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Related Concept Videos

¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are slanted or...
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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¹H NMR: Long-Range Coupling01:27

¹H NMR: Long-Range Coupling

The coupling interactions of nuclei across four or more bonds are usually weak, with J values less than 1 Hz. While these are usually not observed in spectra, the presence of multiple bonds along the coupling pathway can result in observable long-range coupling.
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Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
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Cluster expansions in multicomponent systems: precise expansions from noisy databases.

Alejandro Díaz-Ortiz1, Helmut Dosch, Ralf Drautz

  • 1Max-Planck-Institut für Metallforschung, Heisenbergstraße 3, D-70569 Stuttgart, Germany.

Journal of Physics. Condensed Matter : an Institute of Physics Journal
|November 4, 2011
PubMed
Summary
This summary is machine-generated.

Numerical errors in alloy databases significantly impact cluster expansion models. A new selection criterion filters noise, ensuring more accurate predictions for multicomponent alloys.

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Area of Science:

  • Materials Science
  • Computational Materials Science
  • Alloy Theory

Background:

  • Cluster expansions are crucial for modeling multicomponent alloys.
  • Numerical errors in input databases can compromise model accuracy.
  • Effective cluster interactions and expansion determination are sensitive to data quality.

Purpose of the Study:

  • To systematically analyze numerical errors in alloy databases for cluster expansions.
  • To evaluate the impact of database size and content on expansion accuracy.
  • To develop a robust selection criterion for reliable cluster expansions.

Main Methods:

  • Systematic analysis of numerical errors in cluster expansion databases.
  • Investigation of cross-validation limitations.
  • Development and application of a combined forecasting and physical behavior selection criterion.

Main Results:

  • Numerical noise critically affects effective cluster interactions and expansion outcomes.
  • Cross-validation alone can yield unphysical expansions with long-range coefficients.
  • The proposed criterion effectively filters noise and ensures physical behavior.

Conclusions:

  • Database quality is paramount for accurate cluster expansions in alloys.
  • A novel selection criterion enhances the reliability and physical interpretability of cluster expansion models.
  • This noise-filtering property has significant implications for alloy system modeling.