paper-with-me

홈 › Papers

Discovering Features in Sr$_{14}$Cu$_{24}$O$_{41}$ Neutron Single Crystal Diffraction Data by Cluster Analysis

2018-09-13 · Yawei Hui, Yaohua Liu, Byung-Hoon Park

To address the SMC'18 data challenge, "Discovering Features in Sr$_{14}$Cu$_{24}$O$_{41}$", we have used the clustering algorithm "DBSCAN" to separate the diffuse scattering features from the Bragg peaks, which takes into account both spatial and photometric information in the dataset during in the clustering process. We find that, in additional to highly localized Bragg peaks, there exists broad diffuse scattering patterns consisting of distinguishable geometries. Besides these two distinctive features, we also identify a third distinguishable feature submerged in the low signal-to-noise region in the reciprocal space, whose origin remains an open question.

📄 PDF Abstract BibTeX arXiv:1809.05039

Code (0)

등록된 구현이 없습니다.

Tasks

ClusteringOpen-Ended Question Answering

Similar Papers 제목 키워드 기반

Wavelength-resolved neutron tomography for crystalline materials

2019-02-18

Wavelength-resolved (WR) neutron transmission tomography is an emerging technique to characterize engineering materials. While tomographic reconstruction for amorphous samples is straightforward, it is challenging to rec…

Autonomous Polycrystalline Material Decomposition for Hyperspectral Neutron Tomography

2023-02-27 · Mohammad Samin Nur Chowdhury, Diyu Yang, Shimin Tang, Singanallur V. Venkatakrishnan 외

Hyperspectral neutron tomography is an effective method for analyzing crystalline material samples with complex compositions in a non-destructive manner. Since the counts in the hyperspectral neutron radiographs directly…

Paradigm shift in electron-based crystallography via machine learning

2019-02-10 · Kevin Kaufmann, Chaoyi Zhu, Alexander S. Rosengarten, Daniel Maryanovsky 외

Accurately determining the crystallographic structure of a material, organic or inorganic, is a critical primary step in material development and analysis. The most common practices involve analysis of diffraction patter…

BIG-bench Machine Learning

Artifact Identification in X-ray Diffraction Data using Machine Learning Methods

2022-07-29 · Howard Yanxon, James Weng, Hannah Parraga, Wenqian Xu 외

The in situ synchrotron high-energy X-ray powder diffraction (XRD) technique is highly utilized by researchers to analyze the crystallographic structures of materials in functional devices (e.g., battery materials) or in…

BIG-bench Machine Learning

Autonomous Diffractometry Enabled by Visual Reinforcement Learning

2026-04-13 · J. Oppliger, M. Stifter, A. Rüegg, I. Biało 외 arxiv

Automation underpins progress across scientific and industrial disciplines. Yet, automating tasks requiring interpretation of abstract visual information remain challenging. For example, crystal alignment strongly relies…

Reinforcement Learning