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Open Access Publications from the University of California

Scholarly Works (10 results)

  • Thesis
  • Peer Reviewed
UC Merced Electronic Theses and Dissertations (2014)

Soft materials are a diverse and rich field of interest. Materials which form structure by their own self-assembly are of special interest. New material properties can be achieved by the self-assembly of constituent soft matter. Two soft matter systems are investigated in this dissertation from different perspectives. An in silico approach is applied to explore semiflexible polymers; X-ray scattering is applied to probe QD-LC composites.

Semiflexible polymers can generate a range of filamentous networks significantly different in structure from those seen in conventional polymer solutions. Our coarse-grained simulations with an implicit cross-linker potential show that networks of branching bundles, knotted morphologies, and structural chirality can be generated by a generalized approach independent of specific cross-linkers. Network structure depends primarily on filament flexibility and separation, with significant connectivity increase after percolation. Results should guide the design of engineered semiflexible polymers.

Thermotropic liquid crystal provides an active basis for organization of nanoparticles. Using a bottom-up approach, nanoparticles well dispersed in the isotropic phase can be self-assembled by exclusion from the nematic phase as the material cools from the isotropic phase. A ligand exchange reaction can be used to create nanoparticles with mesogenic ligand coatings to allow better dispersion and assemble novel structures. Small angle X-ray scattering is used to inform the structure of a variety of materials which apply this design concept. These metamaterials have tunable properties with applications in quantum dot based electro-optic devices and more.

    Cover page: Self-assembly and Design of Tunable Soft Materials
    • Article
    • Peer Reviewed
    UC Merced Previously Published Works (2014)
    Semiflexible polymers can generate a range of filamentous networks significantly different in structure from those seen in conventional polymer solutions. Our coarse-grained simulations with an implicit cross-linker potential show that networks of branching bundles, knotted morphologies, and structural chirality can be generated by a generalized approach independent of specific cross-linkers. Network structure depends primarily on filament flexibility and separation, with significant connectivity increase after percolation. Results should guide the design of engineered semiflexible polymers.
      Cover page: Designing highly tunable semiflexible filament networks
      • Article
      • Peer Reviewed
      UC Merced Previously Published Works (2013)
      The isotropic to nematic liquid crystal (LC) phase transition is used to create organized assemblies of CdSe/ZnS core/shell quantum dots (QDs). Under controlled conditions, well dispersed QDs are expelled from the ordered domains of nematic LC into the remaining isotropic domains. The final LC phase produces three dimensional QD assemblies that are situated at the defect points in the LC volume. Through the luminescence of the QDs we are able to track the movement of the nanoparticles as the phase is formed as well as spectrally probe the resulting QD assemblies. Forster resonance energy transfer (FRET) measurements, combined with small angle X-ray scattering (SAXS) data reveal that the QD assemblies have a consistent inter-particle spacing of approximately 7.6 nm. Additionally, the location of the assemblies is shown to be controllable by utilizing beads as defect nucleation points. © The Royal Society of Chemistry 2013.
        Cover page: Quantum dot /liquid crystal composite materials: self-assembly driven by liquid crystal phase transition templating
        • Article
        • Peer Reviewed
        UC Merced Previously Published Works (2015)
        A current goal in nanotechnology focuses on the assembly of different nanoparticle types into 3D organized structures. In this paper we report the use of a liquid crystal host phase in a new process for the generation of micron-scale vesicle-like nanoparticle shells stabilized by ligand-ligand interactions. The constructs formed consist of a robust, thin spherical layer, composed of closely packed quantum dots (QDs) and stabilized by local crystallization of the mesogenic ligands. Ligand structure can be tuned to vary QD packing within the shell and made UV cross-linkable to allow for intact shell extraction into toluene. The assembly method we describe could be extended to other nanoparticle types (metallic, magnetic etc.), where hollow shell formation is controlled by thermally sorting mesogen-functionalized nanoparticles in a liquid crystalline host material at the isotropic to nematic transition. This process represents a versatile method for making non-planar 3D nano-assemblies.
          Cover page: Self-assembled nanoparticle micro-shells templated by liquid crystal sorting
          • Article
          • Peer Reviewed
          UC Merced Previously Published Works (2015)
          The design and development of multifunctional composite materials from artificial nano-constituents is one of the most compelling current research areas. This drive to improve over nature and produce 'meta-materials' has met with some success, but results have proven limited with regards to both the demonstration of synergistic functionalities and in the ability to manipulate the material properties post-fabrication and in situ. Here, magnetic nanoparticles (MNPs) and semiconducting quantum dots (QDs) are co-assembled in a nematic liquid crystalline (LC) matrix, forming composite structures in which the emission intensity of the quantum dots is systematically and reversibly controlled with a small applied magnetic field (<100 mT). This magnetic field-driven brightening, ranging between a two- to three-fold peak intensity increase, is a truly cooperative effect: the LC phase transition creates the co-assemblies, the clustering of the MNPs produces LC re-orientation at atypical low external field, and this re-arrangement produces compaction of the clusters, resulting in the detection of increased QD emission. These results demonstrate a synergistic, reversible, and an all-optical process to detect magnetic fields and additionally, as the clusters are self-assembled in a fluid medium, they offer the possibility for these sensors to be used in broad ranging fluid-based applications.
            Cover page: Magnetic field induced quantum dot brightening in liquid crystal synergized magnetic and semiconducting nanoparticle composite assemblies
            • Article
            • Peer Reviewed
            LBL Publications (2019)
            Extreme ultraviolet (EUV) lithography is one of the most promising printing techniques for high-volume semiconductor manufacturing at the 14-nm half-pitch device node and beyond. However, key challenges around EUV photoresist materials, such as the exposure-dose sensitivity or the line-width roughness, continue to impede its full adoption into industrial nanofab facilities. Metrology tools are required to address these challenges by helping to assess the impact of the EUV materials' properties and processing conditions along different steps of the nanofabrication process. We apply the resonant soft x-ray scattering (RSoXS) technique to gain insights into the structure of patterned EUV resists before the development step takes place. By using energies around the carbon K-edge to take advantage of small differences in chemistry, the electronic density contrast between the exposed and unexposed regions of the resists could be enhanced in order to image the patterns with subnanometer precision. Critical-dimension grazing-incidence small-angle x-ray scattering is then performed at energies where the contrast is maximized, enabling the reconstruction of the three-dimensional shape of the latent image. We demonstrate the potential of RSoXS to provide a high-resolution height-sensitive profile of patterned EUV resists, which will help in quantifying the evolution of critical features, such as the line-edge roughness, at a key step of the nanofabrication process.
              • Article
              • Peer Reviewed
              UC Merced Previously Published Works (2014)
              Mesogenic ligands have the potential to provide control over the dispersion and stabilization of nanoparticles in liquid crystal (LC) phases. The creation of such hybrid materials is an important goal for the creation of soft tunable photonic devices, such as the LC laser. Herein, we present a comparison of isotropic and mesogenic ligands attached to the surface of CdSe (core-only) and CdSe/ZnS (core/shell) quantum dots (QDs). The mesogenic ligand's flexible arm structure enhances ligand alignment, with the local LC director promoting QD dispersion in the isotropic and nematic phases. To characterize QD dispersion on different length scales, we apply fluorescence microscopy, X-ray scattering, and scanning confocal photoluminescent imaging. These combined techniques demonstrate that the LC-modified QDs do not aggregate into the dense clusters observed for dots with simple isotropic ligands when dispersed in liquid crystal, but loosely associate in a fluid-like droplet with an average interparticle spacing >10 nm. Embedding the QDs in a cholesteric cavity, we observe comparable coupling effects to those reported for more closely packed isotropic ligands.
                Cover page: Tuning Quantum‐Dot Organization in Liquid Crystals for Robust Photonic Applications
                • Article
                • Peer Reviewed
                LBL Publications (2019)
                Nano-structured thin films have a variety of applications from waveguides, gaseous sensors to piezoelectric devices. Grazing Incidence Small Angle x-ray Scattering images enable classification of such materials. One challenge is to determine structure information from scattering patterns alone. This paper highlights the design of multiple Convolutional Neural Networks (CNN) to classify nanoparticle orientation in a thin film by learning scattering patterns. The network was trained on several thin films with a success rate of 94%. We demonstrate CNN robustness under different noises as well as demonstrate the potential of our proposed approach as a strategy to decrease scattering pattern analysis time.
                  • Article
                  • Peer Reviewed
                  LBL Publications (2018)
                  Extreme ultraviolet lithography is one of the most promising printing techniques for high volume semiconductor manufacturing at the 14 nm half-pitch device node and beyond. However, key challenges around EUV photoresist materials such as the exposure-dose sensitivity or the line-width roughness continue to impede the full adoption into industrial nanofab facilities. New metrology tools are required to address these challenges by helping to determine the impact of the EUV materials' properties and processing conditions on the roughness through the different step of the process. Here, we apply the resonant soft x-ray scattering (RSOXS) technique to gain insights into the structure of patterned EUV resists before the development step takes place. By using energies around the carbon absorption edge to take advantage of small differences in chemistry, the electronic density contrast between the exposed and unexposed regions of the resists could be enhanced in order to image the patterns with sub-nm precision. Critical-dimension grazing incidence small-angle X-ray scattering (CDGISAXS) was then performed at energies where the contrast was maximized, enabling the reconstruction of the 3D shape of the latent image. This demonstrates the potential of RSOXS to provide a high-resolution heightsensitive profile of patterned EUV resists, which will help to quantify the evolution of critical features, such as the line edge roughness, at each step of the nanofabrication process.
                    • Article
                    • Peer Reviewed
                    UC Berkeley Previously Published Works (2018)
                    Xi-cam is an extensible platform for data management, analysis and visualization. Xi-cam aims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms. Plugins are available for SAXS/WAXS/GISAXS/GIWAXS, tomography and NEXAFS data. With Xi-cam's `advanced' mode, data processing steps are designed as a graph-based workflow, which can be executed live, locally or remotely. Remote execution utilizes high-performance computing or de-localized resources, allowing for the effective reduction of high-throughput data. Xi-cam's plugin-based architecture targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis. Xi-cam is open-source and cross-platform, and available for download on GitHub.
                      Cover page: Xi‐cam: a versatile interface for data visualization and analysis
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