arXiv subjects

Xiaohui Yao

Publications and source records attributed to Xiaohui Yao.

11 recordsLinked to original sources

arXiv2026

Magneto-ionic control of topological transport in SrRuO3 via band topology engineering

The interplay between spin-orbit coupling (SOC) and nontrivial band topology in ferromagnets gives rise to a rich landscape of topological transport phenomena such as anomalous Hall effect (AHE) and topological Hall effect (THE). One central goal in modern spintronics lies in the realization of the active control over topological transport phenomena in a reversible fashion, while unambiguously disentangling respective contributions of THE and AHE to the net Hall effect remains a formidable challenge. Here we establish magneto ionic control as a powerful paradigm for dynamically engineering topological transports in a 4d-orbital SrRuO3 system with sizable SOC and itinerant ferromagnetism. Harnessing controllable protonation or oxygen vacancy incorporation, the Fermi-level upshift relative to avoided band crossings are realized through band filling control, giving rise to tunable reversal temperature of AHE polarity. Of particular note is the emergence of hump like Hall anomalies through extensive ionic doping that can be reversibly switched, irrespective of AHE polarity, providing evidence for a THE signal driven by broken inversion symmetry rather than a two channel AHE. Our findings provide a viable tuning knob for Berry curvature engineering, enabling on demand control of topological transports in strong SOC ferromagnets for low power, reconfigurable all oxide spintronic devices.

cond-mat.str-el↗

arXiv2026

Collective and separate metal-insulator transitions in correlated vanadium dioxide

Deciphering the complicated interplay between collective and separate behaviors lies at the heart of first-order metal-insulator transition (MIT) in correlated electron systems, enabling the rational design of exotic electronic states and functionalities. The critical balance between collective and separate behaviors defines a fundamental collective length scale, typically shorter than 5 nm, that governs emergent quantum orders, yet active control over this dichotomy remains elusive. Here, we realize on-demand manipulation of the collective and separate MIT within the correlated VO2 system in a reversible fashion. Artificially designing the oxygen deficiency in VO2/VO2-x homojunction fosters a collective MIT with an extended collective length scale, whereas the introduction of a TiO2 interlayer drives a crossover from this collective to a two-step separate MIT via decoupling of the electronic order parameter. Incorporating mobile hydrogens into the VO2/TiO2/VO2-x trilayer enables reversible control over electronic phase modulations, transitioning a two-step MIT towards either a one-step MIT or collective electron localization. This ionic control over the electronic band structure of VO2 flexibly triggers multi-state MIT, a process governed by hydrogen-related band filling. Our findings transform the collective length scale from a passive threshold into a dynamic design parameter, establishing a viable handle for engineering collective and separate MIT for adaptive correlated electronics.

cond-mat.str-el↗

arXiv2025

Multi-state electromagnetic phase modulations in NiCo2O4 through cation disorder and hydrogenation

One focal challenge in engineering low-power and scalable all-oxide spintronic devices lies in exploring ferromagnetic oxide material with perpendicular magnetic anisotropy (PMA) and electronic conductivity while exhibiting tunable spin states. Targeting this need, spinel nickel cobaltite (NiCo2O4, NCO), featured by room-temperature ferrimagnetically metallic ground state with strong PMA, emerges as a promising candidate in the field of oxide spintronics. The cation distribution disorder inherent to NCO renders competing electromagnetic states and abnormal sign reversal of anomalous Hall effect (AHE), introducing an additional freedom to adjust electromagnetic transports. Here, we unveil multi-state electromagnetic phase modulations in NCO system through controllable cation disorder and proton evolution, extensively expanding electromagnetic phase diagram. The cation disorder in NCO tunable by growth temperature is identified as a critical control parameter for kinetically adjusting the proton evolution, giving rise to intermediate hydrogenated states with chemical stability. Hydrogen incorporation reversibly drives structural transformation and electromagnetic state evolutions in NCO, with rich spin-dependent correlated physics uncovered by combining the AHE scaling relation and synchrotron-based spectroscopy. Our work not only establishes NCO as a versatile platform for discovering spin-dependent physical functionality but also extends the horizons in materials design for state-of-the-art spintronic devices harnessing magneto-ionic control and inherent cation disorder.

cond-mat.mtrl-sci↗

arXiv2025

Unveiling the critical role of interfacial strain in adjusting electronic phase transitions in correlated vanadium dioxide

Thermally activated abrupt switching between localized and itinerant electronic states during the insulator-metal transition (IMT) in correlated oxide systems serves as a powerful platform for exploring exotic physical phenomena and device functionality. One ongoing focal challenge lies in the realization of the broadly tunable IMT property in correlated system, to satisfy the demands of practical applications across diverse environments. Here, we unveil the overwhelming advantage associated with interfacial strain in bridging the bandwidth and band-filling control over the IMT property of VO2. Tailoring the orbital overlapping through strain-mediated bandwidth control enables a widely tunable thermally-driven IMT property in VO2. Benefiting from adjustable defect dynamics, filling-controlled Mott phase modulations from electron-localized t2g1eg0 state to electron-itinerant t2g1+Δeg0 state through oxygen vacancies can be facilitated by using in-plane tensile distortion, overcoming the high-speed bottlenecks in iontronic devices. Defect-engineered electronic phase transitions are primarily governed by the electron filling in t2g band of VO2, showcasing a definitive relationship with the incorporated defect concentration. Our findings provide fundamentally new insights into the on-demand design of emergent electronic states and transformative functionalities in correlated oxide system by unifying two fundamental control paradigms of bandwidth and band-filling control.

cond-mat.str-el↗

arXiv2025

Manipulating the metal-insulator transitions in correlated vanadium dioxide through bandwidth and band-filling control

The metal-insulator transition (MIT) in correlated oxide systems opens up a new paradigm to trigger the abruption in multiple physical functionalities, enabling the possibility in unlocking exotic quantum states beyond conventional phase diagram. Nevertheless, the critical challenge for practical device implementation lies in achieving the precise control over the MIT behavior of correlated system across a broad temperature range, ensuring the operational adaptability in diverse environments. Herein, correlated vanadium dioxide (VO2) serves as a model system to demonstrate effective modulations on the MIT functionality through bandwidth and band-filling control. Leveraging the lattice mismatching between RuO2 buffer layer and TiO2 substrate, the in-plane tensile strain states in VO2 films can be continuously adjusted by simply altering the thickness of buffer layer, leading to a tunable MIT property over a wide range exceeding 20 K. Beyond that, proton evolution is unveiled to drive the structural transformation of VO2, with a pronounced strain dependence, which is accompanied by hydrogenation-triggered collective carrier delocalization through hydrogen-related band filling in t2g band. The present work establishes an enticing platform for tailoring the MIT properties in correlated electron systems, paving the way for the rational design in exotic electronic phases and physical phenomena.

cond-mat.str-el↗

arXiv2025

Silicon-Compatible Ionic Control over Multi-State Magnetoelectric Phase Transformations in Correlated Oxide System

Realizing room-temperature ferromagnetic insulators, critical enablers for low-power spintronics, is fundamentally challenged by the long-standing trade-off between ferromagnetic ordering and indirect exchange interactions in insulators. Ionic evolution offers tempting opportunities for accessing exotic magnetoelectric states and physical functionality beyond conventional doping paradigm via tailoring the charge-lattice-orbital-spin interactions. Here, we showcase the precise magneto-ionic control over magnetoelectric states in LSMO system, delicately delivering silicon-compatible weakly ferromagnetic insulator state above room temperature. Of particular note is the decoupling of ion-charge-spin interplay in correlated LSMO system, a primary obstacle in clarifying underlying physical origin, with this process concurrently giving rise to an emergent intermediate state characterized by a weakly ferromagnetic half-metallic state. Benefiting from the SrTiO3 buffer layer as epitaxial template to promote interfacial heterogeneous nucleation, hydrogenation enables diverse magnetoelectric states in LSMO integrated on silicon, fully compatible with traditional semiconductor processing. Assisted by theoretical calculations and spectroscopic techniques, hydrogen-induced magnetoelectric transitions in LSMO are driven by band-filling control and suppression in double exchange interaction. Our work not only defines a novel design paradigm for exploring exotic quantum states in correlated system, with transformative potential for spintronics, but also fundamentally unveils the physical origin behind ionic evolution via disentangling the ion-charge-spin coupling.

cond-mat.mtrl-sci↗

arXiv2025

Topotactic phase transformation in correlated vanadium dioxide through oxygen vacancy ordering

Controlling the insulator-metal transition (IMT) in correlated oxide system through oxygen vacancy ordering opens up a new paradigm for exploring exotic structural transformation and physical functionality. Oxygen vacancy serves as a powerful tuning knob for adjusting the IMT property in VO2, though driving topochemical reduction to V2O3 remains challenging due to structural incompatibility and competing phase instability. Here we unveil consecutive oxygen-vacancy-driven VO2-VO2-x-V2O3 topotactic phase transformation route with enticing facet-dependent anisotropy, engendering tunable IMT properties over an extended temperature range. Remarkably, topochemically reduced V2O3 inherits the crystallographic characteristics from parent VO2, enabling emergent lattice framework and IMT behavior inaccessible via direct epitaxial growth. Analogous electron doping arising from hydrogenation and oxygen vacancy contributes cooperatively to drive the Mott phase transition in VO2 through band-filling control. Our work not only unveils sequential topotactic phase transformations in VO2 through oxygen vacancy ordering but also provides fundamentally new insights for defect-mediated Mott transitions.

cond-mat.mtrl-sci↗

arXiv2025

Manipulating the hydrogen-induced insulator-metal transition through artificial microstructure engineering

Hydrogen-associated filling-controlled Mottronics within electron-correlated system provides a groundbreaking paradigm to explore exotic physical functionality and phenomena. Dynamically controlling hydrogen-induced phase transitions through external fields offers a promising route for designing protonic devices in multidisciplinary fields, but faces high-speed bottlenecks owing to slow bulk diffusion of hydrogens. Here, we present a promising pathway to kinetically expedite hydrogen-related Mott transition in correlated VO2 system by taking advantage of artificial microstructure design. Typically, inclined domain boundary configuration and cR-faceted preferential orientation simultaneously realized in VO2/Al2O3 (102) heterostructure significantly lower the diffusion barrier via creating an unobstructed conduit for hydrogen diffusion. As a result, the achievable switching speed through hydrogenation outperforms that of counterpart grown on widely-reported c-plane Al2O3 substrate by 2-3 times, with resistive switching concurrently improved by an order of magnitude. Of particular interest, an anomalous uphill hydrogen diffusion observed for VO2 with a highway for hydrogen diffusion fundamentally deviates from basic Fick's law, unveiling a deterministic role of hydrogen spatial distribution in tailoring electronic state evolution. The present work not only provides a versatile strategy for manipulating ionic evolution, endowing with great potential in designing high-speed protonic devices, but also deepens the understanding of hydrogen-induced Mott transitions in electron-correlated system.

cond-mat.str-el↗

arXiv2025

Trustworthy Enhanced Multi-view Multi-modal Alzheimer's Disease Prediction with Brain-wide Imaging Transcriptomics Data

Brain transcriptomics provides insights into the molecular mechanisms by which the brain coordinates its functions and processes. However, existing multimodal methods for predicting Alzheimer's disease (AD) primarily rely on imaging and sometimes genetic data, often neglecting the transcriptomic basis of brain. Furthermore, while striving to integrate complementary information between modalities, most studies overlook the informativeness disparities between modalities. Here, we propose TMM, a trusted multiview multimodal graph attention framework for AD diagnosis, using extensive brain-wide transcriptomics and imaging data. First, we construct view-specific brain regional co-function networks (RRIs) from transcriptomics and multimodal radiomics data to incorporate interaction information from both biomolecular and imaging perspectives. Next, we apply graph attention (GAT) processing to each RRI network to produce graph embeddings and employ cross-modal attention to fuse transcriptomics-derived embedding with each imagingderived embedding. Finally, a novel true-false-harmonized class probability (TFCP) strategy is designed to assess and adaptively adjust the prediction confidence of each modality for AD diagnosis. We evaluate TMM using the AHBA database with brain-wide transcriptomics data and the ADNI database with three imaging modalities (AV45-PET, FDG-PET, and VBM-MRI). The results demonstrate the superiority of our method in identifying AD, EMCI, and LMCI compared to state-of-the-arts. Code and data are available at https://github.com/Yaolab-fantastic/TMM.

cs.AI↗

arXiv2024

MVKTrans: Multi-View Knowledge Transfer for Robust Multiomics Classification

The distinct characteristics of multiomics data, including complex interactions within and across biological layers and disease heterogeneity (e.g., heterogeneity in etiology and clinical symptoms), drive us to develop novel designs to address unique challenges in multiomics prediction. In this paper, we propose the multi-view knowledge transfer learning (MVKTrans) framework, which transfers intra- and inter-omics knowledge in an adaptive manner by reviewing data heterogeneity and suppressing bias transfer, thereby enhancing classification performance. Specifically, we design a graph contrastive module that is trained on unlabeled data to effectively learn and transfer the underlying intra-omics patterns to the supervised task. This unsupervised pretraining promotes learning general and unbiased representations for each modality, regardless of the downstream tasks. In light of the varying discriminative capacities of modalities across different diseases and/or samples, we introduce an adaptive and bi-directional cross-omics distillation module. This module automatically identifies richer modalities and facilitates dynamic knowledge transfer from more informative to less informative omics, thereby enabling a more robust and generalized integration. Extensive experiments on four real biomedical datasets demonstrate the superior performance and robustness of MVKTrans compared to the state-of-the-art. Code and data are available at https://github.com/Yaolab-fantastic/MVKTrans.

cs.LG↗

arXiv2020

Cognitive Biomarker Prioritization in Alzheimer's Disease using Brain Morphometric Data

Background:Cognitive assessments represent the most common clinical routine for the diagnosis of Alzheimer's Disease (AD). Given a large number of cognitive assessment tools and time-limited office visits, it is important to determine a proper set of cognitive tests for different subjects. Most current studies create guidelines of cognitive test selection for a targeted population, but they are not customized for each individual subject. In this manuscript, we develop a machine learning paradigm enabling personalized cognitive assessments prioritization. Method: We adapt a newly developed learning-to-rank approach PLTR to implement our paradigm. This method learns the latent scoring function that pushes the most effective cognitive assessments onto the top of the prioritization list. We also extend PLTR to better separate the most effective cognitive assessments and the less effective ones. Results: Our empirical study on the ADNI data shows that the proposed paradigm outperforms the state-of-the-art baselines on identifying and prioritizing individual-specific cognitive biomarkers. We conduct experiments in cross validation and level-out validation settings. In the two settings, our paradigm significantly outperforms the best baselines with improvement as much as 22.1% and 19.7%, respectively, on prioritizing cognitive features. Conclusions: The proposed paradigm achieves superior performance on prioritizing cognitive biomarkers. The cognitive biomarkers prioritized on top have great potentials to facilitate personalized diagnosis, disease subtyping, and ultimately precision medicine in AD.

q-bio.QM↗