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In this study, the graphene ion-sensitive field-effect transistor in an electrolyte solution with different K+ concentration has been investigated. It is found that by measuring the gate voltage changes, the… Click to show full abstract
In this study, the graphene ion-sensitive field-effect transistor in an electrolyte solution with different K+ concentration has been investigated. It is found that by measuring the gate voltage changes, the K+ concentration in the electrolyte can be determined because of the interaction between the K+ ions and the gate. For prediction purpose, the artificial neural network has been employed to predict the I–V characteristic, and it demonstrated superior performance.
Keywords:
computational model;
learning predict;
predict graphene;
graphene;
neural learning;
model neural
Journal Title: Journal of Electronic Materials
Year Published: 2019
Link to full text (if available)
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Journal Title: Journal of Electronic Materials
Year Published: 2019
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!