Next Article in Journal
Investigating the Impact of Substrate Preheating on the Thermal Flow and Microstructure of Laser Cladding of Nickel-Based Superalloy
Next Article in Special Issue
Demonstration of 10 nm Ferroelectric Al0.7Sc0.3N-Based Capacitors for Enabling Selector-Free Memory Array
Previous Article in Journal
Study on Vertical Bearing Capacity of Pile Foundation with Distributed Geopolymer Post-Grouting on Pile Side
Previous Article in Special Issue
Analog Memory and Synaptic Plasticity in an InGaZnO-Based Memristor by Modifying Intrinsic Oxygen Vacancies
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Leakage Mechanism and Cycling Behavior of Ferroelectric Al0.7Sc0.3N

1
Institute of Microelectronics, Agency for Science, Technology and Research (A*STAR), Singapore 138634, Singapore
2
Department of Science, Mathematics and Technology, Singapore University of Technology and Design, Singapore 487372, Singapore
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Materials 2024, 17(2), 397; https://doi.org/10.3390/ma17020397
Submission received: 24 November 2023 / Revised: 27 December 2023 / Accepted: 9 January 2024 / Published: 12 January 2024
(This article belongs to the Special Issue Advanced Semiconductor/Memory Materials and Devices)

Abstract

:
Ferroelectric scandium-doped aluminum nitride (Al1-xScxN) is of considerable research interest because of its superior ferroelectricity. Studies indicate that Al1-xScxN may suffer from a high leakage current, which can hinder further thickness scaling and long-term reliability. In this work, we systematically investigate the origin of the leakage current in Al0.7Sc0.3N films via experiments and theoretical calculations. The results reveal that the leakage may originate from the nitrogen vacancies with positively charged states and fits well with the trap-assisted Poole-Frenkel (P-F) emission. Moreover, we examine the cycling behavior of ferroelectric Al0.7Sc0.3N-based FeRAM devices. We observe that the leakage current substantially increases when the device undergoes bipolar cycling with a pulse amplitude larger than the coercive electric field. Our analysis shows that the increased leakage current in bipolar cycling is caused by the monotonously reduced trap energy level by monitoring the direct current (DC) leakage under different temperatures and the P-F emission fitting.

1. Introduction

The substantial increase in data generation and processing associated with the recent rise of artificial intelligence (AI), machining learning (ML), and Internet-of-Things (IoT) has created new challenges in improving computing efficiency and speed. Using an in-memory computing architecture to reduce or eliminate the data movement between the memory and processor unit can save significant power while increasing throughput [1,2,3,4,5]. Extensive studies to construct the building blocks for in-memory computing have been conducted, primarily consisting of non-volatile memory (NVM) devices, such as resistive random-access memory (RRAM) [6,7,8,9,10], ferroelectric random-access memory (FeRAM) [11], ferroelectric field-effect transistor (FeFET) [12,13,14], phase-change memory (PCM) [15], and magnetoresistive random-access memory (MRAM) [16]. Among these, ferroelectric memory devices relying on the switching polarization states of ferroelectric materials possess the advantages of ultra-fast speed and ultra-low power consumption, offering great potential for in-memory computing.
The wurtzite-structure, scandium-doped aluminum nitride (Al1-xScxN) is a widely studied piezoelectric material that has improved piezoelectricity compared with undoped aluminum nitride (AlN) [17,18]. The recent discovery of ferroelectricity in Al1-xScxN offers promise in ferroelectric memory applications [19,20,21,22,23,24,25,26,27]. Unlike other conventional ferroelectric materials, Al1-xScxN exhibits large remnant polarization (Pr) of >100 µC/cm2, sub-10 nm scaling capability, and an ideal square-shape, polarization-electric field (P-E) hysteresis. Additionally, the coercive field (Ec) of Al1-xScxN strongly depends on the Sc doping concentration, in which a higher Sc doping concentration leads to a lower Ec and can help reduce the operating voltage of Al1-xScxN-based memory devices [19]. However, the leakage current of Al1-xScxN with an even higher Sc doping concentration may become larger. Therefore, a moderate Sc doping concentration of ~30% is desired for achieving a moderate Ec and leakage current that enables the implementation in memory applications. Furthermore, it is CMOS-BEOL (back-end-of-line) compatible with a deposition temperature below 400 °C, and the process technology has been well established for MEMS resonator, filter, and transducer applications [28,29,30]. To date, Al1-xScxN-based ferroelectric memory devices, such as a ferroelectric field-effect transistor and a metal-ferroelectric-metal (MFM) diode, have been successfully demonstrated [31,32]. However, Al1-xScxN suffers from an undesired leakage current and poor endurance, which are major obstacles to practical implementation. Although the leakage and cycling behavior of Al1-xScxN has been characterized, the origin of the high leakage is still under debate [33,34,35,36,37]. In our previous works, the conduction mechanism, origin of leakage current, and cycling behavior have been preliminarily studied. The results showed that the dominant conduction mechanism is trap-assisted Poole–Frenkel (PF) emission and the type of vacancies leading to large leakage is a nitrogen vacancy instead of aluminum or scandium vacancies [36], and the bipolar cycling would cause grain fragmentation [37]. However, the trap energy level (ΦT), specific charge state of the vacancy, and impact of cycling on leakage current have not been deeply investigated yet. Therefore, systematic studies of the underlying mechanisms for the leakage and cycling behavior are still needed for further ultra-thin film growth and device design optimization.
In this paper, we deeply investigate the reliability of the Al0.7Sc0.3N by studying the origin of leakage and cycling behavior of ferroelectric Al0.7Sc0.3N-based FeRAM devices by both experimental and theoretical methods. Based on the experimental results, the as-grown Al0.7Sc0.3N is identified as a p-type material by P-F emission fitting with the consideration of compensation factor, which is an essential factor to identify the type of material and extract the ΦT. Moreover, it is found that the large leakage of the p-type Al0.7Sc0.3N can be attributed to nitrogen vacancies with positively charged states via theoretical calculation. Furthermore, the cycling tests show that leakage substantially increases after the FeRAM devices undergo bipolar cycling pulses with the amplitude larger than the Ec, while the leakage current shows no obvious increment after either unipolar cycling pulses or bipolar cycling pulses with the amplitude smaller than the Ec. This observation indicates that the leakage increment requires the polarization to be switched. At the same time, the evolution of the DC leakage under different temperatures is monitored and analyzed via P-F emission fitting, showing that the ΦT decreases from 0.69 eV to 0.44 eV after 105 bipolar cycling and eventually leads to a further leakage increment.

2. Experiment and Methods

The Al0.7Sc0.3N-based MFM capacitors were prepared on an 8-inch silicon wafer. A 100 nm thick Al0.7Sc0.3N ferroelectric film was deposited by pulsed laser deposition (PLD), and patterned on the 200 nm molybdenum (Mo) layer, followed by defining 10 nm chromium (Cr) and 100 nm platinum (Pt) layers as the top circular electrodes with radii ranging from 20 to 100 µm (Figure 1a). The transmission electron microscope (TEM) photo of the cross-section is plotted in Figure 1b. The peak in the X-ray diffraction (XRD) rocking curve for the (002) reflection of the Al0.7Sc0.3N film is observed with the full-width half-maximum (FWHM) value of 2.7° (Figure 1c), indicating a good c-axis orientation. The as-fabricated capacitor exhibits clear ferroelectricity with a large Pr > 100 µC/cm2 and a steep switching slope (Figure 1d).
The ferroelectric behavior-related measurements were carried out using the Radiant Precision Premier II Ferroelectric Tester (Albuquerque, NM, USA), and the DC leakage measurement were conducted by Keysight B1500A Semiconductor Device Parameter Analyzer (Santa Rosa, CA, USA).

3. Results and Discussion

Figure 2a shows the representative non-switching DC J-E curves of the as-fabricated capacitor, in which the leakage current is at 10−3~10−2 A/cm2 level at E = ±4 MV/cm. The positive polarity refers to the circumstance that applies a positive voltage onto the top electrode, while the negative polarity corresponds to the condition of applying a negative voltage onto the top electrode, respectively. We then investigated the conduction mechanism to understand the origin of the large leakage. The Al0.7Sc0.3N film was grown by PLD and contained a few point defects, meaning that several trap states exist within the bandgap. In our previous work, we have found that the dominant conduction mechanism of our Al0.7Sc0.3N films is the P-F emission as illustrated in Figure 2b [34]. The original P-F equation can be expressed by:
  J = q μ n 0 E e x p [ q ϕ T q 3 E / π ε 0 ε r r k T ]
where J is the current density, μ is the carrier mobility, q is the elementary charge, E is the applied electric field, T (= ΦT) is the trap energy level, ε0 is the vacuum permittivity, εr is the optical dielectric constant, r is the compensation factor, k is the Boltzmann constant, T is the absolute temperature [38]. It should be noted that r varies from 2 to 1 with the increase of acceptor concentration [38]. For Equation (1), we note that the εr obtained in the equation is the dielectric constant at high frequency, which can be calculated by ε r = R I 2 , where R I is the refractive index. The ε r of the Al0.7Sc0.3N film used in our calculations is ~4.8 based on literature [39]. We began the P-F analysis by determining the compensation factor based on the J-E results at room temperature (Figure 2a). Figure 2b shows the schematic illustration of P-F emission model, which is a trap-assisted conduction mechanism. The ln(J/E)-E0.5 curve of the device exhibits a clear linear relationship between ln(J/E) and E0.5, following the dependency of the P-F emission, as shown in Figure 2c. The slope obtained from Figure 2c is used for the extraction of the compensation factor, and the r is extracted to be ~1.19. This indicates that the as-grown AlScN film is a p-type material [38]. It should be noted that there might be some different conduction mechanisms (i.e., Schottky emission) for AlScN using different growing methods or with different Sc doping concentration [35]. However, the extracted optical dielectric constant of our film using the Schottky emission model is ~1.39, which is unreasonably smaller than the experimental value (~4.8) [39], indicating the Schottky emission is not the major mechanism for our devices (see Supplementary Materials for more details). Additionally, Figure 2d plots the statistical results of the leakage current at E = ±3.5 MV/cm of the devices with different pad sizes. There is no obvious size-dependent behavior, indicating that the leakage is not contributed to by the conducting filaments.
To further identify the type of traps leading to the leakage current, the density functional theory (DFT) calculations were performed. The DFT calculations were carried out utilizing the pw.x package in Quantum Espresso (QE) and the PBE exchange–correlation functionals for the Al, N, and Sc atoms were employed [40,41]. The crystal model A l 7 S c 0.3 N was constructed using the Special Quasi-Random Structure method [42,43,44]. For the relaxation process, a Monkhorst–Pack mesh with the dimensions of k-points as 6 × 6 × 4 was set. The PAW (projector augmented wave) was utilized as pseudopotentials and structural relaxation was carried out using the Broyden–Fletcher–Goldfarb–Shanno algorithm with Gaussian smearing of 0.01 Ry. The total energy convergence threshold was established at 10−6 Ry and the cut-off energy of 40 Ry was selected for the plane-wave basis set. Subsequently, a more refined k-point grid of 8 × 8 × 5 was utilized for total energy calculations.
A defect (x) in a charge state q state’s formation energy E f o r m X , q is defined as follows:
E f o r m X , q = E d e f e c t X , q E p e r f e c t A l 0.7 S c 0.3 N i n i u i + q E F + E V B M ,
where the E p e r f e c t ( A l 0.7 S c 0.3 N ) is the total energy of the pristine composition Al0.7Sc0.3N model. E d e f e c t ( X , q ) is total energy of the model removed from Al, Sc, or N atom in a q charge state [45]. In addition, the term n i u i represents the energy of the corresponding crystalline reservoir of Al, Sc, or N, as well as the number of vacancies formed when an atom is removed [45]. EF represents the Fermi energy level relative to the energy position (EVBM) of the VBM in the perfect supercell ( A l 0.7 S c 0.3 N ). The summation term is the contribution of the chemical potential of each atomic species on the formation energy of the defect.
Figure 3a shows the relaxed geometry of 32-atom wurtzite Al0.7Sc0.3N supercells. Figure 3b reveals the band structure and density of states (DOS) of the perfect cell wurtzite Al0.7Sc0.3N model with fully geometry relaxation. The calculated bandgap of the pristine Al0.7Sc0.3N model is ~3.28 eV as shown in Figure 3b, which agrees well with experimental values [46]. Figure 3c–e discloses defect formation energies as a function of Fermi level (EF) of the wurtzite Al0.7Sc0.3N model for different types of vacancies, including aluminum vacancy (VAl), scandium vacancy (VSc), and nitrogen vacancy (VN), with different charge states. The overall smallest formation energies resulting from every charge state (from 3- to 1+ charge state for VAl and VSc, and from 1- to 3+ charge state for VN) are exhibited. In the low EF region (i.e., p-type case), the Al0.7Sc0.3N model with VN shows smaller formation energies than other types of vacancies. On the other hand, the systems with a triplet negatively charged aluminum vacancy ( V A l 3 ) or scandium vacancy ( V S c 3 ) exhibit low formation energies in an n-type case, which agree well with the previous native AlN defects. DFT results indicate that the VN in AlN has the lowest formation energy in p-type material and the VAl has the lowest formation energy in n-type material [47,48,49,50]. The experimental results demonstrate that the as-grown AlScN is a p-type material, suggesting that the leakage current is caused by the generation of VN during thin film deposition, rather than VAl or VSc. Especially, VN with positive charge states ( V N 1 + , V N 2 + , V N 3 + ) shows the smallest formation energy at the low EF region, indicating the highest possibility to be formed.
Subsequently, the electronic band structure for the Al0.7Sc0.3N model with one VN at different charge states was calculated, as shown in Figure 4a–e. It is observed that the Fermi level is closer to the valence band (p-type) when there exists V N 1 + / V N 2 + / V N 3 + compared with V N 1 + / V N 0   . This result confirms that the VN is dominated by the vacancies with positive charge states in the p-type AlScN film. The band gaps and the defect states induced by different VN vacancies are summarized as shown in Figure 4f. It is observed that the nitrogen vacancies will induce multiple defect states near both the conduction band and valence band, which might facilitate the P-F emission. Considering the experimental results and theoretical calculation, the large leakage in the as-grown p-type Al0.7Sc0.3N film might originate from the VN with positive charge states and follows the conduction mechanism of P-F emission.
Cycling behavior is another essential property of using this material for practical memory applications. We then characterized the cycling behavior of the Al0.7Sc0.3N-based capacitors. Specifically, bipolar cycling tests by applying a series of consecutive bipolar waves onto the capacitor were performed and P-E loops were measured subsequently. The bipolar cycling waves used in this work are square pulses with a frequency of 2 kHz, and a pulse width of 12 µs (See Supplementary Materials for more details), respectively. It is observed that bipolar cycling with a pulse amplitude (±4.6 MV/cm) larger than the Ec results in a distorted P-E loop, indicating a significant increase of the leakage current which will cause a read disturbed issue for the FeRAM devices (Figure 5a). However, there shows no obvious degradation when either unipolar pulses with a pulse amplitude larger than Ec or bipolar pulses with a pulse amplitude smaller than Ec were applied (see Supplementary Materials for more details). This indicates that the increment in leakage requires the polarization state to be switched. In our previous work, we found that the bipolar cycling would lead to grain fragmentation, but we did not deeply link it to the impact of traps [37]. In this work, after confirming the trap-assisted conduction mechanism and specific type of traps in Al0.7Sc0.3N by the above-mentioned experiment and theoretical calculation, we then analyzed the impact of traps on the cycling behavior of Al0.7Sc0.3N. We conducted DC leakage current measurements after cycling to verify our observations in the P-E measurements and analyzed the impact of traps after cycling. Our DC I-V measurements indicate concordance with our P-E measurements (Figure 5b), in which the device undergoing bipolar cycling with a pulse amplitude (±4.6 MV/cm) larger than Ec can trigger a substantial leakage increment. In the meanwhile, all the ln(J/E)–E0.5 curves of the device undergoing bipolar cycling exhibit a clear linear relationship between ln(J/E) and E0.5 (Figure 5c), agreeing with the dependency of the P-F emission. Then, the slopes obtained from Figure 5c are used for the extraction of the compensation factor (Figure 5d), which will be utilized for extracting the trap energy level subsequently. The r is extracted to be ~1.19, 1.66, 1.62, and 1.6 for the initial state of the device, and when it undergoes 6000, 30,000, and 126,000 cycles of bipolar cycling, respectively. The extracted r increases substantially after bipolar cycling, indicating that the Al0.7Sc0.3N is a less p-type material and its Fermi level shifts to the conduction band. Furthermore, the temperature-dependent DC I-V measurements (from −40 °C to 125 °C, with a step of 25 °C) after undergoing different cycles of bipolar cycling were taken to extract the trap energy level (Figure 6a–d). The ln(J-E)-1/T and Ea-E0.5 curves show clear linearity under all conditions (Figure 7 and Figure 8), where E a = q ϕ T q 3 E / π ε 0 ε r . By taking the compensation factor into consideration, the trap energy level extracted from the temperature-dependent DC I-V results would decrease from 0.69 eV to 0.44 eV monotonously after 105 switching cycles (Figure 9), which should be the cause of leakage increment.

4. Conclusions

In summary, the reliability properties of the Al0.7Sc0.3N, including the origin of the leakage and cycling behavior of Al0.7Sc0.3N-based FeRAM device, are experimentally and theoretically investigated. The findings indicate that the leakage can be traced back to nitrogen vacancies with positive charge states, and it follows the conduction mechanism of P-F emission. Additionally, bipolar cycling tests reveal a significant increase in leakage when the capacitor undergoes cycles with a pulse amplitude larger than the Ec, which is caused by the reduced trap energy level after the bipolar cycling.

Supplementary Materials

The supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ma17020397/s1, Figure S1: Schematic of the pulse setup for cycling tests; Figure S2: Schottky emission fitting; Figure S3: P-E loops of the devices undergoing bipolar cycling with a pulse amplitude smaller than Ec and unipolar cycling with a pulse amplitude larger than Ec.

Author Contributions

Conceptualization, L.C., C.L. and D.K.L.; methodology, L.C., M.L., W.S. and W.W.; formal analysis, L.C., Q.W. and C.L.; data curation, L.C., Q.W. and C.L.; writing—original draft preparation, L.C., Q.W., C.L., M.L., W.S., W.W., D.K.L. and Y.Z.; writing—review and editing, L.C. and C.L.; supervision, C.L., D.K.L. and Y.Z.; funding acquisition, C.L., D.K.L. and Y.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Science and Engineering Research Council of A*STAR (Agency for Science, Technology, and Research) Singapore, under Grant No. A20G9b0135.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Strukov, D.B.; Snider, G.S.; Stewart, D.R.; Williams, R.S. The Missing Memristor Found. Nature 2008, 453, 80–83. [Google Scholar] [CrossRef] [PubMed]
  2. Di Ventra, M.; Pershin, Y.V. The Parallel Approach. Nat. Phys. 2013, 9, 200–202. [Google Scholar] [CrossRef]
  3. Ielmini, D.; Wong, H.S.P. In-memory Computing with Resistive Switching Devices. Nat. Electron. 2018, 1, 333–343. [Google Scholar] [CrossRef]
  4. Xia, Q.; Yang, J.J. Memristive Crossbar Arrays for Brain-inspired Computing. Nat. Mater. 2019, 18, 309–323. [Google Scholar] [CrossRef] [PubMed]
  5. Chen, L.; Pam, M.E.; Li, S.; Ang, K.W. Ferroelectric Memory Based on Two-dimensional Materials for Neuromorphic Computing. Neuromorph. Comput. Eng. 2022, 2, 022001. [Google Scholar] [CrossRef]
  6. Yang, J.J.; Pickett, M.D.; Li, X.; Ohlberg, D.A.; Stewart, D.R.; Williams, R.S. Memristive Switching Mechanism for Metal/oxide/metal Nanodevices. Nat. Nanotechnol. 2008, 3, 429–433. [Google Scholar] [CrossRef]
  7. Wang, Z.; Joshi, S.; Savel’ev, S.E.; Jiang, H.; Midya, R.; Lin, P.; Hu, M.; Ge, N.; Strachan, J.P.; Li, Z.; et al. Memristors with Diffusive Dynamics as Synaptic Emulators for Neuromorphic Computing. Nat. Mater. 2017, 16, 101–108. [Google Scholar] [CrossRef]
  8. Lee, S.; Sohn, J.; Jiang, Z.; Chen, H.Y.; Wong, H.S.P. Metal Oxide-resistive Memory Using Graphene-edge Electrodes. Nat. Commun. 2015, 6, 8407. [Google Scholar] [CrossRef]
  9. Li, Y.; Tang, J.; Gao, B.; Yao, J.; Fan, A.; Yan, B.; Yang, Y.; Xi, Y.; Li, Y.; Li, J.; et al. Monolithic Three-dimensional Integration of RRAM-based Hybrid Memory Architecture for One-shot Learning. Nat. Commun. 2023, 14, 7140. [Google Scholar] [CrossRef]
  10. Wong, H.S.P.; Lee, H.Y.; Yu, S.; Chen, Y.S.; Wu, Y.; Chen, P.S.; Lee, B.; Chen, F.T.; Tsai, M.J. Metal–oxide RRAM. Proc. IEEE 2012, 100, 1951–1970. [Google Scholar] [CrossRef]
  11. Chanthbouala, A.; Garcia, V.; Cherifi, R.O.; Bouzehouane, K.; Fusil, S.; Moya, X.; Xavier, S.; Yamada, H.; Deranlot, C.; Mathur, N.D.; et al. A Ferroelectric Memristor. Nat. Mater. 2012, 11, 860–864. [Google Scholar] [CrossRef] [PubMed]
  12. Kim, M.K.; Lee, J.S. Ferroelectric Analog Synaptic Transistors. Nano Lett. 2019, 19, 2044–2050. [Google Scholar] [CrossRef] [PubMed]
  13. Chen, L.; Wang, L.; Peng, Y.; Feng, X.; Sarkar, S.; Li, S.; Li, B.; Liu, L.; Han, K.; Gong, X.; et al. A van der Waals Synaptic Transistor Based on Ferroelectric Hf0.5Zr0.5O2 and 2D Tungsten Disulfide. Adv. Electron. Mater. 2020, 6, 2000057. [Google Scholar] [CrossRef]
  14. Chen, L.; Song, W.; Wang, W.; Lee, H.K.; Chen, Z.; Zhao, W.; Zhu, Y. KrF Excimer Laser Annealing with an Ultra-Low Laser Fluence for Enabling Ferroelectric HfZrO. IEEE Electron Device Lett. 2023, 44, 32–35. [Google Scholar] [CrossRef]
  15. Jo, S.H.; Chang, T.; Ebong, I.; Bhadviya, B.B.; Mazumder, P.; Lu, W. Nanoscale Memristor Device as Synapse in Neuromorphic Systems. Nano Lett. 2010, 10, 1297–1301. [Google Scholar] [CrossRef]
  16. Kent, A.D.; Worledge, D.C. A New Spin on Magnetic Memories. Nat. Nanotechnol. 2015, 10, 187–191. [Google Scholar] [CrossRef] [PubMed]
  17. Olsson, R.H.; Tang, Z.; D’Agati, M. Doping of Aluminum Nitride and the Impact on Thin Film Piezoelectric and Ferroelectric Device Performance. In Proceedings of the 2020 IEEE Custom Integrated Circuits Conference (CICC), Boston, MA, USA, 22–25 March 2020; pp. 1–6. [Google Scholar]
  18. Zhang, Q.; Chen, M.; Liu, H.; Zhao, X.; Qin, X.; Wang, F.; Tang, Y.; Yeoh, K.H.; Chew, K.H.; Sun, X. Deposition, Characterization, and Modeling of Scandium-doped Aluminum Nitride Thin Film for Piezoelectric Devices. Materials 2021, 14, 6437. [Google Scholar] [CrossRef]
  19. Fichtner, S.; Wolff, N.; Lofink, F.; Kienle, L.; Wagner, B. AlScN: A III-V Semiconductor Based Ferroelectric. J. Appl. Phys. 2019, 125, 114103. [Google Scholar] [CrossRef]
  20. Mikolajick, T.; Slesazeck, S.; Mulaosmanovic, H.; Park, M.H.; Fichtner, S.; Lomenzo, P.D.; Hoffmann, M.; Schroeder, U. Next Generation Ferroelectric Materials for Semiconductor Process Integration and Their Applications. J. Appl. Phys. 2021, 129, 100901. [Google Scholar] [CrossRef]
  21. Yasuoka, S.; Shimizu, T.; Tateyama, A.; Uehara, M.; Yamada, H.; Akiyama, M.; Hiranaga, Y.; Cho, Y.; Funakubo, H. Effects of Deposition Conditions on the Ferroelectric Properties of (Al1−xScx)N Thin Films. J. Appl. Phys. 2020, 128, 114103. [Google Scholar] [CrossRef]
  22. Liu, X.; Wang, D.; Kim, K.H.; Katti, K.; Zheng, J.; Musavigharavi, P.; Miao, J.; Stach, E.A.; Olsson, R.H., III; Jariwala, D. Post-CMOS Compatible Aluminum Scandium Nitride/2D Channel Ferroelectric Field-effect-transistor Memory. Nano Lett. 2021, 21, 3753–3761. [Google Scholar] [CrossRef] [PubMed]
  23. Mizutani, R.; Yasuoka, S.; Shiraishi, T.; Shimizu, T.; Uehara, M.; Yamada, H.; Akiyama, M.; Sakata, O.; Funakubo, H. Thickness Scaling of (Al0.8Sc0.2)N Films with Remanent Polarization Beyond 100 μC/cm−2 around 10 nm in Thickness. Appl. Phys. Express 2021, 14, 105501. [Google Scholar] [CrossRef]
  24. Chen, L.; Liu, C.; Li, M.; Song, W.; Wang, W.; Wang, Z.; Wang, N.; Zhu, Y. Scandium-Doped Aluminum Nitride for Acoustic Wave Resonators, Filters, and Ferroelectric Memory Applications. ACS Appl. Electron. Mater. 2023, 5, 612–622. [Google Scholar] [CrossRef]
  25. Yang, W.; Chen, L.; Li, M.; Liu, F.; Liu, X.; Liu, C.; Kang, J. Stress Effect on the Leakage Current Distribution of Ferroelectric Al0.7Sc0.3N Across the Wafer. Appl. Phys. Lett. 2023, 123, 132903. [Google Scholar] [CrossRef]
  26. Chen, L.; Liu, C.; Wang, Z.; Li, M.; Song, W.; Wang, W.; Zhu, Y. In-wafer Stress-dependent Leakage Current in Ferroelectric Scandium-doped Aluminum Nitride. In Proceedings of the 2023 IEEE International Symposium on Applications of Ferroelectrics (ISAF), Cleveland, OH, USA, 23–27 July 2023; pp. 1–3. [Google Scholar]
  27. Schönweger, G.; Islam, M.R.; Wolff, N.; Petraru, A.; Kienle, L.; Kohlstedt, H.; Fichtner, S. Ultrathin Al1−xScxN for Low-Voltage-Driven Ferroelectric-Based Devices. Phys. Status Solidi Rapid Res. Lett. 2022, 17, 2200312. [Google Scholar] [CrossRef]
  28. Giribaldi, G.; Colombo, L.; Rinaldi, M. 6–20 GHz 30% ScAlN Lateral Field-Excited Cross-sectional Lame’Mode Resonators for Future Mobile RF Front-Ends. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 2023, 70, 1201–1212. [Google Scholar] [CrossRef]
  29. Moe, C.; Olsson, R.H.; Patel, P.; Tang, Z.; D’Agati, M.; Winters, M.; Vetury, R.; Shealy, J. Highly doped AlScN 3.5 GHz XBAW Resonators with 16% k2eff for 5G RF Filter Applications. In Proceedings of the 2020 IEEE International Ultrasonics Symposium (IUS), Las Vegas, NV, USA, 7–11 September 2020; pp. 1–4. [Google Scholar]
  30. Sano, K.H.; Karasawa, R.; Yanagitani, T. ScAlN Thick-film Ultrasonic Transducer in 40–80 MHz. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 2018, 65, 2097–2102. [Google Scholar] [CrossRef]
  31. Liu, X.; Zheng, J.; Wang, D.; Musavigharavi, P.; Stach, E.A.; Olsson, R., III; Jariwala, D. Aluminum Scandium Nitride-based Metal–ferroelectric–metal Diode Memory Devices with High On/off Ratios. Appl. Phys. Lett. 2021, 118, 202901. [Google Scholar] [CrossRef]
  32. Kim, K.H.; Oh, S.; Fiagbenu, M.M.A.; Zheng, J.; Musavigharavi, P.; Kumar, P.; Trainor, N.; Aljarb, A.; Wan, Y.; Kim, H.M.; et al. Scalable CMOS back-end-of-line-compatible AlScN/two-dimensional channel ferroelectric field-effect transistors. Nature Nanotechnol. 2023, 18, 1044–1050. [Google Scholar] [CrossRef]
  33. Tsai, S.L.; Hoshii, T.; Wakabayashi, H.; Tsutsui, K.; Chung, T.K.; Chang, E.Y.; Kakushima, K. On the Thickness Scaling of Ferroelectricity in Al0.78Sc0.22N Films. Jpn. J. Appl. Phys. 2021, 60, SBBA05. [Google Scholar] [CrossRef]
  34. Tsai, S.L.; Hoshii, T.; Wakabayashi, H.; Tsutsui, K.; Chung, T.K.; Chang, E.Y.; Kakushima, K. Field Cycling Behavior and Breakdown Mechanism of Ferroelectric Al0.78Sc0.22N Films. Jpn. J. Appl. Phys. 2022, 61, SJ1005. [Google Scholar] [CrossRef]
  35. Kataoka, J.; Tsai, S.L.; Hoshii, T.; Wakabayashi, H.; Tsutsui, K.; Kakushima, K. A Possible Origin of the Large Leakage Current in Ferroelectric Al1−xScxN Films. Jpn. J. Appl. Phys. 2021, 60, 030907. [Google Scholar] [CrossRef]
  36. Liu, C.; Wang, Q.; Yang, W.; Cao, T.; Chen, L.; Li, M.; Liu, F.; Loke, D.K.; Kang, J.; Zhu, Y. Multiscale Modeling of Al0.7Sc0.3N-based FeRAM: The Steep Switching, Leakage and Selector-free array. In Proceedings of the 2021 IEEE International Electron Devices Meeting (IEDM), San Francisco, CA, USA, 11–16 December 2021; pp. 8.1.1–8.1.4. [Google Scholar]
  37. Chen, L.; Liu, C.; Li, M.; Song, W.; Wang, W.; Chen, Z.; Samanta, S.; Lee, H.K.; Zhu, Y. Bipolar and Unipolar Cycling Behavior in Ferroelectric Scandium-doped Aluminum Nitride. In Proceedings of the 2022 IEEE International Symposium on Applications of Ferroelectrics (ISAF), Tours, France, 27 June–1 July 2022; pp. 1–3. [Google Scholar]
  38. Yeargan, J.R.; Taylor, H.L. The Poole-Frenkel Effect with Compensation Present. J. Appl. Phys. 1968, 39, 5600–5604. [Google Scholar] [CrossRef]
  39. Baeumler, M.; Lu, Y.; Kurz, N.; Kirste, L.; Prescher, M.; Christoph, T.; Wagner, J.; Žukauskaitė, A.; Ambacher, O. Optical Constants and Band Gap of Wurtzite Al1−xScxN/Al2O3 Prepared by Magnetron Sputter Epitaxy for Scandium Concentrations up to x = 0.41. J. Appl. Phys. 2019, 126, 045715. [Google Scholar] [CrossRef]
  40. Giannozzi, P.; Baroni, S.; Bonini, N.; Calandra, M.; Car, R.; Cavazzoni, C.; Ceresoli, D.; Chiarotti, G.L.; Cococcioni, M.; Dabo, I. QUANTUM ESPRESSO: A Modular and Open-source Software Project for Quantum Simulations of Materials. J. Phys. Condens. Matter. 2009, 21, 395502. [Google Scholar] [CrossRef] [PubMed]
  41. Perdew, J.P.; Burke, K.; Ernzerhof, M. Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 1996, 77, 3865. [Google Scholar] [CrossRef] [PubMed]
  42. Zunger, A.; Wei, S.H.; Ferreira, L.G.; Bernard, J.E. Special Quasirandom Structures. Phys. Rev. Lett. 1990, 65, 353–356. [Google Scholar] [CrossRef]
  43. Wei, S.H.; Ferreira, L.G.; Bernard, J.E.; Zunger, A. Electronic Properties of Random Alloys: Special Quasirandom Structures. Phys. Rev. B 1990, 42, 9622–9649. [Google Scholar] [CrossRef]
  44. Van de Walle, A.; Asta, M.; Ceder, G. The Alloy Theoretic Automated Toolkit: A User Guide. Calphad 2002, 26, 539–553. [Google Scholar] [CrossRef]
  45. Van de Walle, C.G.; Neugebauer, J. First-principles Calculations for Defects and Impurities: Applications to III-nitrides. J. Appl. Phys. 2004, 95, 3851–3879. [Google Scholar] [CrossRef]
  46. Deng, R.; Jiang, K.; Gall, D. Optical Phonon Modes in Al1−xScxN. J. Appl. Phys. 2014, 115, 013506. [Google Scholar] [CrossRef]
  47. Laaksonen, K.; Ganchenkova, M.G.; Nieminen, R.M. Vacancies in Wurtzite GaN and AlN. J. Phys. Condens. Matter. 2008, 21, 015803. [Google Scholar] [CrossRef] [PubMed]
  48. Stampfl, C.; Van de Walle, C.G. Theoretical Investigation of Native Defects, Impurities, and Complexes in Aluminum Nitride. Phys. Rev. B 2002, 65, 155212. [Google Scholar] [CrossRef]
  49. Hung, A.; Russo, S.P.; McCulloch, D.G.; Prawer, S. An ab Initio Study of Structural Properties and Single Vacancy Defects in Wurtzite AlN. J. Chem. Phys. 2004, 120, 4890–4896. [Google Scholar] [CrossRef]
  50. Osetsky, Y.; Du, M.-H.; Samolyuk, G.; Zinkle, S.J.; Zarkadoula, E. Native and Radiation Induced Point Defects in AlN and Sc-doped AlN. Phys. Rev. Mater. 2022, 6, 094603. [Google Scholar] [CrossRef]
Figure 1. (a) Schematic of the Al0.7Sc0.3N-based MFM capacitor array. (b) TEM image of the MFM stack. (c) X-ray diffraction rocking curve of the (002) reflection of the Al0.7Sc0.3N film. (d) Representative P-E loop and dynamic current loop of the Al0.7Sc0.3N-based MFM capacitor.
Figure 1. (a) Schematic of the Al0.7Sc0.3N-based MFM capacitor array. (b) TEM image of the MFM stack. (c) X-ray diffraction rocking curve of the (002) reflection of the Al0.7Sc0.3N film. (d) Representative P-E loop and dynamic current loop of the Al0.7Sc0.3N-based MFM capacitor.
Materials 17 00397 g001
Figure 2. (a) Non-switching DC J-E curves of the as fabricated device. (b) Schematic illustration of P-F emission. (c) Fitting of experimental ln(J/E)-E0.5 data to the P-F model, showing good linearity. (d) Current density vs. device size, showing no obvious size-dependent behavior.
Figure 2. (a) Non-switching DC J-E curves of the as fabricated device. (b) Schematic illustration of P-F emission. (c) Fitting of experimental ln(J/E)-E0.5 data to the P-F model, showing good linearity. (d) Current density vs. device size, showing no obvious size-dependent behavior.
Materials 17 00397 g002
Figure 3. (a) Snapshots of the top and side views of the wurtzite Al0.7Sc0.3N model. (b) The band structure of the perfect cell of Al0.7Sc0.3N model. The Fermi level is set to zero and represented by the horizontal dashed line. (ce) Defect formation energies of Al0.7Sc0.3N models with different types of vacancy V N , V S c , and V A l in the relaxed configurations as a function of Fermi level. EF = 0 corresponds to VBM.
Figure 3. (a) Snapshots of the top and side views of the wurtzite Al0.7Sc0.3N model. (b) The band structure of the perfect cell of Al0.7Sc0.3N model. The Fermi level is set to zero and represented by the horizontal dashed line. (ce) Defect formation energies of Al0.7Sc0.3N models with different types of vacancy V N , V S c , and V A l in the relaxed configurations as a function of Fermi level. EF = 0 corresponds to VBM.
Materials 17 00397 g003
Figure 4. (ae) Band gap structures of the Al0.7Sc0.3N with one nitrogen vacancy at different charge states. (f) Extracted band gap and defect states of the perfect Al0.7Sc0.3N and Al0.7Sc0.3N with one nitrogen vacancy at different charge states.
Figure 4. (ae) Band gap structures of the Al0.7Sc0.3N with one nitrogen vacancy at different charge states. (f) Extracted band gap and defect states of the perfect Al0.7Sc0.3N and Al0.7Sc0.3N with one nitrogen vacancy at different charge states.
Materials 17 00397 g004
Figure 5. (a,b) P-E loops and DC I-V curves of the devices undergoing bipolar cycling tests at room temperature, showing a significant leakage current increment after the cycling. (c) Fitting of experimental ln(J/E)-E0.5 data to the P-F model, showing good linearity. (d) Extracted r2εr and compensation factor vs. bipolar cycling numbers.
Figure 5. (a,b) P-E loops and DC I-V curves of the devices undergoing bipolar cycling tests at room temperature, showing a significant leakage current increment after the cycling. (c) Fitting of experimental ln(J/E)-E0.5 data to the P-F model, showing good linearity. (d) Extracted r2εr and compensation factor vs. bipolar cycling numbers.
Materials 17 00397 g005
Figure 6. Temperature-dependent I-V curves of the device undergoing bipolar cycling with a pulse amplitude of ±4.6 MV/cm. Initial I-V curves (a), I-V curves after 6 k (b), 30 k (c), and 126 k cycles (d), respectively.
Figure 6. Temperature-dependent I-V curves of the device undergoing bipolar cycling with a pulse amplitude of ±4.6 MV/cm. Initial I-V curves (a), I-V curves after 6 k (b), 30 k (c), and 126 k cycles (d), respectively.
Materials 17 00397 g006
Figure 7. Fitting of experimental ln(J/E)-1/T data to the P-F model of initial device (a), after 6 k (b), 30 k (c), and 126 k cycles (d), showing good linearity in all conditions.
Figure 7. Fitting of experimental ln(J/E)-1/T data to the P-F model of initial device (a), after 6 k (b), 30 k (c), and 126 k cycles (d), showing good linearity in all conditions.
Materials 17 00397 g007
Figure 8. Fitting of experimental Ea-E0.5 data to the P-F model of initial device (a), after 6 k (b), 30 k (c), and 126 k cycles (d), showing good linearity in all conditions.
Figure 8. Fitting of experimental Ea-E0.5 data to the P-F model of initial device (a), after 6 k (b), 30 k (c), and 126 k cycles (d), showing good linearity in all conditions.
Materials 17 00397 g008
Figure 9. Extracted trap energy level vs. bipolar cycling numbers.
Figure 9. Extracted trap energy level vs. bipolar cycling numbers.
Materials 17 00397 g009
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Chen, L.; Wang, Q.; Liu, C.; Li, M.; Song, W.; Wang, W.; Loke, D.K.; Zhu, Y. Leakage Mechanism and Cycling Behavior of Ferroelectric Al0.7Sc0.3N. Materials 2024, 17, 397. https://doi.org/10.3390/ma17020397

AMA Style

Chen L, Wang Q, Liu C, Li M, Song W, Wang W, Loke DK, Zhu Y. Leakage Mechanism and Cycling Behavior of Ferroelectric Al0.7Sc0.3N. Materials. 2024; 17(2):397. https://doi.org/10.3390/ma17020397

Chicago/Turabian Style

Chen, Li, Qiang Wang, Chen Liu, Minghua Li, Wendong Song, Weijie Wang, Desmond K. Loke, and Yao Zhu. 2024. "Leakage Mechanism and Cycling Behavior of Ferroelectric Al0.7Sc0.3N" Materials 17, no. 2: 397. https://doi.org/10.3390/ma17020397

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop