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相关概念视频

Oxidation Numbers03:14

Oxidation Numbers

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In redox reactions, the transfer of electrons occurs between reacting species. Electron transfer is described by a hypothetical number called the oxidation number (or oxidation state). It represents the effective charge of an atom or element, which is assigned using a set of rules.
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Oxidation-Reduction Reactions03:11

Oxidation-Reduction Reactions

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Oxidation–Reduction Reactions
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Classifying Matter by Composition03:35

Classifying Matter by Composition

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Matter: Pure Substances and Mixtures
According to its composition, the matter can be classified into two broad categories — pure substances and mixtures. 
A pure substance is a form of matter that has a constant composition throughout with uniform properties. For example, any sample of sucrose has the same composition and same physical properties, such as melting point, color, and sweetness, regardless of the source from which it is isolated. 
A mixture is composed of two or...
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Oxidation and Reduction of Organic Molecules01:19

Oxidation and Reduction of Organic Molecules

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Energy production within a cell involves many coordinated chemical pathways. Most of these pathways are combinations of oxidation and reduction reactions, which occur at the same time. An oxidation reaction strips an electron from an atom in a compound, and the addition of this electron to another compound is a reduction reaction. Because oxidation and reduction usually occur together, these pairs of reactions are called redox reactions.
The removal of an electron from a molecule, results in a...
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Classification of Elements and Compounds02:54

Classification of Elements and Compounds

66.7K
Pure substances consist of only one type of matter. A pure substance can be an element or a compound. An element consists of only one type of atom, while a compound consists of two or more types of atoms held together by a chemical bond. Elements are classified as atomic or molecular based on the nature of their basic units.
Compounds are pure substances composed of two or more elements in fixed, definite proportions. Compounds are classified as ionic or molecular (covalent) based on the bonds...
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Oxidation of Alkenes: Syn Dihydroxylation with Potassium Permanganate02:21

Oxidation of Alkenes: Syn Dihydroxylation with Potassium Permanganate

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Alkenes can be dihydroxylated using potassium permanganate.  The method encompasses the reaction of an alkene with a cold, dilute solution of potassium permanganate under basic conditions to form a cis-diol along with a brown precipitate of manganese dioxide.
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使用深度学习语言模型对材料的基于组成的氧化状态预测.

Nihang Fu1, Jeffrey Hu1,2, Ying Feng3

  • 1Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, 29201, USA.

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概括
此摘要是机器生成的。

预测无机化合物的氧化状态 (OS) 现在可以使用一种新的深度学习模型,BERTOS. 这种人工智能方法只从化学成分准确地确定OS,有助于发现新材料.

关键词:
深度学习是一种深度学习.语言模型语言模型材料的发现发现.材料选 材料选 材料选 材料选神经网络的神经网络的神经网络氧化状态是指氧化状态.变压器的变压器是一个变压器.

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科学领域:

  • 计算材料科学 计算材料科学
  • 化学领域的人工智能
  • 对无机化合物的预测建模.

背景情况:

  • 氧化状态 (OS) 对于理解化学性质和材料行为至关重要.
  • 目前用于预测操作系统的方法依赖于启发式规则,但有许多例外,限制了准确性.
  • 现有的机器学习模型主要关注金属离子,需要结构信息.

研究的目的:

  • 开发一种新的深度学习模型,用于预测无机化合物中所有元素的氧化状态.
  • 为了使基于组合的氧化状态预测,消除了确定晶体结构的需要.
  • 促进对假设材料的大规模选,以加速材料发现.

主要方法:

  • 基于深度学习的新型BERT转换器语言模型的实施,称为BERTOS.
  • 培训和比较BERTOS模型在清理的无机晶体结构数据库 (ICSD) 上.
  • 评估模型的准确性,以预测所有元素的氧化状态,特别是氧化物材料.

主要成果:

  • 在ICSD数据集上,BERTOS在所有元素的氧化状态预测方面实现了96.82%的准确性.
  • 该模型在预测氧化物材料中的氧化状态方面表现出高精度 (97.61%).
  • 该研究展示了BERTOS在选假设材料组成中的实用性.

结论:

  • 伯托斯模型提供了一个高度准确的,基于成分的方法,用于预测无机化合物的氧化状态.
  • 这种方法克服了启发式规则和结构依赖模型的局限性.
  • 伯托斯通过快速计算选,显著提升了发现新材料的潜力.