SelectedWorks - Kurtis D. Cantley

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Selected Works of Kurtis D. Cantley

Assistant Professor, Department of Electrical and Computer Engineering

Dr. Kurtis Cantley joined the faculty of the Department of Electrical and Computer Engineering at Boise State University in 2013. He has a Ph.D. in electrical engineering from the University of Texas at Dallas, a master's in electrical engineering from Purdue University, and a bachelor's in electrical engineering (with minors in math, physics, and music) from Washington State University. Dr. Cantley applies his expertise in low-temperature electronic materials and devices, including extensive experience in the simulation, fabrication, and characterization of emerging nanoelectronic devices and circuits, to research of novel computation and biomedical systems.

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About Kurtis D. Cantley

Dr. Kurtis Cantley joined the faculty of the Department of Electrical and Computer Engineering at Boise State University in 2013. He has a Ph.D. in electrical engineering from the University of Texas at Dallas, a master's in electrical engineering from Purdue University, and a bachelor's in electrical engineering (with minors in math, physics, and music) from Washington State University. Dr. Cantley applies his expertise in low-temperature electronic materials and devices, including extensive experience in the simulation, fabrication, and characterization of emerging nanoelectronic devices and circuits, to research of novel computation and biomedical systems.

2013 - Present	Assistant Professor, Boise State University ‐ Department of Electrical and Computer Engineering
Institution Organization Position Type Position Title Time Period to Options Current Position Affiliate my profile with this Institution

Electrical and Computer Engineering and Computer Sciences

Electronic Device Fabrication and Processing, Physical and Electrical Characterization of Materials, and Advanced Semiconductor Devices

2022 - 2025	Machine learning hardware research to improve the reliability of the power grid with intelligent, adaptable and cyber secure electronics that take inspiration from the human brain, otherwise known as neuromorphic systems
	Department of Energy Established Program to Stimulate Competitive Research (EPSCoR)
	$700,000

2007-2010 - National Defense Science and Engineering Graduate Fellowship
2009 - Excellence in Education Award, The University of Texas at Dallas
2017 - $322,866 Grant, Defense Threat Reduction Agency (DTRA)

E-mail: kurtiscantley@boisestate.edu

Articles (15)

Effects of Memristive Synapse Radiation Interactions on Learning in Spiking Neural Networks (Sumedha Gandharava Dahl, Robert C. Ivans and Kurtis D. Cantley) SN Applied Sciences (2021)

This study uses advanced modeling and simulation to explore the effects of external events such as radiation interactions on the synaptic devices in an electronic spiking neural network. Specifically, the networks are trained using the ...

A Model for R(t) Elements and R(t)-Based Spike-Timing-Dependent Plasticity with Basic Circuit Examples (Roberts C. Ivans, Sumedha Gandhereva Dahl and Kurtis D. Cantley) IEEE Transactions on Neural Networks & Learning Systems (2020)

Spike-timing-dependent plasticity (STDP) is a fundamental synaptic learning rule observed in biology that leads to numerous behavioral and cognitive outcomes. Emulating STDP in electronic spiking neural networks with high-density memristive synapses is, therefore, of significant ...

Measurement of Signal‐to‐Noise Ratio In Graphene‐Based Passive Microelectrode Arrays (Sepideh Rastegar, Justin Stadlbauer, Twinkle Pandhi, et al.) Electroanalysis (2019)

This work aims to investigate the influence of various electrode materials on the signal‐to‐noise ratio (SNR) of passive microelectrode arrays (MEAs) intended for use in neural interfaces. Noise reduction substantially improves the performance of systems ...

Graphene Foam as a Three-Dimensional Platform for Myotube Growth (Eric Krueger, A. Nicole Chang, Dale Brown, et al.) ACS Biomaterials Science & Engineering (2016)

This study demonstrates the growth and differentiation of C2C12 myoblasts into functional myotubes on three-dimensional graphene foam bioscaffolds. Specifically, we establish both bare and laminin-coated graphene foam as a biocompatible platform for muscle cells and ...

Spike-Timing-Dependent Plasticity Using Biologically Realistic Action Potentials and Low-Temperature Materials (Anand Subramaniam, Kurtis D. Cantley, Gennadi Bersuker, et al.) IEEE Transactions on Nanotechnology (2013)

Spike-timing-dependent plasticity (STDP) is a fundamental learning rule observed in biological synapses that is desirable to replicate in neuromorphic electronic systems. Nanocrystalline-silicon thin film transistors (TFTs) and memristors can be fabricated at low temperatures, and ...

Low-Temperature Fabrication of Spiking Soma Circuits Using Nanocrystalline-Silicon TFTs (Anand Subramaniam, Kurtis D. Cantley, Harvey J. Stiegler, et al.) IEEE Transactions on Neural Networks and Learning Systems (2013)

Spiking neuron circuits consisting of ambipolar nanocrystalline-silicon (nc-Si) thin-film transistors (TFTs) have been fabricated using low temperature processing conditions (maximum of 250 °C) that allow the use of flexible substrates. These circuits display behaviors commonly ...

Logic Gates and Ring Oscillators Based on Ambipolar Nanocrystalline-Silicon TFTs (Anand Subramaniam, Kurtis D. Cantley and Eric M. Vogel) Active and Passive Electronic Components (2013)

Nanocrystalline silicon (nc-Si) thin film transistors (TFTs) are well suited for circuit applications that require moderate device performance and low-temperature CMOS-compatible processing below 250°C. Basic logic gate circuits fabricated using ambipolar nc-Si TFTs alone are ...

Neural Learning Circuits Utilizing Nano-Crystalline Silicon Transistors and Memristors (Kurtis Cantley, Anand Subramaniam, Harvey J. Stiegler, et al.) IEEE Transactions on Neural Networks and Learning Systems (2012)

Properties of neural circuits are demonstrated via SPICE simulations and their applications are discussed. The neuron and synapse subcircuits include ambipolar nano-crystalline silicon transistor and memristor device models based on measured data. Neuron circuit characteristics ...

Submicron Ambipolar Nanocrystalline Silicon Thin-Film Transistors and Inverters (Anand Subramaniam, Kurtis D. Cantley, Harvey J. Stiegler, et al.) IEEE Transactions on Electron Devices (2012)

Nanocrystalline silicon (nc-Si) thin-film transistors (TFTs) fabricated at a maximum processing temperature of 250 °C operate with high field-effect mobility compared with amorphous-silicon TFTs. By reducing the oxygen content in the channel layer, ambipolar behavior ...

SPICE Macromodel of Silicon-on-Insulator-Field-Effect-Transistor-Based Biological Sensors (Kurtis Cantley) Sensors and Actuators B: Chemical (2012)

A user-friendly behavioral macromodel for biological response of FET-based transistors has been developed for use with commercial SPICE versions and will enable circuit level analysis of biosensor chips. The model is based on the physically ...

Investigation of Tunneling Current in SiO2/HfO2 Gate Stacks for Flash Memory Applications (Bhaswar Chakrabarti, Heesoo Kang, Barry Brennan, et al.) IEEE Transactions on Electron Devices (2011)

Despite theoretical predictions of significant performance improvement in Flash memory devices using tunnel-barrier-engineered (TBE) structures, there have been very few reports that demonstrate experimental verification. In this work, we have studied the role of factors ...

Hebbian Learning in Spiking Neural Networks With Nanocrystalline Silicon TFTs and Memristive Synapses (Kurtis D. Cantley, Anand Subramaniam, Harvey J. Stiegler, et al.) IEEE Transactions on Nanotechnology (2011)

Characteristics similar to biological neurons are demonstrated in SPICE simulations of spiking neuron circuits comprised of submicron nanocrystalline silicon (nc-Si) thin-film transistors (TFTs). Utilizing these neuron circuits and corresponding device models, the properties of a ...

Hydrogenated Amorphous Silicon Nanowire Transistors with Schottky Barrier Source/Drain Junctions (Kurtis D. Cantley) Applied Physics Letters (2010)

Hydrogenated amorphous silicon nanowire field-effect transistors (a-Si:H NWFETs) with Schottky source/drain junctions have been fabricated with a simple process involving maximum temperatures of 250 °C. Electrical characteristics of devices with various numbers of wires and ...

Inﬂuence of Bandstructure and Channel Structure on the Inversion Layer Capacitance of Silicon and GaAs MOSFETs (Himadri S. Pal, Kurtis D. Cantley, Shaikh Shahid Ahmed, et al.) IEEE Transactions on Electron Devices (2008)

The influence of MOSFET channel material and channel structure on the inversion layer capacitance is examined. It is well known that the inversion layer capacitance depends strongly on the bandstructure of the channel, but we ...

Nanoscale transistors: Physics and materials (Mark S. Lundstrom, Kurtis D Cantley and Himadri S Pal) Birck and NCN Publications (2007)

We analyze a modem-day 65nm MOSFET technology to determine its electrical characteristics and intrinsic ballistic efficiency. Using that information, we then predict the performance of similar devices comprised of different materials, such as higb-k gate ...

Spike Timing-Dependent Plasticity Using Memristors and Nano-Crystalline Silicon TFT Memories (Kurtis D. Cantley, Anand Subramaniam and Eric M. Vogel) Nanoelectronic Device Applications Handbook (2013)

Interest in the possibility of using memristive devices as synapses in artificial neural circuits was sparked by the demonstration of TiO<sub>2</sub> resistive switches by HP Labs in 2008 [1]. A great deal of the resulting ...

Investigating R(t) Functions for Spike-Timing-Dependent Plasticity in Memristive Neural Networks (Farhana Afrin and Kurtis D. Cantley) 2023 IEEE 66th International Midwest Symposium on Circuits and Systems (MWSCAS) (2023)

Brain-inspired neuromorphic computation can be extremely efficient at very large scales due to inherent parallelism, scalability, and fault and failure tolerance. One widely used, biologically plausible synaptic learning mechanism is spike-timing-dependent plasticity (STDP). The proposed ...

Work in Progress: Mastery-Based Grading in an Introduction to Circuits Class (Noah Salzman, Kurtis D. Cantley and Gary L. Hunt) 2019 ASEE Annual Conference & Exposition (2019)

Circuits is often the first required course in an electrical engineering curriculum that demands application of multiple concepts from prerequisite math and physics courses. This integration of knowledge can be a challenge for many students. ...

A Spatiotemporal Pattern Detector (Robert Ivans and Kurtis D. Cantley) 2019 IEEE 62nd International Midwest Symposium on Circuits and Systems (MWSCAS) (2019)

A spatiotemporal pattern detector design is presented which can identify three fundamental spatiotemporal patterns consisting of two spikes (from different neurons or from the same neuron). These fundamental cases provide the building blocks for construction ...

Learning Behavior of Memristor-Based Neuromorphic Circuits in the Presence of Radiation (Sumedha Gandharava Dahl, Robert C. Ivans and Kurtis D. Cantley) ICONS '19: Proceedings of the International Conference on Neuromorphic Systems (2019)

In this paper, a feed-forward spiking neural network with memristive synapses is designed to learn a spatio-temporal pattern representing the 25-pixel character ‘B’ by separating correlated and uncorrelated afferents. The network uses spike-timing-dependent plasticity (STDP) ...

Radiation Effect on Learning Behavior in Memristor-Based Neuromorphic Circuit (Sumedha Gandharava Dahl, Robert C. Ivans and Kurtis D. Cantley) 2019 IEEE 62nd International Midwest Symposium on Circuits and Systems (MWSCAS) (2019)

In this work, a memristor-based spiking neural network with a many-to-one feed-forward topology is designed for spatio-temporal pattern learning (25-pixel character ‘B'). A TiO2 non-linear drift behavioral memristor model is used for simulation of a ...

Modeling Memristor Radiation Interaction Events and the Effect on Neuromorphic Learning Circuits (Sumedha Gandharava Dahl, Robert Ivans and Kurtis Cantley) ICONS '18: Proceedings of the International Conference on Neuromorphic Systems (2018)

An ideal memristor model is modified to include the effects of radiation interactions with the device. Modeling is done in Cadence Virtuoso design suite using Verilog-A. Simulations include the effect of radiation events that could ...

A CMOS Synapse Design Implementing Tunable Asymmetric Spike Timing-Dependent Plasticity (Robert C. Ivans, Kurtis D. Cantley and Justin L. Shumaker) 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS) (2017)

A CMOS synapse design is presented which can perform tunable asymmetric spike timing-dependent learning in asynchronous spiking neural networks. The overall design consists of three primary subcircuit blocks, and the operation of each is described. ...

Electrical Characteristics of Nanocrystalline Silicon Resistive Memory Devices (Sumedha Gandharava, Catherine Walker and Kurtis D. Cantley) 2017 IEEE Workshop on Microelectronics and Electron Devices (2017)

Resistive memory devices have been studied and fabricated using a wide variety of materials including chalcogenides [1], metal oxides [2], and hydrogenated amorphous silicon (a-Si:H) [3]. The most promising materials seem to be amorphous in ...

Signal-to-Noise Ratio Enhancement Using Graphene-Based Passive Microelectrode Arrays (Sepideh Rastegar, Justin Stadlbauer, Kiyo Fujimoto, et al.) 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS) (2017)

This work is aimed toward the goal of investigating the influence of different materials on the signal-to-noise ratio (SNR) of passive neural microelectrode arrays (MEAs). Noise reduction is one factor that can substantially improve neural ...