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相关概念视频

Inductively Coupled Plasma-Mass Spectrometry (ICP-MS): Interferences01:20

Inductively Coupled Plasma-Mass Spectrometry (ICP-MS): Interferences

421
Inductively coupled plasma–mass spectrometry (ICP–MS) is a highly selective and sensitive technique for accurate elemental analysis. Though the analysis of ICP–MS mass spectra is comparatively straightforward, it is affected by spectroscopic and non-spectroscopic interferences. Spectroscopic interferences arise when the plasma contains ionic species with an m/z value the same as the analyte ion. Spectroscopic interference can be categorized as isobaric, polyatomic ions, and...
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The Effect of Charging and Discharging Lithium Iron Phosphate-graphite Cells at Different Temperatures on Degradation
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一种可解释的离子电池容量预测方法,考虑到环境干扰.

Zijiang Yang1,2, Hongquan Zhang3,4

  • 1College of Electronic Engineering, Heilongjiang University, Harbin, 150080, China.

Scientific reports
|August 17, 2024
PubMed
概括

本研究引入了一种可解释的离子电池 (LIB) 容量预测方法,提高了准确性和理解力,即使在环境干扰的情况下也是如此. IM-EI模型提供了强大而精确的LIB业绩洞察力.

关键词:
信念规则的基础是信念规则.预测产能 预测产能环境干扰 环境干扰可以解释性 解释性离子电池是离子电池的一种.

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Identification and Quantification of Decomposition Mechanisms in Lithium-Ion Batteries; Input to Heat Flow Simulation for Modeling Thermal Runaway
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科学领域:

  • 电化学 电化学 电化学
  • 材料科学 材料科学 材料科学
  • 人工智能的人工智能

背景情况:

  • 准确的离子电池 (LIB) 容量预测对于安全运行和寿命延长至关重要.
  • 环境干扰可以显著降低预测的准确性.
  • 模型的解释性对于用户的信任和LIB管理中的决策至关重要.

研究的目的:

  • 开发一种可解释的方法来预测LIB容量,以考虑环境干扰.
  • 提高LIB容量预测模型的精度和可解释性.

主要方法:

  • 引入了考虑环境干扰 (IM-EI) 的可解释方法.
  • 使用了斯皮尔曼相关系数,可解释性原则和具有可解释性约束的信念规则基础 (BRB).
  • 集成的动态属性可靠性,以减轻环境干扰效应.

主要成果:

  • 与现有模型相比,IM-EI模型显示出更高的解释性和预测精度.
  • 该模型在环境干扰条件下也保持了良好的精度和稳定性.

结论:

  • 拟议的IM-EI方法有效地解决了LIB容量预测中的环境干扰.
  • 该研究强调了可解释性与准确性对实际LIB应用的重要性.