Suppr超能文献

光谱中子成像的前景:优化电池电解质研究中的实验装置

Prospects of spectroscopic neutron imaging: optimizing experimental setups in battery electrolyte research.

作者信息

Carreón Ruiz E Ricardo, Stalder Natalie, Lee Jongmin, Gubler Lorenz, Boillat Pierre

机构信息

Electrochemistry Laboratory (LEC), Paul Scherrer Institut (PSI), 5232 Villigen PSI, Switzerland.

Laboratory for Neutron Scattering and Imaging (LNS), Paul Scherrer Institut (PSI), 5232 Villigen PSI, Switzerland.

出版信息

Phys Chem Chem Phys. 2023 Sep 20;25(36):24993-25007. doi: 10.1039/d3cp03434h.

Abstract

Spectral neutron imaging methods provide valuable insights into the characterization of hydrogenous materials, including battery electrolytes. However, their application is constrained by sample geometry, setup parameters, and material chemistries, especially when studying physico-chemical changes in battery electrolytes. To address these limitations, we present a framework for simulating and optimizing the investigation of hydrogenous materials. Our approach combines quantitative modeling with experimental data to predict and optimize the contrast achievable in wavelength-resolved neutron imaging methods, thereby maximizing the information obtained in specific neutron imaging setups. While initially demonstrated at the BOA beamline of the Paul Scherrer Institute, this framework is applicable to any continuous source with spectral neutron imaging capabilities with a chopper disk. This work establishes a pathway for accurate studies of hydrogenous materials and their physico-chemical behavior, paving the way for advancements in the field of material characterization with wavelength-resolved neutron imaging.

摘要

光谱中子成像方法为含氢材料(包括电池电解质)的表征提供了有价值的见解。然而,其应用受到样品几何形状、设置参数和材料化学性质的限制,特别是在研究电池电解质的物理化学变化时。为了解决这些限制,我们提出了一个用于模拟和优化含氢材料研究的框架。我们的方法将定量建模与实验数据相结合,以预测和优化波长分辨中子成像方法中可实现的对比度,从而在特定的中子成像设置中最大化获得的信息。虽然最初是在保罗·谢勒研究所的BOA光束线进行演示的,但该框架适用于任何具有斩光盘的具有光谱中子成像能力的连续源。这项工作为准确研究含氢材料及其物理化学行为建立了一条途径,为波长分辨中子成像材料表征领域的进步铺平了道路。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验