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Atomic Emission Spectroscopy: Interference01:30

Atomic Emission Spectroscopy: Interference

In atomic emission spectroscopy (AES), high-temperature atomizers excite a broad range of elements and molecules that generate complex emissions from sources such as oxides, hydroxides, and flame combustion products in the flame or plasma. Several strategies can be employed to minimize spectral interferences caused by overlapping emission lines or bands. These include increasing instrument resolution, choosing alternative emission lines, optimally placing the detector in low-background regions,...
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AES is a powerful analytical technique, especially effective when used with plasma sources, producing abundant spectra in characteristic emission lines. The Inductively Coupled Plasma (ICP), in particular, yields superior quantitative analytical data due to its high stability, low noise, low background, and minimal interferences under optimal experimental conditions. However, newer air-operated microwave sources are emerging as promising alternatives that could be more cost-effective than...

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使用机器学习的原子间潜力探测带电的氧化阴极材料的表面降解路径.

Svenja Both1,2,3, Andrey D Poletayev3,4, Timo Danner1,2

  • 1German Aerospace Center, Institute of Engineering Thermodynamics, Ulm 89081, Germany.

ACS applied materials & interfaces
|September 25, 2025
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概括

研究人员研究了离子电池中基于的分层氧化物阴极的原子级降解. 他们发现了新的稳定的表面重建,并确定了离子迁移作为材料分解的关键步骤.

关键词:
离子电池是一种离子电池.富含的阴极材料是富含的.密度-功能理论密度-功能理论机器学习 原子间潜力表面退化 表面退化

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科学领域:

  • 材料科学 材料科学 材料科学
  • 电化学 电化学 电化学
  • 计算化学的计算化学

背景情况:

  • 基于的分层氧化物是离子电池的有希望的阴极材料,因为它们的能量密度很高.
  • 这些阴极在完全脱 (充电) 时的不稳定性限制了它们的实际应用.
  • 充电阴极降解的原子尺度机制仍然不太清楚.

研究的目的:

  • 阐明完全脱的氧化 (LiNiO2) 表面的原子级结构降解机制.
  • 为了确定稳定的表面重建和退化路径.
  • 了解氧气损失和阴极不稳定中的离子迁移的作用.

主要方法:

  • 使用高层次的初始计算来研究表面能量.
  • 机器学习的原子间潜力是为了分子动力学模拟而开发的.
  • 用分子动力学模拟来探索离子迁移和表面演变.

主要成果:

  • 确定了LiNiO2 (012) 面的以前未报告的稳定重建.
  • 与原始表面相比,这种重建显示出较低的氧空位形成能量.
  • 观察到 (Ni) 离子迁移到层部位是动力学上可信的降解启动步骤.

结论:

  • 发现的表面重建和容易丢失的氧气有助于充电基阴极的不稳定.
  • 离子迁移是表面降解过程中的关键早期步骤.
  • 这些发现为阴极材料分解提供了原子规模的见解,指导了未来的材料设计.