Login / Signup

Revealing the Elusive Structure and Reactivity of Iron Boride α-FeB.

Fernando Igoa SaldañaEmile DefoyDaniel JanischGwenaelle RoussePierre-Olivier AutranAnissa GhoridiAmandine SénéMarzena BaronLeopoldo SuescunYann Le GodecDavid Portehault
Published in: Inorganic chemistry (2023)
Crystal structures can strongly deviate from bulk states when confined into nanodomains. These deviations may deeply affect properties and reactivity and then call for a close examination. In this work, we address the case where extended crystal defects spread through a whole solid and then yield an aperiodic structure and specific reactivity. We focus on iron boride, α-FeB, whose structure has not been elucidated yet, thus hindering the understanding of its properties. We synthesize the two known phases, α-FeB and β-FeB, in molten salts at 600 and 1100 °C, respectively. The experimental X-ray diffraction (XRD) data cannot be satisfactorily accounted for by a periodic crystal structure. We then model the compound as a stochastic assembly of layers of two structure types. Refinement of the powder XRD pattern by considering the explicit scattering interference of the different layers allows quantitative evaluation of the size of these domains and of the stacking faults between them. We, therefore, demonstrate that α-FeB is an intergrowth of nanometer-thick slabs of two structure types, β-FeB and CrB-type structures, in similar proportions. We finally discuss the implications of this novel structure on the reactivity of the material and its ability to perform insertion reactions by comparing the reactivities of α-FeB and β-FeB as reagents in the synthesis of a model layered material: Fe 2 AlB 2 . Using synchrotron-based in situ X-ray diffraction, we elucidate the mechanisms of the formation of Fe 2 AlB 2 . We highlight the higher reactivity of the intergrowth α-FeB in agreement with structural relationships.
Keyphrases
  • crystal structure
  • high resolution
  • magnetic resonance
  • magnetic resonance imaging
  • machine learning
  • computed tomography
  • electronic health record
  • highly efficient
  • data analysis