on
Self-cleaning nanoscale sensor could transform personalized medicine
Imagine a smart bandage that could continuously monitor an infected wound, alerting doctors when bacteria spread or when treatment begins to work. That vision is one step closer to reality with new research from Virginia Tech.
An interdisciplinary team has developed a biosensor that can clean itself after being covered by biological materials like blood that would normally stop it from working. The technology could one day enable continuous monitoring of chronic wounds, infections and other diseases, giving doctors an ongoing view of a patient's condition that's more thorough than periodic checkups or tests.
The research team includes Aditya Garg '18, M.S. '20, Ph.D. '24, who is now a postdoctoral researcher at Massachusetts Institute of Technology; Wei Zhou, director of Virginia Tech's Micro-/Nanofabrication Cleanroom and Laboratory and associate professor of electrical and computer engineering; Peter Vikesland, the Pryor Professor of civil and environmental engineering; and Erin Gloag, assistant professor in the Virginia-Maryland College of Veterinary Medicine. Their work was published in Advanced Science.
"Our self-regenerating sensor paves the way for smart bandages and bedside tools that can detect early signs of infection and guide timely, personalized treatments," said Zhou.
Why biosensors fail over time
The research was inspired by conversations with wound care clinicians, who highlighted a major challenge: After patients leave the clinic, there is no easy way to track what is happening beneath a wound dressing until the next clinical visit.
"Many chronic wounds, like diabetic ulcers or severe burns, fail to heal because underlying bacterial infections are difficult to monitor continuously," said Zhou. "Traditional sensors lose their accuracy because proteins gunk up their surfaces."
While existing molecular sensors can detect disease-related molecules with remarkable sensitivity, many lose that ability within hours as they become coated with proteins and other biological materials naturally present in blood, bodily fluids and tissue. As biological material accumulates on the sensor's surface, the signal fades. It's like trying to see through a window that slowly becomes covered with dirt. Once that happens, the sensor has to be cleaned, regenerated or replaced.
Regenerating the sensor at the nanoscale
To address the problem, researchers built a soft, nanoscale sensor consisting of tiny pockets that are less than 10 nanometers wide—about 5,000 times thinner than human hair.
"The extreme sensitivity comes with a major challenge," said Garg. "Proteins and other biological materials quickly accumulate inside these tiny spaces, blocking them and preventing the sensor from working."
The team engineered the sensor so that when its sensing pockets are exposed to ultrafast laser pulses, they generate microscopic cavitation bubbles. Those bubbles produce localized heat that gently dislodges accumulated proteins and other biological materials to preserve the sensor's function.
In laboratory testing, the sensor was exposed to human serum for 24 hours, but it successfully regained its sensitivity and detected pyocyanin—a molecule produced by the bacterium Pseudomonas aeruginosa that can signal infection.
Just as importantly, the sensor continued to perform reliably after repeated regeneration cycles, monitoring the molecular changes that can signal disease progression in wound models over 24 hours.
A platform for personalized medicine
While the study focused on chronic wound infections, the researchers said the technology could have applications far beyond wound care.
"Our approach has potential for wide utility in any environment where long-term monitoring is important," said Vikesland. "Self-cleaning makes deployment in environmental settings feasible. This approach has potential for use in ensuring water is safe to drink and use."
Long-term molecular monitoring is widely regarded as a major goal in personalized medicine. Instead of tasking clinicians with making decisions based on occasional snapshots like one lab result here or one scan, it would allow them to monitor how diseases develop or respond to treatment in real time.
The same sensor could be used alongside implanted medical devices to flag early signs of complications or help surgeons distinguish healthy from cancerous tissue during treatment. In infections, continuous sensing could reveal how pathogens and their molecular signals shift in response to treatment over time, offering a level of insight that current tools simply can't capture.
But translating that vision into clinical reality will take time. Before reaching patients, the technology must be tested in living systems to confirm that it remains stable, safe and reliable over long periods of use.
The team envisions pairing the sensor with machine learning tools that can sift through the constant stream of molecular signals and translate them into information that clinicians can use in the moment.
"Our long-term vision is to transform health care from reactive to proactive," said Garg. "Instead of waiting for symptoms to appear or relying on periodic tests, we hope to continuously monitor the molecular signals of disease and help clinicians intervene earlier to make informed decisions."
Publication details
Aditya Garg et al, Femtosecond‐Laser Nanocavitation Regenerates SERS‐Active Plasmonic Nanogaps for Longitudinal Molecular Sensing at Biointerfaces, Advanced Science (2026). DOI: 10.1002/advs.76330
Who's behind this story?
BA art history, MA material culture. Former museum editor, paramedic, and transplant coordinator. Editing for Science X since 2021. Full profile →
Bachelor's in mathematical biology, Master's in creative writing. Well-traveled with unique perspectives on science and language. Full profile →
Citation: Self-cleaning nanoscale sensor could transform personalized medicine (2026, July 28) retrieved 28 July 2026 from https://phys.org/news/2026-07-nanoscale-sensor-personalized-medicine.html
This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.