The research group led by Prof. Xin Xu developed a general tensor output framework for equivariant graph neural networks, grounded in a fundamental group-theoretical principle: any Cartesian tensor with a given fundamental symmetry corresponds uniquely to a direct sum of irreducible representations of the rotation group. Leveraging this principle, the authors designed a universal output module—referred to as the node-wise self-mix layer—which concentrates symmetry handling at the output stage. This design enables equivariant graph neural networks to predict tensorial properties of arbitrary order and arbitrary fundamental symmetry in an end-to-end manner, and is applicable to atom-wise, molecular, and periodic crystalline systems alike.

Recently, the Second REST Program Workshop, hosted by the Center for Theoretical Chemistry at Fudan University, was successfully held. Experts, researchers, and students from various institutions gathered to exchange ideas on the theoretical foundations, software implementation, cutting-edge applications, and hands-on practice of the REST program. The workshop fostered in-depth discussions and collaboration, contributing to the advancement of high-precision computational chemistry methods.

    At 3:00 Beijing time on February 14, the research results of the collaborative team of Bo Zhang, Yifei Xu, Sai Duan and Xin Xu from Fudan University were published in the main issue of Science under the title of 'Ultrastable supported oxygen evolution electrocatalyst formed by ripening induced embedding' was published in the main issue of Science. Wenjuan Shi, a full-time associate researcher at the Department of …

Hybrid density functional methods such as B3LYP and PBE0 have been widely successful but often fail for systems with strong static correlation or significant self-interaction errors. In this work, Prof. Xin Xu’s group introduces a cross-entropy corrected hybrid multiconfiguration pair-density functional theory (HMC-PDFT), in which a cross-entropy term is used to approximate the wavefunction-based correlation energy and to balance static and dynamic correlation effects within a B3LYP-like hybridization scheme. The resulting functional, termed tB4LYP, consistently improves upon conventional MC-PDFT and its linear hybrid variants, achieving …

  Prof. Xin Xu and his research team, Prof. Igor Ying Zhang, Prof. Xiao Zheng and Dr. Sai Duan, were invited to attend the Long Feng Science Forum: Symposium on Frontiers of Theoretical Chemistry, and Prof. Igor Ying Zhang was invited to give an academic presentation.

  Prof. Xin Xu's research team hosted the 4th Symposium for Young Scholars on Chemical Theory and Mechanisms in Development.