Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 55
Filtrar
Mais filtros










Base de dados
Intervalo de ano de publicação
1.
Sci Adv ; 10(23): eadn1345, 2024 Jun 07.
Artigo em Inglês | MEDLINE | ID: mdl-38848373

RESUMO

Ferroelectric transistors based on hafnia-based ferroelectrics exhibit tremendous potential as next-generation memories owing to their high-speed operation and low power consumption. Nevertheless, these transistors face limitations in terms of memory window, which directly affects their ability to support multilevel characteristics in memory devices. Furthermore, the absence of an efficient operational technique capable of achieving multilevel characteristics has hindered their development. To address these challenges, we present a gate stack engineering method and an efficient operational approach for ferroelectric transistors to achieve 16-level data per cell operation. By using the suggested engineering method, we demonstrate the attainment of a substantial memory window of 10 V without increasing the device area. Additionally, we propose a displacement current control method, facilitating one-shot programming to the desired state. Remarkably, we suggest the compatibility of these proposed methods with three-dimensional (3D) structures. This study underscores the potential of ferroelectric transistors for next-generation 3D memory applications.

2.
ACS Appl Mater Interfaces ; 16(26): 33763-33770, 2024 Jul 03.
Artigo em Inglês | MEDLINE | ID: mdl-38899561

RESUMO

Ferroelectric transistors are considered promising for next-generation 3D NAND technology due to their lower power consumption and faster operation compared to conventional charge-trap flash memories. However, ensuring their suitability for such applications requires a thorough investigation of array-scale reliability. This study specifically examines the suitability of hafnia-based ferroelectric transistors for advanced 3D NAND applications, with a specific focus on establishing a disturb-free voltage scheme to ensure the reliability of ferroelectric transistors within the array. Our key finding highlights the crucial role of optimal pass voltage in achieving disturb-free operation in both 2D and 3D ferroelectric NAND arrays. Additionally, the study indicates that read disturb remains negligible when an appropriate read voltage is applied. These insights provide a practical strategy for achieving reliable operation in 2D and 3D ferroelectric NAND, highlighting the potential of hafnia-based ferroelectric materials to meet the evolving requirements of high-density and reliable NAND flash memory applications.

3.
Small ; 20(13): e2306871, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-37967323

RESUMO

Hafnia-based ferroelectrics have gained much attention because they can be used in highly scaled, advanced complementary metal-oxide semiconductor (CMOS) memory devices. However, thermal stability should be considered when integrating hafnia-based ferroelectric transistors in advanced CMOS devices, as they can be exposed to high-temperature processes. This work proposed that doping of Al in hafnia-based ferroelectric material can lead to high thermal stability. A ferroelectric capacitor based on Al-doped hafnia, which can be used for one-transistor-one-capacitor applications, exhibits stable operation even after annealing at 900 °C. Moreover, it demonstrates that the ferroelectric transistors based on Al-doped hafnia for one-transistor applications, such as ferroelectric NAND, retain their memory states for 10 years at 100 °C. This study presents a practical method to achieve thermally stable ferroelectric memories capable of enduring high-temperature processes and operation conditions.

4.
Nanotechnology ; 35(1)2023 Oct 13.
Artigo em Inglês | MEDLINE | ID: mdl-37830748

RESUMO

The threshold-switching behaviors of the synapses lead to energy-efficient operation in the neural computing system. Here, we demonstrated the threshold-switching memory devices by inserting the ZnO layer into the ionic synaptic devices. The EMIm(AlCl3)Cl is utilized as the electrolyte because its conductance can be tuned by the charge states of the Al-based ions. The redox reactions of the Al ions in the electrolyte can lead to the analog resistive switching characteristics, such as excitatory postsynaptic current, paired-pulse facilitation, potentiation, and depression. By inserting the ZnO layer into the EMIm(AlCl3)-based ionic synaptic devices, the threshold switching behaviors are demonstrated. Using the resistivity difference between ZnO and EMIm(AlCl3)Cl, the analog resistive switching behaviors are tunned as the threshold-switching behaviors. The threshold-switching behaviors are achieved by applying the spike stimuli to the device. Demonstration of the threshold-switching behaviors of the ionic synaptic devices has a possibility to achieve high energy-efficiency for the ion-based artificial synapses.

5.
ACS Nano ; 17(13): 11994-12039, 2023 Jul 11.
Artigo em Inglês | MEDLINE | ID: mdl-37382380

RESUMO

Memristive technology has been rapidly emerging as a potential alternative to traditional CMOS technology, which is facing fundamental limitations in its development. Since oxide-based resistive switches were demonstrated as memristors in 2008, memristive devices have garnered significant attention due to their biomimetic memory properties, which promise to significantly improve power consumption in computing applications. Here, we provide a comprehensive overview of recent advances in memristive technology, including memristive devices, theory, algorithms, architectures, and systems. In addition, we discuss research directions for various applications of memristive technology including hardware accelerators for artificial intelligence, in-sensor computing, and probabilistic computing. Finally, we provide a forward-looking perspective on the future of memristive technology, outlining the challenges and opportunities for further research and innovation in this field. By providing an up-to-date overview of the state-of-the-art in memristive technology, this review aims to inform and inspire further research in this field.

6.
ACS Omega ; 8(20): 18180-18185, 2023 May 23.
Artigo em Inglês | MEDLINE | ID: mdl-37251138

RESUMO

Zirconium-doped hafnium oxide (HfZrOx) is one of the promising ferroelectric materials for next-generation memory applications. To realize high-performance HfZrOx for next-generation memory applications, the formation of defects in HfZrOx, including oxygen vacancies and interstitials, needs to be optimized, as it can affect the polarization and endurance characteristics of HfZrOx. In this study, we investigated the effects of ozone exposure time during the atomic layer deposition (ALD) process on the polarization and endurance characteristics of 16-nm-thick HfZrOx. HfZrOx films showed different polarization and endurance characteristics depending on the ozone exposure time. HfZrOx deposited using the ozone exposure time of 1 s showed small polarization and large defect concentration. The increase of the ozone exposure time to 2.5 s could reduce the defect concentration and improve the polarization characteristics of HfZrOx. When the ozone exposure time further increased to 4 s, a reduction of polarization was observed in HfZrOx due to the formation of oxygen interstitials and non-ferroelectric monoclinic phases. HfZrOx, with an ozone exposure time of 2.5 s, exhibited the most stable endurance characteristics because of the low initial defect concentration in HfZrOx, which was confirmed by the leakage current analysis. This study shows that the ozone exposure time of ALD needs to be controlled to optimize the formation of defects in HfZrOx films for the improvement of polarization and endurance characteristics.

7.
ACS Appl Mater Interfaces ; 15(14): 18055-18064, 2023 Apr 12.
Artigo em Inglês | MEDLINE | ID: mdl-37000192

RESUMO

Artificial synapse is the basic unit of a neuromorphic computing system. However, there is a need to explore suitable synaptic devices for the emulation of synaptic dynamics. This study demonstrates a photonic multimodal synaptic device by implementing a perovskite quantum dot charge-trapping layer in the organic poly(3-hexylthiophene-2,5-diyl) (P3HT) channel transistor. The proposed device presents favorable band alignment that facilitates spatial separation of photogenerated charge carriers. The band alignment serves as the basis of optically induced charge trapping, which enables nonvolatile memory characteristics in the device. Furthermore, high photoresponse and excellent synaptic characteristics, such as short-term plasticity, long-term plasticity, excitatory postsynaptic current, and paired-pulse facilitation, are obtained through gate voltage regulation. Photosynaptic characteristics obtained from the device showed a multiwavelength response and a large dynamic range (∼103) that is suitable for realizing a highly accurate artificial neural network. Moreover, the device showed nearly linear synaptic weight update characteristics with incremental depression electric gate pulse. The simulation based on the experimental data showed excellent pattern recognition accuracy (∼85%) after 120 epochs. The results of this study demonstrate the feasibility of the device as an optical synapse in the next-generation neuromorphic system.

8.
Nat Commun ; 14(1): 504, 2023 Jan 31.
Artigo em Inglês | MEDLINE | ID: mdl-36720868

RESUMO

Hardware-based neural networks (NNs) can provide a significant breakthrough in artificial intelligence applications due to their ability to extract features from unstructured data and learn from them. However, realizing complex NN models remains challenging because different tasks, such as feature extraction and classification, should be performed at different memory elements and arrays. This further increases the required number of memory arrays and chip size. Here, we propose a three-dimensional ferroelectric NAND (3D FeNAND) array for the area-efficient hardware implementation of NNs. Vector-matrix multiplication is successfully demonstrated using the integrated 3D FeNAND arrays, and excellent pattern classification is achieved. By allocating each array of vertical layers in 3D FeNAND as the hidden layer of NN, each layer can be used to perform different tasks, and the classification of color-mixed patterns is achieved. This work provides a practical strategy to realize high-performance and highly efficient NN systems by stacking computation components vertically.

9.
Adv Mater ; 35(22): e2206864, 2023 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-36484488

RESUMO

Ferroelectric materials have been intensively investigated for high-performance nonvolatile memory devices in the past decades, owing to their nonvolatile polarization characteristics. Ferroelectric memory devices are expected to exhibit lower power consumption and higher speed than conventional memory devices. However, non-complementary metal-oxide-semiconductor (CMOS) compatibility and degradation due to fatigue of traditional perovskite-based ferroelectric materials have hindered the development of high-density and high-performance ferroelectric memories in the past. The recently developed hafnia-based ferroelectric materials have attracted immense attention in the development of advanced semiconductor devices. Because hafnia is typically used in CMOS processes, it can be directly incorporated into current semiconductor technologies. Additionally, hafnia-based ferroelectrics show high scalability and large coercive fields that are advantageous for high-density memory devices. This review summarizes the recent developments in ferroelectric devices, especially ferroelectric transistors, for next-generation memory and neuromorphic applications. First, the types of ferroelectric memories and their operation mechanisms are reviewed. Then, issues limiting the realization of high-performance ferroelectric transistors and possible solutions are discussed. The experimental demonstration of ferroelectric transistor arrays, including 3D ferroelectric NAND and its operation characteristics, are also reviewed. Finally, challenges and strategies toward the development of next-generation memory and neuromorphic applications based on ferroelectric transistors are outlined.

10.
ACS Appl Mater Interfaces ; 14(37): 42308-42316, 2022 Sep 21.
Artigo em Inglês | MEDLINE | ID: mdl-36069456

RESUMO

Neurons are vital components of the brain. When stimulated by neurotransmitters at the dendrites, neurons deliver signals as changes in the membrane potential by ion movement. The signal transmission of a nervous system exhibits a high energy efficiency. These characteristics of neurons are being exploited to develop efficient neuromorphic computing systems. In this study, we develop chemical synapses for neuromorphic devices and emulate the signaling processes in a nervous system using a polymer membrane, in which the ionic permeability can be controlled. The polymer membrane comprises poly(diallyl-dimethylammonium chloride) and poly(3-sulfopropyl acrylate potassium salt), which have positive and negative charges, respectively. The ionic permeability of the polymer membrane is controlled by the injection of a neurotransmitter solution. This device emulates the signal transmission behavior of biological neurons depending on the concentration of the injected neurotransmitter solution. The proposed artificial neuronal signaling device can facilitate the development of bio-realistic neuromorphic devices.


Assuntos
Polímeros , Sinapses , Encéfalo/fisiologia , Potenciais da Membrana , Neurônios/fisiologia , Sinapses/fisiologia
11.
J Phys Chem Lett ; 13(24): 5638-5647, 2022 Jun 23.
Artigo em Inglês | MEDLINE | ID: mdl-35708321

RESUMO

There is an increased demand for next-generation memory devices with high density and fast operation speed to replace conventional memory devices. Memristors are promising candidates for next-generation memory devices because of their scalability, stable data retention, low power consumption, and fast operation. Among the various types of memristors, halide perovskites exhibit potential as emerging materials for memristors by using hysteresis based on the movement of defects or ions in halide perovskites. However, research on the implementation of perovskite materials as memristors is in its early stages; some challenges and problems must be solved to enable the practical application of halide perovskites for next-generation memory devices. From this perspective, we highlight the recent progress in memristors that use halide perovskites. Moreover, we introduce a strategy to enhance the performance and analyze the operation mechanism of memory devices that use halide perovskites. Finally, we summarize the challenges in the development of device technology to use halide perovskites in next-generation memory devices.

12.
Sci Adv ; 8(14): eabm8537, 2022 Apr 08.
Artigo em Inglês | MEDLINE | ID: mdl-35394830

RESUMO

Convolutional neural networks (CNNs) have gained much attention because they can provide superior complex image recognition through convolution operations. Convolution processes require repeated multiplication and accumulation operations, which are difficult tasks for conventional computing systems. Compute-in-memory (CIM) that uses parallel data processing is an ideal device structure for convolution operations. CIM based on two-terminal synaptic devices with a crossbar structure has been developed, but unwanted leakage current paths and the high-power consumption remain as the challenges. Here, we demonstrate integrated ferroelectric thin-film transistor (FeTFT) synaptic arrays that can provide efficient parallel programming and data processing for CNNs by the selective and accurate control of polarization in the ferroelectric layer. In addition, three-terminal FeTFTs can act as both nonvolatile memory and access device, which tackle issues from two-terminal devices. An integrated FeTFT synaptic array with parallel programming capabilities can perform convolution operations to extract image features with a high-recognition accuracy.

13.
ACS Appl Mater Interfaces ; 14(3): 4371-4377, 2022 Jan 26.
Artigo em Inglês | MEDLINE | ID: mdl-35014262

RESUMO

Organic-inorganic halide perovskites (OIHPs) have emerged as an active layer for resistive switching memory (RSM). Among various OIHPs, two-dimensional OIHPs are advantageous in RSMs because of their stability. This stability can be further improved using two-dimensional Dion-Jacobson OIHPs. Moreover, OIHP-based RSMs operated by the formation of halide-ion filaments are affected by grain boundaries because they can act as a shortcut for ion migration. Therefore, it is essential to control the grains in OIHPs for reliable memory operation. Here, we present RSMs using Dion-Jacobson OIHP with controlled grain sizes. The grain sizes of the OIHP are effectively controlled by adjusting the ratio of the N,N-dimethylformamide and dimethyl sulfoxide. The controlled grain sizes can modulate the paths for halide ion migration, which enables the change of the on/off ratio in RSM. In addition, cross-point array structure is essential for high-density memory applications. However, in the cross-point array structure, unwanted current flow through unselected memory cells can happen due to sneak-current paths, so it is necessary to suppress leakage current from neighboring cells by adopting selector devices. We demonstrate the application of selector devices to OIHP-based RSMs to prevent sneak current paths. These results provide the potential of OIHP for use in high-density memory applications.

14.
Nat Commun ; 12(1): 3527, 2021 Jun 10.
Artigo em Inglês | MEDLINE | ID: mdl-34112776

RESUMO

Resistive switching memory that uses halide perovskites (HP) has been considered as next-generation storage devices due to low operation voltage and high on/off ratio. However, the memory still faces challenges for stable operation with fast switching speed, which hinders the practical application. Thus, it should be considered from the stage of designing the HP for memory applications. Here, we design the perovskite memory using a high-throughput screening based on first-principles calculations. Total 696 compositions in four different crystal structures are investigated and essential parameters including stability, vacancy formation, and migration are considered as the descriptor. We select dimer-Cs3Sb2I9 as an optimal HP for memory; the device that uses dimer-Cs3Sb2I9 has ultra-fast switching speed (~20 ns) compared to the device that uses layer-Cs3Sb2I9 (>100 ns). The use of lead-free perovskite avoids environmental problems caused by lead in perovskite. These results demonstrate the feasibility to design the memory with ultra-fast switching speed.

15.
Small ; 17(29): e2100401, 2021 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-34106519

RESUMO

Atomic switch-based selectors, which utilize the formation of conductive filaments by the migration of ions, are researched for cross-point array architecture due to their simple structure and high selectivity. However, the difficulty in controlling the formation of filaments causes uniformity and reliability issues. Here, a multilayer selector with Pt/Ag-doped ZnO/ZnO/Ag-doped ZnO/Pt structure by the sputtering process is presented. A multilayer structure enables control of the filament formation by preventing excessive influx of Ag ions. The multilayer selector device exhibits a high on-current density of 2 MA cm-2 , which can provide sufficient current for the operation with the memory device. Also, the device exhibits high selectivity of 1010 and a low off-current of 10-13 A. The threshold voltage of selector devices can be controlled by modulating the thickness of the ZnO layer. By connecting a multilayer selector device to a resistive switching memory, the leakage current of the memory device can be reduced. These results demonstrate that a multilayer structure can be used in a selector device to improve selectivity and reliability for use in high-density memory devices.

16.
Sci Adv ; 7(3)2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-33523886

RESUMO

Ferroelectric memory has been substantially researched for several decades as its potential to obtain higher speed, lower power consumption, and longer endurance compared to conventional flash memory. Despite great deal of effort to develop ferroelectric memory based on perovskite oxides on Si, formation of unwanted interfacial layer substantially compromises the performance of the ferroelectric memory. Furthermore, three-dimensional (3D) integration has been unimaginable because of high processing temperature, non-CMOS compatibility, difficulty in scaling, and complex compositions of perovskite oxides. Here, we demonstrate a unique strategy to tackle critical issues by applying hafnia-based ferroelectrics and oxide semiconductors. Thus, it is possible to avoid the formation of interfacial layer that finally allows unprecedented Si-free 3D integration of ferroelectric memory. This strategy yields memory performance that could be achieved neither by the conventional flash memory nor by the previous perovskite ferroelectric memories. Device simulation confirms that this strategy can realize ultrahigh-density 3D memory integration.

17.
ACS Appl Mater Interfaces ; 13(1): 1021-1026, 2021 Jan 13.
Artigo em Inglês | MEDLINE | ID: mdl-33369379

RESUMO

Halide perovskites (HPs) have possible uses as an active layer for emerging memory devices due to their low operation voltage and high on/off ratio. However, HP-based memory devices, which are operated by the formation of a conductive filament, still suffer from reliability issues such as limited endurance and stability. To solve the problems, it is essential to control filament formation in the active layer. Here, we present nanoscale HP-based memory devices that have a Ag-doped ZnO (AZO) layer on HP. The AZO layer is used as a Ag ion reservoir for filament formation in HP, and this reservoir enables control of filament formation. By adjusting the Ag concentration in the AZO layer, the controlled filament composed of Ag can be formed; as a result, the memory device has excellent endurance (3 × 104 cycles) compared to the device that uses a Ag electrode instead of an AZO layer (4 × 102 cycles). Also, an AZO layer can passivate HP, so the device operates stably in ambient air for 15 days with a high on/off ratio (106). These results demonstrate that the introduction of the AZO layer can improve the reliability of HP-based memory devices for high-density applications.

18.
iScience ; 23(12): 101846, 2020 Dec 18.
Artigo em Inglês | MEDLINE | ID: mdl-33319174

RESUMO

Neuromorphic devices and systems have attracted attention as next-generation computing due to their high efficiency in processing complex data. So far, they have been demonstrated using both machine-learning software and complementary metal-oxide-semiconductor-based hardware. However, these approaches have drawbacks in power consumption and learning speed. An energy-efficient neuromorphic computing system requires hardware that can mimic the functions of a brain. Therefore, various materials have been introduced for the development of neuromorphic devices. Here, recent advances in neuromorphic devices are reviewed. First, the functions of biological synapses and neurons are discussed. Also, deep neural networks and spiking neural networks are described. Then, the operation mechanism and the neuromorphic functions of emerging devices are reviewed. Finally, the challenges and prospects for developing neuromorphic devices that use emerging materials are discussed.

19.
Adv Sci (Weinh) ; 7(16): 2001367, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32832372

RESUMO

Memory devices have been advanced so much, but still it is highly required to find stable and reliable materials with low-power consumption. Halide perovskites (HPs) have been recently adopted for memory application since they have advantages of fast switching based on ionic motion in crystal structure. However, HPs also suffer from poor stability, so it is necessary to improve the stability of HPs. In this regard, combined first-principles screening and experimental verification are performed to design HPs that have high environmental stability and low-operating voltage for memory devices. First-principles screening identifies 2D layered AB2X5 structure as the best candidate switching layer for memory devices, because it has lower formation energy and defect formation energy than 3D ABX3 or other layered structures (A3B2X7, A2BX4). To verify results, all-inorganic 2D layered CsPb2Br5 is synthesized and used in memory devices. The memory devices that use CsPb2Br5 show much better stability and lower operating voltages than devices that use CsPbBr3. These findings are expected to provide new opportunity to design materials for reliable device applications based on calculation, screening, and experimental verification.

20.
ACS Appl Mater Interfaces ; 12(24): 27467-27475, 2020 Jun 17.
Artigo em Inglês | MEDLINE | ID: mdl-32484645

RESUMO

The aim of the neuromorphic computing is to emulate energy-efficient and smart data-processing ability of the biological brain, which is achieved by massively interconnected neurons and synapses. The strength of a connection between two neurons is modified by homosynaptic and heterosynaptic plasticity. As current research in the neuromorphic device is mainly focused on emulating homosynaptic plasticity, complex biological functions are not easy to mimic because they require both homosynaptic and heterosynaptic plasticity. We demonstrate the use of a liquid crystal-carbon nanotube (LC-CNT) composite as a resistive switching material that can emulate both the homosynaptic and heterosynaptic functions of biological neurons. The LC-CNT composite undergoes resistance change by CNT alignment and aggregated wire formation subjected to an applied electric field. A two-terminal device that exploits this mechanism achieves analog switching and homosynaptic potentiation. In a multiterminal device structure, the modulatory interneuron could tune the synaptic properties to perform heterosynaptic functions such as heterosynaptic potentiation, heterosynaptic facilitation, and synaptic weight normalization to emulate complex biological functions of a brain. Artificial synapses that exploit this multifunctionality of the LC-CNT composite have uses in next-generation neuromorphic devices.


Assuntos
Cristais Líquidos/química , Nanotubos de Carbono/química , Animais , Interneurônios/citologia , Plasticidade Neuronal/fisiologia
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...