Acetone Gas Sensor Based On Porous Structured Oxide Semiconductor

With the development of digital transformation,high precise and comprehensive environmental perception has become a key object in modern technology.Gas sensors,as crucial components of information systems,play a vital role in fields like environmental monitoring and industrial safety,especially in the efficient and accurate detection of volatile organic compounds（VOCs）.Acetone is a typical VOC,and widely exists in our daily life.Its potential impact on human health and environment cannot be ignored,thus developing acetone gas sensors that exhibit high sensitivity,selectivity and stability is essential.Metal Oxide Semiconductor（MOS）gas sensors have become a focal point for gas sensing with their simple device structure,ease of miniaturization,and suitability for online monitoring.However,there are still some challenges in the practical applications,such as the insufficient specific response to acetone and the lack of stability.In order to solve these problems,on the one hand,optimizing the sensing materials and exploring the device structures can significantly improve the properties of gas sensors.On the other hand,combining with algorithms can achieve the sensing signal intelligent analysis to improve the accuracy and reliability of detection.Based on these,a high-performance acetone gas sensor can be developed.This research selects Zinc Oxide（ZnO）as the basic material,constructing porous Metal Organic Framework（MOF）derived ZnO via a self-templating method,enhancing the material with abundant oxygen vacancies（O_V）,improving the reactive sites and increasing the sensitivity of sensors.Subsequently,the energy band structure,electrical properties,and reactivity of sensing materials are modulated through interface engineering.Noble metal loading is applied to further enhance the gas sensitivity and selectivity of sensors.Moreover,the designed bilayer structure of sensors can effectively improve the moisture resistance by constructing the gas sieve hydrophobic layer.Meanwhile,combining with deep learning,specific identification and prediction of acetone can be realized.Ultimately,the selectivity,sensitivity,stability and the moisture resistance of acetone sensor have been significantly improved.The research contents are as below:1.ZnO was established as the basic material through the comparison of gas sensing properties.Subsequently,the self-templating strategy was adopted to construct the Zeolitic Imidazolate Framework-8（ZIF-8）derived ZnO with abundant O_V for acetone detection.These sensing materials have large surface area,mesoporous structure and abundant O_V,which can provide sufficient reaction sites for gas molecules.The acetone sensing performance of ZIF-8 derivative is significantly enhanced by nano-structural modulation.Additionally,the Density Functional Theory（DFT）calculation is used to investigate the mechanism of O_V.O_V is able to act as a reactive active site to adsorb and activate oxygen molecules to produce more chemisorbed oxygen,thus enhancing gas-sensing properties,which provides theoretical foundation for the fabrication of MOF-derived high-performance acetone sensing materials.2.Based on the structural adjustability of MOF,MOF-derived core-shell In₂O₃@ZnO composite sensing materials were prepared by the n-n heterojunction constructing,to regulate the energy band structure and electrical properties of sensing material,thus enhancing the sensitivity and selectivity of acetone sensor.Zeolitic Imidazolate Framework-8（ZIF-8）derived ZnO was deposited on the surface of wrinkled In₂O₃ spheres.By controlling MOF growth time,the thickness of ZnO shell layer is precisely regulated,achieving radial modulation of the electron accumulation layer in ZnO,thereby controlling the concentration of free charge carriers in gas sensing.Moreover,the ZIF-8 derived ZnO shell layer,rich in O_V,facilitates the formation of chemisorbed oxygen.Compared with ZIF-8 derived ZnO based sensors（sensitivity:8.7）,the In₂O₃@ZnO based sensor（ZnO shell thickness:55.3 nm）exhibits higher sensitivity（23.2）,faster response speed,and lower detection limit（100 ppb）at 300°C.Additionally,the intrinsic catalytic activities of In₂O₃ and ZnO are investigated to reveal the catalytic activities of sensing materials towards VOCs,and the selectivity of In₂O₃@ZnO for acetone has been enhanced by modulating the shell thickness of ZnO.3.By utilizing MOF encapsulation strategy,Pt nanoparticles were confined within MOF-derived sensing materials,enhancing the sensitivity and stability simultaneously.Initially,inverse opal（IO）structured IO-ZnO were prepared using self-assembled template.Subsequently,ZIF-8 derivative（ZD）was grown on the surface of IO-ZnO via liquid-phase epitaxial growth,confining Pt nanoparticles（NPs）to form Pt@ZD,resulting in the IO-Pt@ZD/ZnO sensing material with high catalytic activity and stability.The inverse opal structure facilitates molecular diffusion through its well-defined framework,and its high porosity and large surface area provide abundant reactive sites,thereby enhancing gas sensing characteristic.Confining Pt NPs within the pores of MOF derivative prevents the agglomeration of Pt NPs at high temperature effectively,leading to higher catalytic activity and stability.This endows the sensing material with superior free charge carrier formation and transformation capabilities,improving the sensitivity and stability of sensor simultaneously.Consequently,the IO-Pt@ZD/ZnO based sensor exhibits high sensitivity（36.4）towards 100 ppm acetone at275°C,along with excellent short-term repeatability and long-term stability（130 cycles,continuous operating for 50 days）.4.To meet the requirements of practical applications,such as high stability in moisture atmosphere and accurate detection in multi-component gas environments,it is essential to enhance the moisture resistance and selectivity of sensors through the device structural design and the introduction of intelligent algorithm.To mitigate the adverse effects of humidity,a bilayer structured acetone sensor with IO-Pt@ZD/ZnO sensing layer and zeolite molecular sieve hydrophobic layer was constructed.The introduction of hydrophobic Silicalite-1（S-1）molecular sieve significantly improves the stability of sensor in moisture atmosphere.By designing the thickness of S-1molecular sieve layer optimally,the bilayer acetone sensor exhibits high sensitivity under RH 60%and 275°C and detects 0.5 ppm of acetone effectively.Based on the testing data,the deep learning algorithm is applied to learn the impact of humidity changes on acetone detection.The sensor combined with the algorithm achieves precise prediction of acetone concentration and environmental humidity with the mean squared error of 0.08%,thereby reducing moisture interference.Furthermore,the deep learning significantly enhances the sensor’s recognizing between acetone and interfering ethanol,classifying 14 concentrations of acetone and ethanol gases effectively.The combination of gas sensor and algorithm improves the anti-humidity interference and gas recognition ability of the acetone sensor.