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Related Concept Videos

Cluster Sampling Method01:20

Cluster Sampling Method

Appropriate sampling methods ensure 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.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Optimization Problems01:26

Optimization Problems

Optimization problems often involve identifying maximum or minimum values under specific constraints. A well-known example is determining the longest horizontal pipe that can be moved around a right-angled corner, where a 3-meter-wide hallway meets a 2-meter-wide hallway. This scenario, common in architectural design and industrial transport, can be understood conceptually through geometric and trigonometric reasoning.To visualize the problem, consider the pipe as a straight line that touches...
Population Growth00:57

Population Growth

Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.However, realistic environmental conditions limit the number of...
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Multimachine Stability

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Scale-Up Processes01:14

Scale-Up Processes

The scale-up of microbial fermentation processes is essential in industrial biotechnology, allowing the transition from laboratory-scale experiments to commercial-scale production while aiming to maintain product yield and quality. This process requires meticulous adjustment of equipment design, process parameters, and contamination control strategies to accommodate increasing culture volumes.At the laboratory scale, cultures are typically maintained in 1 to 10-liter glass or autoclavable...
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Exponential Equations for Modeling Growth

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Related Experiment Video

Updated: Jul 5, 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

Global optimisation and growth simulation of AuCu clusters.

T J Toai1, G Rossi, R Ferrando

  • 1Dipartimento di Fisica, Università di Genova, Via Dodecaneso 33, 16136 Genova, Italy.

Faraday Discussions
|May 2, 2008
PubMed
Summary

This study explores gold-copper (AuCu) clusters using global optimization and molecular dynamics. Results reveal distinct structural motifs and surface segregation patterns, impacting cluster ordering and growth dynamics.

Related Experiment Videos

Last Updated: Jul 5, 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

Area of Science:

  • Computational chemistry and materials science.
  • Nanoparticle structure and dynamics.

Background:

  • Understanding the atomic arrangement and chemical ordering in bimetallic clusters is crucial for designing novel materials.
  • Gold-copper (AuCu) clusters present complex behaviors due to the distinct properties of gold and copper.

Purpose of the Study:

  • To investigate the structure, chemical order, and growth dynamics of AuCu clusters with varying compositions.
  • To identify stable configurations and understand the influence of atomic arrangement on cluster properties.

Main Methods:

  • Global optimization using the Parallel Excitable Walkers algorithm to find minimum energy configurations.
  • Molecular Dynamics simulations to study cluster growth and dynamics.
  • Analysis of cluster structures, including icosahedral and decahedral motifs, and surface segregation.

Main Results:

  • Stable AuCu clusters (N=100-200 atoms) do not show alloy ordering, favoring icosahedral structures with surface-enriched gold.
  • A decahedral structure was observed for N=100, with copper in the outer shell.
  • Cluster growth simulations confirmed the formation of icosahedral clusters with gold-enriched surfaces when depositing both elements onto a seed.
  • Conversely, depositing copper onto a gold seed resulted in decahedral clusters with a reversed Cu(shell)Au(core) ordering.

Conclusions:

  • The composition and growth method significantly influence the structure and chemical ordering of AuCu clusters.
  • Surface segregation of gold and specific structural motifs like icosahedra and decahedra are key features.
  • The study provides insights into controlling nanoparticle architecture through directed growth processes.