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Yunyue Zhu

Publications and source records attributed to Yunyue Zhu.

4 recordsLinked to original sources

Encapsulation epitaxy of air-stable monolayer superconducting films for quantum circuits and qubits

Two-dimensional (2D) superconductors are an emerging platform for strongly correlated physics and quantum information science. Their reduced dimensionality, atomically flat interfaces, and high crystallinity are attractive for realizing compact lumped-element devices in superconducting circuits. However, synthesizing large-area, monolayer 2D superconductors remains challenging because of their susceptibility to oxidation. Here, we report an "encapsulation epitaxy" mechanism that enables the growth of large-area, air-stable, monolayer superconducting NbSe2 films and explore their use in superconducting quantum circuits. A 2D encapsulation layer, such as graphene or hexagonal boron nitride (hBN), pre-deposited on a 3D substrate (e.g., SiO2 or Si3N4), serves both as a template for epitaxial growth of monolayer NbSe2 (1L-NbSe2) underneath it and as a protective cover. This approach produces uniform, large-area (>1-inch) 1L-NbSe2 with greatly enhanced ambient stability, enabling device fabrication in air. The resulting 1L-graphene/NbSe2 heterostructures exhibit robust superconductivity (Tc ~ 1 K) and enhanced charge density wave order (TCDW ~ 177 K), indicative of high material quality. We further integrate 1L-NbSe2 into superconducting circuits using oxidation-free transfer and superconducting edge-contact techniques. The 1L-NbSe2 exhibits a measured kinetic inductance LK ~ 0.7 nH/square, making it suitable for quantum circuits requiring high-kinetic-inductance elements. Encapsulation epitaxy thus provides a route to air-stable 2D superconductors and van der Waals heterostructures, with potential for wafer-scale, monolithic fabrication of superconducting quantum circuitry.

cond-mat.supr-con↗

Zero-shot Autonomous Microscopy for Scalable and Intelligent Characterization of 2D Materials

Characterization of atomic-scale materials traditionally requires human experts with months to years of specialized training. Even for trained human operators, accurate and reliable characterization remains challenging when examining newly discovered materials such as two-dimensional (2D) structures. This bottleneck drives demand for fully autonomous experimentation systems capable of comprehending research objectives without requiring large training datasets. In this work, we present ATOMIC (Autonomous Technology for Optical Microscopy & Intelligent Characterization), an end-to-end framework that integrates foundation models to enable fully autonomous, zero-shot characterization of 2D materials. Our system integrates the vision foundation model (i.e., Segment Anything Model), large language models (i.e., ChatGPT), unsupervised clustering, and topological analysis to automate microscope control, sample scanning, image segmentation, and intelligent analysis through prompt engineering, eliminating the need for additional training. When analyzing typical MoS2 samples, our approach achieves 99.7% segmentation accuracy for single layer identification, which is equivalent to that of human experts. In addition, the integrated model is able to detect grain boundary slits that are challenging to identify with human eyes. Furthermore, the system retains robust accuracy despite variable conditions including defocus, color temperature fluctuations, and exposure variations. It is applicable to a broad spectrum of common 2D materials-including graphene, MoS2, WSe2, SnSe-regardless of whether they were fabricated via chemical vapor deposition or mechanical exfoliation. This work represents the implementation of foundation models to achieve autonomous analysis, establishing a scalable and data-efficient characterization paradigm that fundamentally transforms the approach to nanoscale materials research.

cond-mat.mtrl-sci↗

Synthesis-related nanoscale defects in Mo-based Janus monolayers revealed by cross-correlated AFM and TERS imaging

Two-dimensional (2D) Janus transition metal dichalcogenides (TMDs) are promising candidates for various applications in non-linear optics, energy harvesting, and catalysis. These materials are usually synthesized via chemical conversion of pristine TMDs. Nanometer-scale characterization of the obtained Janus materials' morphology and local composition is crucial for both the synthesis optimization and the future device applications. In this work, we present a cross-correlated atomic force microscopy (AFM) and tip-enhanced Raman spectroscopy (TERS) study of Janus $\mathrm{Mo}_{\mathrm{Se}}^{\mathrm{S}}$ and Janus $\mathrm{Mo}_{\mathrm{S}}^{\mathrm{Se}}$ monolayers synthesized by the hydrogen plasma-assisted chemical conversion of $\mathrm{MoSe}_2$ and $\mathrm{MoS}_2$, respectively. We demonstrate how the choice of the growth substrate and the starting TMD affects the morphology of the resulting Janus material. Furthermore, by employing TERS imaging, we demonstrate the presence of nanoscale islands (~20 nm across) of $\mathrm{MoSe}_2$-$\mathrm{Mo}_{\mathrm{Se}}^{\mathrm{S}}$ ($\mathrm{MoS}_2$-$\mathrm{Mo}_{\mathrm{S}}^{\mathrm{Se}}$) vertical heterostructures originating from the bilayer nanoislands in the precursor monolayer crystals. The understanding of the origins of nanoscale defects in Janus TMDs revealed in our study can help with further optimization of the Janus conversion process towards uniform and wrinkle-/crack-free Janus materials. Moreover, our work shows that cross-correlated AFM and TERS imaging is a powerful and accessible method for studying nanoscale composition and defects in Janus TMD monolayers.

cond-mat.mtrl-sci↗

The Collinear Limit of the Four-Point Energy Correlator in $\mathcal{N} = 4$ Super Yang-Mills Theory

We present a compact formula, expressed in terms of classical polylogarithms up to weight three, for the leading order four-point energy correlator in maximally supersymmetric Yang-Mills theory, in the limit where the four detectors are collinear. This formula is derived by combining a simplified, manifestly dual conformal invariant form of the 1 -> 4 splitting function obtained from the square of the tree-level five-particle form factor of stress-tensor multiplet operators, with a novel integration-by-parts algorithm operating directly on Feynman parameter integrals. Our results provide valuable data for exploring the structure of physical observables in perturbation theory, and for calculations of jet substructure observables in quantum chromodynamics.

hep-th↗