Nicola J. Ferrier

Characterization of the shape and line-edge roughness of polymer gratings with grazing incidence small-angle X-ray scattering and atomic force microscopy

Grazing-incidence small-angle X-ray scattering (GISAXS) is increasingly used for the metrology of substrate-supported nanoscale features and nanostructured films. In the case of line gratings, where long objects are arranged with a nanoscale periodicity perpendicular to the beam, a series of characteristic spots of high-intensity (grating truncation rods, GTRs) are recorded on a two-dimensional detector. The intensity of the GTRs is modulated by the three-dimensional shape and arrangement of the lines. Previous studies aimed to extract an average cross-sectional profile of the gratings, attributing intensity loss at GTRs to sample imperfections. Such imperfections are just as important as the average shape when employing soft polymer gratings which display significant line-edge roughness. Herein are reported a series of GISAXS measurements of polymer line gratings over a range of incident angles. Both an average shape and fluctuations contributing to the intensity in between the GTRs are extracted. The results are critically compared with atomic force microscopy (AFM) measurements, and it is found that the two methods are in good agreement if appropriate corrections for scattering from the substrate (GISAXS) and contributions from the probe shape (AFM) are accounted for.

Performance analysis, design considerations, and applications of extreme-scale in situ infrastructures

A key trend facing extreme-scale computational science is the widening gap between computational and I/O rates, and the challenge that follows is how to best gain insight from simulation data when it is increasingly impractical to save it to persistent storage for subsequent visual exploration and analysis. One approach to this challenge is centered around the idea of in situ processing, where visualization and analysis processing is performed while data is still resident in memory. This paper examines several key design and performance issues related to the idea of in situ processing at extreme scale on modern platforms: scalability, overhead, performance measurement and analysis, comparison and contrast with a traditional post hoc approach, and interfacing with simulation codes. We illustrate these principles in practice with studies, conducted on large-scale HPC platforms, that include a miniapplication and multiple science application codes, one of which demonstrates in situ methods in use at greater than 1M-way concurrency.

Multi-modal localization algorithm for catheter interventions

Localization of steerable catheters in minimally invasive surgery is critical with respect to patient safety, surgeon manipulation, and procedural efficacy. While there are many potential benefits to patients including shorter recovery times, less tissue trauma, and lower infection rates than traditional surgeries, localization of surgical tools is still an area of much research. Current technology offers several sensory modalities. However, each system has drawbacks which do not provide a clear best practice. This research focuses on incorporating redundant commonplace surgical sensing technologies to reduce the likelihood of errors, failures, or inherent sensor characteristics causing harm to the patient and/or surgeon while providing accurate localization. Dual particle filters are implemented using both a fluoroscopic-like stereo imaging system and an electromagnetic pose sensor for measurement updates in a prototype catheter testbed. A previously developed catheter model is modified to increase accuracy in the particle filter outputs which are combined using a weighted average based on each filters particle statistics. Experimental results implementing the combined particle filter multi-modality algorithm in feedback control validates the algorithms ability to provide accurate localization in a surgical setting while overcoming sensor limitations and possible failure modes.

Grazing-incidence small angle x-ray scattering studies of nanoscale polymer gratings

Grazing-Incidence Small Angle X-ray Scattering (GISAXS) offers the ability to probe large sample areas, providing three-dimensional structural information at high detail in a thin film geometry. In this study we exploit the application of GISAXS to structures formed at one step of the LiNe (Liu-Nealey) flow using chemical patterns for directed self-assembly of block copolymer films. Experiments conducted at the Argonne National Laboratory provided scattering patterns probing film characteristics at both parallel and normal directions to the surface. We demonstrate the application of new computational methods to construct models based on scattering measured. Such analysis allows for extraction of structural characteristics at unprecedented detail.

Reduced electron exposure for energy-dispersive spectroscopy using dynamic sampling

Analytical electron microscopy and spectroscopy of biological specimens, polymers, and other beam sensitive materials has been a challenging area due to irradiation damage. There is a pressing need to develop novel imaging and spectroscopic imaging methods that will minimize such sample damage as well as reduce the data acquisition time. The latter is useful for high-throughput analysis of materials structure and chemistry. In this work, we present a novel machine learning based method for dynamic sparse sampling of EDS data using a scanning electron microscope. Our method, based on the supervised learning approach for dynamic sampling algorithm and neural networks based classification of EDS data, allows a dramatic reduction in the total sampling of up to 90%, while maintaining the fidelity of the reconstructed elemental maps and spectroscopic data. We believe this approach will enable imaging and elemental mapping of materials that would otherwise be inaccessible to these analysis techniques.

Improved deconvolution of very weak confocal signals

Deconvolution is typically used to sharpen fluorescence images, but when the signal-to-noise ratio is low, the primary benefit is reduced noise and a smoother appearance of the fluorescent structures. 3D time-lapse (4D) confocal image sets can be improved by deconvolution. However, when the confocal signals are very weak, the popular Huygens deconvolution software erases fluorescent structures that are clearly visible in the raw data. We find that this problem can be avoided by prefiltering the optical sections with a Gaussian blur. Analysis of real and simulated data indicates that the Gaussian blur prefilter preserves meaningful signals while enabling removal of background noise. This approach is very simple, and it allows Huygens to be used with 4D imaging conditions that minimize photodamage.

Particle tracking and extended object imaging by interferometric super resolution microscopy

An interferometric fluorescent microscope and a novel theoretic image reconstruction approach were developed and used to obtain super-resolution images of live biological samples and to enable dynamic real time tracking. The tracking utilizes the information stored in the interference pattern of both the illuminating incoherent light and the emitted light. By periodically shifting the interferometer phase and a phase retrieval algorithm we obtain information that allow localization with sub-2 nm axial resolution at 5 Hz.

Designing a High-Throughput Pipeline for Digitizing Pinned Insects

This paper presents the design and prototyping of hardware and software to address the problem of rapid and reliable 3D digitization of very large collections of pinned insects. Using the collection at the Field Museum of Natural History (FMNH) as a use case, a pipeline to ingest the entire collection of 4.5 million specimens in circa 1-2 years imposes a few second limit on average processing time per specimen. We describe the design and implementation of multi-camera systems capable of rapidly capturing light field imagery for 3D reconstruction of label surfaces and specimen in single snapshots consistent with this time constraint. With imagery captured using these prototype multi-cameras we demonstrate methods under development for 3D reconstruction of pinned insect specimens and for processing text on label surfaces.

Integrated Dynamic 3D Imaging of Microbial Processes and Communities in Rhizosphere Environments: The Argonne Small Worlds Project

K. M. Kemner, M. Hereld, N. Scherer, A. Selewa, X. Wang, I. Gdor, M. Daddysman, J. Jureller, T. Huynh, O. Cossairt, A. Katsaggelos, K. He, S. Yoo, N. Matsuda, B. Glick, P. La Riviere, J. Austin, K. Day, T. Chandler, S. Papanikou, N. Ferrier, D. Sholto-Douglas, D. Gursoy, O. Antipova, C. Soriano, S. O’Brien, R. Wilton, A. Ahrendt, M. Asplund, S. Zerbs, P. Noirot, C. Atkins, G. Babnigg, J. Johnson, S. Shinde, P. Korajczyk, M. F. Noirot

Under-sampling and Image Reconstruction for Scanning Electron Microscopes

Electron Microscopes have been used to investigate materials from micron to nano scale. Scanning electron microscopes (SEM) as well as scanning transmission electron microscopes (STEM) can acquire image data relatively fast, however acquiring spectroscopic data requires longer data collection times. Depending on the desired resolution or sample area, this can make a significant difference in the duration and feasibility of the experiment. Moreover, for electron beam sensitive samples, it is necessary to acquire the image data with minimal exposure time as not to further damage the sample [1]. Here, we propose an under-sampling and reconstruction method to reduce the data collection time while maintaining imaging accuracy.