1
|
Zindrou A, Psathas P, Deligiannakis Y. Flame Spray Pyrolysis Synthesis of Vo-Rich Nano-SrTiO 3-x. NANOMATERIALS (BASEL, SWITZERLAND) 2024; 14:346. [PMID: 38392719 PMCID: PMC10891825 DOI: 10.3390/nano14040346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 02/24/2024]
Abstract
Engineering of oxygen vacancies (Vo) in nanomaterials allows diligent control of their physicochemical properties. SrTiO3 possesses the typical ABO3 structure and has attracted considerable attention among the titanates due to its chemical stability and its high conduction band energy. This has resulted in its extensive use in photocatalytic energy-related processes, among others. Herein, we introduce the use of Flame Spray Pyrolysis (FSP); an industrial and scalable process to produce Vo-rich SrTiO3 perovskites. We present two types of Anoxic Flame Spray Pyrolysis (A-FSP) technologies using CH4 gas as a reducing source: Radial A-FSP (RA-FSP); and Axial A-FSP (AA-FSP). These are used for the control engineering of oxygen vacancies in the SrTiO3-x nanolattice. Based on X-ray photoelectron spectroscopy, Raman and thermogravimetry-differential thermal analysis, we discuss the role and the amount of the Vos in the so-produced nano-SrTiO3-x, correlating the properties of the nanolattice and energy-band structure of the SrTiO3-x. The present work further corroborates the versatility of FSP as a synthetic process and the potential future application of this process to engineer photocatalysts with oxygen vacancies in quantities that can be measured in kilograms.
Collapse
Affiliation(s)
| | | | - Yiannis Deligiannakis
- Laboratory of Physical Chemistry of Materials & Environment, Department of Physics, University of Ioannina, 45110 Ioannina, Greece; (A.Z.); (P.P.)
| |
Collapse
|
2
|
Sun B, Chen Y, Zhou G, Cao Z, Yang C, Du J, Chen X, Shao J. Memristor-Based Artificial Chips. ACS NANO 2024; 18:14-27. [PMID: 38153841 DOI: 10.1021/acsnano.3c07384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2023]
Abstract
Memristors, promising nanoelectronic devices with in-memory resistive switching behavior that is assembled with a physically integrated core processing unit (CPU) and memory unit and even possesses highly possible multistate electrical behavior, could avoid the von Neumann bottleneck of traditional computing devices and show a highly efficient ability of parallel computation and high information storage. These advantages position them as potential candidates for future data-centric computing requirements and add remarkable vigor to the research of next-generation artificial intelligence (AI) systems, particularly those that involve brain-like intelligence applications. This work provides an overview of the evolution of memristor-based devices, from their initial use in creating artificial synapses and neural networks to their application in developing advanced AI systems and brain-like chips. It offers a broad perspective of the key device primitives enabling their special applications from the view of materials, nanostructure, and mechanism models. We highlight these demonstrations of memristor-based nanoelectronic devices that have potential for use in the field of brain-like AI, point out the existing challenges of memristor-based nanodevices toward brain-like chips, and propose the guiding principle and promising outlook for future device promotion and system optimization in the biomedical AI field.
Collapse
Affiliation(s)
- Bai Sun
- National Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Micro-and Nano-technology Research Center, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Yuanzheng Chen
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, People's Republic of China
| | - Guangdong Zhou
- College of Artificial Intelligence, Brain-inspired Computing & Intelligent Control of Chongqing Key Lab, Southwest University, Chongqing 400715, People's Republic of China
| | - Zelin Cao
- National Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Micro-and Nano-technology Research Center, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Chuan Yang
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, People's Republic of China
| | - Junmei Du
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, People's Republic of China
| | - Xiaoliang Chen
- Micro-and Nano-technology Research Center, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Jinyou Shao
- Micro-and Nano-technology Research Center, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| |
Collapse
|
3
|
Swamynadhan MJ, Ghosh A, Ghosh S. Design of high polarization low switching barrier hybrid improper ferroelectric perovskite oxide superlattices. MATERIALS HORIZONS 2023; 10:5942-5949. [PMID: 37880977 DOI: 10.1039/d3mh01285a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/27/2023]
Abstract
Hybrid improper ferroelectricity is a useful tool to design ABO3/A'BO3 polar superlattices from non polar building blocks. In this study, we have designed high polarization-low switching barrier hybrid improper ferroelectric superlattices with efficient polarization, and polarization-magnetization switching properties above room temperature, using density functional theory and ab initio molecular dynamics simulations. Superlattices with a chemical formula of (AAlO3)m/(A'AlO3)n, where m/n = 1/1, 1/3, 3/1, 1/5 and 5/1, A, A' = Lanthanide and Y cations are considered to outline the design principles behind polarization switching and (LaFeO3)3/(CeFeO3)1 is investigated for polarization-magnetization switching. We find that the unconventional switching paths via out-of-phase rotation QR- (a0a0c-) and tilt precession QTP always yield lower switching barrier compared to those via in-phase rotation QR+ (a0a0c+) and tilt QT (a-a-c0) of BO6 octahedra. Results from ab initio molecular dynamics simulations estimate the temperature at which the lowest energy barrier can be overcome. It is possible to tune the polarization switching barrier by tuning the tolerance factor, A,A' cation radius mismatch and super lattice periodicity. For switching via QR-, the switching barrier varies exponentially with rotation angle, indicating how high switching barrier is expected for systems, away from cubic symmetry. We provide a recipe to overcome such a bottleneck by tuning superlattice periodicity. Finally, we have proposed the multiferroic device application concept through a proposed polarization-temperature hysteresis loop and magnetization switching.
Collapse
Affiliation(s)
- M J Swamynadhan
- Department of Physics and Nanotechnology, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur-603 203, Tamil Nadu, India.
| | - Ayana Ghosh
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, 37831, TN, USA
| | - Saurabh Ghosh
- Department of Physics and Nanotechnology, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur-603 203, Tamil Nadu, India.
| |
Collapse
|
4
|
Khan J, Al-Anazy MM, Yousef ES, D D, Sharma R, Moayad AJA. Comprehensive analysis of novel cubic HgCrO 3 perovskite: a first principles, structural, thermodynamic, and magnetic properties study for spintronic applications. RSC Adv 2023; 13:33603-33612. [PMID: 38019982 PMCID: PMC10653202 DOI: 10.1039/d3ra06392e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 11/09/2023] [Indexed: 12/01/2023] Open
Abstract
The main goal of modern manufacturing is to create products that are affordable, eco-friendly, and energy-efficient. With a focus on HgCrO3, this study sought to discover molecules that meet these requirements. The structural, electrical, thermodynamic, and transport properties of the material were investigated using Wien2K, a full-potential, linearized augmented plane wave program (FP LAPW). Utilizing the generalised gradient approximation (GGA) and lattice constants that have previously produced excellent theoretical and practical findings, structural optimization was carried out. Calculated HgCrO3 magnetic characteristics show that the Cr and Hg atoms are the main contributors to magnetism. Over a temperature range of 0-1200 K and a pressure range of 0-196 GPa, thermodynamic characteristics were evaluated. The thermoelectric properties of HgCrO3 were evaluated using the Boltzmann transport method provided by the BoltzTrap program. This analysis revealed that at room temperature, the figures of merit (ZT) values for HgCrO3 were nearly equal to one. A ZT value close to one indicates that a material has excellent thermoelectric properties and can efficiently convert heat into electricity or vice versa. This investigation highlights the promising thermoelectric capabilities of HgCrO3, which could contribute to more sustainable and energy-efficient technologies in the future.
Collapse
Affiliation(s)
- Junaid Khan
- Department of Physics Khushal Khan Khattak University Karak Pakistan
- Department of Physics Kohat University of Science and Technology Kohat Pakistan
| | - Murefah Mana Al-Anazy
- Department of Chemistry, College of Sciences, Princess Nourah bint Abdulrahman University (PNU) P.O. Box 84428 Riyadh 11671 Saudi Arabia
| | - El Sayed Yousef
- Research Center for Advanced Materials Science (RCAMS), King Khalid University Abha 61413 P. O. Box 9004 Saudi Arabia
- Physics Dep., Faculty of Science, King Khalid University P. O. Box 9004 Abha Saudi Arabia
| | - Datta D
- Dept. of Applied Science, Feroze Gandhi Institute of Engineering and Technology Raebareli 229001 Uttar Pradesh India
| | - Ramesh Sharma
- Dept. of Applied Science, Feroze Gandhi Institute of Engineering and Technology Raebareli 229001 Uttar Pradesh India
| | - A J A Moayad
- Department of Materials Science, Malawi University of Science and Technology, P. O. Box 5196 Limbe Malawi
| |
Collapse
|
5
|
Yu T, Fang Y, Chen X, Liu M, Wang D, Liu S, Lei W, Jiang H, Shafie S, Mohtar MN, Pan L, Zhao Z. Hybridization state transition-driven carbon quantum dot (CQD)-based resistive switches for bionic synapses. MATERIALS HORIZONS 2023; 10:2181-2190. [PMID: 36994553 DOI: 10.1039/d3mh00117b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
As an emerging carbon-based material, carbon quantum dots (CQDs) have shown unstoppable prospects in the field of bionic electronics with their outstanding optoelectronic properties and unique biocompatible characteristics. In this study, a novel CQD-based memristor is proposed for neuromorphic computing. Unlike the models that rely on the formation and rupturing of conductive filaments, it is speculated that the resistance switching mechanism of CQD-based memristors is due to the conductive path caused by the hybridization state transition of the sp2 carbon domain and sp3 carbon domain induced by the reversible electric field. This avoids the drawback of uncontrollable nucleation sites leading to the random formation of conductive filaments in resistive switching. Importantly, it illustrates that the coefficient of variation (CV) of the threshold voltage can be as low as -1.551% and 0.083%, which confirms the remarkable uniform switching characteristics. Interestingly, the Pavlov's dog reflection as an important biological behavior can be demonstrated by the samples. Finally, the accuracy recognition rate of MNIST handwriting can reach up to 96.7%, which is very close to the ideal number (97.8%). A carbon-based memristor based on a new mechanism presented provides new possibilities for the improvement of brain-like computing.
Collapse
Affiliation(s)
- Tianqi Yu
- Joint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing 210096, People's Republic of China.
| | - Yong Fang
- Joint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing 210096, People's Republic of China.
| | - Xinyue Chen
- Joint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing 210096, People's Republic of China.
| | - Min Liu
- Joint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing 210096, People's Republic of China.
| | - Dong Wang
- Joint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing 210096, People's Republic of China.
| | - Shilin Liu
- Joint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing 210096, People's Republic of China.
| | - Wei Lei
- Joint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing 210096, People's Republic of China.
| | - Helong Jiang
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology Chinese Academy of Sciences, Nanjing 210008, People's Republic of China
| | - Suhaidi Shafie
- Institute of Nanoscience and Nanotechnology, University Putra Malaysia, Serdang, Selangor, Malaysia
| | - Mohd Nazim Mohtar
- Institute of Nanoscience and Nanotechnology, University Putra Malaysia, Serdang, Selangor, Malaysia
| | - Likun Pan
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai 200241, People's Republic of China
| | - Zhiwei Zhao
- Joint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing 210096, People's Republic of China.
| |
Collapse
|
6
|
Cao Z, Sun B, Zhou G, Mao S, Zhu S, Zhang J, Ke C, Zhao Y, Shao J. Memristor-based neural networks: a bridge from device to artificial intelligence. NANOSCALE HORIZONS 2023; 8:716-745. [PMID: 36946082 DOI: 10.1039/d2nh00536k] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Since the beginning of the 21st century, there is no doubt that the importance of artificial intelligence has been highlighted in many fields, among which the memristor-based artificial neural network technology is expected to break through the limitation of von Neumann so as to realize the replication of the human brain by enabling strong parallel computing ability and efficient data processing and become an important way towards the next generation of artificial intelligence. A new type of nanodevice, namely memristor, which is based on the variability of its resistance value, not only has very important applications in nonvolatile information storage, but also presents obsessive progressiveness in highly integrated circuits, making it one of the most promising circuit components in the post-Moore era. In particular, memristors can effectively simulate neural synapses and build neural networks; thus, they can be applied for the preparation of various artificial intelligence systems. This study reviews the research progress of memristors in artificial neural networks in detail and highlights the structural advantages and frontier applications of neural networks based on memristors. Finally, some urgent problems and challenges in current research are summarized and corresponding solutions and future development trends are put forward.
Collapse
Affiliation(s)
- Zelin Cao
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China.
- Shaanxi International Joint Research Center for Applied Technology of Controllable Neutron Source, School of Science, Xijing University, Xi'an 710123, China
| | - Bai Sun
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China.
| | - Guangdong Zhou
- College of Artificial Intelligence, Brain-inspired Computing & Intelligent Control of Chongqing Key Lab, Southwest University, Chongqing 400715, China
| | - Shuangsuo Mao
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, Fujian Normal University, Fuzhou, Fujian 350117, China
| | - Shouhui Zhu
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Jie Zhang
- School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Chuan Ke
- School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Yong Zhao
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, Fujian Normal University, Fuzhou, Fujian 350117, China
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
- School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Jinyou Shao
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China.
| |
Collapse
|
7
|
BaTiO3/NixZn1−xFe2O4 (x = 0, 0.5, 1) Composites Synthesized by Thermal Decomposition: Magnetic, Dielectric and Ferroelectric Properties. INORGANICS 2023. [DOI: 10.3390/inorganics11020051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
To investigate the influence of spinel structure and sintering temperature on the functional properties of BaTiO3/NixZn1−xFe2O4 (x = 0, 0.5, 1), NiFe2O4, ZnFe2O4, and Ni0.5Zn0.5Fe2O4 were in situ prepared by thermal decomposition onto BaTiO3 surface from acetylacetonate precursors. As-prepared powders were additionally sintered at 1150 °C and 1300 °C. X-ray powder diffraction (XRPD) and scanning electron microscopy (SEM) coupled with electron dispersive spectroscopy (EDS) were used for the detailed examination of phase composition and morphology. The magnetic, dielectric, and ferroelectric properties were investigated. The optimal phase composition in the BaTiO3/NiFe2O4 composite, sintered at 1150 °C, resulted in a wide frequency range stability. Additionally, particular phase composition indicates favorable properties such as low conductivity and ideal-like hysteresis loop behavior. The favorable properties of BaTiO3/NiFe2O4 make this particular composite an ideal material choice for further studies on applications of multi-ferroic devices.
Collapse
|
8
|
Structural, electronic, optical and mechanical properties of oxide-based perovskite ABO3 (A = Cu, Nd and B = Sn, Sc): A DFT study. J SOLID STATE CHEM 2023. [DOI: 10.1016/j.jssc.2022.123650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
|
9
|
Sun Y, He N, Yuan Q, Wang Y, Dong Y, Wen D. Ferroelectric Polarized in Transistor Channel Polarity Modulation for Reward-Modulated Spike-Time-Dependent Plasticity Application. J Phys Chem Lett 2022; 13:10056-10064. [PMID: 36264655 DOI: 10.1021/acs.jpclett.2c03007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Reward signals reflect the developmental tendency of reinforcement learning (RL) agents. Reward-modulated spike-time-dependent plasticity (R-STDP) is an efficient and concise information processing feature in RL. However, the physical construction of R-STDP normally demands complex circuit design engineering, resulting in large power consumption and large area. In this work, we studied the role of ferroelectric polarization in the modulation of carbon nanotube transistor channel polarity. Furthermore, we applied a modulating channel method to construct a 2T synaptic component by spin-coating technology. Based on the nonvolatility of ferroelectric polarization, the synaptic component constructed has the characteristics of reconfigurable polarity. One channel could be modulated to n-type and the other to p-type. One modulated channel was used to perform the STDP function when the reward signal arrived, and the other modulated channel was used to perform the anti-STDP function when the punishment signal arrived. Finally, R-STDP learning rules are implemented on hardware. This work provides a strategy for hardware construction of RL.
Collapse
Affiliation(s)
- Yanmei Sun
- School of Electronic Engineering, Heilongjiang University, Harbin 150080, China
- Heilongjiang Provincial Key Laboratory of Micro-nano Sensitive Devices and Systems, Heilongjiang University, Harbin 150080, China
- HLJ Province Key Laboratories of Senior-Education for Electronic Engineering, Heilongjiang University, Harbin 150080, China
| | - Nian He
- School of Electronic Engineering, Heilongjiang University, Harbin 150080, China
- Heilongjiang Provincial Key Laboratory of Micro-nano Sensitive Devices and Systems, Heilongjiang University, Harbin 150080, China
- HLJ Province Key Laboratories of Senior-Education for Electronic Engineering, Heilongjiang University, Harbin 150080, China
| | - Qi Yuan
- School of Electronic Engineering, Heilongjiang University, Harbin 150080, China
- Heilongjiang Provincial Key Laboratory of Micro-nano Sensitive Devices and Systems, Heilongjiang University, Harbin 150080, China
- HLJ Province Key Laboratories of Senior-Education for Electronic Engineering, Heilongjiang University, Harbin 150080, China
| | - Yufei Wang
- School of Electronic Engineering, Heilongjiang University, Harbin 150080, China
- Heilongjiang Provincial Key Laboratory of Micro-nano Sensitive Devices and Systems, Heilongjiang University, Harbin 150080, China
- HLJ Province Key Laboratories of Senior-Education for Electronic Engineering, Heilongjiang University, Harbin 150080, China
| | - Yan Dong
- School of Electronic Engineering, Heilongjiang University, Harbin 150080, China
- Heilongjiang Provincial Key Laboratory of Micro-nano Sensitive Devices and Systems, Heilongjiang University, Harbin 150080, China
- HLJ Province Key Laboratories of Senior-Education for Electronic Engineering, Heilongjiang University, Harbin 150080, China
| | - Dianzhong Wen
- School of Electronic Engineering, Heilongjiang University, Harbin 150080, China
- Heilongjiang Provincial Key Laboratory of Micro-nano Sensitive Devices and Systems, Heilongjiang University, Harbin 150080, China
- HLJ Province Key Laboratories of Senior-Education for Electronic Engineering, Heilongjiang University, Harbin 150080, China
| |
Collapse
|
10
|
Scott JJR, Casals B, Luo KF, Haq A, Mariotti D, Salje EKH, Arredondo M. Avalanche criticality in LaAlO[Formula: see text] and the effect of aspect ratio. Sci Rep 2022; 12:14818. [PMID: 36050337 PMCID: PMC9437108 DOI: 10.1038/s41598-022-18390-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 08/10/2022] [Indexed: 11/25/2022] Open
Abstract
Ferroic domain dynamics, as a function of external stimuli, can be collectively described as scale-invariant avalanches characterised by a critical exponent that are sensitive to the complexity of the domain microstructure. The understanding and manipulation of these avalanches lies at the heart of developing novel applications such as neuromorphic computing. Here we combine in situ heating optical observations and mean-field analysis to investigate the collective domain behaviour in pure-ferroelastic lanthanum aluminate (LaAlO[Formula: see text]) as a function of aspect ratio, the ratio of sample length to width, where the movement of the domains is predominantly driven by thermal stresses via thermal expansion/contraction during heat cycling. Our observations demonstrate that the aspect ratio induces (1) distinctive domain microstructures at room temperature, (2) a deviation of dynamical behaviour at high temperatures and (3) critical exponent mixing in the higher aspect ratio samples that accompanies this behaviour. While the critical exponents of each aspect ratio fall within mean-field predicted values, we highlight the effect that the aspect ratio has in inducing exponent mixing. Hence, furthering our understanding towards tuning and controlling avalanches which is crucial for fundamental and applied research.
Collapse
Affiliation(s)
- John J. R. Scott
- School of Mathematics and Physics, Queen’s University Belfast, Belfast, BT7 1NN Northern Ireland, UK
| | - Blai Casals
- Department of Earth Sciences, University of Cambridge, Cambridge, CB2 3EQ England, UK
| | - King-Fa Luo
- School of Mathematics and Physics, Queen’s University Belfast, Belfast, BT7 1NN Northern Ireland, UK
| | - Atta Haq
- School of Engineering, Ulster University, Jordanstown, BT37 0QB Northern Ireland, UK
| | - Davide Mariotti
- School of Engineering, Ulster University, Jordanstown, BT37 0QB Northern Ireland, UK
| | - Ekhard K. H. Salje
- Department of Earth Sciences, University of Cambridge, Cambridge, CB2 3EQ England, UK
| | - Miryam Arredondo
- School of Mathematics and Physics, Queen’s University Belfast, Belfast, BT7 1NN Northern Ireland, UK
| |
Collapse
|
11
|
Gou R, Ouyang Z, Xu C, He S, Cheng S, Shi C, Zhao J, Xiao Y, Lei S, Cheng B. Actual origin and precise control of asymmetrical hysteresis in an individual CH 3NH 3PbI 3 micro/nanowire for optical memory and logic operation. NANOSCALE HORIZONS 2022; 7:1095-1108. [PMID: 35913084 DOI: 10.1039/d2nh00209d] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Although CH3NH3PbI3 can present an excellent photoresponse to visible light, its application in solar cells and photodetectors is seriously hindered due to hysteresis behaviour. Moreover, for its origin, there exist different opinions. Herein, we demonstrate a route to realize precise control for the electrical transport of a single CH3NH3PbI3 micro/nanowire by constructing a two-terminal device with asymmetric Ag and C electrodes, and its hysteresis can be clearly identified as a synergistic effect of the redox reaction at the interface of the Ag electrode and the injection and ejection of holes in the interfacial traps of the C electrode rather than its bulk effect. The device can show superior bias amplitude and illumination intensity dependence of hysteresis loops with typical bipolar resistive switching features. Thus, an excellent multilevel nonvolatile optical memory can be effectively realized by the modulation of the illumination and bias, and moreover a logic OR gate operation can be successfully implemented with voltage and illumination as input signals as well. This work clearly reveals and provides a new insight of hysteresis origin that can be attributed to a synergistic effect of two asymmetrical electrode interfaces, and therefore precisely controlling its electrical transport to realize an outstanding application potential in multifunctional devices integrated with optical nonvolatile memory and logic OR gate operation.
Collapse
Affiliation(s)
- Runna Gou
- School of Physics and Materials, Nanchang University, Jiangxi, 330031, P. R. China.
| | - Zhiyong Ouyang
- Nanoscale Science and Technology Laboratory, Institute for Advanced Study, Nanchang University, Jiangxi, 330031, P. R. China
| | - Changsen Xu
- Nanoscale Science and Technology Laboratory, Institute for Advanced Study, Nanchang University, Jiangxi, 330031, P. R. China
| | - Song He
- School of Physics and Materials, Nanchang University, Jiangxi, 330031, P. R. China.
| | - Shouduan Cheng
- School of Physics and Materials, Nanchang University, Jiangxi, 330031, P. R. China.
| | - Cencen Shi
- Nanoscale Science and Technology Laboratory, Institute for Advanced Study, Nanchang University, Jiangxi, 330031, P. R. China
| | - Jie Zhao
- School of Physics and Materials, Nanchang University, Jiangxi, 330031, P. R. China.
| | - Yanhe Xiao
- School of Physics and Materials, Nanchang University, Jiangxi, 330031, P. R. China.
| | - Shuijin Lei
- School of Physics and Materials, Nanchang University, Jiangxi, 330031, P. R. China.
| | - Baochang Cheng
- School of Physics and Materials, Nanchang University, Jiangxi, 330031, P. R. China.
- Nanoscale Science and Technology Laboratory, Institute for Advanced Study, Nanchang University, Jiangxi, 330031, P. R. China
| |
Collapse
|
12
|
Lv Y, Chen H, Wang Q, Li X, Xie C, Song Z. Post-silicon nano-electronic device and its application in brain-inspired chips. Front Neurorobot 2022; 16:948386. [PMID: 35966373 PMCID: PMC9363789 DOI: 10.3389/fnbot.2022.948386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 06/28/2022] [Indexed: 11/26/2022] Open
Abstract
As information technology is moving toward the era of big data, the traditional Von-Neumann architecture shows limitations in performance. The field of computing has already struggled with the latency and bandwidth required to access memory (“the memory wall”) and energy dissipation (“the power wall”). These challenging issues, such as “the memory bottleneck,” call for significant research investments to develop a new architecture for the next generation of computing systems. Brain-inspired computing is a new computing architecture providing a method of high energy efficiency and high real-time performance for artificial intelligence computing. Brain-inspired neural network system is based on neuron and synapse. The memristive device has been proposed as an artificial synapse for creating neuromorphic computer applications. In this study, post-silicon nano-electronic device and its application in brain-inspired chips are surveyed. First, we introduce the development of neural networks and review the current typical brain-inspired chips, including brain-inspired chips dominated by analog circuit and brain-inspired chips of the full-digital circuit, leading to the design of brain-inspired chips based on post-silicon nano-electronic device. Then, through the analysis of N kinds of post-silicon nano-electronic devices, the research progress of constructing brain-inspired chips using post-silicon nano-electronic device is expounded. Lastly, the future of building brain-inspired chips based on post-silicon nano-electronic device has been prospected.
Collapse
Affiliation(s)
- Yi Lv
- State Key Laboratory of Functional Materials for Informatics, Laboratory of Nanotechnology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Houpeng Chen
- State Key Laboratory of Functional Materials for Informatics, Laboratory of Nanotechnology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
- Shanghai Technology Development and Entrepreneurship Platform for Neuromorphic and AI SoC, Shanghai, China
- *Correspondence: Houpeng Chen
| | - Qian Wang
- State Key Laboratory of Functional Materials for Informatics, Laboratory of Nanotechnology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
| | - Xi Li
- State Key Laboratory of Functional Materials for Informatics, Laboratory of Nanotechnology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
| | - Chenchen Xie
- State Key Laboratory of Functional Materials for Informatics, Laboratory of Nanotechnology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
- Shanghai Nanotechnology Promotion Center, Shanghai, China
| | - Zhitang Song
- State Key Laboratory of Functional Materials for Informatics, Laboratory of Nanotechnology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| |
Collapse
|
13
|
Mao S, Sun B, Zhou G, Guo T, Wang J, Zhao Y. Applications of biomemristors in next generation wearable electronics. NANOSCALE HORIZONS 2022; 7:822-848. [PMID: 35697026 DOI: 10.1039/d2nh00163b] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
With the rapid development of mobile internet and artificial intelligence, wearable electronic devices have a great market prospect. In particular, information storage and processing of real-time collected data are an indispensable part of wearable electronic devices. Biomaterial-based memristive systems are suitable for storage and processing of the obtained information in wearable electronics due to the accompanying merits, i.e. sustainability, lightweight, degradability, low power consumption, flexibility and biocompatibility. So far, many biomaterial-based flexible and wearable memristive devices were prepared by spin coating or other technologies on a flexible substrate at room temperature. However, mechanical deformation caused by mechanical mismatch between devices and soft tissues leads to the instability of device performance. From the current research and practical application, the device will face great challenges when adapting to different working environments. In fact, some interesting studies have been performed to address the above issues while they were not intensively highlighted and overviewed. Herein, the progress in wearable biomemristive devices is reviewed, and the outlook and perspectives are provided in consideration of the existing challenges during the development of wearable biomemristive systems.
Collapse
Affiliation(s)
- Shuangsuo Mao
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, Fujian Normal University, Fuzhou, Fujian 350117, China.
- College of Physics and Energy, Fujian Normal University, Fuzhou, Fujian 351007, China
| | - Bai Sun
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, Fujian Normal University, Fuzhou, Fujian 350117, China.
- College of Physics and Energy, Fujian Normal University, Fuzhou, Fujian 351007, China
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
- Superconductivity and New Energy R&D Center, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Guangdong Zhou
- Scholl of Artificial Intelligence, Southwest University, Chongqing, 400715, China
| | - Tao Guo
- Department of Mechanical and Mechatronics Engineering, Waterloo Institute for Nanotechnology, Centre for Advanced Materials Joining, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
| | - Jiangqiu Wang
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
- Superconductivity and New Energy R&D Center, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Yong Zhao
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, Fujian Normal University, Fuzhou, Fujian 350117, China.
- College of Physics and Energy, Fujian Normal University, Fuzhou, Fujian 351007, China
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
- Superconductivity and New Energy R&D Center, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| |
Collapse
|
14
|
Song Y, Wu Q, Jia C, Gao Z, Zhang W. High-performance ferroelectric nonvolatile memory based on Gd-and Ni-codoped BiFeO 3 films. RSC Adv 2022; 12:15814-15821. [PMID: 35685697 PMCID: PMC9131732 DOI: 10.1039/d2ra01156e] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 05/03/2022] [Indexed: 11/21/2022] Open
Abstract
BiFeO3 (BFO), Bi0.92Gd0.08FeO3 (BGFO) and Bi0.92Gd0.08Fe0.95Ni0.05O3 (BGFNO) films are epitaxially grown on 0.7 wt% Nb-SrTiO3 (NSTO) substrates. The strong ferroelectric property in BGFNO film is confirmed by piezoresponse force microscopy (PFM) and polarization versus voltage (P-V) measurement. It is also found that the Au/BGFNO/NSTO devices possess a ferroelectric resistance switching (RS) effect. Gd- and Ni-codoped BiFeO3 is found to strongly enhance the resistance on/off ratio. A resistance on/off ratio as large as 3 × 106 is achieved with an applied pulse voltage of -8 V and +4 V. In addition, the devices exhibit excellent retention and anti-fatigue characteristics. The memristor behavior of Au/BGFNO/NSTO is attributed to the switching of polarization states, which modulate the width and height of the barrier at the BGFNO/NSTO interface. The excellent resistive switching properties in Au/BGFNO/NSTO devices indicate the promising application in nonvolatile memory.
Collapse
Affiliation(s)
- Yanling Song
- Henan Key Laboratory of Photovoltaic Materials, Center for Topological Functional Materials, Henan University Kaifeng 475004 People's Republic of China
| | - Qiyuan Wu
- Henan Key Laboratory of Photovoltaic Materials, Center for Topological Functional Materials, Henan University Kaifeng 475004 People's Republic of China
| | - Caihong Jia
- Henan Key Laboratory of Photovoltaic Materials, Center for Topological Functional Materials, Henan University Kaifeng 475004 People's Republic of China
| | - Zhaomeng Gao
- Key Laboratory of Microelectronics Devices & Integrated Technology, Institute of Microelectronics of Chinese Academy of Sciences Beijing 100029 China
| | - Weifeng Zhang
- Henan Key Laboratory of Photovoltaic Materials, Center for Topological Functional Materials, Henan University Kaifeng 475004 People's Republic of China
| |
Collapse
|