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Related Concept Videos

Sampling Plans01:23

Sampling Plans

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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...
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Designing and plotting a curve using field data requires precise calculations and execution. A horizontal curve with a radius of 200 meters and an intersection angle of 20 degrees is established using the method of perpendicular offsets from the long chord. The long chord, which spans between the curve's endpoints, is calculated to be 69.46 meters in length. To maintain accuracy in plotting, intervals of 3 meters are selected along the chord.The engineer determines the offset distances for each...
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Related Experiment Video

Updated: May 23, 2025

Hierarchical and Programmable One-Pot Oligosaccharide Synthesis
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ASKCOS: Open-Source, Data-Driven Synthesis Planning.

Zhengkai Tu1, Sourabh J Choure2, Mun Hong Fong2

  • 1Department of Electrical Engineering and Computer Science, MIT, Cambridge, Massachusetts 02139, United States.

Accounts of Chemical Research
|May 21, 2025
PubMed
Summary
This summary is machine-generated.

Data-driven models and machine learning are advancing computer-aided synthesis planning (CASP). The ASKCOS software suite integrates retrosynthetic planning, condition prediction, and outcome prediction for practical synthesis route ideation.

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Area of Science:

  • * Computational chemistry and cheminformatics.
  • * Organic synthesis and reaction informatics.

Background:

  • * Machine learning and large reaction datasets have accelerated data-driven computer-aided synthesis planning (CASP).
  • * Bridging the gap between research and practical application is crucial for advancing chemical synthesis.

Purpose of the Study:

  • * To describe data-driven methods and models in the newest version of ASKCOS, an open-source synthesis planning software.
  • * To highlight the integration of various modules for comprehensive synthesis planning capabilities.

Main Methods:

  • * Integration of modules for retrosynthetic planning (Interactive Path Planner, Tree Builder with MCTS and Retro*).
  • * Utilization of four one-step retrosynthesis models (template-based and template-free).
  • * Development of capabilities for reaction condition, pathway, and outcome prediction (major product, impurities, selectivity).

Main Results:

  • * ASKCOS integrates retrosynthesis, condition prediction, and outcome prediction modules.
  • * Auxiliary capabilities include solubility and quantum mechanical descriptor prediction.
  • * The software provides user-friendly interfaces for chemists.

Conclusions:

  • * ASKCOS assists chemists in daily tasks by complementing expert decision-making and route ideation.
  • * Computer-aided synthesis planning tools are increasingly important and accessible in modern chemistry research.
  • * The integration of diverse data-driven methods enhances the utility of CASP software.