A new method has been developed by chemical engineers from the University of Wisconsin–Madison to create low-cost chemical sensors for detecting industrial pollutants, explosives, or even chemical markers of disease in the breath of a patient.
Using their knowledge in computational chemistry and liquid crystals, Manos Mavrikakis and Nicholas L. Abbott, UW–Madison professors of chemical and biological engineering, aimed to convert a sensor designed by Abbott to identify a molecular imitation of lethal sarin gas into a roadmap for tweaking similar sensors to raise an alert for other hazardous or significant chemicals.
We’ve established a new framework.
Manos Mavrikakis, Professor UW-Madison
The material they created has been described in the November 2 issue of the Nature Communications journal.
Their framework forms the basis for a new method for improving the components - similar to those located in flat-panel TVs - of a liquid-crystal-based sensor: metal cations, which are positively charged ions, solvents, salt anions, and molecules that make up liquid crystals.
The research relied on the computational chemistry expertise of Mavrikakis and the experimental expertise of Abbott, and it revolved between quantum chemical modeling and the lab-based experiments to improve the sensor parts for a specific substance.
By tuning all the individual components, they managed to identify a suitable configuration that specifically reacted to the molecule they aimed to sense, known as the analyte. The same method could produce new sensors for a number of different analytes.
This concept can be adapted in the future to detect the freshness of meat or fish based on the presence of trace quantities of cadaverine, a foul-smelling molecule. Similarly, another variation could be used to identify respiratory diseases based on the examination of tiny molecules such as nitric oxide found in breath.
However, creating this type of highly specific and sensitive materials in a lab is not an easy task. To build complex sensors using many components, chemicals need to be mixed and matched on a trial basis with a hope of figuring out the perfect combination. However this is tedious and inefficient.
Therefore, rather than performing years of trial and error, the researchers choose to use computer simulations before starting experiments in the lab.
This is indeed the first time that computational chemistry with quantum mechanics has been used to put together a coherent way of thinking for narrowing down possible solutions for an explosively complicated problem.
Manos Mavrikakis, Professor UW-Madison
Mavrikakis; work was supported by the National Science Foundation and the Army Research Office.
Once the researchers spotted potential candidates, they used real-world measurements to further tweak and enhance their computational models.
The sensor material comprises of a thin film of metal salt, with liquid crystals, all pointing in one direction, anchored to the surface.
The researchers created metal cations and specific liquid crystal molecules so that tiny quantities of analyte would disturb the liquid crystals’ interactions with the surface, and cause the ordered arrangement to become disorderly. The alteration in the liquid crystal would be an observable indicator of the presence of the analyte.
In contrast to the pricey explosive-detecting puffer machines in airports that depend on high-performance liquid chromatography equipment or complex mass spectrometry, these liquid crystal sensors could be wearable, portable, and economical.
Going forward, the researchers want to study new combinations for other analytes and create new liquid crystalline molecules, in conjunction with other solvents and metal salts, to develop even more selective and sensitive sensors.
Other authors on the research paper include past and present members of the Mavrikakis and Abbott labs: Luke Roling, Jessica Scaranto, Jeffrey Herron, Huaizhe Yu and Sangwook Choi.