arXiv subjects

Yixing Zhao

Publications and source records attributed to Yixing Zhao.

4 recordsLinked to original sources

arXiv2026

Magneto-Structural Coupling Enables Cryogenic Cation Redistribution in a Spinel Oxide

Ionic transport in oxides is generally frozen at cryogenic temperatures, where thermal energy lies far below typical cation-migration barriers. Neutron powder diffraction reveals progressive Fe/Mg redistribution between tetrahedral (A) and octahedral (B) sites in the spinel Mg0.5Fe0.5TiFeO4 upon cooling from 200 K to 5 K. A-site Fe occupancy increases toward near completion at 5 K within Rietveld resolution, while Ti remains on the B site. This exchange coincides with complex magnetic correlations rather than a classical thermally activated window. Low-temperature magnetostrictive volume changes indicate strong spin-lattice coupling, but do not identify magnetostriction as the sole thermodynamic driver. Room-temperature high-pressure X-ray diffraction produces the opposite occupancy trend, showing that volume contraction alone cannot explain the cryogenic site exchange. These results point to magneto-structural free-energy minimization as a plausible mechanism for unlocking cryogenic cation mobility in a correlated spinel oxide.

cond-mat.mtrl-sci↗

arXiv2026

Regulating oxygen content and superconductivity in La$_3$Ni$_2$O$_{7+\delta}$

The synthesis of high-quality Ruddlesden-Popper (RP) nickelates remains challenging due to variations in oxygen content and the prevalence of intergrown RP phases. Precisely controlling the stoichiometry and characterizing the resulting physical properties are essential for understanding the mechanism of high-$T_c$ superconductivity in these materials. In this work, we synthesize a series of La$_3$Ni$_2$O$_{7+\delta}$ samples with systematically controlled oxygen content and perform comprehensive structural and compositional analyses. Precise oxygen tuning enables us to tailor the microstructure, yielding a pure bilayer phase, a mixture of bilayer and hybrid single-layer-bilayer phases, and a predominantly bilayer phase containing trilayer intergrowths. High-pressure transport measurements reveal distinct superconducting transitions with contrasting $T_c$ values, corresponding to the bilayer phase, the hybrid phase, and trilayer inclusions. Notably, we find that oxygen content not only governs the phase purity$-$i.e., the presence of intergrowth phases$-$but also directly modulates the upper critical field ($H_{c2}$) of the bilayer superconductivity. By establishing a phase diagram of $T_c$ and $H_{c2}$ as functions of oxygen content in La$_3$Ni$_2$O$_{7+\delta}$, this work advances synthetic control and provides new insights into the superconducting mechanism of RP nickelates.

cond-mat.supr-con↗

arXiv2024

BEV-TSR: Text-Scene Retrieval in BEV Space for Autonomous Driving

The rapid development of the autonomous driving industry has led to a significant accumulation of autonomous driving data. Consequently, there comes a growing demand for retrieving data to provide specialized optimization. However, directly applying previous image retrieval methods faces several challenges, such as the lack of global feature representation and inadequate text retrieval ability for complex driving scenes. To address these issues, firstly, we propose the BEV-TSR framework which leverages descriptive text as an input to retrieve corresponding scenes in the Bird's Eye View (BEV) space. Then to facilitate complex scene retrieval with extensive text descriptions, we employ a large language model (LLM) to extract the semantic features of the text inputs and incorporate knowledge graph embeddings to enhance the semantic richness of the language embedding. To achieve feature alignment between the BEV feature and language embedding, we propose Shared Cross-modal Embedding with a set of shared learnable embeddings to bridge the gap between these two modalities, and employ a caption generation task to further enhance the alignment. Furthermore, there lack of well-formed retrieval datasets for effective evaluation. To this end, we establish a multi-level retrieval dataset, nuScenes-Retrieval, based on the widely adopted nuScenes dataset. Experimental results on the multi-level nuScenes-Retrieval show that BEV-TSR achieves state-of-the-art performance, e.g., 85.78% and 87.66% top-1 accuracy on scene-to-text and text-to-scene retrieval respectively. Codes and datasets will be available.

cs.CV↗

arXiv2023

A Profit-Maximizing Strategy for Advertising on the e-Commerce Platforms

The online advertising management platform has become increasingly popular among e-commerce vendors/advertisers, offering a streamlined approach to reach target customers. Despite its advantages, configuring advertising strategies correctly remains a challenge for online vendors, particularly those with limited resources. Ineffective strategies often result in a surge of unproductive ``just looking'' clicks, leading to disproportionately high advertising expenses comparing to the growth of sales. In this paper, we present a novel profit-maximing strategy for targeting options of online advertising. The proposed model aims to find the optimal set of features to maximize the probability of converting targeted audiences into actual buyers. We address the optimization challenge by reformulating it as a multiple-choice knapsack problem (MCKP). We conduct an empirical study featuring real-world data from Tmall to show that our proposed method can effectively optimize the advertising strategy with budgetary constraints.

cs.IR↗