Abstract
Suppressing critical current density (Jc) fluctuations in Josephson junctions is essential for improving the reproducibility and scalability of superconducting quantum processors. Despite many elucidations of microscopic mechanisms, the physical modulation of Jc by atomic-scale disorder at the metal-insulator interface remains elusive. Here, we reveal that interfacial bonding topology distortions are the dominant source that regulates Jc uniformity. We identify a new disorder metric, Interface Bonding Topology Factor (IBTF), that captures bond-angle fluctuations and oxygen-coordination heterogeneity within Jc variations. Through multivariate analysis, Jc is exponentially correlated with interface disorder and barrier thickness (d) by Jc ∝ e−IBTF⋅d, explaining 91.88% of the observed Jc inhomogeneity. We establish IBTF as a tunable physical degree of freedom whose suppression efficacy enhances significantly with increasing d, and demonstrate its active modulation by twin boundary engineering in electrodes. This work provides a device-oriented strategy and a tunable physical metric beyond single-feature control for scalable high-performance quantum processors.
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Acknowledgements
This work was supported by the Major Science and Technology Project of Henan Province (221100210400), and the Natural Science Foundation of Henan Province (222300420546). Computational resources were provided by the National Supercomputing Center in Zhengzhou. We thank Jianshe Liu, Wenlong Yu, Zhao Wang, and Dong Lan for their valuable insights and comments. We thank the School of Physics at Nanjing University for the nanofabrication. We thank the software services from Hzwtech.
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C.Han, H.S., and Z.S. conceived the study and planned the computational work. C.Han and J.Q. performed the first principles calculations, feature extraction, experimental characterization analysis, and machine-learning calculations with assistance from H.S., Y.S., and Z.S. H.S. and Y.S. characterized the sample. P.X., X.Y., W.W., S.W., Q.M., B.Y., L.W., and C.Hou advised on the machine learning method and interpretation of results. F.L., B.Z., and Z.S. supervised the study. All authors analyzed the data and contributed to reviewing and editing the manuscript and the Supplementary Information.
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Han, C., Sun, H., Shen, Y. et al. Revealing the role of interface disorder in modulating critical current density of Josephson junctions. npj Comput Mater (2026). https://doi.org/10.1038/s41524-025-01941-7
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DOI: https://doi.org/10.1038/s41524-025-01941-7
