Kevin G. Yager

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Organization of spherical particles into lattices is typically driven by packing considerations. Although the addition of directional binding can significantly broaden structural diversity, nanoscale implementation remains challenging. Here we investigate the assembly of clusters and lattices in which anisotropic polyhedral blocks coordinate isotropic(More)
Self-assembly of block copolymers is a powerful motif for spontaneously forming well-defined nanostructures over macroscopic areas. Yet, the inherent energy minimization criteria of self-assembly give rise to a limited library of structures; diblock copolymers naturally form spheres on a cubic lattice, hexagonally packed cylinders and alternating lamellae.(More)
Directed self-assembly (DSA) of block copolymers is an emergent technique for nano-lithography, but is limited in the range of structures possible in a single fabrication step. Here we expand on traditional DSA chemical patterning. A blend of lamellar- and cylinder-forming block copolymers assembles on specially designed surface chemical line gratings,(More)
Diamond lattices formed by atomic or colloidal elements exhibit remarkable functional properties. However, building such structures via self-assembly has proven to be challenging because of the low packing fraction, sensitivity to bond orientation, and local heterogeneity. We report a strategy for creating a diamond superlattice of nano-objects via(More)
Epitaxial van der Waals (vdW) heterostructures of organic and layered materials are demonstrated to create high-performance organic electronic devices. High-quality rubrene films with large single-crystalline domains are grown on h-BN dielectric layers via vdW epitaxy. In addition, high carrier mobility comparable to free-standing single-crystal(More)
Coherent X-ray scattering is an emerging technique for measuring structure at the nanoscale. Data management and analysis is becoming a bottleneck in this technique. We present an unsupervised method which can sort and cluster the scattering snapshots, uncovering patterns inherent in the data. Our algorithm operates without resorting to templates, specific(More)
Self-assembly is a powerful paradigm, wherein molecules spontaneously form ordered phases exhibiting well-defined nanoscale periodicity and shapes. However, the inherent energy-minimization aspect of self-assembly yields a very limited set of morphologies, such as lamellae or hexagonally packed cylinders. Here, we show how soft self-assembling(More)
While equilibrium block-copolymer morphologies are dictated by energy-minimization effects, the semi-ordered states observed experimentally often depend on the details of ordering pathways and kinetics. Here, we explore reordering transitions in thin films of block-copolymer cylinder-forming polystyrene-block-poly(methyl methacrylate). We observe several(More)
Visual inspection of x-ray scattering images is a powerful technique for probing the physical structure of materials at the molecular scale. In this paper, we explore the use of deep learning to develop methods for automatically analyzing x-ray scattering images. In particular, we apply Convolutional Neural Networks and Convolutional Autoen-coders for x-ray(More)
The National Synchrotron Light Source II (NSLS-II) at Brookhaven National Laboratory (BNL) is now providing some of the world's brightest x-ray beams. A suite of imaging and diffraction methods, exploiting megapixel detectors with kilohertz frame-rates at NSLS-II beamlines, generate a variety of image streams in unprecedented velocities and volumes. A(More)