AIMC Topic: Filtration

Clear Filters Showing 1 to 10 of 26 articles

Assessment of ceramic rings and k1 biofilter as carriers in phenol and COD removal using SB-MBBR using machine learning and statistical technique.

Biodegradation
This investigation evaluates the performance of a sequencing batch moving bed biofilm reactor (SB-MBBR) employing Ceramic Rings and K1 biofilters as biofilm carriers for the removal of phenol and chemical oxygen demand (COD) from synthetic landfill l...

A machine learning model guided by physical principles for biofilter performance prediction.

Scientific reports
Despite the critical role of biofilters in water quality and sustainability, predicting their performance remains challenging due to the complexity of microbial interactions and limitations of sparse, high-dimensional datasets. Here, we introduce Env...

A 3D Nanofiltration Array for Direct Plasma EV Purification with Label-Free SERS Detection toward Accurate Clinical Breast Cancer Staging.

ACS sensors
Extracellular vesicles (EVs) have emerged as promising biomarkers in cancer diagnostics. However, rapid and nondestructive isolation of EVs from plasma remains challenging due to the presence of abundant interferents with smaller sizes (e.g., protein...

Machine learning-driven optical microfiltration device for improved nanoplastic sampling and detection in water systems.

Journal of hazardous materials
The rising presence of nanoplastics in water poses toxicity risks and long-term ecological and health impacts. Detecting nanoplastics remains challenging due to their small size, complex chemistry, and environmental interference. Traditional filtrati...

Novel PVDF mixed matrix membranes incorporated with green synthesized magnesium oxide nanoparticles for enhanced dye removal: Optimization using RSM, SOLVER, and ANN approach.

Environmental research
The application of nanofiltration membrane technology for removing pollutant dyes from industrial wastewater represents a significant advance in environmental remediation. This research explores the development and performance evaluation of a novel P...

A machine learning based framework to tailor properties of nanofiltration and reverse osmosis membranes for targeted removal of organic micropollutants.

Water research
Nanofiltration (NF) and reverse osmosis (RO) membranes play an increasingly important role in the removal of organic micropollutants (OMPs), which puts higher demands on the customization of membranes suitable for OMPs removal based on the rejection ...

Loss of micropollutants on syringe filters during sample filtration: Machine learning approach for selecting appropriate filters.

Chemosphere
Prefiltration before chromatographic analysis is critical in the monitoring of environmental micropollutants (MPs). However, in an aqueous matrix, such monitoring often leads to out-of-specification results owing to the loss of MPs on syringe filters...

Spectral fusion-based machine learning classifiers for discriminating membrane breakage in multiple scenarios.

Water research
Membrane breakage can lead to filtration failure, which allows harmful substances to enter the effluent, posing potential hazards to human health and the environment. This study is an innovative combination of fluorescence and ultraviolet-visible (UV...

Applications of artificial intelligence (AI) in drinking water treatment processes: Possibilities.

Chemosphere
In water treatment processes (WTPs), artificial intelligence (AI) based techniques, particularly machine learning (ML) models have been increasingly applied in decision-making activities, process control and optimization, and cost management. At leas...

The intelligent prediction of membrane fouling during membrane filtration by mathematical models and artificial intelligence models.

Chemosphere
Recently, membrane separation technology has been widely utilized in filtration process intensification due to its efficient performance and unique advantages, but membrane fouling limits its development and application. Therefore, the research on me...