AIMC Topic: Gases

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Customizable Colorimetric Sensor Array via a High-Throughput Robot for Mitigation of Humidity Interference in Gas Sensing.

ACS sensors Aug 1, 2024
One challenge for gas sensors is humidity interference, as dynamic humidity conditions can cause unpredictable fluctuations in the response signal to analytes, increasing quantitative detection errors. Here, we introduce a concept: Select humidity se...
Algorithms Gases Humidity Colorimetry Robotics
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Prediction of Vacuum Ultraviolet/Ultraviolet Gas-Phase Absorption Spectra Using Molecular Feature Representations and Machine Learning.

Journal of chemical information and modeling Jun 28, 2024
Ultraviolet (UV) absorption spectroscopy is a widely used tool for quantitative and qualitative analyses of chemical compounds. In the gas phase, vacuum UV (VUV) and UV absorption spectra are specific and diagnostic for many small molecules. An accur...
Machine Learning Ultraviolet Rays Spectrophotometry, Ultraviolet Vacuum Gases
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Automated machine learning-aided prediction and interpretation of gaseous by-products from the hydrothermal liquefaction of biomass.

The Science of the total environment Jun 20, 2024
Hydrothermal liquefaction (HTL) is a thermochemical conversion technology that produces bio-oil from wet biomass without drying. However, by-product gases will inevitably be produced, and their formation is unclear. Therefore, an automated machine le...
Machine Learning Biofuels Gases Methane Carbon Dioxide Biomass
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Ultralow-Power Single-Sensor-Based E-Nose System Powered by Duty Cycling and Deep Learning for Real-Time Gas Identification.

ACS sensors Jun 10, 2024
This study presents a novel, ultralow-power single-sensor-based electronic nose (e-nose) system for real-time gas identification, distinguishing itself from conventional sensor-array-based e-nose systems, whose power consumption and cost increase wit...
Electronic Nose Gases Electric Power Supplies Deep Learning Semiconductors
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Prediction of Individual Gas Yields of Supercritical Water Gasification of Lignocellulosic Biomass by Machine Learning Models.

Molecules (Basel, Switzerland) May 16, 2024
Supercritical water gasification (SCWG) of lignocellulosic biomass is a promising pathway for the production of hydrogen. However, SCWG is a complex thermochemical process, the modeling of which is challenging via conventional methodologies. Therefor...
Hydrogen Methane Carbon Dioxide Lignin Gases Water Support Vector Machine Biomass Neural Networks, Computer Machine Learning Algorithms
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Measuring volume fractions of a three-phase flow without separation utilizing an approach based on artificial intelligence and capacitive sensors.

PloS one May 16, 2024
Many different kind of fluids in a wide variety of industries exist, such as two-phase and three-phase. Various combinations of them can be expected and gas-oil-water is one of the most common flows. Measuring the volume fraction of phases without se...
Gases Neural Networks, Computer Electric Capacitance Artificial Intelligence Water
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General Model for Predicting Response of Gas-Sensitive Materials to Target Gas Based on Machine Learning.

ACS sensors Apr 20, 2024
Gas sensors play a crucial role in various industries and applications. In recent years, there has been an increasing demand for gas sensors in society. However, the current method for screening gas-sensitive materials is time-, energy-, and cost-con...
Machine Learning Gases Density Functional Theory Adsorption Zinc Oxide
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Gas Graph Convolutional Transformer for Robust Generalization in Adaptive Gas Mixture Concentration Estimation.

ACS sensors Mar 21, 2024
Gas concentration estimation has a tremendous research significance in various fields. However, existing methods for estimating the concentration of mixed gases generally depend on specific data-preprocessing methods and suffer from poor generalizabi...
Neural Networks, Computer Algorithms Gases
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Data-centric artificial olfactory system based on the eigengraph.

Nature communications Feb 8, 2024
Recent studies of electronic nose system tend to waste significant amount of important data in odor identification. Until now, the sensitivity-oriented data composition has made it difficult to discover meaningful data to apply artificial intelligenc...
Odorants Smell Technology Humans Gases Artificial Intelligence
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Deep Learning Enabled SERS Identification of Gaseous Molecules on Flexible Plasmonic MOF Nanowire Films.

ACS sensors Feb 1, 2024
Through the capture of a target molecule at the metal surface with a highly confined electromagnetic field induced by surface plasmon, surface enhanced Raman spectroscopy (SERS) emerges as a spectral analysis technology with high sensitivity. However...
Gases Nanowires Aldehydes Spectrum Analysis, Raman Deep Learning Metal-Organic Frameworks
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