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X-ray Crystallography02:18

X-ray Crystallography

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The size of the unit cell and the arrangement of atoms in a crystal may be determined from measurements of the diffraction of X-rays by the crystal, termed X-ray crystallography.
Diffraction
Diffraction is the change in the direction of travel experienced by an electromagnetic wave when it encounters a physical barrier whose dimensions are comparable to those of the wavelength of the light. X-rays are electromagnetic radiation with wavelengths about as long as the distance between neighboring...
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X-ray Diffraction of Biological Samples01:10

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X-ray diffraction or XRD is an analytical tool that utilizes X-rays to study ordered structures such as crystalline organic and inorganic samples, polycrystalline materials, proteins, carbohydrates, and drugs.
According to Bragg's law, when X-rays strike the sample positioned on a stage, the rays are  scattered by the electron clouds around the sample atoms. The  X-ray diffraction or scattering is caused by constructive interference of the X-ray waves that reflect off the internal...
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Crystal Growth: Principles of Crystallization01:25

Crystal Growth: Principles of Crystallization

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Crystallization is a phase transformation process in which crystals are precipitated from a supersaturated solution or formed from other sources. During crystallization, atoms or molecules arrange themselves into a well-defined, rigid crystal lattice to minimize energy.
Initiating crystallization involves manipulating the concentration of the solute and the temperature of the solution. Since crystal growth occurs when the ratio of concentration and solubility of the solute in the solvent...
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Related Experiment Video

Updated: Jun 18, 2025

Microcrystallography of Protein Crystals and In Cellulo Diffraction
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Microcrystallography of Protein Crystals and In Cellulo Diffraction

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PhAI: A deep-learning approach to solve the crystallographic phase problem.

Anders S Larsen1, Toms Rekis1, Anders Ø Madsen1

  • 1Department of Pharmacy, University of Copenhagen, Copenhagen, Denmark.

Science (New York, N.Y.)
|August 1, 2024
PubMed
Summary
This summary is machine-generated.

A novel neural network can solve the crystallographic phase problem, crucial for determining 3D crystal structures. This AI approach uses less data and achieves high resolution, potentially revolutionizing X-ray crystallography.

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Area of Science:

  • Crystallography and Structural Biology
  • Artificial Intelligence in Science
  • Computational Chemistry

Background:

  • X-ray crystallography is vital for determining 3D molecular structures.
  • Reconstructing electron density maps requires complex structure factors, including amplitudes and phases.
  • The loss of phase information during experiments is known as the crystallographic phase problem.

Purpose of the Study:

  • To investigate the potential of neural networks in solving the crystallographic phase problem.
  • To develop an AI-driven method for reconstructing crystal structures from X-ray diffraction data.
  • To assess the efficiency and resolution achievable by a neural network approach.

Main Methods:

  • Training a neural network on millions of artificial structure factor datasets.
  • Utilizing the trained neural network to predict phase information from diffraction data.
  • Evaluating the network's performance on solving the phase problem at a resolution of 2 angstroms.

Main Results:

  • The neural network successfully solved the crystallographic phase problem at 2 angstrom resolution.
  • The AI method required only 10-20% of the data typically needed for direct methods.
  • The network demonstrated efficacy in common space groups and for modest unit-cell dimensions.

Conclusions:

  • Neural networks offer a powerful new tool for addressing the crystallographic phase problem.
  • This AI-driven method significantly reduces data requirements and computational time.
  • The approach shows promise for analyzing weakly scattering crystals and advancing structural biology.