X-ray photon correlation spectroscopy (XPCS) allows for the resolution of dynamic processes within a material across a wide range of length and time scales. X-ray speckle visibility spectroscopy (XSVS) is a related method that uses a single diffraction pattern to probe ultrafast dynamics. Interpretation of the XPCS and XSVS data in terms of underlying physical processes is necessary to establish the connection between the macroscopic responses and the microstructural dynamics. To aid the interpretation of the XPCS and XSVS data, we present a computational framework to model these experiments by computing the X-ray scattering intensity directly from the atomic positions obtained from molecular dynamics (MD) simulations. We compare the efficiency and accuracy of two alternative computational methods: the direct method computing the intensity at each diffraction vector separately, and a method based on fast Fourier transform that computes the intensities at all diffraction vectors at once. The computed X-ray speckle patterns capture the density fluctuations over a range of length and time scales and are shown to reproduce the known properties and relations of experimental XPCS and XSVS for liquids.

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The analysis and design of piezoelectric actuators and sensors require the understanding of their failure due to the coupled electromechanical interactions. We present a phase-field model for damage to capture the brittle fracture associated with piezoelectric ceramics. A homogeneous PZT-4 specimen is used to demonstrate the interaction of various geometric parameters and polarization direction on the growth and arrest of a crack. In addition, the effect of holes and their arrangement on the fracture load is also discussed to assist in topology optimization. It was found that an ordered arrangement of holes could enhance the reliability of these ceramics more than a single hole with a similar amount of material removed. Finally, the functional gradation of material properties is modelled to understand the fracture in a piezoelectric composite containing PZT-4 and BaTiO 3 . The effect of the relative orientation of the material with respect to the polarization direction, on the fracture load is studied to improve the life of such piezoelectric composites. The resistance of fracture is found to be the maximum when the crack propagates into the tougher region of the domain. Whereas, the field enhances the fracture load irrespective of its magnitude when the gradation of material properties for the PZT-4/BaTiO 3 ceramic is along the polarization direction. The aim of the study is to identify the factors that arrest crack propagation by analyzing the coupled system for the better design of piezoelectric sensors and actuators.

Understanding and predicting the properties of polymers is vital to developing tailored polymer molecules for desired applications. Classical force fields may fail to capture key properties, for example, the transport properties of certain polymer systems such as polyethylene glycol. As a solution, we present an alternative potential energy surface, a charge recursive neural network (QRNN) model trained on DFT calculations made on smaller atomic clusters that generalizes well to oligomers comprising larger atomic clusters or longer chains. We demonstrate the validity of the polymer QRNN workflow by modeling the oligomers of ethylene glycol. We apply two rounds of active learning (addition of new training clusters based on current model performance) and implement a novel model training approach that uses partial charges from a semi-empirical method. Our developed QRNN model for polymers produces stable molecular dynamics (MD) simulation trajectory and captures the dynamics of polymer chains as indicated by the striking agreement with experimental values. Our model allows working on much larger systems than allowed by DFT simulations, at the same time providing a more accurate force field than classical force fields which provides a promising avenue for large-scale molecular simulations of polymeric systems.

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