Recent Trends in Two Dimensional Borophene Nanosheet for Sensor Applications Using Machine Learning: A Mini Review

Abstract

Borophene, a new two-dimensional (2D) material possesses metallic behaviour, Dirac nature, exceptional thermal as well as electrical conductivity and mechanical properties. These excellent properties of borophene nanosheet could be utilized in many research fields including sensor. Borophene shows excellent conductivity due to increased density of states around Fermi level and this is attributed to the $P_{z}$ orbital than $P_{x}$ and $P_{y}$ orbitals, and also due to the Dirac nature of borophene nanosheet. This favours the enhanced performance of borophene nanosheet as sensor. The present review focuses on the development of borophene nanosheet and its applications as various kinds of sensor such as NO2, humidity and pressure sensor using experimental observations, and as sensors for methanol, ethanol, metronidazole drug, ammonia, nucleobases, formaldehyde electric sensor, bromoacetone, CO, NH3, SO2, H2S and NO2 using theoretical predictions. Furthermore, this review gives insights on the use of Machine Learning (ML) and Artificial Intelligence (AI) such as artificial neural network to predict the performance of borophene as refractive index sensor. The challenges and future perspectives in the field of borophene nanosheet based sensor using ML and AI have also been discussed.

Keywords

• Borophene
• two-dimensional material
• sensor
• machine learning
• artificial Intelligence