A method to interpret artificial intelligence (AI) models used in materials discovery by analyzing their learned features has been developed by researchers from Japan. The method extracts key features ...

Cornell researchers are demonstrating how artificial intelligence—particularly deep learning and generative modeling—can accelerate the design of new molecules and materials, and even function as an ...

The advent of large language models (LLMs) has started to reshape many technology development efforts and research roadmaps. Apart from transforming the space of natural language processing, LLMs have ...

(a) A feasible route for developing large materials models capable of describing the structure-property relationship of materials. The universal materials model of DeepH accepts an arbitrary material ...

Tokyo, Japan – Discovering new inorganic materials is central to advancing technologies in catalysis, energy storage, semiconductors, and more. But finding a material with just the right properties is ...

The discovery and simulation of inorganic materials is core to diverse applications from climate change to semiconductor manufacturing. Artificial intelligence has the potential to dramatically ...

People have always looked for patterns to explain the universe and to predict the future. “Red sky at night, sailor’s delight. Red sky in morning, sailor’s warning” is an adage predicting the weather.

For the past couple of years, innovation has been accelerating in new materials development. And a new French startup called Altrove plans to play a role in this innovation cycle. The deep tech ...

Companies working at the frontier of aerospace, energy and computing are constantly looking for new materials to improve performance. But in order to understand how those materials will actually ...