The diagram illustrates the interplay among data acquisition, machine learning, and experiment synthesis. Physical models such as thermodynamics and kinetics can be integrated into ML models as expert ...

Researchers developed an AI model that guides material synthesis by predicting multiple viable production pathways.

MXenes are an emerging class of two-dimensional materials whose properties depend sensitively on the atoms bound to their surfaces. A new synthesis approach now allows researchers to control these ...

Recently, National Science Review published the research work on the synthesis of quantum dots (QDs) in the nucleus of live cells by Dr. Hu Yusi, Associate Professor Wang Zhi-Gang, and Professor Pang ...

DeepMind has shared the discovery of 2.2 million new crystals – equivalent to nearly 800 years’ worth of knowledge. They introduce Graph Networks for Materials Exploration (GNoME), a new deep learning ...

One of the ways industry makes inorganic materials is by mixing raw materials called precursor powders and placing them in an oven to start a reaction. The end products can include everything from ...

An international team of researchers has developed a breakthrough method for producing MXenes—an important family of ...

Researchers have successfully applied machine learning to guide the synthesis of new nanomaterials, eliminating barriers associated with materials discovery. The highly trained algorithm combed ...

A research team led by Prof. Yousung Jung of the Department of Chemical and Biological Engineering at Seoul National University (SNU) has developed an innovative AI-based technology that uses large ...

Scientists and institutions dedicate more resources each year to the discovery of novel materials to fuel the world. As natural resources diminish and the demand for higher value and advanced ...