The work depicts an electrochemical hydrogel-eutectic gallium indium alloy interface for the recognition of enantiomeric chemicals. This interface allows for the recording of nonlinear current−voltage responses, depending on the composition of the hydrogel. The current-voltage data for the machine learning model are trained by a multilayer perceptron. This model accurately recognizes the enantiomeric tyrosine in mixture with interfering Phosphate-buffered saline with 79% accuracy. Thus, this interface can be used as a convenient method for expressed recognition of various chemicals and pathogens detection.

Вейни Т., Балдина А.А., Николаев К.Г., Иванов А.С. (науч. рук. Скорб Е.В.) Electrochemical detection of enantiomeric tyrosine by machine learning // Сборник тезисов докладов конгресса молодых ученых. Электронное издание. – СПб: Университет ИТМО, [2021]. URL: https://kmu.itmo.ru/digests/article/5432