Materials with advanced customized properties drive innovation in a number of real-life applications across various fields, such as information technology, transportation, green energy and health ...

The integration of machine learning techniques into microstructure design and the prediction of material properties has ushered in a transformative era for materials science. By leveraging advanced ...

Artificial Intelligence and its related tools, such as machine learning, deep learning, and neural networks, are revolutionizing every field of life. The domain of materials science and engineering is ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. Material science, at its core, is an interdisciplinary field focusing on the discovery and ...

A research group has developed an innovative machine learning technology that enables predictions beyond the distribution of training data and demonstrated its effectiveness in materials research. The ...

Scientists have used artificial intelligence (AI) to design never-before-seen nanomaterials with the strength of carbon steel and the lightness of styrofoam. The new nanomaterials, made using machine ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

Materials testing is critical in product development and manufacturing across various industries. It ensures that products can withstand tough conditions in their ...

The rapid evolution of quantum materials has opened new frontiers in next-generation electronics, energy storage, and quantum computing. However, their ...

From 11.5 million alloy candidates to AI-guided perovskites, this piece unpacks how materials informatics is speeding up ...

This paper comprehensively surveys existing works of chip design with ML algorithms from an algorithm perspective. To accomplish this goal, the authors propose a novel and systematical taxonomy for ...

When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...