Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Predicting Molecular Geometry

Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries

Ionic Crystal Structures

Ionic Crystal Structures

Ionic crystals consist of two or more different kinds of ions that usually have different sizes. The packing of these ions into a crystal structure is more complex than the packing of metal atoms that are the same size.
Most monatomic ions behave as charged spheres, and their attraction for ions of opposite charge is the same in every direction. Consequently, stable structures for ionic compounds result (1) when ions of one charge are surrounded by as many ions as possible of the opposite...

What is Evolutionary History?

What is Evolutionary History?

Scientists record evolutionary history by analyzing fossil, morphological, and genetic data. The fossil record documents the history of life on Earth and provides evidence for evolution. However, both fossil and living organisms offer evidence that outlines Earth’s evolutionary history.

Ecological Niches

Ecological Niches

All organisms have a position within an ecosystem. The complete set of living and nonliving factors—including food resources, climate, and terrain—that define the position of a given organism are collectively referred to as the organism’s ecological niche.

Genetics of Speciation

Genetics of Speciation

Speciation is the evolutionary process resulting in the formation of new, distinct species—groups of reproductively isolated populations.

Molecular Structure and Acidity

Molecular Structure and Acidity

An acid can be deprotonated to form a conjugate base or an anion. If the produced anion is more stable, then the acid is stronger. On the contrary, if the anion is unstable, then the acid is weaker. Hence, to determine the acidity of the compound, the stability of its conjugate base is studied using various factors.
The size effect explains the change in atomic size on acidity. When comparing the acids formed from elements that belong to the same column in the periodic table, their atomic sizes...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Structure Prediction of Organic/Inorganic Interfaces with Genarris.

Journal of chemical theory and computation·2026

Same author

Open Molecular Crystals 2025 (OMC25) dataset and models.

Scientific data·2026

Same author

Efficient Molecular Crystal Structure Prediction and Stability Assessment with AIMNet2 Neural Network Potentials.

Crystal growth & design·2025

Same author

Genarris 3.0: Generating Close-Packed Molecular Crystal Structures with Rigid Press.

Journal of chemical theory and computation·2025

Same author

PAH101: A GW+BSE Dataset of 101 Polycyclic Aromatic Hydrocarbon (PAH) Molecular Crystals.

Scientific data·2025

Same author

Structure Prediction of Ionic Epitaxial Interfaces with Ogre Demonstrated for Colloidal Heterostructures of Lead Halide Perovskites.

ACS nano·2025

Search research articles

Related Experiment Video

Updated: Feb 7, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

Evolutionary niching in the GAtor genetic algorithm for molecular crystal structure prediction.

Farren Curtis¹, Timothy Rose, Noa Marom

¹Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA. nmarom@andrew.cmu.edu.

Faraday Discussions

|August 4, 2018

Summary

Genetic algorithms (GAs) for crystal structure prediction (CSP) were enhanced using evolutionary niching. This method improves the discovery of diverse, low-energy molecular crystal structures.

More Related Videos

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

Related Experiment Videos

Last Updated: Feb 7, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

Area of Science:

Computational Chemistry
Materials Science
Crystallography

Background:

Molecular crystal structure prediction (CSP) aims to identify all possible polymorphs for a molecule.
Global optimization in high-dimensional spaces is crucial for CSP.
Genetic algorithms (GAs) are commonly used for global optimization in CSP.

Purpose of the Study:

To investigate the impact of evolutionary niching on CSP.
To enhance the GAtor code with machine learning-driven niching for multi-modal optimization.
To improve the success rate of finding experimental and novel low-energy crystal structures.

Main Methods:

Implementation of evolutionary niching in the GAtor CSP code.
Utilizing machine learning for dynamic population clustering into structural similarity niches.
Development of a cluster-based fitness function to promote exploration of diverse structures.

Main Results:

The cluster-based fitness function increased the success rate of predicting the experimental crystal structure.
Additional low-energy crystal structures with similar packing motifs were successfully generated.
Evolutionary niching effectively supported the formation of multiple stable subpopulations, preventing over-sampling.

Conclusions:

Evolutionary niching is a valuable strategy for improving the efficiency and diversity of crystal structure prediction.
The GAtor code, enhanced with ML-based niching, demonstrates improved performance in CSP.
This approach facilitates the discovery of a wider range of plausible molecular polymorphs.