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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Combined Falling Drop/Open Port Sampling Interface System for Automated Flow Injection Mass Spectrometry

The aim of this work was to demonstrate and to evaluate the analytical performance of a combined falling drop/open port sampling interface (OPSI) system as a simple noncontact, no-carryover, automated system for flow injection analysis with mass spectrometry. The falling sample drops were introduced into the OPSI using a widely available autosampler platform utilizing low cost disposable pipet tips and conventional disposable microtiter well plates. The volume of the drops that fell onto the OPSI was in the 7–15 μL range with an injected sample volume of several hundred nanoliters. Sample drop height, positioning of the internal capillary on the sampling end of the probe, and carrier solvent flow rate were optimized for maximum signal. Sample throughput, signal reproducibility, matrix effects, and quantitative analysis capability of the system were established using the drug molecule propranolol and its isotope labeled internal standard in water, unprocessed river water and two commercially available buffer matrices. A sample-to-sample throughput of ~45 s with a ~4.5 s base-to-base flow injection peak profile was obtained in these experiments. In addition, quantitation with minimally processed rat plasma samples was demonstrated with three different statin drugs (atorvastatin, rosuvastatin, and fluvastatin). Direct characterization capability of unprocessed samples was demonstrated by the analysis of neat vegetable oils. Employing the autosampler system for spatially resolved liquid extraction surface sampling exemplified by the analysis of propranolol and its hydroxypropranolol glucuronide phase II metabolites from a rat thin tissue section was also illustrated.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Additive Lithography–Organic Monolayer Patterning Coupled with an Area-Selective Deposition

The combination of area-selective deposition (ASD) with a patternable organic monolayer provides a versatile additive lithography platform, enabling the generation of a variety of nanoscale feature geometries. Stearate hydroxamic acid self-assembled monolayers (SAMs) were patterned with extreme ultraviolet (λ = 13.5 nm) or electron beam irradiation and developed with ASD to achieve line space patterns as small as 50 nm. Density functional theory was employed to aid in the synthesis of hydroxamic acid derivatives with optimized packing density to enhance the imaging contrast and improve dose sensitivity. Near-edge X-ray absorption fine structure spectroscopy and infrared spectroscopy reveal that the imaging mechanism is based on improved deposition inhibition provided by the cross-linking of the SAM to produce a more effective barrier during a subsequent deposition step. With patterned substrates composed of coplanar copper lines and silicon spacers, hydroxamic acids selectively formed monolayers on the metal portions and could undergo a pattern-wise exposure followed by ASD in the first combination of a patternable monolayer with ASD. This material system presents an additional capability compared to traditional ASD approaches that generally reflect a starting patterned surface. Finally, this bottoms-up additive approach to lithography may be a viable alternative to subtractive nanoscale feature generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Assessment of wafer scale MoS 2 atomic layers grown by metal–organic chemical vapor deposition using organo-metal, organo-sulfide, and H 2 S precursors

Transition Metal Dichalcogenides (TMDs) are a unique class of materials that exhibit attractive electrical and optical properties which have generated significant interest for applications in microelectronics, optoelectronics, energy storage, and sensing. Considering the potential of these materials to impact such applications, it is crucial to develop a reliable and scalable synthesis process that is compatible with modern industrial manufacturing methods. Metal–organic chemical vapor deposition (MOCVD) offers an ideal solution to produce TMDs, due to its compatibility with large-scale production, precise layer control, and high material purity. Optimization of MOCVD protocols is necessary for effective TMD synthesis and integration into mainstream technologies. Additionally, improvements in metrology are necessary to measure the quality of the fabricated samples more accurately. In this work, we study MOCVD of wafer-scale molybdenum disulfide (MoS 2 ) utilizing two common chalcogen precursors, H 2 S and DTBS. We then develop a metrology platform for wafer scale samples quality assessment. For this, the coalesced films were characterized using Raman spectroscopy, atomic force microscopy, transmission electron microscopy, X-ray photoelectron spectroscopy, and Kelvin probe force microscopy. We then correlate the structural analysis of these grown films with electrical performance by using aerosol jet printing to fabricate van der Pauw test structures and assess sheet resistance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

ChemPren: a new and economical technology for conversion of waste plastics to light olefins

With the ever-increasing demand for plastics, sustainable recycling methods are key necessities. Here, the current plastics industry can manage to recycle only 10% of the 400 million metric tons of plastic produced globally. Waste plastics, in the current infrastructure, land up mostly in landfills. Although a lot of research efforts have been spent on processing and recycling co-mingled mixed plastics, energy-efficient sustainable and scalable routes for plastic upcycling are still lacking. Catalytic valorization of waste plastic feedstock is one of the potential scalable routes for plastic upcycling. Silica-alumina based materials, and zeolites have shown a lot of promise. A major interest lies in restricting catalyst deactivation, and refining product selectivity and yield for such catalytic processes. This article highlights ChemPren technology as a clean energy solution to waste plastic recycling. Co-mingled, mixed plastic feedstock along with spray dried, attrition resistant, ZSM-5 containing catalysts is preprocessed with an extruder to form optimally sized particles and fed into a fluidized bed reactor for short contact times to produce selectively and in high yields ethylenes, propylenes and butylenes. This techno-economic perspective indicates that the ChemPren technology can produce propylene at $\$$0.16 per lb, whereas the current selling price of virgin propylene is $0.54 per lb. This technology can serve as a platform for mixed plastic upcycling, with more advancements necessary in the form of robust and resilient catalysts and reactor operation strategies for tuning product selectivity.

25 - ENERGY STORAGE↗
DOE OSTI2026

A Short-Lived Isotope Counting System (SLICS) to measure reaction cross sections producing light, beta-decaying nuclei on OMEGA

A new activation detector optimized for short-lived isotopes was designed, installed, and tested on OMEGA. The Short-Lived Isotope Counting System (SLICS) can be positioned as close as 35 cm from the OMEGA target chamber center in a ten-inch-manipulator. Stable target samples can be mounted on the front end of the detector assembly to undergo triton-, deuteron-, or neutron-induced reactions that produce short-lived reaction products that beta decay. The emitted betas are detected in a phoswich configuration to eliminate the gamma background. The detector is optimized for isotopes with half-lives from 150 ms to 20 s, filling a gap in OMEGA’s current activation detectors for isotopes with half-lives >5 min. In a pilot study, SLICS achieved an efficiency of 24.5% ± 2.0% for counting 8Li, with a total of 505.8 ± 4.4 qualifying events. Using the existing triton laser-ion acceleration platform on OMEGA, this detector can be used to measure rarely studied tritium-induced reactions on light nuclei with an estimated uncertainty of 12%. As a result, the design of the detector and its performance during a first experiment employing deuterium as a surrogate will be discussed.

Beta spectrometry↗
NASA NTRS2000

Photon-Counting Multikilohertz Microlaser Altimeters for Airborne and Spaceborne Topographic Measurements

We consider the optimum design of photon-counting microlaser altimeters operating from airborne and spaceborne platforms under both day and night conditions. Extremely compact Q-switched microlaser transmitters produce trains of low energy pulses at multi-kHz rates and can easily generate subnanosecond pulse-widths for precise ranging. To guide the design, we have modeled the solar noise background and developed simple algorithms, based on Post-Detection Poisson Filtering (PDPF), to optimally extract the weak altimeter signal from a high noise background during daytime operations. Practical technology issues, such as detector and/or receiver dead times, have also been considered in the analysis. We describe an airborne prototype, being developed under NASA's instrument Incubator Program, which is designed to operate at a 10 kHz rate from aircraft cruise altitudes up to 12 km with laser pulse energies on the order of a few microjoules. We also analyze a compact and power efficient system designed to operate from Mars orbit at an altitude of 300 km and sample the Martian surface at rates up to 4.3 kHz using a 1 watt laser transmitter and an 18 cm telescope. This yields a Power-Aperture Product of 0.24 W-square meter, corresponding to a value almost 4 times smaller than the Mars Orbiting Laser Altimeter (0. 88W-square meter), yet the sampling rate is roughly 400 times greater (4 kHz vs 10 Hz) Relative to conventional high power laser altimeters, advantages of photon-counting laser altimeters include: (1) a more efficient use of available laser photons providing up to two orders of magnitude greater surface sampling rates for a given laser power-telescope aperture product; (2) a simultaneous two order of magnitude reduction in the volume, cost and weight of the telescope system; (3) the unique ability to spatially resolve the source of the surface return in a photon counting mode through the use of pixellated or imaging detectors; and (4) improved vertical and transverse spatial resolution resulting from both (1) and (3). Furthermore, because of significantly lower laser pulse energies, the microaltimeter is inherently more eyesafe to observers on the ground and less prone to internal optical damage, which can terminate a space mission prematurely.

Degnan, John J.↗
NASA NTRS2011

Optimal Padding for the Two-Dimensional Fast Fourier Transform

One-dimensional Fast Fourier Transform (FFT) operations work fastest on grids whose size is divisible by a power of two. Because of this, padding grids (that are not already sized to a power of two) so that their size is the next highest power of two can speed up operations. While this works well for one-dimensional grids, it does not work well for two-dimensional grids. For a two-dimensional grid, there are certain pad sizes that work better than others. Therefore, the need exists to generalize a strategy for determining optimal pad sizes. There are three steps in the FFT algorithm. The first is to perform a one-dimensional transform on each row in the grid. The second step is to transpose the resulting matrix. The third step is to perform a one-dimensional transform on each row in the resulting grid. Steps one and three both benefit from padding the row to the next highest power of two, but the second step needs a novel approach. An algorithm was developed that struck a balance between optimizing the grid pad size with prime factors that are small (which are optimal for one-dimensional operations), and with prime factors that are large (which are optimal for two-dimensional operations). This algorithm optimizes based on average run times, and is not fine-tuned for any specific application. It increases the amount of times that processor-requested data is found in the set-associative processor cache. Cache retrievals are 4-10 times faster than conventional memory retrievals. The tested implementation of the algorithm resulted in faster execution times on all platforms tested, but with varying sized grids. This is because various computer architectures process commands differently. The test grid was 512 512. Using a 540 540 grid on a Pentium V processor, the code ran 30 percent faster. On a PowerPC, a 256x256 grid worked best. A Core2Duo computer preferred either a 1040x1040 (15 percent faster) or a 1008x1008 (30 percent faster) grid. There are many industries that can benefit from this algorithm, including optics, image-processing, signal-processing, and engineering applications.

Dean, Bruce H.↗
DOE OSTI2023

Deployment of Dynamic Neural Network Optimization to Minimize Heat Rate During Ramping for Coal Power Plants (Final Technical Report)

Much success was achieved throughout the course of this project. A successful implementation of Dynamic Neural Network Optimization (D-NNO) was coupled with Adaptive Predictive Controls (APC) and a novel hardware installation comprised of an advanced sensor network (ASN) measuring mass-weighted averages of flue gas constituents above the horizontal superheater of a coal-fired utility boiler. From 2019 through 2023 (including an extension due to COVID delays), the team was able to prototype, evaluate, deploy, iterate, and ultimately finalize an advanced closed-loop control D-NNO system which demonstrated the ability to: •improve unit efficiency ~2.0% relative to unoptimized operation (represented as total fuel fired per MWh generated) •improve unit NOx emission rates 10%+ beyond static optimization baselines •improve unit temperature stability as much as 58% and on average 12% •improve operating load stability as much as 35% The culmination of this project has generated an advanced methodology of deploying specially designed recurrent neural networks (long short-term memory, gated recurrent unit, encoder-decoder networks, transformers, etc.), customized trajectory planning and closed-loop optimization modules capable of adapting to live electric grid responses and demands, self-tuning and adaptive expert controls constantly adjusting prediction parameters to real-time unit behavior, and a hardware/software package able to reliably calculate net unit heat rate (NUHR) in real-time using flue gas constituents, machine learning, and known combustion relationships. Through this real-time NUHR value, immediate feedback on system adjustments relative to operating efficiency was available, allowing for rapid improvements to system performance. In addition to development and deployment of the advanced D-NNO system, the approach methodology has been readily commercialized through the project platform Griffin Open Systems, LLC, the D-NNO software platform host. Similar methodologies to those developed by this project have already been deployed at 5 other units across the United States, with another 6 implementations scheduled, and more expected. Over the course of the project, multiple academic papers were submitted and accepted for publication within esteemed academic journals, and PhD students were trained and graduated, as well as undergraduate students becoming involved and participating to project objectives.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Optimization of Conditions for Photoluminescence-Based Sensing of Critical Minerals: Strategies and Outlook

Economically critical minerals and metals are vital to America’s security, with application areas in energy, advanced technologies, and defense systems. The growing implementation of renewable energy sources such as electric vehicles is expected to significantly increase demand for these minerals, while the global supply is monopolistic, with most of the production occurring in a few countries outside of the US. To mitigate potential supply chain vulnerabilities, the domestic production of economically critical metals has become a bipartisan priority of the US government, and unconventional sources such as coal and its utilization byproducts such as fly ash and acid mine drainage are being actively explored as an alternative method for meeting domestic demand. Slow and expensive characterization methods for critical metals present a significant pain point for domestic production, which has led to the exploration of alternative low-cost, portable platforms capable of detecting target metals during resource prospecting and downstream process monitoring. The National Energy Technology Laboratory has developed a portable fiber optic-based luminescence spectrometer that utilizes a metal-organic framework (MOF) material to detect and distinguish parts-per-billion levels of the visible-emitting rare earth elements terbium, dysprosium, samarium, and europium, which are all economically critical metals. Although preliminary results with this system are promising, a crucial barrier to practical deployment is the ability to operate in low pH, high ionic strength environments, as acidic conditions and the presence of other metal ions can significantly reduce luminescence signal. Here, current strategies related to sample treatment, material design, and sensor configuration are discussed in the context of improving sensor performance in application-relevant conditions. Additionally, future opportunities, such as the optimization of the sensing binding environment through computational methods and specific metals to be removed for treatment will be discussed, presenting a forward-looking view for innovation in luminescent sensing of critical metals.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ETOP 503689: Pre-optimized cell free lysates for rapid prototyping of genes and pathways

This ETOP project aimed to re-conceive how we engineer complex biological systems by linking pathway design, prospecting, and validation into an integrated framework. Specifically, our vision seeks to advance and interweave high-throughput cell-based systems and rapid cell-free technologies in a way suitable for automation and microdroplet manipulation in a DOE JGI user facility setting. The key technology to be investigated toward this vision is a cell-free platform for combinatorial assembly of pathways by mixing-and-matching crude cell lysates derived from a suite of flux-enhanced background strains, each enriched with pathway enzymes. Through this work, we have established rewired E. coli and S. cerevisiae cells suitable to generated rewired lysates. We have demonstrated that lysates derived from rewired cells can generate higher fluxes of products and can enable a more robust discovery method going from gene to function annotations. Finally, we demonstrate that these rewired lysates can be stored for up to a year and still retain function. Collectively, these technologies enable a more rapid screening approach for enzyme and pathway variants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Performance Evaluation of an Offshore Wave Measurement Buoy in Monochromatic Waves

The accurate measurement of waves underpins marine energy resource characterization, device design, and project development. Datawell wave buoys are widely deployed and have long served as a trusted standard for wave measurements. We quantify the measurement performance, including wave elevation and energy flux estimation, of a Datawell DWR-MkIII buoy using prescribed monochromatic heave motions on a large-amplitude six-degree-of-freedom motion platform at the National Laboratory of the Rockies, assuming the buoy behaves as an ideal wave follower. Commanded motions were validated with an optical motion tracking system while buoy elevation and raw acceleration were recorded. Wave elevations were propagated to wave energy flux estimation using four methods, including one frequency-domain method and three time-domain methods. The Bayesian optimization was applied for design of experiments, and records from three test sites were also applied and evaluated in the present study. Results show two error regions within the nominal period range of 1.6 s to 30 s. For wave periods between 5 s and 25 s, the buoy provides accurate wave height measurements. For short periods less than 5 s, the 1.28 Hz sampling frequency induces sub-Nyquist artifacts that bias elevation and can drive maximum energy flux estimation errors above 100%. For long periods exceeding 25 s, the buoy reported elevation is underpredicted with error depending on period but relatively independent of wave height, with maximum wave height and wave energy flux errors reaching 64% and 87%, respectively. Furthermore, analysis of three field-derived cases shows that frequency-domain estimates at 1.28 Hz agree within 2% of the corresponding 100 Hz estimates, while larger method-dependent differences are observed for the Hilbert method.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro

The ability to control cellular processes using optogenetics is inducer-limited, with most optogenetic systems responding to blue light. To address this limitation, we leverage an integrated framework combining Lustro, a powerful high-throughput optogenetics platform, and machine learning tools to enable multiplexed control over blue light-sensitive optogenetic systems. Specifically, we identify light induction conditions for sequential activation as well as preferential activation and switching between pairs of light-sensitive split transcription factors in the budding yeast, Saccharomyces cerevisiae. We use the high-throughput data generated from Lustro to build a Bayesian optimization framework that incorporates data-driven learning, uncertainty quantification, and experimental design to enable the prediction of system behavior and the identification of optimal conditions for multiplexed control. This work lays the foundation for designing more advanced synthetic biological circuits incorporating optogenetics, where multiple circuit components can be controlled using designer light induction programs, with broad implications for biotechnology and bioengineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Inverse design of nanoporous crystalline reticular materials with deep generative models

Reticular frameworks are crystalline porous materials that form via the self-assembly of molecular building blocks in different topologies, with many having desirable properties for gas storage, separation, catalysis, biomedical applications and so on. The notable variety of building blocks makes reticular chemistry both promising and challenging for prospective materials design. Here we propose an automated nanoporous materials discovery platform powered by a supramolecular variational autoencoder for the generative design of reticular materials. We demonstrate the automated design process with a class of metal–organic framework (MOF) structures and the goal of separating carbon dioxide from natural gas or flue gas. Our model shows high fidelity in capturing MOF structural features. Here, we show that the autoencoder has a promising optimization capability when jointly trained with multiple top adsorbent candidates identified for superior gas separation. MOFs discovered here are strongly competitive against some of the best-performing MOFs/zeolites ever reported.

36 MATERIALS SCIENCE↗
DOE OSTI2024

GPAW: An open Python package for electronic structure calculations

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for the implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE), providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe–Salpeter Equation, variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn–Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support for graphics processing unit (GPU) acceleration has been achieved with minor modifications to the GPAW code thanks to the CuPy library. We end the review with an outlook, describing some future plans for GPAW.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Interfacial defect reduction enhances universal power law response in Mo–SiNx granular metals

Granular metals (GMs), consisting of metal nanoparticles separated by an insulating matrix, frequently serve as a platform for fundamental electron transport studies. However, few technologically mature devices incorporating GMs have been realized, in large part because intrinsic defects (e.g., electron trapping sites and metal/insulator interfacial defects) frequently impede electron transport, particularly in GMs that do not contain noble metals. Here, we demonstrate that such defects can be minimized in molybdenum–silicon nitride (Mo–SiN x ) GMs via optimization of the sputter deposition atmosphere. For Mo–SiN x GMs deposited in a mixed Ar/N 2 environment, x-ray photoemission spectroscopy shows a 40%–60% reduction of interfacial Mo-silicide defects compared to Mo–SiN x GMs sputtered in a pure Ar environment. Electron transport measurements confirm the reduced defect density; the dc conductivity improved (decreased) by 10 4 –10 5 and the activation energy for variable-range hopping increased 10×. Since GMs are disordered materials, the GM nanostructure should, theoretically, support a universal power law (UPL) response; in practice, that response is generally overwhelmed by resistive (defective) transport. Here, the defect-minimized Mo–SiN x GMs display a superlinear UPL response, which we quantify as the ratio of the conductivity at 1 MHz to that at dc, Δσ ω ⁠. Remarkably, these GMs display a Δσ ω up to 10 7 , a three-orders-of-magnitude improved response than previously reported for GMs. By enabling high-performance electric transport with a non-noble metal GM, this work represents an important step toward both new fundamental UPL research and scalable, mature GM device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

SYMBIOSYS: A Methodology for Performance Analysis of Composable HPC Data Services

Microservices are a powerful new way of building, customizing, and deploying distributed services owing to their flexibility and maintainability. Several large-scale distributed platforms have emerged to serve the growing needs of data-centric workloads and services in commercial computing. Concurrently, high-performance computing (HPC) systems and software are rapidly evolving to meet the demands of diversified applications and heterogeneity. The interplay of hardware factors, software configuration parameters, and the flexibility offered with a microservice architecture makes it nontrivial to estimate the optimal service instantiation for a given application workload. Further, this problem is exacerbated when considering that these services operate in a dynamic and heterogeneous HPC environment. An optimally integrated service can be vastly more performant than a haphazardly integrated one. Existing performance tools for HPC either fail to understand the request-response model of communication inherent to microservices or they operate within a narrow scope, limiting the insight that can be gleaned from employing them in isolation. We propose a methodology for integrated performance analysis of HPC microservices frameworks and applications called SYMBIOSYS. We describe its design and implementation within the context of the Mochi framework. This integration is achieved by combining distributed callpath profiling and tracing with a performance data exchange strategy that collects fine-grained, low-level metrics from the RPC communication library and network layers. The result is a portable, low-overhead performance analysis setup that provides a holistic profile of the dependencies among microservices and how they interact with the Mochi RPC software stack. Using HEPnOS, a production-quality Mochi data service, we demonstrate the low-overhead operation of SYMBIOSYS at scale and use it to identify the root causes of poorly performing service configurations.

microservices↗
DOE OSTI2022

Evaluating Unified Memory Performance in HIP

Heterogeneous unified memory management between a CPU and a GPU is a major challenge in GPU computing. Recently, unified memory (UM) has been supported by software and hardware components on AMD computing platforms. The support could simplify the complexities of memory management. In this paper, we attempt to have a better understanding of UM by evaluating the performance of UM programs on an AMD MI100 GPU. More specifically, we evaluate data migration using UM against other data transfer techniques for the overall performance of an application, assess the impacts of three commonly used optimization techniques on the kernel execution time of a vector add sample, and compare the performance and productivity of selected benchmarks with and without UM. The performance overhead associated with UM is not trivial, but it can improve programming productivity by reducing lines of code for scientific applications. We aim to present early results and feedback on the UM performance to the vendor.

Jin, Zheming↗
DOE OSTI2016

Rapid Carbon Fiber Prepreg Molding Technology for Automobile Structural Parts - "SEAHAWKS"

Carbon fiber reinforced plastics (CFRP) offer a variety of potential benefits to automotive parts vs. metals, mainly in the form of light-weighting, part consolidation, and corrosion resistance. However, complexities of composite manufacturing and lack of robust supply chain evolution and integration have hindered technological advancements to overcome high manufacturing costs, slow production rates and prolonged time to market. As a result, the use of CFRP in automotive structural parts has been limited to expensive “low to medium” volume platforms. The project overall investigates a concept of ecosystem-based composite manufacturing that enables rapid implementation of an integrated manufacturing system. Through partnering with individual organizations in the prepreg supply chain along with their respective technological advancements in materials, part designs, tool, equipment, recycling and repair, this project’s objective is to integrate these technologies into a manufacturing system through optimizing them individually and as a whole. Upon a successful delivery of a finished composite component to market, all associated technologies are evolved to production readiness levels not only individually but also in part of the integrated manufacturing system itself. Risks are mitigated effectively, as development costs and successes (and/or failures) are shared among all organizations. As a result, further cost reduction of the finished component is anticipated. Toray Composites (America) Inc. led the effort along with 13 other organizations to investigate and validate the concept. Phase I of this project via flat panel demonstrations focused on molding aspects of the integrated manufacturing system from several combinations of prepreg materials and molding methods used such as hydraulic press, RapidClave®, heated composite light tool (HCLT), light induction tool (LIT) and Quickstep. Other aspects such as automation equipment, recycling and component identification to further investigate and validate the concept via component demonstration in Phase II were also explored. It was found that several prepreg/process combinations could achieve a 3-6 min cure cycle time with panel thickness from 0.8 to 2.4 mm. This can be achieved under compaction pressure as low as vacuum, leading to composite panels that are void free, have good to excellent molded surfaces, Tg (by G’onset of DMA) ranging from 120-190 °C, and mechanical performance comparable to conventional autoclave cure.

36 MATERIALS SCIENCE↗