Material informatics

By leveraging the power of artificial intelligence, machine learning, and data-driven approaches, the discovery, design, and optimization of new materials can be accelerated. This emerging field holds tremendous potential to revolutionize materials research and drive innovation across various industries, from electronics and energy to healthcare and beyond. At Qmat, we develop new deep-learning models for various applications, enabling us to predict outputs with high accuracy. Additionally, we work on machine-learning-based molecular dynamics, allowing us to perform time-evolution simulations for large systems and extended simulation times while preserving the accuracy of first-principles methods. Our cutting-edge approaches in material informatics empower us to unlock new possibilities in materials science and contribute to groundbreaking advancements in diverse fields.