AIMC Topic: Nanostructures

Clear Filters Showing 111 to 120 of 162 articles

Machine learning predictions of concentration-specific aggregate hazard scores of inorganic nanomaterials in embryonic zebrafish.

Nanotoxicology
The possibility of employing computational approaches like nano-QSAR or nano-read-across to predict nanomaterial hazard is attractive from both a financial, and most importantly, where in vivo tests are required, ethical perspective. In the present w...

Self-assembled Janus plasmene nanosheets as flexible 2D photocatalysts.

Materials horizons
A leaf is a free-standing photocatalytic system that can effectively harvest solar energy and convert CO and HO into carbohydrates in a continuous manner without the need for regeneration or tedious product extraction steps. Despite encouraging advan...

Knowledge gaps in immune response and immunotherapy involving nanomaterials: Databases and artificial intelligence for material design.

Biomaterials
Exploring the interactions between the immune system and nanomaterials (NMs) is critical for designing effective and safe NMs, but large knowledge gaps remain to be filled prior to clinical applications (e.g., immunotherapy). The lack of databases on...

Robotic DNA Nanostructures.

ACS synthetic biology
Over the past decade, DNA nanotechnology has spawned a broad variety of functional nanostructures tailored toward the enabled state at which applications are coming increasingly in view. One of the branches of these applications is in synthetic biolo...

Development of Deep Learning Models for Predicting the Effects of Exposure to Engineered Nanomaterials on Daphnia magna.

Small (Weinheim an der Bergstrasse, Germany)
This study presents the results of applying deep learning methodologies within the ecotoxicology field, with the objective of training predictive models that can support hazard assessment and eventually the design of safer engineered nanomaterials (E...

Magnetic Elements for Neuromorphic Computing.

Molecules (Basel, Switzerland)
Neuromorphic computing is assumed to be significantly more energy efficient than, and at the same time expected to outperform, conventional computers in several applications, such as data classification, since it overcomes the so-called von Neumann b...

Neuromorphic nanoelectronic materials.

Nature nanotechnology
Memristive and nanoionic devices have recently emerged as leading candidates for neuromorphic computing architectures. While top-down fabrication based on conventional bulk materials has enabled many early neuromorphic devices and circuits, bottom-up...

3D nanostructural characterisation of grain boundaries in atom probe data utilising machine learning methods.

PloS one
Boosting is a family of supervised learning algorithm that convert a set of weak learners into a single strong one. It is popular in the field of object tracking, where its main purpose is to extract the position, motion, and trajectory from various ...

Multifunctional Nanorobot System for Active Therapeutic Delivery and Synergistic Chemo-photothermal Therapy.

Nano letters
Nanorobots are safe and exhibit powerful functionalities, including delivery, therapy, and diagnosis. Therefore, they are in high demand for the development of new cancer therapies. Although many studies have contributed to the progressive developmen...

Cloisite Microrobots as Self-Propelling Cleaners for Fast and Efficient Removal of Improvised Organophosphate Nerve Agents.

ACS applied materials & interfaces
Naturally available microclays are well-known materials with great adsorption capabilities that are available in nature in megatons quantities. On the contrary, artificial nanostructures are often available at high cost via precision manufacturing. S...