/read VG are applied to the gate electrode. As shown in Fig. 5a, during the stimuli or read, the amplitude and time of the VG pulse are fixed, and the cycle period T is changed by varying the interval parameter. The ID of the transistor was read at low voltage immediately after each stimulation pulse, which is denoted by I1, I2, …, I10 [19].

Fig. 5
figure 5

a VG pulse waveform with the different T. b The ID increase as a function of the gate stimulus number plots with the different T. c Extracted (I2 − I1)/I1 and (I10 − I1)/I1, representing PPF and PTP behaviors, respectively, of the transistor

The dynamic change in the ID of the amorphous HfO2 NVFET under a series of VG pulses with the different T at a VDS of − 0.5 V is shown in Fig. 5b. The ID (i.e., ΔID/I1) of the device increases with the stimuli T numbers to mimic the memory behavior in the biological system. Here, ΔID is calculated by IN − I1, (N = 1, 2, …, 10). Note that the ID of the device increases, i.e., (ΔID/I1) with the reduced T. With a high stimulation rate being the most effective and a low stimulation rate being the least effective for transforming from STM to LTM.

Figure 5c plots the (I2 − I1)/I1 and (I10 − I1)/I1, which represent the experimental conditions for paired-pulse facilitation (PPF) and post-tetanic potentiation (PTP) used in biological studies, respectively [20, 21]. The PPF and PTP phenomena in our amorphous HfO2 synaptic transistor can be compared to synapses in biology. If be former, the synaptic response is enhanced when one stimulus is followed by the same stimulus soon after; if be latter, the synaptic transmission gradually increases with the number of stimuli when a series of stimuli are received [20,21,22]. These verify the feasibility of the amorphous HfO2 device in realizing the transformation of simulated biological memory. The error bars reflect the standard deviation when repeating the measurement a few times to prove the correctness of the data and minimize fluctuations in data.

The temporal relationship of activity between the pre- and post-synaptic neurons is another important aspect of the synapse. We define tPRE and tPOST as the arrival times of the pre-spike and the post-spike, respectively. The change in synaptic weight (Δw) is a function of the Δtt = tPRE − tPOST) between pre- and post-synaptic activity [23]. For a given stimulation, LTD will occur if Δt > 0, while LTP will occur if Δt < 0. STDP is defined as the change in synaptic weight of the Δt between pre- and post-synaptic activity. By utilizing the waveforms adopted in Fig. 6a, b, the STDP curves for the amorphous HfO2 NVFET-based synapse are extracted with 100 ns spikes and shown in Fig. 6c. The pre-and the post-spike resembling the output of the leaky integrate-and-fire neurons are constitutive of an initial negative pulse followed by a sequence of positive pulses with the decreased amplitude. As shown in Fig. 6c, the amorphous HfO2 NVFET can stimulate the STDP learning rule successively with spiking period time TSTDP varying from 170 to 210 ns. The HfO2 NVFET obtains a steeper conductivity change around Δt = 0 at the TSTDP = 190 ns compared to the other TSTDP conditions, which is possibly due to the better matching between the spike waveform shape applied at the gate electrode and the non-volatile characteristics induced by ferroelectric-like behavior of the device.

Fig. 6
figure 6

a and b Spike timing waveform for the implementation of STDP. c Measured STDP curves in the amorphous HfO2 synaptic transistor with different spike periods (T = 170, 190, and 210 ns)

Conclusions

In this work, we report an ultrathin amorphous HfO2 NVFET to emulate the bio-synapse. An MW of 0.56 V with an endurance above 106 cycles is experimentally demonstrated under the ± 3 V and 100 ns W/E pulses. Furthermore, various synaptic behaviors including STP under different stimuli, transitioning from STM to LTM, PPF, PTP, and STDP performance are realized in the device.

Availability of data and materials

The datasets supporting the conclusions of this article are included in the article.

Abbreviations

TaN:

Tantalum nitride

P r :

Remnant polarization

E c :

Coercive electric field

Ge:

Germanium

ALD:

Atomic layer deposition

BF2 + :

Boron fluoride ion

HfO2 :

Hafnium oxide

GeOx :

Germanium oxide

HRTEM:

High-resolution transmission electron microscope

Ni:

Nickel

RTA:

Repaid thermal annealing

MW:

Memory window

I D :

Drain current

Δw :

Synaptic weight

V G :

Gate voltage

V TH :

Threshold voltage

NVFET:

Non-volatile field-effect transistor

T:

Period

FeFET:

Ferroelectric field-effect transistor

STDP:

Spike-timing-dependent plasticity

STP:

Short-term plasticity

LTP:

Long-term potentiation

STM:

Short-term memory

LTM:

Long-term memory

PPF:

Paired-pulse facilitation

PTP:

Post-tetanic potentiation

References

  1. Ali T, Polakowski P, Kühnel K, Czernohorsky M, Kämpfe T, Rudolph M, Pätzold B, Lehninger D, Müller F, Olivo R, Lederer M, Hoffmann R, Steinke P, Zimmermann K, Mühle U, Seidel K, Müller J (2019) A multilevel FeFET memory device based on laminated HSO and HZO ferroelectric layers for high-density storage. In: IEDM Tech. Dig., San Francisco, CA, USA, pp 665–668. https://doi.org/10.1109/IEDM.19573.2019.8993642

  2. Ota K, Yamaguchi M, Berdan R, Marukame T, Nishi Y, Matsuo K, Takahashi K, Kamiya Y, Miyano S, Deguchi J, Fujii S, Saitoh M (2019) Performance maximization of in-memory reinforcement learning with variability-controlled Hf1−xZrxO2 ferroelectric tunnel junctions. In: IEDM Tech. Dig., San Francisco, CA, USA, pp 114–117. https://doi.org/10.1109/IEDM.19573.2019.8993564

  3. Sun X, Wang P, Ni K, Datta S, Yu S (2018) Exploiting hybrid precision for training and inference: a 2T-1FeFET based analog synaptic weight cell. In: IEDM Tech. Dig., San Francisco, CA, USA, pp 55–58. https://doi.org/10.1109/IEDM.2018. 8614611

  4. Guo X, Bayat FM, Bavandpour M, Klachko M, Mahmoodi MR, Prezioso M, Likharev KK, Strukov DB (2017) Fast, energy efficient, robust, and reproducible mixed-signal neuromorphic classifier based on embedded NOR flash memory technology. In: IEDM Tech. Dig., San Francisco, CA, USA, pp 151–154. https://doi.org/10.1109/IEDM.2017.8268341

  5. Jang JT, Kim D, Choi WS, Choi S-J, Kim DM, Kim Y, Kim DH (2020) One transistor–two memristor based on amorphous indium-gallium-zinc-oxide for neuromorphic synaptic devices. ACS Appl Electron Mater 2(9):2837–2844. https://doi.org/10.1021/acsaelm.0c00499

    CAS  Article  Google Scholar 

  6. Chung W, Si M, Ye PD (2018) First demonstration of ge ferroelectric nanowire FET as synaptic device for online learning in neural network with high number of conductance state and Gmax/Gmin. In: IEDM Tech. Dig., San Francisco, CA, USA, pp 344–347. https://doi.org/10.1109/IEDM.2018.8614516

  7. Seo M, Kang M-H, Jeon S-B, Bae H, Hur J, Jang BC, Yun S, Cho S, Kim W-K, Kim M-S, Hwang K-M, Hong S, Choi S-Y, Choi Y-K (2018) first demonstration of a logic-process compatible junctionless ferroelectric FinFET synapse for neuromorphic applications. IEEE Electron Device Lett 39(9):1445–1448. https://doi.org/10.1109/LED.2018.2852698

    CAS  Article  Google Scholar 

  8. Peng Y, Xiao W, Han G, Liu Y, Liu F, Liu C, Zhou Y, Yang N, Zhong N, Duan C, Hao Y (2020) Memory behavior of an Al2O3 gate dielectric non-volatile field-effect transistor. IEEE Electron Device Lett 41(9):1340–1343. https://doi.org/10.1109/LED.2020.3010363

    CAS  Article  Google Scholar 

  9. Peng Y, Xiao W, Liu F, Liu Y, Han G, Yang N, Zhong N, Duan C, Liu C, Zhou Y, Feng Z, Dong H, Hao Y (2020) non-volatile field-effect transistors enabled by oxygen vacancy related dipoles for memory and synapse applications. IEEE Trans Electron Devices 67(9):3632–3636. https://doi.org/10.1109/TED.2020.3007563

    CAS  Article  Google Scholar 

  10. Liu H, Peng Y, Han G, Liu Y, Zhong N, Duan C, Hao Y (2020) ZrO2 ferroelectric field-effect transistors enabled by the switchable oxygen vacancy dipoles. Nanoscale Res Lett 15:120. https://doi.org/10.1186/s11671-020-03353-6

    CAS  Article  Google Scholar 

  11. Peng Y, Liu F, Han G, Xiao W, Liu Y, Zhong N, Duan C, Feng Z, Dong H, Hao Y (2020) Ferroelectric-like behavior originating from oxygen vacancy dipoles in amorphous film for non-volatile memory. Nanoscale Res Lett 15:134. https://doi.org/10.1186/s11671-020-03364-3

    CAS  Article  Google Scholar 

  12. Mikheev V, Chouprik A, Lebedinskii Y, Zarubin S, Markeev AM, Zenkevich AV, Negrov D (2020) Memristor with a ferroelectric HfO2 layer: in which case it is a ferroelectric tunnel junction. Nanotechnology 31:215205. https://doi.org/10.1088/1361-6528/ab746d

    CAS  Article  Google Scholar 

  13. Yurchuk E, Müller J, Müller S, Paul J, Pešić M, van Bentum R, Schröeder U, Mikolajick T (2016) Charge-trapping phenomena in HfO2-based FeFET-type non-volatile memories. IEEE Trans Electron Devices 63(9):3501–3507. https://doi.org/10.1109/TED.2016.2588439

    CAS  Article  Google Scholar 

  14. Luo Q, Gong T, Cheng Y, Cheng Y, Zhang Q, Yu H, Yu J, Ma H, Yu J, Ma H, Xu X, Huang K, Zhu X, Dong D, Yin J, Yuan P, Tai L, Gao J, Li J, Yin H, Long S, Liu Q, Lv H, Liu M (2018) Hybrid 1T e-DRAM and e-NVM realized in one 10 nm node Ferro FinFET device with charge trapping and domain switching effects. In: IEDM Tech. Dig., San Francisco, CA, USA, pp 47–50. https://doi.org/10.1109/IEDM.2018.8614650

  15. Daus A, Lenarczyk P, Petti L, Münzenrieder N, Knobelspies S, Cantarella G, Vogt C, Salvatore GA, Luisier M, Tröster G (2017) Ferroelectric-like charge trapping thin-film transistors and their evaluation as memories and synaptic devices. Adv Electron Mater 3(12):1700309. https://doi.org/10.1002/aelm.201700309

    CAS  Article  Google Scholar 

  16. Chang S-C, Haratipour N, Shivaraman S, Heft TLB, Peck J, Lin C-C, Tung I-C, Merrill DR, Liu H, Lin C-Y, Hamzaoglu F, Metz MV, Young IA, Kavalieros J, Avci UE (2020) Anti-ferroelectric HfxZr1−xO2 capacitors for high-density 3-D embedded-DRAM. In IEDM Tech. Dig., San Francisco, CA, USA, pp 605–608

  17. Belmonte A, Oh H, Rassoul N, Donadio GL, Mitard J, Dekkers H, Delhougne R, Subhechha S, Chasin A, van Setten MJ, Kljucar L, Mao M, Puliyalil H, Pak M, Teugels L, Tsvetanova D, Banerjee K, Souriau L, Tokei Z, Goux L, Kar GS (2020) Capacitor-less, long-retention (> 400s) DRAM cell paving the way towards low-power and high-density monolithic 3D DRAM. In: IEDM Tech. Dig., San Francisco, CA, USA, pp 609–612

  18. Abbott LF, Regehr WG (2004) Synaptic computation. Nature 431:796–803. https://doi.org/10.1038/nature03010

    CAS  Article  Google Scholar 

  19. Chang T, Jo S-H, Lu W (2011) Short-term memory to long-term memory transition in a nanoscale memristor. ACS Nano 5(9):7669–7676. https://doi.org/10.1021/nn202983n

    CAS  Article  Google Scholar 

  20. Atluri PP, Regehr WG (1996) Determinants of the time course of facilitation at the granule cell to purkinje cell synapse. J Neurosci 16(18):5661–5671. https://doi.org/10.1523/JNEUROSCI.16-18-05661.1996

    CAS  Article  Google Scholar 

  21. Magleby KL (1973) The effect of repetitive stimulation on facilitation of transmitter release at the frog neuromuscular. Junct J Physiol 234(2):327–352. https://doi.org/10.1113/jphysiol.1973.sp010348

    CAS  Article  Google Scholar 

  22. Magleby LK, Zengel JEA (1982) Quantitative description of stimulation-induced changes in transmitter release at the frog neuro muscular junction. J Gen Physiol 80(4):613–638. https://doi.org/10.1085/jgp.80.4.613

    CAS  Article  Google Scholar 

  23. Zhang X, Liu S, Zhao X, Wu F, Wu Q, Wang W, Cao R, Fang Y, Lv H, Long S, Liu Q, Liu M (2017) Emulating short-term and long-term plasticity of bio-synapse based on Cu/a–Si/Pt memristor. IEEE Electron Device Lett 38(9):1208–1211. https://doi.org/10.1109/LED.2017.2722463

    CAS  Article  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

The authors acknowledge support from the National Key Research and Development Project (Grant Nos. 2018YFB2202800 and 2018YFB2200500), the National Natural Science Foundation of China (Grant Nos. 62025402, 62004149, 92064003, 91964202, 61534004, and 61874081) and Major Scientific Research Project of Zhejiang Lab (No. 2021MD0AC01).

Author information

Authors and Affiliations

Authors

Contributions

YP carried out the experiments and drafted the manuscript. YP, WWX, and GQH designed the experiments. GQZ helped to measure the device. GQH and YL helped to revise the manuscript. YH supported the study. All the authors read and approved the final manuscript.

Corresponding author

Correspondence to Genquan Han.

Ethics declarations

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Peng, Y., Xiao, W., Zhang, G. et al. Synaptic Behaviors in Ferroelectric-Like Field-Effect Transistors with Ultrathin Amorphous HfO2 Film. Nanoscale Res Lett 17, 17 (2022). https://doi.org/10.1186/s11671-022-03655-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s11671-022-03655-x

Keywords

  • FET
  • HfO2
  • Oxygen vacancy dipole
  • Memory
  • Synapse