News and Events

September 28, 2026

NanoSI researchers have developed and optimized palladium-coated aluminum nitride resonators that detect hydrogen with among the highest sensitivities reported to date, work published in the IEEE Journal of Microelectromechanical Systems. By fabricating devices spanning 123 to 396 MHz on a single wafer, the team isolated how operating frequency, palladium thickness and residual stress each shape sensing performance — identifying residual stress, an often-overlooked fabrication parameter, as capable of shifting sensitivity by up to 2.6 times. Their optimal device, a 317 MHz resonator with a 150-nanometer palladium layer, reached a peak sensitivity of 772 Hz/ppm while maintaining strong electromechanical performance, offering a design roadmap for compact sensors for hydrogen leak detection and clean-energy infrastructure.

September 25, 2026

In the latest Humans of NanoSI, Postdoctoral Research Associate Saion K. Roy discusses his work at the intersection of integrated circuits, machine learning and hardware security. Building on doctoral research in energy-efficient in-memory computing, Roy now studies how choices at the algorithm, architecture and circuit levels shape both the efficiency and the attack surface of machine-learning hardware. His recent papers at CCS and ICCAD 2026 demonstrate side-channel attacks on Apple Silicon and Rowhammer-based backdoor injection in deployed neural networks, reinforcing his case for treating security as a design constraint from the start rather than a layer added afterward.

September 23, 2026

NanoSI faculty member Aravind Nagulu is part of a six-year, $9 million U.S. Army-funded project to build smaller, faster and more energy-efficient electromagnetic sensing systems. Led by Duke University with Northeastern, Yale and Raytheon, the RAPTORS effort pairs reconfigurable metamaterial antennas with radio-frequency integrated circuits that process signals in the analog domain, close to where they are received, rather than shipping raw data to digital processors. Nagulu's group will develop that near-sensor, approximate-computing hardware, with potential applications in wireless communications, radar and spectrum monitoring.

September 22, 2026

NanoSI researchers led by Professors Cristian Cassella, Xufeng Zhang, and Mingzhong Wu have published new work in the IEEE Journal of Microelectromechanical Systems on the design and physics of chip-scale magnetoelectric antennas. The team built two Aluminum Scandium Nitride bulk acoustic wave antennas that achieved the highest bandwidths reported to date for this device class. Their modeling also showed that magnetoelastic coupling, not stray electrical effects, drives nearly all of the radiation. The resulting design framework could help replace bulky circuit-board antennas with miniaturized, low-cost wireless sensors and IoT devices.

September 17, 2026

NanoSI faculty member Aatmesh Shrivastava has received a ~$1.2M NIH R01 to develop ultra-low-power, machine-learning-enabled sub-scalp EEG implants that process brain activity in real time. The project pairs new ML algorithms with an analog-computing ASIC, using epilepsy as a proof of concept, with broader potential for neurological monitoring, closed-loop therapies, and brain-computer interfaces.

July 7, 2026

Northeastern's David Horsley, with Michelle Kiang of MTM Venture Partners, received a $7.1M NSF grant for "Scaling Deep Tech Innovation Through International Partnerships." The four-year project builds on earlier Taiwan and Singapore workshops, expands collaboration to Japan and South Korea, and creates a competitive grant framework funding U.S. deep-tech startups directly.