Dresden 2026 – scientific programme
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TT: Fachverband Tiefe Temperaturen
TT 95: Fe-based Superconductors
TT 95.6: Talk
Friday, March 13, 2026, 11:00–11:15, HSZ/0103
Predicting isostructural collapses in the ThCr2Si2 structure type - fast and efficient — •Adrian Valadkhani1, Paul Canfield2, and Roser Valentí1 — 1Goethe Universität ITP, Frankfurt am Main, Germany — 2Ames National Laboratory, Ames, USA
Isostructural collapse transitions in tetragonal ThCr2Si2(122) compounds strongly affect magnetism, topology, and superconductivity, yet most studies treat materials on a case-by-case basis, making the overall approach computationally inefficient. Here, we present a general, efficient framework to predict isostructural collapses across the 122 family - readily extensible to other structure types. We classify collapsibility from the ambient-pressure unit cell using a linear, supervised classifier. In addition, an ambient-pressure calibration of the density-functional-theory-based calculations anchored to the experimental structure determines both the form of collapse and the critical pressure, if it exists. We validate the method against literature data and recent work on SrCo2P2, and we show how the same calibration subsequently enables efficient exploration of the pressure-dependent electronic structure. Because the procedure requires minimal experimental input and fast, efficient and standard computations, it is directly transferable to other structure families where isostructural transitions or distortions occur. This establishes a practical route for screening and designing materials with collapse-tunable functionalities.
We acknowledge support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) for funding through TRR 288 - 422213477 (project A05)
Keywords: ThCr2Si2; collapse; machine learning