With research that sits at the crossroads of physics, nanotechnology and big data, scientists have developed a new method for detecting and analyzing organic compounds that solves some of the challenges of the benchmark technique of infrared spectroscopy.
IR spectroscopy requires complicated procedures and large, expensive instruments, making device miniaturization challenging. These factors also hinder its use for some industrial and medical applications, and for data collection in the field. The technique also requires large sample amounts due to its low sensitivity.
The new system, by contrast, is sensitive and compact. Instead of relying on conventional spectroscopy, it relies on nanophotonics. It uses an engineered surface covered with hundreds of metapixels, tiny sensors that can generate a distinct bar code for every molecule with which the surface comes into contact. These bar codes can then be massively analyzed and classified using advanced pattern recognition and sorting technology.
The process for creating the bar code relies upon the fact that chemical bonds in organic molecules each have a specific orientation and vibrational mode. As a result, each type of molecule absorbs light at different frequencies, which translates to a unique “signature.” IR spectroscopy uses this information to test whether a sample absorbs light rays at the molecule’s signature frequencies. With the new system, the metapixels each resonate at different frequencies; the way the molecule absorbs light changes the behavior of all of the metapixels it touches. This creates a pixelated map of light absorption that can be translated into a bar code.
The scientists, who hail from École Polytechnique Fédérale de Lausanne (EPFL) School of Engineering and Australian National University (ANU), have successfully used their system to detect polymers, pesticides and organic compounds. A paper on their research appeared today in the journal Science.
The potential applications are many. "For instance, it could be used to make portable medical testing devices that generate bar codes for each of the biomarkers found in a blood sample," said Dragomir Neshev, one of the co-authors of the study. The system is compatible with complementary metal-oxide-semiconductor (CMOS) technology, used for constructing integrated circuits. By combining the new technology with AI, it also could be used to create and process a whole library of molecular bar codes for a wide variety of compounds — giving researchers a new tool for quickly and accurately spotting even miniscule amounts present in complex samples.