arXiv subjects

Yujiao Li

Publications and source records attributed to Yujiao Li.

8 recordsLinked to original sources

arXiv2026

A thermally grown SiO2 diffusion barrier enabling high-temperature investigation of Ag-Au-Pd-Pt thin films

Combinatorial processing platforms (CPPs), integrating Si microtip arrays with combinatorial thin film synthesis and atom probe tomography (APT), enable near-atomic-scale characterization of compositionally complex solid solutions (CCSSs) under diverse processing and reaction conditions, including oxidation, thermal phase stability and electrocatalytic reactions. Their application at elevated temperatures, however, can be limited when CCSS constituents such as Pd and Pt react with the Si support to form silicides. Although thermally grown SiO2 has proven effective as a diffusion barrier between pure Pt and Si, its performance for multicomponent CCSS thin films is unclear. Here, using Ag-Au-Pd-Pt as a model system, we compare a 25 nm thermally grown SiO2 barrier with native Si oxide during annealing using APT and transmission electron microscopy. Native Si oxide prevents detectable interfacial reactions up to 300{\deg}C, but at 400{\deg}C Pd and Pt react with Si, causing silicide formation and substantial redistribution of the film constituents. At 600{\deg}C, extensive substrate reactions disrupt the CCSS film and produce a pronounced needle-shaped silicide morphology. In contrast, thermally grown SiO2 suppresses CCSS thin film-substrate reactions up to 600{\deg}C and retains the CCSS composition. The thermally grown SiO2 thus extends the applicable temperature range of Si-based CPPs to at least 600{\deg}C for near-atomic-scale characterization of CCSS thin films.

cond-mat.mtrl-sci↗

arXiv2026

A hidden low-temperature transformation pathway in compositionally complex materials

Most compositionally complex materials (CCMs, frequently referred to as high entropy alloys) are metastable and their attractive properties often belong to kinetically trapped states. However, pathways towards lower-free-energy phase states governing long-term stability, can remain hidden because diffusion-controlled atomic redistribution is too slow to be revealed at experimentally accessible timescales. This blind spot is acute in CCM design: enormous compositional spaces are screened for performance, yet the low-temperature kinetics and the associated transformation pathways determining whether that performance persists are rarely considered in material selection. Here we use defect-rich nanoscale volumes coupled with atom-probe tomography to access and reconstruct the hidden phase-evolution pathway in a metastable Ag24Au20Pd50Pt6 electrocatalyst, without relying on elevated temperatures to accelerate the transformation. By varying microstructural starting state, annealing temperature and time, we reveal precipitation of a Pt-rich phase within the fcc matrix, its coarsening and re-homogenization. The Pt-rich phase recurs after homogenization with delayed kinetic accessibility, while prolonged annealing extends the pathway to 300{\deg}C. Atomistic simulations independently predict the same Pt-rich phase selection. The transformation is accompanied by a 3.7-fold loss of catalytic activity for hydrogen evolution. These results establish hidden phase-evolution pathways as a materials-design variable: resolving them can guide the selection of metastable CCMs not only for their as-synthesized properties, but also for the phase states and associated functionalities they may access over time.

cond-mat.mtrl-sci↗

arXiv2026

Understanding early stages of low-temperature hydrogen-driven direct co-reduction of Fe-Ni mixed oxide thin films at the near atomic scale

Kinetic understanding of hydrogen co-reduction of multinary and multi-phase oxides is of interest for enhancing sustainability of alloy production and transition to a hydrogen-based economy. Benefits include decrease in energy consumption, enhanced kinetics, and conversion of oxides to alloys. Thin films provide a platform to study these processes as reactive co-deposition from multiple elemental, alloy or compound targets and precise oxygen flow control allow atomic mixing into various oxide phases which are well-defined nanoscale precursor structures for the subsequent reduction study at the near atomic scale. The early stages of hydrogen direct reduction of oxide thin films are investigated using a Fe50Ni50Ox thin film consisting of NiFe2O4 and NiO phases. After reduction at 280 C in pure H2 for different times, structural, morphological, and nanoscale changes were examined by different characterisation methods including atom probe tomography (APT). The low-temperature reduction is nucleation-limited marked by grain-boundary nucleation preceded by an incubation time of more than 5 min. APT revealed that the early-stages of the reduction involves phase separation into a Ni-rich FexNiy metallic phase and a transformed remaining oxide (magnetite, Fe3O4). Further reduction induces magnetite reduction and alloying into a nearly equiatomic FeNi alloy. The low-temperature reduction and alloying are facilitated by synergetic effects from the nanostructure of the film, and Ni autocatalytic effects through alloying and hydrogen spillover. The results pave the way for low-temperature formation of Fe-Ni alloy thin films with tunable compositions directly from oxides, and broaden the scope of hydrogen direct reduction of multinary oxides to thin-film platforms.

cond-mat.mtrl-sci↗

arXiv2026

Influence of Ru content on electrocatalytic activity and defect formation of Au-Pd-Pt-Ru compositionally complex solid solution thin films

Compositionally complex solid solutions (CCSSs) consist of a randomly mixed single phase with the potential to enhance electrocatalytic activity through their polyelemental surface atom arrangements. However, microstructural complexity originating from multiple principal elements influences local structure, chemistry, and lattice strain, which might also affect electrocatalytic activity. Here, we investigate the effect of Ru content on electrochemistry and defect formation in Au-Pd-Pt-Ru CCSS thin films. Such defects could provide active sites when terminating at the CCSS surface or modify surface composition through preferential segregation. A thin-film material library covering a wide composition range was fabricated by room-temperature combinatorial co-sputtering. High-throughput compositional, structural and functional characterization, including electron microscopy equipped with energy dispersive X-ray spectroscopy, X-ray diffraction, and electrochemical screening, were used to correlate composition and microstructural features with catalytic activity. Three representative compositions selected from the library - Au68Pd13Pt15Ru4, Au27Pd24Pt23Ru26, and Au9Pd21Pt18Ru52 - were examined in detail. The three samples exhibit face-centered cubic structures, with lattice contraction occurring with increasing Ru content. In addition, with increasing Ru content, a transition from a high density of nanotwins to high-density, atomic-layer stacking faults was observed. Moreover, the hydrogen evolution reaction activity improves with higher Ru content. Atom probe tomography reveals local compositional fluctuations, including element-specific enrichment and depletion at grain boundaries. The findings provide a new insight into surface atom arrangement design in the CCSS electrocatalysts with enhanced performance.

cond-mat.mtrl-sci↗

arXiv2024

GACE: Learning Graph-Based Cross-Page Ads Embedding For Click-Through Rate Prediction

Predicting click-through rate (CTR) is the core task of many ads online recommendation systems, which helps improve user experience and increase platform revenue. In this type of recommendation system, we often encounter two main problems: the joint usage of multi-page historical advertising data and the cold start of new ads. In this paper, we proposed GACE, a graph-based cross-page ads embedding generation method. It can warm up and generate the representation embedding of cold-start and existing ads across various pages. Specifically, we carefully build linkages and a weighted undirected graph model considering semantic and page-type attributes to guide the direction of feature fusion and generation. We designed a variational auto-encoding task as pre-training module and generated embedding representations for new and old ads based on this task. The results evaluated in the public dataset AliEC from RecBole and the real-world industry dataset from Alipay show that our GACE method is significantly superior to the SOTA method. In the online A/B test, the click-through rate on three real-world pages from Alipay has increased by 3.6%, 2.13%, and 3.02%, respectively. Especially in the cold-start task, the CTR increased by 9.96%, 7.51%, and 8.97%, respectively.

cs.IR↗

arXiv2020

Solute hydrogen and deuterium observed at the near atomic scale in high-strength steel

Observing solute hydrogen (H) in matter is a formidable challenge, yet, enabling quantitative imaging of H at the atomic-scale is critical to understand its deleterious influence on the mechanical strength of many metallic alloys that has resulted in many catastrophic failures of engineering parts and structures. Here, we report on the APT analysis of hydrogen (H) and deuterium (D) within the nanostructure of an ultra-high strength steel with high resistance to hydrogen embrittlement. Cold drawn, severely deformed pearlitic steel wires (Fe-0.98C-0.31Mn-0.20Si-0.20Cr-0.01Cu-0.006P-0.007S wt.%, ε=3.1) contains cementite decomposed during the pre-deformation of the alloy and ferrite. We find H and D within the decomposed cementite, and at some interfaces with the surrounding ferrite. To ascertain the origin of the H/D signal obtained in APT, we explored a series of experimental workflows including cryogenic specimen preparation and cryogenic-vacuum transfer from the preparation into a state-of-the-art atom probe. Our study points to the critical role of the preparation, i.e. the possible saturation of H-trapping sites during electrochemical polishing, how these can be alleviated by the use of an outgassing treatment, cryogenic preparation and transfer prior to charging. Accommodation of large amounts of H in the under-stoichiometric carbide likely explains the resistance of pearlite against hydrogen embrittlement.

cond-mat.mtrl-sci↗

arXiv2018

Transaction Fraud Detection Using GRU-centered Sandwich-structured Model

Rapid growth of modern technologies such as internet and mobile computing are bringing dramatically increased e-commerce payments, as well as the explosion in transaction fraud. Meanwhile, fraudsters are continually refining their tricks, making rule-based fraud detection systems difficult to handle the ever-changing fraud patterns. Many data mining and artificial intelligence methods have been proposed for identifying small anomalies in large transaction data sets, increasing detecting efficiency to some extent. Nevertheless, there is always a contradiction that most methods are irrelevant to transaction sequence, yet sequence-related methods usually cannot learn information at single-transaction level well. In this paper, a new "within->between->within" sandwich-structured sequence learning architecture has been proposed by stacking an ensemble method, a deep sequential learning method and another top-layer ensemble classifier in proper order. Moreover, attention mechanism has also been introduced in to further improve performance. Models in this structure have been manifested to be very efficient in scenarios like fraud detection, where the information sequence is made up of vectors with complex interconnected features.

cs.CR↗

arXiv2016

Variable Total Variation Regularization for Backward Time-Space Fractional Diffusion Problem

In this paper, we consider a backward problem for a time-space fractional diffusion process. For this problem, we propose to construct the initial data by minimizing data residual error in fourier space domain and variable total variation (TV) regularizing term which can protect the edges as TV regularizing term and reduce staircasing effect. The well-posedness of this optimization problem is studied under a very general setting. Actually, we write the time-space fractional diffusion equation as an abstract fractional differential equation and get our results by using fractional semigroup theory, so our results can be applied to other backward problems for more general fractional differential equations. Then a modified Bregman iterative algorithm is proposed to approximate the minimizer. The new features of this algorithm is that the regularizing term changed in each step and we need not to solve the complexed Euler-Lagrange equations of variable TV regularizing term (just need to solve a simpler Euler-Lagrange equations). The convergence of this algorithm and the strategy of choosing parameters are also obtained. Numerical implementations are given to support our analysis to show the flexibility of our minimization model.

math.NA↗