As product development teams face increasingly complex challenges — including the need for greater sustainability — there’s a growing awareness of the critical contributions made by materials. Many of ...
Together with colleagues from Heidelberg University and Karlsruhe Institute of Technology (KIT), HITS researchers are addressing challenges in the simulation of biomolecules and molecular materials by ...
A new technical paper titled “Multiscale Simulation and Machine Learning Facilitated Design of Two-Dimensional Nanomaterials-Based Tunnel Field-Effect Transistors: A Review” was published by ...
An illustration of the machine learning model framework, showing its application in predicting the electro-mechanical behavior of CNTs/PDMS composites. As featured in National Science Open, the ...
The arrangement of electrons in matter, known as the electronic structure, plays a crucial role in fundamental but also applied research such as drug design and energy storage. However, the lack of a ...
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 ...
Materials testing is critical in product development and manufacturing across various industries. It ensures that products can withstand tough conditions in their ...
Machine learning, with its ability to analyze large datasets and identify patterns, is particularly well-suited to address the challenges presented by the vast and complex data generated in ...
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