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SUMMARY:Searching for Superconducting Hydrides - Dr. Maélie Caussé\, Mat
 erials Theory Group\, University of Cambridge
DTSTART:20260213T190000Z
DTEND:20260213T200000Z
UID:TALK244732@talks.cam.ac.uk
CONTACT:Indigo Luksch
DESCRIPTION:Abstract:\nComputational methods have revolutionised material 
 discovery\, driving interest in designing new advanced materials\, e.g.\, 
 superconductors\, which exhibit zero resistivity below a critical temperat
 ure (Tc). Reaching pressures in the 100 GPa range enables the synthesis of
  superhydrides\, a new class of hydrogen-rich materials that exhibit remar
 kable properties such as superconductivity\, hydrogen diffusion\, and hydr
 ogen storage. A striking example is LaH₁₀\, which holds the record for
  the highest superconducting transition temperature at Tc = 250 K [1\,2]\,
  and showcases high hydrogen diffusion at high temperatures [3]. However\,
  stabilising such compounds at ambient or low pressure remains a major cha
 llenge for practical applications. This has driven the search beyond binar
 y hydrides toward ternary superhydrides\, aiming to discover new supercond
 uctors with high critical temperatures that can persist near ambient press
 ure.\n\nThe discovery of new superconducting hydrides traditionally relies
  on ab initio crystal structure prediction and experimental synthesis. How
 ever\, ab initio calculations become computationally prohibitive\, e.g. fo
 r assessing the thermodynamic stability of complex systems such as ternary
  superhydrides\, due to the extremely vast chemical space. To overcome thi
 s limitation\, our group has successfully developed tailored machine learn
 ing interatomic potentials – ephemeral data-driven potentials (EDDPs) 
 – enabling a great acceleration in structure prediction [4]. This approa
 ch was used to build the convex-hull of a new predicted metastable ambient
 -pressure hydrogen-based superconductor Mg2IrH6 with a Tc of 160 K [5].\n 
 \nThis talk will trace the hunt for high-pressure superconductors\, highli
 ght how EDDPs revolutionize our high-throughput search workflow\, and show
 case some of our recent prediction of a new ternary hydride superconductor
  [6].\n\nReferences\n[1] M. Somayazulu et al.\, Phys. Rev. Lett.\, vol. 12
 2 (2019) 027001\n[2] A.P. Drozdov et al.\, Nature\, vol 569 (2019) 528-531
 \n[3] M. Caussé et al.\, Phy. Rev. B\, vol 107 (2023) L060301\n[4] C. J. 
 Pickard\, Phys Rev B\, vol 106 (2022) 014102\n[5] K. Dolui et al.\, Phys. 
 Rev. Lett.\, vol 132 (2024) 16600\n[6] M. Caussé et al. arXiv (2025) http
 s://doi.org/10.48550/arXiv.2512.19901
LOCATION:Department of Chemistry (Pfizer lecture theatre)
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