AIMC Topic: Nanostructures

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ZnO nanoflower-mediated paper-based electrochemical biosensor for perfect classification of cardiac biomarkers with physics-informed machine learning.

Mikrochimica acta
The widespread exposure of acute myocardial infarction globally demands an ultrasensitive, rapid, and cost-effective biosensor for troponin-I and T in a dynamic concentration range. Traditionally, the saturation of sensor response limits accurate pre...

Nanomaterial-Based Molecular Imaging in Cancer: Advances in Simulation and AI Integration.

Biomolecules
Nanomaterials represent an innovation in cancer imaging by offering enhanced contrast, improved targeting capabilities, and multifunctional imaging modalities. Recent advancements in material engineering have enabled the development of nanoparticles ...

Multimodal feature fusion machine learning for predicting chronic injury induced by engineered nanomaterials.

Nature communications
Concerns regarding chronic injuries (e.g., fibrosis and carcinogenesis) induced by nanoparticles raised public health concerns and need to be rapidly assessed in hazard identification. Although in silico analysis is commonly used for risk assessment ...

Deep-Learning Potential Molecular Dynamics Study on Nanopolycrystalline Al-Er Alloys: Effects of Er Concentration, Grain Boundary Segregation, and Grain Size on Plastic Deformation.

Journal of chemical information and modeling
Understanding the tensile mechanical properties of Al-Er alloys at the atomic scale is essential, and molecular dynamics (MD) simulations offer valuable insights. However, these simulations are constrained by the unavailability of suitable interatomi...

Nanomaterial Innovations and Machine Learning in Gas Sensing Technologies for Real-Time Health Diagnostics.

ACS sensors
Breath sensors represent a frontier in noninvasive diagnostics, leveraging the detection of volatile organic compounds (VOCs) in exhaled breath for real-time health monitoring. This review highlights recent advancements in breath-sensing technologies...

Design and performance analysis of multi-enzyme activity-doped nanozymes assisted by machine learning.

Colloids and surfaces. B, Biointerfaces
Traditional design approaches for nanozymes typically rely on empirical methods and trial-and-error, which hampers systematic optimization of their structure and performance, thus limiting the efficiency of developing innovative nanozymes. This study...

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...

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...

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...