AIMC Topic: Gases

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A Principal Component Analysis-Integrated Machine Learning Approach for Predicting Gas-Phase VUV/UV Absorption Spectra of Molecular Compounds.

Journal of chemical information and modeling
This study integrates principal component analysis (PCA) with random forest (RF) modeling to present an enhanced machine learning framework for predicting gas-phase vacuum ultraviolet/ultraviolet (VUV/UV) absorption spectra. This method overcomes a s...

Synergistic Integration of Frequency-Dependent Impedance and Machine Learning in Semiconductor Metal Oxide-Based Breath Sensors for High-Performance Gas Discrimination.

ACS sensors
Frequency-dependent impedance spectroscopy in combination with machine learning offers a powerful strategy for discriminating among gas species using mutually interacting semiconductor metal oxide (SMO) gas sensors. In this study, 0.3 at% platinum-lo...

Durative Monitoring of Sulfur Hexafluoride Characteristic Gases under Hydrogen Interference Using a Time2Vec-Encoded CNN-Transformer-LSTM Model Based on a Heterogeneous Gas Sensor Array.

ACS sensors
Gas-insulated switchgear (GIS) systems extensively employ sulfur hexafluoride (SF) as an insulating medium and are widely deployed in modern power systems. Under partial discharge (PD) conditions, SF decomposes to generate hazardous byproducts such a...

A HAZOP-based hazard identification model for urban gas accidents: Development and empirical validation.

PloS one
Urban gas accidents pose significant threats to public safety and urban infrastructure, with traditional hazard identification methods often relying on manual inspections and experience-based judgments, leading to incomplete or inconsistent results. ...

Metal-Organic Framework-Based Chemiresistive Array Paired with Machine Learning Algorithms for the Detection and Differentiation of Toxic Gases.

ACS sensors
The development of low-power, sensitive, and selective gas sensors capable of detecting and differentiating toxic gases is pivotal for safety and environmental monitoring. This paper describes a chemiresistive sensor array comprising a series of thre...

Understanding the Role of Noncovalent Interactions in Gas Sensing with Metal-Coordinated Complexes (MCCs).

Topics in current chemistry (Cham)
Gas sensing is vital for environmental monitoring, safety, and healthcare. This review highlights the role of noncovalent interactions, hydrogen bonding, π-π stacking, and electrostatic forces in enhancing the sensitivity and selectivity of metal-coo...

Acetone Gas Sensors for Noninvasive Diabetes Diagnosis: A Comprehensive Review.

Chemical record (New York, N.Y.)
The development of sensors for monitoring breath acetone, a key biomarker for ketosis in diabetes mellitus, represents a critical frontier in medical diagnostics, promising a painless alternative to invasive blood tests. This review provides a compre...

Neural Network-Enhanced FMCW Gas Spectroscopy.

ACS sensors
Detecting multicomponent gases over extensive concentration ranges with laser spectroscopy faces challenges of complex configurations, intricate spectral analysis, and reduced accuracy. Neural networks offer transformative potential for advancing las...

Pocket Electronic Nose Integrating an Ultra-Compact Sensor Array Chip and Spatiotemporal Network Enables Highly Selective Gas Sensing.

ACS sensors
Accurately distinguishing gases with nearly identical molecular structures─such as nitric oxide (NO) and nitrogen dioxide (NO)─remains challenging for conventional sensors. We report a palm-sized (5 cm × 5 cm) electronic nose that integrates an ultra...

Systematic selection of best performing mathematical models for in vitro gas production using machine learning across diverse feeds.

Scientific reports
In vitro gas production (GP) is commonly used to evaluate ruminant feed, yet its accurate interpretation requires robust mathematical modeling. This study systematically explores a wide array of nonlinear models to explain GP dynamics across various ...