Engineers analyzing large-scale simulation data (Credit: NASA/Advanced Supercomputing Division/Dominic Hart)
SUBTOPIC

Material Science

Designing matter atom by atom, before a single gram is ever synthesized.

Image: NASA/Advanced Supercomputing Division/Dominic Hart

From Quantum Mechanics to Qualified Parts

Modeling a new battery chemistry or superconductor means solving quantum-mechanical equations for how electrons and atoms interact — a problem whose computational cost grows exponentially with system size. Exascale machines make it possible to simulate thousands of atoms with genuine quantum fidelity, and to model entire manufacturing processes, such as additive manufacturing microstructure, at a level of detail that used to require years of physical testing. Malgukke delivers the exascale-class GPU infrastructure that brings these simulations within reach.

HPC Solution Architecture: Atom to Qualified Component

A quantum-to-manufacturing materials pipeline, comparable to ORNL's ExaAM and quantum chemistry workflows on Frontier:

Candidate Composition Alloy, polymer, electrolyte Quantum Core CPU Nodes DFT / quantum chemistry GPU Nodes Molecular dynamics at scale Property Prediction: strength, conductivity Process Model Additive manufacturing sim Qualified Component specification Physical test data validates simulation fidelity and narrows the next composition search

Running on the TOP500: Frontier

TOP500 — TOP-TIER SYSTEM

Frontier at Oak Ridge National Laboratory has consistently ranked among the top three systems on the TOP500 list, with a measured 1.353 exaflop/s. It is the platform behind ORNL's ExaAM project, which uses exascale computing to simulate additive-manufacturing microstructure for aircraft and nuclear-plant components — cutting materials qualification from years to a fraction of that time — as well as quantum chemistry research into next-generation battery and biofuel materials.

Yes — this is a real, currently operating top-tier TOP500 system, directly used by ORNL researchers for the materials-qualification and quantum-chemistry workloads described on this page.

Top 3
Global TOP500 Position
1.353
Exaflop/s (HPL)

Voices from the Field

Matt Bement

Computational Scientist, Oak Ridge National Laboratory (ExaAM project lead)

On how exascale computing cuts materials qualification for aircraft and nuclear parts from years to a fraction of that time.

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Dmytro Bykov

Group Leader, Computing for Chemistry and Materials, ORNL

On why accurately predicting atomic-scale behavior is fundamental to developing improved drug therapeutics, medical materials, and biofuels.

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