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Guo T, Li S, Zhou YN, Lu WD, Yan Y, Wu YA. Interspecies-chimera machine vision with polarimetry for real-time navigation and anti-glare pattern recognition. Nat Commun 2024; 15:6731. [PMID: 39112546 PMCID: PMC11306562 DOI: 10.1038/s41467-024-51178-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 08/01/2024] [Indexed: 08/10/2024] Open
Abstract
Cutting-edge humanoid machine vision merely mimics human systems and lacks polarimetric functionalities that convey the information of navigation and authentic images. Interspecies-chimera vision reserving multiple hosts' capacities will lead to advanced machine vision. However, implementing the visual functions of multiple species (human and non-human) in one optoelectronic device is still elusive. Here, we develop an optically-controlled polarimetry memtransistor based on a van der Waals heterostructure (ReS2/GeSe2). The device provides polarization sensitivity, nonvolatility, and positive/negative photoconductance simultaneously. The polarimetric measurement can identify celestial polarizations for real-time navigation like a honeybee. Meanwhile, cognitive tasks can be completed like a human by sensing, memory, and synaptic functions. Particularly, the anti-glare recognition with polarimetry saves an order of magnitude energy compared to the traditional humanoid counterpart. This technique promotes the concept of interspecies-chimera visual systems that will leverage the advances of autonomous vehicles, medical diagnoses, intelligent robotics, etc.
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Affiliation(s)
- Tao Guo
- School of Physics, Henan Normal University, Henan, 453007, China
- Department of Mechanical and Mechatronics Engineering, and Waterloo Institute of Nanotechnology, Materials Interfaces Foundry, University of Waterloo, Waterloo, ON, N2L 3G1, Canada
| | - Shasha Li
- School of Physics, Henan Normal University, Henan, 453007, China
| | - Y Norman Zhou
- Department of Mechanical and Mechatronics Engineering, and Waterloo Institute of Nanotechnology, Materials Interfaces Foundry, University of Waterloo, Waterloo, ON, N2L 3G1, Canada
| | - Wei D Lu
- Department of Electrical and Computer Engineering, the University of Michigan, Ann Arbor, MI, 48109, USA
| | - Yong Yan
- School of Physics, Henan Normal University, Henan, 453007, China.
- Department of Mechanical and Mechatronics Engineering, and Waterloo Institute of Nanotechnology, Materials Interfaces Foundry, University of Waterloo, Waterloo, ON, N2L 3G1, Canada.
- iGaN Laboratory, School of Microelectronics, University of Science and Technology ofChina Hefei, Anhui, 230026, China.
| | - Yimin A Wu
- Department of Mechanical and Mechatronics Engineering, and Waterloo Institute of Nanotechnology, Materials Interfaces Foundry, University of Waterloo, Waterloo, ON, N2L 3G1, Canada.
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2
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Wang H, Yang J, Yang Z, Liu G, Tang Y, Shao Y, Yan X. Optical-Electrical Coordinately Modulated Memristor Based on 2D Ferroelectric RP Perovskite for Artificial Vision Applications. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2403150. [PMID: 38952052 DOI: 10.1002/advs.202403150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 05/17/2024] [Indexed: 07/03/2024]
Abstract
Traditional artificial vision systems built using separate sensing, computing, and storage units have problems with high power consumption and latency caused by frequent data transmission between functional units. An effective approach is to transfer some memory and computing tasks to the sensor, enabling the simultaneous perception-storage-processing of light signals. Here, an optical-electrical coordinately modulated memristor is proposed, which controls the conductivity by means of polarization of the 2D ferroelectric Ruddlesden-Popper perovskite film at room temperature. The residual polarization shows no significant decay after 109-cycle polarization reversals, indicating that the device has high durability. By adjusting the pulse parameters, the device can simulate the bio-synaptic long/short-term plasticity, which enables the control of conductivity with a high linearity of ≈0.997. Based on the device, a two-layer feedforward neural network is built to recognize handwritten digits, and the recognition accuracy is as high as 97.150%. Meanwhile, building optical-electrical reserve pool system can improve 14.550% for face recognition accuracy, further demonstrating its potential for the field of neural morphological visual systems, with high density and low energy loss.
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Affiliation(s)
- Hong Wang
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, Hebei Key Laboratory of Photo-Electricity Information and Materials, Hebei University, Baoding, 071002, China
| | - Jialiang Yang
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, Hebei Key Laboratory of Photo-Electricity Information and Materials, Hebei University, Baoding, 071002, China
| | - Zheng Yang
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, Hebei Key Laboratory of Photo-Electricity Information and Materials, Hebei University, Baoding, 071002, China
| | - Gongjie Liu
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, Hebei Key Laboratory of Photo-Electricity Information and Materials, Hebei University, Baoding, 071002, China
| | - Yusong Tang
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, Hebei Key Laboratory of Photo-Electricity Information and Materials, Hebei University, Baoding, 071002, China
| | - Yiduo Shao
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, Hebei Key Laboratory of Photo-Electricity Information and Materials, Hebei University, Baoding, 071002, China
| | - Xiaobing Yan
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, Hebei Key Laboratory of Photo-Electricity Information and Materials, Hebei University, Baoding, 071002, China
- Department of Materials Science and Engineering, National University of Singapore, Singapore, 117576, Singapore
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3
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Cheng J, Yuan JH, Li PY, Wang J, Wang Y, Zhang YW, Zheng Y, Zhang P. Applying the Wake-Up-like Effect to Enhance the Capabilities of Two-Dimensional Ferroelectric Field-Effect Transistors. ACS APPLIED MATERIALS & INTERFACES 2024. [PMID: 38712685 DOI: 10.1021/acsami.4c06177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
For traditional ferroelectric field-effect transistors (FeFETs), enhancing the polarization domain of bulk ferroelectric materials is essential to improve device performance. However, there has been limited investigation into the enhancement of polarization field in two-dimensional (2D) ferroelectric material such as CuInP2S6 (CIPS). In this study, similar to bulk ferroelectric materials, CIPS exhibited enhanced polarization field upon application of external cyclic voltage. Moreover, unlike traditional ferroelectric materials, the polarization enhancement of CIPS is not due to redistribution of the defect but rather originates from a mechanism: the long-distance migration of Cu ions. We termed this mechanism the "wake-up-like effect". After incorporating the wake-up-like effect into the graphene/CIPS/WSe2 FeFET device, we successfully increased the hysteresis window and enhanced the current on/off ratio by 4 orders of magnitude. Moreover, the FeFET yielded remarkable achievements, such as multilevel nonvolatile memory with 21 distinct conductance levels, a high on/off ratio exceeding 106, a long retention time exceeding 103 s, and neuromorphic computing with 93% accuracy at recognizing handwritten digits. Introducing the wake-up-like effect to 2D CIPS may pave the way for innovative approaches to achieve advanced multilevel nonvolatile memory and neuromorphic computing capabilities for next-generation micro-nanoelectronic devices.
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Affiliation(s)
- Jie Cheng
- The State Key Laboratory of Precision Manufacturing for Extreme Service Performance, School of Mechanical and Electrical Engineering, Central South University, Changsha 410073, China
| | - Jun-Hui Yuan
- Department of Physics, School of Science, Wuhan University of Technology, Wuhan 430070, China
| | - Pei Yue Li
- National Key Laboratory of Advanced Micro and Nano Manufacture Technology, School of Integrated Circuits, Peking University, Beijing 100871, China
| | - Jiafu Wang
- Department of Physics, School of Science, Wuhan University of Technology, Wuhan 430070, China
| | - Yuan Wang
- Institute of Microelectronics, State Key Laboratory of Analog and Mixed-Signal VLSI, University of Macau, Taipa 999078, Macau, China
| | - You Wei Zhang
- MOE Key Laboratory of Fundamental Physical Quantities Measurement & Hubei Key Laboratory of Gravitation and Quantum Physics, PGMF and School of Physics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Yu Zheng
- The State Key Laboratory of Precision Manufacturing for Extreme Service Performance, School of Mechanical and Electrical Engineering, Central South University, Changsha 410073, China
| | - Pan Zhang
- National Key Laboratory of Advanced Micro and Nano Manufacture Technology, School of Integrated Circuits, Peking University, Beijing 100871, China
- Institute of Microelectronics, State Key Laboratory of Analog and Mixed-Signal VLSI, University of Macau, Taipa 999078, Macau, China
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Maity K, Dayen JF, Doudin B, Gumeniuk R, Kundys B. Graphene Magnetoresistance Control by Photoferroelectric Substrate. ACS NANO 2024. [PMID: 38284570 DOI: 10.1021/acsnano.3c07277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/30/2024]
Abstract
Ultralow dimensionality of 2D layers magnifies their sensitivity to adjacent charges enabling even postprocessing electric control of multifunctional structures. However, functionalizing 2D layers remains an important challenge for on-demand device-property exploitation. Here we report that an electrical and even fully optical way to control and write modifications to the magnetoresistive response of CVD-deposited graphene is achievable through the electrostatics of the photoferroelectric substrate. For electrical control, the ferroelectric polarization switch modifies graphene magnetoresistance by 67% due to a Fermi level shift with related modification in charge mobility. A similar function is also attained entirely by bandgap light due to the substrate photovoltaic effect. Moreover, an all-optical way to imprint and recover graphene magnetoresistance by light is reported as well as magnetic control of graphene transconductance. These findings extend photoferroelectric control in 2D structures to magnetic dimensions and advance wireless operation for sensors and field-effect transistors.
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Affiliation(s)
- Krishna Maity
- Université de Strasbourg, CNRS, Institut de Physique et Chimie des Matériaux de Strasbourg, UMR 7504, 23 rue du Loess, Strasbourg F-67000, France
| | - Jean-François Dayen
- Université de Strasbourg, CNRS, Institut de Physique et Chimie des Matériaux de Strasbourg, UMR 7504, 23 rue du Loess, Strasbourg F-67000, France
| | - Bernard Doudin
- Université de Strasbourg, CNRS, Institut de Physique et Chimie des Matériaux de Strasbourg, UMR 7504, 23 rue du Loess, Strasbourg F-67000, France
| | - Roman Gumeniuk
- Institut für Experimentelle Physik, TU Bergakademie Freiberg, Leipziger Str. 23, Freiberg 09596, Germany
| | - Bohdan Kundys
- Université de Strasbourg, CNRS, Institut de Physique et Chimie des Matériaux de Strasbourg, UMR 7504, 23 rue du Loess, Strasbourg F-67000, France
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Maity K, Dayen JF, Doudin B, Gumeniuk R, Kundys B. Single Wavelength Operating Neuromorphic Device Based on a Graphene-Ferroelectric Transistor. ACS APPLIED MATERIALS & INTERFACES 2023; 15:55948-55956. [PMID: 37983566 DOI: 10.1021/acsami.3c10010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
As global data generation continues to rise, there is an increasing demand for revolutionary in-memory computing methodologies and efficient machine learning solutions. Despite recent progress in electrical and electro-optical simulations of machine learning devices, the all-optical nonthermal function remains challenging, with single wavelength operation still elusive. Here we report on an optical and monochromatic way of neuromorphic signal processing for brain-inspired functions, eliminating the need for electrical pulses. Multilevel synaptic potentiation-depression cycles are successfully achieved optically by leveraging photovoltaic charge generation and polarization within the photoferroelectric substrate interfaced with the graphene sensor. Furthermore, the demonstrated low-power prototype device is able to reproduce exact signal profile of brain tissues yet with more than 2 orders of magnitude faster response. The reported properties should trigger all-optical and low power artificial neuromorphic development based on photoferroelectric structures.
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Affiliation(s)
- Krishna Maity
- Université de Strasbourg, CNRS, Institut de Physique et Chimie des Matériaux de Strasbourg, UMR 7504, 23 rue du Loess, Strasbourg F-67000, France
| | - Jean-François Dayen
- Université de Strasbourg, CNRS, Institut de Physique et Chimie des Matériaux de Strasbourg, UMR 7504, 23 rue du Loess, Strasbourg F-67000, France
| | - Bernard Doudin
- Université de Strasbourg, CNRS, Institut de Physique et Chimie des Matériaux de Strasbourg, UMR 7504, 23 rue du Loess, Strasbourg F-67000, France
| | - Roman Gumeniuk
- Institut für Experimentelle Physik, TU Bergakademie Freiberg, Leipziger Str. 23, Freiberg 09596, Germany
| | - Bohdan Kundys
- Université de Strasbourg, CNRS, Institut de Physique et Chimie des Matériaux de Strasbourg, UMR 7504, 23 rue du Loess, Strasbourg F-67000, France
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Ram A, Maity K, Marchand C, Mahmoudi A, Kshirsagar AR, Soliman M, Taniguchi T, Watanabe K, Doudin B, Ouerghi A, Reichardt S, O'Connor I, Dayen JF. Reconfigurable Multifunctional van der Waals Ferroelectric Devices and Logic Circuits. ACS NANO 2023; 17:21865-21877. [PMID: 37864568 DOI: 10.1021/acsnano.3c07952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2023]
Abstract
Emerging reconfigurable devices are fast gaining popularity in the search for next-generation computing hardware, while ferroelectric engineering of the doping state in semiconductor materials has the potential to offer alternatives to traditional von-Neumann architecture. In this work, we combine these concepts and demonstrate the suitability of reconfigurable ferroelectric field-effect transistors (Re-FeFETs) for designing nonvolatile reconfigurable logic-in-memory circuits with multifunctional capabilities. Modulation of the energy landscape within a homojunction of a 2D tungsten diselenide (WSe2) layer is achieved by independently controlling two split-gate electrodes made of a ferroelectric 2D copper indium thiophosphate (CuInP2S6) layer. Controlling the state encoded in the program gate enables switching between p, n, and ambipolar FeFET operating modes. The transistors exhibit on-off ratios exceeding 106 and hysteresis windows of up to 10 V width. The homojunction can change from Ohmic-like to diode behavior with a large rectification ratio of 104. When programmed in the diode mode, the large built-in p-n junction electric field enables efficient separation of photogenerated carriers, making the device attractive for energy-harvesting applications. The implementation of the Re-FeFET for reconfigurable logic functions shows how a circuit can be reconfigured to emulate either polymorphic ferroelectric NAND/AND logic-in-memory or electronic XNOR logic with a long retention time exceeding 104 s. We also illustrate how a circuit design made of just two Re-FeFETs exhibits high logic expressivity with reconfigurability at runtime to implement several key nonvolatile 2-input logic functions. Moreover, the Re-FeFET circuit demonstrates high compactness, with an up to 80% reduction in transistor count compared to standard CMOS design. The 2D van de Waals Re-FeFET devices therefore exhibit promising potential for both More-than-Moore and beyond-Moore future of electronics, in particular for an energy-efficient implementation of in-memory computing and machine learning hardware, due to their multifunctionality and design compactness.
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Affiliation(s)
- Ankita Ram
- Université de Strasbourg, IPCMS-CNRS UMR 7504, 23 Rue du Loess, 67034 Strasbourg, France
| | - Krishna Maity
- Université de Strasbourg, IPCMS-CNRS UMR 7504, 23 Rue du Loess, 67034 Strasbourg, France
| | - Cédric Marchand
- École Centrale de Lyon, 36 Avenue Guy de Collongue, Ecully 69134, France
| | - Aymen Mahmoudi
- Université Paris-Saclay, CNRS, Centre de Nanosciences et de Nanotechnologies, 91120 Palaiseau, France
| | - Aseem Rajan Kshirsagar
- Department of Physics and Materials Science, University of Luxembourg, Luxembourg 1511, Luxembourg
| | - Mohamed Soliman
- Université de Strasbourg, IPCMS-CNRS UMR 7504, 23 Rue du Loess, 67034 Strasbourg, France
| | - Takashi Taniguchi
- Research Center for Materials Nanoarchitectonics, National Institute for Materials Science, 1-1 Namiki, Tsukuba 305-0044, Japan
| | - Kenji Watanabe
- Research Center for Electronic and Optical Materials, National Institute for Materials Science, 1-1 Namiki, Tsukuba 305-0044, Japan
| | - Bernard Doudin
- Université de Strasbourg, IPCMS-CNRS UMR 7504, 23 Rue du Loess, 67034 Strasbourg, France
- Institut Universitaire de France, 1 rue Descartes, 75231 Paris cedex 05, France
| | - Abdelkarim Ouerghi
- Université Paris-Saclay, CNRS, Centre de Nanosciences et de Nanotechnologies, 91120 Palaiseau, France
| | - Sven Reichardt
- Department of Physics and Materials Science, University of Luxembourg, Luxembourg 1511, Luxembourg
| | - Ian O'Connor
- École Centrale de Lyon, 36 Avenue Guy de Collongue, Ecully 69134, France
| | - Jean-Francois Dayen
- Université de Strasbourg, IPCMS-CNRS UMR 7504, 23 Rue du Loess, 67034 Strasbourg, France
- Institut Universitaire de France, 1 rue Descartes, 75231 Paris cedex 05, France
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Luo J, Tian G, Zhang DG, Zhang XC, Lu ZN, Zhang ZD, Cai JW, Zhong YN, Xu JL, Gao X, Wang SD. Voltage-Mode Ferroelectric Synapse for Neuromorphic Computing. ACS APPLIED MATERIALS & INTERFACES 2023; 15:48452-48461. [PMID: 37802499 DOI: 10.1021/acsami.3c09506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Ferroelectric materials with a modulable polarization extent hold promise for exploring voltage-driven neuromorphic hardware, in which direct current flow can be minimized. Utilizing a single active layer of an insulating ferroelectric polymer, we developed a voltage-mode ferroelectric synapse that can continuously and reversibly update its states. The device states are straightforwardly manifested in the form of variable output voltage, enabling large-scale direct cascading of multiple ferroelectric synapses to build a deep physical neural network. Such a neural network based on potential superposition rather than current flow is analogous to the biological counterpart driven by action potentials in the brain. A high accuracy of over 97% for the simulation of handwritten digit recognition is achieved using the voltage-mode neural network. The controlled ferroelectric polarization, revealed by piezoresponse force microscopy, turns out to be responsible for the synaptic weight updates in the ferroelectric synapses. The present work demonstrates an alternative strategy for the design and construction of emerging artificial neural networks.
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Affiliation(s)
- Jie Luo
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, P. R. China
| | - Guo Tian
- Institute for Advanced Materials and Guangdong Provincial Key Laboratory of Optical Information Materials and Technology, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, P. R. China
| | - Ding-Guo Zhang
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, P. R. China
| | - Xing-Chen Zhang
- Institute for Advanced Materials and Guangdong Provincial Key Laboratory of Optical Information Materials and Technology, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, P. R. China
| | - Zhen-Ni Lu
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, P. R. China
| | - Zhong-Da Zhang
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, P. R. China
| | - Jia-Wei Cai
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, P. R. China
| | - Ya-Nan Zhong
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, P. R. China
| | - Jian-Long Xu
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, P. R. China
| | - Xu Gao
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, P. R. China
| | - Sui-Dong Wang
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, P. R. China
- Macao Institute of Materials Science and Engineering (MIMSE), MUST-SUDA Joint Research Center for Advanced Functional Materials, Macau University of Science and Technology, Taipa, Macao 999078, P. R. China
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Noor-A-Alam M, Nolan M. Engineering Ferroelectricity and Large Piezoelectricity in h-BN. ACS APPLIED MATERIALS & INTERFACES 2023; 15:42737-42745. [PMID: 37650582 PMCID: PMC10510043 DOI: 10.1021/acsami.3c07744] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 08/16/2023] [Indexed: 09/01/2023]
Abstract
Hexagonal boron nitride (h-BN) is a well-known layered van der Waals (vdW) material that exhibits no spontaneous electric polarization due to its centrosymmetric structure. Extensive density functional theory (DFT) calculations are used to demonstrate that doping through the substitution of B by isovalent Al and Ga breaks the inversion symmetry and induces local dipole moments along the c-axis, which promotes a ferroelectric (FE) alignment over antiferroelectric. For doping concentrations below 25%, a "protruded layered" structure in which the dopant atoms protrude out of the planar h-BN layers is energetically more stable than the flat layered structure of pristine h-BN or a wurtzite structure similar to w-AlN. The computed polarization, between 7.227 and 21.117 μC/cm2, depending on dopant concentration and the switching barrier (16.684 and 45.838 meV/atom) for the FE polarization reversal are comparable to that of other well-known FEs. Interestingly, doping of h-BN also induces a large negative piezoelectric response in otherwise nonpiezoelectric h-BN. For example, we compute d33 of -24.214 pC/N for Ga0.125B0.875N, which is about 5 times larger than that of pure w-AlN (5 pC/N), although the computed e33 (-1.164 C/m2) is about 1.6 times lower than that of pure w-AlN (1.462 C/m2). Because of the layered structure, the rather small elastic constant C33 provides the origin of the large d33. Moreover, doping makes h-BN an electric auxetic piezoelectric. We also show that ferroelectricity in doped h-BN may persist down to its trilayer, which indicates high potential for applications in FE nonvolatile memories.
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Affiliation(s)
- Mohammad Noor-A-Alam
- Tyndall National Institute, University College Cork, Lee Maltings, Dyke Parade, Cork T12 R5CP, Ireland
| | - Michael Nolan
- Tyndall National Institute, University College Cork, Lee Maltings, Dyke Parade, Cork T12 R5CP, Ireland
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Wang H, Wen Y, Zeng H, Xiong Z, Tu Y, Zhu H, Cheng R, Yin L, Jiang J, Zhai B, Liu C, Shan C, He J. 2D Ferroic Materials for Nonvolatile Memory Applications. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023:e2305044. [PMID: 37486859 DOI: 10.1002/adma.202305044] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 07/21/2023] [Indexed: 07/26/2023]
Abstract
The emerging nonvolatile memory technologies based on ferroic materials are promising for producing high-speed, low-power, and high-density memory in the field of integrated circuits. Long-range ferroic orders observed in 2D materials have triggered extensive research interest in 2D magnets, 2D ferroelectrics, 2D multiferroics, and their device applications. Devices based on 2D ferroic materials and heterostructures with an atomically smooth interface and ultrathin thickness have exhibited impressive properties and significant potential for developing advanced nonvolatile memory. In this context, a systematic review of emergent 2D ferroic materials is conducted here, emphasizing their recent research on nonvolatile memory applications, with a view to proposing brighter prospects for 2D magnetic materials, 2D ferroelectric materials, 2D multiferroic materials, and their relevant devices.
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Affiliation(s)
- Hao Wang
- Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology, Wuhan University, Wuhan, 430072, China
| | - Yao Wen
- Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology, Wuhan University, Wuhan, 430072, China
| | - Hui Zeng
- Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology, Wuhan University, Wuhan, 430072, China
| | - Ziren Xiong
- Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology, Wuhan University, Wuhan, 430072, China
| | - Yangyuan Tu
- Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology, Wuhan University, Wuhan, 430072, China
| | - Hao Zhu
- Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology, Wuhan University, Wuhan, 430072, China
| | - Ruiqing Cheng
- Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology, Wuhan University, Wuhan, 430072, China
| | - Lei Yin
- Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology, Wuhan University, Wuhan, 430072, China
| | - Jian Jiang
- Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology, Wuhan University, Wuhan, 430072, China
| | - Baoxing Zhai
- Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology, Wuhan University, Wuhan, 430072, China
| | - Chuansheng Liu
- Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology, Wuhan University, Wuhan, 430072, China
| | - Chongxin Shan
- Henan Key Laboratory of Diamond Optoelectronic Materials and Devices, Key Laboratory of Material Physics, Ministry of Education, School of Physics, Zhengzhou University, Zhengzhou, 450052, China
| | - Jun He
- Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology, Wuhan University, Wuhan, 430072, China
- Hubei Luojia Laboratory, Wuhan, 430079, China
- Wuhan Institute of Quantum Technology, Wuhan, 430206, China
- Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing, 100190, China
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