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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Thermodynamic database development: Al-Am-Ga-Pu-U

The goal of this study is about the thermodynamic re-assessment of the Plutonium- Uranium (Pu-U) system as a first step leading to the development of a plutonium-based thermodynamic database (i.e., Pu with Al, Am, Ga, Mo, U…) with resulting phase diagrams and associated thermodynamic data. Indeed, phase stability trends and phase diagrams of multi-component nuclear materials are crucial for predicting properties and performance under normal, hypothetical or even accidental conditions. This work is based on a coupling between ab initio energetics, phenomenological thermodynamics models - based on the CALPHAD (CALculation of PHAse Diagrams) approach - and the use of the Thermo-Calc software, together with experimental data (whenever available). The present report summarizes results obtained (quarter period: 10/07/2013-01/07/2014) under the auspices of an agreement between CEA/DAM and NNSA/DP on cooperation in fundamental science supporting stockpile stewardship (P182).

36 MATERIALS SCIENCE↗
DOE OSTI2024

Unifying Quantum Materials Modeling and Experiments: The Role of Machine Learning Interatomic Potentials

Computational experiments have emerged as a powerful complement to traditional experiments in the design of new materials. The development of machine learning (ML) and deep learning techniques, combined with database construction and data mining, has significantly enhanced traditional quantum mechanical methods. This synergy enables the rapid development of structure-property relationships. In this talk, I will discuss our recent efforts in applying Machine Learning Interatomic Potentials (MLIAPs) to accelerate materials modeling across various material classes and challenging applications where traditional methods fall short. First, I will highlight the success of MLIAPs in accurately modeling the melting behavior of complex materials. Our results demonstrate high fidelity with experimental observations and also with calculated reference melting temperatures. In the second application, I will discuss how MLIAPs are trained and applied to elucidate the interplay between segregation tendencies and surface reconstructions in CuNi alloys under oxidizing conditions. A key factor in the success of these MLIAP applications is the design of minimalistic yet flexible datasets along with a computational framework for training MLIAPs.

Saidi, Wissam↗
DOE OSTI2017

Cation-exchanged zeolites for the selective oxidation of methane to methanol

Motivated by the increasing availability of cheap natural gas resources, considerable experimental and computational research efforts have focused on identifying selective catalysts for the direct conversion of methane to methanol. One promising class of catalysts are cation-exchanged zeolites, which have steadily increased in popularity over the past decade. Here, in this article, we first present a broad overview of this field from a conceptual perspective, and highlight the role of theory in developing a molecular-level understanding of the reaction. Next, by performing and analyzing a large database of density functional theory (DFT) calculations for a wide range of transition metal cations, zeolite topologies and active site motifs, we present a unifying picture of the methane activation process in terms of active site stability, C–H bond activation and methanol extraction. Based on the trade-offs of active site stability and reactivity, we propose a framework for identifying new, promising active site motifs in these systems. Further, we show that the high methanol selectivity arises due to the strong binding nature of the C–H activation products. Lastly, using the atomistic and mechanistic insight obtained from these analyses, we summarize the key challenges and future strategies for improving the performance of cation-exchanged zeolites for this industrially relevant conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Development and Validation of Predictive Models for In-Cylinder Radiation and Wall Heat Transfer

The lack of accurate submodels for in-cylinder radiation and heat transfer has been identified as a key shortcoming in developing truly predictive, physics-based computational fluid dynamics (CFD) models that can be used to develop and design combustion systems for advanced high-efficiency, low-emissions engines. Measurements of wall boundary layers in engines show discrepancies of up to 100% with respect to standard CFD boundary layer models. And analysis of in-cylinder radiation based on the most recent spectral property databases and high-fidelity radiative transfer equation solvers has shown that at operating pressures and exhaust-gas recirculation levels typical of modern compression-ignition truck engines, molecular gas radiation (mainly carbon dioxide and water vapor) can be more important than soot particle radiation, and that a significant fraction of the emitted radiation (50% or more) can be reabsorbed before reaching the walls, thereby acting to redistribute energy in the combustion chamber. In this project, an integrated experimental and simulation approach has been used to generate new physical insight into in-cylinder heat-transfer processes in engines, and to develop computationally practicable CFD-based models that accurately represent the physics. New experimental data have been taken in an optically accessible single-cylinder research engine, and in a multi-cylinder production engine. Those data have provided new insight into the radiative environment in engines. New CFD models have been developed and validated for in-cylinder heat transfer, focusing mainly on radiative heat transfer and coupling between turbulent boundary layer wall heat transfer and radiative heat transfer. The CFD models have been developed and implemented in an open-source software framework that can be shared with other researchers. The models are compatible both with unsteady Reynolds-averaged Navier Stokes (URANS) formulations and with large-eddy simulations (LES) of in-cylinder processes in engines.

02 PETROLEUM↗
NASA NTRS1993

Establishment of computerized numerical databases on thermophysical and other properties of molten as well as solid materials and data evaluation and validation for generating recommended reliable reference data

The Center for Information and Numerical Data Analysis and Synthesis, (CINDAS), measures and maintains databases on thermophysical, thermoradiative, mechanical, optical, electronic, ablation, and physical properties of materials. Emphasis is on aerospace structural materials especially composites and on infrared detector/sensor materials. Within CINDAS, the Department of Defense sponsors at Purdue several centers: the High Temperature Material Information Analysis Center (HTMIAC), the Ceramics Information Analysis Center (CIAC) and the Metals Information Analysis Center (MIAC). The responsibilities of CINDAS are extremely broad encompassing basic and applied research, measurement of the properties of thin wires and thin foils as well as bulk materials, acquisition and search of world-wide literature, critical evaluation of data, generation of estimated values to fill data voids, investigation of constitutive, structural, processing, environmental, and rapid heating and loading effects, and dissemination of data. Liquids, gases, molten materials and solids are all considered. The responsibility of maintaining widely used databases includes data evaluation, analysis, correlation, and synthesis. Material property data recorded on the literature are often conflicting, diverging, and subject to large uncertainties. It is admittedly difficult to accurately measure materials properties. Systematic and random errors both enter. Some errors result from lack of characterization of the material itself (impurity effects). In some cases assumed boundary conditions corresponding to a theoretical model are not obtained in the experiments. Stray heat flows and losses must be accounted for. Some experimental methods are inappropriate and in other cases appropriate methods are carried out with poor technique. Conflicts in data may be resolved by curve fitting of the data to theoretical or empirical models or correlation in terms of various affecting parameters. Reasons (e.g. phase transitions) must be found for unusual dependence or any anomaly. Such critical evaluation involves knowledge of theory, experience in measurement, familiarity with metallurgy (microstructural behavior) and not inconsiderable judgment. An examination of typical data compiled and analyzed by CINDAS shows that the thermal conductivity of a material reported in the literature may vary by a factor of two of more; the range of reported values increases as temperature increases reflecting the difficulty of high temperature measurements. Often only estimates of melt behavior are available, despite the importance of melt properties in modeling, welding, or other solidification processes. There may be only a few measurements available for properties such as kinematic viscosity, even for widely used materials such as stainless steel. In the face of such a paucity of existing data and in a national environment where too few new data are being generated it is nonetheless the responsibility of CINDAS to select and disseminate recommended values of a wide variety of thermophysical properties.

Ho, C. Y.↗
NASA NTRS2003

Evaluation of Flush-Mounted, S-Duct Inlets With Large Amounts of Boundary Layer Ingestion

A new high Reynolds number test capability for boundary layer ingesting inlets has been developed for the NASA Langley Research Center 0.3-Meter Transonic Cryogenic Tunnel. Using this new capability, an experimental investigation of four S-duct inlet configurations with large amounts of boundary layer ingestion (nominal boundary layer thickness of about 40% of inlet height) was conducted at realistic operating conditions (high subsonic Mach numbers and full-scale Reynolds numbers). The objectives of this investigation were to 1) develop a new high Reynolds number, boundary-layer ingesting inlet test capability, 2) evaluate the performance of several boundary layer ingesting S-duct inlets, 3) provide a database for CFD tool validation, and 4) provide a baseline inlet for future inlet flow-control studies. Tests were conducted at Mach numbers from 0.25 to 0.83, Reynolds numbers (based on duct exit diameter) from 5.1 million to a fullscale value of 13.9 million, and inlet mass-flow ratios from 0.39 to 1.58 depending on Mach number. Results of this investigation indicate that inlet pressure recovery generally decreased and inlet distortion generally increased with increasing Mach number. Except at low Mach numbers, increasing inlet mass-flow increased pressure recovery and increased distortion. Increasing the amount of boundary layer ingestion (by decreasing inlet throat height and increasing inlet throat width) or ingesting a boundary layer with a distorted profile decreased pressure recovery and increased distortion. Finally, increasing Reynolds number had almost no effect on inlet distortion but increased inlet recovery by about one-half percent at a Mach number near cruise.

Berrier, Bobby L.↗
NASA NTRSDate not supplied

Towards Quantifying and Correlating RTV Intumescence to Entry-Relevant Conditions

Room Temperature Vulcanizing silicone (RTV) is a high-temperature adhesive used as a gap-filler between Thermal Protection System (TPS) tiles for heatshields on numerous missions. It is also adopted to bond instrumentation plugs of temperature and pressure sensors into heatshield’s tiles. While RTV has been traditionally assumed to be a non-porous and non-ablating material, numerous experiments have shown that RTV pyrolyzes and becomes highly porous as it is heated. Experimental data has also shown heating rate-dependent swelling (or intumescence) and shrinking of RTV, these volume changes may cause roughness-induced boundary layer transition. Outgassing and surface oxide formation of RTV upon decomposition also occur, which can be sources of contamination of heat shield sensors. This combination of detrimental effects motivates a critical need to develop a high-fidelity model for RTV ablation. As a first critical step in RTV modeling, a comprehensive material properties database for RTV was collected that account for the lack of data in properties such as pyrolysis char yield, shape change, virgin and char porosity. The next step is to quantify the volume change of RTV as a function of temperature. While this was done in previous campaigns, limited data was collected which showed a possible heating rate dependent intumescent behavior. To further understand the intumescence phenomenon of RTV, numerous dedicated experiments were performed at Beamline 8.3.2 of the Advanced Light Source, where RTV samples were heated while X-ray scans were taken in situ. Micro-Computed Tomography scans were taken in situ for low heating rates (≤ 60 °C/min), whereas continuous radiography scans were taken for higher heating rates (≤ 1500 ºC/min). Unconstrained samples and samples constrained in different holders (quartz, graphite, FiberForm and PICA) were tested to determine the change in intumescence due to confinement. Using deep learning techniques, the tomographies and radiographies are segmented to obtain volume change, porosity, pore size distributions and connectivity. From the results obtained, modifications to the previous RTV intumescence model are proposed, along with preliminary comparisons to testing RTV at high-enthalpy facilities.

RTV↗
DOE OSTI2020

DISCo-microbe: design of an identifiable synthetic community of microbes

Microbiomes are extremely important for their host organisms, providing many vital functions and extending their hosts’ phenotypes. Natural studies of host-associated microbiomes can be difficult to interpret due to the high complexity of microbial communities, which hinders our ability to track and identify individual members along with the many factors that structure or perturb those communities. For this reason, researchers have turned to synthetic or constructed communities in which the identities of all members are known. However, due to the lack of tracking methods and the difficulty of creating a more diverse and identifiable community that can be distinguished through next-generation sequencing, most such in vivo studies have used only a few strains. To address this issue, we developed DISCo-microbe, a program for the design of an identifiable synthetic community of microbes for use in in vivo experimentation. The program is composed of two modules; (1) create, which allows the user to generate a highly diverse community list from an input DNA sequence alignment using a custom nucleotide distance algorithm, and (2) subsample, which subsamples the community list to either represent a number of grouping variables, including taxonomic proportions, or to reach a user-specified maximum number of community members. As an example, we demonstrate the generation of a synthetic microbial community that can be distinguished through amplicon sequencing. The synthetic microbial community in this example consisted of 2,122 members from a starting DNA sequence alignment of 10,000 16S rRNA sequences from the Ribosomal Database Project. We generated simulated Illumina sequencing data from the constructed community and demonstrate that DISCo-microbe is capable of designing diverse communities with members distinguishable by amplicon sequencing. Using the simulated data we were able to recover sequences from between 97–100% of community members using two different post-processing workflows. Furthermore, 97–99% of sequences were assigned to a community member with zero sequences being misidentified. We then subsampled the community list using taxonomic proportions to mimic a natural plant host–associated microbiome, ultimately yielding a diverse community of 784 members. DISCo-microbe can create a highly diverse community list of microbes that can be distinguished through 16S rRNA gene sequencing, and has the ability to subsample (i.e., design) the community for the desired number of members and taxonomic proportions. Although developed for bacteria, the program allows for any alignment input from any taxonomic group, making it broadly applicable. The software and data are freely available from GitHub and Python Package Index (PYPI).

16S rRNA↗
DOE OSTI2016

A novel analysis method for paired-sample microbial ecology experiments

Many microbial ecology experiments use sequencing data to measure a community s response to an experimental treatment. In a common experimental design, two units, one control and one experimental, are sampled before and after the treatment is applied to the experimental unit. The four resulting samples contain information about the dynamics of organisms that respond to the treatment, but there are no analytical methods designed to extract exactly this type of information from this configuration of samples. Here we present an analytical method specifically designed to visualize and generate hypotheses about microbial community dynamics in experiments that have paired samples and few or no replicates. The method is based on the Poisson lognormal distribution, long studied in macroecology, which we found accurately models the abundance distribution of taxa counts from 16S rRNA surveys. To demonstrate the method s validity and potential, we analyzed an experiment that measured the effect of crude oil on ocean microbial communities in microcosm. Our method identified known oil degraders as well as two clades, Maricurvus and Rhodobacteraceae, that responded to amendment with oil but do not include known oil degraders. Furthermore, our approach is sensitive to organisms that increased in abundance only in the experimental unit but less sensitive to organisms that increased in both control and experimental units, thus mitigating the role of bottle effects .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Modeling electron temperature profiles in the pedestal with simple formulas for ETG transport

Abstract This paper reports on the refinement (building on (Hatch D.R. et al 2022 Phys. Plasmas 29 062501)) and application of simple formulas for electron heat transport from electron temperature gradient (ETG) driven turbulence in the pedestal. The formulas are improved by (1) improving the parameterization for certain key parameters and (2) carefully accounting for the impact of geometry and shaping in the underlying gyrokinetic simulation database. Comparisons with nonlinear gyrokinetic simulations of ETG transport in the MAST pedestal demonstrate the model’s applicability to spherical tokamaks in addition to standard aspect ratio tokamaks. We identify bounds for model applicability: the model is accurate in the steep gradient region, where the ETG turbulence is largely slab-like, but accuracy decreases as the temperature gradient becomes weaker in the pedestal top. We use the formula to model the electron temperature profile in the pedestal for four experimental scenarios while extensively varying input parameters to represent uncertainties. In all cases, the predicted electron temperature profile exhibits extreme sensitivity to separatrix temperature and density, which has implications for core-edge integration. The model reproduces the electron temperature profile for high η e = L n e / L T e scenarios but not for low η e scenarios in which microtearing modes (MTMs) have been identified. We develop a proof-of-concept model for MTM transport and explore the relative roles of ETG and MTM in setting the electron temperature profile.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2004

FAA Pilot Knowledge Tests: Learning or Rote Memorization?

The FAA pilot knowledge test is a multiple-choice assessment tool designed to measure the extent to which applicants for FAA pilot certificates and ratings have mastered a corpus of required aeronautical knowledge. All questions that appear on the test are drawn from a database of questions that is made available to the public. The FAA and others are concerned that releasing test questions may encourage students to focus their study on memorizing test questions. To investigate this concern, we created our own database of questions that differed from FAA questions in four different ways. Our first three question types were derived by modifying existing FAA questions: (1) rewording questions and answers; (2) shuffling answers; and (3) substituting different figures for problems that used figures. Our last question type posed a question about required knowledge for which no FAA question currently exists. Forty-eight student pilots completed one of two paper-and-pencil knowledge tests that contained a mix of these experimental questions. The results indicate significantly lower scores for some question types when compared to unaltered FAA questions to which participants had prior access.

Casner, Stephen M.↗
NASA NTRS1995

Trainable Cataloging for Digital Image Libraries with Applications to Volcano Detection

Users of digital image libraries are often not interested in image data per se but in derived products such as catalogs of objects of interest. Converting an image database into a usable catalog is typically carried out manually at present. For many larger image databases the purely manual approach is completely impractical. In this paper we describe the development of a trainable cataloging system: the user indicates the location of the objects of interest for a number of training images and the system learns to detect and catalog these objects in the rest of the database. In particular we describe the application of this system to the cataloging of small volcanoes in radar images of Venus. The volcano problem is of interest because of the scale (30,000 images, order of 1 million detectable volcanoes), technical difficulty (the variability of the volcanoes in appearance) and the scientific importance of the problem. The problem of uncertain or subjective ground truth is of fundamental importance in cataloging problems of this nature and is discussed in some detail. Experimental results are presented which quantify and compare the detection performance of the system relative to human detection performance. The paper concludes by discussing the limitations of the proposed system and the lessons learned of general relevance to the development of digital image libraries.

digital image libraries, trainable cataloging↗
NASA NTRS2009

Processing Images of Craters for Spacecraft Navigation

A crater-detection algorithm has been conceived to enable automation of what, heretofore, have been manual processes for utilizing images of craters on a celestial body as landmarks for navigating a spacecraft flying near or landing on that body. The images are acquired by an electronic camera aboard the spacecraft, then digitized, then processed by the algorithm, which consists mainly of the following steps: 1. Edges in an image detected and placed in a database. 2. Crater rim edges are selected from the edge database. 3. Edges that belong to the same crater are grouped together. 4. An ellipse is fitted to each group of crater edges. 5. Ellipses are refined directly in the image domain to reduce errors introduced in the detection of edges and fitting of ellipses. 6. The quality of each detected crater is evaluated. It is planned to utilize this algorithm as the basis of a computer program for automated, real-time, onboard processing of crater-image data. Experimental studies have led to the conclusion that this algorithm is capable of a detection rate >93 percent, a false-alarm rate <5 percent, a geometric error <0.5 pixel, and a position error <0.3 pixel.

Cheng, Yang↗
DOE OSTI2013

Coupled alkai fieldspar dissolution and secondary mineral precipatation in batch systems-2: New experiments with supercritical CO2 and implications for carbon sequestration

In order to evaluate the extent of CO{sub 2}–water–rock interactions in geological formations for C sequestration, three batch experiments were conducted on alkali feldspars–CO{sub 2}–brine interactions at 150–200 °C and 300 bars. The elevated temperatures were necessary to accelerate the reactions to facilitate attainable laboratory measurements. Temporal evolution of fluid chemistry was monitored by major element analysis of in situ fluid samples. SEM, TEM and XRD analysis of reaction products showed extensive dissolution features (etch pits, channels, kinks and steps) on feldspars and precipitation of secondary minerals (boehmite, kaolinite, muscovite and paragonite) on feldspar surfaces. Therefore, these experiments have generated both solution chemistry and secondary mineral identity. The experimental results show that partial equilibrium was not attained between secondary minerals and aqueous solutions for the feldspar hydrolysis batch systems. Evidence came from both solution chemistry (supersaturation of the secondary minerals during the entire experimental duration) and metastable co-existence of secondary minerals. The slow precipitation of secondary minerals results in a negative feedback in the dissolution–precipitation loop, reducing the overall feldspar dissolution rates by orders of magnitude. Furthermore, the experimental data indicate the form of rate laws greatly influence the steady state rates under which feldspar dissolution took place. Negligence of both the mitigating effects of secondary mineral precipitation and the sigmoidal shape of rate–ΔG{sub r} relationship can overestimate the extent of feldspar dissolution during CO{sub 2} storage. Finally, the literature on feldspar dissolution in CO{sub 2}-charged systems has been reviewed. The data available are insufficient and new experiments are urgently needed to establish a database on feldspar dissolution mechanism, rates and rate laws, as well as secondary mineral information at CO{sub 2} storage conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Combustion characteristics and detailed simulations of surrogates for a Tier II gasoline certification fuel

An experimental and numerical study of combustion of a gasoline certification fuel (‘indolene’), and four (S4) and five (S5) component surrogates for it, is reported for the configurations of an isolated droplet burning with near spherical symmetry in the standard atmosphere, and a single cylinder engine designed for advanced compression ignition of pre-vaporized fuel. The intent was to compare performance of the surrogate for these different combustion configurations and to assess the broader applicability of the kinetic mechanism and property database for the simulations. A kinetic mechanism comprised of 297 species and 16,797 reactions was used in the simulations that included soot formation and evolution, and accounted for unsteady transport, liquid diffusion inside the droplet, radiative heat transfer, and variable properties. The droplet data showed a clear preference for the S5 surrogate in terms of burning rate. The simulations showed generally very good agreement with measured droplet, flame, and soot shell diameters. Measurements of combustion timing, in-cylinder pressure, and mass-averaged gas temperature were also well predicted with a slight preference for the S5 surrogate. Preferential vaporization was not evidenced from the evolution of droplet diameter but was clearly revealed in simulations of the evolution of mixture fractions inside the droplets. Here, the influence of initial droplet diameter (D o ) on droplet burning was strong, with S5 burning rates decreasing with increasing D o due to increasing radiation losses from the flame. Flame extinction was predicted for D o =3.0 mm as a radiative loss mechanism but not predicted for smaller D o for the conditions of the simulations.

42 ENGINEERING↗
DOE OSTI2025

Dislocation-Grain Boundary Interaction Dataset for FCC Cu

Interactions between dislocations and grain boundaries play a major role in controlling the strength and ductility of structural materials. Experimentally, assessing and probing geometric and stress-based criteria at the local level for dislocation transmission through grain boundaries remains challenging. Therefore, there have been many efforts to systematically generate datasets of dislocation-grain boundary interactions (DGI) via computational models such as molecular dynamics simulations. So far, most DGI datasets have focused only on the subset of nominal minimum-energy grain boundary structures, which limits their applicability, especially to materials processed far from equilibrium. We present a comprehensive database of dislocation-grain boundary interactions for edge, screw, and 60° mixed dislocation with 330 <110> and 257 <112> symmetric tilt grain boundaries (total of 587) in FCC Cu consisting of 73 minimum-energy grain boundary structures and 514 metastable structures. The dataset contains the outcomes for 5234 unique interactions for various dislocation types, grain boundary structures, and applied shear stresses.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Metabolites Associated with Adaptation of Microorganisms to an Acidophilic, Metal-Rich Environment Identified by Stable-Isotope-Enabled Metabolomics

Microorganisms grow under a remarkable range of extreme conditions. Environmental transcriptomic and proteomic studies have highlighted metabolic pathways active in extremophilic communities. However, metabolites directly linked to their physiology are less well defined because metabolomics methods lag behind other omics technologies due to a wide range of experimental complexities often associated with the environmental matrix. We identified key metabolites associated with acidophilic and metal-tolerant microorganisms using stable isotope labeling coupled with untargeted, high-resolution mass spectrometry. We observed >3,500 metabolic features in biofilms growing in pH ~0.9 acid mine drainage solutions containing millimolar concentrations of iron, sulfate, zinc, copper, and arsenic. Stable isotope labeling improved chemical formula prediction by >50% for larger metabolites (>250 atomic mass units), many of which were unrepresented in metabolic databases and may represent novel compounds. Taurine and hydroxyectoine were identified and likely provide protection from osmotic stress in the biofilms. Community genomic, transcriptomic, and proteomic data implicate fungi in taurine metabolism. Leptospirillum group II bacteria decrease production of ectoine and hydroxyectoine as biofilms mature, suggesting that biofilm structure provides some resistance to high metal and proton concentrations. The combination of taurine, ectoine, and hydroxyectoine may also constitute a sulfur, nitrogen, and carbon currency in the communities.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

Absolute Rovibrational Intensities of C-12O2-16 Absorption Bands in the 3090-3850/ CM Spectral Region

A multispectrum nonlinear least-squares fitting technique has been used to determine the absolute intensities for approximately 1500 spectral lines in 36 vibration - rotation bands Of C-12O2-16 between 3090 and 3850/ cm. A total of six absorption spectra of a high- purity (99.995% minimum) natural sample of carbon dioxide were used in the analysis. The spectral data (0.01/cm resolution) were recorded at room temperature and low pressure (1 to 10 Torr) using the McMath-Pierce Fourier transform spectrometer of the National Solar Observatory (NSO) on Kitt Peak. The absorption path lengths for these spectra varied between 24.86 and 385.76 m. The first experimental determination of the intensity of the theoretically predicted 2(nu)(sub 2, sup 2) + nu(sub 3) "forbidden" band has been made. The measured line intensities obtained for each band have been analyzed to determine the vibrational band intensity, S(sub nu), in /cm/( molecule/sq cm) at 296 K, square of the rotationless transition dipole moment |R|(exp 2) in Debye, as well as the nonrigid rotor coefficients. The results are compared to the values listed in the 1996 HITRAN database which are obtained using the direct numerical diagonalization (DND) technique as well as to other published values where available.

Devi, V. Malathy↗