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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Noise Benefits of Increased Fan Bypass Nozzle Area

An advanced model turbofan (typical of current engine technology) was tested in the NASA Glenn 9 by 15 Foot Low Speed Wind Tunnel (9-by 15-Foot LSWT) to explore far field acoustic effects of increased bypass nozzle area. This fan stage test was part of the NASA Glenn Fan Broadband Source Diagnostic Test, second entry (SDT2) which acquired aeroacoustic results over a range of test conditions. The baseline nozzle was sized to produce maximum stage performance for the engine at a high altitude, cruise point condition. However, the wind tunnel testing is conducted near sea level conditions. Therefore, in order to simulate and obtain performance at other aircraft operating conditions, two additional nozzles were designed and tested-one with a +5 percent increase in weight flow (+5.4 percent increase in nozzle area compared with the baseline nozzle), sized to simulate the performance at the stage design point conditions, and the other with a +7.5 percent increase in weight flow (+10.9 percent increase in nozzle area), sized for maximum weight flow with a fixed nozzle at sea level conditions. Measured acoustic benefits with increased nozzle area were very encouraging, showing overall sound power level (OAPWL) reductions of 2 or more dB while the stage thrust actually increased by several percentage points except fro the most open nozzle at takeoff rotor speed where stage performance decreased. These noise reduction benefits were seen to primarily affect broadband noise, and were evident throughout the range of measured sideline angles.

Woodward, Richard P.↗
DOE OSTI2023

Growth and passivation of individual carbon nanoparticles by C2H2 addition at high temperatures: Dependence of growth rate and evolution on material and size

Absolute kinetics for reactions of C2H2 with a series of ∼60 individual carbon nanoparticles (NPs) from graphite, graphene, graphene oxide, carbon black, diamond, and nano-onion feedstocks were measured for temperatures (TNP) ranging from 1200 to 1700 K. All the NPs were observed to gain mass by carbon addition under conditions that varied with feedstock but with large variations in initial growth rate. Long reaction periods were studied to allow the evolution of growth rates over time to be observed. Diamond NPs were found to passivate against C2H2 addition if heated above ∼1400 K, and the highly variable initial reactivity for carbon nano-onions was found to depend on the presence of non-onion-structure surface carbon. For graphitic and carbon black NPs, three distinct growth modes were observed, correlated with the initial NP mass (Minitial). Smallest graphitic and carbon black NPs, with masses <∼25 MDa, initially grew rapidly but also passivated quickly after adding <4% of Minitial. NPs in the 20–50 MDa range also passivated but only after multiple waves of fast growth separated by periods of low reactivity, with up to ∼11% total mass gain before passivation. The largest carbon black and graphitic NPs, with Minitial >50 MDa, grew rapidly and continuously, adding up to ∼300% of Minitial with no sign of rate slowing as long as C2H2 was present. The efficiencies for C2H2 addition and etching by O2 are strongly correlated, but the correlation changes as the NPs passivate. Growth and passivation mechanisms are discussed.

Chemistry↗
DOE OSTI2026

Supervised Learning-Based Spatial Position Estimation with Vertical Displacement for Hovering UAV Wireless Power Transfer

This study presents a supervised learning-based spatial position estimation approach for wireless power transfer (WPT) systems supporting hovering unmanned aerial vehicle (UAV) charging. Unlike stationary charging scenarios, hovering UAVs introduce continuous lateral misalignment and vertical displacement, leading to variations in magnetic coupling and reduced power transfer efficiency. To address this challenge, the proposed method estimates the relative spatial position of the receiver coil using only electrical measurements obtained at the secondary side. A supervised learning model is trained to map output voltage and current features to spatial coordinates, enabling position awareness without requiring external sensors, vision systems, or communication links. The sensing functionality is inherently integrated into the WPT system, allowing simultaneous power transfer and localization through the same magnetic interface. Experimental validation is conducted on a laboratory-scale prototype under varying lateral offsets and air-gap conditions. In addition, spline-based interpolation is employed to increase spatial data density for training. The results demonstrate that the proposed framework can capture spatial variations associated with both lateral and vertical displacement, providing reliable position estimation under hovering conditions. This work establishes a hardware-efficient, sensorless solution for UAV wireless charging and serves as a baseline for advanced data-driven position estimation methods in dynamic WPT systems.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
NASA NTRS2004

Convective Instability in Ice I: Application to Callisto and Ganymede

Laboratory experiments measuring ice rheology suggest that it deforms under the influence of several nonNewtonian creep mechanisms, where the viscosity depends on both strain rate and temperature [Goldsby & Kohlstedt, 2001]. Whether or not a fluid with a purely temperature-dependent viscosity convects can be determined by comparing the Rayleigh number of the system to the critical Rayleigh number (Racr), which depends on rheological, thermal, and physical parameters of the fluid layer. However, in a nonNewtonian fluid where viscosity depends on the strain rate (i.e. velocity), convection can only occur if a temperature or velocity perturbation is issued to the system to lower the viscosity and permit fluid motions. Therefore, whether convection occurs in an ice I layer depends on initial conditions, in addition to rheological, thermal, and physical properties of the layer. We show new results for a scaling between the critical Rayleigh number and perturbation amplitude for grain boundary sliding rheology. This scaling can be used to determine the conditions required to initiate convection in the ice I shell of a generic icy satellite. We use this scaling to judge the convective instability of Ganymede and Callisto's ice shells in the absence of tidal dissipation.

Barr, A. C.↗
DOE OSTI2021

SURFACE FINISHING AND ELECTROLESS NICKEL PLATING OF ADDITIVELY MANUFACTURED (AM) METAL COMPONENTS

This study investigates the application of electroless nickel deposition on additively manufactured stainless steel samples. Current additive manufacturing (AM) technologies produce metal components with a rough surface. Rough surfaces generally exhibit fatigue characteristics, increasing the probability of initiating a crack or fracture to the printed part. For this reason, the direct use of as-produced parts in a finished product cannot be actualized, which presents a challenge. Post-processing of the AM parts is therefore required to smoothen the surface. This study analyzes chempolish (CP) and electropolish (EP) surface finishing techniques for post-processing AM stainless steel components CP has a great advantage in creating uniform, smooth surfaces regardless of size or part geometry EP creates an extremely smooth surface, which reduces the surface roughness to the sub-micrometer level. In this study, we also investigate nickel deposition on EP, CP, and as-built AM components using electroless nickel solutions. Electroless nickel plating is a method of alloy treatment designed to increase manufactured component's hardness and surface resistance to the unrelenting environment. The electroless nickel plating process is more straightforward than its counterpart electroplating.. We use low-phosphorus (2-5% P), medium-phosphorus (6-9% P), and high-phosphorus (10-13% P). These Ni deposition experiments were optimized using the L9 Taguchi design of experiments (TDOE), which compromises the prosperous content in the solution, surface finish, plane of the geometry, and bath temperature. The pre-and post-processed surface of the AM parts was characterized by KEYENCE Digital MicroscopeVHX-7000 and Phenom XL Desktop SEM. The experimental results show that electroless nickel deposition produces uniform Ni coating on the additively manufactured components up to 20 μm per hour. Mechanical properties of as-built and Ni coated AM samples were analyzed by applying a standard 10 N scratch test. Nickel coated AM samples were up to two times scratch resistant compared to the as-built samples. This study suggests electroless nickel plating is a robust viable option for surface hardening and finishing AM components for various applications and operating conditions.

Keywords: additive manufacturing, fatigue, chempol↗
NASA NTRS1977

Wide range operation of advanced low NOx combustors for supersonic high-altitude aircraft gas turbines

An initial rig program tested the Jet Induced Circulation (JIC) and Vortex Air Blast (VAB) systems in small can combustor configurations for NOx emissions at a simulated high altitude, supersonic cruise condition. The VAB combustor demonstrated the capability of meeting the NOx goal of 1.0 g NO2/kg fuel at the cruise condition. In addition, the program served to demonstrate the limited low-emissions range available from the lean, premixed combustor. A follow-on effort was concerned with the problem of operating these lean, premixed combustors with acceptable emissions at simulated engine idle conditions. Various techniques have been demonstrated that allow satisfactory operation on both the JIC and VAB combustors at idle with CO emissions below 20 g/kg fuel. The VAB combustor was limited by flashback/autoignition phenomena at the cruise conditions to a pressure of 8 atmospheres. The JIC combustor was operated up to the full design cruise pressure of 14 atmospheres without encountering an autoignition limitation although the NOx levels, in the 2-3 g NO2/kg fuel range, exceeded the program goal.

Roberts, P. B.↗
NASA NTRS2014

Effect of Fuel Injection and Mixing Characteristics on Pulse-Combustor Performance at High-Pressure

Recent calculations of pulse-combustors operating at high-pressure conditions produced pressure gains significantly lower than those observed experimentally and computationally at atmospheric conditions. The factors limiting the pressure-gain at high-pressure conditions are identified, and the effects of fuel injection and air mixing characteristics on performance are investigated. New pulse-combustor configurations were developed, and the results show that by suitable changes to the combustor geometry, fuel injection scheme and valve dynamics the performance of the pulse-combustor operating at high-pressure conditions can be increased to levels comparable to those observed at atmospheric conditions. In addition, the new configurations can significantly reduce the levels of NOx emissions. One particular configuration resulted in extremely low levels of NO, producing an emission index much less than one, although at a lower pressure-gain. Calculations at representative cruise conditions demonstrated that pulse-combustors can achieve a high level of performance at such conditions.

Propulsion↗
NASA NTRSDate not supplied

Quantifying Medical Risk on a Long Duration Lunar Mission: A Demonstration of NASA’s IMPACT Tradespace Analysis Tool

Background NASA’s human exploration spaceflight missions to the Moon and Mars present unprecedented challenges for in-mission medical care. The distance from Earth will mean increased mission durations, communication delays, limited to no resupply opportunities, and constraints on the medical evacuation of astronauts. Mass, volume, power, and data will be limited while higher demands will be placed on the crew to manage medical care. NASA’s Moon to Mars exploration strategy lays out increasingly complex Artemis missions both in terms of duration and operations. In these more challenging deep space missions, it is important to quantitatively estimate the human medical risk to inform a traditional heuristic approach to medical risk. Prior tools have been developed for missions in low Earth orbit, but a new tool is required to plan for future exploration missions. Methods IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a risk assessment tool developed by NASA to advance exploration mission medical system design by quantitatively estimating mission medical risk. IMPACT v1.0 includes a novel evidence library baselined to exploration environments; an expanded list of 119 medical conditions; the addition of medical resources; and the ability for rapid and iterative analysis. Medical system risk estimates include loss of crew life, consideration of the need for return to definitive care (medical evacuation), and an estimate of crew time affected due to medical conditions. A notional long duration lunar orbit and lunar surface design reference mission (DRM) was chosen with a 4-astronaut crew to represent a sustained exploration Artemis mission. Results/Discussion Overall, IMPACT successfully quantified medical risk and derived an optimized medical system to support crew on a long duration lunar mission. In this DRM, the calculated loss of crew life from a medical event was 0.008 events per mission, risk of potential need for evacuation was 0.30 events per mission, and cumulative crew time affected by medical conditions was 103 days. The medical conditions that most contributed to overall medical risk were decompression sickness, trauma conditions, and respiratory failure. The conditions that had the largest effects on crew performance included musculoskeletal injuries and lunar dust exposure. The IMPACT-generated medical system included resources that target the most common and highest risk conditions. This systematic analysis demonstrates the value of the IMPACT tool in medical system design for human exploration spaceflight missions.

Missions to Mars↗
NASA NTRS2024

Quantifying Medical Risk on a Long Duration Lunar Mission: A Demonstration of NASA’s IMPACT Tradespace Analysis Tool

Background NASA’s human exploration spaceflight missions to the Moon and Mars present unprecedented challenges for in-mission medical care. The distance from Earth will mean increased mission durations, communication delays, limited to no resupply opportunities, and constraints on the medical evacuation of astronauts. Mass, volume, power, and data will be limited while higher demands will be placed on the crew to manage medical care. NASA’s Moon to Mars exploration strategy lays out increasingly complex Artemis missions both in terms of duration and operations. In these more challenging deep space missions, it is important to quantitatively estimate the human medical risk to inform a traditional heuristic approach to medical risk. Prior tools have been developed for missions in low Earth orbit, but a new tool is required to plan for future exploration missions. Methods IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a risk assessment tool developed by NASA to advance exploration mission medical system design by quantitatively estimating mission medical risk. IMPACT v1.0 includes a novel evidence library baselined to exploration environments; an expanded list of 119 medical conditions; the addition of medical resources; and the ability for rapid and iterative analysis. Medical system risk estimates include loss of crew life, consideration of the need for return to definitive care (medical evacuation), and an estimate of crew time affected due to medical conditions. A notional long duration lunar orbit and lunar surface design reference mission (DRM) was chosen with a 4-astronaut crew to represent a sustained exploration Artemis mission. Results/Discussion Overall, IMPACT successfully quantified medical risk and derived an optimized medical system to support crew on a long duration lunar mission. In this DRM, the calculated loss of crew life from a medical event was 0.008 events per mission, risk of potential need for evacuation was 0.30 events per mission, and cumulative crew time affected by medical conditions was 103 days. The medical conditions that most contributed to overall medical risk were decompression sickness, trauma conditions, and respiratory failure. The conditions that had the largest effects on crew performance included musculoskeletal injuries and lunar dust exposure. The IMPACT-generated medical system included resources that target the most common and highest risk conditions. This systematic analysis demonstrates the value of the IMPACT tool in medical system design for human exploration spaceflight missions.

Missions to Mars↗
DOE OSTI2024

Spray process of multi-component gasoline surrogate fuel under ECN Spray G conditions

As modern gasoline direct injection (GDI) engines utilize sophisticated injection strategies, a detailed understanding of the air-fuel mixing process is crucial to further improvements in engine emission and fuel economy. In this study, a comprehensive evaluation of the spray process of single-component iso-octane (IC8) and multi-component gasoline surrogate E00 (36 % n-pentane, 46 % iso-octane, and 18 % n-undecane, by volume) fuels was conducted using an Engine Combustion Network (ECN) Spray G injector. High-speed extinction, schlieren, and microscopy imaging campaigns were carried out under engine-like ambient conditions in a spray vessel. Experimental results including liquid/vapor penetration, local liquid volume fraction, droplet size, and projected liquid film on the nozzle tip were compared under ECN G1 (573 K, 3.5 kg/m 3 ), G2 (333 K, 0.5 kg/m 3 ), and G3 (333 K, 1.01 kg/m 3 ) conditions. In addition to the experiments, preferential evaporation process of the E00 fuel was elucidated by Large–Eddy Simulations (LES). The three-dimensional liquid volume fraction measurement enabled by the computed tomographic reconstruction showed substantial plume collapse for E00 under the G2 and G3 conditions having wider plume growth and plume-to-plume interaction due to the fuel high vapor pressure. Here, the CFD simulation of E00 showed an inhomogeneity in the way fuel components vaporized, with more volatile components carried downstream in the spray after the end of injection. The high vapor pressure of E00 also results in ~4 μm smaller average droplet diameter than IC8, reflecting a higher rate of initial vaporization even though the final boiling point temperature is higher. Consistent with high vapor pressure, E00 had a wider plume cone angle and enhanced interaction with the wall to cover the entire surface of the nozzle tip in a film. However, the liquid fuel underwent faster evaporation, so the final projected tip wetting area was smaller than the IC8 under the flash-boiling condition.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1977

Development of a special purpose spacecraft interior coating. Phase 2

Numerous acrylic and epoxy modifiers for the fluorocarbon latex resin base were investigated. Optimum coatings were developed by modifying the fluorocarbon latex with an epoxy acrylic resin system. In addition, a number of other formulations, containing hard acrylics as modifiers, displayed attractive properties and potential for further improvements. The preferred formulations dried to touch in about one hour and were fully dried in about twenty four hours under normal room temperature and humidity conditions. In addition to physical and mechanical properties either comparable or superior to those of commercial solvent base polyurethane or polyester coatings, the preferred compositions meet the flammability and offgassing requirements specified by NASA.

Bartoszek, E. J.↗
NASA NTRSDate not supplied

Understanding Relationships Between Satellite, Model, and Ground-Based Surface Temperature Characterizations From Overcast to Clear Conditions in Support of Satellite Remote Sensing of Clouds and Radiation

Accurate and consistent global estimates of cloud coverage and their properties are fundamental to long-term Earth radiation budget (ERB) monitoring efforts like the Clouds and the Earth’s Radiant Energy System (CERES) project. Cloud detection algorithms often apply thresholding approaches to identify where clouds occur by comparing satellite-measured radiances with those that are expected under cloud-free conditions. In addition, once a cloud is detected, the derivation of cloud optical and microphysical properties also requires knowledge of the background radiances below the cloud. In the infrared, knowledge of the surface emissivity and the expected skin temperature under both cloudy and cloud-free conditions is needed. These traits are generally well known over the oceans. Over land, however, comparisons between satellite-derived land surface temperature (LST) with that characterized in numerical weather analyses reveal large differences in many parts of the world, often exceeding 5 K, which can lead to significant satellite cloud detection and cloud property retrieval errors. Furthermore, clouds have a dramatic influence on the LST, and therefore characterization of that model parameter also depends on the capability of the model to accurately resolve clouds. Thus, the LST characterized in models is, at times, a poor approximation for what would otherwise be observed, thereby impeding accurate satellite cloud retrievals. As a result, we seek to develop a more robust method for estimating the LST required for satellite cloud characterizations. This effort is accomplished through a combination of surface emission/air temperature relationship studies in all-sky conditions using ground measurement stations, along with deep neural network (DNN) estimates of expected LST under overcast and cloud-free conditions. We demonstrate that substituting DNN-predicted LST for that generated by numerical models can mitigate model-inherent diurnal dependencies and reduce overall bias and uncertainty relative to satellite/ground observations by 0.5–4 K and 0.5–2 K, respectively. It is expected that this work will lead to improved satellite cloud retrievals that enhance ERB monitoring efforts.

B Scarino↗
DOE OSTI2022

Interlayer fusion bonding of semi-crystalline polymer composites in extrusion deposition additive manufacturing

This work focuses on the evolution of interlayer fracture toughness properties of fiber-reinforced, semi-crystalline polymers in the extrusion deposition additive manufacturing (EDAM) process. Further, this work bridges the gap between the additive process conditions (time-temperature history) and the effective layer-to-layer fracture properties developed within a printed component. This is the first step to predict delamination that can occur during printing, during cooling to room temperature after printing, and during service performance of an additively manufactured geometry. A phenomenological model is developed for fusion bonding of semi-crystalline polymer matrix composites by coupling the interdiffusion of polymer chains with the evolution of polymer crystallinity. While the interdiffusion is captured by reptation theory of polymer dynamics, the evolution of crystallinity is modeled by phenomenological crystallization kinetics and crystal melting dynamics. Further, a methodology is developed to determine the critical strain energy release rate, G IC of the interlayer interface and experiments are conducted utilizing the double cantilever beam fracture test geometry. In conclusion, predictions of GIC as a function of thermal history are compared with experiments.

36 MATERIALS SCIENCE↗
NASA NTRS2005

Additional Results of Ice-Accretion Scaling at SLD Conditions

To determine scale velocity an additional similarity parameter is needed to supplement the Ruff scaling method. A Weber number based on water droplet MVD has been included in several studies because the effect of droplet splashing on ice accretion was believed to be important, particularly for SLD conditions. In the present study, ice shapes recorded at Appendix-C conditions and recent results at SLD conditions are reviewed to show that droplet diameter cannot be important to main ice shape, and for low airspeeds splashing does not appear to affect SLD ice shapes. Evidence is presented to show that while a supplementary similarity parameter probably has the form of a Weber number, it must be based on a length proportional to model size rather than MVD. Scaling comparisons were made between SLD reference conditions and Appendix-C scale conditions using this Weber number. Scale-to-reference model size ratios were 1:1.7 and 1:3.4. The reference tests used a 91-cm-chord NACA 0012 model with a velocity of approximately 50 m/s and an MVD of 160 m. Freezing fractions of 0.3, 0.4, and 0.5 were included in the study.

Bond, Thomas H.↗
DOE OSTI2022

Computational Fluid Dynamic Modeling of Dry Cask Simulator with Crosswind

The purpose of this study is to create a STAR-CCM+ model of a Belowground Vertical Dry Cask Simulator (BVDCS) at Sandia National Laboratories (SNL) and validate the model with SNL’s experimental results. The BVDCS consists of a single boiling water reactor assembly fitted with electric heaters encompassed by a containment vessel and shell to represent a belowground spent nuclear fuel (SNF) dry storage system. Blowers are located near the inlet and outlet of the BVDCS to simulate crosswind conditions. In addition to the experimental results, the STAR-CCM+ model developed for this study is compared with a previous computational fluid dynamics (CFD) model in a different software program, which is used as a software-to-software benchmark. The experimental results provide a dataset to compare the STAR-CCM+ model results for a variety of different conditions. The main objective is to validate and improve STAR-CCM+ CFD models for spent nuclear fuel storage systems with explicitly modeled external environments and “wind driven” crossflows. These CFD models aide in the study of external particle deposition in spent nuclear fuel storage systems, which is important to predicting the significance of chloride induced stress corrosion cracking (CISCC). In addition to experimental comparison, a sensitivity analysis study is performed using the STAR-CCM+ model. The sensitivity analysis provides a quantitative assessment of the sensitivity of various parameters. This helps provide information on various parameters that are of particular importance to constructing a model representative of real life systems. The STAR-CCM+ model compared well to the experimental results showing similar responses to changes in cross wind flow, and a number of parameters are identified for model improvement.

Jensen, Ben J.↗
DOE OSTI2025

Low responsiveness of machine learning models to critical or deteriorating health conditions

Machine learning (ML) based mortality prediction models can be immensely useful in intensive care units. Such a model should generate warnings to alert physicians when a patient’s condition rapidly deteriorates, or their vitals are in highly abnormal ranges. Before clinical deployment, it is important to comprehensively assess a model’s ability to recognize critical patient conditions. We develop multiple medical ML testing approaches, including a gradient ascent method and neural activation map. We systematically assess these machine learning models’ ability to respond to serious medical conditions using additional test cases, some of which are time series. Guided by medical doctors, our evaluation involves multiple machine learning models, resampling techniques, and four datasets for two clinical prediction tasks. We identify serious deficiencies in the models’ responsiveness, with the models being unable to recognize severely impaired medical conditions or rapidly deteriorating health. For in-hospital mortality prediction, the models tested using our synthesized cases fail to recognize 66% of the injuries. In some instances, the models fail to generate adequate mortality risk scores for all test cases. Our study identifies similar kinds of deficiencies in the responsiveness of 5-year breast and lung cancer prediction models. Using generated test cases, we find that statistical machine-learning models trained solely from patient data are grossly insufficient and have many dangerous blind spots. Most of the ML models tested fail to respond adequately to critically ill patients. How to incorporate medical knowledge into clinical machine learning models is an important future research direction.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2003

Prebiotic Synthesis of Autocatalytic Products From Formaldehyde-Derived Sugars as the Carbon and Energy Source

Our research objective is to understand and model the chemical processes on the primitive Earth that generated the first autocatalytic molecules and microstructures involved in the origin of life. Our approach involves: (a) investigation of a model origin-of-life process named the Sugar Model that is based on the reaction of formaldehyde- derived sugars (trioses and tetroses) with ammonia, and (b) elucidation of the constraints imposed on the chemistry of the origin of life by the fixed energies and rates of C,H,O-organic reactions under mild aqueous conditions. Recently, we demonstrated that under mild aqueous conditions the Sugar Model process yields autocatalytic products, and generates organic micropherules (2-20 micron dia.) that exhibit budding, size uniformity, and chain formation. We also discovered that the sugar substrates of the Sugar Model are capable of reducing nitrite to ammonia under mild aqueous conditions. In addition studies done in collaboration with Sandra Pizzarrello (Arizona State University) revealed that chiral amino acids (including meteoritic isovaline) catalyze both the synthesis and specific handedness of chiral sugars. Our systematic survey of the energies and rates of reactions of C,H,O-organic substrates under mild aqueous conditions revealed several general principles (rules) that govern the direction and rate of organic reactions. These reactivity principles constrain the structure of chemical pathways used in the origin of life, and in modern and primitive metabolism.

Weber, Arthur L.↗
NASA NTRS2004

Chemical Reaction and Flow Modeling in Fullerene and Nanotube Production

The development of processes to produce fullerenes and carbon nanotubes has largely been empirical. Fullerenes were first discovered in the soot produced by laser ablation of graphite [1]and then in the soot of electric arc evaporated carbon. Techniques and conditions for producing larger and larger quantities of fullerenes depended mainly on trial and error empirical variations of these processes, with attempts to scale them up by using larger electrodes and targets and higher power. Various concepts of how fullerenes and carbon nanotubes were formed were put forth, but very little was done based on chemical kinetics of the reactions. This was mainly due to the complex mixture of species and complex nature of conditions in the reactors. Temperatures in the reactors varied from several thousand degrees Kelvin down to near room temperature. There are hundreds of species possible, ranging from atomic carbon to large clusters of carbonaceous soot, and metallic catalyst atoms to metal clusters, to complexes of metals and carbon. Most of the chemical kinetics of the reactions and the thermodynamic properties of clusters and complexes have only been approximated. In addition, flow conditions in the reactors are transient or unsteady, and three dimensional, with steep spatial gradients of temperature and species concentrations. All these factors make computational simulations of reactors very complex and challenging. This article addresses the development of the chemical reaction involved in fullerene production and extends this to production of carbon nanotubes by the laser ablation/oven process and by the electric arc evaporation process. In addition, the high-pressure carbon monoxide (HiPco) process is discussed. The article is in several parts. The first one addresses the thermochemical aspects of modeling; and considers the development of chemical rate equations, estimates of reaction rates, and thermodynamic properties where they are available. The second part addresses modeling of the arc process for fullerene and carbon nanotube production using O-D, 1-D and 2-D fluid flow models. The third part addresses simulations of the pulsed laser ablation process using time-dependent techniques in 2-D, and a steady state 2-D simulation of a continuous laser ablation process. The fourth part addresses steady state modeling in O-D and 2-D of the HiPco process. In each of the simulations, there is a variety of simplifications that are made that enable one to concentrate on one aspect or another of the process. There are simplifications that can be made to the chemical reaction models , e.g. reduction in number of species by lumping some of them together in a representative species. Other simulations are carried out by eliminating the chemistry altogether in order to concentrate on the fluid dynamics. When solving problems with a large number of species in more than one spatial dimension, it is almost imperative that the problem be decoupled by solving for the fluid dynamics to find the fluid motion and temperature history of "particles" of fluid moving through a reactor. Then one can solve the chemical rate equations with complex chemistry following the temperature and pressure history. One difficulty is that often mixing with an ambient gas is involved. Therefore, one needs to take dilution and mixing into account. This changes the ratio of carbon species to background gas. Commercially available codes may have no provision for including dilution as part of the input. One must the write special solvers for including dilution in decoupled problems. The article addresses both ful1erene production and single-walled carbon nanotube (SWNT) production. There are at least two schemes or concepts of SWNT growth. This article will only address growth in the gas phase by carbon and catalyst cluster growth and SW T formation by the addition of carbon. There are other models that conceive of SWNT growth as a phase separation process from clusters me up carbon and metal catalyst, with the carbon precipitating from the cluster as it cools. We will not deal with that concept in this article. Further research is needed to determine the rates at which these composite clusters form, evaporate, and segregate.

Scott, Carl D.↗