arXiv subjects

Yubin Zhang

Publications and source records attributed to Yubin Zhang.

15 recordsLinked to original sources

arXiv2026

Operando observation of strain relaxation in fatigued pearlitic steel

Pearlitic steels are the material of choice for railway wheels and rails, where their lamellar ferrite-cementite structure balances cost, strength, and wear resistance. However, in use, cyclic loading combined with frictional heat softens the steel, promoting fatigue and eventual failure. Here we use Dark-Field X-ray Microscopy (DFXM) to follow, operando, the grain-scale response of a fatigued pearlitic colony during annealing up to 550 °C. Orientation maps reveal negligible lattice rotation and no sub-cell formation, indicating that the cementite lamellae suppress long-range dislocation motion. Strain maps nonetheless show pronounced relaxation: the elastic strain spread narrows by nearly 40%, with recovery starting below 250 °C, within the operating temperatures of railway wheels. We attribute this relaxation to short-range annihilation of dislocations confined between lamellae, linking grain-scale strain recovery to the macroscopic softening of pearlitic railway steels in service.

cond-mat.mtrl-sci↗

arXiv2026

On stress-assisted boundary migration during recrystallization

This study investigates the boundary migration mechanisms near the sample surface of recrystallizing grains in high-purity Al subjected to cryogenic rolling. Local strain and stress tensors were characterized during \textit{in situ} annealing by combining high-resolution electron backscatter diffraction with microstructure-based digital image correlation strain analysis. The results reveal local residual strains on the order of $10^{-3}$ within the recrystallizing grain, with values several times higher in the adjacent deformed matrix. The residual stresses in recrystallizing grains are a passive response to those developed within the surrounding deformed grains; the latter being strongly influenced by the local geometry and characteristics of dislocation boundaries, as well as by constraints imposed by neighboring grains. No evidence of shear-coupled motion was observed during the recrystallization boundary migration, despite the presence of shear stress across the boundary. In contrast, detailed analysis of the principal strain components reveals a clear correlation between residual strain patterns and boundary migration directions. These findings indicate that recrystallization boundary migration is modulated by the anisotropy of the local internal stress state.

cond-mat.mtrl-sci↗

arXiv2026

3D Mapping of Intragranular Residual Strain and Microstructure in Recrystallized Iron Using Dark-Field X-ray Microscopy

Grain growth is a key process in the thermomechanical treatment of metals. Recently, the presence of local residual stresses within fully recrystallized grains has attracted increasing interest in connection with shear-coupled grain boundary migration mechanisms. In this work, we provide the first direct experimental measurements of residual elastic strain variations in fully recrystallized commercial-purity iron, on the order of $10^{-4}$. Using dark-field X-ray microscopy (DFXM), we performed non-destructive three-dimensional measurements of strain and orientation variations within individual grains. Our results reveal heterogeneous strain distributions across all measured grains. In one case, we observed several isolated dislocations accommodating two second-phase particles, exhibiting a localized strain signature with no detectable long-range effect. The formation mechanisms of intragranular residual strains and their potential influence on grain boundary migration during subsequent grain growth are discussed. This work highlights the importance of accounting for such residual elastic strains in future grain growth models.

cond-mat.mtrl-sci↗

arXiv2026

IDProxy: Cold-Start CTR Prediction for Ads and Recommendation at Xiaohongshu with Multimodal LLMs

Click-through rate (CTR) models in advertising and recommendation systems rely heavily on item ID embeddings, which struggle in item cold-start settings. We present IDProxy, a solution that leverages multimodal large language models (MLLMs) to generate proxy embeddings from rich content signals, enabling effective CTR prediction for new items without usage data. These proxies are explicitly aligned with the existing ID embedding space and are optimized end-to-end under CTR objectives together with the ranking model, allowing seamless integration into existing large-scale ranking pipelines. Offline experiments and online A/B tests demonstrate the effectiveness of IDProxy, which has been successfully deployed in both Content Feed and Display Ads features of Xiaohongshu's Explore Feed, serving hundreds of millions of users daily.

cs.IR↗

arXiv2026

Non-Invasive Diagnosis for Clubroot Using Terahertz Time-Domain Spectroscopy and Physics-Constrained Neural Networks

Clubroot, a major soilborne disease affecting canola and other cruciferous crops, is characterized by the development of large galls on the roots of susceptible hosts. In this study, we present the first application of terahertz time-domain spectroscopy (THz-TDS) as a non-invasive diagnosis tool in plant pathology. Compared with conventional molecular, spectroscopic, and immunoassay-based methods, THz-TDS offers distinct advantages, including non-contact, non-destructive, and preparation-free measurement, enabling rapid in situ screening of plant and soil samples. Our results demonstrate that THz-TDS can differentiate between healthy and clubroot-infected tissues by detecting both structural and biochemical alterations. Specifically, infected roots exhibit a blue shift in the refractive index in the low-frequency THz range, along with distinct peaks-indicative of disruptions in water transport and altered metabolic activity in both roots and leaves. Interestingly, the characteristic root swelling observed in infected plants reflects internal tissue disorganization rather than an actual increase in water content. Furthermore, a physics-constrained neural network is proposed to extract the main feature in THz-TDS. A comprehensive evaluation, including time-domain signals, amplitude and phase images, refractive index and absorption coefficient maps, and principal component analysis, provides enhanced contrast and spatial resolution compared to raw time-domain or frequency signals. These findings suggest that THz-TDS holds significant potential for early, non-destructive detection of plant diseases and may serve as a valuable tool to limit their spread in agricultural systems.

eess.IV↗

arXiv2025

Local mobility variations along recrystallization boundaries

Understanding recrystallization boundary migration mechanisms is crucial for materials design. However, the lack of comprehensive mobility data for high-angle grain boundaries in typical polycrystalline samples has impeded gaining insights into the factors that govern boundary migration. Here, we propose an Iterative Mobility Matching (IMM) methodology to determine local mobility values and their spatial variations along recrystallization boundaries in partially recrystallized samples. This method optimizes mobility inputs in a phase field model by matching simulated microstructures with time-series recrystallization experiments. We first validate this method using synthetic data before applying it to real experimental data. For the first time, we reveal a three-order-magnitude variation in local mobility along individual recrystallization boundaries. The results show that local mobility depends strongly on boundary misorientation, and its variation significantly influences boundary dynamics, shedding light on the interplay of factors that impact the observed boundary migration behavior. The IMM methodology offers a new framework for interpreting experimental recrystallization behavior and can be broadly applied to other materials using in situ experiments.

cond-mat.mtrl-sci↗

arXiv2025

Bridging Grain Mapping and Dark Field X-ray Microscopy for Multiscale Diffraction Imaging

Resolving how defects emerge and interact within the hierarchical structure of polycrystalline materials remains a core challenge in materials science. Grain-mapping methods such as three-dimensional X-ray diffraction (3DXRD) and diffraction contrast tomography (DCT) provide essential mesoscale context but lack the resolution to image lattice defects. Conversely, high-resolution methods like Dark Field X-ray Microscopy (DFXM) capture lattice distortions but not the surrounding microstructure. Here, we introduce a transferable framework that unifies these complementary approaches into a single, non-destructive workflow. Enabled by open-source software, the method translates grain orientation and position data into precise goniometer settings for DFXM imaging without dismounting or reorienting the sample. Applied to an iron polycrystal containing 1100 grains, DFXM motor positions were calculated for all grains within seconds, enabling on-the-fly targeting of specific grains. This allows reproducible zooming from the millimetre-scale aggregate to individual dislocations. We resolve three-dimensional misorientation fields across grain boundaries with 36 nm pixel size, directly capturing grain-grain interactions within their microstructural context. Finally, we show transferability from LabDCT to synchrotron and XFEL platforms, enabling new ways of studying defect interactions across scales.

physics.app-ph↗

arXiv2025

A Metric for MLLM Alignment in Large-scale Recommendation

Multimodal recommendation has emerged as a critical technique in modern recommender systems, leveraging content representations from advanced multimodal large language models (MLLMs). To ensure these representations are well-adapted, alignment with the recommender system is essential. However, evaluating the alignment of MLLMs for recommendation presents significant challenges due to three key issues: (1) static benchmarks are inaccurate because of the dynamism in real-world applications, (2) evaluations with online system, while accurate, are prohibitively expensive at scale, and (3) conventional metrics fail to provide actionable insights when learned representations underperform. To address these challenges, we propose the Leakage Impact Score (LIS), a novel metric for multimodal recommendation. Rather than directly assessing MLLMs, LIS efficiently measures the upper bound of preference data. We also share practical insights on deploying MLLMs with LIS in real-world scenarios. Online A/B tests on both Content Feed and Display Ads of Xiaohongshu's Explore Feed production demonstrate the effectiveness of our proposed method, showing significant improvements in user spent time and advertiser value.

cs.IR↗

arXiv2025

A high-temperature furnace for multi-modal synchrotron-based X-ray microscopy and diffraction imaging

The design, calibration, and initial application of a non-contact high-temperature furnace developed for in situ synchrotron X-ray experiments are presented. The system enables a stable operation up to 1000 °C, with heating rates exceeding 6000 °C/min and thermal stability better than {\pm}2 °C. Temperature calibration was performed using (i) direct measurements with a thermocouple to characterize heating and cooling ramp rates and map temperature gradients along the x, y, and z axes, and (ii) synchrotron X-ray diffraction to track the ferrite-to-austenite (BCC to FCC) phase transition in an iron grain under beamline conditions. The furnace's contactless geometry provides full translational and rotational freedom, with 360° rotation and wide tilt capabilities, making it fully compatible with a range of diffraction and imaging techniques. Its 3D-printed modular body includes closable apertures for auxiliary functions such as active cooling or X-ray fluorescence. The design is easily customizable for diverse experimental requirements and can be adapted to most beamlines. The furnace has been implemented at the ID03 beamline of the European Synchrotron Radiation Facility (ESRF) which supports Dark field X-ray Microscopy (DFXM), 3D X-ray Diffraction (3DXRD), magnified topotomography (MTT), phase-contrast tomography (PCT) and diffraction contrast tomography (DCT). As a first application, a DFXM case study on a cold-rolled Al1050 sample during isothermal annealing is presented. The imaging of a selected grain before and after the heat treatment reveals strain relaxation and grain growth. This furnace offers a robust and flexible platform for high-temperature synchrotron studies across materials science, including metals, ceramics, and energy materials. It is now part of the ESRF sample environment pool and is available to all users.

physics.ins-det↗

arXiv2025

A Low-Noise and High-Stability DC Source for Superconducting Quantum Circuits

With the rapid scaling of superconducting quantum processors, electronic control systems relying on commercial off-the-shelf instruments face critical bottlenecks in signal density, power consumption, and crosstalk mitigation. Here we present a custom dual-channel direct current (DC) source module (QPower) dedicated for large-scale superconducting quantum processors. The module delivers a voltage range of $\pm$7 V with 200 mA maximum current per channel, while achieving the following key performance benchmarks: noise spectral density of 20 nV/$\sqrt{\mathrm{Hz}}$ at 10 kHz, output ripple $<$500 $μ$V$_{\mathrm{pp}}$ within 20 MHz bandwidth, and long-term voltage drift $<$5 $μ$V$_{\mathrm{pp}}$ over 12 hours. Integrated into the control electronics of a 66-qubit quantum processor, QPower enables qubit coherence times of $T_1 = 87.6~μ\mathrm{s}$ and Ramsey $T_2 = 5.1~μ\mathrm{s}$, with qubit resonance frequency drift constrained to $\pm$40 kHz during 12-hour operation. This modular design is compact in size and efficient in energy consumption, providing a scalable DC source solution for intermediate-scale quantum processors with stringent noise and stability requirements, with potential extensions to other quantum hardware platforms and precision measurement.

quant-ph↗

arXiv2025

Laboratory Three-dimensional X-ray Micro-beam Laue Diffraction

The development of three-dimensional (3D) non-destructive X-ray characterization techniques in home laboratories is essential for enabling many more researchers to perform 3D characterization daily, overcoming the limitations imposed by competitive and scarce access to synchrotron facilities. Recent efforts have focused on techniques such as laboratory diffraction contrast tomography (LabDCT), which allows 3D characterization of recrystallized grains with sizes larger than 15-20 $μ$m, offering a boundary resolution of approximately 5$μ$m using commercial X-ray computed tomography (CT) systems. To enhance the capabilities of laboratory instruments, we have developed a new laboratory-based 3D X-ray micro-beam diffraction (Lab-3D$μ$XRD) technique. Lab-3D$μ$XRD combines the use of a focused polychromatic beam with a scanning-tomographic data acquisition routine to enable depth-resolved crystallographic orientation characterization. This work presents the first realization of Lab-3D$μ$XRD, including hardware development through the integration of a newly developed Pt-coated twin paraboloidal capillary X-ray focusing optics into a conventional X-ray $μ$CT system, as well as the development of data acquisition and processing software. The results are validated through comparisons with LabDCT and synchrotron phase contrast tomography. The findings clearly demonstrate the feasibility of Lab-3D$μ$XRD, particularly in detecting smaller grains and providing intragranular information. Finally, we discuss future directions for developing Lab-3D$μ$XRD into a versatile tool for studying materials with smaller grain sizes and high defect densities, including the potential of combining it with LabDCT and $μ$CT for multiscale and multimodal microstructural characterization.

cond-mat.mtrl-sci↗

arXiv2025

Pink-Beam Dark Field X-ray Microscopy: Expanding 3D/4D Imaging for Complex and Deformed Microstructures

Dark Field X-ray Microscopy (DFXM) has advanced 3D non-destructive, high-resolution imaging of strain and orientation in crystalline materials, enabling the study of embedded structures in bulk. However, the photon-intensive nature of monochromatic DFXM limits its applicability to highly deformed or weakly crystalline structures and constrains time-resolved studies in industrially relevant materials. We present pink-beam DFXM (\pDFXM) at the ID03 beamline of ESRF, achieving a 27-fold increase in diffracted intensity while maintaining 100 nm spatial resolution. We validate \pDFXM{} by imaging a partially recrystallized aluminum grain, confirming sufficient angular resolution for microstructure mapping. The increased flux significantly enhances the diffracted signal, enabling the resolution of subgrain structures. Additionally, we image a highly deformed ferritic iron grain, previously inaccessible in monochromatic mode without focusing optics. Beyond static imaging, \pDFXM{} enables real-time tracking of grain growth during annealing, achieving hundred-millisecond temporal resolution. By combining high photon flux with non-destructive, high-resolution 3D mapping, \pDFXM{} expands diffraction-contrast imaging to poorly diffracting crystals, unlocking new opportunities for studying grain growth, fatigue, and corrosion in bulk materials.

physics.app-ph↗

arXiv2024

M2CS: A Microwave Measurement and Control System for Large-scale Superconducting Quantum Processors

As superconducting quantum computing continues to advance at an unprecedented pace, there is a compelling demand for the innovation of specialized electronic instruments that act as crucial conduits between quantum processors and host computers. Here, we introduce a Microwave Measurement and Control System (M2CS) dedicated for large-scale superconducting quantum processors. M2CS features a compact modular design that balances overall performance, scalability, and flexibility. Electronic tests of M2CS show key metrics comparable to commercial instruments. Benchmark tests on transmon superconducting qubits further show qubit coherence and gate fidelities comparable to state-of-the-art results, confirming M2CS's capability to meet the stringent requirements of quantum experiments run on intermediate-scale quantum processors. The system's compact and scalable design offers significant room for further enhancements that could accommodate the measurement and control requirements of over 1000 qubits, and can also be adopted to other quantum computing platforms such as trapped ions and silicon quantum dots. The M2CS architecture may also be applied to wider range of scenarios, such as microwave kinetic inductance detectors, as well as phased array radar systems.

quant-ph↗

arXiv2023

Deep Speech Synthesis from MRI-Based Articulatory Representations

In this paper, we study articulatory synthesis, a speech synthesis method using human vocal tract information that offers a way to develop efficient, generalizable and interpretable synthesizers. While recent advances have enabled intelligible articulatory synthesis using electromagnetic articulography (EMA), these methods lack critical articulatory information like excitation and nasality, limiting generalization capabilities. To bridge this gap, we propose an alternative MRI-based feature set that covers a much more extensive articulatory space than EMA. We also introduce normalization and denoising procedures to enhance the generalizability of deep learning methods trained on MRI data. Moreover, we propose an MRI-to-speech model that improves both computational efficiency and speech fidelity. Finally, through a series of ablations, we show that the proposed MRI representation is more comprehensive than EMA and identify the most suitable MRI feature subset for articulatory synthesis.

eess.AS↗

arXiv2022

Parallel measurements of vibrational modes in a few-layer graphene nanomechanical resonator using software-defined radio dongles

Software-defined radio dongles are small and inexpensive receivers well known to amateur radio enthusiasts. When connected to an antenna, they enable monitoring of a wide range of the radio spectrum by conditioning the input signal and transferring a downconverted version of it to a personal computer for software processing. Here, we employ a composite of two such dongles, interfaced with codes written in MATLAB and GNU Radio, as a measuring instrument to study the flexural vibrations of a few-layer graphene nanomechanical resonator. Instead of an antenna, we connect the dongles to the split output of a photodetector used to detect vibrations optically. We first perform a quantitative analysis of the dynamics of the first vibrational mode. We then measure the response of the first two vibrational modes in parallel. To illustrate our technique, we detect changes in the vibrational amplitude of both modes induced by periodic strain modulation with a delay of $\approx1$ ms between measurements. Last, we show that our software-based instrument can be employed to demodulate human voice encoded in the vibrations of our resonator. For parallel measurements of several frequency channels, and provided that the input signal is not too weak, our composite system may offer an alternative to the use of multiple lock-in amplifiers or multiple spectrum analyzers, with the distinct advantage of being cost-effective per frequency channel.

cond-mat.mes-hall↗