Multiplexed DNA-functionalized graphene sensor with artificial intelligence discrimination performance of chemical vapor composition

Abstract This study presents a new technology that can detect and discriminate individual chemical vapors to determine the chemical vapor composition from mixed chemical composition in situ based on a multiplexed DNA-functionalized graphene (MDFG) nano-electrode without condensing the original vapor or target dilution. To the best of our knowledge, AI (Artificial Intelligence)-operated arrayed-electrodes identified the composition of mixed chemical gas with mixed ratio of it in early stage. This innovative technology comprises an optimized combination of nano-deposited arrayed electrodes and artificial intelligence techniques with advanced sensing capabilities that are comparable to the biological limit, resulting to verify mixed vapor chemical components. Highly selective sensors that are tolerant to high humidity levels provide a target for “breath chemo-vapor fingerprinting” for the early diagnosis of diseases. The feature selection analysis achieves recognition rates of 99% and above under low-humidity conditions and 98% and above in humid conditions for mixed chemical compositions. The 1D convolutional neural network analysis performed better with discriminates the compositional state of chemical vapor under low- and high-humidity conditions almost perfectly. This study provides a basis for the use of multiplexed DNA-functionalized graphene gas sensor array and artificial intelligence discrimination of chemical vapor compositions in breath analysis applications.