Web Articles

  • Yuri Alexeev

The best of both worlds: how to solve real problems on modern quantum computers

With help from ALCF computing resources, Argonne researchers are combining quantum and classical approaches to overcome limitations in current quantum computing hardware.

July 11, 2019

Predicting material properties with quantum Monte Carlo

Recent advances in quantum Monte Carlo (QMC) methods have the potential to revolutionize computational materials science, a discipline traditionally driven by density functional theory (DFT). Using DOE supercomputers, a team led by Paul Kent of Oak Ridge National Laboratory is using QMC to simulate promising materials that elude DFT’s investigative and predictive powers.

July 09, 2019
  • 2019 ALCF Computational Performance Workshop

ALCF workshop helps attendees advance use of supercomputing resources

This spring, more than 50 researchers from across the country visited the Argonne Leadership Computing Facility (ALCF), a U.S. Department of Energy (DOE) Office of Science User Facility, for the ALCF Computational Performance Workshop. The annual training event is designed to help attendees boost code performance and prepare for future ALCF projects.

June 17, 2019
  • Deep Transfer Learning at Scale for Cosmology

Scientists spearhead convergence of AI and HPC for cosmology

Using an ALCF Data Science Program award, researchers from NCSA and ALCF have developed a novel combination of deep learning methods to provide a highly accurate approach to classifying hundreds of millions of unlabeled galaxies.

June 14, 2019
  • Argonne researchers are using machine learning to transform transportation technologies

On the road to efficiency

From engine design to traffic predictions, Argonne researchers are using machine learning techniques for a variety of projects aimed at transforming our transportation and vehicle technology systems.

June 11, 2019
  • Boron

Combination of experiments and calculations allows examination of boron’s complicated dance

In a study that combines experimental work and theoretical calculations made possible by ALCF supercomputers, scientists have determined the nuclear geometry of two isotopes of boron. The result could help open a path to precise calculations of the structure of other nuclei that scientists could experimentally validate.

June 07, 2019

Tapping the power of AI and high-performance computing to extend evolution to superconductors

ALCF supercomputing resources enabled researchers to use genetic algorithms to assess the performance of superconductors.

May 29, 2019

Simulating electronic stopping in solids and DNA

The question of what happens at the microscopic scale during electronic stopping processes—that is, what happens when kinetic energy is transferred from charged particles, such as protons, to the electrons in a target material—drives the advanceme

May 23, 2019
  • ALCF simulations lead to patented process for biofuel production

ALCF simulations lead to patented process for biofuel production

Using supercomputers at the Argonne Leadership Computing Facility (ALCF), a team of researchers from the University of Minnesota employed computational screening to identify promising microporous materials, called zeolites, for various biofuel pro

May 14, 2019

Researchers discover quantum effect in hard disk drive material

Sometimes scientific discoveries can be found along well-trodden paths. That proved the case for a cobalt-iron alloy material commonly found in hard disk drives.

May 03, 2019