From nanoplastics to quantum magnets: Four teams selected for SciRIS awards

Transforming Computing through Spintronics

SciRIS Stage 3 Award

Members of the physics, mathematics and chemistry departments are leading a collaborative project to design and control spin waves in quantum magnets for future spintronic technologies.

Spintronics is an emerging field that could transform computing by using magnons — tiny packets of spin waves — instead of electrons to process and store information. Because magnons do not produce resistive heating, they offer a path to faster, more energy-efficient devices. Yet, scientists still need to understand how these waves behave and how to manipulate them for practical applications.

The cross-disciplinary team includes Oksana Ostroverkhova from the Department of Physics, Axel Saenz Rodriguez from the Department of Mathematics and Chong Fang and Tim Zuehlsdorff from the Department of Chemistry.

The group will focus on two-dimensional magnetic materials with highly tunable properties. Using OSU’s ultrafast laser facility and advanced theoretical models, the researchers aim to uncover the physical mechanisms behind spin-wave propagation in emerging 2D magnetics and develop innovative ways to control spin-wave properties for next-generation spintronics.

Cell Based Artificial Intelligence

Stage 2 Award

Bo Sun is building a transdisciplinary team to address key challenges in cell-based artificial intelligence, a groundbreaking approach in the field of computation, leveraging the inherent processing capabilities of biological cells to perform complex calculations and tasks.

With modern science, these cells can be engineered to process information, sense environmental changes, and produce outputs in response to specific inputs, much like traditional computer systems. Cell-based computing is energy efficient, environmentally friendly and capable of self-replication and repair. Advancements in cell-based artificial intelligence may also help researchers better understand brain functions to treat neurological and cognitive disorders.

Collaborating with Patrick Chappell in the College of Veterinary Medicine and an external partner at the University of Pittsburgh, Sun aims to address key challenges in cell-based artificial intelligence using a transdisciplinary approach.

Using Machine Learning to Develop Single Pixel Spectrometers

Stage 2 Award

Experimental physicist Ethan Minot is leading a pioneering effort to reinvent how we measure light. His team is developing “single-pixel spectrometers,” ultra-compact devices built from atomically thin semiconductors that can provide detailed spectral data without the bulky components used in traditional systems.

Working with electrical engineering professor Xiao Fu, Minot’s group is pairing these next-generation photodetectors with advanced machine-learning algorithms. Their goal is to enable new uses of spectroscopy through these ultra-compact photodetectors.

Future applications could include drone-based crop monitoring and wearable sensors to record ambient environmental data and manage health and well-being. Together, the team will lower barriers to deploying spectroscopy, enabling new scientific discovery and commercial opportunities.

Labeling Nanoplastics

Stage 2 Award

Marilyn Mackiewicz, associate professor of chemistry, leads a transdisciplinary project developing a metal nanoparticle-based tracker for visually tracking nanoplastic uptake in cells and in embryonic zebrafish models.

Nanoplastics, created by the breakdown of larger plastic debris, are increasingly found in water, soil and even the human body. However, concerns about the health implications of widespread exposure to micro- and nanoplastics remain largely unanswered. While toxicity studies are being conducted, visualizing these plastics in living systems is difficult due to their small size and composition.

Along with a Stacey Harper, from the Colleges of Agricultural Sciences and Engineering, Mackiewicz plans to develop a customized, stable nanotracer designed to label nanoplastics ranging from just a few billionths of a meter, slightly wider than a DNA strand, to the size of microscopic bacteria.

This tool would allow researchers to increase their understanding of nanoplastics, nanoparticle-biological interactions, and their mechanisms of uptake and toxicity. This information would be valuable to a diverse array of experts, including scientists in bioengineering, imaging and analytics, as well as climate scientists, waste management professionals and toxicologists.