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Research Projects

Designer optical nanocomposites for up- and down-conversion

Designer optical nanocomposites for up- and down-conversion

This project aims to develop novel ‘designer’ glass ceramics based on a modified fluorozirconate (ZBLAN) glass composition, and to explore their luminescence behavior. The project goal is to gain insights leading to optimization of designer nanocomposites for applications as wavelength shifters pertaining to up- and down-converters in solar cells, and for applications in nuclear safety, border security and medical imaging.

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Integrative Materials Design (IMaD): Leverage, Innovate, & Disseminate

Integrative Materials Design (IMaD): Leverage, Innovate, & Disseminate

IMaD and the Midwest Big Data Hub will allow leading materials design projects and institutions to produce new integrated data resources and engage a broad community in the development and use of those resources. IMaD links and integrates the following projects and institutions: the NIST/MGI Center of Excellence for Hierarchical Materials Design (CHiMaD), involving Northwestern, UChicago, and Argonne; NSF MGI projects at Illinois and Wisconsin; the DOE PRedictive Integrated Structural Materials Science (PRISMS) Center at Michigan; the DOE Midwest Center for Computational Materials (MICCoM) involving Chicago, Northwestern, Michigan, and Notre Dame; and projects at NIST.

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Development of Sub 100 nm Resolution X-ray Nanotomography of Centimeter-Sized Tissues

Development of Sub 100 nm Resolution X-ray Nanotomography of Centimeter-Sized Tissues

We are developing and validating cryo confocal light microscopy of Bionanoprobe-mounted samples to complement X-ray fluorescence microscopes (XFM) with the capability to image selectively labeled proteins, and to move ptychography from 2D to 3D imaging. (Bionanoprobe is an instrument operated at the Advanced Photon Source (APS) at Argonne and open to researchers based on peer-reviewed, no-cost beamtime proposals.) This project is in the context of ongoing research in the use of DNA-conjugated nanoparticles containing titanium and/or gadolinium that are meant to target mitochondria for the treatment and imaging of prostrate, breast, and other cancers.

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ALETHEIA: A Framework for Automatic Detection/Correction of Corruptions in Extreme Scale Scientific Executions

ALETHEIA: A Framework for Automatic Detection/Correction of Corruptions in Extreme Scale Scientific Executions

This project aims at developing a new disruptive approach for detection/correction of systematic and non-systematic corruptions in executions composed of numerical simulation/data analytics followed by a lossy compression stage. We are developing a detection/correction framework following and extending the external algorithmic observer approach. We are investigating and modeling the features of several families of surrogate, lossy compression and approximate comparison functions. We consider five application domains: climatology, cosmology, astrophysics, fluid dynamics, weather forecasting. We are exploring the multi-objective problem of selecting the surrogate, lossy compression and approximate functions to optimize objectives set by the users and considering constraints also set by users. We will provide formulation and tools to help users make these selections.

Formation and Stability of Eutectic Nanostructures in Laser-Irradiated Particle Suspensions

Formation and Stability of Eutectic Nanostructures in Laser-Irradiated Particle Suspensions

To overcome the limitations of laser sources used with metallic and semiconducting materials, laser irradiation of eutectic alloys in particulate form is being employed to generate nanostructured eutectic composites. We are improving the understanding of the coupling between the particle size and the emergent eutectic length scales and investigating the efficacy of different embedding or suspension media, geometries, heat transfer and particle size. Further, we are employing a phase field modeling formalism to investigate the dynamics of solidification. Once a formalism for this modeling has been established, it will be applied to the fundamental study of eutectic solidification and wavelength selection at the nanoscale. We are exploring the complex interactions between initial particulate size, cooling rates, i.e., solidification rates, and thermal profiles with simulation. Data from these various simulations will be collected and characterized, whereby we may correlate the morphology of the eutectic structures, their length scales and the particle size and compare with experimental results.

Cyberalloys

Cyberalloys

To overcome the limitations of laser sources used with metallic and semiconducting materials, laser irradiation of eutectic alloys in particulate form is being employed to generate nanostructured eutectic composites. We are improving the understanding of the coupling between the particle size and the emergent eutectic length scales and investigating the efficacy of different embedding or suspension media, geometries, heat transfer and particle size. Further, we are employing a phase field modeling formalism to investigate the dynamics of solidification. Once a formalism for this modeling has been established, it will be applied to the fundamental study of eutectic solidification and wavelength selection at the nanoscale. We are exploring the complex interactions between initial particulate size, cooling rates, i.e., solidification rates, and thermal profiles with simulation. Data from these various simulations will be collected and characterized, whereby we may correlate the morphology of the eutectic structures, their length scales and the particle size and compare with experimental results.

Ptychography-based Rapid Imaging of Nano-Structures with Multi-layer Assemblies (PRISMA)

Ptychography-based Rapid Imaging of Nano-Structures with Multi-layer Assemblies (PRISMA)

To overcome the limitations of laser sources used with metallic and semiconducting materials, laser irradiation of eutectic alloys in particulate form is being employed to generate nanostructured eutectic composites. We are improving the understanding of the coupling between the particle size and the emergent eutectic length scales and investigating the efficacy of different embedding or suspension media, geometries, heat transfer and particle size. Further, we are employing a phase field modeling formalism to investigate the dynamics of solidification. Once a formalism for this modeling has been established, it will be applied to the fundamental study of eutectic solidification and wavelength selection at the nanoscale. We are exploring the complex interactions between initial particulate size, cooling rates, i.e., solidification rates, and thermal profiles with simulation. Data from these various simulations will be collected and characterized, whereby we may correlate the morphology of the eutectic structures, their length scales and the particle size and compare with experimental results.

Past Research Projects

Personalized Benchmarks for High Performance Computing Applications

Personalized Benchmarks for High Performance Computing Applications

The goal of this project is to develop methods to provide personalized supercomputing I/O benchmarks and analytics that represent the entire range of production workloads. To do this we are instrumenting a broad sampling of jobs at production HPC facilities, automating analysis of that instrumentation, and creating customized benchmarks that reflect the aggregate workload of the system.

Data-driven Discovery of Novel Thermoelectric Materials

Data-driven Discovery of Novel Thermoelectric Materials

Data-driven effort to discover high-ZT thermoelectrics within an integrated computational materials engineering framework, bridging length scales and heterogeneous datasets. This project plans on developing tools for integrating heterogeneous materials property databases, determine functional relationships that describe the behavior of complex materials, and exploit these relationships to develop novel high-ZT thermoelectric materials.

Materials Genome Initiative for Global Competitiveness

Materials Genome Initiative for Global Competitiveness

NAISE brings together Argonne's and Northwestern's strengths in materials, scientific computation, energy and nanoscience to focus on research related to the Materials Genome Initiative for Global Competitiveness. Recently announced by the Obama administration, the Initiative focuses on an integrated computational and experimental approach to the design of materials. With the ability to compute the properties of multiphase multicomponent materials, and to verify these codes experimentally, it is possible to design materials prior to synthesis in the laboratory. This process can speed materials to the marketplace by drastically reducing testing and verification times. Just as bioinformatics has impacted the field of molecular biology, this new approach to materials design promises a similar effect. New materials resulting from this process will address the nation’s challenges in energy, national security, and human health. • PROJECT: Mesoscale Electrochemical Modeling This project is aimed at developing a scalable mesoscale computational model for the Li insertion process that accompanies the charge and discharge cycles in materials that are used for cathodes in Li-ion batteries. The code will be developed such that it can be used to assess reliability and guide the design of future materials.

Interfacial Polymer Properties in Glass Fiber Composites

Interfacial Polymer Properties in Glass Fiber Composites

This project develops new measurement tools,that will provide accurate structure-property relationships for toughened Glass Fiber Polymer Composites. We are using interfacial shear strength (IFSS) measurements, atomic force microscopy (AFM), multi-functional molecular probes, and advanced fluorescence microscopy to explore the importance of glass-surface chemistry in controlling composite properties such as strength, toughness and service-life. These measurement tools are used to determine how to better characterize the properties of the interphase of GFPCs.

Compute on Data Path: Combating Data Movement in High Performance Computing

Compute on Data Path: Combating Data Movement in High Performance Computing

Northwestern University manages the storage and data movement component of this project. The storage component serves as persistent storage for the input and output of the programs executed using the compute-on-data path approach. Backwards compatibility is provided through this component, making it possible to inject legacy files into the compute-on-data path system. The data movement component handles transporting input and output data between all of the nodes executing the application. In addition, Northwestern University is leading the evaluation of the proposed system. This includes working with the other project partners to select and integrate a number of representative applications, and evaluate the performance of those applications under the proposed system.

Electrochemical Society Symposium on GaN and SiC Power Technologies 4

Electrochemical Society Symposium on GaN and SiC Power Technologies 4

The main objective of the proposed project is to organize an industry session at the ECS Symposium on GaN and SiC Power Technologies 4 to discuss the workforce development needs in order to successfully address the daunting challenges faced by the wide bandgap (WBG) power electronics supply chain manufacturing industry. The Symposium is an integral part of the Electrochemical Society (ECS) Fall 2014 meeting to be held in Cancun, MX during October 5-10, 2014. The funds received from the NSF will be used to partially support the expenses incurred by the students in attending this conference session. Minority and women students will be encouraged to attend the conference.

CINET

CINET

Working with collaborators at Virginia Tech and Indiana University, we are exploring automated mechanisms for configuring virtual machine (VM) images to run on cloud research at Argonne National Laboratory. The VMs will be designed to allow both storage of integrated data sets, for use by large open communities, as well as on-demand computational resources. The integration of this on-demand resource is key to easy deployment and use, and we will explore APIs and remote interfaces that allow CINet users to access, start, and stop resources as the work. Finally, while many VM environments use single node images for cloud computing, we expect that CINet users will need larger computational resources, and will explore the automatic integration of MPI-based multi-node VM environments by utilizing the Nimbus infrastructure.