Researchers at Argonne National Laboratory and the University of Chicago have released PyRET, an open-source Python package for calculating how energy moves between tiny defects inside solid materials.
The name stands for Python code for resonance energy transfer. Resonance energy transfer happens when an excited site passes energy to another site without moving an electrical charge across the full distance. In a crystal, the sites can be atomic-scale imperfections that absorb or emit light.
That sounds narrow, but these defects are central to work on optical memory, solid-state sensors, microelectronics and some quantum devices. Their interactions can preserve a useful signal, amplify it or leak energy away from the part of a device meant to hold information.
The hard part is scale. The electronic structure around a defect is measured in fractions of a nanometre. Light can carry energy across tens or hundreds of nanometres in the same device. Calculations that describe one scale do not automatically explain the other.
PyRET connects those layers. It can use wavefunctions from Quantum ESPRESSO, a widely used electronic-structure package, and link them with quantum defect calculations produced by WEST. It then models both radiative transfer, where a photon carries the energy, and non-radiative transfer between nearby defects.
The underlying methods were described in peer-reviewed Physical Review Research papers in 2024 and 2025. In the later work, the researchers calculated that placing defects inside a tuned photonic cavity could change their energy-transfer rate by nearly two orders of magnitude. A photonic cavity is a tiny structure that confines selected frequencies of light.
The newly public code matters because other teams can now inspect the implementation, reproduce the calculations and adapt them to different materials. The repository uses the GPL-3.0 licence and includes installation instructions, documentation and examples.
That openness also makes comparisons easier. A laboratory testing a new defect can keep the physical method visible while changing the material, cavity geometry or electronic input. Failed predictions can be traced to assumptions in the workflow instead of disappearing inside a proprietary service.
PyRET is not a push-button materials discovery app. Researchers still need electronic-structure inputs, familiarity with specialist simulation software and, for large calculations, substantial computing resources. The public repository is also young, with a small visible user community and no packaged releases listed yet.
Those limitations are part of the useful signal. The immediate advance is not a finished memory chip or quantum sensor. It is a more transparent bridge between theories that operate at different scales.
For working scientists, that can shorten the distance between a promising defect found in a calculation and a device design worth testing in the lab. For everyone else, PyRET is a reminder that open source in science is often less about a polished consumer tool and more about making a difficult claim testable by someone outside the original team.