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Evolution of the conductive filament system in HfO2-based memristors observed by direct atomic-scale imaging
Open accessAbstract
The resistive switching effect in memristors typically stems from the formation and rupture of localized conductive filament paths, and HfO 2 has been accepted as one of the most promising resistive switching materials. However, the dynamic changes in the resistive switching process, including the composition and structure of conductive filaments, and especially the evolution of conductive filament surroundings, remain controversial in HfO 2-based memristors. Here, the conductive filament system in the amorphous HfO 2-based memristors with various top electrodes is revealed to be with a quasi-core-shell structure consisting of metallic hexagonal-Hf 6 O and its crystalline surroundings (monoclinic or tetragonal HfO x). The phase of the HfO x shell varies with the oxygen reservation capability of the top electrode. According to extensive high-resolution transmission electron microscopy observations and ab initio calculations, the phase transition of the conductive filament shell between monoclinic and tetragonal HfO 2 is proposed to depend on the comprehensive effects of Joule heat from the conductive filament current and the concentration of oxygen vacancies. The quasi-core-shell conductive filament system with an intrinsic barrier, which prohibits conductive filament oxidation, ensures the extreme scalability of resistive switching memristors. This study renovates the understanding of the conductive filament evolution in HfO 2-based memristors and provides potential inspirations to improve oxide memristors for nonvolatile storage-class memory applications.
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The estimated accuracy is comparable to other hardware-based simulation performances ranging from 70% to 94%.
“Although our device is not ideal yet, the estimated accuracy is comparable to other hardware‐based simulation performances ranging from 70% to 94%.[ 41 , 42 , 43 , 44 , 45 ]”
From Retention Secured Nonlinear and Self-Rectifying Analog Charge Trap Memristor for Energy-Efficient Neuromorphic Hardware (2023) · cites this paper as [43]
The Results section on device fabrication and switching performance reports resistance ratios, retention, and switching times, not simulation accuracy. Searches for “70%,” “94%,” and hardware-based classification accuracy found no passage in our copy reporting the claimed performance range. (LLM, conf=0.76)
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Chen, P., Liu, F., Lin, P., Li, P., Xiao, Y., Zhang, B., & Pan, G. (2023) · Nature Communications · doi:10.1038/s41467-023-41958-4 · Cited by 57
Emerging memristive artificial neuron and synapse devices for the neuromorphic electronics era
Li, J., Abbas, H., Ang, D. S., Ali, A., & Ju, X. (2023) · Nanoscale Horizons · doi:10.1039/d3nh00180f · Cited by 52
Zong, L., Lu, F., Li, P., Fan, K., Zhan, T., Liu, P., Jiang, L., Chen, D., Zhang, R., & Wang, L. (2024) · Advanced Materials · doi:10.1002/adma.202403525 · Cited by 49
Self-citationAn innovative biomimetic technology: Memristors mimic human sensation
Wang, K., Wang, M., Sun, B. T., Yang, C. S., Cao, Z., Wu, T., Gao, K., Ma, H., Yan, W., Wang, H., et al. (2025) · Nano Energy · doi:10.1016/j.nanoen.2025.110698 · Cited by 47
Yang, J., Tang, X.-G., Gu, X., Sun, Q., Tang, Z., Li, W., & Jiang, Y. (2025) · Nano-Micro Letters · doi:10.1007/s40820-025-01891-1 · Cited by 47
MODELING THE CRYSTAL STRUCTURE OF SPINELS USING A RELATIONAL DATA MODEL
Sechenykh, P. A. (2023) · International Conference on Mathematical Modeling in Materials Science of Electronic Components (MMMSEC) · doi:10.29003/m3597.mmmsec-2023/98-101 · Cited by 46
Advances in memristor based artificial neuron fabrication-materials, models, and applications
Bian, J., Liu, Z., Tao, Y., Wang, Z., Zhao, X., Lin, Y., Xu, H., & Liu, Y. (2023) · International Journal of Extreme Manufacturing · doi:10.1088/2631-7990/acfcf1 · Cited by 45
Self-citationSliding Memristor in Parallel‐Stacked Hexagonal Boron Nitride
Du, S., Yang, W., Gao, H., Dong, W., Xu, B., Watanabe, K., Taniguchi, T., Zhao, J., Zheng, F., Zhou, J., et al. (2024) · Advanced Materials · doi:10.1002/adma.202404177 · Cited by 45
Kwon, J. U., Song, Y. G., Kim, J. E., Chun, S. Y., Kim, G. H., Noh, G., Kwak, J. Y., Hur, S., Kang, C.-Y., Jeong, D. S., et al. (2022) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.2c12247 · Cited by 44
Durable Ru Nanocrystal with HfO2 Modification for Acidic Overall Water Splitting
Kong, X., Xu, J., Ju, Z., & Chen, C. (2024) · Nano-Micro Letters · doi:10.1007/s40820-024-01384-7 · Cited by 44
Polyoxometalate Accelerated Cationic Migration for Reservoir Computing
Zhang, G., Xiong, Z., Gong, Y., Zhu, Z., Lv, Z., Wang, Y., Yang, J., Xing, X., Wang, Z., Qin, J., et al. (2022) · Advanced Functional Materials · doi:10.1002/adfm.202204721 · Cited by 44
Ferroelectricity in HfO2 from a Coordination Number Perspective
Yuan, J., Mao, G., Xue, K., Bai, N., Wang, C., Cheng, Y., Lyu, H., Sun, H., Wang, X., & Miao, X. (2022) · Chemistry of Materials · doi:10.1021/acs.chemmater.2c02660 · Cited by 43
Self-citationRecent Progress in Multiterminal Memristors for Neuromorphic Applications
Leng, Y., Zhang, Y., Lv, Z., Wang, J., Xie, T., Zhu, S., Qin, J., Xu, R., Zhou, Y., & Han, S. (2023) · Advanced Electronic Materials · doi:10.1002/aelm.202300108 · Cited by 42
Self-citationKundale, S. S., Pawar, P. S., Kumbhar, D. D., Devara, I. K. G., Sharma, I., Patil, P. R., Lestari, W. A., Shim, S., Park, J., Dongale, T. D., et al. (2024) · Advanced Science · doi:10.1002/advs.202405251 · Cited by 42
Kumar, A., Bhardwaj, K., Singh, S. P., Lee, Y., Lee, S., Kumar, M., & Sharma, S. K. (2024) · InfoMat · doi:10.1002/inf2.12644 · Cited by 41
Designing Wake‐Up Free Ferroelectric Capacitors Based on the HfO2/ZrO2 Superlattice Structure
Bai, N., Xue, K., Huang, J., Yuan, J., Wang, W., Mao, G., Zou, L., Yang, S., Lu, H., Sun, H., et al. (2022) · Advanced Electronic Materials · doi:10.1002/aelm.202200737 · Cited by 40
Self-citationFAULT-TOLERANT SELT-TIMED COUNTERS
Zatsarinny, A. A., Stepchenkov, Y. A., Diachenko, Y., Khilko, D. V., Orlov, G., & Diachenko, D. Y. (2023) · International Conference on Mathematical Modeling in Materials Science of Electronic Components (MMMSEC) · doi:10.29003/m3614.mmmsec-2023/167-170 · Cited by 40
Ultrasound: A new strategy for artificial synapses modulation
Yuan, J., Li, Y., Wang, M., Huang, X., Zhang, T., Xue, K., Yuan, J., Ou‐Yang, J., Yang, X., Miao, X., et al. (2024) · InfoMat · doi:10.1002/inf2.12528 · Cited by 40
Self-citationFerroelectric memristor and its neuromorphic computing applications
Du, J., Sun, B. T., Yang, C. S., Cao, Z., Zhou, G., Wang, H., & Chen, Y. (2024) · Materials Today Physics · doi:10.1016/j.mtphys.2024.101607 · Cited by 40
Stereoscopic artificial compound eyes for spatiotemporal perception in three-dimensional space
Bae, B., Lee, D., Park, M., Mu, Y., Baek, Y., Sim, I., Shen, C., & Lee, K. (2024) · Science Robotics · doi:10.1126/scirobotics.adl3606 · Cited by 39
Conductive mechanism in memristor at the thinnest limit: The case based on monolayer boron nitride
Li, X., Chen, N., Wang, B., & Li, X. (2022) · Applied Physics Letters · doi:10.1063/5.0098120 · Cited by 34
Khan, R., Raziq, F., Ahmad, I., Ghosh, S., Kheawhom, S., & Sangaraju, S. (2024) · ACS Applied Electronic Materials · doi:10.1021/acsaelm.4c01506 · Cited by 31
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Ferroelectric coupling for dual-mode non-filamentary memristors
Gao, Z., Wang, Y., Lv, Z., Xie, P., Xu, Z., Luo, M., Zhang, Y., Huang, S., Zhou, K., Zhang, G., et al. (2022) · Applied Physics Reviews · doi:10.1063/5.0087624 · Cited by 30
Self-citationThermodynamic origin of nonvolatility in resistive memory
Li, J., Appachar, A., Peczonczyk, S. L., Harrison, E. T., Ievlev, A. V., Hood, R., Shin, D. J., Yoo, S., Roest, B., Sun, K., et al. (2024) · Matter · doi:10.1016/j.matt.2024.07.018 · Cited by 29
Self-citationZhao, Y., Su, R., Cheng, L., Cheng, M., Cheng, W., Tong, H., Sun, H., Yan, J., & Miao, X. (2022) · Ceramics International · doi:10.1016/j.ceramint.2022.11.066 · Cited by 28
Self-citationSynapse-Mimetic Hardware-Implemented Resistive Random-Access Memory for Artificial Neural Network
Seok, H., Son, S., Jathar, S. B., Lee, J., & Kim, T. (2023) · Sensors · doi:10.3390/s23063118 · Cited by 28
Ling, Y., Wang, Z., Yu, Z., Bao, S., Yang, Y., Bao, L., Sun, Y., Cai, Y., & Huang, R. (2023) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2023.3266186 · Cited by 28
Xu, Z., Chen, S., Pan, Y., Li, F., Sun, H., Lu, Q., Li, Y., Bai, Y., Yang, X., Cheng, X., et al. (2024) · International Journal of Extreme Manufacturing · doi:10.1088/2631-7990/ad9bff · Cited by 27
Self-citationRan, K., Jo, J., Cruces, S., Wang, Z., Dunin‐Borkowski, R. E., Mayer, J., & Lemme, M. C. (2025) · Nature Communications · doi:10.1038/s41467-025-62592-2 · Cited by 27
Forming‐Free, Self‐Compliance, Bipolar Multi‐Level Resistive Switching in WO 3–x Based MIM Device
Rudrapal, K., Bhattacharya, G., Venimadhav, A., & Chaudhuri, A. R. (2022) · Advanced Electronic Materials · doi:10.1002/aelm.202200250 · Cited by 26
Advances in two-dimensional heterojunction for sophisticated memristors
Qin, S., Tao, Y., Hu, T., Zhang, S., Feng, C., Lv, L., Ma, G., Rao, Y., Shen, L., Wan, H., et al. (2024) · Materials Today Physics · doi:10.1016/j.mtphys.2024.101336 · Cited by 25
Deng, W., Yan, X., Wang, L., Yu, N., Luo, W., & Mai, L. (2024) · Nano Energy · doi:10.1016/j.nanoen.2024.109861 · Cited by 25
Self-citationWang, Z., Zhang, J., Zhang, Z., Meng, J., Lei, C., & Wang, T. (2025) · Nano Letters · doi:10.1021/acs.nanolett.5c01843 · Cited by 25
Research Process of Carbon Dots in Memristors
Hao, H., Yan, L., Wang, M., Cao, Y., He, J., & Yang, Y. (2023) · Advanced Electronic Materials · doi:10.1002/aelm.202201195 · Cited by 25
Resistive switching mechanism of MoS2 based atomristor
Li, X., Wang, B., Chen, N., & Li, X. (2023) · Nanotechnology · doi:10.1088/1361-6528/acb69d · Cited by 24
Cheung, S. S., Tossoun, B. M., Yuan, Y., Peng, Y., Hu, Y., Sorin, W. V., Kurczveil, G., Liang, D., & Beausoleil, R. G. (2024) · Communications Engineering · doi:10.1038/s44172-024-00197-1 · Cited by 24
Khan, R., Iqbal, S., Hui, K. N., Khera, E. A., Kalluri, S., Soliyeva, M., & Sangaraju, S. (2025) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2025.116316 · Cited by 24
George, T., & Murugan, A. V. (2022) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.2c13478 · Cited by 23
Improved Performance of HfxZnyO‐Based RRAM and its Switching Characteristics down to 4 K Temperature
Lan, J., Li, Z., Chen, Z., Zhu, Q., Wang, W., Zaheer, M., Lu, J., Liang, J., Shen, M., Chen, P., et al. (2023) · Advanced Electronic Materials · doi:10.1002/aelm.202201250 · Cited by 23
Self-citationKhan, R., Iqbal, S., Raziq, F., Maram, P. S., Chakrabortty, S., & Sangaraju, S. (2024) · Materials Science in Semiconductor Processing · doi:10.1016/j.mssp.2024.109111 · Cited by 23
Zhou, Z., Wang, L., Liu, G., Li, Y., Guan, Z., Zhang, Z., Li, P., Pei, Y., Zhao, J., Sun, J., et al. (2025) · Light Science & Applications · doi:10.1038/s41377-025-01928-5 · Cited by 22
Self-citationSun, D., Zhu, X., Chen, S., Fang, H., Zhu, G., Lan, G., He, L., & Shi, Y. (2024) · Nano Letters · doi:10.1021/acs.nanolett.4c04434 · Cited by 22
A review of MXene memristors and their applications
Hota, M. K., Pazos, S. M., Lanza, M., & Alshareef, H. N. (2025) · Materials Science and Engineering R Reports · doi:10.1016/j.mser.2025.100983 · Cited by 21
Park, S., Jeong, H., Seo, S., Kwon, Y., Lee, J., & Choi, S. (2025) · Nature Communications · doi:10.1038/s41467-025-60818-x · Cited by 21
A Compact Memristor Model Based on Physics-Informed Neural Networks
Lee, Y., Kim, K., & Lee, J. (2024) · Micromachines · doi:10.3390/mi15020253 · Cited by 20
A Balanced CMOS Compatible Ternary Memristor-NMOS Logic Family and Its Application
Wang, X., Chen, X., Zhou, J., Liu, G., Kang, S.-M. S., Nandi, S. K., Elliman, R. G., & Iu, H. H. (2024) · IEEE Transactions on Circuits and Systems I Regular Papers · doi:10.1109/tcsi.2024.3441852 · Cited by 20
Zhang, D. “., Wang, J., Wu, Q., & Du, Y. (2022) · Physical Chemistry Chemical Physics · doi:10.1039/d2cp05803k · Cited by 19
Lee, M., Narayan, D., Kim, J.-H., Le, D. N., Shirodkar, S., Park, S., Kang, J., Lee, S., Ahn, Y., Ryu, S. W., et al. (2024) · ACS Applied Electronic Materials · doi:10.1021/acsaelm.4c01071 · Cited by 19
Lee, M. J., Kim, T. H., Lee, S. H., Oh, S., Khan, M. A., Lee, G. M., Choi, Y. K., Lee, S., Ahn, H., Oh, S. J., et al. (2025) · Advanced Functional Materials · doi:10.1002/adfm.202421080 · Cited by 19
Electrochemical anodic oxidation assisted fabrication of memristors
Hua, S., Tian, J., & Guo, X. (2024) · International Journal of Extreme Manufacturing · doi:10.1088/2631-7990/ad2c61 · Cited by 18
A bioinspired configurable cochlea based on memristors
Cheng, L., Gao, L., Zhang, X., Wu, Z., Zhu, J., Yu, Z., Yang, Y., Ding, Y., Li, C., Zhu, F., et al. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.982850 · Cited by 18
Self-citationOxygen Vacancy Dynamics in Different Switching Modes of Hf 0.5 Zr 0.5 O 2−δ
Knabe, J., Goß, K., Liu, Y., Golias, E., Zakharov, A. A., Cojocariu, I., Jugovac, M., Locatelli, A., Menteş, T. O., Céolin, D., et al. (2025) · ACS Nano · doi:10.1021/acsnano.5c07038 · Cited by 17
Uniform, fast, and reliable CMOS compatible resistive switching memory
Hao, Y., Zhang, Y., Wu, Z., Zhang, X., Shi, T., Wang, Y., Zhu, J., Wang, R., Wang, Y., & Liu, Q. (2022) · Journal of Semiconductors · doi:10.1088/1674-4926/43/5/054102 · Cited by 17
Self-citationOxygen tracer diffusion in amorphous hafnia films for resistive memory
Shin, D. J., Ievlev, A. V., Beckmann, K., Li, J., Ren, P., Cady, N. C., & Li, Y. (2024) · Materials Horizons · doi:10.1039/d3mh02113k · Cited by 17
Self-citationMultiphase Reset Induced Reliable Dual-Mode Resistance Switching of the Ta/HfO 2 /RuO 2 Memristor
Shin, D. H., Park, H., Ghenzi, N., Kim, Y. R., Cheong, S., Shim, S. K., Yim, S., Park, T. W., Song, H., Lee, J., et al. (2024) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.3c19523 · Cited by 17
Density functional theory and molecular dynamics simulations for resistive switching research
Villena, M. A., Kaya, O., Schwingenschlögl, U., Roche, S., & Lanza, M. (2024) · Materials Science and Engineering R Reports · doi:10.1016/j.mser.2024.100825 · Cited by 17
Qin, L., Yu, Y., Fang, C., Liu, Y.-J., Zhu, K., Ouyang, D., Liu, S., Song, B., Zhou, R., Lanza, M., et al. (2025) · 中国科学通报：英文版 · doi:10.1016/j.scib.2025.03.051 · Cited by 17
Self-citationYin, L., Cheng, R., Pan, S., Xiong, W., Chang, S., Zhai, B., Wen, Y., Cai, Y., Guo, Y., Sendeku, M. G., et al. (2023) · Advanced Materials · doi:10.1002/adma.202306850 · Cited by 16
Self-citationHighly Stable HfO2 Memristors through van der Waals Electrode Lamination and Delamination
Tong, W., Wei, W., Zhang, X., Ding, S., Lu, Z., Liu, L., Li, W., Pan, C., Kong, L., Wang, Y., et al. (2023) · Nano Letters · doi:10.1021/acs.nanolett.3c02888 · Cited by 16
Self-citationOxygen vacancy and hydrogen in amorphous HfO 2
Sklénard, B., Cvitkovich, L., Waldhoer, D., & Li, J. (2023) · Journal of Physics D Applied Physics · doi:10.1088/1361-6463/acc878 · Cited by 15
An, Y.-J., Yan, H., Yeom, C.-M., Jeong, J.-K., Eadi, S. B., Lee, H., & Kwon, H.-M. (2024) · Nanoscale · doi:10.1039/d3nr04917e · Cited by 15
Interface characteristic and performance optimization mechanism for HfO -based RRAM devices
Xie, W., Bai, J., Li, Y., Qin, F., & Wang, D. (2024) · Applied Surface Science · doi:10.1016/j.apsusc.2024.161291 · Cited by 15
Self-citation2022 roadmap on neuromorphic devices and applications research in China
Wan, Q. C., Wan, C., Wu, H., Yang, Y., Huang, X., Zhou, P., Chen, L., Wang, T., Li, Y., Xue, K., et al. (2022) · Neuromorphic Computing and Engineering · doi:10.1088/2634-4386/ac7a5a · Cited by 15
Self-citationMultisensory Neuromorphic Devices: From Physics to Integration
Gui, A., Mu, H., Yang, R., Zhang, G., & Lin, S. (2026) · Nano-Micro Letters · doi:10.1007/s40820-025-01940-9 · Cited by 14
Online Fault Detection and Diagnosis in RRAM
Fieback, M., Bradarić, F., Taouil, M., & Hamdioui, S. (2023) · IEEE European Test Symposium (ETS) · doi:10.1109/ets56758.2023.10174113 · Cited by 14
Wang, C.-H., Lo, H., Huang, C., Chen, J.-Y., & Wu, W. (2024) · Journal of Alloys and Compounds · doi:10.1016/j.jallcom.2024.173889 · Cited by 14
Self-citationForming and compliance-free operation of low-energy, fast-switching HfO x S y /HfS 2 memristors
Xhameni, A., AlMutairi, A. A., Guo, X., Chircă, I., Wen, T., Hofmann, S., Nicolosi, V., & Lombardo, A. (2025) · Nanoscale Horizons · doi:10.1039/d4nh00508b · Cited by 14
Advancements in gallium-oxide-based memristors
Zhang, S., Zhang, F., Sun, T., Peng, Y. H., Chen, Z., Liu, X., Guo, D., Wang, X., & Li, H. (2025) · Journal of Alloys and Compounds · doi:10.1016/j.jallcom.2025.181365 · Cited by 14
Analog Ion‐Slicing LiNbO3 Memristor Based on Hopping Transport for Neuromorphic Computing
Wang, J., Zeng, H., Xie, Y., Zhao, Z., Pan, X., Luo, W., Shuai, Y., Tang, L., Zhu, D., Xie, Q., et al. (2023) · Advanced Intelligent Systems · doi:10.1002/aisy.202300155 · Cited by 14
Physical Reservoir Computing System via Hybrid Ferroelectric‐Ionic Transistors
Koo, R., Han, C., Yim, J., Im, J., Cho, Y., Lee, J., Cheema, S., Kim, J., Shin, W., & Kwon, D. (2025) · Advanced Materials · doi:10.1002/adma.202511337 · Cited by 13
Resilience evaluation of memristor based PUF against machine learning attacks
Ibrahim, H. M., Skovorodnikov, H., & Alkhzaimi, H. A. (2024) · Scientific Reports · doi:10.1038/s41598-024-73839-1 · Cited by 13
Alqahtani, B., Kumbhar, D. D., Syed, A. M., Ansari, M. E., Li, H., Dominguez, K., Pal, P., Albagami, M., Kumar, D., Alvarado, A., et al. (2025) · Materials Today · doi:10.1016/j.mattod.2025.08.032 · Cited by 13
Kim, T., Lee, D., Chae, M., Kim, K.-H., & Kim, H.-D. (2024) · Sensors · doi:10.3390/s24196382 · Cited by 13
Cheung, S. S., Liang, D., Yuan, Y., Peng, Y., Tossoun, B. M., Hu, Y., Xiao, X., Sorin, W. V., Kurczveil, G., & Beausoleil, R. G. (2024) · Laser & Photonics Review · doi:10.1002/lpor.202400001 · Cited by 12
Large ferroelectricity in Hf 0.85 Ce 0.15 O 2− δ polycrystalline thin films via lattice expansion
Li, H., Tu, J., Xi, G., Liu, X. G., Liu, X., Du, S., Lu, D.-F., Zu, D., Zhang, Y., Wang, Q., et al. (2024) · Inorganic Chemistry Frontiers · doi:10.1039/d4qi01558d · Cited by 12
Self-citationIn-depth conduction mechanism analysis of programmable memristor and its biosynaptic applications
Zhu, S., Chen, Y., Zhou, G., Zhao, H., Zhang, Y., Xu, M., Zhao, Y. X., & Sun, B. T. (2024) · Materials Today Nano · doi:10.1016/j.mtnano.2024.100543 · Cited by 12
Self-citationFemtosecond laser induced oxygen vacancies in CeO2 with filament-type resistive switching memory
Fan, L., Wu, L., Wang, Y., Tang, X., Bao, X., Zhang, S., Ding, X., Pan, J., Tofil, S., Song, Q., et al. (2025) · Applied Surface Science · doi:10.1016/j.apsusc.2025.162555 · Cited by 12
Jang, H., Ju, D., & Kim, S. (2025) · Journal of Alloys and Compounds · doi:10.1016/j.jallcom.2025.178897 · Cited by 12
Improving ion uptake in artificial synapses through facilitated diffusion mechanisms
Sung, J., Cheon, H., Lee, D., Chung, S., Ayuningtias, L., Yang, H., Jeon, B., Seo, B., Kim, Y., & Lee, E. (2025) · Materials Horizons · doi:10.1039/d5mh00005j · Cited by 12
One Transistor−One Memristor Integrated Device Based on the Dual Conductive Filament Mechanism
Zhao, L., Pan, Z., Zhou, R., Zhao, T., Wu, X., & Huo, N. (2025) · ACS Applied Electronic Materials · doi:10.1021/acsaelm.5c00267 · Cited by 12
Metadata
- Authors
- Zhang, Y., Mao, G.-Q., Zhao, X., Li, Y., Zhang, M., Wu, Z., Wu, W., Sun, H., Guo, Y., Wang, L., Zhang, X., Liu, Q., Lv, H., Xue, K.-H., Xu, G., Miao, X., Long, S., & Liu, M.
- Affiliations
- University of Science and Technology of China (CN)
- Huazhong University of Science and Technology (CN)
- Chinese Academy of Sciences (CN)
- Beijing University of Technology (CN)
- Corresponding author
- Zhao, Xiaolong
- Xue, Kan-Hao
- Long, Shibing
- Liu, Ming
- ORCID
- Venue
- Nature Communications
- Published
- 2021-12-13
- Volume
- 12
- Issue
- 1
- Pages
- 7232-7232
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC8668918
- OpenAlex
- W4200157328
- Cited by
- 300
- References
- 75
- Citations by year
- 2026: 47 · 2025: 72 · 2024: 70 · 2023: 85 · 2022: 26
- FWCI
- 13.31
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China (61925110, 61821091, 51961145110)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Ferroelectric and Negative Capacitance Devices
- Physical Sciences › Materials Science › Materials Chemistry › Phase-change materials and chalcogenides
- Keywords
- conductive filaments, resistive switching, amorphous HfO2, core-shell structure, tetragonal to monoclinic phase transformation, oxygen vacancies, Joule heating, non-volatile memory
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