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Titanium

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Machine learning-driven fluorescent sensor array using aqueous CsPbBr perovskite quantum dots for rapid detection and sterilization of foodborne pathogens.

Journal of hazardous materials
With the growing global concern over food safety, the rapid detection and disinfection of foodborne pathogens have become critical in public health. This study presents a novel machine learning-driven fluorescent sensor array utilizing aqueous CsPbBr...

Taming Prolonged Ionic Drift-Diffusion Dynamics for Brain-Inspired Computation.

Advanced materials (Deerfield Beach, Fla.)
Recent advances in neural network-based computing have enabled human-like information processing in areas such as image classification and voice recognition. However, many neural networks run on conventional computers that operate at GHz clock freque...

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...

Based on T.E.S.T toxicity prediction and machine learning to forecast toxicity dynamics in the photocatalytic degradation of tetracycline.

Physical chemistry chemical physics : PCCP
The integration of photocatalysis and biological treatment provides an effective strategy for controlling antibiotic contamination, which requires precise monitoring of toxicity changes during the photocatalytic process. In this study, nanoscale TiO ...

Quotient Complex (QC)-Based Machine Learning for 2D Hybrid Perovskite Design.

Journal of chemical information and modeling
With remarkable stability and exceptional optoelectronic properties, two-dimensional (2D) halide layered perovskites hold immense promise for revolutionizing photovoltaic technology. Effective data representations are key to the success of all learni...

Multifunctional Fiber Robotics with Low Mechanical Hysteresis for Magnetic Navigation and Inhaled Gas Sensing.

ACS sensors
Recently, increasing research attention has been directed toward detecting the distribution of hazardous gases in the respiratory system for potential diagnosis and treatment of lung injury. Among various technologies, magnetic fiber robots exhibit g...

Machine Learning Methodologies Applied to Magnetocaloric Perovskites Discovery.

Journal of chemical information and modeling
Traditionally, designing novel materials involves exploring new compositions guided by insights from previous work, relying on a trial-and-error approach, where continuous synthesis and characterization proceed until the properties meet the improveme...

Deep learning assisted prediction of osteogenic capability of orthopedic implant surfaces based on early cell morphology.

Acta biomaterialia
The surface modification of titanium (Ti) and its alloys is crucial for improving their osteogenic capability, as their bio-inert nature limits effective osseointegration despite their prevalent use in orthopedic implants. However, these modification...

Hierarchical Crack Engineering-Enabled High-Linearity and Ultrasensitive Strain Sensors.

ACS sensors
Growing imperative for intelligent transformation of electro-ionic actuators in soft robotics has necessitated self-perception for accurately mapping their nonlinear dynamic responses. Despite the promise of integrating crack-based strain sensors for...

Harnessing Transfer Deep Learning Framework for the Investigation of Transition Metal Perovskite Oxides with Advanced p-n Transformation Sensing Performance.

ACS sensors
Gas sensing materials based on transition metal perovskite oxides (TMPOs) have garnered extensive attention across various fields such as air quality control, environmental monitoring, healthcare, and national defense security. To overcome challenges...