arXiv subjects

Lijun Yang

Publications and source records attributed to Lijun Yang.

At least 19 recordsLinked to original sources

arXiv2026

How Surface Viscoelasticity Eliminates Satellite Drops

Satellite drops form widely during the breakup of liquid threads and constitute deleterious byproducts across a broad range of industrial technologies, yet their complete suppression has remained a longstanding challenge. Here, we experimentally report that surface viscoelasticity introduced by a small amount of bovine serum albumin can fully eliminate satellite drops, via modulating the localized spatiotemporal topology near pinch-off singularity. During the late thinning stage, surface shear viscosity counterbalances the capillary and stably anchors the thinning neck at the midpoint between the two primary beads, fundamentally precluding satellite droplet formation. We further propose a scaling law to describe the unique self-similar thinning behaviors dictated by surface viscosity. These results shed light on the thinning dynamics of liquid threads with surface rheology and offer a promising strategy to eliminate satellite drops in practical applications.

physics.flu-dyn↗

arXiv2026

Marangoni modulation of coupled Rayleigh-Taylor and Faraday instabilities in vertically oscillated liquid films

We investigate the Marangoni modulation of coupled Rayleigh-Taylor and Faraday instabilities in a vertically oscillated Newtonian liquid film carrying insoluble surfactants. Linear stability analysis using Floquet theory reveals that an increasing Marangoni number (Ma) selectively suppresses subharmonic modes, driving the system into a harmonic-dominated regime. The interfacial response is found to be highly frequency-dependent. At low forcing frequencies, increasing Ma causes adjacent harmonic tongues to merge into a novel surfactant mode that migrates towards long wavelengths, ultimately coalescing with the RTI branch and fragmenting the dynamically stable window. Conversely, at high frequencies, surfactants monotonically elevate the harmonic instability threshold, significantly widening the stable parameter space. To uncover the underlying mechanisms, a long-wave asymptotic analysis is performed, demonstrating that the critical forcing amplitude factorizes into a static capillary-gravity margin and a dynamic elasto-inertial modulation, yielding a scaling law for the critical mode balance. Finally, nonlinear simulations based on a rigorous weighted-residual reduced model are utilized to dissect the spatial work performed by individual forces, which shows that surfactants modulate stability through phase-controlled Marangoni transport. In the RTI regime, increasing Ma reverses the transport direction and drives fluid into the peaks, inducing a transition from stabilization to destabilization. In the Faraday instability (FI) regime, the response exhibits a strong frequency dependence, governed by Marangoni transport that redistributes fluid away from interfacial peaks at high frequencies but toward them at low frequencies, thereby suppressing or enhancing the instability accordingly.

physics.flu-dyn↗

arXiv2026

Constrained Particle Seeking: Solving Diffusion Inverse Problems with Just Forward Passes

Diffusion models have gained prominence as powerful generative tools for solving inverse problems due to their ability to model complex data distributions. However, existing methods typically rely on complete knowledge of the forward observation process to compute gradients for guided sampling, limiting their applicability in scenarios where such information is unavailable. In this work, we introduce \textbf{\emph{Constrained Particle Seeking (CPS)}}, a novel gradient-free approach that leverages all candidate particle information to actively search for the optimal particle while incorporating constraints aligned with high-density regions of the unconditional prior. Unlike previous methods that passively select promising candidates, CPS reformulates the inverse problem as a constrained optimization task, enabling more flexible and efficient particle seeking. We demonstrate that CPS can effectively solve both image and scientific inverse problems, achieving results comparable to gradient-based methods while significantly outperforming gradient-free alternatives. Code is available at https://github.com/deng-ai-lab/CPS.

cs.LG↗

arXiv2025

Nonlinear opto-magnetic signature of d-wave altermagnets

Altermagnetism, a recently discovered collinear magnetic order with net zero magnetization but exhibiting spin-splitting band structure, has attracted much research interest due to the rich fundamental physics and possible applications. In this work, we investigate the opto-magnetic response of $d$-wave altermagnets, focusing on the inverse Cotton-Mouton effect--the induction of static magnetization via linearly polarized light. We find that the direction of the induced magnetization is determined by the N\'eel vector. Moreover, its magnitude exhibits a periodic dependence on the polarization angle of the incident light, a hallmark of the system's symmetry. Our findings demonstrate that the inverse Cotton-Mouton effect offers a direct method both for detecting $d$-wave altermagnets and for probing their intrinsic properties.

cond-mat.mtrl-sci↗

arXiv2025

You Only Look One Step: Accelerating Backpropagation in Diffusion Sampling with Gradient Shortcuts

Diffusion models (DMs) have recently demonstrated remarkable success in modeling large-scale data distributions. However, many downstream tasks require guiding the generated content based on specific differentiable metrics, typically necessitating backpropagation during the generation process. This approach is computationally expensive, as generating with DMs often demands tens to hundreds of recursive network calls, resulting in high memory usage and significant time consumption. In this paper, we propose a more efficient alternative that approaches the problem from the perspective of parallel denoising. We show that full backpropagation throughout the entire generation process is unnecessary. The downstream metrics can be optimized by retaining the computational graph of only one step during generation, thus providing a shortcut for gradient propagation. The resulting method, which we call Shortcut Diffusion Optimization (SDO), is generic, high-performance, and computationally lightweight, capable of optimizing all parameter types in diffusion sampling. We demonstrate the effectiveness of SDO on several real-world tasks, including controlling generation by optimizing latent and aligning the DMs by fine-tuning network parameters. Compared to full backpropagation, our approach reduces computational costs by $\sim 90\%$ while maintaining superior performance. Code is available at https://github.com/deng-ai-lab/SDO.

cs.LG↗

arXiv2025

Weyl-mediated Ruderman-Kittel-Kasuya-Yosida interaction revisited: imaginary-time formalism and finite temperature effects

Noncentrosymmetric magnetic Weyl semimetals provide a platform for investigating the interplay among magnetism, inversion symmetry breaking, and topologically nontrivial Weyl fermions. The Weyl-mediated Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction may be related to the magnetic orders observed in rare-earth magnetic Weyl semimetals. Previous studies of RKKY interaction between magnetic impurities in Weyl semimetals found Heisenberg, Ising-like, and Dzyaloshinskii-Moriya (DM) types of interactions. However, different range functions are obtained in the literature. In this work, we calculate the Weyl-mediated RKKY interaction by using the divergence-free imaginary-time formalism and obtain exact analytical results at finite temperature. The discrepancies among zero temperature range functions in the literature are resolved. At nonzero temperature, the interaction strength decays exponentially in the long distance limit. But in the short distance limit, the DM interaction shows a thermal enhancement, an effect persists up to higher temperature for shorter distance. This provides a mechanism stabilizing the helical order observed in rare-earth magnetic Weyl semimetals.

cond-mat.mes-hall↗

arXiv2024

Compression-thinning behavior of bubble suspensions

Rheology of bubble suspensions is critical for the prediction and control of bubbly flows in a wide range of industrial processes. It is well-known that the bubble suspension exhibits a shear-thinning behavior due to the bubble shape deformation under pure shear, but how the shear rheology response to dilatation remains unexplored. Here, we report a compression-thinning behavior that the bubble suspension exhibits a decreasing shear viscosity upon compressing. This peculiar rheological behavior is microscopically due to that a shrinking bubble surface effectively weakens the flow resistance of the surrounding liquid. We theoretically propose a constitutive equation for dilute bubble suspensions considering both shear and dilatation effects, and demonstrate that the contribution of dilatation effect on the shear viscosity can be significant at a changing pressure.

physics.flu-dyn↗

arXiv2024

A data-driven sparse learning approach to reduce chemical reaction mechanisms

Reduction of detailed chemical reaction mechanisms is one of the key methods for mitigating the computational cost of reactive flow simulations. Exploitation of species and elementary reaction sparsity ensures the compactness of the reduced mechanisms. In this work, we propose a novel sparse statistical learning approach for chemical reaction mechanism reduction. Specifically, the reduced mechanism is learned to explicitly reproduce the dynamical evolution of detailed chemical kinetics, while constraining on the sparsity of the reduced reactions at the same time. Compact reduced mechanisms are be achieved as the collection of species that participate in the identified important reactions. We validate our approach by reducing oxidation mechanisms for $n$-heptane (194 species) and 1,3-butadiene (581 species). The results demonstrate that the reduced mechanisms show accurate predictions for the ignition delay times, laminar flame speeds, species mole fraction profiles and turbulence-chemistry interactions across a wide range of operating conditions. Comparative analysis with directed relation graph (DRG)-based methods and the state-of-the-art (SOTA) methods reveals that our sparse learning approach produces reduced mechanisms with fewer species while maintaining the same error limits. The advantages are particularly evident for detailed mechanisms with a larger number of species and reactions. The sparse learning strategy shows significant potential in achieving more substantial reductions in complex chemical reaction mechanisms.

physics.chem-ph↗

arXiv2024

Physics-aligned Schr\"{o}dinger bridge

The reconstruction of physical fields from sparse measurements is pivotal in both scientific research and engineering applications. Traditional methods are increasingly supplemented by deep learning models due to their efficacy in extracting features from data. However, except for the low accuracy on complex physical systems, these models often fail to comply with essential physical constraints, such as governing equations and boundary conditions. To overcome this limitation, we introduce a novel data-driven field reconstruction framework, termed the Physics-aligned Schr\"{o}dinger Bridge (PalSB). This framework leverages a diffusion Schr\"{o}dinger bridge mechanism that is specifically tailored to align with physical constraints. The PalSB approach incorporates a dual-stage training process designed to address both local reconstruction mapping and global physical principles. Additionally, a boundary-aware sampling technique is implemented to ensure adherence to physical boundary conditions. We demonstrate the effectiveness of PalSB through its application to three complex nonlinear systems: cylinder flow from Particle Image Velocimetry experiments, two-dimensional turbulence, and a reaction-diffusion system. The results reveal that PalSB not only achieves higher accuracy but also exhibits enhanced compliance with physical constraints compared to existing methods. This highlights PalSB's capability to generate high-quality representations of intricate physical interactions, showcasing its potential for advancing field reconstruction techniques.

physics.flu-dyn↗

arXiv2024

Efficient nonlinear flame response modeling for propulsion thermoacoustic analysis using limited numerical data

Characterizing nonlinear flame response is critical for predicting thermoacoustic instabilities in propulsion combustors, yet obtaining a comprehensive response map through high-fidelity simulations remains computationally prohibitive. This study proposes a data-driven approach for learning nonlinear flame-response dynamics from limited numerical samples. Instead of requiring exhaustive harmonic-forcing simulations, a frequency-sweeping dataset with multiple perturbation amplitudes is designed to capture the coupled effects of excitation frequency and amplitude, enabling efficient learning of the nonlinear input-output relationship between flow perturbations and heat-release-rate fluctuations. A dual-path temporal surrogate model is developed to represent nonlinear response evolution in the time domain, where complementary temporal features are extracted to retain both global response trends and local nonlinear characteristics. The proposed framework is validated using numerical simulations of a laminar premixed flame. It accurately predicts nonlinear single-frequency responses over a wide range of forcing amplitudes and frequencies, with an average mean relative error of 6.69\% for 72 independent test cases. Further evaluation using a modified $n-\tau$ model demonstrates that the framework can capture stronger nonlinear responses by increasing the diversity of the training data. This work provides an efficient alternative for constructing nonlinear flame-response models and offers a promising approach for rapid thermoacoustic stability analysis of propulsion combustors.

cs.LG↗

arXiv2023

On the flame transfer function models for laminar premixed conical and V- flames considering the stretch effect

This paper investigates a predictive model that considers the impact of stretch on the dynamic response of laminar premixed conical and V- flames; the flame stretch consists of two components: the flame curvature and flow strain. The steady and perturbed flame fronts are determined via the linearized $G$-equation associated with the flame stretch model. Parameter analyses of the effects of Markstein length $\mathcal{L}$, flame radius $R$ and unstretched flame aspect ratio $\beta$ are also conducted. Results show that the flame stretch reduces the steady flame height, with this effect being more significant for larger Markstein lengths and smaller flame sizes. The effects of flame stretch on perturbed flames are evaluated by comparing the flame transfer function (FTF) considering the flame stretch and not. For flames of different sizes, the impact of flame stretch on FTF gain can be divided into three regions. When both $\beta$ and $R$ are relatively small, due to the decrease in steady flame height and the impact of flow strain, the FTF gain increases. As $\beta$ and $R$ gradually increase, the FTF gain of the conical flame oscillates periodically while the FTF gain of the V-flame decreases, primarily due to the flame curvature enhancing the flame front disturbance and the wrinkle counteracting effect. When $\beta$ and $R$ are large, a disruption in wrinkle counteracting effect ensues, leading to a significant increase in FTF gain. Furthermore, as the actual flame height is reduced, the flame stretch also reduces the FTF phase lag which is related to the disturbance propagation time from the flame root to the tip.

physics.flu-dyn↗

arXiv2023

Algebraic Multiplicity and the Poincar\'{e} Problem

In this paper we derive an upper bound for the degree of the strict invariant algebraic curve of a polynomial system in the complex project plane under generic condition. The results are obtained through the algebraic multiplicities of the system at the singular points. A method for computing the algebraic multiplicity using Newton polygon is also presented.

math.CA↗

arXiv2023

Nonlinear responses of the premixed V-flame subjected to dual-frequency disturbances

The two-way interaction between the unsteady flame heat release rate (HRR) and acoustic waves can lead to combustion instability within combustors. Previous studies have typically characterised premixed flame responses to pure harmonic forcing, assuming dynamically linear or weakly nonlinear behaviour, to quantify flame-acoustic interactions. By combining third-order asymptotic analysis with numerical simulations of the G-equation, this study investigates the nonlinear response of laminar premixed V-flames subjected to dual-frequency velocity perturbations (St1 and St2, dimensionless frequencies). The positive correlation between disturbance propagation speed uc and frequency St is captured by integrating a velocity-potential model with calibration against existing experimental data. The mechanism by which the disturbance at one forcing frequency, say St2, affects the flame dynamic response at the other forcing frequency, St1, is studied in detail. The perturbation at St2 couples with that at St1 to induce third-order nonlinear terms, giving rise to a non-monotonic suppression mechanism that smooths out the flame's spatial wrinkling owing to the positive correlation between uc and St. As a result, excitation at St2 modifies the HRR response at St1, delineating an effective region bounded on the left by the frequency threshold of the linear response and on the right by the aforementioned non-monotonicity. Within this region, excitation at St2 can markedly attenuate the HRR gain at St1 compared with the case where the flame is driven solely by the perturbation at St1. For instance, once both perturbation amplitudes exceed a certain threshold, excitation at St2 can attenuate the flame response at St1 by more than 40% compared with the case without excitation at St2.

physics.flu-dyn↗

arXiv2023

Direct Laser Writing of Surface Micro-Domes by Plasmonic Bubbles

Plasmonic microbubbles produced by laser irradiated gold nanoparticles (GNPs) in various liquids have emerged in numerous innovative applications. The nucleation of these bubbles inherently involves rich phenomena. In this paper, we systematically investigate the physicochemical hydrodynamics of plasmonic bubbles upon irradiation of a continuous wave (CW) laser on a GNP decorated sample surface in ferric nitrate solution. Surprisingly, we observe the direct formation of well-defined micro-domes on the sample surface. It reveals that the nucleation of a plasmonic bubble is associated with the solvothermal decomposition of ferric nitrate in the solution. The plasmonic bubble acts as a template for the deposition of iron oxide nanoparticles. It first forms a rim, then a micro-shell, which eventually becomes a solid micro-dome. Experimental results show that the micro-dome radius Rd exhibits an obvious dependence on time t, which can be well interpreted theoretically. Our findings reveal the rich phenomena associated with plasmonic bubble nucleation in a thermally decomposable solution, paving a plasmonic bubble-based approach to fabricate three dimensional microstructures by using an ordinary CW laser.

physics.plasm-ph↗

arXiv2023

Sub-megahertz nucleation of plasmonic vapor microbubbles by asymmetric collapse

Laser triggered and photothermally induced vapor bubbles have emerged as promising approaches to facilitate optomechanical energy conversion for numerous relevant applications in micro/nanofluidics. Here we report the observation of a sub-megahertz spontaneous nucleation of explosive plasmonic bubbles, triggered by a continuous wave laser. The periodic nucleation is found to be a result of the competition of Kelvin impulsive forces and thermal Marangoni forces applied on residual bubbles after collapse. The former originates from asymmetric bubble collapse, resulting in the directed locomotion of residual bubbles away from the laser spot. The latter arises in a laser irradiation induced heat affected zone (HAZ). When the Kelvin impulses dominates, residual bubbles move out of the HAZ and the periodic bubble nucleation occurs, with terminated subsequent steadily growing phases. We experimentally and numerically study the dependence of the nucleation frequency f on laser power and laser spot size. Moreover, we show that strong fluid flows over 10 mm/s in a millimeter range is steadily achievable by the periodically nucleated bubbles. Overall, our observation highlights the opportunities of remotely realizing strong localized flows, paving a way to achieve efficient micro/nanofluidic operations.

physics.flu-dyn↗

arXiv2022

Analytical solutions for the acoustic field in thin annular combustion chambers with linear gradients of cross-sectional area and mean temperature

Predictions of thermoacoustic instabilities in annular combustors are essential but difficult. Axial variations of flow and thermal parameters increase the cost of numerical simulations and restrict the application of analytical solutions. This work aims to find approximate analytical solutions for the acoustic field in annular ducts with linear gradients of axially non-uniform cross-sectional area and mean temperature. These solutions can be applied in low-order acoustic network models and enhance the ability of analytical methods to solve thermoacoustic instability problems in real annular chambers. A modified WKB method is used to solve the wave equation for the acoustic field, and an analytical solution with a wide range of applications is derived. The derivation of the equations requires assumptions such as low Mach number, high frequency and small non-uniformity. Cases with arbitrary distributions of cross-sectional surface area and mean temperature can be solved by the piecewise method as long as the assumptions are satisfied along the entire chamber.

physics.flu-dyn↗

arXiv2022

Entrapment of Interfacial Nanobubbles on Nano Structured Surfaces

Spherical-cap-shaped interfacial nanobubbles (NBs) forming on hydrophobic surfaces in aqueous solutions have extensively been studied both from a fundamental point of view and due to their relevance for various practical applications. In this study, the nucleation mechanism of spontaneously generated NBs at solid-liquid interfaces of immersed nanostructured hydrophobic surfaces is studied. Depending on the size and density of the surface nanostructures, NBs with different size and density were reproducibly and deterministically obtained. A two-step process can explain the NB nucleation, based on the crevice model, i.e., entrapped air pockets in surface cavities which grow by diffusion. The results show direct evidence for the spontaneous formation of NBs on a surface at its immersion. Next, the influence of size and shape of the nanostructures on the nucleated NBs are revealed. In particular, on non-circular nanopits we obtain NBs with a non-circular footprint, demonstrating the strong pinning forces at the three-phase contact line.

physics.flu-dyn↗

arXiv2022

Theoretical analysis of sound propagation and entropy generation across a distributed steady heat source

Acoustic and entropy waves interacting in a duct with a steady heat source and mean flow are analysed using an asymptotic expansion (AE) for low frequencies. The analytical AE solutions are obtained by taking advantage of flow invariants and applying a multi-step strategy. The proposed solutions provide first-order corrections to the compact model in the form of integrals of mean flow variables. An eigenvalue system is then built to predict the thermoacoustic modes of a duct containing a distributed heat source or sink. Predictions from the AE solutions agree well with the numerical results of the linearised Euler equations for both frequencies and growth rates, as long as the low-frequency condition is satisfied. The AE solutions are able to accurately reconstruct the acoustic and entropy waves and correct the significant errors in the predicted entropy wave associated with the compact model. The analysis illustrates that the thermoacoustic system needs to account for the entropy wave generated by the interaction of acoustic wave and the distributed steady heat source, especially when density- or entropy-dependent boundary conditions are prescribed at the duct ends. Furthermore, a combination of the AE method and the modified WKB approximation method is discussed for a cooling case. The AE solutions remedy the disadvantage of the WKB solution in the low and very low-frequency domain and facilitate full-frequency theoretical analyses of sound propagation and entropy generation in inhomogeneous duct flow fields.

physics.flu-dyn↗