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Catalysis

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Synthesis of δ-MnO via ozonation routine for low temperature formaldehyde removal.

Journal of environmental sciences (China)
Nowadays, it is still a challenge to prepared high efficiency and low cost formaldehyde (HCHO) removal catalysts in order to tackle the long-living indoor air pollution. Herein, δ-MnO is successfully synthesized by a facile ozonation strategy, where ...

Application of triple-branch artificial neural network system for catalytic pellets combustion.

Journal of environmental management
On the international level, it is common to act on reducing emissions from energy systems. However, in addition to industrial emissions, low-stack emissions also make a significant contribution. A good step in reducing its environmental impact, is to...

Validity of zinc oxide nanoparticles biosynthesized in food wastes extract in treating real samples of printing ink wastewater; prediction models using feed-forward neural network (FFNN).

Chemosphere
In the present study, biosynthesized ZnO nanoparticles in food wastewater extract (FWEZnO NPs) was used in the photocatalytic degradation of real samples of printing ink wastewater. FWEZnO NPs were prepared using green synthesis methods using a compo...

Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater.

International journal of biological macromolecules
To maintain human health and purity of drinking water, it is crucial to eliminate harmful chemicals such as nitrophenols and azo dyes, considering their natural presence in the surroundings. In this particular research study, the application of machi...

Task decomposition strategy based on machine learning for boosting performance and identifying mechanisms in heterogeneous activation of peracetic acid process.

Water research
Heterogeneous activation of peracetic acid (PAA) process is a promising method for removing organic pollutants from water. Nevertheless, this process is constrained by several complex factors, such as the selection of catalysts, optimization of react...

Smartphone-Assisted Nanozyme Colorimetric Sensor Array Combined "Image Segmentation-Feature Extraction" Deep Learning for Detecting Unsaturated Fatty Acids.

ACS sensors
Conventional methods for detecting unsaturated fatty acids (UFAs) pose challenges for rapid analyses due to the need for complex pretreatment and expensive instruments. Here, we developed an intelligent platform for facile and low-cost analysis of UF...

Preparation of Multistage Pore TS-1 with Enhanced Photocatalytic Activity, Including Process Studies and Artificial Neural Network Modeling for Synergy Assessment.

Langmuir : the ACS journal of surfaces and colloids
Antibiotic residues have been found in several aquatic ecosystems as a result of the widespread use of antibiotics in recent years, which poses a major risk to both human health and the environment. At present, photocatalytic degradation is the most ...

Based on T.E.S.T toxicity prediction and machine learning to forecast toxicity dynamics in the photocatalytic degradation of tetracycline.

Physical chemistry chemical physics : PCCP
The integration of photocatalysis and biological treatment provides an effective strategy for controlling antibiotic contamination, which requires precise monitoring of toxicity changes during the photocatalytic process. In this study, nanoscale TiO ...

Innovations in plastic remediation: Catalytic degradation and machine learning for sustainable solutions.

Journal of contaminant hydrology
Plastic pollution is an extreme environmental threat, necessitating novel restoration solutions. The present investigation investigates the integration of machine learning (ML) techniques with catalytic degradation processes to improve plastic waste ...