Javed I. Khan, Ph.D - US grants

Julia Fulghum and Javed Khan of Kent State University are supported by the Division of Chemistry under the Information Technology Research (ITR) program to create new methods for the non-destructive, three-dimensional characterization of heterogeneous, solid polymeric materials. Data will be acquired from polymer samples of increasing complexity using a variety of analytical techniques, including x-ray photoelectron spectroscopy, time-of-flight secondary ion mass spectrometry, and Fourier transform infrared spectroscopy. All of these methods can be used to obtain chemical information from different sample volumes, and to generate multidimensional data sets. Multivariate statistical analysis and classification methods will be used to enhance interpretation of the acquired data sets, ultimately enabling creation of a unified polymer framework, called an active knowledge mesh. The combined system will create synergy between the computer and the user in large and complex information space exploration, posing interesting challenges for multi-modal data analysis and its multi-perspective visualization.

Polymers are widely used in a variety of high technology applications. For example, many current and proposed biomaterials are polymers, and polymers are contained as well in composites used for a light aircraft and automobiles. Commercially important materials often involve molecularly complex polymer blends whose surface chemistry and structure are particularly challenging to analyze. Outcomes from this project are expected to improve the understanding and evaluation of complex polymer blend characteristics, and ultimately enable enhanced control of technologically important materials properties.

This collections project builds on the advances in information technology, the Internet, and the World Wide Web that provide opportunities to create and disseminate rich scientific content to many people. To capitalize on these advances, this project provides bridges for novice and expert users to find useful content. The project researches the best delivery of a materials digital library using a three-pronged approach which consists of use of materials digital library content in the curriculum, collection of materials content with an emphasis on soft matter, and construction of authoring tools for improved delivery. Submission, editing, and composing tools enable experts and novices to characterize their contributions to the Materials Digital Library, as materials scientists would, using metadata schemas such as Dublin Core and IEEE Learning Object Metadata as well as domain-specific markup languages such as Materials Markup Language. Metadata records are stored in XML based format to support generation of other materials resources such as automated classification schemes, glossaries, and thesauri.

Initial content of the Materials Digital Library is based on existing resources selected from the Materials Science and Engineering Laboratory at the National Institute of Standards and Technology.
Students and educators in three Materials Science Engineering (MSE) courses use and contribute to the Materials Digital Library utilizing the proposed domain-specific tools. Two courses are part of MIT's newly revised undergraduate MSE curriculum and its OpenCourseWare Initiative. The first MIT course (Introduction to Solid State Chemistry) is a large freshmen undergraduate chemistry course with no laboratory component. The second MIT course, Introduction to Modeling and Simulation, is a multidisciplinary science course team-taught across seven engineering departments. The third course, Computational Nanoscience and Soft Matter taught at the University of Michigan, introduces students to cutting edge research on building new nanomaterials. MatWeb.com, the project's industrial partner, is working with the investigators to build a business plan and to host the Materials Digital Library as a sustainable enterprise.

The Office of Multidisciplinary Activities in the NSF Directorate for Mathematical and Physical Sciences (MPS) is providing significant co-funding of this project in recognition of the importance of materials science education within the goals of MPS.

This project will add an agile locally and globally sharable HPCC (High-Performance Computing Cluster) hosted in a ScienceDMZ enclave, integrated with national science computing facilities, including the Open Science Grid (OSG), by creatively using recent advances in federated science networking and distributed systems’ virtualization open to regional faculty. The system is composed of 18 nodes with dual Intel Xeon Gold 6242R class CPUs (20 core), 192GB RAM, and an NVIDIA A30 class GPUs. Storage is spread across the nodes using CEPH

The project supports several interesting newly emerging collaborative HPCC workflows- scienceware as-a-service (SAS) and science-data-lakes (SDL), and intense real-time-computing (iRTC) besides supporting the HPC and HTC workflows. NSF-funded resources in this project are open to all faculty researchers in northeast Ohio colleges and their collaborators, including the faculty of all eight campuses of Kent who are in the network’s latency proximity and engaged in data-intensive collaborative workflows. In order to support high throughput and collaborative computing, the ScienceDMZ exercises a new model of unimpeded host-centric cauterized and federated security, as opposed to the traditional perimeter focused security approach. It is already fronted by a 100-Gbps Data Transfer Node (DTN) capable of ‘friction-free’ long-haul transferring massive datasets.

The project directly contributes to NSF’s goals to foster innovation, integration, and engineering of new campus-level networking and cyberinfrastructure that can assertively support widely collaborative, multi-campus distributed massive-data driven research and harness largely untapped potential to share unused compute cycles and resources across the entire academic fabric, while leveraging a compelling set of science projects from a wide variety of disciplines.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.