Ronald Pandolfi

Quantum dot/liquid crystal composite materials: self-assembly driven by liquid crystal phase transition templating

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.

Tuning Quantum-Dot Organization in Liquid Crystals for Robust Photonic Applications

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 ligands 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.

On-the-fly data assessment for high-throughput x-ray diffraction measurements

Investment in brighter sources and larger and faster detectors has accelerated the speed of data acquisition at national user facilities. The accelerated data acquisition offers many opportunities for the discovery of new materials, but it also presents a daunting challenge. The rate of data acquisition far exceeds the current speed of data quality assessment, resulting in less than optimal data and data coverage, which in extreme cases forces recollection of data. Herein, we show how this challenge can be addressed through the development of an approach that makes routine data assessment automatic and instantaneous. By extracting and visualizing customized attributes in real time, data quality and coverage, as well as other scientifically relevant information contained in large data sets, is highlighted. Deployment of such an approach not only improves the quality of data but also helps optimize the usage of expensive characterization resources by prioritizing measurements of the highest scientific impact. We anticipate our approach will become a starting point for a sophisticated decision-tree that optimizes data quality and maximizes scientific content in real time through automation. With these efforts to integrate more automation in data collection and analysis, we can truly take advantage of the accelerating speed of data acquisition.

Critical-dimension grazing incidence small angle x-ray scattering

With the advent of high brightness sources and fast detectors, there is a possibility for combining fast X-ray acquisition with high-speed data treatment to reach the timescale for an effective in-line characterization method. We will highlight two recent developments using Small Angle X-ray Scattering on nanoscale etched patterns: the first is the inclusion of a CD-SAXS tool, allowing the data treatment and simulations to reconstruct the form-factor, inside the Xi-cam framework; the second is the development of a high performance Grazing Incidence approach to reconstruct the shape of line profile. This study also shows the comparison between the line profiles reconstructed from both techniques as well as the profile extracted from cross-section SEM.

Using resonant soft x-ray scattering to image patterns on undeveloped resists

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.

Designing highly tunable semiflexible filament networks

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.