AIMC Topic: Nanostructures

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Rational Design Strategies for Nanozymes.

ACS nano
Nanozymes constitute an emerging class of nanomaterials with enzyme-like characteristics. Over the past 15 years, more than 1200 nanozymes have been developed, and they have demonstrated promising potentials in broad applications. With the diversific...

Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation.

Chemical reviews
Decades of nanotoxicology research have generated extensive and diverse data sets. However, data is not equal to information. The question is how to extract critical information buried in vast data streams. Here we show that artificial intelligence (...

Modular reconfiguration of DNA origami assemblies using tile displacement.

Science robotics
The power of natural evolution lies in the adaptability of biological organisms but is constrained by the time scale of genetics and reproduction. Engineeringartificial molecular machines should not only include adaptability as a core feature but als...

Top-down design of protein architectures with reinforcement learning.

Science (New York, N.Y.)
As a result of evolutionary selection, the subunits of naturally occurring protein assemblies often fit together with substantial shape complementarity to generate architectures optimal for function in a manner not achievable by current design approa...

Prediction and Control in DNA Nanotechnology.

ACS applied bio materials
DNA nanotechnology is a rapidly developing field that uses DNA as a building material for nanoscale structures. Key to the field's development has been the ability to accurately describe the behavior of DNA nanostructures using simulations and other ...

Artificial intelligence and machine learning disciplines with the potential to improve the nanotoxicology and nanomedicine fields: a comprehensive review.

Archives of toxicology
The use of nanomaterials in medicine depends largely on nanotoxicological evaluation in order to ensure safe application on living organisms. Artificial intelligence (AI) and machine learning (MI) can be used to analyze and interpret large amounts of...

Quantitative Prediction of Inorganic Nanomaterial Cellular Toxicity via Machine Learning.

Small (Weinheim an der Bergstrasse, Germany)
Organic chemistry has seen colossal progress due to machine learning (ML). However, the translation of artificial intelligence (AI) into materials science is challenging, where biological behavior prediction becomes even more complicated. Nanotoxicit...

DNA Origami Nanostructure Detection and Yield Estimation Using Deep Learning.

ACS synthetic biology
DNA origami is a milestone in DNA nanotechnology. It is robust and efficient in constructing arbitrary two- and three-dimensional nanostructures. The shape and size of origami structures vary. To characterize them, an atomic force microscope, a trans...

A comprehensive deep learning method for empirical spectral prediction and its quantitative validation of nano-structured dimers.

Scientific reports
Nanophotonics exploits the best of photonics and nanotechnology which has transformed optics in recent years by allowing subwavelength structures to enhance light-matter interactions. Despite these breakthroughs, design, fabrication, and characteriza...