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Articles 1 - 11 of 11
Full-Text Articles in Nanoscience and Nanotechnology
Vi Energy-Efficient Memristor-Based Neuromorphic Computing Circuits And Systems For Radiation Detection Applications, Jorge Iván Canales Verdial
Vi Energy-Efficient Memristor-Based Neuromorphic Computing Circuits And Systems For Radiation Detection Applications, Jorge Iván Canales Verdial
Electrical and Computer Engineering ETDs
Radionuclide spectroscopic sensor data is analyzed with minimal power consumption through the use of neuromorphic computing architectures. Memristor crossbars are harnessed as the computational substrate in this non-conventional computing platform and integrated with CMOS-based neurons to mimic the computational dynamics observed in the mammalian brain’s visual cortex. Functional prototypes using spiking sparse locally competitive approximations are presented. The architectures are evaluated for classification accuracy and energy efficiency. The proposed systems achieve a 90% true positive accuracy with a high-resolution detector and 86% with a low-resolution detector.
Material Characterization And Comparison Of Sol-Gel Deposited And Rf Magnetron Deposited Lead Zirconate Titanate Thin Films, Katherine Lynne Miles
Material Characterization And Comparison Of Sol-Gel Deposited And Rf Magnetron Deposited Lead Zirconate Titanate Thin Films, Katherine Lynne Miles
Mechanical Engineering ETDs
Lead zirconate titanate (PZT) has been a material of interest for sensor, actuator, and transducer applications in microelectromechanical systems (MEMS). This is due to their favorable piezoelectric, pyroelectric and ferroelectric properties. While various methods are available to deposit PZT thin films, radio frequency (RF) magnetron sputtering was selected to provide high quality PZT films with the added capability of batch processing. These sputter deposited PZT films were characterized to determine their internal film stress, Young’s modulus, composition, and structure. After characterization, the sputtered PZT samples were poled using corona poling and direct poling methods. As a means of comparison, commercially …
A Versatile Python Package For Simulating Dna Nanostructures With Oxdna, Kira Threlfall
A Versatile Python Package For Simulating Dna Nanostructures With Oxdna, Kira Threlfall
Computer Science and Computer Engineering Undergraduate Honors Theses
The ability to synthesize custom DNA molecules has led to the feasibility of DNA nanotechnology. Synthesis is time-consuming and expensive, so simulations of proposed DNA designs are necessary. Open-source simulators, such as oxDNA, are available but often difficult to configure and interface with. Packages such as oxdna-tile-binding pro- vide an interface for oxDNA which allows for the ability to create scripts that automate the configuration process. This project works to improve the scripts in oxdna-tile-binding to improve integration with job scheduling systems commonly used in high-performance computing environments, improve ease-of-use and consistency within the scripts compos- ing oxdna-tile-binding, and move …
Treated Hfo2 Based Rram Devices With Ru, Tan, Tin As Top Electrode For In-Memory Computing Hardware, Yuvraj Dineshkumar Patel
Treated Hfo2 Based Rram Devices With Ru, Tan, Tin As Top Electrode For In-Memory Computing Hardware, Yuvraj Dineshkumar Patel
Theses
The scalability and power efficiency of the conventional CMOS technology is steadily coming to a halt due to increasing problems and challenges in fabrication technology. Many non-volatile memory devices have emerged recently to meet the scaling challenges. Memory devices such as RRAMs or ReRAM (Resistive Random-Access Memory) have proved to be a promising candidate for analog in memory computing applications related to inference and learning in artificial intelligence. A RRAM cell has a MIM (Metal insulator metal) structure that exhibits reversible resistive switching on application of positive or negative voltage. But detailed studies on the power consumption, repeatability and retention …
Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh
Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh
Doctoral Dissertations
Society has benefited from the technological revolution and the tremendous growth in computing powered by Moore's law. However, we are fast approaching the ultimate physical limits in terms of both device sizes and the associated energy dissipation. It is important to characterize these limits in a physically grounded and implementation-agnostic manner, in order to capture the fundamental energy dissipation costs associated with performing computing operations with classical information in nano-scale quantum systems. It is also necessary to identify and understand the effect of quantum in-distinguishability, noise, and device variability on these dissipation limits. Identifying these parameters is crucial to designing …
Liquid Metal Particle Popping: Nanoscale To Macroscale, Trevor R. Lear
Liquid Metal Particle Popping: Nanoscale To Macroscale, Trevor R. Lear
Open Access Theses
Liquid metal nanoparticles can be used to produce stretchable electronic devices. Understanding the mechanical properties of liquid metal nanoparticles is crucial to optimizing their use in various applications, especially printing of flexible, stretchable electronics. Smaller nanoparticles are desired for high-resolution printing and compatibility with existing scalable manufacturing methods; however, they contain less liquid metal and are more difficult to rupture than larger particles, making them less desirable for post-processing functionality. This study investigates the mechanics of liquid metal particle rupture as a function of particle size. We employ compression of particle films to characterize the composition of the particle core …
Analog Spiking Neuromorphic Circuits And Systems For Brain- And Nanotechnology-Inspired Cognitive Computing, Xinyu Wu
Boise State University Theses and Dissertations
Human society is now facing grand challenges to satisfy the growing demand for computing power, at the same time, sustain energy consumption. By the end of CMOS technology scaling, innovations are required to tackle the challenges in a radically different way. Inspired by the emerging understanding of the computing occurring in a brain and nanotechnology-enabled biological plausible synaptic plasticity, neuromorphic computing architectures are being investigated. Such a neuromorphic chip that combines CMOS analog spiking neurons and nanoscale resistive random-access memory (RRAM) using as electronics synapses can provide massive neural network parallelism, high density and online learning capability, and hence, paves …
Design, Fabrication And Testing Of Monolithic Low-Power Passive Sigma-Delta Analog-To-Digital Converters, Angsuman Roy
Design, Fabrication And Testing Of Monolithic Low-Power Passive Sigma-Delta Analog-To-Digital Converters, Angsuman Roy
UNLV Theses, Dissertations, Professional Papers, and Capstones
Analog-to-digital converters are critically important in electronic systems. The
difficulty in meeting high performance parameters increases as integrated circuit design
process technologies advance into the deep nanometer region. Sigma-delta analog-todigital
converters are an attractive option to fulfill many data converter requirements.
These data converters offer high performance while relaxing requirements on the precision
of components within an integrated circuit. Despite this, the active integrators found within
sigma-delta analog-to-digital converters present two main challenges. These challenges are
the power consumption of the active amplifier and achieving gain-bandwidth necessary for
sigma-delta data converters in deep nanometer process technologies. Both of these
challenges …
Physically Equivalent Intelligent Systems For Reasoning Under Uncertainty At Nanoscale, Santosh Khasanvis
Physically Equivalent Intelligent Systems For Reasoning Under Uncertainty At Nanoscale, Santosh Khasanvis
Doctoral Dissertations
Machines today lack the inherent ability to reason and make decisions, or operate in the presence of uncertainty. Machine-learning methods such as Bayesian Networks (BNs) are widely acknowledged for their ability to uncover relationships and generate causal models for complex interactions. However, their massive computational requirement, when implemented on conventional computers, hinders their usefulness in many critical problem areas e.g., genetic basis of diseases, macro finance, text classification, environment monitoring, etc. We propose a new non-von Neumann technology framework purposefully architected across all layers for solving these problems efficiently through physical equivalence, enabled by emerging nanotechnology. The architecture builds …
Graphene-Based Post-Cmos Architecture, Sansiri Tanachutiwat
Graphene-Based Post-Cmos Architecture, Sansiri Tanachutiwat
Legacy Theses & Dissertations (2009 - 2024)
The semiconductor industry relies on CMOS technology which is nearing its scaling limitations. In order to continue the historical growth rate of the device density of digital logic chips, novel nanomaterials and nanodevices will need to be developed.
Design, Synthesis And Test Of Reversible Circuits For Emerging Nanotechnologies, Himanshu Thapliyal
Design, Synthesis And Test Of Reversible Circuits For Emerging Nanotechnologies, Himanshu Thapliyal
USF Tampa Graduate Theses and Dissertations
Reversible circuits are similar to conventional logic circuits except that they are built from reversible gates. In reversible gates, there is a unique, one-to-one mapping between the inputs and outputs, not the case with conventional logic. Also, reversible gates require constant ancilla inputs for reconfiguration of gate functions and garbage outputs that help in keeping reversibility. Reversible circuits hold promise in futuristic computing technologies like quantum computing, quantum dot cellular automata, DNA computing, optical computing, etc. Thus, it is important to minimize parameters such as ancilla and garbage bits, quantum cost and delay in the design of reversible circuits.
The …