Machine learning guides carbon nanotechnology

Carbon nanostructures could become easier to design and synthesize thanks to a machine learning method that predicts how they grow on metal surfaces. The new approach, developed by researchers at Japan's Tohoku University ...

Chiral detection of biomolecules based on reinforcement learning

As one of the basic physical properties, chirality plays an important role in many fields. Especially in biomedical chemistry, the discrimination of enantiomers is a very important research subject. Most biomolecules exhibit ...

Scientists have grown custom-shaped nanoparticles

Physicists at Ural Federal University (UrFU) and their colleagues from the Institute of Electrophysics, Ural Branch of the Russian Academy of Sciences, and the Institute of Ion Plasma and Laser Technologies, Academy of Sciences ...

Strain-induced isomerization of molecular chains

National University of Singapore scientists have demonstrated a strain-induced structural rearrangement of one-dimensional (1D) metal-organic molecular chains for potential use in fabricating functional nanostructures.

Metal-organic framework nanoribbons

The nanostructure of metal-organic frameworks (MOFs) plays an important role in various applications since different nanostructures usually exhibit different properties and functions. In this work, the authors reported the ...

Heterophase nanostructures contributing to efficient catalysis

Selective catalysis plays a key role in various applications, such as the chemical industry and oil refining, hence, developing catalysts with high efficiency and excellent chemoselectivity has become a research hotspot. ...

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