Researchers at the University of Minnesota combined graphene with nano-sized metal ribbons of gold to create an ultrasensitive biosensor that could help detect a variety of diseases in humans and animals. Image: Oh Group, University of Minnesota.
Researchers at the University of Minnesota combined graphene with nano-sized metal ribbons of gold to create an ultrasensitive biosensor that could help detect a variety of diseases in humans and animals. Image: Oh Group, University of Minnesota.

Using the wonder material graphene, researchers at the University of Minnesota have developed a unique new device that represents the first step toward ultrasensitive biosensors for detecting diseases at the molecular level with near perfect efficiency. The researchers report their work in a paper in Nature Nanotechnology.

Ultrasensitive biosensors for probing protein structures could greatly improve the diagnosis of a wide variety of diseases, extending to both humans and animals. These include Alzheimer's disease, chronic wasting disease and mad cow disease – disorders related to protein misfolding. Such biosensors could also lead to improved technologies for developing new pharmaceutical compounds.

"In order to detect and treat many diseases we need to detect protein molecules at very small amounts and understand their structure," said Sang-Hyun Oh, professor of electrical and computer engineering at the University of Minnesota and lead researcher on the study. "Currently, there are many technical challenges with that process. We hope that our device using graphene and a unique manufacturing process will provide the fundamental research that can help overcome those challenges."

Graphene, which is made of a single layer of carbon atoms, was discovered more than a decade ago. Ever since, it has enthralled researchers with its range of amazing properties that have found uses in many new applications, including creating better sensors for detecting diseases.

Significant attempts have been made to improve biosensors using graphene, but researchers have encountered a difficulty with its remarkable single-atom thickness, which means it does not interact efficiently with light shone through it. Light absorption and conversion to local electric fields is essential for detecting small amounts of molecules when diagnosing diseases. Previous research utilizing similar graphene nanostructures has only demonstrated a light absorption rate of less than 10%.

In this new study, University of Minnesota researchers combined graphene with nano-sized metal ribbons of gold. Using sticky tape and a high-tech nanofabrication technique developed at the University of Minnesota, called ‘template stripping’, the researchers were able to create an ultra-flat base layer surface for the graphene.

They then used the energy of light to generate a sloshing motion of electrons in the graphene, termed plasmons, which can be thought of as like ripples or waves spreading through a ‘sea’ of electrons. These waves can build in intensity to giant ‘tidal waves’ of local electric fields.

By shining light on the single-atom-thick graphene layer device, the researchers were able to create a ‘tidal’ plasmon wave with unprecedented efficiency, producing a near-perfect 94% light absorption. When they inserted protein molecules between the graphene and the metal ribbons, they were able to harness enough energy to view single layers of the protein molecules.

"Our computer simulations showed that this novel approach would work, but we were still a little surprised when we achieved the 94% light absorption in real devices," said Oh. "Realizing an ideal from a computer simulation has so many challenges. Everything has to be so high quality and atomically flat. The fact that we could obtain such good agreement between theory and experiment was quite surprising and exciting."

This story is adapted from material from the University of Minnesota, with editorial changes made by Materials Today. The views expressed in this article do not necessarily represent those of Elsevier. Link to original source.