AIMC Topic: Volatile Organic Compounds

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Portable Mass Spectrometry for On-site Detection of Hazardous Volatile Organic Compounds via Robotic Extractive Sampling.

Analytical chemistry
Various hazardous volatile organic compounds (VOCs) are frequently released into environments during accidental events that cause many hazards to ecosystems and humans. Therefore, rapid, sensitive, and on-site detection of hazardous VOCs is crucial t...

Graphene and metal-organic framework hybrids for high-performance sensors for lung cancer biomarker detection supported by machine learning augmentation.

Nanoscale
Conventional diagnostic methods for lung cancer, based on breath analysis using gas chromatography and mass spectrometry, have limitations for fast screening due to their limited availability, operational complexity, and high cost. As potential repla...

Data-driven, explainable machine learning model for predicting volatile organic compounds' standard vaporization enthalpy.

Chemosphere
The accurate prediction of standard vaporization enthalpy (ΔH°) for volatile organic compounds (VOCs) is of paramount importance in environmental chemistry, industrial applications and regulatory compliance. To overcome traditional experimental metho...

Online sequential analysis of volatile and semivolatile organic compounds in water matrices by double robotic sample preparations and dual-channel mono and comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry system.

Journal of chromatography. A
The monitoring of organic compounds in aquatic matrices poses challenges due to its complexity and time-intensive nature. To address these challenges, we introduce a novel approach utilizing a dual-channel mono (D) and comprehensive two-dimensional (...

The Classification of VOCs Based on Sensor Images Using a Lightweight Neural Network for Lung Cancer Diagnosis.

Sensors (Basel, Switzerland)
The application of artificial intelligence to point-of-care testing (POCT) disease detection has become a hot research field, in which breath detection, which detects the patient's exhaled VOCs, combined with sensor arrays of convolutional neural net...

Application of a generalized hybrid machine learning model for the prediction of HS and VOCs removal in a compact trickle bed bioreactor (CTBB).

Chemosphere
This study presents a generalized hybrid model for predicting HS and VOCs removal efficiency using a machine learning model: K-NN (K - nearest neighbors) and RF (random forest). The approach adopted in this study enabled the (i) identification of odo...

VOC data-driven evaluation of vehicle cabin odor: from ANN to CNN-BiLSTM.

Environmental science and pollution research international
Emissions of volatile organic compounds (VOCs) in vehicles represent a significant problem, causing unpleasant odors. To mitigate VOCs and odors in vehicles, it is critical to choose interior parts with low odor and VOC emissions. However, prevailing...

Rapid and non-destructive microbial quality prediction of fresh pork stored under modified atmospheres by using selected-ion flow-tube mass spectrometry and machine learning.

Meat science
Volatile organic compounds (VOCs) indicative of pork microbial spoilage can be quantified rapidly at trace levels using selected-ion flow-tube mass spectrometry (SIFT-MS). Packaging atmosphere is one of the factors influencing VOC production patterns...

Multichannel Hierarchical Analysis of Time-Resolved Hyperspectral Data for Advanced Colorimetric E-Nose.

ACS sensors
The colorimetric sensor-based electronic nose has been demonstrated to discriminate specific gaseous molecules for various applications, including health or environmental monitoring. However, conventional colorimetric sensor systems rely on RGB senso...

Rapid classification of coffee origin by combining mass spectrometry analysis of coffee aroma with deep learning.

Food chemistry
Mislabeling the geographical origin of coffee is a prevalent form of fraud. In this study, a rapid, nondestructive, and high-throughput method combining mass spectrometry (MS) analysis and intelligence algorithms to classify coffee origin was develop...