Understanding materials properties is a strategic in addressing the challenges related to satisfying the requirements in the fields of energy transition, environmental compliance, and sustainable development. MAPS 4.,5, the new release of MAPS natively enables researchers to run virtual experimentations on a product’s digital twin and establish design rules utilizing the relationship between its performance and its chemical composition. MAPS 4.5 can be used to study and improve all types of materials and products, including polymers, electrolytes, catalysts, nanocomposites, and any complex fluid formulation in several industrial segments. MAPS 4.5 technology spans from the quantum and atomistic/mesoscopic scales up to the macroscopic and machine learning.
Combining individual tasks into virtual experiments and workflows can enable the researcher to work efficiently and concentrate on the scientific and product-related issues at hand, which result in massive time savings. In MAPS 4.5 such virtual experiments can be automatically created and executed efficiently. Moreover, several Machine Learning models have been integrated into MAPS to enable fast and reliable property prediction. All compute engines have been updated to their newest stable versions, and a new scheme has been implemented for the communication between the compute engines and MAPS.
The examples presented will demonstrate how to translate a real-life problem into a simulation workflow applied on the digital twin of the product of interest. In particular:
- Organic electrolyte for lithium-ion secondary batteries
- Development of coatings and ink materials
- Prediction of properties for polymers such as Tg, monomer diffusion, viscosity, thermal conductivity, mechanical properties etc.
- Dielectric properties of polymers
- Many others
Anyone interested in sustainable product development and virtual experimentation will benefit from this free webinar and Q&A session. We will be pleased to have you with us!
Register to our webinar