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The Evidence for Evolution02:55

The Evidence for Evolution

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Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.
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Convergent Evolution01:54

Convergent Evolution

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Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.
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Optimal Foraging

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How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
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Eukaryotic Evolution01:24

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The endosymbiont theory is the most widely accepted theory of eukaryotic evolution; however, its progression is still somewhat debated. According to the nucleus-first hypothesis, the ancestral prokaryote first evolved a membrane to enclose DNA and form the nucleus. Conversely, the mitochondria-first hypothesis suggests that the nucleus was formed after endosymbiosis of mitochondria.
Contrary to the endosymbiont theory, the eukaryote-first hypothesis proposes that the simpler prokaryotic and...
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Synteny and Evolution02:31

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John H. Renwick first coined the term “synteny” in 1971, which refers to the genes present on the same chromosomes, even if they are not genetically linked. The species with common ancestry tend to show conserved syntenic regions. Therefore, the concept of synteny is nowadays used to describe the evolutionary relationship between species.
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Synthesis of Bimetallic Pt/Sn-based Nanoparticles in Ionic Liquids
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協調的差分進化法を用いた二金属クラスター構造最適化のためのC++ツールキット

Xiaomin Wu1, Miao He2, Yousi Lin1

  • 1School of Optoelectronic and Communication Engineering, Xiamen University of Technology, Xiamen 361024, China.

Journal of chemical information and modeling
|February 4, 2026
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まとめ
この要約は機械生成です。

効率的なナノクラスター構造予測のための協調的差分進化法（CDE）アルゴリズムを開発しました。この方法は、二金属および単金属クラスターの安定な配置の発見を加速します。

キーワード:
協調的差分進化法ナノクラスター構造最適化材料発見計算化学C++ツールキット

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科学分野:

  • 材料科学
  • 計算化学
  • ナノテクノロジー

背景:

  • 二金属および単金属クラスター構造のグローバル最適化は計算集約的です。
  • 可能な構成（ホモトープ）の数は、システムのサイズと複雑さとともに急速に増加します。

研究 の 目的:

  • ナノクラスターシステムの安定構造を予測するための効率的なアルゴリズムを開発すること。
  • 多様なクラスター構造のグローバル最適化における計算上の課題に対処すること。

主な方法:

  • 協調的差分進化法（CDE）アルゴリズムの導入。
  • 探索、活用、バランスに特化したサブポピュレーションを持つマルチサブポピュレーション協調アーキテクチャの利用。
  • 金属ナノクラスターに合わせて調整された適応型操作の実装と、オンラインC++ツールキットとしての利用可能性。

主要な成果:

  • Pt-Pd、Cu-Auの二金属クラスター、および単金属Ptクラスターの構造最適化を通じて、その汎用性と堅牢性が実証されました。
  • 従来のメソッドと比較して、収束が50〜100％高速化されました。
  • テストされたすべてのシステムで、構造予測における優れた安定性が示されました。

結論:

  • CDEアルゴリズムは、多様なクラスター材料における安定な構成の発見を加速するための、堅牢で一般化可能なツールです。
  • 開発されたツールキットは、ナノクラスター構造予測のための効率的でユーザーフレンドリーなソリューションを提供します。