13 citations · 29 across the 10 of their papers we have counts for
10 papers
A Priori Sampling of Transition States with Guided Diffusion
Hyukjun Lim, Soojung Yang, Lucas Pinède +3
Transition states, the first-order saddle points on the potential energy surfaces, govern the kinetics and mechanisms of chemical reactions and conformational changes. Locating the…
Accelerating Scientific Discovery with Autonomous Goal-evolving Agents
Yuanqi Du, Botao Yu, Tianyu Liu +25
There has been unprecedented interest in developing agents that expand the boundary of scientific discovery, primarily by optimizing quantitative objective functions specified by s…
The Rise of Generative AI for Metal-Organic Framework Design and Synthesis
Chenru Duan, Aditya Nandy, Shyam Chand Pal +17
Advances in generative artificial intelligence are transforming how metal-organic frameworks (MOFs) are designed and discovered. This Perspective introduces the shift from laboriou…
Building-Block Aware Generative Modeling for 3D Crystals of Metal Organic Frameworks
Chenru Duan, Aditya Nandy, Sizhan Liu +5
Metal-organic frameworks (MOFs) marry inorganic nodes, organic edges, and topological nets into programmable porous crystals, yet their astronomical design space defies brute-force…
MatLLMSearch: Crystal Structure Discovery with Evolution-Guided Large Language Models
Jingru Gan, Peichen Zhong, Yuanqi Du +7
Crystal structure generation is fundamental to materials science, enabling the discovery of novel materials with desired properties. While existing approaches leverage Large Langua…
AlphaNet: Scaling Up Local-frame-based Atomistic Interatomic Potential
Bangchen Yin, Jiaao Wang, Weitao Du +9
Molecular dynamics simulations demand an unprecedented combination of accuracy and scalability to tackle grand challenges in catalysis and materials design. To bridge this gap, we…
Generative Design of Functional Metal Complexes Utilizing the Internal Knowledge of Large Language Models
Jieyu Lu, Zhangde Song, Qiyuan Zhao +4
Designing functional transition metal complexes (TMCs) faces challenges due to the vast search space of metals and ligands, requiring efficient optimization strategies. Traditional…
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
Yuanqi Du, Michael Plainer, Rob Brekelmans +5
Rare event sampling in dynamical systems is a fundamental problem arising in the natural sciences, which poses significant computational challenges due to an exponentially large sp…
Navigating Chemical Space with Latent Flows
Guanghao Wei, Yining Huang, Chenru Duan +2
Recent progress of deep generative models in the vision and language domain has stimulated significant interest in more structured data generation such as molecules. However, beyon…
React-OT: Optimal Transport for Generating Transition State in Chemical Reactions
Chenru Duan, Guan-Horng Liu, Yuanqi Du +6
Transition states (TSs) are transient structures that are key in understanding reaction mechanisms and designing catalysts but challenging to be captured in experiments. Alternativ…