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Nanostructures

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Machine Learning-Based Nanozyme Sensor Array as an Electronic Tongue for the Discrimination of Endogenous Phenolic Compounds in Food.

Analytical chemistry
The detection of endogenous phenolic compounds (EPs) in food is of great significance in elucidating their bioactivity and health effects. Here, a novel bifunctional vanillic acid-Cu (VA-Cu) nanozyme with peroxidase-like and laccase-like activities w...

Machine learning based predictive analysis of DNA cleavage induced by diverse nanomaterials.

Scientific reports
DNA cleavage by nanomaterials has the potential to be utilized as an innovative tool for gene editing. Numerous nanomaterials exhibiting DNA cleavage properties have been identified and cataloged. Yet, the exploitation of property data through data-d...

Nanomaterial Texture-Based Machine Learning of Ciprofloxacin Adsorption on Nanoporous Carbon.

International journal of molecular sciences
Drug substances in water bodies and groundwater have become a significant threat to the surrounding environment. This study focuses on the ability of the nanoporous carbon materials to remove ciprofloxacin from aqueous solutions under specific experi...

Artificial intelligence modeling and experimental studies of oily pollutants uptake from water using ZIF-8/carbon fiber nanostructure.

Journal of environmental management
In this study, the experimental and modeling of oily pollutants (crude oil, asphaltene, and maltene) uptake by ZIF-8/carbon fiber nanostructure was investigated. The influence of pollutant type, concentration, ionic strength, and sorption time on upt...

Convergence of Nanotechnology and Machine Learning: The State of the Art, Challenges, and Perspectives.

International journal of molecular sciences
Nanotechnology and machine learning (ML) are rapidly emerging fields with numerous real-world applications in medicine, materials science, computer engineering, and data processing. ML enhances nanotechnology by facilitating the processing of dataset...

Design of Biocompatible Nanomaterials Using Quasi-SMILES and Recurrent Neural Networks.

ACS applied materials & interfaces
Screening nanomaterials (NMs) with desired properties from the extensive chemical space presents significant challenges. The potential toxicity of NMs further limits their applications in biological systems. Traditional methods struggle with these co...

A novel four-modal nano-sensor based on two-dimensional Mxenes and fully connected artificial neural networks for the highly sensitive and rapid detection of ochratoxin A.

Talanta
Timely and accurate on-site detection of ochratoxin A (OTA) is extremely important for global public health. In this study, a fluorescence/colorimetric biosensor based on TiC nano-materials (TiC-NMS) and a machine-learning (ML) based fluorescence/col...

Application of artificial neural network for the mechano-bactericidal effect of bioinspired nanopatterned surfaces.

European biophysics journal : EBJ
This study aimed to calculate the effect of nanopatterns' peak sharpness, width, and spacing parameters on P. aeruginosa and S. aureus cell walls by artificial neural network and finite element analysis. Elastic and creep deformation models of bacter...

Artificial intelligence for personalized nanomedicine; from material selection to patient outcomes.

Expert opinion on drug delivery
INTRODUCTION: Artificial intelligence (AI) is changing the field of nanomedicine by exploring novel nanomaterials for developing therapies of high efficacy. AI works on larger datasets, finding sought-after nano-properties for different therapeutic a...

A supervised machine learning tool to predict the bactericidal efficiency of nanostructured surface.

Journal of nanobiotechnology
The emergence and rapid spread of multidrug-resistant bacterial strains is a growing concern of public health. Inspired by the natural bactericidal surfaces of lotus leaves and shark skin, increasing attention has been focused on the use of mechano-b...