Accelerated Materials Discovery Through In Situ X-ray Diffraction: Solvothermal Formation of Pd_xM_y (M═Si, Ge, Sn, Pb)...

Machine learning and artificial intelligence approaches are expected to accelerate the development of new materials, for example through automated synthesis. Here, we investigate another approach to accelerate materials discovery, namely in situ synchrotron Powder x-ray diffraction (PXRD), which enables efficient exploration of a large range of synthesis parameters to identify optimal synthesis conditions. We study the solvothermal formation of Pd_xM_y (M═Si, Ge, Sn, Pb) nanoparticles with varying temperature, solvent, and metal precursor. Intermetallic phases are obtained for all systems except for Pd_xSi_y, and specific conditions are identified for preparing Pd₂₅Ge₉, Pd₂Ge, SnPd₂, Sn₁₃Pd₂₀, SnPd, Pb₃Pd₅, Pb₉Pd₁₃, PbPd, and Pb₂Pd intermetallic phases. A general formation mechanism is suggested, where Pd nanoparticles are formed initially, followed by adsorption and diffusion of the secondary metal to form intermetallic phases. Based on the learnings from the in situ experiments, SnPd₂, Sn₁₃Pd₂₀, and SnPd nanoparticles are synthesized ex situ in a simple solvothermal process. Scanning transmission electron microscopy-energy-dispersive x-ray spectroscopy (STEM-EDS) establishes a gradient of Sn across the nanoparticles with a Pd-rich core and increasing Sn content towards the edges, reflecting the diffusion of Sn into the initial Pd nanoparticles and thereby corroborating the formation mechanism observed from the in situ data.