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Articles by Mao Su
U‐Shaped Relationship Between CT‐Measured Liver‐To‐Spleen Volume Ratio and Mortality in HBV‐ACLF Patients
1 Introduction Acute-on-chronic liver failure (ACLF) has been recognised as a complex syndrome that is associated with a high short-term mortality rate. The only definitive and effective treatment is liver transplantation, which could not be widely used due to the lack of donor livers and the high cost in China. Early diagnosis and early determination of the prognosis are critical to guide clinical management and decrease the high mortality rate.
Online test-time adaptation for better generalization of interatomic potentials to out-of-distribution data - Nature Communications
Abstract Machine learning interatomic potentials (MLIPs) enable more efficient molecular dynamics (MD) simulations with ab initio accuracy, which have been used in various domains of physical science. However, distribution shift between training and test data causes deterioration of the test performance of MLIPs, and even leads to collapse of MD simulations. In this work, we propose an online Test-time Adaptation Interatomic Potential (TAIP) framework to improve the generalization on test data.
Geometry-enhanced pretraining on interatomic potentials - Nature Machine Intelligence
Abstract Machine learning interatomic potentials (MLIPs) describe the interactions between atoms in materials and molecules by learning them from a reference database generated by ab initio calculations. MLIPs can accurately and efficiently predict such interactions and have been applied to various fields of physical science. However, high-performance MLIPs rely on a large amount of labelled data, which are costly to obtain by ab initio calculations.
Transferable equivariant graph neural networks for the Hamiltonians of molecules and solids - npj Computational Materials
Abstract This work presents an E(3) equivariant graph neural network called HamGNN, which can fit the electronic Hamiltonian matrix of molecules and solids by a complete data-driven method. Unlike invariant models that achieve equivariance approximately through data augmentation, HamGNN employs E(3) equivariant convolutions to construct the Hamiltonian matrix, ensuring strict adherence to all equivariant constraints inherent in the physical system.
Atomic origins of water-vapour-promoted alloy oxidation
The presence of water vapour, intentional or unavoidable, is crucial to many materials applications, such as in steam generators, turbine engines, fuel cells, catalysts and corrosion1,2,3,4. Phenomenologically, water vapour has been noted to accelerate oxidation of metals and alloys5,6. However, the atomistic mechanisms behind such oxidation remain elusive.
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