LiFe<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si7.svg" display="inline" id="d1e452"><mml:msub><mml:mrow/><mml:mrow><mml:mn>5</mml:mn></mml:mrow></mml:msub></mml:math>O<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si8.svg" display="inline" id="d1e460"><mml:msub><mml:mrow/><mml:mrow><mml:mn>8</mml:mn></mml:mrow></mml:msub></mml:math>-based gas sensor: A machine learning approach for selective VOCs detection

Nayak, Sharmistha; Majumder, S.B.; Thiruppathi, K.P.; Misra, Sudip

doi:10.1016/j.matchemphys.2023.128628

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Applications Of Machine Learning In the Nanosensors Field1

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2024

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Cited by 2 publications

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References 27 publications

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“…Mahata et al 304 optimized the synthesis process of SnO 2 nanopetals used in nanosensor fabrication. Nayak et al 305 fabricated LiFe 5 O 8 -based nanosensors using a single-step hydrothermal technique. The sensor's selectivity issue was tackled using simpler ML algorithms, including K-nearest neighbor, RF, DT, and SVM.…”

Section: Applications Of Machine Learning In the Nanosensors Fieldmentioning

confidence: 99%