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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Direct Breakthrough Curve Prediction From Statistics of Heterogeneous Conductivity Fields

In this paper, we present a methodology to predict the shape of solute breakthrough curves in heterogeneous aquifers at early times and/or under high degrees of heterogeneity, both cases in which the classical macrodispersion theory may not be applicable. The methodology relies on the observation that breakthrough curves in heterogeneous media are generally well described by lognormal distributions, and mean breakthrough times can be predicted analytically. The log-variance of solute arrival is thus sufficient to completely specify the breakthrough curves, and this is calibrated as a function of aquifer heterogeneity and dimensionless distance from a source plane by means of Monte Carlo analysis and statistical regression. Using the ensemble of simulated groundwater flow and solute transport realizations employed to calibrate the predictive regression, reliability estimates for the prediction are also developed. Additional theoretical contributions include heuristics for the time until an effective macrodispersion coefficient becomes applicable, and also an expression for its magnitude that applies in highly heterogeneous systems. Finally, it is seen that the results here represent a way to derive continuous time random walk transition distributions from physical considerations rather than from empirical field calibration.

58 GEOSCIENCES↗
DOE OSTI2019

eSHAFTS: Integrated and graphical drug design software based on 3D molecular similarity

With the development of computer technology, computer‐aided drug design (CADD) has become an important means for drug research and development, and its representative method is virtual screening. Various virtual screening platforms have emerged in an endless stream and play great roles in the field of drug discovery. With the increasing number of compound molecules, virtual screening platforms face two challenges: low fluency and low visibility of software operations. In this article, we present an integrated and graphical drug design software eSHAFTS based on three‐dimensional (3D) molecular similarity to overcome these shortcomings. Compared with other software, eSHAFTS has four main advantages, which are integrated molecular editing and drawing, interactive loading and analysis of proteins, multithread and multimode 3D molecular similarity calculation, and multidimensional information visualization. Experiments have verified its convenience, usability, and reliability. By using eSHAFTS, various tasks can be submitted and visualized in one desktop software without locally installing any dependent plug‐ins or software. The software installation package can be downloaded for free at http://lilab.ecust.edu.cn/home/resource.html . © 2019 Wiley Periodicals, Inc.

He, Gaoqi↗
DOE OSTI2019

Magnetocaloric Effect and Critical Behavior Investigations in La{sub 0.45}Pr{sub 0.2}Sr{sub 0.35}MnO{sub 3} Manganite Oxide

Structural, magnetic, and magnetocaloric effect (MCE) properties and the critical behavior of the La{sub 0.45}Pr{sub 0.2}Sr{sub 0.35}MnO{sub 3} sample prepared by the sol–gel method have been investigated. The X-ray diffraction characterization reveals that our sample crystallizes in the orthorhombic structure with Pnma space group. Magnetization versus temperature measurement shows that our compound exhibits a ferromagnetic–paramagnetic transition. The Curie temperature is found to be 348 K. Close to this temperature, the maximum values of the magnetic entropy change (ΔS{sub M}) and the relative cooling power (RCP) are found to be 2.84 J/kg/K and 230 J/K under µ{sub 0}H = 5 T, respectively. The Arrott plots revealed that this compound exhibits a second-order magnetic phase transition at T{sub C}. The critical behavior has been investigated by several techniques which are the modified Arrott plot method, the Kouvel–Fisher method, and the critical isotherm analysis. The obtained critical exponents β, γ, and δ are consistent with those predictions of the mean-field model. Their reliability was confirmed by Widom’s scaling relation, as well as the universal scaling hypothesis.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Design update of the ITER upper wide angle viewing system

One of the diagnostic systems being provided by the US is the Upper Wide Angle Viewing System (UWAVS) which provides real-time, simultaneous visible and infrared (IR) images of the ITER divertor regions via optical systems located in five upper ports. UWAVS is designed in three main sections: in-vessel, interspace and port cell assemblies. Each assembly utilizes multiple steering and relay mirrors to direct the in-vessel light out of the tokamak to the port cell camera sensors. The primary design challenge of the in-vessel assembly is maximizing performance of the overall system while surviving the severe electromagnetic and nuclear ITER environment. A first mirror material study was conducted and determined that single crystal molybdenum was the best choice for the first two mirrors in the optical train. A fail open, bellows actuated shutter with cross pivot flexure design was determined to be the most reliable mechanism to protect the first mirror. A geometrically representative glow discharge mirror cleaning system is being created and will be tested to maximize cleaning effectiveness while minimizing optical degradation of the molybdenum mirrors adjacent to the plasma. The shutter and first mirror assemblies were packaged and designed for replacement via remote handling methods to minimize radiation waste and cost associated with eventual component replacement. The preliminary optical and structural design provides a robust and reliable system while maximizing the field of view. The R&D efforts, the technical challenges and issues, and the design and analysis results are introduced.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Reduced order models for assessing CO 2 impacts in shallow unconfined aquifers

Risk assessment studies of potential CO 2 sequestration projects consider many factors, including the possibility of brine and/or CO 2 leakage from the storage reservoir. Detailed multiphase reactive transport simulations have been developed to predict the impact of such leaks on shallow groundwater quality; however, these simulations are computationally expensive and thus difficult to directly embed in a probabilistic risk assessment analysis. Here we present a process for developing computationally fast reduced-order models which emulate key features of the more detailed reactive transport simulations. A large ensemble of simulations that take into account uncertainty in aquifer characteristics and CO 2 /brine leakage scenarios were performed. Twelve simulation outputs of interest were used to develop response surfaces (RSs) using a MARS (multivariate adaptive regression splines) algorithm (Milborrow, 2015). A key part of this study is to compare different measures of ROM accuracy. We then show that for some computed outputs, MARS performs very well in matching the simulation data. The capability of the RS to predict simulation outputs for parameter combinations not used in RS development was tested using cross-validation. Again, for some outputs, these results were quite good. For other outputs, however, the method performs relatively poorly. Performance was best for predicting the volume of depressed-pH-plumes, and was relatively poor for predicting organic and trace metal plume volumes. We believe several factors, including the non-linearity of the problem, complexity of the geochemistry, and granularity in the simulation results, contribute to this varied performance. The reduced order models were developed principally to be used in probabilistic performance analysis where a large range of scenarios are considered and ensemble performance is calculated. We demonstrate that they effectively predict the ensemble behavior. But, the performance of the RSs is much less accurate when used to predict time-varying outputs from a single simulation. If an analysis requires only a small number of scenarios to be investigated, computationally expensive physics-based simulations would likely provide more reliable results. Finally, if the aggregate behavior of a large number of realizations is the focus, as will be the case in probabilistic quantitative risk assessment, the methodology presented here is relatively robust.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Validation of gamma-ray detection techniques for safeguards monitoring at natural uranium conversion facilities

Recent IAEA circulars and policy papers have sought to implement safeguards when any purified aqueous uranium solution or uranium oxides suitable for isotopic enrichment or fuel fabrication exists. Under the revised policy, IAEA Policy Paper 18, the starting point for nuclear material under safeguards was reinterpreted, suggesting that purified uranium compounds should be subject to safeguards procedures no later than the first point in the conversion process. In response to this technical need, a combination of simulation models and experimental measurements were employed to develop and validate concepts of nondestructive assay monitoring systems in a natural uranium conversion plant (NUCP). In particular, uranyl nitrate (UO 2 (NO 3 ) 2 ) solution exiting solvent extraction was identified as a key measurement point (KMP), where gamma-ray spectroscopy was selected as the process monitoring tool. The Uranyl Nitrate Calibration Loop Equipment (UNCLE) facility at Oak Ridge National Laboratory was employed to simulate the full-scale operating conditions of a purified uranium-bearing aqueous stream exiting the solvent extraction process in an NUCP. Nondestructive assay techniques using gamma-ray spectroscopy were evaluated to determine their viability as a technical means for drawing safeguards conclusions at NUCPs, and if the IAEA detection requirements of 1 significant quantity (SQ) can be met in a timely way. This work investigated gamma-ray signatures of uranyl nitrate circulating in the UNCLE facility and evaluated various gamma-ray detector sensitivities to uranyl nitrate. These detector validation activities include assessing detector responses to the uranyl nitrate gamma-ray signatures for spectrometers based on sodium iodide, lanthanum bromide, and high-purity germanium detectors. The results of measurements under static and dynamic operating conditions at concentrations ranging from 10–90 g U/L of natural uranyl nitrate are presented. A range of gamma-ray lines is examined, including attenuation for transmission measurement of density and concentration. It was determined that transmission-corrected gamma-ray spectra provide a reliable way to monitor the 235 U concentration of uranyl nitrate solution in transfer pipes in NUCPs. Furthermore, existing predictive and analysis methods are adequate to design and realize practical designs. The 137 Cs transmission source employed in this work is viable but not optimal for 235 U densitometry determination. Validated simulations assessed the viability of 133 Ba and 57Co as alternative densitometry sources. All three gamma-ray detectors are viable for monitoring natural uranium feed; although high-purity germanium is easiest to interpret, it is, however, the least attractive as an installation instrument. Overall, for monitoring throughput in a facility such as UNCLE, emulating the uranium concentration and pump speeds of the Springfields conversion facility in the United Kingdom, an uncertainty of less than 0.17% is required in order to detect the diversion of 1 SQ of uranyl nitrate through changes in uranium concentration over an accountancy period of one year with a detection probability of 50%. As a result, calibrated gamma-ray detection systems are capable of determining the concentration of uranium content in NUCPs, it is only in combination with verifiable operator declarations and supporting data, such as flow rate and enrichment, that safeguards conclusions can be drawn.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Design and structural assessment of the Spallation Neutron Source 2.0 MW target

The Proton Power Upgrade (PPU) project is underway at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory. The project will double the proton accelerator power from 1.4 MW to 2.8 MW, increase power to the First Target Station (FTS), and enable a future Second Target Station (STS). The power increase partly comes from raising proton energy from 1.0 GeV to 1.3 GeV. The STS will operate at 0.7 MW at 15 Hz when completed. Until then, PPU will provide the capability to operate the FTS at 2.0 MW at 60 Hz. Maximum power at the FTS to date has been 1.4 MW at 60 Hz with 1.0 GeV protons. A new mercury target module design to operate reliably under PPU conditions has been completed after a multi-year effort. The design philosophy and assessment of the structural analysis are described here. This target underwent an unprecedented design and analysis process for SNS using the latest engineering techniques and incorporating years of operating lessons and outcomes from R&D to meet structural design criteria. Finally, it also incorporates high-flow gas injection to further mitigate pulse fatigue stresses as well as cavitation damage to the mercury vessel.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

How threshold effects in spectroscopic factors influence heavy-ion knockout reactions

A two-decade-old puzzle in heavy-ion one-nucleon knockout reactions is the strong correlation between the reduction factor R S = σ exp /σ t h and the Fermi surface asymmetry ΔS. Theoretical cross sections typically rely on spectroscopic factors (SFs) from shell model (SM) calculations, which neglect continuum coupling effects. Here, we employ the Gamow shell model (GSM), which explicitly incorporates continuum coupling, to compute SFs for p-shell nuclei and predict corresponding theoretical cross sections. Systematic calculations demonstrate that using GSM-derived SFs substantially reduces discrepancies between theoretical and experimental results. This improvement is particularly significant for deeply bound nucleon knockout in nuclei near the dripline, where traditional SM-based calculations fall short. As a result, using GSM SFs, the ratio R s exhibits no pronounced dependence on ΔS. Furthermore, both the ratio of GSM SFs to SM SFs and their corresponding reaction cross sections ratios exhibit a strong ΔS dependence. We have also compared GSM SFs and cross sections with those from the no-core shell model calculations, giving a similar pronounced sensitivity to ΔS. Detailed analysis attributes these correlations to threshold effects for SFs in weakly bound systems. Overall, incorporating continuum coupling via GSM enhances the reliability of SF predictions for exotic, weakly bound nuclei and provides key insights toward resolving the enduring puzzle in heavy-ion knockout reactions from a nuclear structure perspective.

Gamow shell model↗
DOE OSTI2025

Modeling receiver flux of commercial power tower concentrating solar power plants using ray tracing: a round-robin comparison of SolTrace, Solstice, and TieSOL

This study presents a multi-stage, cross-validation comparison of three software packages for Monte Carlo ray tracing (MCRT) applied to central tower concentrating solar power (CSP) systems. The three packages evaluated are: (1) SolTrace, an open-source tool developed by the National Renewable Energy Laboratory (NREL); (2) Solstice, an open-source program created by CNRS-PROMES and Meso-Star, with enhancements for CSP applications (called solsticepy) from the Australian National University; and (3) TieSOL, a commercial software developed by Tietronix. This investigation extends previous ray tracing comparisons by incorporating models of multi-facet heliostats within a commercial-scale solar field, taking into account zoned focal lengths and canting configurations. Receiver flux distributions were compared across the tools using a series of case studies, including single-heliostat scenarios, isolated blocking situations, and comprehensive full-field simulations. The case studies were designed to diagnose differences across the models at varying levels of complexity, and to identify and resolve discrepancies as additional parameters were introduced. Key factors examined in the analysis include sun positions, heliostat location, facet and canting focus, and aimpoint strategies. The comparison aims to improve the accuracy and reliability of these tools while providing benchmark cases for validating future optical modeling tools.

14 SOLAR ENERGY↗
DOE OSTI2018

Rapidly Assessing the Quality of Targeted Proteomics Experiments through Monitoring Stable-Isotope Labeled Standards

Selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), is a data acquisition technique used in targeted analysis of molecules, including targeted proteomic studies. It exploits the unique capability of triple-quadrupole (QQQ) mass spectrometers to monitor the predefined precursor and fragment ion pairs of specific molecules of interest throughout a liquid chromatography (LC) elution profile. Compared to shotgun proteomics, targeted proteomics using SRM has high selectivity, high sensitivity, and a wide linear dynamic range,(1-3) which makes it especially useful in the accurate and reproducible quantification of low-abundance proteins in highly complex biological samples. SRM has been widely used in the fields of biomarker discovery,(4-7) analysis of protein post-translational modifications(8) and characterization of biological protein networks.(4,9) In the recent years, multiple technical advances have greatly improved the throughput of SRM analyses, allowing for the quantification of hundreds of peptides in a single analysis.(6,7,10) For example, a single 800-plex SRM assay (e.g., 400 unlabeled and heavy-labeled peptide pairs and 2400 transitions with retention time scheduling) using ultrahigh-performance liquid chromatography (UHPLC) has been developed to quantify proteins in plasma.(11) Advanced labeling techniques utilizing in vitro proteome-assisted MRM for protein absolute quantification (iMPAQT) demonstrated the capability of SRM in genome-wide protein quantification of over 18?000 human proteins.(12) Moreover, the scan speed of QQQ instrumentation has been greatly improved in recent releases of commercial instrumentation. The newly developed TSQ Altis (released in 2017) can scan more than 600 transitions per second, which is 6 times more than a traditional QQQ scan speed of 100 transitions per second. The breadth of measurement enabled by these technological improvements to QQQ mass spectrometry has increased the feasibility and popularity of large scale targeted proteomics studies,(13) a major application of which will be in clinical studies in which up to hundreds of protein candidates need to be quantified in hundreds of clinical specimens.(14) Quantitative accuracy is a primary motivating factor for utilizing a targeted proteomics protocol. The precise and reproducible absolute quantification produced by SRM assays is essential to many clinical and laboratory experiments.(15,16) Because the abundance of an endogenous peptide is calculated from the measurement of the spiked-in reference standard, it is essential to assess the data quality of these references.(17) In early applications of targeted proteomics, when instrument speed greatly limited the number of transitions that could be monitored, much of this quality assessment was done manually. However, recent improvements in instrument performance and experimental design have enabled a dramatic increase in the number of target peptides and associated SRM transitions, which makes manual quality assessment an untenable and laborious task. A variety of computational tools assist in SRM experiment design and data analysis. The first task in creating an SRM experiment is the choice of proteins and representative peptides to monitor. Achieving a reliable protein abundance requires appropriately choosing peptides that have a strong signal and are free from interferences in the biological matrix. Numerous computational tools exist to facilitate assay design by identifying peptides and refining SRM transitions.(18-21) To help share these assays and eliminate time spent designing the same transitions at multiple institutions, community portals have begun to host well-designed and vetted assays.(22-24) Analyzing the experimental data requires significant computational effort to align files across replicates and experimental conditions, pick peaks and produce quantitative values, normalize data and perform statistical tests, etc.(25-27)

Gibbons, Bryson C.↗
DOE OSTI2017

Calcination does not remove all carbon from colloidal nanocrystal assemblies

Removing organics from hybrid nanostructures is a crucial step in many bottom-up materials fabrication approaches. It is usually assumed that calcination is an effective solution to this problem, especially for thin films. This assumption has led to its application in thousands of papers. Here in this paper, we show that this general assumption is incorrect by using a relevant and highly controlled model system consisting of thin films of ligand-capped ZrO 2 nanocrystals. After calcination at 800 °C for 12 h, while Raman spectroscopy fails to detect the ligands after calcination, elastic backscattering spectrometry characterization demonstrates that ~18% of the original carbon atoms are still present in the film. By comparison plasma processing successfully removes the ligands. Our growth kinetic analysis shows that the calcined materials have significantly different interfacial properties than the plasma-processed counterparts. Calcination is not a reliable strategy for the production of single-phase all-inorganic materials from colloidal nanoparticles.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Design and Modeling of a Prototype Floating Membrane Reservoir System Application for Pumped Storage Hydropower

Design and modeling were performed for a prototype floating membrane reservoir system for closed-loop pumped storage hydropower (PSH) application. Typically, new construction of PSH requires high up-front development costs and long investment return periods. The proposed floating membrane reservoir system innovative technology would eliminate the need for highly disruptive and costly reservoir construction. Such modular systems may ultimately provide reliable, flexible power generation and can be replicated multiple times to increase energy storage capacity. This paper documents the modeling response analysis completed to refine and validate the design prior to the testing of the prototype. Computational fluid dynamics modeling efforts were completed to assess hydrostatic and hydrodynamic forces acting on the reservoir for several deployment and alignment arrangements. The system stability was evaluated using material stress and frequency response analysis. The conclusions, based on hydrodynamic and structural response modeling, support a decision to move forward with construction, deployment, and testing of the innovative prototype floating reservoir system.

Hadjerioua, Boualem↗
DOE OSTI2022

Detecting hidden transient events in noisy nonlinear time-series

The information impulse function (IIF), running Variance, and local Hölder Exponent are three conceptually different time-series evaluation techniques. These techniques examine time-series for local changes in information content, statistical variation, and point-wise smoothness, respectively. Using simulated data emulating a randomly excited nonlinear dynamical system, this study interrogates the utility of each method to correctly differentiate a transient event from the background while simultaneously locating it in time. Computational experiments are designed and conducted to evaluate the efficacy of each technique by varying pulse size, time location, and noise level in time-series. Our findings reveal that, in most cases, the first instance of a transient event is more easily observed with the information-based approach of IIF than with the Variance and local Hölder Exponent methods. While our study highlights the unique strengths of each technique, the results suggest that very robust and reliable event detection for nonlinear systems producing noisy time-series data can be obtained by incorporating the IIF into the analysis.

42 ENGINEERING↗
DOE OSTI2013

A high-dispersion molecular gas component in nearby galaxies

We present a comprehensive study of the velocity dispersion of the atomic (H I) and molecular (H{sub 2}) gas components in the disks (R ≲ R {sub 25}) of a sample of 12 nearby spiral galaxies with moderate inclinations. Our analysis is based on sensitive high-resolution data from the THINGS (atomic gas) and HERACLES (molecular gas) surveys. To obtain reliable measurements of the velocity dispersion, we stack regions several kiloparsecs in size, after accounting for intrinsic velocity shifts due to galactic rotation and large-scale motions. We stack using various parameters: the galactocentric distance, star formation rate surface density, H I surface density, H{sub 2} surface density, and total gas surface density. We fit single Gaussian components to the stacked spectra and measure median velocity dispersions for H I of 11.9 ± 3.1 km s{sup –1} and for CO of 12.0 ± 3.9 km s{sup –1}. The CO velocity dispersions are thus, surprisingly, very similar to the corresponding ones of H I, with an average ratio of σ{sub HI}/σ{sub CO}= 1.0 ± 0.2 irrespective of the stacking parameter. The measured CO velocity dispersions are significantly higher (factor of ∼2) than the traditional picture of a cold molecular gas disk associated with star formation. The high dispersion implies an additional thick molecular gas disk (possibly as thick as the H I disk). Our finding is in agreement with recent sensitive measurements in individual edge-on and face-on galaxies and points toward the general existence of a thick disk of molecular gas, in addition to the well-known thin disk in nearby spiral galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

The primordial helium abundance from updated emissivities

Observations of metal-poor extragalactic H II regions allow the determination of the primordial helium abundance, Y{sub p}. The He I emissivities are the foundation of the model of the H II region's emission. Porter, Ferland, Storey, and Detisch (2012) have recently published updated He I emissivities based on improved photoionization cross-sections. We incorporate these new atomic data and update our recent Markov Chain Monte Carlo analysis of the dataset published by Izotov, Thuan, and Stasi'nska (2007). As before, cuts are made to promote quality and reliability, and only solutions which fit the data within 95% confidence level are used to determine the primordial He abundance. The previously qualifying dataset is almost entirely retained and with strong concordance between the physical parameters. Overall, an upward bias from the new emissivities leads to a decrease in Y{sub p}. In addition, we find a general trend to larger uncertainties in individual objects (due to changes in the emissivities) and an increased variance (due to additional objects included). From a regression to zero metallicity, we determine Y{sub p} = 0.2465 ± 0.0097, in good agreement with the BBN result, Y{sub p} = 0.2485 ± 0.0002, based on the Planck determination of the baryon density. In the future, a better understanding of why a large fraction of spectra are not well fit by the model will be crucial to achieving an increase in the precision of the primordial helium abundance determination.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Mitigating baryonic effects with a theoretical error covariance

ABSTRACT One of the primary sources of uncertainties in modelling the cosmic-shear power spectrum on small scales is the effect of baryonic physics. Accurate cosmology for stage-IV surveys requires knowledge of the matter power spectrum deep in the non-linear regime at the per cent level. Therefore, it is important to develop reliable mitigation techniques to take into account baryonic uncertainties if information from small scales is to be considered in the cosmological analysis. In this work, we develop a new mitigation method for dealing with baryonic physics for the case of the shear angular power spectrum. The method is based on an augmented covariance matrix that incorporates baryonic uncertainties informed by hydrodynamical simulations. We use the results from 13 hydrodynamical simulations and the residual errors arising from a fit to a ΛCDM model using the extended halo model code HMCode to account for baryonic physics. These residual errors are used to model a so-called theoretical error covariance matrix that is added to the original covariance matrix. In order to assess the performance of the method, we use the 2D tomographic shear from four hydrodynamical simulations that have different extremes of baryonic parameters as mock data and run a likelihood analysis comparing the residual bias on Ωm and σ8 of our method and the HMCode for an LSST-like survey. We use different modelling of the theoretical error covariance matrix to test the robustness of the method. We show that it is possible to reduce the bias in the determination of the tested cosmological parameters at the price of a modest decrease in the precision.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Connecting mechanical properties to hydrogen defects in PAN-based carbon fibers

Atomic-level defects dictate the mechanical properties of carbon fibers and strong correlations have been established between the crystallite sizes and mechanical properties. We recently demonstrated similar correlations with hydrogen content, but reliably quantifying the hydrogen content is not possible using only inelastic neutron scattering experiments. Here, we present prompt-gamma activation analysis (PGAA) experiments collected on 20 commercially available carbon fibers to quantify the hydrogen content of carbon fibers and find correlations between fiber modulus and hydrogen content. We then evaluate the role of hydrogen defect type and connect the PGAA results to both newly acquired and recently reported inelastic neutron scattering experiments. In conclusion, we find that intercalated hydrogen defects are preferentially removed at carbonization temperatures required for high-modulus fibers, potentially giving rise to voids within the carbon fibers that undermine their tensile strength.

36 MATERIALS SCIENCE↗