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相关概念视频

Voltammetry: Stripping Methods01:13

Voltammetry: Stripping Methods

177
Anodic Stripping Voltammetry (ASV), Cathodic Stripping Voltammetry (CSV), and Adsorptive Stripping Voltammetry (AdSV) are electrochemical techniques used to determine trace amounts of analytes in solution. These methods involve applying a potential to an electrode and measuring the resulting current.
Anodic Stripping Voltammetry (ASV)
ASV is used to determine metals and metalloids at trace levels. It involves two steps: deposition and stripping. First, a negative potential is applied to the...
177
Voltammetry: Overview01:20

Voltammetry: Overview

1.2K
Voltammetry is an electroanalytical technique in which the current flowing through an electrochemical cell is measured as a function of applied potential, typically under conditions of concentration polarization. The technique provides valuable information about redox-active species, and the current response is plotted as a voltammogram.
A voltammetric cell uses three electrodes: a working electrode, a reference electrode, and an auxiliary electrode. The redox reactions occur in the working...
1.2K
Electrogravimetric Analysis: Overview01:30

Electrogravimetric Analysis: Overview

202
Electrogravimetric analysis measures the weight of an analyte deposited electrolytically onto a suitable working electrode. This method involves applying a potential to a pre-weighed electrode submerged in a solution, which results in the desired substance being deposited through reduction at the cathode or oxidation at the anode. The electrode's weight is recorded after deposition, and the difference in weight gives the analyte's weight in the solution.
To test the completeness of the...
202
Electrodeposition01:08

Electrodeposition

597
Electrodeposition is a technique used to separate an analyte from interferents by electrochemical processes. Here, the analyte is a metal ion that can be deposited on an electrode immersed in the sample solution. The electrochemical setup consists of an anode and a cathode. When an electric current is applied to the setup, oxidation occurs at the anode. At the cathode, which consists of a large metal surface, metal ions undergo reduction and deposit onto the surface.
Electrodeposition can...
597
Voltammetric Techniques: Cyclic Voltammetry01:10

Voltammetric Techniques: Cyclic Voltammetry

368
Cyclic voltammetry (CV) is an electrochemical technique used to investigate the redox properties of a chemical species. It involves measuring the current response of an electrochemical cell as a function of the applied potential. The setup for cyclic voltammetry typically consists of a working electrode, a reference electrode, and a counter electrode—all immersed in an electrolyte solution. The working electrode is where the redox reaction of interest occurs, while the reference electrode...
368
Controlled-Potential Coulometry: Electrolytic Methods01:17

Controlled-Potential Coulometry: Electrolytic Methods

136
Controlled-potential coulometry, also known as potentiostatic coulometry, employs a three-electrode system in which the working electrode's potential is precisely regulated using a potentiostat. Platinum working electrodes are utilized for positive potentials, while mercury pool electrodes are favored for extremely negative potentials. The platinum counter electrode is separated from the analyte using a membrane or salt bridge to avoid interference in the analysis.
The chosen potential...
136

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Three-electrode Coin Cell Preparation and Electrodeposition Analytics for Lithium-ion Batteries
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电压采矿用于 (脱) 稳定阴极和离子阴极电压的机器学习模型.

Haoming Howard Li1, Qian Chen2, Gerbrand Ceder1,2

  • 1Department of Material Science and Engineering, University of California, Berkeley, California 94720, United States.

ACS applied materials & interfaces
|December 9, 2024
PubMed
概括

研究人员探索了用于先进电池的无正极材料. 他们确定了高压阴极的设计原则,并开发了一种用于准确预测电压的机器学习模型,推动了电池材料的发现.

关键词:
离子电池是一种离子电池.电池电压电池电压的电压.阴极是天主体,它们是天主体.数据挖掘是数据挖掘的一个方法.机器学习是机器学习.设计材料设计材料的设计.

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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
  • 计算化学计算化学

背景情况:

  • 金属阳极引发了人们对无阴极的发现的兴趣.
  • 商业离子电池阴极在放电状态下是稳定的,与在充电状态下发现的许多无候选人不同.

研究的目的:

  • 分析无和商业阴极材料的电压分布.
  • 建立用于高压阴极发现的设计原则.
  • 开发和验证用于预测阴极电压的机器学习模型.

主要方法:

  • 计算了5577个充电状态和2423个放电状态的独特结构对的阴极电压数据.
  • 基于氧化还原对和离子类型的电压分布分析.
  • 训练机器学习模型使用化学公式进行电压预测.

主要成果:

  • 高压阴极更倾向于4期后期的过渡金属和电负离子 (例如,聚离子).
  • 充电状态阴极通常比化对应物具有较低的电压,与离子分布相关的偏差.
  • 与Roost和Crab.Net相比,开发的机器学习模型实现了最先进的性能.

结论:

  • 确定了高压无阴极的关键设计原则.
  • 机器学习为预测正极电压和加速材料发现提供了一个强大的工具.
  • 了解离子分布对于预测正极电压行为至关重要.