Researchers at the University of Illinois Urbana-Champaign have resolved a long-standing question in materials science by identifying how magnetism at the atomic scale slows the movement of carbon in steel. Led by Dallas Trinkle from the Grainger College of Engineering, the work provides a clear physical explanation for experimental observations made more than fifty years ago, when metallurgists noticed that magnetic fields could influence how steel responds to heat treatment. The findings bring predictive clarity to a phenomenon that had remained largely empirical.
Wirth, L. J., & Trinkle, D. R. (2025). External Magnetic Field Suppression of Carbon Diffusion in Iron. Physical Review Letters, 135(25), 256302. https://doi.org/10.1103/j4sg-qmg7
Steel owes many of its mechanical properties to the way carbon atoms move through an iron lattice during heating and cooling. Carbon diffuses through small interstitial sites formed by surrounding iron atoms, and this diffusion controls phase transformations, grain size, and hardness. Because these processes typically occur at high temperatures, steel manufacturing remains energy intensive. Understanding how to influence carbon motion more precisely has long been a goal for engineers seeking more efficient processing routes.
Dallas Trinkle from the Grainger College of Engineering, University of Illinois Urbana-Champaign stated,
“We wanted to be able to do real calculations; to show not just qualitatively but quantitatively the effective field and temperature. Now that we have this information, we can start thinking more about engineering alloys. It may be choosing alloys that already exist or even thinking about alloy chemistries that we’re not yet using that could be extremely advantageous.”
Earlier studies showed that applying magnetic fields during heat treatment could alter microstructure and performance in certain steels. However, explanations were often qualitative, linking the effect loosely to magnetic ordering without identifying a mechanism that could be calculated or generalized. As a result, the observations were difficult to translate into practical design rules for alloys or processing conditions.
The Illinois team approached the problem using modern computational tools that combine diffusion theory with atomic-scale magnetism. By modeling iron atoms with different spin alignments, they were able to simulate how temperature and magnetic order affect the local environment surrounding carbon atoms. Their calculations focused on how carbon moves between octahedral sites within the iron lattice and how this movement changes when iron atoms transition between magnetically ordered and disordered states.
The simulations showed that magnetic alignment in iron raises the energy barrier that carbon must overcome to move between sites. When iron atoms are magnetically ordered, as they are below the Curie temperature, the atomic cages surrounding carbon become less symmetric and more restrictive. This makes diffusion slower. As magnetic order decreases at higher temperatures, the lattice becomes more isotropic, allowing carbon to move more freely. External magnetic fields reinforce this ordering near the Curie point, further suppressing diffusion.
This result explains why relatively modest magnetic fields can have an outsized effect during heat treatment, even though much stronger fields would be required to force magnetic alignment at lower temperatures. It also provides a quantitative framework for predicting how changes in field strength and temperature will affect diffusion, something that had not been possible with earlier phenomenological models.
The implications extend beyond academic interest. By incorporating magnetic effects into diffusion calculations, engineers may be able to fine-tune heat treatment schedules, reduce processing temperatures, or shorten treatment times. Even small improvements could translate into meaningful reductions in energy use and emissions across large-scale steel production. The approach could also be adapted to other alloys where diffusion plays a key role and magnetic effects are present.
More broadly, the study highlights how advances in computational materials science are reshaping long-standing industrial knowledge. Observations once treated as empirical rules can now be traced back to atomic-scale mechanisms, making them easier to predict and apply. In the case of steel, a material that underpins modern infrastructure, this deeper understanding offers a path toward more efficient and controllable manufacturing without requiring entirely new alloy systems.
Adrian graduated with a Masters Degree (1st Class Honours) in Chemical Engineering from Chester University along with Harris. His master’s research aimed to develop a standardadised clean water oxygenation transfer procedure to test bubble diffusers that are currently used in the wastewater industry commercial market. He has also undergone placments in both US and China primarely focused within the R&D department and is an associate member of the Institute of Chemical Engineers (IChemE).
