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関連する概念動画

Reaction Quotient02:35

Reaction Quotient

47.9K
The status of a reversible reaction is conveniently assessed by evaluating its reaction quotient (Q). For a reversible reaction described by m A + n B ⇌ x C + y D, the reaction quotient is derived directly from the stoichiometry of the balanced equation as
47.9K
Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

9.1K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
9.1K
Predicting Products: SN1 vs. SN202:27

Predicting Products: SN1 vs. SN2

13.2K
Nucleophilic substitution reactions of alkyl halides can proceed via an SN1 or an SN2 mechanism. While in SN2 reactions, the nucleophile attacks the substrate simultaneously as the leaving group departs, in SN1 reactions, the substrate first dissociates to give the carbocation intermediate. Various factors such as the structure of the substrate, the strength of the nucleophile, and the nature of the solvent promote one mechanism over the other.
With increased substitution on the alkyl halide,...
13.2K
Crossed Aldol Reactions: Overview01:04

Crossed Aldol Reactions: Overview

5.4K
Crossed aldol addition is the reaction between two different carbonyl compounds under acidic or basic conditions. Here, both the carbonyl compounds function as nucleophiles and electrophiles. As shown in Figure 1, such a reaction yields a mixture of products, two of which are formed via self-condensation, while the remaining two are formed via crossed-condensation. Without adjustment, the reaction's usefulness in organic chemistry is decreased.
5.4K
Classification of Titrimetric Analysis Based on Reaction Types01:01

Classification of Titrimetric Analysis Based on Reaction Types

2.0K
Titrimetric analysis in solution chemistry involves measuring the volume of solutions and is often called volumetric analysis. The standard solution of known concentration in the burette is called the titrant, whereas the solution of unknown concentration in the flask is called the analyte, or titrand. Titrimetric analyses can be classified into four types based on the reactions between the titrant and analyte.
Titrations between an acid and a base lead to neutralization reactions that form...
2.0K
Catalysis01:27

Catalysis

10
Catalysis influences the rate of chemical reactions by providing an alternative reaction pathway with lower activation energy. A catalyst speeds up a reaction, but it is not consumed during the process. The fundamental principle of catalysis is the ability of a catalyst to alter the reaction mechanism, often introducing a more efficient pathway than the uncatalyzed process.In a catalyzed reaction, the catalyst participates directly in the reaction mechanism. It interacts with reactants to form...
10

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Network Pharmacology Prediction and Metabolomics Validation of the Mechanism of Fructus Phyllanthi against Hyperlipidemia
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"機械学習を用いたC-Nクロスカップリングにおける反応性能の予測"に関するコメントへの返信

Jesús G Estrada1, Derek T Ahneman1, Robert P Sheridan2

  • 1Department of Chemistry, Princeton University, Princeton, NJ 08544, USA.

Science (New York, N.Y.)
|November 17, 2018
PubMed
まとめ
この要約は機械生成です。

化学特性のモデルでは 汎用性のない代替品と比較して 優れた予測性能を示しています これは,データセットにおける機械学習パターンの抽出のための化学フィチュライゼーションの使用を検証します.

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科学分野:

  • コンピュータ化学
  • 機械学習アプリケーション
  • 予測モデリング

背景:

  • 非一般化可能なモデルは科学的な予測に課題をもたらす.
  • 機械学習における化学フィチュライゼーションの有用性は検証が必要です

研究 の 目的:

  • 化学特性のモデルと一般化できないモデルを区別する.
  • 化学特性モデルのサンプル外予測性能を評価する.

主な方法:

  • 予測モデルの比較分析
  • サンプルの外での予測の精度評価
  • 機械学習の化学特性を活用する

主要な成果:

  • 化学特性のモデルは,一般化できないモデルとは明らかに異なる.
  • 検体外予測における化学特性モデルの性能を大幅に上回る.
  • 有意義なデータパターンを抽出するための化学特性の検証.

結論:

  • 化学特性のモデルは 優れた予測力を提供します
  • 化学データセットにおける機械学習の 強力なアプローチです
  • 発見はパターンの抽出のための元の方法論を支持します.