Publications

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Mapping of radiation-induced resistance changes and multiple conduction channels in TaOx memristors

IEEE Transactions on Nuclear Science

Hughart, David R.; Pacheco, Jose L.; Lohn, Andrew L.; Mickel, Patrick R.; Bielejec, Edward S.; Vizkelethy, Gyorgy V.; Doyle, Barney L.; Wolfley, Steven L.; Dodd, Paul E.; Shaneyfelt, Marty R.; McLain, Michael L.; Marinella, Matthew J.

The locations of conductive regions in TaOx memristors are spatially mapped using a microbeam and Nanoimplanter by rastering an ion beam across each device while monitoring its resistance. Microbeam irradiation with 800 keV Si ions revealed multiple sensitive regions along the edges of the bottom electrode. The rest of the active device area was found to be insensitive to the ion beam. Nanoimplanter irradiation with 200 keV Si ions demonstrated the ability to more accurately map the size of a sensitive area with a beam spot size of 40 nm by 40 nm. Isolated single spot sensitive regions and a larger sensitive region that extends approximately 300 nm were observed.

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Characterization of Switching Filament Formation in TaOx Memristive Memory Films

Marinella, Matthew J.; Marinella, Matthew J.; Howell, Stephen W.; Howell, Stephen W.; Decker, Seth D.; Decker, Seth D.; Hughart, David R.; Hughart, David R.; Lohn, Andrew L.; Lohn, Andrew L.; Mickel, Patrick R.; Mickel, Patrick R.; Apodaca, Roger A.; Apodaca, Roger A.; Bielejec, Edward S.; Bielejec, Edward S.; Beechem, Thomas E.; Beechem, Thomas E.; Wolfley, Steven L.; Wolfley, Steven L.; Stevens, James E.; Brennecka, Geoffrey L.

Abstract not provided.

Development characterization and modeling of a TaOx ReRAM for a neuromorphic accelerator

Marinella, Matthew J.; Mickel, Patrick R.; Lohn, Andrew L.; Hughart, David R.; Bondi, Robert J.; Mamaluy, Denis M.; Hjalmarson, Harold P.; Stevens, James E.; Decker, Seth D.; Apodaca, Roger A.; Evans, Brian R.; Aimone, James B.; Rothganger, Fredrick R.; James, Conrad D.; DeBenedictis, Erik

This report discusses aspects of neuromorphic computing and how it is used to model microsystems.

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Detection and characterization of multi-filament evolution during resistive switching

Applied Physics Letters

Mickel, Patrick R.; Lohn, Andrew L.; Marinella, Matthew J.

We report resistive switching data in TaOx memristors displaying signatures of multi-filament switching modes and present a technique which enables the characterization of the evolution of multiple filaments within a single device during switching, including their temperature, heat flow, conductivity, and time evolving areas. Using a geometrically defined equivalent circuit, we resolve the individual current/voltage values of each filament and demonstrate that the switching curves of each filament collapse onto a common curve determined by the analytical steady-state resistive switching solution for filamentary switching. Finally, we discuss operational modes which may limit the formation of additional conducting filaments, potentially leading to increased device endurance. © 2014 AIP Publishing LLC.

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A comprehensive approach to decipher biological computation to achieve next generation high-performance exascale computing

Howell, Jamie D.; Lohn, Andrew L.; Marinella, Matthew J.; Baca, Michael J.; Finnegan, Patrick S.; Wolfley, Steven L.; Dagel, Daryl D.; Spahn, Olga B.; Harper, Jason C.; Pohl, Kenneth R.; Mickel, Patrick R.

The human brain (volume=1200cm3) consumes 20W and is capable of performing > 10^16 operations/s. Current supercomputer technology has reached 1015 operations/s, yet it requires 1500m^3 and 3MW, giving the brain a 10^12 advantage in operations/s/W/cm^3. Thus, to reach exascale computation, two achievements are required: 1) improved understanding of computation in biological tissue, and 2) a paradigm shift towards neuromorphic computing where hardware circuits mimic properties of neural tissue. To address 1), we will interrogate corticostriatal networks in mouse brain tissue slices, specifically with regard to their frequency filtering capabilities as a function of input stimulus. To address 2), we will instantiate biological computing characteristics such as multi-bit storage into hardware devices with future computational and memory applications. Resistive memory devices will be modeled, designed, and fabricated in the MESA facility in consultation with our internal and external collaborators.

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34 Results
34 Results