17 results on '"Lu, Wei D."'
Search Results
2. Perspective: Entropy-stabilized oxide memristors.
- Author
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Chae, Sieun, Yoo, Sangmin, Kioupakis, Emmanouil, Lu, Wei D., and Heron, John T.
- Abstract
A memristor array has emerged as a potential computing hardware for artificial intelligence (AI). It has an inherent memory effect that allows information storage in the form of easily programmable electrical conductance, making it suitable for efficient data processing without shuttling of data between the processor and memory. To realize its full potential for AI applications, fine-tuning of internal device dynamics is required to implement a network system that employs dynamic functions. Here, we provide a perspective on multicationic entropy-stabilized oxides as a widely tunable materials system for memristor applications. We highlight the potential for efficient data processing in machine learning tasks enabled by the implementation of "task specific" neural networks that derive from this material tunability. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
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3. A Crossbar-Based In-Memory Computing Architecture.
- Author
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Wang, Xinxin, Zidan, Mohammed A., and Lu, Wei D.
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NONVOLATILE random-access memory , *ENERGY dissipation , *MEMORY , *DATA conversion , *ADAPTIVE computing systems - Abstract
To address the von Neumann bottleneck that leads to both energy and speed degradations, in-memory processing architectures have been proposed as a promising alternative for future computing applications. In this paper, we present an in-memory computing system based on resistive random-access memory (RRAM) crossbar arrays that is reconfigurable and can potentially perform parallel and general computing tasks. The system consists of small look-up tables (LUTs), a memory block, and two search auxiliary blocks, all implemented in the same RRAM crossbar array. External data access and data conversions are eliminated to allow operations fully in-memory. Details of addition, AND logic and multiplication operations are discussed on the basis of search and writeback steps. A compact instruction set consisting of 10 instructions is demonstrated on this architecture through circuit level simulations. Performance evaluations show that the proposed in-memory computing architecture is suitable for handling data-intensive problems. The average power consumption of the crossbar chip is estimated to be $45~\mu \text{W}$. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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4. Stabilization of Mode-Dependent Impulsive Hybrid Systems Driven by DFA With Mixed-Mode Effects.
- Author
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Zhang, Junhui, Li, Anni, Lu, Wei D., and Sun, Jitao
- Subjects
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HYBRID systems , *SYMMETRIC matrices , *ROBOTS , *FUNCTIONALS - Abstract
This paper is concerned with mode-dependent impulsive hybrid systems driven by deterministic finite automaton (DFA) with mixed-mode effects. In the hybrid systems, a complex phenomenon called mixed mode, caused in time-varying delay switching systems, is considered explicitly. Furthermore, mode-dependent impulses, which can exist not only at the instants coinciding with mode switching but also at the instants when there is no system switching, are also taken into consideration. First, we establish a rigorous mathematical equation expression of this class of hybrid systems. Then, several criteria of stabilization of this class of hybrid systems are presented based on semi-tensor product (STP) techniques, multiple Lyapunov–Krasovskii functionals, as well as the average dwell time approach. Finally, an example is simulated to illustrate the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
5. Utilizing multiple state variables to improve the dynamic range of analog switching in a memristor.
- Author
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YeonJoo Jeong, Sungho Kim, and Lu, Wei D.
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THERMODYNAMIC state variables , *DYNAMIC range (Acoustics) , *MEMRISTORS , *TANTALUM oxide , *DIFFUSION processes - Abstract
Memristors and memristive systems have been extensively studied for data storage and computing applications such as neuromorphic systems. To act as synapses in neuromorphic systems, the memristor needs to exhibit analog resistive switching (RS) behavior with incremental conductance change. In this study, we show that the dynamic range of the analog RS behavior can be significantly enhanced in a tantalum-oxide-based memristor. By controlling different state variables enabled by different physical effects during the RS process, the gradual filament expansion stage can be selectively enhanced without strongly affecting the abrupt filament length growth stage. Detailed physics-based modeling further verified the observed experimental effects and revealed the roles of oxygen vacancy drift and diffusion processes, and how the diffusion process can be selectively enhanced during the filament expansion stage. These findings lead to more desirable and reliable memristor behaviors for analog computing applications. Additionally, the ability to selectively control different internal physical processes demonstrated in the current study provides guidance for continued device optimization of memristor devices in general. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
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6. Feature Extraction Using Memristor Networks.
- Author
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Sheridan, Patrick M., Du, Chao, and Lu, Wei D.
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EXTRACTION (Linguistics) , *DATA dictionaries , *CROSSBAR switches (Electronics) , *CODING standards (Coding theory) , *MEMRISTORS , *ANALOG computers - Abstract
Crossbar arrays of memristive elements are investigated for the implementation of dictionary learning and sparse coding of natural images. A winner-take-all training algorithm, in conjunction with Oja’s rule, is used to learn an overcomplete dictionary of feature primitives that resemble Gabor filters. The dictionary is then used in the locally competitive algorithm to form a sparse representation of input images. The impacts of device nonlinearity and parameter variations are evaluated and a compensating procedure is proposed to ensure the robustness of the sparsification. It is shown that, with proper compensation, the memristor crossbar architecture can effectively perform sparse coding with distortion comparable with ideal software implementations at high sparsity, even in the presence of large device-to-device variations in the excess of 100%. [ABSTRACT FROM PUBLISHER]
- Published
- 2016
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7. Memristive technologies for data storage, computation, encryption, and radio-frequency communication.
- Author
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Lanza, Mario, Sebastian, Abu, Lu, Wei D., Le Gallo, Manuel, Meng-Fan Chang, Akinwande, Deji, Puglisi, Francesco M., Alshareef, Husam N., Ming Liu, and Roldan, Juan B.
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ELECTRICAL resistance tomography , *ELECTRIC insulators & insulation , *METALLIC oxides , *FERROELECTRIC materials , *CIRCUIT elements - Abstract
The article reports that memristive devices exhibit an electrical resistance that can be adjusted to two or more nonvolatile levels by applying electrical stresses. Topics include considered that the core of the advanced memristive devices is a metal/insulator/metal nanocell made of phase-change, metaloxide, magnetic, or ferroelectric materials, which is placed in series with other circuit elements to enhance their performance in array configurations.
- Published
- 2022
- Full Text
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8. Crossbar RRAM Arrays: Selector Device Requirements During Write Operation.
- Author
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Kim, Sungho, Zhou, Jiantao, and Lu, Wei D.
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NONVOLATILE random-access memory , *CROSSBAR switches (Electronics) , *ELECTRIC potential , *ELECTRIC power consumption , *STRAY currents - Abstract
A comprehensive analysis of write operations (SET and RESET) in a resistance-change memory (resistive random access memory) crossbar array is carried out. Three types of resistive switching memory cells-nonlinear, rectifying-SET, and rectifying-RESET-are compared with each other in terms of voltage delivery, current delivery, and power consumption. Two different write schemes, V/2 and V/3, were considered, and the V/2 write scheme is preferred due to much lower power consumption. A simple numerical method was developed that simulates entire current flows and node voltages within a crossbar array and provides a quantitative tool for the accurate analysis of crossbar arrays and guidelines for developing reliable write operation. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
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9. How to Build a Memristive Integrate-and-Fire Model for Spiking Neuronal Signal Generation.
- Author
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Kang, Sung Mo, Choi, Donguk, Eshraghian, Jason K., Zhou, Peng, Kim, Jieun, Kong, Bai-Sun, Zhu, Xiaojian, Demirkol, Ahmet Samil, Ascoli, Alon, Tetzlaff, Ronald, Lu, Wei D., and Chua, Leon O.
- Subjects
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ACTION potentials , *CIRCUIT elements , *MEMRISTORS , *SURFACE area , *INTEGRATED circuits - Abstract
We present and experimentally validate two minimal compact memristive models for spiking neuronal signal generation using commercially available low-cost components. The first neuron model is called the Memristive Integrate-and-Fire (MIF) model, for neuronal signaling with two voltage levels: the spike-peak, and the rest-potential. The second model MIF2 is also presented, which promotes local adaptation by accounting for a third refractory voltage level during hyperpolarization. We show both compact models are minimal in terms of the number of circuit elements and integration area. Using the MIF and MIF2 models, we postulate the design of a memristive solid-state brain with an estimation of its surface area and power consumption. Analytical projections show that a memristive solid-state brain could be realized within (i) the surface area of the median human brain, 2,400cm2, (ii) the same volume of the median human brain, and (iii) a total power budget of approximately 20 W using a 3.5 nm technology. Distinct from the past decade of memristive neuron literature, our benchmarks are attained using generic commercially available memristors that are reproducible using off-the-shelf components. We expect this work can promote more experimental demonstrations of memristive circuits that do not rely on prohibitively expensive fabrication processes. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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10. Experimental Demonstration of Feature Extraction and Dimensionality Reduction Using Memristor Networks.
- Author
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Shinhyun Choi, Shin, Jong Hoon, Jihang Lee, Sheridan, Patrick, and Lu, Wei D.
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FEATURE extraction , *MEMRISTORS , *NONVOLATILE memory , *PATTERN recognition systems , *MULTIPLE correspondence analysis (Statistics) - Abstract
Memristors have been considered as a leading candidate for a number of critical applications ranging from nonvolatile memory to non-Von Neumann computing systems. Feature extraction, which aims to transform input data from a high-dimensional space to a space with fewer dimensions, is an important technique widely used in machine learning and pattern recognition applications. Here, we experimentally demonstrate that memristor arrays can be used to perform principal component analysis, one of the most commonly used feature extraction techniques, through online, unsupervised learning. Using Sanger's rule, that is, the generalized Hebbian algorithm, the principal components were obtained as the memristor conductances in the network after training. The network was then used to analyze sensory data from a standard breast cancer screening database with high classification success rate (97.1%). [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
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11. Vertical Ge/Si Core/Shell Nanowire Junctionless Transistor.
- Author
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Lin Chen, Fuxi Cai, Otuonye, Ugo, and Lu, Wei D.
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NANOWIRES , *NANOFABRICATION , *GERMANIUM , *DENSITY functional theory , *METAL microstructure - Abstract
Vertical junctionless transistors with a gate-all-around (GAA) structure based on Ge/Si core/shell nanowires epitaxially grown and integrated on a 〈111〉 Si substrate were fabricated and analyzed. Because of efficient gate coupling in the nanowire-GAA transistor structure and the high density one-dimensional hole gas formed in the Ge nanowire core, excellent P-type transistor behaviors with Ion of 750 µA/µm were obtained at a moderate gate length of 544 nm with minimal short-channel effects. The experimental data can be quantitatively modeled by a GAA junctionless transistor model with few fitting parameters, suggesting the nanowire transistors can be fabricated reliably without introducing additional factors that can degrade device performance. Devices with different gate lengths were readily obtained by tuning the thickness of an etching mask film. Analysis of the histogram of different devices yielded a single dominate peak in device parameter distribution, indicating excellent uniformity and high confidence of single nanowire operation. Using two vertical nanowire junctionless transistors, a PMOS-logic inverter with near rail-to-rail output voltage was demonstrated, and device matching in the logic can be conveniently obtained by controlling the number of nanowires employed in different devices rather than modifying device geometry. These studies show that junctionless transistors based on vertical Ge/Si core/shell nanowires can be fabricated in a controlled fashion with excellent performance and may be used in future hybrid, high-performance circuits where bottom-up grown nanowire devices with different functionalities can be directly integrated with an existing Si platform. [ABSTRACT FROM AUTHOR]
- Published
- 2016
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- View/download PDF
12. Temporal information encoding in dynamic memristive devices.
- Author
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Wen Ma, Lin Chen, Chao Du, and Lu, Wei D.
- Subjects
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MICROFABRICATION , *SILVER compounds , *DISTRIBUTION (Probability theory) , *ELECTRIC potential , *SWITCHING theory - Abstract
We show temporal and frequency information can be effectively encoded in memristive devices with inherent short-term dynamics. Ag/Ag2S/Pd based memristive devices with low programming voltage (~100 mV) were fabricated and tested. At weak programming conditions, the devices exhibit inherent decay due to spontaneous diffusion of the Ag atoms. When the devices were subjected to pulse train inputs emulating different spiking patterns, the switching probability distribution function diverges from the standard Poisson distribution and evolves according to the input pattern. The experimentally observed switching probability distributions and the associated cumulative probability functions can be well-explained using a model accounting for the shortterm decay effects. Such devices offer an intriguing opportunity to directly encode neural signals for neural information storage and analysis. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
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13. Biorealistic Implementation of Synaptic Functions with Oxide Memristors through Internal Ionic Dynamics.
- Author
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Du, Chao, Ma, Wen, Chang, Ting, Sheridan, Patrick, and Lu, Wei D.
- Subjects
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ARTIFICIAL neural networks , *MEMRISTORS , *IONIC interactions , *POSTSYNAPTIC potential , *COMPLEMENTARY metal oxide semiconductors - Abstract
Memristors have attracted broad interest as a promising candidate for future memory and computing applications. Particularly, it is believed that memristors can effectively implement synaptic functions and enable efficient neuromorphic systems. Most previous studies, however, focus on implementing specific synaptic learning rules by carefully engineering external programming parameters instead of focusing on emulating the internal cause that leads to the apparent learning rules. Here, it is shown that by taking advantage of the different time scales of internal oxygen vacancy ( VO) dynamics in an oxide-based memristor, diverse synaptic functions at different time scales can be implemented naturally. Mathematically, the device can be effectively modeled as a second-order memristor with a simple set of equations including multiple state variables. Not only is this approach more biorealistic and easier to implement, by focusing on the fundamental driving mechanisms it allows the development of complete theoretical and experimental frameworks for biologically inspired computing systems. [ABSTRACT FROM AUTHOR]
- Published
- 2015
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14. Experimental Demonstration of a Second-Order Memristor and Its Ability to Biorealistically Implement Synaptic Plasticity.
- Author
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Sungho VKim, Chao Du, Sheridan, Patrick, Wen Ma, ShinHyun Choi, and Lu, Wei D.
- Subjects
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MEMRISTORS , *INFORMATION retrieval , *NEUROPLASTICITY , *ELECTRIC resistance , *CALCIUM channels - Abstract
Memristors have been extensively studied for data storage and low-power computation applications. In this study, we show that memristors offer more than simple resistance change. Specifically, the dynamic evolutions of internal state variables allow an oxide-based memristor to exhibit Ca2+-like dynamics that natively encode timing information and regulate synaptic weights. Such a device can be modeled as a second-order memristor and allow the implementation of critical synaptic functions realistically using simple spike forms based solely on spike activity. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
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15. Retention failure analysis of metal-oxide based resistive memory.
- Author
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Shinhyun Choi, Jihang Lee, Sungho Kim, and Lu, Wei D.
- Subjects
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FAILURE analysis , *ELECTRIC switchgear , *FIBERS , *ELECTRIC conductivity , *NONVOLATILE random-access memory , *MICROFABRICATION - Abstract
Resistive switching devices (RRAMs) have been proposed a promising candidate for future memory and neuromorphic applications. Central to the successful application of these emerging devices is the understanding of the resistance switching and failure mechanism, and identification of key physical parameters that will enable continued device optimization. In this study, we report detailed retention analysis of a TaOx based RRAM at high temperatures and the development of a microscopic oxygen diffusion model that fully explains the experimental results and can be used to guide future device developments. The device conductance in low resistance state (LRS) was constantly monitored at several elevated temperatures (above 300 °C), and an initial gradual conductivity drift followed by a sudden conductance drop were observed during retention failure. These observations were explained by a microscopic model based on oxygen vacancy diffusion, which quantitatively explains both the initial gradual conductance drift and the sudden conductance drop. Additionally, a non-monotonic conductance change, with an initial conductance increase followed by the gradual conductance decay over time, was observed experimentally and explained within the same model framework. Specifically, our analysis shows that important microscopic physical parameters such as the activation energy for oxygen vacancy migration can be directly calculated from the failure time versus temperature relationship. Results from the analytical model were further supported by detailed numerical multi-physics simulation, which confirms the filamentary nature of the conduction path in LRS and the importance of oxygen vacancy diffusion in device reliability. Finally, these high-temperature stability measurements also reveal the existence of multiple filaments in the same device. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
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16. Data Clustering using Memristor Networks.
- Author
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Choi, Shinhyun, Sheridan, Patrick, and Lu, Wei D.
- Subjects
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MEMRISTORS , *NEUROMORPHICS , *PRINCIPAL components analysis , *MACHINE learning , *VON Neumann architecture (Computers) - Abstract
Memristors have emerged as a promising candidate for critical applications such as non-volatile memory as well as non-Von Neumann computing architectures based on neuromorphic and machine learning systems. In this study, we demonstrate that memristors can be used to perform principal component analysis (PCA), an important technique for machine learning and data feature learning. The conductance changes of memristors in response to voltage pulses are studied and modeled with an internal state variable to trace the analog behavior of the device. Unsupervised, online learning is achieved in a memristor crossbar using Sanger's learning rule, a derivative of Hebb's rule, to obtain the principal components. The details of weights evolution during training is investigated over learning epochs as a function of training parameters. The effects of device non-uniformity on the PCA network performance are further analyzed. We show that the memristor-based PCA network is capable of linearly separating distinct classes from sensory data with high clarification success of 97.6% even in the presence of large device variations. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
- View/download PDF
17. Oxaliplatin long-circulating liposomes improved therapeutic index of colorectal carcinoma.
- Author
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Chuang Yang, Liu, Hai Z., Fu, Zhong X., and Lu, Wei D.
- Subjects
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OXALIPLATIN , *TUMORS , *COLON cancer , *CELL death , *ANTINEOPLASTIC agents - Abstract
Background: Cytotoxic drugs are non-selective between normal and pathological tissue, and this poses a challenge regarding the strategy for treatment of tumors. To achieve sufficient antitumor activity for colorectal carcinoma, optimization of the therapeutic regimen is of great importance. We investigated the ability of oxaliplatin long-circulating liposomes (PEG-liposomal L-oHP) to provide an improved therapeutic index of colorectal carcinoma. Results: We determined that PEG- liposomes conjugated with cells at 2 h, with a mean fluorescence intensity that was enhanced upon extended induction time. The PEG-liposomal L-oHP induced a significant apoptotic response as compared with free L-oHP, 23.21% ± 3.38% vs. 16.85% ± 0.98%, respectively. Fluorescence imaging with In-Vivo Imaging demonstrated that PEG- liposomes specifically targeted tumour tissue. After intravenous injections of PEGliposomal L-oHP or free L-oHP, the tumour volume suppression ratio was 26.08% ± 12.43% and 18.19% ± 7.09%, respectively, the percentage increased life span (ILS%) was 45.36% and 76.19%, respectively, and Bcl-2, Bax mRNA and protein expression in tumour tissue was 0.27-fold vs. 0.88-fold and 1.32-fold vs. 1.61-fold compared with free L-oHP, respectively. Conclusion: The PEG-liposomal L-oHP exhibited a tendency to target tumour tissue and demonstrated a significantly greater impact on apoptosis compared to free oxaliplatin. [ABSTRACT FROM AUTHOR]
- Published
- 2011
- Full Text
- View/download PDF
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