AIMC Topic: Catalysis
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Task decomposition strategy based on machine learning for boosting performance and identifying mechanisms in heterogeneous activation of peracetic acid process.
Water research
Sep 26, 2024
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
Sep 19, 2024
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
Sep 6, 2024
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 ...
Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater.
International journal of biological macromolecules
Aug 14, 2024
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...
Application of triple-branch artificial neural network system for catalytic pellets combustion.
Journal of environmental management
Jul 10, 2024
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
Jul 5, 2024
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...
Application of machine learning models to improve the prediction of pesticide photodegradation in water by ZnO-based photocatalysts.
Chemosphere
Jul 5, 2024
Pesticide pollution has been posing a significant risk to human and ecosystems, and photocatalysis is widely applied for the degradation of pesticides. Machine learning (ML) emerges as a powerful method for modeling complex water treatment processes....
Potential prediction and coupling relationship revealing for recovery of platinum group metals from spent auto-exhaust catalysts based on machine learning.
Journal of environmental management
Jun 24, 2024
As hazardous waste, the massive generation of spent auto-exhaust catalysts (SACs) puts enormous pressure on environmental management, but provides a rare opportunity for platinum group metals (PGMs) recycling. In this study, machine learning (ML) met...
Prediction of g-CN-based photocatalysts in tetracycline degradation based on machine learning.
Chemosphere
Jun 17, 2024
Investigating the effects of g-CN-based photocatalysts on experimental parameters during tetracycline (TC) degradation can be helpful in discovering the optimal parameter combinations to improve the degradation efficiencies in general. Machine learni...
Machine learning screening of biomass precursors to prepare biomass carbon for organic wastewater purification: A review.
Chemosphere
Jun 16, 2024
In the past decades, the amount of biomass waste has continuously increased in human living environments, and it has attracted more and more attention. Biomass is regarded as the most high-quality and cost-effective precursor material for the prepara...
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