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3,336 results on '"Chen, Xiaobo"'

51. Composition-dependent ordering transformations in Pt–Fe nanoalloys

Author

Chen, Xiaobo, Zhang, Siming, Li, Can, Liu, Zhijuan, Sun, Xianhu, Cheng, Shaobo, Zakharov, Dmitri N, Hwang, Sooyeon, Zhu, Yimei, Fang, Jiye, Wang, Guofeng, and Zhou, Guangwen

Subjects
Macromolecular and Materials Chemistry, Chemical Sciences, Physical Sciences, Pt–Fe nanoparticles, alloy composition, chemical ordering, in situ electron microscopy
Abstract

SignificanceDynamically understanding the microscopic processes governing ordering transformations has rarely been attained. The situation becomes even more challenging for nanoscale alloys, where the significantly increased surface-area-to-volume ratio not only opens up a variety of additional freedoms to initiate an ordering transformation but also allows for kinetic interplay between the surface and bulk due to their close proximity. We provide direct evidence of the microscopic processes controlling the ordering transformation through the surface-bulk interplay in Pt-Fe nanoalloys and new features rendered by variations in alloy composition and chemical stimuli. These results provide a mechanistic detail of ordering transformation phenomena which are widely relevant to nanoalloys as chemical ordering occurs in most multicomponent materials under suitable environmental bias.

Published
2022

93. Brain Network Construction and Classification Toolbox (BrainNetClass)

Author

Zhou, Zhen, Chen, Xiaobo, Zhang, Yu, Qiao, Lishan, Yu, Renping, Pan, Gang, Zhang, Han, and Shen, Dinggang

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Brain functional network has become an increasingly used approach in understanding brain functions and diseases. Many network construction methods have been developed, whereas the majority of the studies still used static pairwise Pearson's correlation-based functional connectivity. The goal of this work is to introduce a toolbox namely "Brain Network Construction and Classification" (BrainNetClass) to the field to promote more advanced brain network construction methods. It comprises various brain network construction methods, including some state-of-the-art methods that were recently developed to capture more complex interactions among brain regions along with connectome feature extraction, reduction, parameter optimization towards network-based individualized classification. BrainNetClass is a MATLAB-based, open-source, cross-platform toolbox with graphical user-friendly interfaces for cognitive and clinical neuroscientists to perform rigorous computer-aided diagnosis with interpretable result presentations even though they do not possess neuroimage computing and machine learning knowledge. We demonstrate the implementations of this toolbox on real resting-state functional MRI datasets. BrainNetClass (v1.0) can be downloaded from https://github.com/zzstefan/BrainNetClass.

Published
2019
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95. A Comprehensive Performance Evaluation for 3D Transformation Estimation Techniques

Author

Zhao, Bao, Chen, Xiaobo, Le, Xinyi, and Xi, Juntong

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

3D local feature extraction and matching is the basis for solving many tasks in the area of computer vision, such as 3D registration, modeling, recognition and retrieval. However, this process commonly draws into false correspondences, due to noise, limited features, occlusion, incomplete surface and etc. In order to estimate accurate transformation based on these corrupted correspondences, numerous transformation estimation techniques have been proposed. However, the merits, demerits and appropriate application for these methods are unclear owing to that no comprehensive evaluation for the performance of these methods has been conducted. This paper evaluates eleven state-of-the-art transformation estimation proposals on both descriptor based and synthetic correspondences. On descriptor based correspondences, several evaluation items (including the performance on different datasets, robustness to different overlap ratios and the performance of these technique combined with Iterative Closest Point (ICP), different local features and LRF/A techniques) of these methods are tested on four popular datasets acquired with different devices. On synthetic correspondences, the robustness of these methods to varying percentages of correct correspondences (PCC) is evaluated. In addition, we also evaluate the efficiencies of these methods. Finally, the merits, demerits and application guidance of these tested transformation estimation methods are summarized.

Published
2019

97. Atomic-scale phase separation induced clustering of solute atoms.

Author

Zou, Lianfeng, Cao, Penghui, Lei, Yinkai, Zakharov, Dmitri, Sun, Xianhu, House, Stephen D, Luo, Langli, Li, Jonathan, Yang, Yang, Yin, Qiyue, Chen, Xiaobo, Li, Chaoran, Qin, Hailang, Stach, Eric A, Yang, Judith C, Wang, Guofeng, and Zhou, Guangwen

Abstract

Dealloying typically occurs via the chemical dissolution of an alloy component through a corrosion process. In contrast, here we report an atomic-scale nonchemical dealloying process that results in the clustering of solute atoms. We show that the disparity in the adatom-substrate exchange barriers separate Cu adatoms from a Cu-Au mixture, leaving behind a fluid phase enriched with Au adatoms that subsequently aggregate into supported clusters. Using dynamic, atomic-scale electron microscopy observations and theoretical modeling, we delineate the atomic-scale mechanisms associated with the nucleation, rotation and amorphization-crystallization oscillations of the Au clusters. We expect broader applicability of the results because the phase separation process is dictated by the inherent asymmetric adatom-substrate exchange barriers for separating dissimilar atoms in multicomponent materials.

Published
2020

98. Surface-reaction induced structural oscillations in the subsurface

Author

Sun, Xianhu, Zhu, Wenhui, Wu, Dongxiang, Li, Chaoran, Wang, Jianyu, Zhu, Yaguang, Chen, Xiaobo, Boscoboinik, Jorge Anibal, Sharma, Renu, and Zhou, Guangwen

Subjects
Physical Sciences, Engineering, Chemical Sciences, Physical Chemistry
Abstract

Surface and subsurface are commonly considered as separate entities because of the difference in the bonding environment and are often investigated separately due to the experimental challenges in differentiating the surface and subsurface effects. Using in-situ atomic-scale transmission electron microscopy to resolve the surface and subsurface at the same time, we show that the hydrogen-CuO surface reaction results in structural oscillations in deeper atomic layers via the cycles of ordering and disordering of oxygen vacancies in the subsurface. Together with atomistic calculations, we show that the structural oscillations in the subsurface are induced by the hydrogen oxidation-induced cyclic loss of oxygen from the oxide surface. These results demonstrate the propagation of the surface reaction dynamics into the deeper layers in inducing nonstoichiometry in the subsurface and have significant implications in modulating various chemical processes involving surface-subsurface mass transport such as heterogeneous catalysis, oxidation, corrosion and carburization.

Published
2020

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