Nathan’s second NSF proposal entitled, “High-endurance phase-change devices for electrically reconfigurable optical systems” was funded! Our lab will be working in collaboration with co-PI Feng Xiong at Pitt to investigate the mechanisms limiting the endurance and cyclability of electrically-controlled, phase-change photonic memory. See the following technical abstract for more information:... [Read More]
Welcome to the Youngblood Photonics Lab at PittOur research combines unique optoelectronic materials with nanophotonics to create new platforms for high-efficiency machine learning and high-precision biosensing. Key to our work is a fundamental understanding of light-matter interaction at the nanoscale and use of advanced nanofabrication techniques to address major challenges facing these disciplines. The following areas of research in our group are: 1) Photonic Devices and Architectures for Machine Learning; 2) Waveguide-Integrated Nanoplasmonics for High Density Biosensing; and 3) Waveguide-Integrated 2D Materials for High Performance Optoelectronics.
Openings:Prospective graduate students interested in joining our group should apply to the PhD program in the ECE Department. Please email Nathan with your CV and research interests if you have an undergraduate degree in physics, EE, or a related field and would like to join the group.
Vivswan joins the lab!
The lab welcomes Vivswan Shah to Pitt! Vivswan is a new PhD student starting this fall who graduated from Illinois College with a double major in Physics and Computer Science. He will be developing waveguide-integrated 2D optoelectronic memory using MoTe2 and will use his coding chops to automate experiments in... [Read More]
Youngblood Photonics Lab wins an NSF grant to explore 2D PCMs
Our proposal on “Elucidating Structural Transformations in MoTe2 for Efficient Optoelectronic Memory” in collaboration with Feng Xiong from Pitt was funded! We are excited to better understand the mechanism for phase transition in the 2D material MoTe2 using optical and electrical techinques. See the following technical abstract for more information:... [Read More]
Plasmonic nanogap enhanced phase-change devices with dual electrical-optical functionality
All-optical spiking neurosynaptic networks with self-learning capabilities
Our article on spiking neural networks using phase-change photonics has been published on Nature! News coverage includes an article by Geoffrey Burr in Nature News and Views and Oxford University. Many congratulations to first author Johannes Feldmann from Wolfram Pernice’s group. Read the article here.