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Researchers have improved the optical properties of the 2D material molybdenum disulphide by removing defects with laser light and water.
Scientists have not only visualized the nanoscale structures of borophene lattices, but also built theoretical models of their crystalline forms.
Researchers have synthesized tiny, individual, flexible phosphorene nanoribbons from crystals of black phosphorous and lithium ions.
Scientists have developed a novel 3D printing process for fabricating flexible conducting fibers on textiles, which can be used to harvest energy.
Scientists have theorized a new ‘oil-and-vinegar’ approach for inducing spherical nanoparticles to self-assemble into unusual architectures.
Researchers have developed a wood membrane than can generate an ionic voltage from a small temperature differential.
Researchers have used machine learning to create molecular models for faster screening of materials such as organic electronics.
Researchers have found a layered material made from sodium, tin and arsenic that can act as both an electron-holder and a hole-holder.
Researchers have found that thin layers of niobium arsenide, a Weyl semimetal, have three times the conductivity of copper at room temperature.
Researchers have discovered the strongest topological conductor yet, in the form of thin crystal samples with a spiral-staircase structure.
fast-screening of potential non-noble metal two-dimensional catalysts for hydrogen evolution reaction
Hydrogen from seawater without decay or delay
Sandwiching a layer of graphene between two layers of 2D boron nitride can produce superlattices that confer novel electrical properties.
Scientists have used a new technique called ultrafast surface X-ray scattering to visualize the motion of atoms in a 2D material.
Physicists have discovered that placing 2D semiconductors on top of each other and twisting them causes the emergence of novel hybrid properties.
The twist angle between layers of 2D semiconductors provides a ‘tuning knob’ to turn them into an exotic quantum material.
By combining supercomputing with experimental methods, researchers have been able to identify promising materials for dye-sensitized solar cells
Researchers used machine learning to simulate the quantum mechanics analysis of two capacitor materials, greatly speeding up the process.
Researchers have developed a blueprint for understanding and predicting the properties and behavior of nanoparticles containing multiple elements.
We welcome you to the sixth international biennial ‘Nanomaterials and Nanotechnology Meeting’ in Ostrava.