Machine Learning-Assisted Multifunctional Environmental Sensing Based on a Piezoelectric Cantilever

Abstract

Multifunctional environmental sensing is crucial for various applications in agriculture, pollution monitoring, and disease diagnosis. However, most of these sensing systems consist of multiple sensors, leading to significantly increased dimensions, energy consumption, and structural complexity. They also often suffer from signal interferences among multiple sensing elements. Herein, we report a multifunctional environmental sensor based on one single sensing element. A MoS 2 film was deposited on the surface of a piezoelectric microcantilever (300 × 1000 μm 2 ) and used as both a sensing layer and top electrode to make full use of the changes in multiple properties of MoS 2 after its exposure to various environments. The proposed sensor has been demonstrated for humidity detection and achieved high resolution (0.3% RH), low hysteresis (5.6%), and fast response (1 s) and recovery (2.8 s). Based on the analysis of the magnitude spectra for transmission using machine learning algorithms, the sensor accurately quantifies temperatures and CO 2 concentrations in the interference of humidity with accuracies of 91.9 and 92.1%, respectively. Furthermore, the sensor has been successfully demonstrated for real-time detection of humidity and temperature or CO 2 concentrations for various applications, revealing its great potential in human−machine interactions and health monitoring of plants and human beings.

Machine Learning-Aided All-Organic Air-Permeable Piezoelectric Nanogenerator

“…Apart from these, we have also shown that our fabricated flexible, all-organic device is also air-permeable for wearable electronics applications, − by performing the air permeability test with water vapor from our lab-made setup. In our test, we have obtained a water vapor transmission rate (WVTR) of ∼250 g m –2 day –1 , which indicates better air permeability, breathability, and appropriateness for wearable devices and sensor applications.…”

2D Materials in Flexible Electronics: Recent Advances and Future Prospectives

“…Li et al demonstrated a multifunctional environmental sensor using a single sensor composed of a MoS 2 film deposited on a piezoelectric microcantilever (Figure 29e). 1056 The MoS 2 film served as both a sensing layer and top electrode, and the humidity and CO 2 concentration sensing was demonstrated using a single sensor. The sensor demonstrated excellent performance in detecting humidity, with high resolution (0.3% RH), low hysteresis (5.6%), and fast response (1 s) and recovery (2.8 s) times.…”

“…Multifunctional environmental sensing is of great importance for various applications, such as agriculture, pollution monitoring, and disease diagnosis. Li et al demonstrated a multifunctional environmental sensor using a single sensor composed of a MoS 2 film deposited on a piezoelectric microcantilever (Figure e) . The MoS 2 film served as both a sensing layer and top electrode, and the humidity and CO 2 concentration sensing was demonstrated using a single sensor.…”

Harnessing Deep Neural Networks to Analyze Multi‐Channel Anion Sensing Characteristics of a Ru(II)‐Pyrazolyl‐Bis(Benzimidazole) Complex

“…The technological progress of ML is now manifested in nearly all branches of science and technology [1–11] . Through proper handling of powerful computation and high‐throughput experimentation, ML has expedited the scientific research and technological development [12–31] . Even though the adoption of data‐guided growth of materials is inspiring to recognize the accurate potential of ML models, they should also have the potentiality over solely predictive ability.…”

“…[1][2][3][4][5][6][7][8][9][10][11] Through proper handling of powerful computation and highthroughput experimentation, ML has expedited the scientific research and technological development. [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] Even though the adoption of data-guided growth of materials is inspiring to recognize the accurate potential of ML models, they should also have the potentiality over solely predictive ability. The prediction and inner execution of models must offer appropriate explanation to the human specialists.…”