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Understanding and interpreting dynamics of functional materials \textit{in situ} is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales, however spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work we have developed an unsupervised deep learning (DL) framework for automated classification and interpretation of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system behavior. We demonstrate how this method can be used to rapidly explore large datasets to identify samples of interest, and we apply this approach to directly correlate bulk properties of a model system to microscopic dynamics. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery.

Nanoparticle monolayer sheets are ultrathin inorganic-organic hybrid materials that combine highly controllable optical and electrical properties with mechanical flexibility and remarkable strength. Like other thin sheets, their low bending rigidity allows them to easily roll into or conform to cylindrical geometries. Nanoparticle monolayers not only can bend, but also cope with strain through local particle rearrangement and plastic deformation. This means that, unlike thin sheets such as paper or graphene, nanoparticle sheets can much more easily conform to surfaces with complex topography characterized by non-zero Gaussian curvature, like spherical caps or saddles. Here, we investigate the limits of nanoparticle monolayers' ability to conform to substrates with Gaussian curvature by stamping nanoparticle sheets onto lattices of larger polystyrene spheres. Tuning the local Gaussian curvature by increasing the size of the substrate spheres, we find that the stamped sheet morphology evolves through three characteristic stages: from full substrate coverage, where the sheet extends over the interstices in the lattice, to coverage in the form of caps that conform tightly to the top portion of each sphere and fracture at larger polar angles, to caps that exhibit radial folds. Through analysis of the nanoparticle positions, obtained from scanning electron micrographs, we extract the local strain tensor and track the onset of strain-induced dislocations in the particle arrangement. By considering the interplay of energies for elastic and plastic deformations and adhesion, we construct arguments that capture the observed changes in sheet morphology as Gaussian curvature is tuned over two orders of magnitude., Comment: 13 pages for main text + 5 pages for supplementary information

We report on the fabrication and current-voltage (IV) characteristics of very narrow, strip-like arrays of metal nanoparticles. The arrays were formed from gold nanocrystals self-assembled between in-plane electrodes. Local cross-linking of the ligands by exposure to a focused electron beam and subsequent removal of the unexposed regions produced arrays as narrow as four particles wide and sixty particles long, with high degree of structural ordering. Remarkably, even for such quasi-one-dimensional strips, we find nonlinear, power-law IV characteristics similar to that of much wider two-dimensional (2D) arrays. However, in contrast to the robust behavior of 2D arrays, the shape of the IV characteristics is much more sensitive to temperature changes and temperature cycling. Furthermore, at low temperatures we observe pronounced two-level current fluctuations, indicative of discrete rearrangements in the current paths. We associate this behavior with the inherent high sensitivity of single electron tunneling to the polarization caused by the quenched offset charges in the underlying substrate., Comment: 5 pages, 4 figures

The nucleation and growth kinetics of highly ordered nanocrystal superlattices during the evaporation of nanocrystal colloidal droplets was elucidated by in situ time resolved small-angle x-ray scattering. We demonstrated for the first time that evaporation kinetics can affect the dimensionality of the superlattices. The formation of two-dimensional nanocrystal superlattices at the liquid-air interface of the droplet has an exponential growth kinetics that originates from interface "crushing"., Comment: 4 pages, 4 figures

We investigate how temperature affects transport through large networks of nonlinear conductances with distributed thresholds. In monolayers of weakly-coupled gold nanocrystals, quenched charge disorder produces a range of local thresholds for the onset of electron tunneling. Our measurements delineate two regimes separated by a cross-over temperature $T^*$. Up to $T^*$ the nonlinear zero-temperature shape of the current-voltage curves survives, but with a threshold voltage for conduction that decreases linearly with temperature. Above $T^*$ the threshold vanishes and the low-bias conductance increases rapidly with temperature. We develop a model that accounts for these findings and predicts $T^*$., Comment: 5 pages including 3 figures; replaced 3/30/04: minor changes; final version

We investigate the impact of structural disorder on electronic transport in gold nanocrystal monolayers. Arrays ranging from void-filled networks to well-ordered superlattices show clear voltage thresholds V_T due to Coulomb blockade, and temperature-independent conduction indicative of quantum tunneling. Current-voltage characteristics of arrays with and without long-range structural order were found to collapse onto distinct scaling curves. The former follow a single power-law: I (V-V_T)^\zeta, \zeta = 2.25+/-0.1. The latter show additional structure, reflecting the underlying disordered topology., Comment: 4 pages, 3 figures. Figure 1 is best viewed in the PostScript version.