3 papers
physics.chem-ph2025
SynTwins: A Retrosynthesis-Guided Framework for Synthesizable Molecular Analog Generation
Shuan Chen, Gunwook Nam, Alan Aspuru-Guzik +1
The disconnect between AI-generated molecules with desirable properties and their synthetic feasibility remains a critical bottleneck in computational discovery of drugs and materi…
cond-mat.mtrl-sci2025
Integrating electronic structure into generative modeling of inorganic materials
Junkil Park, Junyoung Choi, Yousung Jung
Recent advances in generative models have introduced a new paradigm for the inverse design of inorganic materials, enabling the discovery of new crystalline structures with desired…
physics.chem-ph2025
Predicting Chemical Reaction Outcomes Based on Electron Movements Using Machine Learning
Shuan Chen, Kye Sung Park, Taewan Kim +2
Accurately predicting chemical reaction outcomes and potential byproducts is a fundamental task of modern chemistry, enabling the efficient design of synthetic pathways and driving…