Media
Press coverage and announcements relating to my work and my groups' work.
Graphene nanoribbons for radiation sensing
Coverage of the demonstration that nine-atom-wide graphene nanoribbons keep their atomic structure under gamma exposure while their electrical transport changes sharply, which points toward sensors for fusion reactors and deep space. The lab photograph used across this coverage is by Leslie Hawthorne Klingler, University of Arizona Office of Research and Partnerships.
- Quantum materials discovery could advance electronics for extreme environments
- Quantum materials discovery could advance electronics for extreme environments
- Laboratory feature image
- U of A researchers improve sensing for fusion energy, space science
- Graphene nanoribbon explored as basis for gamma monitoring in fusion machines
- Graphene nanoribbons survive gamma exposure, revealing potential for fusion and space tech
- GNR sensors could monitor fusion reactor first walls directly
- Graphene nanoribbons could lead to sensors for fusion and space
- Quantum material discovery could be key to nuclear fusion
- Quantum materials discovery could advance electronics for extreme environments
- Graphene nanoribbons for extreme radiation sensors
- Graphene nanoribbons survive gamma radiation, revealing potential sensors for fusion reactors
Awards and fellowships
Computational random-access memory
Coverage of the magnetic tunnel junction based CRAM demonstration published in npj Unconventional Computing in 2024, a collaboration between the University of Minnesota and the University of Arizona.
- Researchers develop state of the art device to make artificial intelligence more energy efficient
- New hardware device could make artificial intelligence applications more energy efficient
- Researchers develop state of the art device to make AI more energy efficient
- Engineers develop magnetic tunnel junction based device to make AI more energy efficient
- Rethinking computing to tackle the energy problem in AI
- Video feature on the CRAM demonstration
- For AI to reach its potential, energy demand has to be addressed
- La CRAM, une technologie de mémoire innovante pour des applications d'IA moins énergivores
- Coverage of the CRAM demonstration
- NNCI Year 9 highlights by site
Multi-interface Magnetic Tunnel Junctions
Coverage of high signal-to-noise ratio enabling low energy computing by MRAM published in Applied Physics Letters in 2021, a collaboration between the National Institute of Standards and Technology (NIST) and the University of Arizona.