Workflow behind the MPT model. In this approach, the model learns from various material properties simultaneously in an initial training phase, followed by fine-tuning on the target property data.

If large-scale datasets of experimental data can be built through this approach, it is expected to enable researchers to gain ...

A massive new database of dielectric material properties could speed up the development of electronics like smartphones and energy storage systems. AI-driven materials discovery has great potential to ...

In response to numerous inquiries from academia, industry, and other government labs, the National Institute of Standards and Technology (NIST) recently published a new database on the properties of ...

Nanoengineers have developed an AI algorithm that predicts the structure and dynamic properties of any material -- whether existing or new -- almost instantaneously. Known as M3GNet, the algorithm was ...

Compared to metals such as aluminum and steel, the number of stiffness and strength properties associated with polymer matrix composites (PMCs) is extensive. For metals, these mechanical properties ...

How many free websites do you have to visit to find materials data from 50 of the world's biggest plastics suppliers? Just one, thanks to a new web-enabled version of the CAMPUS material property ...

This is a particular problem for smaller aircraft manufacturers who have neither the budget to develop the required databases, nor access to those generated by larger organizations, often in support ...