Scientists simulate how tens of thousands of electrons move in real time

Scientists have developed a simulation that can predict how tens of thousands of electrons move in materials in real time, or natural time rather than compute time.

Developed by a team from the Department of Energy’s Oak Ridge National Laboratory, in collaboration with North Carolina State University, the model combines ORNL’s expertise in time-dependent quantum methods with NCSU’s advanced quantum simulation platform.

Researchers revealed that the latest effort is vital in designing new technologies such as advanced photovoltaic cells and emerging information systems.

Observing thousands of electrons in real-time

They underlined that by directly observing thousands of electrons in real-time, scientists gain powerful insights into how materials respond at the quantum level.

Published in the Journal of Chemical Theory and Computation, the team developed a real-time, time-dependent density functional theory, or RT-TDDFT, capability within the open-source Real-space Multigrid, or RMG, code to model systems of up to 24,000 electrons.

RT-TDDFT is a quantum mechanical method that allows researchers to simulate how electrons move and interact in materials over time, once they are excited by an external stimulus. It works by calculating how the electron density in materials changes in response to the application of electric and electromagnetic fields (i.e. light), for instance. 

Real-time evolution of quantum-mechanical property

Researchers highlighted that the real-time, time-dependent describes the real-time evolution of the wavefunction or quantum-mechanical property. 24,000 electrons is about the same size as treating 4,000 carbon atoms or 2,400 water molecules treating the time evolution of all their electrons. 

“Think of it like watching a slow-motion replay of all the electrons in a tiny piece of metal responding to a flash of light, but at an incredibly detailed, quantum level,” said ORNL’s Jacek Jakowski.

“Our calculations are so large that they require one of the world’s fastest supercomputers to run them in ‘real time’. By capturing these electron movements at scale, we can predict how new materials will behave, potentially leading to more efficient photovoltaic cells, faster computers, and better quantum technologies.”

Method offers insights into nonequilibrium dynamics

The study revealed that their method offers insights into nonequilibrium dynamics and excited states across a diverse range of systems, from small organic molecules to large metallic nanoparticles. Benchmarking results demonstrate excellent agreement with established TDDFT implementations and showcase the superior stability of our time integration algorithm, enabling long-term simulations with minimal energy drift.

Researchers also highlighted that metallic nanoparticles, or metals with dimensions within 1-100 nanometers, have unique optical properties caused by the way thousands of electrons within these metals interact with incoming light. It’s critical for researchers to understand the ways these electrons move under a range of conditions to advance these new technologies.

The challenge in moving these technologies forward has been capturing these ultrafast electron dynamics in realistic nanoscale materials, or materials where at least one dimension is on the scale of nanometers, according to a press release.

Achievement enables design of novel materials with tunable optical

The study underlined that the achievement enables the design of novel materials with tunable optical, electronic and magnetic properties and opens the door to new innovations in optical and quantum information devices.

“These developments hold great promise for creating novel devices with tailored electronic, optical and magnetic properties,” said Professor Bernholc. “Ultimately, we hope our real-time approach will guide experimental efforts and accelerate breakthroughs in areas ranging from spintronics to quantum information science.”

Next steps for the project include simulating even more complex scenarios to discover new physics in quantum systems and enhancing efficiency and accuracy to handle larger, more intricate simulations, as per the release.

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