arXiv subjects

Bai Song

Publications and source records attributed to Bai Song.

At least 19 recordsLinked to original sources

arXiv2026

Vibe-FDTR: An agent-oriented framework for reproducible frequency-domain thermoreflectance data analysis

Frequency-domain thermoreflectance (FDTR) is a laser pump-probe technique widely used to measure thermal properties at the micro- and nanoscale; however, it relies on a complex data analysis procedure that demands substantial domain expertise and is susceptible to subtle human errors. Here, we present Vibe-FDTR, an agent-oriented framework that enables large language model (LLM) agents to perform reliable and reproducible FDTR analyses directly from natural language requests. This framework couples a configuration-driven FDTR code package, which enforces physical and parametric consistency, with procedural agent skills that translate user intentions into organized and verifiable analysis steps. We evaluate Vibe-FDTR using a controlled benchmark with two levels: synthetic single-step tasks and real-data multi-step tasks based on measurements of gold-coated graphite samples. Across the two levels, agents using Vibe-FDTR achieve success rates of 100% and 98.9%, respectively. In sharp contrast, ablating skills (Code-agent) reduces performance to 91.4% and 36.7%, which drops further to 38.6% and 0% when the domain package is also omitted (Agent-only). Beyond success rate, Vibe-FDTR also reduces computational cost by 87.7% relative to the Code-agent variant and cuts execution time by more than 60%. Finally, an optional expert mode supports experimental planning via autonomous sensitivity and uncertainty evaluations, and formulates physically grounded recommendations for underspecified tasks. These results demonstrate that encapsulating domain code and expert knowledge into agent skills offers a promising route toward low-barrier, autonomous, and trustworthy thermal metrology.

physics.app-ph↗

arXiv2026

Intrinsically low thermal conductivity of stoichiometric lithium niobate:Experimental measurement and microscopic origin

With the rapid development of integrated electro-optic and nonlinear optical devices based on lithium niobate (LiNbO$_3$, LN), thermal management is becoming a critical area of focus. However, experimental measurement of thermal transport in stoichiometric LiNbO$_3$ (sLN) remains scarce, and the intrinsic microscopic mechanisms remain to be established. Here, we combine the laser pump-probe technique of frequency-domain thermoreflectance (FDTR) with state-of-the-art machine-learned atomistic simulations to comprehensively investigate thermal transport in sLN. The measured and simulated room-temperature thermal conductivity ($\kappa$) values of sLN agree well, which are orders-of-magnitude lower than that of many classic and emerging semiconductors such as silicon. Furthermore, the temperature-dependent $\kappa$ exhibits a $T^{-\alpha}$ scaling with $\alpha$ near unity, suggesting that thermal transport is dominated by intrinsic phonon-phonon scattering. By comparing sLN with cubic boron arsenide (cBAs) which serves as an ultrahigh-$\kappa$ benchmark, we reveal that harmonic properties are not responsible for the low $\kappa$ of sLN, which feature phonon heat capacity and group velocities that are either higher than or comparable to those in cBAs. Instead, the low $\kappa$ originates from substantially stronger anharmonicity and larger scattering phase space. These two factors collectively suppress phonon lifetimes by 1-2 orders of magnitude, leading to a maximum phonon mean free path of approximately 140 nm. As a result, notable size effects emerge in thin-film sLN below 1 $\mu$m, with $\kappa$ dropping to half the bulk value at 10 nm. Altogether, our findings establish a fundamental understanding of thermal transport in sLN and provide atomistic insights for thermal management in advanced lithium niobate technologies.

cond-mat.mtrl-sci↗

arXiv2026

Zero-Field Thermal Hall Effect in Insulator

Fourier's law dictates that heat flow is usually parallel to the applied temperature gradient. However, under a high magnetic field, heat flow carried by both electrons in conductors and phonons in insulators can be deflected, a phenomenon known as thermal Hall effect. Intriguingly, we observe at zero field a spontaneous thermal Hall effect in an antiferromagnetic insulator. Despite a vanishingly small uncompensated magnetization, the magnitude of this effect is surprisingly large, comparable to typical responses induced by several teslas of external field. This zero-field behavior indicates that charge-neutral heat carriers can be governed by an intrinsic effective field arising from the unique spin arrangement. Our discovery challenges the centuries-old preconception of heat conduction and open up new avenues for exploring non-trivial topological responses in quantum materials.

cond-mat.str-el↗

arXiv2026

Intrinsically ultralow thermal conductivity in all-inorganic superatomic bulk crystals

Superatomic compounds, composed of atomic clusters interwoven by weak chemical bonds exhibit large anharmonicity vibrations, are excellent candidates for ultralow thermal conductivity (\k{appa}) materials. However, growing bulk superatomic single crystals is challenging due to complex chemical composition and chemical bonds, and studies on their intrinsic thermal property are scarce. Here, we grew high-quality superatomic single crystals of Re6Se8Te7 and Re6Te15, both of which are narrow band gap semiconductors that change into metals under external physical pressure. At room-temperature, the \k{appa} are 0.32 W m-1 K-1 and 0.53 W m-1 K-1 in Re6Se8Te7 and Re6Te15, respectively, ranking among the lowest value reported in all-inorganic bulk crystals. It is mainly attributed to the large Gr\"uneisen parameter (1.93) and low average sound speed (< 1482 m/s), which are due to soft Te7 nets weakly embedded among the rigid Re6Se8 (Re6Te8) quasi-cubic clusters. The appearance of boson peak, i. e., hump of C(T)/T3, verifies the existence of disordered phonon transports. Besides, the temperature dependence of \k{appa} can be described by classic Debye-Callaway model. Notably, above 350 K, the \k{appa} values of Re6Se8Te7 and Re6Te15 are remarkably close to the upper limit derived from glassy-like diffusion model. This finding sets the superatomic compounds as a promising family for searching ultralow-\k{appa} and energy management materials.

cond-mat.mtrl-sci↗

arXiv2026

Invariant ionic conductance in an atomically thin polar nanopore

Ion channels regulate many essential properties of biological cells, especially the membrane potential. Despite decades of efforts on artificial channels, it remains a great challenge to mimic the dipole potential-an indispensable constituent of the membrane potential, due to its angstrom-scale characteristic length. Here, we explore nanopores in monolayer molybdenum sulfide selenide (MoSSe) considering its intrinsic dipole and atomic thickness. Remarkably, an invariant ionic conductance was observed over salt concentrations spanning six orders of magnitude, distinct from all known conductance-concentration scaling laws and reminiscent of the current saturation in cell membranes at high concentrations. Molecular dynamics simulations revealed the fundamental role of the dipole-modulated dielectric properties of nanoconfined water. Our findings highlight an exotic conductance scaling law and open up a novel avenue for controlling ion transport in unprecedented ways.

cond-mat.mes-hall↗

arXiv2025

Heat transport in superionic materials via machine-learned molecular dynamics

Precise modeling and understanding of heat transport in the superionic phase are of great interest. Although simulations combining Green-Kubo (GK) molecular dynamics with machine-learned potentials (MLPs) stand as a promising approach, substantial challenges remain due to the crucial impact of atomic diffusion. Here, we first show that the thermal conductivity (${\kappa}$) of superionic materials calculated via conventional GK integral of the energy flux varies notably with the MLP model. Subsequently, we highlight that reliable, model-independent $\kappa$ values can be obtained by applying Onsager's reciprocal relations to correctly capture the coupled heat and mass transport. Remarkably, an anomalously invariant $\kappa$ can be observed over a wide temperature range, distinct from the characteristic trends in traditional crystals and glasses. In addition, we illustrate that conventional $\kappa$ decompositions into kinetic, potential, and cross terms suffer from ambiguities in the physical interpretation, despite their mathematical rigor. Finally, we propose a criterion for the necessity of the Onsager correction and reveal the underlying mechanism as a competition between thermally and chemically driven ion fluxes.

cond-mat.mtrl-sci↗

arXiv2025

GUI-Rise: Structured Reasoning and History Summarization for GUI Navigation

While Multimodal Large Language Models (MLLMs) have advanced GUI navigation agents, current approaches face limitations in cross-domain generalization and effective history utilization. We present a reasoning-enhanced framework that systematically integrates structured reasoning, action prediction, and history summarization. The structured reasoning component generates coherent Chain-of-Thought analyses combining progress estimation and decision reasoning, which inform both immediate action predictions and compact history summaries for future steps. Based on this framework, we train a GUI agent, \textbf{GUI-Rise}, through supervised fine-tuning on pseudo-labeled trajectories and reinforcement learning with Group Relative Policy Optimization (GRPO). This framework employs specialized rewards, including a history-aware objective, directly linking summary quality to subsequent action performance. Comprehensive evaluations on standard benchmarks demonstrate state-of-the-art results under identical training data conditions, with particularly strong performance in out-of-domain scenarios. These findings validate our framework's ability to maintain robust reasoning and generalization across diverse GUI navigation tasks. Code is available at https://leon022.github.io/GUI-Rise.

cs.AI↗

arXiv2025

Ultrahigh interfacial thermal conductance for cooling gallium oxide electronics using cubic boron arsenide

Gallium oxide (Ga$_2$O$_3$) has attracted significant interest for its unique potential especially in power electronics. However, its low and anisotropic thermal conductivity poses a major challenge for heat dissipation. Here, we explore an effective cooling strategy centering on the heterogeneous integration of $\beta$-Ga$_2$O$_3$ devices with cubic boron arsenide (cBAs), an emerging material with an ultrahigh thermal conductivity $\kappa$ of ~1300 Wm$^{-1}$K$^{-1}$. Machine-learned potentials for representative $\beta$-Ga$_2$O$_3$/cBAs interfaces are trained, enabling accurate and efficient calculation of the interfacial thermal conductance $G$ via nonequilibrium molecular dynamics. At 300 K, remarkable $G$ values of 749$\pm$33 MWm$^{-2}$K$^{-1}$ and 824$\pm$35 MWm$^{-2}$K$^{-1}$ are predicted for Ga-As and O-B bonding across the interface, respectively, which are primarily attributed to the well-matched phonon density of states considering the similar Debye temperatures of $\beta$-Ga$_2$O$_3$ and cBAs. Moreover, finite-element simulations directly show a notable device temperature reduction when comparing cBAs with other substrates. The simultaneously ultrahigh $\kappa$ and $G$ highlight cBAs as an ideal substrate for Ga$_2$O$_3$ electronics.

cond-mat.mtrl-sci↗

arXiv2024

Insight into the effect of force error on the thermal conductivity from machine-learned potentials

Machine-learned potentials (MLPs) have been extensively used to obtain the lattice thermal conductivity via atomistic simulations. However, the impact of force errors in various MLPs on thermal transport has not been widely recognized and remains to be fully understood. Here, we employ MLP-driven molecular dynamics (MD) and anharmonic lattice dynamics (LD) to systematically investigate how the calculated thermal conductivity varies with the force errors, using boron arsenide as a prototypical material. We consistently observe an underestimation of thermal conductivity in MD simulations with three different MLPs including the neuroevolution potential, deep potential, and moment tensor potential. We provide a robust extrapolation scheme based on controlled force noises via the Langevin thermostat to correct this underestimation. The corrected results achieve a good agreement with previous experimental measurement from 200 K to 600 K. In contrast, the thermal conductivity values from LD calculations with MLPs readily align with the experimental data, which is attributed to the much smaller effects of the force errors on the force-constant calculations.

cond-mat.mtrl-sci↗

arXiv2024

Highly efficient path-integral molecular dynamics simulations with GPUMD using neuroevolution potentials: Case studies on thermal properties of materials

Path-integral molecular dynamics (PIMD) simulations are crucial for accurately capturing nuclear quantum effects in materials. However, their computational intensity and reliance on multiple software packages often limit their applicability at large scales. Here, we present an integration of PIMD methods, including thermostatted ring-polymer molecular dynamics (TRPMD), into the open-source GPUMD package, combined with highly accurate and efficient machine-learned neuroevolution potential (NEP) models. This approach achieves almost the accuracy of first-principles calculations with the computational efficiency of empirical potentials, enabling large-scale atomistic simulations that incorporate nuclear quantum effects. We demonstrate the efficacy of the combined NEP-PIMD approach by examining various thermal properties of diverse materials, including lithium hydride (LiH), three porous metal-organic frameworks (MOFs), liquid water, and elemental aluminum. For LiH, our NEP-PIMD simulations successfully capture the isotope effect, reproducing the experimentally observed dependence of the lattice parameter on the reduced mass. For MOFs, our results reveal that achieving good agreement with experimental data requires consideration of both nuclear quantum effects and dispersive interactions. For water, our PIMD simulations capture the significant impact of nuclear quantum effects on its microscopic structure. For aluminum, the TRPMD method effectively captures thermal expansion and phonon properties, aligning well with quantum mechanical predictions. This efficient NEP-PIMD approach opens new avenues for exploring complex material properties influenced by nuclear quantum effects, with potential applications across a broad range of materials.

cond-mat.mtrl-sci↗

arXiv2024

Phonon heat conduction across slippery interfaces in twisted graphite

Interlayer rotation in van der Waals (vdW) materials offers great potential for manipulating phonon dynamics and heat flow in advanced electronics with ever higher compactness and power density. However, despite extensive theoretical efforts in recent years, experimental measurements remain scarce especially due to the critical challenges of preparing single-crystalline twisted interfaces and probing interfacial thermal transport with sufficient resolution. Here, we exploited the intrinsic twisted interfaces in highly oriented pyrolytic graphite (HOPG). By developing novel experimental schemes based on microfabricated mesas, we managed to achieve simultaneous mechanical characterizations and thermal measurements. In particular, we pushed the HOPG mesas with a microprobe to identify and rotate single-crystalline intrinsic interfaces owing to their slippery nature as is well known in structural superlubricity. Remarkably, we observed over 30-fold suppression of thermal conductance for the slippery interfaces by using epitaxial graphite as a control. Nonetheless, the interfacial conductance remains around 600 $\mathrm{MWm^{-2}K^{-1}}$ which surpasses the highest values for artificially stacked vdW structures by more than five times. Further, atomic simulations revealed the predominant role of the transverse acoustic phonons. Together, our findings highlight a general physical picture that directly correlates interfacial thermal transport with sliding resistance, and lay the foundation for twist-enabled thermal management which are particularly beneficial to twistronics and slidetronics.

cond-mat.mes-hall↗

arXiv2024

Thermal transport in a 2D amorphous material

Two-dimensional (2D) crystals proved revolutionary soon after graphene was discovered in 2004. However, 2D amorphous materials only became accessible in 2020 and remain largely unexplored. In particular, the thermophysical properties of amorphous materials are of great interest upon transition from 3D to 2D. Here, we probe thermal transport in 2D amorphous carbon. A cross-plane thermal conductivity ($\kappa$) down to 0.079 $\rm{Wm}^{-1}K^{-1}$ is measured for van der Waals stacked multilayers at room temperature, which is among the lowest reported to date. Meanwhile, an unexpectedly high in-plane $\kappa$ is obtained for freestanding monolayers which is a few times larger than what is predicted by conventional wisdom for 3D amorphous carbon with similar $\rm{sp}^{2}$ fraction. Our molecular dynamics simulations reveal the role of disorder and highlight the impact of dimensionality. Amorphous materials at the 2D limit open up new avenues for understanding and manipulating heat at the atomic scale.

cond-mat.mtrl-sci↗

arXiv2024

Isotope engineering of carrier mobility via Fr\"ohlich electron-phonon interaction

Isotope effects on phonon properties and transport have been predicted and observed for decades. However, despite the crucial impact of electron-phonon interactions, the effect of isotopes on electron transport remains largely unexplored. Here, by using first-principles calculations, we theoretically predict that the electron mobility of lithium hydride (LiH) can increase by up to ~100% as $^3\rm{H}$ is replaced with $^1\rm{H}$. This remarkable phenomenon is primarily attributed to the isotope engineering of the Fr\"ohlich interaction by the mass-induced line shift of the longitudinal optical (LO) phonons. Notably, the isotope-dependent absorption of LO phonons dominates while the isotope-insensitive emission process is mostly suppressed due to energy conservation. We further propose general guidelines for evaluating isotope effects on carrier transport in different materials.

cond-mat.mtrl-sci↗

arXiv2024

Correcting force error-induced underestimation of lattice thermal conductivity in machine learning molecular dynamics

Machine learned potentials (MLPs) have been widely employed in molecular dynamics (MD) simulations to study thermal transport. However, literature results indicate that MLPs generally underestimate the lattice thermal conductivity (LTC) of typical solids. Here, we quantitatively analyze this underestimation in the context of the neuroevolution potential (NEP), which is a representative MLP that balances efficiency and accuracy. Taking crystalline silicon, GaAs, graphene, and PbTe as examples, we reveal that the fitting errors in the machine-learned forces against the reference ones are responsible for the underestimated LTC as they constitute external perturbations to the interatomic forces. Since the force errors of a NEP model and the random forces in the Langevin thermostat both follow a Gaussian distribution, we propose an approach to correcting the LTC by intentionally introducing different levels of force noises via the Langevin thermostat and then extrapolating to the limit of zero force error. Excellent agreement with experiments is obtained by using this correction for all the prototypical materials over a wide range of temperatures. Based on spectral analyses, we find that the LTC underestimation mainly arises from increased phonon scatterings in the low-frequency region caused by the random force errors.

cond-mat.mtrl-sci↗

arXiv2022

Isotope effect on the Casimir force

Isotopic dependence of the Casimir force is key to probing new physics and pushing novel technologies at the micro and nanoscale, but is largely unexplored. In 2002, an isotope effect of 10^(-4) was estimated for metals -- orders of magnitude beyond the experimental resolution. Here, by employing the Lifshitz theory, we reveal a significant isotope effect of over 10^(-1) for polar dielectrics. This effect arises from the isotope-mass-induced line shift of the zone-center optical phonons and is insensitive to the linewidth. We perform numerical analyses on both the imaginary and real-frequency axes, and derive analytical formulas for predicting the isotope effect.

cond-mat.mes-hall↗

arXiv2022

Isotope effect on radiative thermal transport

Isotope effects on heat conduction and convection have been known for decades. However, whether thermal radiation can be isotopically engineered remains an open question. Here, we predict over 3-orders-of-magnitude variation of radiative heat flow with varying isotopic compositions for polar dielectrics at room temperature. We reveal this as an isotope mass effect which induce phonon line shift and broadening that in turn affect phonon-mediated resonant absorption both in the near and far field. In contrast, the isotope effect is negligible for metals and doped semiconductors which largely depend on free carriers. We also discuss the role of temperature with regard to surface mode excitation.

cond-mat.mes-hall↗

arXiv2022

VMRF: View Matching Neural Radiance Fields

Neural Radiance Fields (NeRF) have demonstrated very impressive performance in novel view synthesis via implicitly modelling 3D representations from multi-view 2D images. However, most existing studies train NeRF models with either reasonable camera pose initialization or manually-crafted camera pose distributions which are often unavailable or hard to acquire in various real-world data. We design VMRF, an innovative view matching NeRF that enables effective NeRF training without requiring prior knowledge in camera poses or camera pose distributions. VMRF introduces a view matching scheme, which exploits unbalanced optimal transport to produce a feature transport plan for mapping a rendered image with randomly initialized camera pose to the corresponding real image. With the feature transport plan as the guidance, a novel pose calibration technique is designed which rectifies the initially randomized camera poses by predicting relative pose transformations between the pair of rendered and real images. Extensive experiments over a number of synthetic and real datasets show that the proposed VMRF outperforms the state-of-the-art qualitatively and quantitatively by large margins.

cs.CV↗

arXiv2022

Fundamental limit to the rectification of near-field heat flow: The potential of intrinsic semiconductor films

We derive the fundamental limit to near-field radiative thermal rectification mediated by an intrinsic semiconductor film within the framework of fluctuational electrodynamics. By leveraging the electromagnetic local density of states, we identify {\epsilon}"_H/{\epsilon}"_L as an upper bound on the rectification magnitude, where {\epsilon}"_H and {\epsilon}"_L are respectively the imaginary parts of the film permittivity at high and low temperatures. This bound is tight and can be approached regardless of whether the film is suspended or supported. For intrinsic silicon the limit can in principle exceed 10^9. Our work highlights the possibility of controlling heat flow as effectively as electric current, and offers guidelines to potentially achieve this goal.

cond-mat.mes-hall↗