Probing morphology and chemistry in complex soft materials within situresonant soft x-ray scattering

Small angle scattering methodologies have been evolving at fast pace over the past few decades due to the ever-increasing demands for more details on the complex nanostructures of multiphase and multicomponent soft materials like polymer assemblies and biomaterials. Currently, element-specific and contrast variation techniques such as resonant (elastic) soft/tender x-ray scattering, anomalous small angle x-ray scattering, and contrast-matching small angle neutron scattering, or combinations of above are routinely used to extract the chemical composition and spatial arrangement of constituent elements at multiple length scales and examine electronic ordering phenomena. Here we present some recent advances in selectively characterizing structural architectures of complex soft materials, which often contain multi-components with a wide range of length scales and multiple functionalities, where novel resonant scattering approaches have been demonstrated to decipher a higher level of structural complexity that correlates to functionality. With the advancement of machine learning and artificial intelligence assisted correlative analysis, high-throughput and autonomous experiments would open a new paradigm of material research. Further development of resonant x-ray scattering instrumentation with crossplatform sample environments will enable multimodalin situ/operando characterization of the system dynamics with much improved spatial and temporal resolution.