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Speckbacher M, Rinderle M, Bienek O, Sharp ID, Gagliardi A, Tornow M. Conductive filament distribution in nano-scale electrochemical metallization cells. NANOSCALE 2024. [PMID: 39397512 DOI: 10.1039/d4nr02870h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/15/2024]
Abstract
We report a combined experimental and theoretical study of the spatial distributions and sizes of conductive filaments in nano-scale electrochemical metallization (ECM) cells. Each cell comprises a silver nanocube as active electrode, a titanium dioxide (TiO2) or aluminum oxide (Al2O3) layer as dielectric, and a highly-doped silicon substrate as passive counter electrode. Following electroforming of the ECM cell and subsequent mechanical delamination of the silver nanocubes, current maps at previous particle locations reveal an intriguing metal distribution in the TiO2, with preferential accumulation close to the original locations of the nanocube edges. We assign this behavior to electric field enhancements close to the cube edge positions. In contrast, filaments in Al2O3 layers show a comparatively homogenous distribution, which may be assigned to its lower dielectric permittivity. By increasing the oxide thickness, the total area of conductive spots in the current maps increases monotonically for both materials. Kinetic Monte-Carlo simulations of ion migration dynamics in TiO2 confirm the experimental observations, describing both the preferred locations and oxide thickness-dependent metal loadings associated with filament formation. Overall, our findings are highly valuable for the design of future electrochemical metallization cells, especially in the sub-100 nm regime, where optimal filament control is of major importance for achieving lowest device-to-device variability.
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Affiliation(s)
- Maximilian Speckbacher
- Molecular Electronics, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Technical University of Munich, 85748 Garching, Germany.
| | - Michael Rinderle
- Chair of Simulation of Nanosystems for Energy Conversion, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Atomistic Modeling Center (AMC), Munich Data Science Institute (MDSI), Technical University of Munich, 85748 Garching, Germany.
| | - Oliver Bienek
- Walter Schottky Institute, Technical University of Munich, 85748 Garching, Germany
- Physics Department, TUM School of Natural Sciences, Technical University of Munich, 85748 Garching, Germany
| | - Ian D Sharp
- Walter Schottky Institute, Technical University of Munich, 85748 Garching, Germany
- Physics Department, TUM School of Natural Sciences, Technical University of Munich, 85748 Garching, Germany
| | - Alessio Gagliardi
- Chair of Simulation of Nanosystems for Energy Conversion, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Atomistic Modeling Center (AMC), Munich Data Science Institute (MDSI), Technical University of Munich, 85748 Garching, Germany.
| | - Marc Tornow
- Molecular Electronics, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Technical University of Munich, 85748 Garching, Germany.
- Fraunhofer Institute for Electronic Microsystems and Solid State Technologies (EMFT), 80686 Munich, Germany
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Wang Y, Wang H, Guo D, An Z, Zheng J, Huang R, Bi A, Jiang J, Wang S. High-Linearity Ta 2O 5 Memristor and Its Application in Gaussian Convolution Image Denoising. ACS APPLIED MATERIALS & INTERFACES 2024; 16:47879-47888. [PMID: 39188162 DOI: 10.1021/acsami.4c09056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/28/2024]
Abstract
In the image Gaussian filtering process, convolving with a Gaussian matrix is essential due to the numerous arithmetic computations involved, predominantly multiplications and additions. This can heavily tax the system's memory, particularly with frequent use. To address this issue, a W/Ta2O5/Ag memristor was employed to substantially mitigate the computational overhead associated with convolution operations. Additionally, an interlayer of ZnO was subsequently introduced into the memristor. The resulting Ta2O5/ZnO heterostructure layer exhibited improved linearity in the pulse response, which enhanced linearity facilitates easy adjustment of the conductance magnitude through a linear mapping of the number of pulses and the conductance. Subsequently, the conductance of the W/Ta2O5/ZnO/Ag bilayer memristor was employed as the weights for the convolution kernel in convolution operations. Gaussian noise removal in image processing was achieved by assembling a 5 × 5 memristor array as the kernel. When denoising was performed using memristor arrays, compared to denoising achieved through Gaussian matrix convolution, an average loss of less than 5% was observed. The provided memristors demonstrate significant potential in convolutional computations, particularly for subsequent applications in convolutional neural networks (CNNs).
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Affiliation(s)
- Yucheng Wang
- Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen 518057, China
| | - Hexin Wang
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Dingyun Guo
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Zeyang An
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Jiawei Zheng
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Ruixi Huang
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Antong Bi
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Junyu Jiang
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Shaoxi Wang
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
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3
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Gamage S, Manna S, Zajac M, Hancock S, Wang Q, Singh S, Ghafariasl M, Yao K, Tiwald TE, Park TJ, Landau DP, Wen H, Sankaranarayanan SKS, Darancet P, Ramanathan S, Abate Y. Infrared Nanoimaging of Hydrogenated Perovskite Nickelate Memristive Devices. ACS NANO 2024; 18:2105-2116. [PMID: 38198599 PMCID: PMC10811663 DOI: 10.1021/acsnano.3c09281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 12/21/2023] [Accepted: 12/22/2023] [Indexed: 01/12/2024]
Abstract
Solid-state devices made from correlated oxides, such as perovskite nickelates, are promising for neuromorphic computing by mimicking biological synaptic function. However, comprehending dopant action at the nanoscale poses a formidable challenge to understanding the elementary mechanisms involved. Here, we perform operando infrared nanoimaging of hydrogen-doped correlated perovskite, neodymium nickel oxide (H-NdNiO3, H-NNO), devices and reveal how an applied field perturbs dopant distribution at the nanoscale. This perturbation leads to stripe phases of varying conductivity perpendicular to the applied field, which define the macroscale electrical characteristics of the devices. Hyperspectral nano-FTIR imaging in conjunction with density functional theory calculations unveils a real-space map of multiple vibrational states of H-NNO associated with OH stretching modes and their dependence on the dopant concentration. Moreover, the localization of excess charges induces an out-of-plane lattice expansion in NNO which was confirmed by in situ X-ray diffraction and creates a strain that acts as a barrier against further diffusion. Our results and the techniques presented here hold great potential for the rapidly growing field of memristors and neuromorphic devices wherein nanoscale ion motion is fundamentally responsible for function.
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Affiliation(s)
- Sampath Gamage
- Department
of Physics and Astronomy, University of
Georgia, Athens, Georgia 30602, United States
| | - Sukriti Manna
- Center for
Nanoscale Materials, Argonne National Laboratory, Lemont, Illinois 60439, United States
- Department
of Mechanical and Industrial Engineering, University of Illinois, Chicago, Illinois 60607, United States
| | - Marc Zajac
- Advanced
Photon Source, Argonne National Laboratory, Lemont, Illinois 60439, United States
| | - Steven Hancock
- Center
for
Simulational Physics and Department of Physics and Astronomy, University of Georgia, Athens, Georgia 30602, United States
| | - Qi Wang
- School
of
Materials Engineering, Purdue University, West Lafayette, Indiana 47907, United States
| | - Sarabpreet Singh
- Department
of Physics and Astronomy, University of
Georgia, Athens, Georgia 30602, United States
| | - Mahdi Ghafariasl
- Department
of Physics and Astronomy, University of
Georgia, Athens, Georgia 30602, United States
| | - Kun Yao
- School
of
Electrical and Computer Engineering, University
of Georgia, Athens, Georgia 30602, United States
| | - Tom E. Tiwald
- J.A. Woollam
Co., Inc., Lincoln, Nebraska 68508, United States
| | - Tae Joon Park
- School
of
Materials Engineering, Purdue University, West Lafayette, Indiana 47907, United States
| | - David P. Landau
- Center
for
Simulational Physics and Department of Physics and Astronomy, University of Georgia, Athens, Georgia 30602, United States
| | - Haidan Wen
- Advanced
Photon Source, Argonne National Laboratory, Lemont, Illinois 60439, United States
- Materials
Science Division, Argonne National Laboratory, Lemont, Illinois 60439, United States
| | - Subramanian K.
R. S. Sankaranarayanan
- Center for
Nanoscale Materials, Argonne National Laboratory, Lemont, Illinois 60439, United States
- Department
of Mechanical and Industrial Engineering, University of Illinois, Chicago, Illinois 60607, United States
| | - Pierre Darancet
- Center for
Nanoscale Materials, Argonne National Laboratory, Lemont, Illinois 60439, United States
- Northwestern
Argonne Institute of Science and Engineering, Evanston, Illinois 60208, United States
| | - Shriram Ramanathan
- School
of
Materials Engineering, Purdue University, West Lafayette, Indiana 47907, United States
- Department
of Electrical & Computer Engineering, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, United States
| | - Yohannes Abate
- Department
of Physics and Astronomy, University of
Georgia, Athens, Georgia 30602, United States
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