Slim Chourou

High aspect ratio sub-15 nm silicon trenches from block copolymer templates.

High-aspect-ratio sub-15-nm silicon trenches are fabricated directly from plasma etching of a block copolymer mask. A novel method that combines a block copolymer reconstruction process and reactive ion etching is used to make the polymer mask. Silicon trenches are characterized by various methods and used as a master for subsequent imprinting of different materials. Silicon nanoholes are generated from a block copolymer with cylindrical microdomains oriented normal to the surface.

HipGISAXS: a high-performance computing code for simulating grazing-incidence X-ray scattering data

This article describes the development of a flexible grazing-incidence small-angle X-ray scattering (GISAXS) simulation code in the framework of the distorted wave Born approximation that effectively utilizes the parallel processing power provided by graphics processors and multicore processors. The code, entitled High-Performance GISAXS, computes the GISAXS image for any given superposition of user-defined custom shapes or morphologies in a material and for various grazing-incidence angles and sample orientations. These capabilities permit treatment of a wide range of possible sample structures, including multilayered polymer films and nanoparticles on top of or embedded in a substrate or polymer film layers. In cases where the material displays regions of significant refractive index contrast, an algorithm has been implemented to perform a slicing of the sample and compute the averaged refractive index profile to be used as the reference geometry of the unperturbed system. A number of case studies are presented, which demonstrate good agreement with the experimental data for a variety of polymer and hybrid polymer/nanoparticle composite materials. The parallelized simulation code is well suited for addressing the analysis efforts required by the increasing amounts of GISAXS data being produced by high-speed detectors and ultrafast light sources.

PbS Nanoparticles Capped with Tetrathiafulvalenetetracarboxylate: Utilizing Energy Level Alignment for Efficient Carrier Transport

We fabricate a field-effect transistor by covalently functionalizing PbS nanoparticles with tetrathiafulvalenetetracarboxylate. Following experimental results from cyclic voltammetry and ambient-pressure X-ray photoelectron spectroscopy, we postulate a near-resonant alignment of the PbS 1Sh state and the organic HOMO, which is confirmed by atomistic calculations. Considering the large width of interparticle spacing, we observe an abnormally high field-effect hole mobility, which we attribute to the postulated resonance. In contrast to nanoparticle devices coupled through common short-chained ligands, our system maintains a large degree of macroscopic order as revealed by X-ray scattering. This provides a different approach to the design of hybrid organic-inorganic nanomaterials, circumvents the problem of phase segregation, and holds for versatile ways to design ordered, coupled nanoparticle thin films.

Massively parallel X-ray scattering simulations

Although present X-ray scattering techniques can provide tremendous information on the nano-structural properties of materials that are valuable in the design and fabrication of energy-relevant nano-devices, a primary challenge remains in the analyses of such data. In this paper we describe a high-performance, flexible, and scalable Grazing Incidence Small Angle X-ray Scattering simulation algorithm and codes that we have developed on multi-core/CPU and many-core/GPU clusters. We discuss in detail our implementation, optimization and performance on these platforms. Our results show speedups of ~125x on a Fermi-GPU and ~20x on a Cray-XE6 24-core node, compared to a sequential CPU code, with near linear scaling on multi-node clusters. To our knowledge, this is the first GISAXS simulation code that is flexible to compute scattered light intensities in all spatial directions allowing full reconstruction of GISAXS patterns for any complex structures and with highresolutions while reducing simulation times from months to minutes.

Large-scale Nanostructure Simulations from X-ray Scattering Data On Graphics Processor Clusters

X-ray scattering is a valuable tool for measuring the structural properties of materials used in the design and fabrication of energy-relevant nanodevices (e.g., photovoltaic, energy storage, battery, fuel, and carbon capture and sequestration devices) that are key to the reduction of carbon emissions. Although todays ultra-fast X-ray scattering detectors can provide tremendous information on the structural properties of materials, a primary challenge remains in the analyses of the resulting data. We are developing novel high-performance computing algorithms, codes, and software tools for the analyses of X-ray scattering data. In this paper we describe two such HPC algorithm advances. Firstly, we have implemented a flexible and highly efficient Grazing Incidence Small Angle Scattering (GISAXS) simulation code based on the Distorted Wave Born Approximation (DWBA) theory with C++/CUDA/MPI on a cluster of GPUs. Our code can compute the scattered light intensity from any given sample in all directions of space; thus allowing full construction of the GISAXS pattern. Preliminary tests on a single GPU show speedups over 125x compared to the sequential code, and almost linear speedup when executing across a GPU cluster with 42 nodes, resulting in an additional 40x speedup compared to using one GPU node. Secondly, for the structural fitting problems in inverse modeling, we have implemented a Reverse Monte Carlo simulation algorithm with C++/CUDA using one GPU. Since there are large numbers of parameters for fitting in the in X-ray scattering simulation model, the earlier single CPU code required weeks of runtime. Deploying the AccelerEyes Jacket/Matlab wrapper to use GPU gave around 100x speedup over the pure CPU code. Our further C++/CUDA optimization delivered an additional 9x speedup.