ECTS: An ultra-fast diffusion model for exploring chemical reactions with equivariant consistency

Unveiling reaction mechanisms through the exploration of reaction paths, including identification of transition states (TS), prediction of reaction energy barriers (), and mapping of reaction pathways, is crucial for the study of chemical reactions. However, this process usually requires extensive and computationally demanding quantum chemistry calculations. Here, we propose an equivariant consistency generative model ECTS, an ultra-fast diffusion method that unifies TS generation, energy prediction, and pathway search within one framework. Our results highlight that the efficiency of ECTS is at least two orders of magnitude higher than conventional diffusion models. TS structures generated by ECTS exhibit an error margin of just 0.12 Å root mean square deviation compared to the ground truth. Additionally, by continuously refining the energy barrier predictions in the denoising process, ECTS achieves a median error of merely 2.4 kcal/mol without any post-DFT calculations. Moreover, as a novel feature, ECTS can also generate reaction paths which are in general agreement with the true reaction paths, indicating ECTS could potentially be useful for exploring reaction mechanisms.