Identification of amino acids with a diode-based microdevice
DOI: 10.1063/10.0001818
Identification of amino acids with a diode-based microdevice lead image
Sensing protein deficit or excess is critical in understanding metabolism on a microscopic scale. Common sensing methods often involve a tradeoff between user-friendly setup and the reliability of results. For instance, quantum detection displays high accuracy but requires low temperature or high vacuum. On the other hand, classical semiconductor devices are easier to use but more susceptible to variations in sample volume and biofouling.
Looking to strike a balance between reliability and ease of usage, Alkhidir et al. present a scalable diode-based microdevice that allows for the direct sensing of amino acids. The device consists of an array of microsensor diodes based on a P-I-N trilayer of gallium arsenide combined with a Schottky contact.
The researchers chose a Schottky contact due to its limiting of currents to the microampere range, as opposed to the milliampere range for the more conventional ohmic contacts, which makes the device an energy-efficient electronic system. The P-I-N diode’s presence of n-type and p-type doping allows the device to be sensitive to molecules of varied polarity, in a broader range of low voltages.
When tested in a water solution of amino acids, the diode-like sensor was able to distinguish a variety of amino acids, in a broad range of pH factor values, and at low voltages. The authors also used quantum structure modeling to estimate which atom or functional group within an amino acid molecule is most likely to end up attached to the gallium arsenide surface.
Lastly, the authors tested a machine learning process that may be used for future improvement of amino acid identification, including the simultaneous testing of several amino acids.
Source: “Detection of amino acids with modulation doped and surface nanoengineered GaAs schottky diodes,” by Tamador Alkhidir, Maguy Abi Jaoude, Deborah L. Gater, Christopher Alpha, and Abdel F. Isakovic, JVST: B (2020). The article can be accessed at http://doi.org/10.1116/6.0000186 .
