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Yu Zou

Publications and source records attributed to Yu Zou.

At least 19 recordsLinked to original sources

Pharos-ESG: A Framework for Multimodal Parsing, Contextual Narration, and Hierarchical Labeling of ESG Report

Environmental, Social, and Governance (ESG) principles are reshaping the foundations of global financial governance, transforming capital allocation architectures, regulatory frameworks, and systemic risk coordination mechanisms. However, as the core medium for assessing corporate ESG performance, the ESG reports present significant challenges for large-scale understanding, due to chaotic reading order from slide-like irregular layouts and implicit hierarchies arising from lengthy, weakly structured content. To address these challenges, we propose Pharos-ESG, a unified framework that transforms ESG reports into structured representations through multimodal parsing, contextual narration, and hierarchical labeling. It integrates a reading-order modeling module based on layout flow, hierarchy-aware segmentation guided by table-of-contents anchors, and a multi-modal aggregation pipeline that contextually transforms visual elements into coherent natural language. The framework further enriches its outputs with ESG, GRI, and sentiment labels, yielding annotations aligned with the analytical demands of financial research. Extensive experiments on annotated benchmarks demonstrate that Pharos-ESG consistently outperforms both dedicated document parsing systems and general-purpose multimodal models. In addition, we release Aurora-ESG, the first large-scale public dataset of ESG reports, spanning Mainland China, Hong Kong, and U.S. markets, featuring unified structured representations of multi-modal content, enriched with fine-grained layout and semantic annotations to better support ESG integration in financial governance and decision-making.

cs.AI↗

Diamond-to-graphite transformation under hypersonic impact

Diamond to graphite transformation is a complex kinetically driven process which has been studied under various conditions for its fundamental importance. We report the transformation of diamond embedded ceramic matrix composites during hypersonic impact. Diamond particles embedded in cubic boron nitride matrix provide a superhard composite that was subjected to high impact collisions of metal projectiles travelling at speeds reaching Mach 8.45. Our observations suggest that the energy absorption and fracture of the composite is primarily enabled via the phase change of diamond into graphite. Characterization of the impact-fractured composite shows transformed diamond particles and provides details of the shock-induced phase transformation and the nature of diamond-graphite interfaces formed during rapid phase change. The study provides new understanding of phase transformation of diamond under extreme conditions.

cond-mat.mtrl-sci↗

Conditional grain-graph diffusion for property-guided inverse design of polycrystalline microstructures

Graph representations compactly encode polycrystalline microstructures while retaining grain topology and grain boundary information. We present a conditional graph diffusion framework for property-guided inverse design of dual-phase Ti-6Al-4V microstructures. An enhanced grain graph neural network (GNN) with grain boundary edge features, learnable node and edge embeddings, and multi-statistic pooling serves as a forward surrogate for stress prediction and candidate evaluation. The conditional diffusion model generates candidates through reverse diffusion under prescribed α-phase volume fraction, elastic modulus, and yield-stress proxy targets. Across four target regimes and independently seeded starting sets, generated candidates consistently approach the prescribed properties, including a target outside the property envelope of the existing microstructures. Local crystallographic consistency is evaluated post-generation from deviations from the Burgers orientation relationship (BOR). BOR-aware ranking increases mean BOR consistency by up to 44.9% and 56.4% for the in- and out-of-envelope targets, respectively, while maintaining property alignment. Finite element validation of the five best candidates in each primary design case yields a maximum absolute relative error of 1.0% in their mean properties. In a representative benchmark, diffusion requires 32 candidate evaluations per input graph, compared with approximately 40,000 for random search and evolutionary optimization, and reduces runtime by approximately two orders of magnitude in the tested implementations. These results establish conditional grain-graph diffusion as an efficient framework for property-guided polycrystalline microstructure design.

cond-mat.mtrl-sci↗

Unveiling competitions between carrier recombination pathways in semiconductors via mechanical damping

The total rate of carrier recombination in semiconductors has conventionally been expressed using an additive model, r_total = Σr_i , which rules out the interactions between carrier recombination pathways. Here we challenge this paradigm by demonstrating pathway competitions using our newly developed light-induced mechanical absorption spectroscopy (LIMAS), which allows us to probe genuine recombination dynamics in semiconductors via mechanical damping. We show that the total recombination rate in zinc sulfide (ZnS), a model semiconductor material, follows a multiplicative weighting model, r_total \propto Πr_i ^(w_i) with Σw_i=1. Under both steady-state and switch-on illuminations, the weighting factors w_i for each recombination pathway-direct, trap-assisted, and sublinear-are dictated by the carrier generation mechanism: (i) interband transition favors direct recombination; (ii) single-defect level-mediated generation promotes trap-assisted recombination; (iii) generation involving multiple saturated defect levels gives rise to sublinear recombination. Upon light switch-off, localized state changes drive a dynamic evolution of w_i, altering pathway competitions. These findings reshape our fundamental understanding of carrier dynamics and provide a new strategy to optimize next-generation optoelectronic devices.

cond-mat.mtrl-sci↗

NasZip: Software and Hardware Co-Design to Accelerate Approximate Nearest Neighbor Search with DIMM-Based Near-Data Processing

As large language models (LLMs) continue to advance, retrieval-augmented generation (RAG) has become the key mechanism for expanding model knowledge and reducing hallucinations. Central to RAG is approximate nearest neighbor search (ANNS), which retrieves database vectors most similar to a given query. However, distance calculation over high-dimensional vectors is inherently memory-bound, causing retrieval performance to be constrained by I/O bandwidth on mainstream platforms such as CPUs and GPUs. Although many prior early exiting (EE) techniques attempt to reduce memory accesses by only computing partial dimensions, the partial distance converges too slowly to the EE threshold, which ultimately limits their performance gains. To address these challenges, we propose NASZIP, a hardware-software co-designed framework that integrates near data processing (NDP) with a novel feature-level early exiting guided by statistics-based principal component analysis (PCA). Instead of relying solely on partial distances, NASZIP incorporates estimation and correction parameters to approximate full dimensional distances accurately, enabling earlier exiting without compromising accuracy. We further introduce a bit-level NDP-aware dynamic-float scheme that significantly reduces memory access for vector data. On the hardware side, we develop a data aware neighbor list mapping strategy that reduces neighbor retrieval latency and inter-channel communication overhead, complemented by a dedicated cache that exploits data locality and enhances prefetch efficiency. With these co-optimized techniques, NASZIP delivers speedups of up to $8.4\times$ / $1.4\times$ over CPU baseline and state-of-the-art GPU implementation at equal accuracy. Relative to the state-of-the-art NDP ANNS accelerator ANSMET, NASZIP achieves $1.69\times$ performance improvement.

cs.AR↗

Polymer-inspired mechanical metamaterials

Metamaterials benefit from unique architected patterns to achieve lightweight with exceptional mechanical properties inaccessible to conventional materials. Typical mechanical metamaterials are inspired by crystal-like lattice structures, whose closely packed frameworks often exhibit a rigid mechanical nature. Here, we present polymer-inspired metamaterials (PIMs) by programming deformation and strengthening mechanisms that mimic the mechanical roles of key constituent elements in polymer networks. By combining metamaterial programmability with polymer-inspired structures, we design crosslinking, proto-crystalline order, and entanglement in PIMs to enable macroscale strengthening mechanisms inspired by crosslink, molecular-density, and pre-stretch strengthening in polymers, expanding the metamaterial structure-property design space. This macroscale polymer-inspired programmability also suggests that PIMs could serve as a design platform incorporating the programmability strategies to achieve desired deformation and strengthening responses, holding a potential for applications in soft robotic joints and compliant connectors.

physics.app-ph↗

Wavelength-dependent photo-creep in halide perovskite single crystals

Halide perovskites are promising optoelectronic materials, but their time-dependent permanent deformation under illumination (i.e., photo-creep) is poorly understood, limiting their mechanical stability. Here we report wavelength-dependent photo-creep phenomena in CsPbBr3 and FAPbBr3 single crystals, studied by constant-load nanoindentation under controlled light with various wavelengths. Compared with creep in dark, continuous green light (near-bandgap) suppresses creep by 19% in CsPbBr3 and 10% in FAPbBr3, whereas violet (far above-bandgap) light enhances creep by 16% in CsPbBr3 and 8% in FAPbBr3. In contrast, when light is onset during creep, blue light enhances creep most prominently, whereas green light exhibits minimal influence. Such photo-creep behavior in halide perovskites are distinct with photo-plasticity phenomenon in conventional semiconductors. By combining the photoluminescence and photocurrent measurements, we unveil that ion migration promotes dislocation climb and creep, while carrier trapping suppresses dislocation glide and related creep in halide perovskites. Such competition between carrier trapping and ion migration tuned by wavelength governs the photo-creep response. Our findings uncover a photomechanical effect in halide perovskites and highlight how coupled carrier and ion dynamics under illumination affect their device reliability.

cond-mat.mtrl-sci↗

Identification and Prediction of Photoplasticity in Semiconductors Using Feature Engineering and Machine learning

Photoplasticity, the light-induced change in plastic deformation, plays a pivotal role in the mechanical durability and manufacturing of semiconductor materials. Yet, its governing mechanisms remain incompletely understood, owing to the interplay of coupled multiphysics factors. Here, we conduct high-throughput nanoindentation measurements to compile a dataset of paired hardness values in dark and light conditions. Then, we engineer physics-informed descriptors spanning electrical, mechanical, and optical properties, and identify the ten most informative features, including bandgap, breakdown field, and refractive index, to enable an interpretable machine learning framework that yields transferable design rules for light-tunable semiconductor mechanics. By identifying and predicting photoplasticity in semiconductors, this work provides a practical pathway for extracting mechanism-linked, transferable guidelines to engineer light-responsive mechanical behavior in semiconductor materials and devices.

cond-mat.mtrl-sci↗

Strain-released epitaxy of GaN enabled by compliant single-crystalline metal foils

Heteroepitaxy conventionally relies on rigid crystalline substrates, implicitly assuming that lattice and thermal mismatch must be accommodated within the epitaxial layer, leading to residual strain and defects that worsen with increasing substrate size. Here we demonstrate a substrate-mediated strain-partitioning regime in which lattice and thermal mismatch are preferentially partitioned into the substrate rather than stored in the epitaxial layer. We report the epitaxial growth of single-crystalline GaN on mechanically compliant yet crystallographically ordered single-crystalline copper foils. Atomic-resolution microscopy, geometric phase analysis and density functional theory reveal that mismatch-induced stress is primarily screened by elastic deformation of the Cu lattice, accompanied by localized interfacial slip confined to a few atomic layers, leaving the AlN and GaN epilayers nearly strain-free despite large nominal mismatch. Leveraging this strain-released epitaxial platform, we further demonstrate dense GaN micro-light-emitting diode arrays that benefit from efficient vertical electrical conduction and thermal dissipation enabled by the metallic substrate. By establishing compliant single-crystal metal foils as a new substrate class, this work identifies mechanical contrast as an underexplored governing parameter in heteroepitaxial design, with implications extending beyond GaN.

cond-mat.mtrl-sci↗

Direct evidence and atomic-scale mechanisms of reduced dislocation mobility in an inorganic semiconductor under illumination

Photo-plasticity in semiconductors, wherein their mechanical properties such as strength, hardness and ductility are influenced by light exposure, has been reported for several decades. Although such phenomena have drawn significant attention for the manufacturability and usage of deformable semiconductor devices, their underlying mechanisms are not well understood due to the lack of direct evidence. Here we provide experimental observation and atomic insights into the reduced mobility of dislocations in zinc sulfide, as a model material, under light. Using photo-nanoindentation and transmission electron microscopy, we observe that dislocations glide shorter distances under light than those in darkness and there are no apparent deformation twins in both conditions. By atomic-scale simulations, we demonstrate that the decreased dislocation mobility is attributed to the increased Peierls stress for dislocation motion and enhanced stress fields around dislocation cores due to photoexcitation. This study improves the understanding of photo-plastic effects in inorganic semiconductors, offering the opportunities for modulating their mechanical properties using light.

cond-mat.mtrl-sci↗

Generative metamaterials based on large language models

Mechanical metamaterials utilize intricate architectural designs to achieve advanced properties beyond those of their bulk counterparts. Existing metamaterial designs often rely on design inspirations and extensive experimental and numerical studies operated by design professionals, which can be time- and resource-consuming and limited in exploring the vast design space. Here, we transform metamaterial design by developing ChatMetamaterials based on large language models, a prompt-based generative metamaterial design engine capable of inventing architecture codes, and conducting reasoning-based diagnostics and evolution for complex metamaterial systems based on simple text prompts or hand-drawn sketches. This approach changes the way metamaterials are designed, and provides new opportunities for high-throughput metamaterial discovery.

physics.app-ph↗

Radiation-induced Instability of Organic-Inorganic Halide Perovskite Single Crystals

Organic-inorganic halide perovskites (OIHPs) are promising optoelectronic materials, but their instability under radiation environments restricts their durability and practical applications. Here we employ electron and synchrotron X-ray beams, individually, to investigate the radiation-induced instability of two types of OIHP single crystals (FAPbBr3 and MAPbBr3). Under the electron beam, we observe that 3-point star-style cracks grow on the surface of FAPbBr3, and bricklayer-style cracks are formed on the surface of MAPbBr3. Under the X-ray beam, a new composition without organic components appears in both FAPbBr3 and MAPbBr3. Such cracking and composition changes are attributed to the volatilization of organic components. We propose a volume-strain-based mechanism, in which the energy conversion results from the organic cation loss. Using nanoindentation, we reveal that beam radiations reduce the Youngs modulus and increase the hardness of both OIHPs. This study provides valuable insights into the structural and mechanical stabilities of OIHP single crystals in radiation environments.

cond-mat.mtrl-sci↗

Accurate and efficient predictions of keyhole dynamics in laser materials processing using machine learning-aided simulations

The keyhole phenomenon has been widely observed in laser materials processing, including laser welding, remelting, cladding, drilling, and additive manufacturing. Keyhole-induced defects, primarily pores, dramatically affect the performance of final products, impeding the broad use of these laser-based technologies. The formation of these pores is typically associated with the dynamic behavior of the keyhole. So far, the accurate characterization and prediction of keyhole features, particularly keyhole depth, as a function of time, has been a challenging task. In situ characterization of keyhole dynamic behavior using the synchrotron X-ray technique is informative but complicated and expensive. Current simulations are generally hindered by their poor accuracy and generalization abilities in predicting keyhole depths due to the lack of accurate laser absorptance data. In this study, we develop a machine learning-aided simulation method that accurately predicts keyhole dynamics, especially in keyhole depth fluctuations, over a wide range of processing parameters. In two case studies involving titanium and aluminum alloys, we achieve keyhole depth prediction with a mean absolute percentage error of 10%, surpassing those simulated using the ray-tracing method with an error margin of 30%, while also reducing computational time. This exceptional fidelity and efficiency empower our model to serve as a cost-effective alternative to synchrotron experiments. Our machine learning-aided simulation method is affordable and readily deployable for a large variety of materials, opening new doors to eliminate or reduce defects for a wide range of laser materials processing techniques.

cond-mat.mtrl-sci↗

Microscopic mechanisms of Strong Electron Scattering and Giant Anomalous Hall Effect in high-Curie-temperature Fe3GaTe2 van der Waals Films

Van der Waals ferromagnet Fe3GaTe2 with room-temperature perpendicular magnetic anisotropy and strong anomalous Hall effect has attracted considerable interest for their potential in spintronics. However, the microscopic mechanisms and manipulation of the electron scattering and the anomalous Hall effect of Fe3GaTe2 have remained unsettled. Here, we demonstrate strong tuning of the electron scattering and anomalous Hall effect of pattern-defined Fe3GaTe2 Hall-bar devices with perpendicular magnetic anisotropy, high Curie temperature (340 K, as high as that of Fe3GaTe2 bulk), and giant anomalous Hall effect by varying the layer thickness and temperature. Temperature-dependent resistivity experiments reveal that the electron scattering of the high-quality Fe3GaTe2 is dominated by impurity scattering and phonon scattering, regardless of the thickness. Combined temperature- and thickness-dependent scaling analyses of the anomalous Hall resistivity reveal that the anomalous Hall effect of the Fe3GaTe2 is predominantly from the positive, temperature-independent skew-scattering contribution that competes with negative temperature-independent, side-jump contribution, and negative, temperature-dependent intrinsic Berry-curvature contribution. The intrinsic anomalous Hall conductivity decreases rapidly with increasing impurity scattering, which is consistent with the characteristic variation of intrinsic Hall conductivities in the dirty-metal regime. These findings advance the understanding of electron scattering and the anomalous Hall effect in van der Waals magnets and would benefit the application of the Fe3GaTe2 in spintronics.

cond-mat.mtrl-sci↗

Anomalous properties of spark plasma sintered boron nitride solids

Hexagonal boron nitride (h-BN) is a brittle ceramic with a layered structure, however, recent experiments have suggested that inter-layer structural engineering could be key to new structural and functional properties. Here we report the scalable bulk synthesis of high-density crystalline h-BN solids, by using high-temperature spark plasma sintering (SPS) of h-BN powders, which show high values of mechanical strength, ductility, dielectric constant, thermal conductivity, and exceptional neutron radiation shielding capability. Through exhaustive characterizations we reveal that SPS induces non-basal plane crystallinity, twisting of layers, and facilitates inter-grain fusion with a high degree of in-plane alignment across macroscale dimensions, resulting in near-theoretical density and improved properties. Our findings highlight the importance of material design, via new approaches such as layer twisting and interlayer interconnections, to create novel ceramics with properties that could go beyond their intrinsic limits.

cond-mat.mtrl-sci↗

On-demand longitudinal transformations of light beams via an amplitude-phase-decoupled Pancharatnam-Berry phase element

Overcoming the inherent phase-only modulation limitation of conventional Pancharatnam-Berry (PB) elements, we propose a checkerboard-encoded PB element that enables simultaneous amplitude and phase modulation through PB phase engineering. This single-element platform directly generates polarization-rotating beams with continuously varying polarization angles along the propagation axis, eliminating traditional dynamic phase requirements. By strategically combining the proposed element with a liquid crystal q-plate and waveplates, we demonstrate on-demand longitudinal transformations of polarization states and high-order Poincaré sphere beams. Significantly, we achieve, for the first time to our knowledge, the propagation-transformed optical skyrmions, whose topological textures evolve with propagation distance. This amplitude-phase decoupling mechanism and the integration solution for various longitudinal transformations open new avenues in structured light manipulation, particularly benefiting quantum optics and topological photonics applications requiring longitudinal mode control.

physics.optics↗

Atomistic insight into the effects of solute and pressure on phase transformation in titanium alloys

The phase stability and transformation between hexagonal close-packed (hcp) α-phase and body-centered cubic (bcc) \b{eta}-phase in titanium (Ti) alloys are critical to their mechanical properties and manufacturing processes for engineering applications. However, many factors, both intrinsic and extrinsic (e.g., solute elements and external pressures, respectively), may govern their phase transformations dynamically, which is crucial to the design of new Ti alloys with desirable properties. In this work, we study the effects of various solute elements and external hydrostatic pressures on the solid-state phase transformations in Ti alloys using density functional theory (DFT) and nudged elastic band (NEB) calculations. The results show that both alloying and applied pressure reduce transformation barriers, with Al and Mo being most effective under ambient conditions, while Nb, V, Zr, and Sn show enhanced transformation kinetics under stress. Solute-induced modifications to the local electronic structure and bonding environment, particularly under pressure, contribute to variations in phase stability. We identify a synergistic interaction between solute effects and external stress, which facilitates phase transitions that are unachievable under static conditions. These findings provide atomistic insights into the coupled chemical-mechanical mechanisms underlying phase transformations in Ti alloys with improved phase stability and mechanical performance.

cond-mat.mtrl-sci↗