AIMC Topic: Gases
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Recent advances in medical gas sensing with artificial intelligence-enabled technology.
Medical gas research
Jan 18, 2025
Recent advancements in artificial intelligence-enabled medical gas sensing have led to enhanced accuracy, safety, and efficiency in healthcare. Medical gases, including oxygen, nitrous oxide, and carbon dioxide, are essential for various treatments b...
Accelerated Screening of Highly Sensitive Gas Sensor Materials for Greenhouse Gases Based on DFT and Machine Learning Methods.
ACS sensors
Jan 6, 2025
Greenhouse gases (GHGs) have caused great harm to the ecological environment, so it is necessary to screen gas sensor materials for detecting GHGs. In this study, we propose an ideal gas sensor design strategy with high screening efficiency and low c...
Novel method for predicting concentrations of incineration flue gas based on waste composition and machine learning.
Journal of environmental management
Dec 5, 2024
The complex composition of solid waste leads to the variability of flue gas emissions during its incineration, which poses a challenge to the stable operation of incineration and pollution control systems. To address this problem, the study explored ...
Feasibility of classification of drainage and river water quality using machine learning methods based on multidimensional data from a gas sensor array.
Annals of agricultural and environmental medicine : AAEM
Dec 2, 2024
OBJECTIVE: The aim of the study is to verify whether the electronic nose system - an array of 17 gas sensors with a signal analysis system - is a useful tool for the classification and preliminary assessment of the quality of drainage water.
A Novel Calibration Scheme of Gas Sensor Array for a More Accurate Measurement Model of Mixed Gases.
ACS sensors
Nov 13, 2024
Gas sensor arrays (GSAs) usually encounter challenges due to the cross-contamination of mixed gases, leading to reduced accuracy in measuring gas mixtures. However, with the advent of artificial intelligence, there is a promising avenue for addressin...
Selective Identification of Hazardous Gases Using Flexible, Room-Temperature Operable Sensor Array Based on Reduced Graphene Oxide and Metal Oxide Nanoparticles via Machine Learning.
ACS sensors
Oct 29, 2024
Selective detection and monitoring of hazardous gases with similar properties are highly desirable to ensure human safety. The development of flexible and room-temperature (RT) operable chemiresistive gas sensors provides an excellent opportunity to ...
A machine learning-based electronic nose system using numerous low-cost gas sensors for real-time alcoholic beverage classification.
Analytical methods : advancing methods and applications
Aug 29, 2024
This study introduces numerous low-cost gas sensors and a real-time alcoholic beverage classification system based on machine learning. Dogs possess a superior sense of smell compared to humans due to having 30 times more olfactory receptors and thre...
Neural Network Based Aliasing Spectral Decoupling Algorithm for Precise Mid-Infrared Multicomponent Gases Sensing.
ACS sensors
Aug 16, 2024
Owing to the overlapping and cross-interference of absorption lines in multicomponent gases, the simultaneous measurement of such gases via laser absorption spectroscopy frequently necessitates the use of supplementary pressure sensors to distinguish...
Production of high calorific value hydrogen-rich combustible gas by supercritical water gasification of straw assisted by machine learning.
Bioresource technology
Aug 14, 2024
This article reveals the basic laws of straw supercritical water gasification (SCWG) and provides basic experimental data for the effective utilization of straw. The paper studied the impact of three operational conditions on the production of high-c...
Improved medical waste plasma gasification modelling based on implicit knowledge-guided interpretable machine learning.
Waste management (New York, N.Y.)
Aug 3, 2024
Ensuring the interpretability of machine learning models in chemical engineering remains challenging due to inherent limitations and data quality issues, hindering their reliable application. In this study, a qualitatively implicit knowledge-guided m...
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