Highlights with ‘machine learning’

Discuss your Battery Research & Development at InterBattery Korea

The Dutch embassy in Korea hosts a stand at InterBattery (B401, Hall B COEX) where Fedor will represent SCM and will be happy to discuss how atomistic and multiscale simulations can help you understand battery...

Discuss your Materials Research Challenges at TMS2024

Come and talk about your materials challenges with Nicolas at the TMS meeting in Orlando. He would be happy to discuss how simulations could accelerate your discovery of new materials or optimize your processes. Exhibit...

Concentration dependent Li migration barriers in LiTiS2 with M3GNET (video tip of the week)

In this video tip of the week we take a look at Li migration barriers inside a crystal structure with the fast and accuratue M3GNET machine learning potential. The video is based on a new...

Discuss your Materials Research Challenges at the MRS Fall Meeting

Come and talk about your materials challenges with Fedor and Nicolas at the MRS while enjoying a Dutch caramel waffle, stroopwafel, at booth 719 at the MRS exhibition. We love to discuss how we can...

Li ion reduction at the graphene surface with eReaxFF (video tip of the week)

In this video tip of the week we use eReaxFF to simulate the dynamics of explicit Li ion reduction at a graphene surface. These state-of-the-art simulations bring us a step closer to modeling an entire...

Fast and accurate Li intercalation potentials in layered cathodes with machine learning potentials (video tip of the week)

In this video tip of the week, Ole demonstrates how the machine learning potential M3GNET can be used to screen layered cathode materials for their Li intercalation potentials, fast and accurate. The input files for...

ChemAI: Entering the fifth paradigm for chemistry, 16 November 2023

Find out how AI is transforming chemical discovery: join the ChemAI event organized by the Amsterdam Chemical Network in Amsterdam on 16 November. Discuss with Maria, Matti or Paul how we can help you accelerate...

White Paper & Webinar: Combining machine learning with physics and chemistry models to accelerate materials R&D

The utilization of machine learning and artificial intelligence is currently playing a pivotal role in accelerating research in the fields of chemistry and materials. It is straightforward to generate quantum chemistry inspired descriptors for a...

Discuss your materials discovery challenges at TechConnect World 19-21 June

At the TechConnect World meeting in Washington, Nicolas will discuss how to accelerate the computational design of materials and processes with machine learning, discussing applications for batteries, catalysis, and OLEDs. He’ll be happy to learn...

Fast and accurate prediction of Kevlar’s mechanical properties via ANI-2X Machine Learning Potential (video tip of the week)

In this video tip of the week Ole shows how to use the ANI-2x machine learning potential to calculate the Elastic Tensor and mechanical properties of Kevlar. The input file for the calculation is available...