AIMC Topic: Nanofibers

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Ultralow-resistance and self-sterilization biodegradable nanofibrous membranes for efficient PM removal and machine learning-assisted health management.

Journal of hazardous materials
The development of multifunctional nanofibrous membranes (NFMs) that enable anti-viral protection during air purification and respiratory disease diagnosis for health management is of increasing importance. Herein, we unraveled a heterostructure-enha...

Interfacial Polarization Strategy to Electroactive Poly(lactic acid) Nanofibers for Humidity-Resistant Respiratory Protection and Machine Learning-Assisted Monitoring.

ACS applied materials & interfaces
The advancement of intelligent and biodegradable respiratory protection equipment is pivotal in the realm of human health engineering. Despite significant progress, achieving a balance between efficient filtration and intelligent monitoring remains a...

Machine learning powered CN-coordinated cobalt nanoparticles embedded cellulosic nanofibers to assess meat quality via clenbuterol monitoring.

Biosensors & bioelectronics
The World Anti-Doping Agency (WADA) has prohibited the use of clenbuterol (CLN) because it induces anabolic muscle growth while potentially causing adverse effects such as palpitations, anxiety, and muscle tremors. Thus, it is vital to assess meat qu...

Deep Learning-Assisted Colorimetric/Electrical Dual-Sensing System for Ultrafast Detection of Hydrogen Sulfide.

ACS sensors
This study presents a colorimetric/electrical dual-sensing system (CEDS) for low-power, high-precision, adaptable, and real-time detection of hydrogen sulfide (HS) gas. The lead acetate/poly(vinyl alcohol) (Pb(Ac)/PVA) nanofiber film was transferred ...

All-Fabric Capacitive Pressure Sensors with Piezoelectric Nanofibers for Wearable Electronics and Robotic Sensing.

ACS applied materials & interfaces
Flexible pressure sensors are increasingly sought after for applications ranging from physiological signal monitoring to robotic sensing; however, the challenges associated with fabricating highly sensitive, comfortable, and cost-effective sensors re...

Generation of Interconnected Neural Clusters in Multiscale Scaffolds from Human-Induced Pluripotent Stem Cells.

ACS applied materials & interfaces
The development of in vitro neural networks depends to a large extent on the scaffold properties, including the scaffold stiffness, porosity, and dimensionality. Herein, we developed a method to generate interconnected neural clusters in a multiscale...

Highly Efficient, Transparent, and Multifunctional Air Filters Using Self-Assembled 2D Nanoarchitectured Fibrous Networks.

ACS nano
Particulate matter (PM) pollution is a significant burden on global economies and public health. Most present air filters are heavy, bulky, and nontransparent and typically have inevitable compromise between removal efficiency and air permeability. W...

Deep learning for high-throughput quantification of oligodendrocyte ensheathment at single-cell resolution.

Communications biology
High-throughput quantification of oligodendrocyte myelination is a challenge that, if addressed, would facilitate the development of therapeutics to promote myelin protection and repair. Here, we established a high-throughput method to assess oligode...

Employing AgNPs doped amidoxime-modified polyacrylonitrile (PAN-oxime) nanofibers for target induced strand displacement-based electrochemical aptasensing of CA125 in ovarian cancer patients.

Materials science & engineering. C, Materials for biological applications
In this study, a high-performance biosensing nanoplatform based on amidoxime-modified polyacrylonitrile nanofibers decorated with Ag nanoparticles (AgNPs-PAN-oxime NFs) is described. The AgNPs-PAN-oxime NFs were prepared by the combination of electro...

Evaluation of the computational capabilities of a memristive random network (MN) under the context of reservoir computing.

Neural networks : the official journal of the International Neural Network Society
This work presents the simulation results of a novel recurrent, memristive neuromorphic architecture, the MN and explores its computational capabilities in the performance of a temporal pattern recognition task by considering the principles of the re...