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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

CCCP and MENeaCS: (updated) weak-lensing masses for 100 galaxy clusters

ABSTRACT Large area surveys continue to increase the samples of galaxy clusters that can be used to constrain cosmological parameters, provided that the masses of the clusters are measured robustly. To improve the calibration of cluster masses using weak gravitational lensing we present new results for 48 clusters at 0.05 < z < 0.15, observed as part of the Multi Epoch Nearby Cluster Survey, and re-evaluate the mass estimates for 52 clusters from the Canadian Cluster Comparison Project. Updated high-fidelity photometric redshift catalogues of reference deep fields are used in combination with advances in shape measurements and state-of-the-art cluster simulations, yielding an average systematic uncertainty in the lensing signal below 5 per cent, similar to the statistical uncertainty for our cluster sample. We derive a scaling relation with Planck measurements for the full sample and find a bias in the Planck masses of 1 − b = 0.84 ± 0.04 (stat) ±0.05 (syst). We find no statistically significant trend of the mass bias with redshift or cluster mass, but find that different selections could change the bias by up to 0.07. We find a gas fraction of 0.139 ± 0.014 (stat) for eight relaxed clusters in our sample, which can also be used to infer cosmological parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

A dual dynamic shutter system for accelerating ion irradiation sample throughput via lateral gas implantation gradients

Ion irradiation for material performance testing is limited due to its serial nature, which allows for only one value of the implantation (appm) versus dose (dpa) parameter space to be explored for each ion and experiment at a time. While ion irradiation can accelerate the process by up to three orders of magnitude compared to neutron irradiation experiments, the sample throughput for ion irradiation remains relatively low. To address these limitations, a novel capability has been developed at the Michigan Ion Beam Laboratory (MIBL), enabling for the creation of single- and two-dimensional lateral ion implantation gradients using recently installed motorized-controlled ion-beam shutters. This advancement can generate a wide scope of the two-dimensional (H+, He2+) implantation parameter space within a single sample. Integration of this new capability now allows for dual- and triple-ion beam experiments to be performed with full user control over not only the ion implantation depth, but also laterally across the sample by imposing ion implantation concentration gradients, thus providing researchers with a high-throughput means for material testing under various irradiation conditions. Furthermore, recent improvements in MIBL's microbeam ion-beam analysis (IBA) target station now allow for probing these concentration gradients in irradiated alloys with exceptional spatial resolution, down to 10 µm. These two approaches promise to significantly improve ion irradiation capabilities and increase the sample throughput by several orders of magnitude. The application of the shutter technique plus the subsequent microbeam characterization of the imposed implantation gradients are showcased by two proof-of-principle ion-irradiated experiments, one performed on single-crystal Si and the other on the fusion-candidate alloy F82H-IEA. These advancements mark a substantial leap in ion-beam technology, offering researchers a robust, high-throughput method to efficiently investigate candidate alloys with high technological readiness for both advanced fission and fusion reactor applications, in a time- and cost-effective manner.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

Chitosan Coating Functionalized with Flaxseed Oil and Green Tea Extract as a Bio-Based Solution for Beef Preservation

Ecological and safe packaging solutions arise as pivotal points in the development of an integrated system for sustainable meat production. The aim of this study was to assess the effect of a combined chitosan (Ch) + green tea extract (GTE) + essential oil (thyme oil, TO; flaxseed oil, FO; or oregano oil, OO) coating on the safety and quality of vacuum-packaged beef during storage at 4 °C. An optimized bio-based coating formulation was selected (2% Ch + 2% GTE + 0.1% FO) to be applied to three fresh beef cuts (shoulder, Sh; knuckle, Kn; Striploin, St) based on its pH (5.8 ± 0.1), contact angle (22.3 ± 0.4°) and rheological parameters (viscosity = 0.05 Pa.s at shear rate > 20 s−1). Shelf-life analysis showed that the Ch–GTE–FO coating delayed lipid oxidation and reduced total viable counts (TVC) and Enterobacteriaceae growth compared with uncoated beef samples over five days. In addition, Ch–GTE–FO coating decreased total color changes of beef samples (e.g., ∆E* = 9.84 and 3.94, for non-coated and coated Kn samples, respectively) for up to five days. The original textural parameters (hardness, adhesiveness and springiness) of beef cuts were maintained during storage when Ch–GTE–FO coating was applied. Based on the physicochemical and microbial characterization results, the combination of the Ch–GTE–FO coating developed was effective in preserving the quality of fresh beef cuts during refrigerated storage along with vacuum packaging.

Mendes, Cíntia G.↗
DOE OSTI2021

Do quasar X-ray and UV flux measurements provide a useful test of cosmological models?

ABSTRACT The recent compilation of quasar (QSO) X-ray and ultraviolet (UV) flux measurements include QSOs that appear to not be standardizable via the X-ray luminosity and UV luminosity (LX–LUV) relation and so should not be used to constrain cosmological model parameters. Here, we show that the largest of seven sub-samples in this compilation, the SDSS-4XMM QSOs that contribute about 2/3 of the total QSOs, have LX–LUV relations that depend on the cosmological model assumed and also on redshift, and is the main cause of the similar problem discovered earlier for the full QSO compilation. The second and third biggest sub-samples, the SDSS-Chandra and XXL QSOs that together contribute about 30 per cent of the total QSOs, appear standardizable, but provide only weak constraints on cosmological parameters that are not inconsistent with the standard spatially flat ΛCDM model or with constraints from better-established cosmological probes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The Spatial Clustering of ROSAT All-Sky Survey Active Galactic Nuclei. V. The Evolution of Broad-line AGN Clustering Properties in the Last 6 Gyr

This is the fifth paper in a series of investigations of the clustering properties of luminous, broad-emission-line active galactic nuclei (AGNs) identified in the ROSAT All-Sky Survey (RASS) and Sloan Digital Sky Survey (SDSS). In this work we measure the cross-correlation function (CCF) between RASS/SDSS Data Release 14 AGNs with the SDSS CMASS galaxy sample at 0.44 < z < 0.64. We apply halo occupation distribution (HOD) modeling to the CCF along with the autocorrelation function of the CMASS galaxies. We find that X-ray-selected and optically selected AGNs at 0.44 < z < 0.64 reside in statistically identical halos with a typical dark matter halo (DMH) mass of $M$$^{typ,AGN}_{DMH}$ ~ 10 12.7 h –1 M ⊙ . The acceptable HOD parameter space for these two broad-line AGN samples have only statistically marginal differences caused by small deviations of the CCFs in the one-halo-dominated regime on small scales. In contrast to optically selected AGNs, the X-ray AGN sample may contain a larger population of satellites at MDMH ~ 1013h–1M⊙. We compare our measurements in this work with our earlier studies at lower independent redshift ranges, spanning a lookback time of 6 Gyr. The comparison over this wider redshift range of 0.07 < z < 0.64 reveals (i) no significant difference between the typical DMH masses of X-ray-selected and optically selected AGNs, (ii) weak positive clustering dependencies of $M$$^{typ,AGN}_{DMH}$ with L X and M BH , (iii) no significant dependence of $M$$^{typ,AGN}_{DMH}$ on Eddington ratio, and (iv) the same DMH masses host more-massive accreting black holes at high redshift than at low redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Deep Learning for Simultaneous Inference of Hydraulic and Transport Properties

Abstract Identification of a heterogeneous conductivity field and reconstruction of a contaminant release history are key aspects of subsurface remediation. These two goals are achieved by combining model predictions with sparse and noisy hydraulic head and concentration measurements. Solution of this inverse problem is notoriously difficult due to, in part, high dimensionality of the parameter space and high computational cost of repeated forward solves. We use a convolutional adversarial autoencoder (CAAE) to parameterize a heterogeneous non‐Gaussian conductivity field via a low‐dimensional latent representation. A three‐dimensional dense convolutional encoder‐decoder (DenseED) network serves as a forward surrogate of the flow and transport model. The CAAE‐DenseED surrogate is fed into the ensemble smoother with multiple data assimilation (ESMDA) algorithm to sample from the Bayesian posterior distribution of the unknown parameters, forming a CAAE‐DenseED‐ESMDA inversion framework. The resulting CAAE‐DenseED‐ESMDA inversion strategy is used to identify a three‐dimensional contaminant source and conductivity field. A comparison of the inversion results from CAAE‐ESMDA with physical flow and transport simulator and from CAAE‐DenseED‐ESMDA shows that the latter yields accurate reconstruction results at the fraction of the computational cost of the former.

Zhou, Zitong↗
DOE OSTI2023

BEYONDPLANCK XI. Bayesian CMB analysis with sample-based end-to-end error propagation

We present posterior sample-based cosmic microwave background (CMB) constraints from Planck LFI and WMAP observations as derived through global end-to-end Bayesian processing within the BeyondPlanck framework. We first use these samples to study correlations between CMB, foreground, and instrumental parameters, and we identify a particularly strong degeneracy between CMB temperature fluctuations and free-free emission on intermediate angular scales (400 ≲ ℓ ≲ 600), which is mitigated through model reduction, masking, and resampling. We compare our posterior-based CMB results with previous Planck products, and find generally good agreement, although with notably higher noise due to our exclusion of HFI data. We find a best-fit CMB dipole amplitude of 3362.7 ± 1.4 µK, in excellent agreement with previous Planck results. The quoted dipole uncertainty is derived directly from the sampled posterior distribution, and does not involve any ad hoc contributions for Planck instrumental systematic effects. Similarly, we find a temperature quadrupole amplitude of ${σ}_{2}^{TT}$ = 229 ± 97 µK 2 , which is in good agreement with previous results in terms of the amplitude, but the uncertainty is an order of magnitude larger than the naive diagonal Fisher uncertainty. Relatedly, we find lower evidence for a possible alignment between the quadrupole and octopole than previously reported due to a much larger scatter in the individual quadrupole coefficients, caused both by marginalizing over a more complete set of systematic effects, but also by our more conservative analysis mask required to mitigate the free-free degeneracy. For higher multipoles, we find that the angular temperature power spectrum is generally in good agreement with both Planck and WMAP. At the same time, we note that this is the first time the sample-based asymptotically exact Blackwell-Rao estimator has been successfully established for multipoles up to ℓ ≤ 600, and it now accounts for the majority of the cosmologically important information. Overall, this analysis demonstrates the unique capabilities of the Bayesian approach with respect to end-to-end systematic uncertainty propagation, and we believe it can and should play an important role in the analysis of future CMB experiments. Cosmological parameter constraints are presented in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Generating mock galaxy catalogues for flux-limited samples like the DESI Bright Galaxy Survey

ABSTRACT Accurate mock galaxy catalogues are crucial to validate analysis pipelines used to constrain dark energy models. We present a fast HOD-fitting method which we apply to the AbacusSummit simulations to create a set of mock catalogues for the DESI Bright Galaxy Survey, which contain r-band magnitudes and $(g-r)$ colours. The halo tabulation method fits HODs for different absolute magnitude threshold samples simultaneously, preventing unphysical HOD crossing between samples. We validate the HOD fitting procedure by fitting to real-space clustering measurements and galaxy number densities from the MXXL BGS mock, which was tuned to the SDSS and GAMA surveys. The best-fitting clustering measurements and number densities are mostly within the assumed errors, but the clustering for the faint samples is low on large scales. The best-fitting HOD parameters are robust when fitting to simulations with different realizations of the initial conditions. When varying the cosmology, trends are seen as a function of each cosmological parameter. We use the best-fitting HOD parameters to create cubic box and cut sky mocks from the AbacusSummit simulations, in a range of cosmologies. As an illustration, we compare the ${}^{0.1}M_r\lt -20$ sample of galaxies in the mock with BGS measurements from the DESI one-percent survey. We find good agreement in the number densities, and the projected correlation function is reasonable, with differences that can be improved in the future by fitting directly to BGS clustering measurements. The cubic box and cut-sky mocks in different cosmologies are made publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Tensile testing and fracture mechanism analysis of polyvinyl alcohol nanofibrous webs

Abstract A tensile properties testing study was conducted to understand the influence of thickness, cross‐head speed (speed of testing), gauge length (GL; specimen test length), and sample shape on important tensile properties of polyvinyl alcohol (PVA) nanofiber webs. The effects of each testing parameter on load at break, extension at break, Young's modulus, and tensile stress–strain curve of PVA nanofiber webs are analyzed. The Welch two sample t ‐tests show the significant difference among tested data. Using interaction plots, two‐way analysis of variance, and margin mean plots, the interaction effects among testing parameters have been analyzed. Of all the factors, cross‐head speed, the interaction among GL, and sample thickness (GL: Thickness) and the interaction among GL, testing speed and sample thickness (GL: Speed: Thickness) have significant influence on the tensile properties of PVA nanofiber webs. Moreover, the hypothesized model of mechanism of tensile strain–stress curve of PVA nanofiber webs has been proposed. Based on the model, the tensile strain–stress curve can be split into three stages: linear elastic, partial break up, and complete breakage. This study will provide a better understanding of tensile testing parameters' effects and their interaction effects on the tensile properties of nanowebs.

Lou, Lihua↗
DOE OSTI2025

Multi-physics melt pool modeling and process optimization for laser direct energy deposition of Nb-based refractory C103: Defect formation, geometric precision, and process mapping

Recent developments in additive manufacturing (AM) technology have reignited interest in the fabrication of the Nb-based refractory C103 alloy offering solutions to the challenges posed by traditional manufacturing methods. However, the limited numerical and experimental studies on laser direct energy deposition (DED) of C103 have hindered the understanding of the relationships between process parameters and build quality. This has made it challenging to consistently produce parts with the desired quality and microstructure suitable for critical applications. In this study, we focus on optimizing the laser DED process for C103 by employing a hybrid approach that combines experimental techniques and computational fluid dynamics (CFD). This approach facilitates the development of process maps for defect detection and geometric precision. To achieve this, multi-layer C103 samples were fabricated using laser DED under various process parameters, enabling the creation of a process map for defect detection. Additionally, a multi-physics, multiphase simulation framework was developed within a high-performance computing (HPC) environment to establish process maps for geometric precision. Using these process maps, printability windows were identified for achieving both the desired geometric accuracy and defect-free prints. It was observed that prints with a power-to-velocity (P/V) ratio close to unity resulted in defect-free outcomes. This study provides a foundation for reducing design lead time and rejected parts, ultimately optimizing the laser DED process for C103.

Defect formation and geometric precision↗
DOE OSTI2025

Understanding the Effect of Sample Geometry on Temperature Distribution during Optical Floating Zone Crystal Growth in Vacuum Environment through Heat Transfer Modeling

Optical floating zone furnaces (OFZ) have had a transformative impact on fundamental science due to their ability to rapidly produce large single crystals of a wide variety of complex materials. However, a quantitative understanding of the OFZ growth environment is generally lacking due to the difficulty of measuring the local sample temperatures during OFZ growth, as well as to the general lack of information about the temperature-dependent physical parameters needed to model heat transfer. To overcome these challenges, we apply a physics-based heat transfer model, parametrized by measurements from synchrotron experiments and a machine-learning (ML) algorithm, to simulate the temperature distributions of samples heated in an OFZ furnace in a vacuum environment. This model is used to quantitatively understand how the sample maximum temperature and temperature gradient (key parameters that influence the success of crystal growth) are affected by the rod size, rod shape, and heat-zone position on the rod. The results of this study can be applied to make informed decisions on how crystal growth parameters can be tuned to modify temperature profiles and to optimize crystal growth outcomes even when data on internal sample temperature profiles (e.g., those obtained through in situ synchrotron experiments) are not accessible.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The discriminant power of bubble wall velocities: gravitational waves and electroweak baryogenesis

A precise determination of the bubble wall velocity v$_{w}$ is crucial for making accurate predictions of the baryon asymmetry and gravitational wave (GW) signals in models of electroweak baryogenesis (EWBG). Working in the local thermal equilibrium approximation, we exploit entropy conservation to present efficient algorithms for computing v$_{w}$, significantly streamlining the calculation. We then explore the parameter dependencies of v$_{w}$, focusing on two sample models capable of enabling a strong first-order electroweak phase transition: a ℤ$_{2}$-symmetric singlet extension of the SM, and a model for baryogenesis with CP violation in the dark sector. We study correlations among v$_{w}$ and the two common measures of phase transition strength, α$_{n}$ and v$_{n}$/T$_{n}$. Interestingly, we find a relatively model-insensitive relationship between v$_{n}$/T$_{n}$ and α$_{n}$. We also observe an upper bound on α$_{n}$ for the deflagration/hybrid wall profiles naturally compatible with EWBG, the exact value for which varies between models, significantly impacting the strength of the GW signals. In summary, our work provides a framework for exploring the feasibility of EWBG models in light of future GW signals.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Forecasting Multi-Wave Epidemics Through Bayesian Inference

We present a simple, near-real-time Bayesian method to infer and forecast a multiwave outbreak, and demonstrate it on the COVID-19 pandemic. The approach uses timely epidemiological data that has been widely available for COVID-19. It provides short-term forecasts of the outbreak’s evolution, which can then be used for medical resource planning. The method postulates one- and multiwave infection models, which are convolved with the incubation-period distribution to yield competing disease models. The disease models’ parameters are estimated via Markov chain Monte Carlo sampling and information-theoretic criteria are used to select between them for use in forecasting. The method is demonstrated on two- and three-wave COVID-19 outbreaks in California, New Mexico and Florida, as observed during Summer-Winter 2020. We find that the method is robust to noise, provides useful forecasts (along with uncertainty bounds) and that it reliably detected when the initial single-wave COVID-19 outbreaks transformed into successive surges as containment efforts in these states failed by the end of Spring 2020.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

An extended polynomial chaos expansion for PDF characterization and variation with aleatory and epistemic uncertainties

This paper presents an extended polynomial chaos formalism for epistemic uncertainties and a new framework for evaluating sensitivities and variations of output probability density functions (PDF) to uncertainty in probabilistic models of input variables. An ”extended” polynomial chaos expansion (PCE) approach is developed that accounts for both aleatory and epistemic uncertainties, modeled as random variables, thus allowing a unified treatment of both types of uncertainty. We explore in particular epistemic uncertainty associated with the choice of prior probabilistic models for input parameters. A PCE-based Kernel Density (KDE) construction provides a composite map from the PCE coefficients and germ to the PDF of quantities of interest (QoI). Here, the sensitivities of these PDF with respect to the input parameters are then evaluated. Input parameters of the probabilistic models are considered. By sampling over the epistemic random variable, a family of PDFs is generated and the failure probability is itself estimated as a random variable with its own PCE. Integrating epistemic uncertainties within the PCE framework results in a computationally efficient paradigm for propagation and sensitivity evaluation. Two typical illustrative examples are used to demonstrate the proposed approach.

Aleatory uncertainty↗
DOE OSTI2026

Solid state 59 Co NMR study of a Np(VII) compound

Np(VII) compounds with [Co(NH 3 ) 6 ] 3+ cations were synthesized and structurally examined using powder X-ray diffraction. Multiple phases were observed, consisting of octahedral [Co(NH 3 ) 6 ] 3+ cations, discrete tetragonal bipyramidal [NpO 4 (OH) 2 ] 3− anions, and waters of hydration. Electric field gradient tensors at Co sites were measured by solid state 59 Co nuclear magnetic resonance (NMR) spectroscopy and compared with theoretical calculations. The relative contributions of the chemical shift and electric field tensors to the NMR lineshape were determined by recording spectra at field strengths of 7.04 and 11.74 Tesla. Further, the evolution of structure and morphology as a function of sample age and the effects on NMR spectral parameters has also been investigated. These results demonstrate the use of NMR at multiple fields to expand understanding of the stability and electronic structure of high valent neptunium compounds.

heptavalent neptunium↗
DOE OSTI2025

Process intensification approach to enhancing heat and mass transfer: Radio frequency (RF) assisted drying of paper and board

Conventional multi-cylinder drying of paper and board typically relies on both conductive drying from steam-heated cylinders and convective drying, where heated air flows over the paper web surface. Conduction primarily contributes to heat transfer, while convection is the main driver of mass transfer. However, conventional drying systems are heavily dependent on steam, usually powered by fossil fuels, and are often energy-inefficient with high levels of waste. Additionally, these surface-driven processes result in a lower percentage of energy absorption compared to the energy supplied, leading to significant energy losses. To improve this long-standing process, an experimental system was developed to investigate a process intensification approach involving the integration of Radio Frequency (RF) heating, a volumetric electromagnetic technology, alongside traditional conduction and convection drying methods. This study also emphasizes the use of sensors to continuously monitor key parameters such as moisture content, supply system temperatures, sample temperatures, air flows, and drying rates in real-time. The effect of RF as an auxiliary energy source in localized environments at varying moisture levels was explored to optimize industrial drying systems, quantify potential improvements, and provide insights for future studies. Experimental results from trials combining RF with convection and with the base case alternating conduction-convection drying processes are presented. It is shown that RF is a viable process intensification approach for paper drying improving the drying rate and energy intensity at higher moisture contents. These findings offer valuable insights for process intensification and contribute to the process development, modeling, and simulation of advanced paper drying techniques.

42 ENGINEERING↗
DOE OSTI2022

Supported molybdenum oxides for the aldol condensation reaction of acetaldehyde

The (retro-)aldol condensation reaction is an important chemical transformation in the upgrading of biomass-derived compounds into fuels and valuable specialty chemicals. In this study, we found that supported molybdenum oxide (MoO x ) catalysts were active and selective for the aldol condensation of acetaldehyde to crotonaldehyde under steady-state reactor conditions. Through a combination of transmission electron microscopy (TEM), ultraviolet–visible (UV–VIS) diffuse reflectance spectroscopy, Fourier transform infrared (FTIR) spectroscopy of adsorbed pyridine, and steady-state reactor testing, we determined that highly dispersed MoO x has a strong interaction with a γ-Al 2 O 3 support resulting in optimal catalyst performance at low weight loadings. In contrast, MoO x particles supported on SiO 2 have a weaker interaction with the support, resulting in a monotonic relationship between Mo loading and aldol condensation activity. The Lewis acid site density and strength are important parameters for predicting aldol condensation activity across all samples. The concentration of weak acid sites had a poor correlation with aldol condensation activity, most likely because these sites are too weak to activate acetaldehyde for the reaction. Medium and strong acid sites both had good correlations to aldol condensation activity. Results from X-ray absorption near edge structure (XANES) and acetaldehyde temperature programmed desorption (TPD) indicated that partially reduced MoO x was more active for aldol condensation, but pretreatment in reducing or oxidizing environments had no significant effect on steady-state catalytic activity. Finally, characterization of spent catalyst samples through temperature programmed oxidation (TPO) and thermogravimetric analysis (TGA) revealed that catalysts with high densities of strong acid sites tended to form more carbonaceous deposits on the surface over the course of the reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Radiation-Induced Changes in Single Crystal Calcite and Dolomite: Mineral Analogues of Light Water Reactor, Nuclear Power Plant Concrete Aggregates

Two analogues of aggregates (calcite and dolomite) found in nuclear power plant (NPP) concrete have been neutron irradiated to fluences up to 2 × 10 20 n/cm 2 at 52 °C and 4 × 10 19 n/cm 2 at 95 °C (E > 0.1 MeV). X-ray diffraction studies showed that these aging conditions affected crystallography of both calcite and dolomite, with both showing a growth in their unit cells compared to that of the unirradiated samples. Only dolomite samples showed a continuous increase of its lattice parameters with the increase in irradiation. In calcites, the lattice growth with irradiation dissipated after a fluence of 5 × 10 18 n/cm 2 . Radiation-induced disordering of the crystal structure was observed in both materials, while a healing effect of irradiation temperature was mainly observed in calcites. Dislocation densities calculated by using XRD data also supported these observations. Insights made into the unit cells of both minerals by using Fourier synthesis showed that the Mg sites are more prone to the neutron irradiation than the Ca sites, resulting in larger radiation effects and higher disruption in the crystal structure of dolomite than that of calcite. Furthermore, other than the polycrystalline characteristics observed by using TEM, these minerals did not show complete amorphization or significant structural decomposition at the studied irradiation fluences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗