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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Quantum Computing by Coherent Cooling

Interesting problems in quantum computation take the form of finding low-energy states of (pseudo)spin systems with engineered Hamiltonians that encode the problem data. Motivated by the practical possibility of producing very low-temperature spin systems, we propose and exemplify the possibility to compute by coupling the computational spins to a quantum coherent bath that serves as a heat sink. The quantum tunneling effect provides additional cooling channels to accelerate the cooling process. Here, we demonstrate both analytically and numerically that this strategy can achieve a quantum advantage in the unstructured search problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Active Colloids as Models, Materials, and Machines

Active colloids use energy input at the particle level to propel persistent motion and direct dynamic assemblies. We consider three types of colloids animated by chemical reactions, time-varying magnetic fields, and electric currents. For each type, we review the basic propulsion mechanisms at the particle level and discuss their consequences for collective behaviors in particle ensembles. These microscopic systems provide useful experimental models of nonequilibrium many-body physics in which dissipative currents break time-reversal symmetry. Freed from the constraints of thermodynamic equilibrium, active colloids assemble to form materials that move, reconfigure, heal, and adapt. Colloidal machines based on engineered particles and their assemblies provide a basis for mobile robots with increasing levels of autonomy. This review provides a conceptual framework for understanding and applying active colloids to create material systems that mimic the functions of living matter. We highlight opportunities for chemical engineers to contribute to this growing field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Topological Control of Triply Periodic Minimal Surfaces for Thermal Design and Advanced Manufacturing: A Gyroid Case Study

Recently, there has been a heightened interest in using triply periodic minimal surfaces (TPMSs) in the design of compact process engineering components. The benefits of high surface area per unit volume, modular form, and inherent periodicity provide a holistic self-supporting network and flow-conducive features. Applications of importance include thermal power management, biomimetic scaffolds and structures, and feasibility of advanced manufacturing. This study presents a novel approach to the manipulation of the characteristic Schwarz-G, or gyroid TPMS, for thermal design in the context of advanced manufacturing. The study presents relationships between design parameters and resulting surface area as a target response using the characteristic equation of a gyroid. Through parametric control, the characteristic equation is manipulated to produce a 20-fold increase in achievable area over a baseline design characteristic of 25.4 mm through controlled combinations of design parameters. A second relationship is presented as a function of the maximum area achieved and manipulated design parameters. Through the analysis, the study presents a framework to identify and maximize the achievable area of TPMSs for advanced manufacturing and thermal management applications.

gyroid↗
DOE OSTI2020

Shaped cutting tool

A cutting tool for forming a finished part from a rotating workpiece includes a first cutting edge extending from a first end of the cutting tool, a second cutting edge extending from a second end of the cutting tool, and a shaping edge disposed between the first cutting edge and the second cutting edge. The first cutting edge is operable to remove a trailing end of the rotating workpiece and the second cutting edge is operable to remove a working portion of the rotating workpiece disposed between the trailing end and a leading end. The shaping edge is operable to shape the working portion of the rotating workpiece by advancing the cutting tool into the rotating workpiece until the first cutting edge removes the trailing end of the rotating workpiece and the second cutting edge removes the working portion of the rotating workpiece to form the finished part.

42 ENGINEERING↗
DOE OSTI2023

Cell Free and Immobilization Technologies (CFIT)

Today, several key factors negatively impact the production of fuels and chemicals from renewable sources. Common hindrances in the biological production of biochemicals are: (1) end-product or intermediate toxicity to the microbial biocatalyst, (2) the diversion of carbon to biomass formation, and (3) co-production of undesired byproducts. A particularly attractive alternative is to eliminate the biocatalyst entirely and instead operate the desired metabolic pathways in isolation, thus circumventing the roadblocks of biological toxicity, lower yields, and lack of specificity. However, cell-free enzyme systems still suffer from low productivities owing in part to the effects of free diffusion of intermediates, lack of long term enzyme stability, cofactor cost or inefficient recycling rates, and finally, the cost of enzyme production/purification. This project represents a new effort to propose innovative and cost competitive routes to producing biochemicals from a variety of feedstocks using cell free approaches. These routes will help reduce the current risk and cost associated with classical cell free production. Cell free technologies show promise for application to the production of toxic/inhibitory products or products difficult to separate from microbial growth media and can help reduce the production barriers in multiple areas of biological conversion of feedstocks to biochemicals. More specifically, we are developing new technologies and routes that could be used to produce high value biochemicals such as 2,3 BDO and terpenes (among many others) from biomass derived C5/C6 sugars or lignin but also from waste byproducts such as glycerol. This project will lead to significant innovation and also lead to new concepts and rational design of pathways and enzymes. Within this project, we will develop new metabolic enzyme cascades that will represent natural or artificial combinations of enzymes to produce the desired biochemicals from a variety of feedstocks. We are also developing basic design principals for constructing synthetic metabolons, using fusion proteins and synthetic protein scaffolds, to promote substrate channeling and stability while conserving peak activity. Additionally, our efforts include a techno economic analysis (TEA) of cell free approaches to provide the sensitivities of the process to enzyme loading, activity, pH, reactor volumes, cofactor recycling rates. Finally, we are focusing on further increasing stability, operating lifetime and efficiency of the pathway enzymes by immobilization on support surfaces. We are also focus on immobilizing pathway enzymes or combinations of enzymes on several different conducting polymers and evaluate the effect on stability and operating lifetime. As more combinations become available we will conduct a more systematic study of the means of immobilizing these enzymes. This preliminary work will enable the in-depth study of cofactor recycling at these interfaces using mediators for electron transfer. Taken together, these approaches will enable process intensification, continuous operation, lower capital and separations costs and end-product flexibility, and thus has the potential to contribute significantly to BETO's goals of cost competitive biofuels and bioproducts. To date we have demonstrated 1) the conversion of pyruvate to 2,3 BDO (4 enzymes with cofactor recycling, no additional cofactors needed) at >100g/L (>3g/L/h) using our enzyme tethering approach, 2) Generated mutants of a key redox enzyme with >180- fold improvement in NADH utilization over WT to >85% of NADPH utilization. 3) Produced mevalonate at >10g/L from glucose, limonene at >10g/L from mevalonate and more than >5g/L from glucose with crude enzyme preparations and complete cofactor recycling. 4) successfully generated fully active cross-linked aggregates (CLEAs) of NOX, a cofactor-regenerating water-forming oxidase that is key to our process with increased stability 5) Engineered and identified enzymes able to use the biomimetic cofactor NMN and synthesized new synthetic cofactors.

biocatalysis↗
DOE OSTI2020

Band Engineering of Large-Twist-Angle Graphene/h-BN Moiré Superlattices with Pressure

Graphene interfacing hexagonal boron nitride (h-BN) forms lateral moiré superlattices that host a wide range of new physical effects such as the creation of secondary Dirac points and band gap opening. A delicate control of the twist angle between the two layers is required as the effects weaken or disappear at large twist angles. In this Letter, we show that these effects can be reinstated in large-angle (~1.8°) graphene/h-BN moiré superlattices under high pressures. Additionally, a graphene/h-BN moiré superlattice microdevice is fabricated directly on the diamond culet of a diamond anvil cell, where pressure up to 8.3 GPa is applied. The band gap at the primary Dirac point is opened by 40-60 meV, and fingerprints of the second Dirac band gap are also observed in the valence band. Theoretical calculations confirm the band engineering with pressure in large-angle graphene/h-BN bilayers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Multifunctional Fibroblasts Enhanced via Thermal and Freeze-Drying Post-treatments of Aligned Electrospun Nanofiber Membranes

Parallel fibrous scaffolds play a critical role in controlling the morphology of cells to be more natural and biologically inspired. Among popular tissue engineering materials, poly(2-hydroxyethyl methacrylate) (pHEMA) has been widely investigated in conventional forms due to its biocompatibility, low toxicity, and hydrophilicity. However, the swelling of pHEMA in water remains a major concern. To address this issue, randomly oriented and aligned as-spun pHEMA nanofibrous scaffolds were first fabricated at speeds of 300 and 2000 rpm in this study, which were then post-treated using either a thermal or a freeze-drying method. In cell assays, human dermal fibroblasts (HDFs) adhered to the freeze-drying treated substrates at a significantly faster rate, whereas they had a higher cell growth rate on thermally-treated substrates. Results indicated that the structural properties of pHEMA nanofibrous scaffolds and subsequent cellular behaviors were largely dependent on post-treatment methods. Moreover, this study suggests that aligned pHEMA nanofibrous substrates tended to induce regular fibroblast orientation and unidirectionally oriented actin cytoskeletons over random pHEMA nanofibrous substrates. Such information has predictive power and provides insights into promising post-treatment methods for improving the properties of aligned pHEMA scaffolds for numerous tissue engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Sparse Matrix-Based HPC Tomography

Tomographic imaging has benefited from advances in X-ray sources, detectors and optics to enable novel observations in science, engineering and medicine. These advances have come with a dramatic increase of input data in the form of faster frame rates, larger fields of view or higher resolution, so high performance solutions are currently widely used for analysis. Tomographic instruments can vary significantly from one to another, including the hardware employed for reconstruction: from single CPU workstations to large scale hybrid CPU/GPU supercomputers. Furthermore, flexibility on the software interfaces and reconstruction engines are also highly valued to allow for easy development and prototyping. This paper presents a novel software framework for tomographic analysis that tackles all aforementioned requirements. The proposed solution capitalizes on the increased performance of sparse matrix-vector multiplication and exploits multi-CPU and GPU reconstruction over MPI. Furthermore, the solution is implemented in Python and relies on CuPy for fast GPU operators and CUDA kernel integration, and on SciPy for CPU sparse matrix computation. As opposed to previous tomography solutions that are tailor-made for specific use cases or hardware, the proposed software is designed to provide flexible, portable and high-performance operators that can be used for continuous integration at different production environments, but also for prototyping new experimental settings or for algorithmic development. The experimental results demonstrate how our implementation can even outperform state-of-the-art software packages used at advanced X-ray sources worldwide.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Optimization of thermal barrier coating performance and durability over a drive cycle

A methodology to thermo-mechanically optimize a piston thermal barrier coating over a full drive cycle was established. The optimization objective was to minimize the heat transfer to the engine wall while maintaining structural integrity of the coating. Over 800 candidate materials were investigated and the optimization required more than one million non-road transient drive cycle calculations; real materials were investigated to ensure a realizable result and the existence of thermal and mechanical properties. High computational efficiency was achieved using a recently developed analytical heat transfer technique for multilayer engine walls. An uncoupled approach was utilized for the optimization, wherein the gas temperature and heat transfer coefficient profiles from a fully coupled and calibrated baseline model over the 20-min drive cycle were employed. The coating/piston interface temperature was constrained to be below the maximum piston service temperature limit. The durability was assessed using a recently developed analytical coating delamination framework for engine in-cylinder coatings based on the energy release rate when a crack forms. Results are presented for a mechanically unconstrained optimization and for cases constrained to three fixed levels of drive-cycle maximum energy release rate, and also constrained by the individual material’s toughness. The best-performing coating materials identified were verified using the fully coupled system-level model, which compared well to the uncoupled predictions. A study on the effect of adding a sealing layer to some high-performing, but porous, coatings showed a reduction in fuel consumption benefit and an increased exhaust temperature over the cycle, but the system still outperformed the uncoated case. The results of the study elucidate the importance of including engine performance and mechanical failure considerations in thermal barrier coating design.

Engineering↗
DOE OSTI2022

Black hole–neutron star mergers: The first mass gap and kilonovae

Observations of X-ray binaries indicate a dearth of compact objects in the mass range from ~2 –5 M ⊙ . The existence of this (first mass) gap has been used to discriminate between proposed engines behind core-collapse supernovae. From LIGO/Virgo observations of binary compact remnant masses, several candidate first mass gap objects, either neutron stars (NSs) or black holes (BHs), were identified during the O3 science run. Motivated by these new observations, we study the formation of BH-NS mergers in the framework of isolated classical binary evolution, using population synthesis methods to evolve large populations of binary stars (Population I and II) across cosmic time. We present results on the NS to BH mass ratios (q = M NS /M BH ) in merging systems, showing that although systems with a mass ratio as low as q = 0.02 can exist, typically BH-NS systems form with moderate mass ratios q = 0.1 –0.2. If we adopt a delayed supernova engine, we conclude that ~30% of BH-NS mergers may host at least one compact object in the first mass gap (FMG). Even allowing for uncertainties in the processes behind compact object formation, we expect the fraction of BH-NS systems ejecting mass during the merger to be small (from ~0.6 –9%). In our reference model, we assume: (i) the formation of compact objects within the FMG, (ii) natal NS/BH kicks decreased by fallback, (iii) low BH spins due to Tayler-Spruit angular momentum transport in massive stars. We find that ≲1% of BH-NS mergers will have any mass ejection and about the same percentage will produce kilonova bright enough to have a chance of being detected with a large (Subaru-class) 8 m telescope. Interestingly, all these mergers will have both a BH and an NS in the FMG.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

In situ multimodal imaging for nanoscale visualization of tribofilm formation

A third of the energy from fuel combustion in passenger car gasoline engines is lost due to friction. Carefully designed engine lubricants can recover some of these losses by reducing friction and wear by forming a nanometer-scale chemico-physico tribofilm between surfaces. Accordingly, attention has focused on developing oil formulations that form low-friction tribofilms. However, analyses of resultant tribofilms are typically conducted after tribo-tests with conventional characterization tools and do not offer insights into tribofilm formation and evolution, precluding information critical to tuning tribofilm properties. In this work, we developed a unique multimodal methodology based on Atomic Force Microscopy (AFM) with local probe heating for in situ tribological studies that activates friction modifiers and simultaneously captures the evolution of friction and surface roughness, with nanometer resolution. As a platform to demonstrate the ability of this methodology to visualize dynamics of tribofilm formation in situ, we apply it to molybdenum-based friction modifiers to distinguish key factors in their functionality and correlate nanoscale AFM and Friction Force Microscopy data to bench tribo-tests used in the industry. To decode the formation mechanisms observed in situ and underlying chemistry of tribofilms, we performed ab initio Molecular Dynamics (AIMD) simulations at comparable conditions. AIMD simulations confirmed both nanoscale and bench tribo-test results and showed deviations in molecular organization in tribofilms that are formed from different molybdenum-based friction modifiers that corroborates with surface functionality. With this innovative methodology, we demonstrate proof-of-principle in situ formation of molybdenum-based tribofilms directly on steel surfaces that could be applied generally to studying tribofilm formation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

System Engineers and Decisions: It?s All about Knowledge

In order to guarantee that a system meets adequate levels of reliability and availability, system performances are continuously monitored and analyzed thanks to the technological advancements driving the Industry 4.0 revolution. An Industry 4.0 approach is typically based on advanced statistical, big data mining, machine learning, and internet-of-things methods designed to detect anomalies in the behavior of system, detect the most likely failure modes, and provide indications to system engineers on when maintenance activities should be performed before system performance are deemed unacceptable (which can be generated by diagnostic and prognostic methods). However, these analyses, which are designed to automatize and increase the efficacy of the system maintenance program, require large amount of data which can come in various forms: numeric, textual, images, sounds etc. Such data constitutes the historic knowledge benchmark to track system performances and support system engineer decisions. Here we claim that data is not sufficient to support this kind of analyses when applied to systems characterized by complex architectures and behaviors. Robust system engineer decisions require the ability to understand the system operational context that lies behind the observed data elements. In this respect, system models are in fact necessary to “put data in context” and capture relationships between data elements. Industry 4.0 methods require in fact contextual knowledge as a basis upon which hypotheses can be generated and assumptions tested. In our view, for complex systems, model-based system engineering (MBSE) models can afford this contextual knowledge, as they are typically used to describe systems architecture and dynamic behaviors. System knowledge is here intended as the blending of collected data and system architecture which takes the form of a “knowledge graph”. A knowledge graph is a database which consists of a large set of nodes (in our case an entity can be either a data or an MBSE element) which are linked to each other. The types of nodes and links follow a pre-defined topology, sometimes also refers as an ontology, that is designed to fit the actual decisions that needs to be performed. We show here how a knowledge graph can be defined to support system engineer maintenance decisions and how the same graph can be built based on system MBSE models and pre-processed data from numeric (through anomaly detections and diagnostic methods) and textual elements (through technical language processing TLP).

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Artificial Intelligence for Power Electronics in Electric Vehicles: Challenges and Opportunities

We report progress in the field of power electronics within electric vehicles has generally been driven by conventional engineering design principles and experiential learning. Power electronics is inherently a multidomain field where semiconductor physics and electrical, thermal, and mechanical design knowledge converge to achieve a practical realization of desired targets in the form of conversion efficiency, power density, and reliability. Due to the promising nature of artificial intelligence in delivering rapid results, engineers are starting to explore the ways in which it can contribute to making power electronics more compact and reliable. Here, we conduct a brief review of the foray of artificial intelligence in three distinct subtechnologies within a power electronics system in the context of electric vehicles: semiconductor devices, power electronics module design and prognostics, and thermal management design. The intent is not to report an exhaustive literature review, but to identify the state of the art and opportunities for artificial intelligence to play a meaningful role in power electronics design from a mechanical and thermal standpoint, as well as to discuss a few promising future research directions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

TNet: A Model-Constrained Tikhonov Network Approach for Inverse Problems

Deep learning (DL), in particular deep neural networks, by default is purely data-driven and in general does not require physics. This is the strength of DL but also one of its key limitations when applied to science and engineering problems in which underlying physical properties—such as stability, conservation, and positivity—and accuracy are required. DL methods in their original forms are often not capable of respecting the underlying mathematical models or achieving desired accuracy even in big-data regimes. On the other hand, many data-driven science and engineering problems, such as inverse problems, typically have limited experimental or observational data, and DL would overfit the data in this case. Leveraging information encoded in the underlying mathematical models, we argue, not only compensates for missing information in low data regimes but also provides opportunities to equip DL methods with the underlying physics, hence promoting better generalization. This paper develops a model-constrained DL approach and its variant TNet—a Tikhonov neural network—which are capable of learning not only information hidden in the training data but also in the underlying mathematical models to solve inverse problems governed by partial differential equations in low data regimes. We provide the constructions and some theoretical results for the proposed approaches for both linear and nonlinear inverse problems. Since TNet is designed to learn inverse solutions with Tikhonov regularization, it is interpretable: in fact it recovers Tikhonov solutions for linear cases while potentially approximating Tikhonov solutions for nonlinear inverse problems. We also prove that data randomization can enhance not only the smoothness of the networks but also their generalizations. Comprehensive numerical results confirm the theoretical findings and show that with even as little as 1 training data sample for one-dimensional (1D) deconvolution, 5 for an inverse 2D heat conductivity problem, 100 for inverse initial conditions for a time-dependent 2D Burgers’s equation, and 50 for inverse initial conditions for 2D Navier–Stokes equations, TNet solutions can be as accurate as Tikhonov solutions while being several orders of magnitude faster. Furthermore, this is possible owing to the model-constrained term, replications, and randomization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Biological funneling of phenolics from transgenic plants engineered to express the bacterial 3-dehydroshikimate dehydratase (qsuB) gene

The economic and environmental sustainability of lignocellulosic biomass biorefineries is predicated on generating biofuels and bioproducts from cell-wall polysaccharide and lignin polymers. Historical efforts in plant genetic engineering have focused on the development of strategies that facilitate biomass deconstruction, with more recently efforts including the synthesis of high-value chemicals in planta . One such genetic modification is the expression of the bacterial quinate and shikimate utilization B ( qsuB ) gene that increases the accumulation of protocatechuic acid in lignocellulosic biomass. Herein, we evaluated the effectiveness of an alkaline pretreatment process to extract phenolics directly from wild-type and QsuB-transgenic lines of Arabidopsis, poplar, and sorghum, and then upgrade them to the polyester precursor 2-pyrone-4,6-dicarboxylic acid (PDC) with an engineered strain of Novosphingobium aromaticivorans . Protocatechuic acid extracted from all QsuB transgenic lines was found to be mostly in the glycosylated form. Glycosylated protocatechuic acid and other plant-derived phenolics were effectively metabolized by N. aromaticivorans, and PDC production was greatest using extracts from an Arabidopsis QsuB transgenic line (∼5% w/w), followed by QsuB sorghum (∼1.1% w/w), and QsuB poplar (∼0.4% w/w) lines. The comparison of PDC production from wild-type and QsuB transgenic lines of Arabidopsis, poplar, and sorghum demonstrates the utility of a mild alkaline pretreatment to liberate phenolics from plant biomass that are either naturally present or that accumulate as a consequence of genetic engineering strategies. All QsuB transgenic lines outperformed their wild-type counterparts with respect to observed PDC yields. In addition, microbial funneling to PDC was effective even when most of the protocatechuic acid extracted was in glycosylated form, clearly demonstrating that this bacterium can metabolize these aromatic conjugates. These findings illustrate the benefits of combining plant and microbial engineering for bioproduct formation from phenolics in lignocellulosic biorefineries.

Umana, German E.↗
DOE OSTI2024

Grid Forming Inverter With Increased Short-Circuit Contribution to Address Inverter-Based Microgrid Protection Challenges

Substantial differences in fault levels between grid-tied and islanded modes is one of the primary challenges of microgrid protection. During grid-tied mode, the bulk grid provides significant short-circuit, while during islanded operation the short-circuit magnitude is small due to inverter-based resources limiting their current output close to nominal ratings. Consequently, conventional distribution protection strategies based on overcurrent cannot reliably protect microgrids when operating in islanded mode. Fuses and circuit breakers are particularly affected because of their inverse characteristics. Presently, the absence of affordable solutions for protecting microgrids in islanded mode leads to microgrids shutting down during electrical faults. The contribution of this article is two-fold. The first innovation proposes specific hardware modifications to grid-forming inverters to increase their short-circuit current during electrical faults. The second innovation introduces a novel control strategy designed to preserve control stability margins even when the grid-filter saturates, ensuring sinusoidal output currents under normal and fault conditions. Through experimental results, the inverter with the proposed modifications can provide more than three-times its nominal current during electrical faults. For the prototype testbed, this was sufficient to enable the use of traditional legacy overcurrent protection, achieving the fuse-to-relay and relay-to-relay minimum coordination time for the line-to-ground, line-to-line to ground, and three-phase electrical faults.

42 ENGINEERING↗
DOE OSTI2026

Uranium Doped Gallium Nitride Epitaxial Thin Films

Gallium nitride (GaN) is near ubiquitous in modern day technologies, forming the backbone of solid-state lighting and high-power electronics. Engineering the physical properties of GaN has been investigated to some degree by the incorporation or doping of most of the elements of the periodic table, but the actinides remain unexplored. Molecular beam epitaxy is used to demonstrate uranium doping of GaN single crystals. High structural quality of the host matrix is maintained despite partial elemental segregation of the uranium dopant into 1D structures at the levels presented here. Electronic transport measurements reveal relatively high conductivity, which persists down to cryogenic temperature and is characterized by the formation of narrow gaps in the electronic band structures very close to the Fermi level. Photoluminescence measurements reveal that the U-doped GaN exhibits optical behavior similar to that of the GaN substrate. The addition of actinide materials to a non-centrosymmetric, optically active, radiation-hard, and electronically tunable host matrix opens a world of possibilities for investigating and leveraging elements with high electron correlations in the pursuit of novel devices.

36 - MATERIALS SCIENCE↗
DOE OSTI2020

PAH formation from jet stirred reactor pyrolysis of gasoline surrogates

Soot particles and their precursor polycyclic aromatic hydrocarbon (PAH) species, formed during combustion, are responsible for particulate emissions in gasoline direct injection (GDI) engines. To better understand the effects of fuel composition on formation of soot in GDI engines, the pyrolysis of several gasoline surrogates was studied in a jet-stirred reactor across a broad temperature range at atmospheric pressure and 1 s residence time. Fuel and intermediate species, including aromatics up to naphthalene, were measured using gas chromatography (GC). PAH concentrations from pyrolysis of surrogate fuels were compared to gain insight into the effects of fuel composition on PAH formation. In addition, synergistic effects were observed in pyrolysis experiments of binary blends. A detailed kinetic model, recently developed at Lawrence Livermore National Laboratory (LLNL), successfully captured the effects of blending and the concentration of major PAHs. Major reaction pathways are discussed, as well as the role of important intermediate species, such as acetylene, and resonantly stabilized radicals such as allyl, propargyl, cyclopentadienyl, and benzyl in the formation of PAH.

36 MATERIALS SCIENCE↗