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相关概念视频

Sampling Plans01:23

Sampling Plans

866
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
866
Random Sampling Method01:09

Random Sampling Method

14.0K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
14.0K
Sampling Methods: Overview01:06

Sampling Methods: Overview

2.1K
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
2.1K
VSEPR Theory02:37

VSEPR Theory

13.9K
Valence shell electron-pair repulsion theory (VSEPR theory) enables us to predict the molecular structure around a central atom from an examination of the number of bonds and lone electron pairs in its Lewis structure. The VSEPR model assumes that electron pairs in the valence shell of a central atom will adopt an arrangement that minimizes repulsions between these electron pairs by maximizing the distance between them. The electrons in the valence shell of a central atom form either bonding...
13.9K
Chemical Shift: Internal References and Solvent Effects01:17

Chemical Shift: Internal References and Solvent Effects

1.2K
In an NMR sample, precise measurement of the absolute absorption frequencies of nuclei is difficult. A standard internal reference compound is added, and the frequency difference between the reference signal and sample signals is measured.
The internal reference compound generally used in NMR spectroscopy is tetramethylsilane (TMS). TMS is preferred because it is chemically inert, soluble in NMR solvents, and easily removable. Also, the highly shielded methyl protons in TMS yield an intense...
1.2K
Molecular Models02:00

Molecular Models

43.4K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
43.4K

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相关实验视频

Updated: Jan 9, 2026

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

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化学空间的代表性随机抽样.

Diego J Monterrubio-Chanca1,2, Guido Falk von Rudorff1,2

  • 1Institut für Chemie, Universität Kassel, 34109 Kassel, Germany.

Journal of chemical theory and computation
|December 2, 2025
PubMed
概括

探索广的化学空间是具有挑战性的,因为分子的数量庞大. 本研究引入了一种用于无偏的采样和化学空间大小估计的方法,使得代表性数据库分析成为可能.

科学领域:

  • 计算化学和化学信息学.
  • 数据科学和机器学习在化学中的应用.

背景情况:

  • 化学空间的广,所有可能的分子的集合,阻止了全面的探索,并导致当前数据库中偏见的采样.
  • 分析化学空间的现有方法受到无法列举所有分子的限制,这阻碍了数据驱动的表征.
  • 当前分子数据库中的大量偏差限制了它们对真正化学空间的代表性.

研究的目的:

  • 开发一种方法,在不列出所有分子的情况下,生成化学空间的无偏,代表性的随机样本.
  • 为了使任何定义的定制化学空间内的分子总数的估计.
  • 评估现有的分子数据库的代表性,并建立它们的大小标准.

主要方法:

  • 这是一种新的方法,用于生成化学空间的无偏随机样本,适用于可以用图形表示的分子.
  • 有效的算法可扩展到多达30个原子的分子.
  • 估计定制化学空间大小的方法.

主要成果:

  • 开发的方法允许对化学空间进行无偏的采样和尺寸估计.
  • 这种方法在计算上是高效的,即使对于中等大小的分子.
  • 对当前数据库的分析揭示了它们的代表性,并为数据库大小设定了下限,以确保代表性.

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相关实验视频

Last Updated: Jan 9, 2026

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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

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结论:

  • 这项工作为客观地探索和描述化学空间提供了一个强大的工具.
  • 这些发现为构建具有代表性的分子数据库提供了标准,对于数据驱动的发现至关重要.
  • 该方法有助于更准确地了解化学多样性和数据库限制.