Advancements in Machine Learning for Materials Science Machine learning (ML) is really shaking things up in materials ...

Machine learning (ML) enables the accurate and efficient computation of fundamental electronic properties of binary and ternary oxide surfaces, as shown by scientists from Tokyo Tech. Their ML-based ...

Material science, at its core, is an interdisciplinary field focusing on the discovery and design of new materials. It combines elements of physics, chemistry and engineering to understand and ...

Conventional clustering techniques often focus on basic features like crystal structure and elemental composition, neglecting target properties such as band gaps and dielectric constants. A new study ...

Tungsten's superior performance in extreme environments makes it a leading candidate for plasma-facing components (PFCs) in ...

The chapters of “Machine Learning Methods for Engineering Application Development“ book are organized into five parts Machine Learning Essentials, Applied Machine Learning, Surveillance Systems, ...

An integrated framework combining first-principles calculations and machine learning was developed to predict gas-sensing performance. Key descriptors such as adsorption energy, adsorption distance, ...

Artificial Intelligence (AI) has become a buzzword in today’s tech-driven world, promising new possibilities and reshaping industries. Despite its prevalence, there is often confusion surrounding the ...