Researchers at Penn State, led by Huanyu 'Larry' Cheng, have developed a novel breath sensor that can diagnose diabetes and prediabetes within minutes by analyzing acetone levels in exhaled breath.

The sensor detects elevated acetone, a natural byproduct of fat metabolism, which serves as a reliable biomarker for diabetes when levels exceed 1.8 parts per million.

This new device offers a non-invasive alternative to traditional diabetes testing methods, which often involve blood or sweat glucose measurements that can be invasive or impractical.

Currently, the sensor requires breath collection in a bag to minimize environmental interference, but future designs aim for direct use under the nose or integration into masks for more convenience.

The sensor utilizes laser-induced graphene, created by a CO₂ laser on polyimide film, to produce a porous, patterned material that enhances its gas sensing capabilities.

A moisture barrier layer has been added to the sensor to block water vapor interference, addressing the humidity challenges present in human breath.

Unlike existing sensors that detect glucose in sweat requiring induced sweating through exercise or chemicals, this breath sensor only needs a simple sample, making it more user-friendly.

The technology has the potential to make diabetes screening more accessible and affordable, especially in settings lacking advanced laboratory facilities.

Traditional diagnostic methods involve invasive blood tests or impractical sweat analysis, highlighting the significance of this rapid, non-invasive approach.

To improve specificity for acetone detection, the sensor combines graphene with zinc oxide, forming a junction that selectively detects acetone over other gases.

The research findings, recently published in the Chemical Engineering Journal, underscore the potential for this technology to revolutionize quick and non-invasive diabetes screening.

The team plans to investigate how fluctuations in breath acetone relate to diet and exercise, which could expand the sensor's application for broader health monitoring beyond diabetes.