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

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 Pz orbital than Px and Py 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.

Summary for Non-Scientists

Researchers are reviewing the unique properties and potential applications of borophene, a new two-dimensional material with excellent electrical and thermal conductivity, as well as strong mechanical properties.

Here’s a simplified summary:

  • Borophene has metallic behavior and exceptional properties that make it suitable for use in sensors.
  • Its high conductivity is due to certain electronic characteristics (specifically the Pz orbital and Dirac nature) that enhance its performance as a sensor.
  • The review discusses the development of borophene nanosheets and their use in various types of sensors, such as those for detecting NO2, humidity, pressure, methanol, ethanol, ammonia, and more.
  • It also explores how Machine Learning (ML) and Artificial Intelligence (AI) can be used to predict borophene’s performance in sensing applications.
  • The review highlights the challenges and future possibilities for borophene-based sensors, emphasizing the role of ML and AI in advancing this field.

Overall, this research suggests that borophene could be a game-changer in developing high-performance sensors, with the potential to revolutionize various applications.

Source :
IEEE Access
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