Proposal submission instructions

DESCRIPTION: Lightweight materials such as laminated composites and polymer materials are being increasingly used in the aerospace industry mainly due to their high strength and high stiffness to weight ratios. In existing military helicopters, such as the UH-60, composites are used to build the main rotor blade, the tail rotor flexbeam spar, and several major airframe components [1]. Composite structures are susceptible to degradation due to prolonged use, exposure to severe service environment, fatigue, sand abrasion as well as operator abuse and neglect [2].

The failure of polymeric materials and composites begins on a molecular level when local strains contribute to chain slippage or rupture leading to a loss of structure or modulus. Polymers under repeated cycles of mechanical stress will eventually experience chain slippage and bond breakage, which can initiate micro-cracks that propagate and lead to mechanical failure. Conversely, in biological materials, where molecules and tissues are mechanochemically activated, a repeated cycle of mechanical load and/or molecular-scale damage causes muscle fibers to strengthen through active reinforcement and growth processes.

This topic calls for unique approaches to facilitate mechanochemical reactions induced by bonds bending, flexing, and/or rupturing within a polymer chain (i.e., either force-induced or damage-induced mechanisms) that will initiate stress sensing and damage resistance/mitigation. The goal is to have molecular mechanochemical responses facilitate a constructive response to a destructive force.

Recent studies have shown that fluorescent or photochromic dyes can highlight hard-to-detect damage in composite structures by chemically incorporating force-activated molecular units directly into the polymer, matrix, or interphase material. When sufficient force is applied in the proper orientation, strain responsive molecules respond with a change in chemical activity at the molecular scale (i.e., change in absorbance, light emission, change in charge, activation/deactivation of a catalyst, etc.) that is often reversible. This topic seeks a novel mechanochemical-based composite material design that is able to detect and actively mitigate early stages of microscopic damage such as delamination, fiber fracture, and interfacial debonding autonomously.

This topic seeks a mechanochemical solution to sensing and repairing macromolecular damage in polymer matrix materials. It is anticipated that this could be achieved through the use of mechanochemically active molecules to trigger chemical reactions in response to macroscopic stresses and strains, and also allow that these same molecules could initiate active reinforcement and self-healing to mitigate structural damage.

PHASE I: Design a mechanochemical-based composite material system that can detect molecular-scale damage prior to failure. Successful efforts are expected to: 1) characterize and predict the relationship between macromolecular and intermolecular forces, 2) leverage mechanochemical interactions and design composites to exploit these to respond to and mitigate the early stages of structural damage and mechanical deformation, 3) demonstrate and quantify the stress-sensing and/or self-healing response in novel stimuli-responsive composites, and 4) estimate the extent of damage detection and mitigation/healing under typical operating and loading conditions.

PHASE II: Fabricate a mechanochemical-based composite material system that can detect and mitigate sub-micron-scale damage. Successful efforts are expected to: 1) demonstrate the ability to detect and track damage at a length scale one order of magnitude smaller than complementary commercially available damage detection techniques (i.e., optical, ultrasonic, thermal, penetration, radiography, eddy current, microCT, etc.), and 2) manufacture test pieces or articles suitable for full-scale testing and demonstration.

PHASE III DUAL USE APPLICATIONS: Scale the manufacturing process for producing novel mechanochemical-based composites and products. An embedded materials solution capable of self-sensing and self-healing would be of great benefit to the U.S. Military and commercial aircraft platforms for increased reliability, reduced maintenance costs, and enhanced durability and resistance to damage.

REFERENCES:

1. Smith HR (2013) Army adopts stronger, lighter composite materials. Available at: www.army.mil/article/107563/Army_adopts_stronger__lighter_composite_materials (accessed 25 April 2015)

2. Drwiega A (2013) Future Vertical Lift: An Overview. Available at:

3. Gourley SR (2013) Joint Multi-Role (JMR): The Technology Demonstrator Phase Contenders. Available at: http://www.defensemedianetwork.com/stories/joint-multi-role-jmr-the-technology-demonstrator-phase-contenders/ (accessed 25 April 2015)

4. Hall A, Haile MA, Yoo JH, Haynes R and Coatney M, “Structural Health Sensing of Damage Precursors using Magnetostrictive Particles Embedded in Composite Structures", Proceedings for American Helicopter Society, 70th annual Forum and Technology Display, 20-22 May 2014, Montreal, Canada.

5. J. Larsen, et al., “Opportunities and Challenges in Damage Prognosis for Materials and Structures in Complex Systems," AFOSR Discovery Challenge Thrust (DCT) Workshop on Prognosis of Aircraft and Space Devices, Components and Systems, Cincinnati, Ohio, Feb 19-20, 2008.

6. Sun BN, Hou HS and Hsiao CC (1988) Analysis of crack-induced-craze in polymers. Engineering Fracture Mechanics 30(5):595-607.

7. Haile MA, Chen TK, Sediles F, Shiao M and Le D (2012) Estimating crack growth in rotorcraft structures subjected to mission load spectrum. International Journal of Fatigue 43:142-149

8. Makyla, K. Muller, C. Lorcher, S., Winkler, T., Nussbaumer, M., Eder, M., Bruns, N., “Fluorescent Protein Senses and Reports Mechanical Damage in Glass-Giver-Reinforced Polymer Composites", Advanced Materials, Vo. 25, N 19, (2013) 2701-2706.

KEYWORDS: embedded materials solution, early stages of damage detection, in-situ structural health monitoring

TECHNOLOGY AREA(S): Information Systems

OBJECTIVE: Develop new algorithms to accurately, compactly, and efficiently summarize large amounts of data on existing petascale and future exascale systems. These will be used to (i) minimize communication/data movement by passively coordinating statistical data compression across nodes, (ii) find anomalies in data in real time by supporting fast likelihood estimation for data as it is generated, and therefore, (iii) perform on-the-fly data curation, reduction, analysis and visualization across nodes.

DESCRIPTION: In both DoD and industry, unprecedented amounts of data are being generated from many sources, including sensors and simulations. In DoD-related R&D and on High Performance Computing (HPC) machines both owned by DoD and used in support of DoD R&D, data-driven discovery and data-management are critical areas requiring significant algorithmic developments and the creation of libraries and tools that can be used in a transformational way across many disciplines. Current big-data challenges are further exacerbated by the not-so-distant arrival of exascale scientific computing, which promises both capabilities for study in new data regimes, but also increased technical challenges in scientific data management.

Improvements in data management will do more than enable better utilization of exascale machines, they may help make exascale machines feasible. Power requirements to operate HPC machines generally increase as processor and memory density increase; algorithmic methods for data summarization may reduce the amount of memory required per processor core, decreasing density requirements and thus power requirements. To support the type of massive parallelism desired for exascale systems, new global mechanisms for managing data movement and overall data summarization must be developed. In addition, the quantity of data generated by such a system requires that those new mechanisms be efficient with respect to memory usage, data movement, and computational complexity. In particular, all data management algorithms must efficiently process, analyze, and then summarize/reduce the supplied data in a single pass, while simultaneously minimizing data movement in the process.

We seek real-time algorithmic techniques, incorporated in new algorithms capable of accurately, compactly, and efficiently summarizing large amounts of data on existing petascale and future exascale systems. Recent fundamental understanding has been achieved in parallel methods for constructing multiscale data partition trees [1], fast estimation of network state performance [2], reduced basis methods applicable to data compression [3,4], and data movement costs at the device level [5]. Summarizations that are now possible with this understanding hold the possibility of helping (i) minimize communication and data movement by passively coordinating statistical data compression across nodes, (ii) find anomalies in data in real time by supporting fast likelihood estimation for data as it is generated, and therefore, (iii) serve as a general platform for real time data summarization, reduction, analysis, and visualization across nodes.

The developed data summarization and related algorithms will form the basis of a library/middleware layer that can be practically used on existing petascale and future exascale systems. This library will: (i) help developers utilize fast statistical estimation and summarization algorithms within next-generation computer software that is likely to have a reduced amount of memory available per core; (ii) provide real-time summarizations of data, possibly non-intrusively, so that a re-searcher can interact directly with simulations performed using existing software; (iii) allow fast statistical analysis of total system data (with error estimates); and (iv) facilitate summarization of data with minimal communication costs.

We anticipate that in this project, the library described above will be developed within the context of one or several application areas. This/these application area(s) are at the discretion of the proposer.

PHASE I: In Phase I, the following shall be accomplished:

a) Survey existing fast parallel methods for constructing multiscale data partition trees across system cores. Investigate suitability for implementation on different hardware architectures, such as Intel Xeon Phi, Nvidia GPU, and other processors.

PHASE II: In Phase II, the following shall be accomplished:

a) The fast parallel techniques for multiscale data partition trees investigated in Phase I will be developed and implemented for at least two different processor architectures.
b) The data summarization algorithm(s) developed in Phase I will be implemented. Additional workload due to data movement will be measured and reported under various run-time tasks and conditions.
c) The fast compression techniques investigated in Phase I will be developed and implemented. Performance under various run-time tasks and conditions will be measured and reported. Comparisons between actual and theoretical performance will be reported and sources of discrepancy will be investigated and explained..
d) The fast methods for data reduction, anomaly detection, and visualization for user monitoring of data summarization investigated in Phase I will be developed and implemented.
e) The final portable version of the software will be made available to interested government parties for assessment and use.
f) Interested users in academia and private industry will receive access to the software under appropriate licensing agreements.
g) Theoretical and numerical results of the study will be published in the peer-reviewed literature.
h) A comprehensive set of software documentation will be prepared and made available to users.
i) A long-term program for maintenance and subsequent improvement of the software will be created.
j) The company will set up a support service for both existing and new users capable of addressing installation issues and correcting bugs. This will include creating a web site with the latest news, FAQs, user' forum, etc.

PHASE III DUAL USE APPLICATIONS: The technology developed under this topic will be provide an effective real time summarization capability for streaming data in the application area(s) selected. It will generate reduced bases that can be used to solve problems of interest of interest, enabling the potential reduction in memory-per-core for exascale systems. The firm will follow-up on appropriate marketing opportunities in industry and licensing opportunities in academia from collaborations and contacts developed during earlier phases. Government retains rights to the delivered product and will utilize on problems of interest in its DSRC-managed HPC systems.

The end state of this project will be exascale computers (industrial, university, govt-DSRC) whose existence have been enabled by the lower power densities at the component level, in turn enabled by improved, more efficient and reduced data movement from these data summarization techniques at the middle-ware level. The end state includes new sysadmin and user capabilities for calling and visualizing summaries of data and data movement during run time. The end state will include predictive and engineering design applications such as synthetic biological simulations and designs at multiscale levels, enabled through the faster and more efficient passing of summarized data at the component level.

REFERENCES:

1. W. K. Allard, G. Chen, and M. Maggioni. Multi-scale Geometric Methods for Data Sets ii: Geometric multi-resolution analysis. Applied and Computational Harmonic Analysis, 32(3):435-462, 2012.

2. P. Balachandran, E. Airoldi, E. Kolaczyk, Inference of Network Summary Statistics Through Network Denoising, Statistical Machine Learning, arXiv:1310.0423, 2013

3. M. Barrault, Y. Maday, N.C. Nguyen, and A.T. Patera. An 'empirical interpolation' method: Application to efficient reduced-basis discretization of partial differential equations. C. R. Acad. Sci. Paris, Serie I, Vol. 339, 667-672, (2004)

4. D.B.P. Huynh, D.J. Knezevic, A.T. Patera. A static condensation reduced basis element method: Complex problems, Computer Methods in Applied Mechanics and Engineering, Vol 259, 197-216 (2013).

KEYWORDS: Scientific data management, Data summarization

A17A-T011

TITLE: Synthetic Biology Toolkit for Bioconversion of Food Waste

TECHNOLOGY AREA(S): Materials/Processes

OBJECTIVE: Develop a Clostridium molecular toolkit that enable engineering of Clostridium species (spp.) to convert food waste to fuel or other intermediates of value to reduce waste removal costs and to improve sustainability in the field.

DESCRIPTION: The Army has an urgent need for low-energy, portable solutions for bioconversion in an end-deployment field. Bioconversion can be used to produce fuels and materials, or to remove waste. There is a clear demand for bioconversion: at forward military bases, basic commodities such as gasoline can cost up to $400 per gallon due to delivery costs [1]. In addition, significant waste is generated at forward bases of which 87% are carbon-sources convertible to energy, averaging approximately 7 pounds per day - conversion of this waste would save up to $3500 per year per soldier [1] and significantly reduce waste removal costs.

While waste-to-energy technologies are under development to conduct limited bioconversion, these technologies are typically combustion-based and suffer from high equipment needs and significant energy usage. In addition, waste-to-energy technologies are unable to efficiently handle sources of diluted carbon without pretreatment. Specifically, food waste composes the majority of solid waste generated (19%), but also has the highest moisture content (54%) [2].

Microbes can be used for bioconversion of food waste through fermentation technology [3] to either biofuels worth $200-400/ton converted or specialty chemicals and materials such as plastics or enzymes worth $1000/ton converted [4]. Species of Clostridium have been explored for bioconversion such as Clostridium acetobutylicum [3], Clostridium beijerinckii [5], and Clostridium tyrobutyricum [6], among others. Clostridium is a particularly attractive target for its ability to make butanol, hydrogen, and valuable intermediates. However, Clostridium species have been minimally engineered due to the lack of characterization on the organism's regulatory regions and genetics, and the difficulty of growing and genetically engineering the organism. This project seeks to further characterize parts (i.e. biologically functional units) to allow for the synthetic biological engineering of Clostridium, as has been done extensively for model organisms such as E. coli and yeast [7].

The ultimate goal of this project is to develop a toolkit for the engineering of Clostridium for the application of bioconversion of food waste. If successful, these toolkits will allow the construction of efficient Clostridium-powered fermentations.

PHASE I: Develop assays to isolate and test transcriptional and translational regulatory regions, such as promoters and ribosome binding sites in Clostridium spp. that can produce higher-order compounds (butanol, ethanol, hydrogen, or other valuable intermediates to the Soldier in the field) from carbohydrates (or food waste simulant). The assays should use host derived transcriptional and translational machinery and can be cellular, or cell-free extract based and should be easily extensible to other organisms. The Phase I effort should include a proof-of-principle of the functionality of the assays, and demonstrate expression of non-host derived enzymes using a subset of at least 5 native regulatory elements with differential responses. Native or recombinant multi-enzyme pathways shall be identified where improved transcriptional and translational control will allow for modulation of metabolic output based upon internal and/or external cues.

PHASE II: Demonstrate the functionality of the assays by producing an expanded parts list of tested functional regulatory regions which are responsive to external and/or internal cues, and construct two of the identified pathways in Phase I in Clostridium spp. using the information obtained from the toolkit. Demonstrate that the genetic elements and circuits function, as designed, in the organism through demonstration of altered protein expression. Demonstrate transcriptional and translational control (via protein expression levels or metabolic output) in the engineered Clostridium using internal or external cues. Demonstrate that engineered Clostridium strains are able to convert food waste into the desired final products more efficiently (>100%) than a non-engineered strain in batch fermentation at an equivalent residence time. Assess scalability and cost-effectiveness of the engineered conversion process and reproducibility as a function of relevant food waste composition and benchmark it against the existing chemical-based technologies. Determine feasibility for ancillary beneficial processes (e.g. generation of potable water and removal of organics from food waste) as a function of the bioconversion process. Assess waste-to-energy conversion in terms of processing parameters (e.g. food waste composition, residence/conversion time, bacterial wash-out/replenishment schedules, etc.). Demonstrate functionality of the engineering toolkit for one or more additional bacteria including but not limited to other Clostridia spp., spore forming bacteria and/or extremophiles. The final deliverable of this effort includes: 1) a list of functional regulator regions and synthetic circuits if used, 2) engineered Clostridium strains, 3) design specifications/parameters for the food waste batch fermenter, 4) scalability and cost analysis, and 5) lab-scale feasibility (as a function of altered protein expression or metabolic outputs) of extending engineering toolkit to at least one other relevant bacterial system.

PHASE III DUAL USE APPLICATIONS: The Phase III work will produce a refined genetic engineering toolkit for translation to a host of anaerobic/aerobic bacteria for engineered metabolic outputs based on variable food-derived waste inputs. The toolkit will support the commercially-viable, environmentally responsible design and development of a biologically-based food waste conversion process that can be integrated into an existing or new waste-to-energy conversion system for fielding within forward operating bases to mitigate complications in meeting fuel/energy and water demands. The waste-to-energy system will facilitate a cost-effective, efficient means for the conversion of food waste into higher-order compounds for generation of bioenergy (biofuels, biohydrogen, etc.) to operate generators, lights, vehicles, etc. in addition to other valuable co-products (e.g. potable water). Waste-to-energy systems also have dual-use applications within the civilian sector for efficient municipal waste products. Furthermore, the toolkit would be a basis for engineering other microorganisms, in addition to the novel Clostridium strain, that produce commercially-viable metabolic byproducts. The biologically-derived waste-to-energy solution must be cost effective and commercially competitive compared to existing chemical-based conversion systems.

REFERENCES:

1. L. M. Powell, "Converting Army Waste to Fuel: Mobile Integrated Sustainable Energy Recovery," 13th Annual North American Waste-to-Energy Conference pp. 5-6, Jan. 2005.

2. "US Army Central (USARCENT) Area of Responsibility (AOR) Contingency Base Waste Stream Analysis (CBWSA)," pp. 1-53, Apr. 2013.

3. M. D. Servinsky, S. Liu, and E. S. Gerlach, "Fermentation of oxidized hexose derivatives by Clostridium acetobutylicum," Microbial Cell Fact 13 2014.

4. E. Uckun Kiran, A. P. Trzcinski, W. J. Ng, and Y. Liu, "Bioconversion of food waste to energy: A review," Fuel, vol. 134, pp. 389-399, Oct. 2014.

5. H. Huang, V. Singh, and N. Qureshi, "Butanol production from food waste: a novel process for producing sustainable energy and reducing environmental pollution," Biotechnology for Biofuels 2015 8:1, vol. 8, no. 1, p. 1, Sep. 2015.

6. J. JO, D. LEE, D. Park, and J. PARK, "Biological hydrogen production by immobilized cells of Clostridium tyrobutyricum JM1 isolated from a food waste treatment process," Bioresource Technology, vol. 99, no. 14, pp. 6666-6672, Sep. 2008.

7. C. A. Voigt, Synthetic Biology, Part A: Methods for Part/Device Characterization and Chassis Engineering. 2011.

KEYWORDS: clostridium, food waste, bioconversion, low energy, synthetic biology, bioengineering, fermentation, cell-free