AIMC Topic: Gases

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Gas Recognition in E-Nose System: A Review.

IEEE transactions on biomedical circuits and systems
Gas recognition is essential in an electronic nose (E-nose) system, which is responsible for recognizing multivariate responses obtained by gas sensors in various applications. Over the past decades, classical gas recognition approaches such as princ...

Zero-Padding and Spatial Augmentation-Based Gas Sensor Node Optimization Approach in Resource-Constrained 6G-IoT Paradigm.

Sensors (Basel, Switzerland)
Ultra-low-power is a key performance indicator in 6G-IoT ecosystems. Sensor nodes in this eco-system are also capable of running light-weight artificial intelligence (AI) models. In this work, we have achieved high performance in a gas sensor system ...

Modeling solubility of CO-N gas mixtures in aqueous electrolyte systems using artificial intelligence techniques and equations of state.

Scientific reports
Determining the solubility of non-hydrocarbon gases such as carbon dioxide (CO) and nitrogen (N) in water and brine is one of the most controversial challenges in the oil and chemical industries. Although many researches have been conducted on solubi...

Assessment of medical waste generation, associated environmental impact, and management issues after the outbreak of COVID-19: A case study of the Hubei Province in China.

PloS one
COVID-19 greatly challenges the human health sector, and has resulted in a large amount of medical waste that poses various potential threats to the environment. In this study, we compiled relevant data released by official agencies and the media, an...

Rapid Quantitative Analysis of IR Absorption Spectra for Trace Gas Detection by Artificial Neural Networks Trained with Synthetic Data.

Sensors (Basel, Switzerland)
Infrared absorption spectroscopy is a widely used tool to quantify and monitor compositions of gases. The concentration information is often retrieved by fitting absorption profiles to the acquired spectra, utilizing spectroscopic databases. In compl...

Pyrolytic characteristics of fine materials from municipal solid waste using TG-FTIR, Py-GC/MS, and deep learning approach: Kinetics, thermodynamics, and gaseous products distribution.

Chemosphere
Fine materials (FM) from municipal solid waste (MSW) classification require disposal, and pyrolysis is a feasible method for the treatments. Hence, the behavior, kinetics, and products of FM pyrolysis were investigated in this study. A deep learning ...

Advanced Recovery and High-Sensitive Properties of Memristor-Based Gas Sensor Devices Operated at Room Temperature.

ACS sensors
Fast recovery, high sensitivity, high selectivity, and room temperature (RT) sensing characteristics of NO gas sensors are essential for environmental monitoring, artificial intelligence, and inflammatory diagnosis of asthma patients. However, the co...

Flexible IoT Gas Sensor Node for Automated Life Science Environments Using Stationary and Mobile Robots.

Sensors (Basel, Switzerland)
In recent years the degree of automation in life science laboratories increased considerably by introducing stationary and mobile robots. This trend requires intensified considerations of the occupational safety for cooperating humans, since the robo...

Targeted Free Energy Perturbation Revisited: Accurate Free Energies from Mapped Reference Potentials.

The journal of physical chemistry letters
We present an approach that extends the theory of targeted free energy perturbation (TFEP) to calculate free energy differences and free energy surfaces at an accurate quantum mechanical level of theory from a cheaper reference potential. The converg...

Machine Learning Directed Optimization of Classical Molecular Modeling Force Fields.

Journal of chemical information and modeling
Accurate force fields are necessary for predictive molecular simulations. However, developing force fields that accurately reproduce experimental properties is challenging. Here, we present a machine learning directed, multiobjective optimization wor...