News & features
![The image features a complex network of interconnected nodes with a molecular structure, illuminated in blue against a dark background.](https://www.microsoft.com/en-us/research/uploads/prodnew/2024/05/NEWMatterSim2024-BlogHeroFeature-1400x788-1-480x280.png)
MatterSim: A deep-learning model for materials under real-world conditions
| Han Yang, Jielan Li, Hongxia Hao, and Ziheng Lu
Property prediction for materials under realistic conditions has been a long-standing challenge within the digital transformation of materials design. MatterSim investigates atomic interactions from the very fundamental principles of quantum mechanics.
![A schematic diagram illustrating the goal of Distributional Graphormer (DiG). A molecular system is represented by a basic descriptor D, such as the amino acid sequence for a protein. DiG transforms D into a structural ensemble S, which consists of multiple possible conformations and their probabilities. S is expected to follow the equilibrium distribution of the molecular system. A legend shows a example of D and S for Adenylate kinase protein.](https://www.microsoft.com/en-us/research/uploads/prod/2023/06/DiG-msr-blog-hero-1400x788-1-480x280.png)
Distributional Graphormer: Toward equilibrium distribution prediction for molecular systems
| Shuxin Zheng, Chang Liu, Yu Shi, Ziheng Lu, Fusong Ju, Jianwei Zhu, Hongxia Hao, Peiran Jin, Frank Noé, Haiguang Liu, and Tie-Yan Liu
Distributional Graphormer, Microsoft’s new deep learning framework for predicting the equilibrium distribution of molecular structures, can generate realistic and diverse molecular structures with high efficiency and low cost.
![climate research - photo of a man taking a photo of the Northern Lights](https://www.microsoft.com/en-us/research/uploads/prod/2022/06/MCRI-environment-northern-lights_1400x788-480x280.jpg)
Introducing the Microsoft Climate Research Initiative
Addressing and mitigating the effects of climate change requires a collective effort, bringing our strengths to bear across industry, government, academia, and civil society.