Atom-thin sheets of carbon are finding applications not just in consumer electronics, but cars, concrete, and brain implants

Twenty years since its discovery, the journey to reach graphene’s true potential is still underway

Nature Communications - Hybrid density functionals are crucial for accurate materials calculations, yet their application is limited by the computational cost. Here, authors overcome this...

Nature Physics - The 2024 Nobel prize for Physics was awarded for foundational contributions to the development of artificial neural networks. The award reflects a shift in how we understand...

Researchers at the Schulich Faculty of Chemistry at the Technion have developed a new chemical process to produce raw materials for the manufacture of polymers, pharmaceuticals, and agricultural compounds.

Carbon nanotubes (CNTs) have emerged as one of the most capable and interesting materials in recent decades and have extraordinary mechanical properties (MPs) and resourceful applications in bioengineering and medicine. Equilibrium molecular dynamics simulations…

Nature Synthesis - The emergence of high-entropy materials affords opportunities to harmonize precision and disorder for materials design. This Review highlights the synthesis principles and...

Controlling matter at the atomic level has taken a major step forward, thanks to nanotechnology research by an international team of scientists led by physicists at the University of Bath.

Nature Machine Intelligence - Recurrent neural networks are efficient and capable agents for discovering new peptides with strong self-organizing capabilities.

Nature Electronics - Multiscale thermal modelling with AI

Nature - These scientists are bringing fresh perspectives to solving the world’s big challenges in materials.

Nature - All these nations are making a splash with their Nature Index research output in the field.

MIT physicists and colleagues have for the first time measured the geometry, or shape, of electrons in solids at the quantum level. Scientists have long known how to measure the energies and velocities ...

An international team of scientists has used machine learning to help them develop perovskite solar cells with near-record efficiency. In their paper published in the journal Science, the group describes ...