Collaboration pairs PerkinElmer's ICP-MS/MS and LC-MS/MS technologies with Covalent's failure analysis expertise to help manufacturers pinpoint the root causes of material failure and performance ...

Lawrence Livermore National Laboratory (LLNL) scientists have developed a new approach that can rapidly predict the structure and chemical composition of heterogeneous materials. In a new study in ...

Before any medical materials testing program can begin in earnest, there must be a well-conceived plan for understanding the composition of a medical device material and its potential for an adverse ...

As global energy storage demand grows, the need for safer, more powerful, and longer-lasting batteries is rising. The key to battery performance, safety, and longevity lies in the materials used. From ...

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 ...

Nanomaterials are used in various fields due to their distinct size-dependent properties, and accurate characterization is essential to optimize and design them for specific applications. 1 For ...

Traditionally, analyzing materials involved techniques tailored for specific scales, which made integrating data from these different methods quite challenging. However, recent advancements in ...

The objective of this course is to develop broad knowledge of the most commonly used techniques for characterizing soft and hard materials, with a strong focus on microscopy techniques. This is a ...

An introductory course focused on the new and existing materials that are crucial for mitigating worldwide anthropogenic CO2 emissions and associated greenhouse gases. Emphasis will be placed on how ...