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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Sensitivity of Turbine-Height Wind Speeds to Parameters in Planetary Boundary-Layer and Surface-Layer Schemes in the Weather Research and Forecasting Model

We evaluate the sensitivity of simulated turbine-height winds to 26 parameters applied in a planetary boundary layer (PBL) scheme and a surface layer scheme of the Weather Research and Forecasting (WRF) model over an area of complex terrain during the Columbia Basin Wind Energy Study. An efficient sampling algorithm and a generalized linear model are used to explore the multiple-dimensional parameter space and quantify the parametric sensitivity of modeled turbine-height winds. The results indicate that most of the variability in the ensemble simulations is contributed by parameters related to the dissipation of the turbulence kinetic energy (TKE), Prandtl number, turbulence length scales, surface roughness, and the von Kármán constant. The relative contributions of individual parameters are found to be dependent on both the terrain slope and atmospheric stability. The parameter associated with the TKE dissipation rate is found to be the most important one, and a larger dissipation rate can produce larger hub-height winds. A larger Prandtl number results in weaker nighttime winds. Increasing surface roughness reduces the frequencies of both extremely weak and strong winds, implying a reduction in the variability of the wind speed. All of the above parameters can significantly affect the vertical profiles of wind speed, the altitude of the low-level jet and the magnitude of the wind shear strength. The wind direction is found to be modulated by the same subset of influential parameters. Remainder of abstract is in attachment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Towards an improved understanding of the influence of subpixel vegetation structure on pixel-level spectra: a simulation approach

The planned NASA Hyperspectral Infrared Imager (HyspIRI) mission, equipped with an imaging spectrometer that has the capability of monitoring ecosystems globally, will provide an unprecedented opportunity to address scientific challenges related to ecosystem function and change. However, uncertainty remains around the impact of subpixel vegetation structure, in combination with the point spread function, on pixel-level imaging spectroscopy data. We estimated structural parameters, e.g., leaf area index (LAI), canopy cover, and tree location, from HyspIRI spectral data, with the goal of assessing how subpixel variation in these parameters impact pixel-level imaging spectroscopy data. The fine-scale variability of real vegetation structure makes this a challenging endeavor. Therefore, we utilized a simulation-based approach to counter the time-consuming and often destructive sampling needs of vegetation structural analysis and to simultaneously generate synthetic HyspIRI data pre-launch. Three virtual scenes were constructed, corresponding to the actual vegetation structure in the National Ecological Observatory Network’s (NEON) Pacific Southwest Domain (Fresno, CA). These included an oak savanna, a dense coniferous forest, and a conifer-manzanita-mixed forest. Simulated spectroscopy data for these scenes were then generated using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. Simulations first were used to verify the physical model, virtual scene geometrical information, and simulation parameters. This was followed by simulations of HyspIRI data, where within-pixel structural variability was introduced, e.g., by iteratively changing per-pixel canopy cover and tree placement, tree clustering, leaf area index (LAI), etc., between simulation runs for the virtual scenes. Finally, narrow-band vegetation indices (VIs) were extracted from the data in an attempt to describe the variability of the subpixel structural parameters; this was done in order to assess VI robustness to changes in structural “levels”, as well as placement of trees/canopies within the instrument’s instantaneous field-of-view (IFOV). Our ultimate goal is not only to better understand how such subpixel variability influence imaging spectroscopy outputs, but also to better estimate vegetation structural parameters using spectra. We constructed regression models for LAI (R2 = 0.92) and canopy cover (R2 = 0.97) with narrow-band VIs via this simulation approach. Our models ultimately are intended to improve the HyspIRI mission’s ability to monitor global vegetation structure.

Van Aardt, Jan↗
DOE OSTI2012

Boulder damage symposium annual thin film laser damage competition

Optical instruments and laser systems are often fluence-limited by multilayer thin films deposited on the optical surfaces. When comparing publications within the laser damage literature, there can be confusing and conflicting laser damage results. This is due to differences in testing protocols between research groups studying very different applications. In this series of competitions, samples from multiple vendors are compared under identical testing parameters and a single testing service. Unlike a typical study where a hypothesis is tested within a well-controlled experiment with isolated variables, this competition isolates the laser damage testing variables so that trends can be observed between different deposition processes, coating materials, cleaning techniques, and multiple coating suppliers. The resulting series of damage competitions has also been designed to observe general trends of damage morphologies and mechanisms over a wide range of coating types (high reflector and antireflector), wavelengths (193 to 1064 nm), and pulse lengths (180 fs to 13 ns). A double blind test assured sample and submitter anonymity were used in each of the competitions so only a summary of the deposition process, coating materials, layer count and spectral results are presented. Laser resistance was strongly affected by substrate cleaning, coating deposition method, and coating material selection whereas layer count and spectral properties had minimal impact.

42 ENGINEERING↗
DOE OSTI2017

A Histogram-Free Multicanonical Monte Carlo Algorithm for the Basis Expansion of Density of States

We report a new multicanonical Monte Carlo (MC) algorithm to obtain the density of states (DOS) for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain an analytical form for the DOS expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical (MUCA) sampling and Wang-Landau (WL) sampling. This is enabled by storing the visited states directly in a data set and avoiding the explicit collection of a histogram. This practice also has the advantage of avoiding undesirable artificial errors caused by the discretization and binning of continuous state variables. Our results show that this scheme is capable of obtaining converged results with a much reduced number of Monte Carlo steps, leading to a significant speedup over existing algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

A histogram-free multicanonical Monte Carlo algorithm for the construction of analytical density of states

We report a new multicanonical Monte Carlo (MC) algorithm to obtain the density of states (DOS) for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain an analytical form for the DOS expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical (MUCA) sampling and Wang-Landau (WL) sampling. This is enabled by storing the visited states directly in a data set and avoiding the explicit collection of a histogram. This practice also has the advantage of avoiding undesirable artificial errors caused by the discretization and binning of continuous state variables. Our results show that this scheme is capable of obtaining converged results with a much reduced number of Monte Carlo steps, leading to a significant speedup over existing algorithms.

Li, Ying Wai↗
DOE OSTI2018

Intraday Water Quality Patterns in East Fork Poplar Creek with an Emphasis on Mercury and Monomethylmercury

We conducted a diel sampling campaign at three locations along the Hg contaminated East Fork Poplar Creek (EFPC) in Oak Ridge, Tennessee to (i) quantify diel patterns of particulate and dissolved mercury (Hg) and monomethylmercury (MMHg) (Hg D , Hg P , MMHg D , and MMHg P , respectively) and associated water quality parameters along a longitudinal gradient of EFPC during the summer season, (ii) determine if diel patterns in Hg and/or MMHg are related to the daily photocycle or any other short term cycle, such as wastewater treatment plant discharge, (iii) determine if diel variability in turbidity and dissolved organic matter (DOM) composition correspond to particulate Hg P or MMHg P and dissolved organic carbon (DOC) or dissolved Hg D or MMHg D . Samples were collected every two hours for a 30 hour period. The farthest upstream site was located at the boundary of Y-12 and the City of Oak Ridge (EFK 23.4) while two additional sites were located 7.2 kilometers (Wiltshire Drive, EFK 16.2) and 18 kilometers (Horizon Center, EFK 5.4) downstream of EFK 23.4). Hg P and MMHg P concentrations increased overnight at EFK 16.2 and EFK 5.4 coincident with increases in turbidity and total suspended solids (TSS). These overnight increases were likely due to diel changes in the activity of macrobiota (re)suspending contaminated sediments in the creek. Both Hg D and MMHg D were higher during the day at EFK 23.4 and EFK 5.4. The underlying causes for the patterns in Hg D and MMHg D are less clear but correspond with similar patterns in DOC concentration and DOM composition. Photochemical reactions may also play a role in these Hg D , MMHg D , DOC, and DOM patterns. Total loads of both Hg and MMHg increased with downstream distance. The greatest increase in loading occurred in the reach from EFK 23.4 to EFK 16.2 which encompasses areas where the Historic Release Deposits (HRD) have been identified. These results demonstrate that diffuse legacy sources of Hg, outside of Y-12, contribute Hg load to EFPC. Both total and dissolved MMHg loads increased approximately linearly with downstream distance. Particluate MMHg loading increased in the upper reach but did not change over the lower reach. The HRD may contribute to MMHg P load in the upper reach but most of the total, dissolved, and particulate MMHg appears to originate from in-stream production. Due to intraday patterns in concentration and flow rate, loading estimates are best derived from diel sampling campaigns. Intraday patterns in Hg and MMHg concentration and speciation have implications with respect to biotic exposure. Greater biotic activity and feeding during times of higher concentration would correspond to greater exposure than estimated from daily or longer-term averages. Both Hg and MMHg responded rapidly to processes governing their concentration. This latter point is encouraging from the perspective of site remediation as it suggests that MMHg concentrations and flux in EFPC would respond rapidly to appropriate remedial actions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Adaptive stratified importance sampling: hybridization of extrapolation and importance sampling Monte Carlo methods for estimation of wind turbine extreme loads

Wind turbine extreme load estimation is especially difficult because turbulent inflow drives nonlinear turbine physics and control strategies; thus there can be huge differences in turbine response to essentially equivalent environmental conditions. The two main current approaches, extrapolation and Monte Carlo sampling, are both unsatisfying: extrapolation-based methods are dangerous because by definition they make predictions outside the range of available data, but Monte Carlo methods converge too slowly to routinely reach the desired 50-year return period estimates. Thus a search for a better method is warranted. We introduce an adaptive stratified importance sampling approach that allows for treating the choice of environmental conditions at which to run simulations as a stochastic optimization problem that minimizes the variance of unbiased estimates of extreme loads. Furthermore, the framework, built on the traditional bin-based approach used in extrapolation methods, provides a close connection between sampling and extrapolation, and thus allows the solution of the stochastic optimization (i.e., the optimal distribution of simulations in different wind speed bins) to guide and recalibrate the extrapolation. Results show that indeed this is a promising approach, as the variance of both the Monte Carlo and extrapolation estimates are reduced quickly by the adaptive procedure. We conclude, however, that due to the extreme response variability in turbine loads to the same environmental conditions, our method and any similar method quickly reaches its fundamental limits, and that therefore our efforts going forward are best spent elucidating the underlying causes of the response variability.

17 WIND ENERGY↗
DOE OSTI2024

Microbial Community Changes across Time and Space in a Constructed Wetland

Constructed wetlands are artificial ecosystems designed to replicate natural wetland processes. Microbial communities play a pivotal role in cycling essential elements, particularly sulfur, which is crucial for trace metal fixation and remobilization in these ecosystems. By their response to their environment, microbial communities act as biological indicators of the wetland performance. To address knowledge gaps pertinent to the changes in trace metal bioavailability in relation to microbial activities in the H-02 constructed wetland, we performed this study to investigate temporal and spatial variations in microbial communities by using molecular biology tools. Quantitative polymerase chain reaction and next generation sequencing techniques were employed to analyze archaeal and bacterial groups associated with sulfur and methane cycling. Alpha diversity indices were used to assess species richness, evenness, and dominance. Results indicated high gene abundance of Desulfuromonas (5.37 × 10 6 g.cell –1 ), methane oxidizing bacteria (6.92 × 10 6 g.cell –1 ), and methanogenic microorganisms (3.02 × 10 5 g.cell –1 ) during cool months. Warm months were marked by sulfate reducing bacteria dominance (3.31 × 10 6 g.cell –1 ), potentially due to competitive interactions and environmental conditions, higher temperatures, and lower redox potential. Spatial variability among microbial groups was insignificant, but trends in gene abundance indicated complex factors influencing these groups. Next generation sequencing data demonstrated Firmicutes as the most abundant phylum with over 50% regardless of the season or sampling location. Cool months exhibited higher alpha diversity than warm months. Overall, this study showed that seasonal changes significantly impacted the microbial communities in the H-02 constructed wetland that are associated with the sulfur cycle and eventually trace metal biogeochemistry, revealing two distinct mechanisms of the sulfur cycle between the two main seasons, whereas spatial variability effects were not conclusive.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Search for new physics in the multijet and missing transverse momentum final state in proton-proton collisions at $\sqrt{s}$= 8 TeV

A search for new physics is performed in multijet events with large missing transverse momentum produced in proton-proton collisions at $\sqrt{s}$ = 8 TeV using a data sample corresponding to an integrated luminosity of 19.5 fb⁻¹collected with the CMS detector at the LHC. The data sample is divided into three jet multiplicity categories (3-5, 6-7, and ≥8 jets), and studied further in bins of two variables: the scalar sum of jet transverse momenta and the missing transverse momentum. The observed numbers of events in various categories are consistent with backgrounds expected from standard model processes. Exclusion limits are presented for several simplified supersymmetric models of squark or gluino pair production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Inclusive and differential cross-sections for dilepton $t\overline{t}$ production measured in $\sqrt{s}$ = 13 TeV pp collisions with the ATLAS detector

Differential and double-differential distributions of kinematic variables of leptons from decays of top-quark pairs ($t\bar{t}$) are measured using the full LHC Run 2 data sample collected with the ATLAS detector. The data were collected at a pp collision energy of $\sqrt{s}$ = 13 TeV and correspond to an integrated luminosity of 140 fb –1 . The measurements use events containing an oppositely charged e μ pair and b-tagged jets. The results are compared with predictions from several Monte Carlo generators. While no prediction is found to be consistent with all distributions, a better agreement with measurements of the lepton p T distributions is obtained by reweighting the $t\bar{t}$ sample so as to reproduce the top-quark p T distribution from an NNLO calculation. The inclusive top-quark pair production cross-section is measured as well, both in a fiducial region and in the full phase-space. The total inclusive cross-section is found to be $σ_{t\bar{t}}=$ 829 ± 1 (stat) ± 13 (syst) ± 8 (lumi) ± 2 (beam) pb, where the uncertainties are due to statistics, systematic effects, the integrated luminosity and the beam energy. This is in excellent agreement with the theoretical expectation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

A systematic approach to resolve high impedance of multifunctional energy storage composites

Previous work has proposed and characterized the structural and electrical performance of Multifunctional Energy Storage Composite (MESC) structures: structural elements with embedded lithium-ion batteries which were developed by the Structures and Composite Laboratory (SACL) at Stanford University. This work conducts a comprehensive parametric study over the design variables in the manufacturing process to determine the root cause of increased DC impedance compared to commercial pouch cell batteries. Several MESC samples were assembled under various controlled environmental temperatures and pressures. The samples underwent Hybrid Peak Pulse Characterization (HPPC) to approximate the DC impedance as a function of state of charge (SOC). Failure limits of the battery with respect to assembly temperature and pressure were tested, and an MESC manufacturing simulation model was constructed in Abaqus to validate the manufacturing limits. Samples assembled without enough temperature or pressure failed due to a lack of structural integrity or hermetic seal. Conversely, samples which underwent elevated temperatures and pressures resulted in high DC impedance due to nonuniform electrolyte wetting. This work resolves the primary concern of MESC by achieving comparable DC impedance to commercial pouch cells of the same chemistry and testing procedure.

25 ENERGY STORAGE↗
DOE OSTI2025

Contributions of major tau kinase activation and phospho-tau accumulation to cortical and hippocampal tangle formation and cognition in older adults

Aberrant activation of tau kinases (tauK) has been proposed as a major step in tau hyperphosphorylation and misfolding, and subsequent formation of neurofibrillary tangles (NFT) in Alzheimer's disease (AD). However, evidence of tauK hyperactivation in actual AD brains is scarce and inconsistent, and their role in age-related cognitive decline remains undocumented. We evaluated activated/inhibited species of CDK5/p35/p25, GSK3a/ß, and ERK1/2 as well as ten tau/phospho-tau (ptau) peptides (mapping Ser 202 , Thr 217 , Ser 262 , Ser 305 , and Ser 404 phospho-residues) by Western blot or selected reaction monitoring proteomics, respectively, in postmortem dorsolateral prefrontal cortex (DLPFC) and hippocampal samples of 150 participants from the Rush Memory and Aging Project (MAP). Regression models and mediation analyses assessed the contributions of these variables to tau phosphorylation, NFT deposition and antemortem cognitive status of MAP participants. Surprisingly, greater p25 and p35 (indices for CDK5 activation) and lower pSer 21/9 -GSK3a/ß (inhibited species) immunodensities were associated with lower ptau peptide amounts. Individuals with higher p25 cortical densities displayed better cognitive outcomes, particularly working memory. Statistical mediation analyses indicated that the beneficial effect of CDK5/p25 on cognition was mediated by lower densities of phospho-Thr 217 -tau and NFT deposition in DLPFC, and also identified Thr 217 and Ser 262 as the ptau sites with greatest influence in both NFT accumulation and cognitive impairment. The present data suggest that tau hyperphosphorylation, tangle deposition, and the subsequent cognitive impairment do not rely on aberrant activation of major tauKs. Additionally, novel evidence was provided for the beneficial contribution of cortical CDK5/p25 to the maintenance of working memory.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Multimodal Nanoscale Mapping of Local Structure and CO 2 Adsorption in Metal–Organic Frameworks

Diamine functionalization of the metal−organic framework Mg 2 (dobpdc) (dobpdc 4− = 4,4′-dioxidobiphenyl-3,3′-dicarboxylate) significantly enhances its selectivity for CO 2 capture from flue gases and air. The structure and CO 2 capacity of such materials are typically assessed using bulk techniques that rely on averaging signal over large ensembles of unit cells, obscuring local heterogeneities, such as variations in CO 2 occupancy across individual nanocrystals. To resolve this limitation, we demonstrate a multimodal, nanoscale characterization of Mg 2 (dobpdc) appended with 1,3-diaminopropane. By employing recently developed characterization techniques at progressively smaller length scales, we uncover insights from correspondingly smaller populations of unit cells. First, we use parallel-beam 3D electron diffraction (3D ED) to identify a prominent expansion in lattice parameters upon desorption of CO 2 , as observed at the level of single nanocrystals. Second, we use convergent-probe 4D scanning transmission electron microscopy (4D-STEM) to quantify associated differences in lattice strain as a function of gas loading and diamine appending. These measurements sample small subvolumes within individual nanocrystals. Finally, we apply infrared scattering scanning near-field optical microscopy (IR s- SNOM) to confirm variable CO 2 chemisorption across adsorption sites at the surface of single nanocrystals. This multimodal, multiscale approach allows us to map heterogeneity within individual nanocrystals. Collectively, these findings emphasize the importance of local, nanoscale characterization of metal−organic frameworks in revealing previously unresolvable features that impact their performance.

Karstens, Sarah L. [University of California, Berk↗
DOE OSTI2026

Haze processing of atmospheric particles during wintertime in the Indo-Gangetic Plains

The impacts of haze on visibility, air quality, and climate are not well quantified due to a lack of understanding of the evolution of the mixing state and phase state of atmospheric particles during haze processing. The variability of the mixing state of atmospheric particles contributes significantly to uncertainties associated with the estimated aerosol radiative forcing. We collected particle samples in January 2018 from the highly polluted Indo-Gangetic plain during hazy conditions to study haze-processed particles. Single particle analysis using multi-modal micro-spectroscopy techniques revealed an abundance (40–70% by number) of potassium-rich sulfate particles from biomass-burning influenced smoke. Tilted view imaging showed that most of the organic particles that had inorganic potassium and sulfate inclusions were liquid-like while those without inclusions were more semi-solid. High-resolution mass spectrometry analysis revealed a significant presence of organosulfates and nitroxy-organosulfates in the morning samples (24%) compared to the afternoon samples (9%), despite higher relative humidity in the afternoon. Overall, our results highlight the significant contribution of both organic and inorganic sulfate to the total particulate sulfur budget during haze processing in winter, when anthropogenic emissions such as household burning, agricultural burning, and vehicular emissions are major contributors to particle mass.

Mathai, Susan [Pacific Northwest National Laborato↗
DOE OSTI2012

A novel apparatus for in situ compression of submicron structures and particles in a high resolution SEM

We report on the development and characterization of a novel in situ manipulation device to perform stressing experiments on the submicron scale inside a high resolution field emission scanning electron microscope. The instrument comprises two main assembly groups: an upper part for positioning and moving a mounted probe and a force sensor as well as a specimen support as lower part. The upper part consists of a closed loop tripod piezoelectric scanner mounted on a self-locking coarse positioning stage. Two interlocked steel springs and a linear variable differential transformer measuring the springs' deflections compose the lower part of the instrument. This arrangement acts as force-sensor and sample support. In comparison to already well-established concepts a wide measuring range is covered by adjusting the spring constant between 30 N/m and 50000 N/m. Moreover, the new device offers striking advantages with respect to force calibration and sample deformation measurements. Force calibration is performed using the eigenfrequency of the force detection system directly inside the SEM. Deformation data are obtained with high accuracy by simultaneously recording displacements above and below the specimen. The detrimental apparatus compliance is determined, and the influence on measured data subsequently minimized: an easy to validate two-springs-in-series model is used for data correction. A force resolution in normal direction of 100 nN accompanied by a sample deformation resolution of 5 nm can be achieved with the instrument using an appropriate load cell stiffness. The capabilities and versatility of this instrument are exemplified by compression experiments performed on submicron amorphous silica particles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Preparation of metallic nanoparticles by irradiation in starch aqueous solution

Colloidal silver nanoparticles (AgNPs) were synthesized in a single step by electron beam irradiation reduction of silver ions in aqueous solution containing starch. The nanoparticles were characterized by spectrophotocolorimetry and compared with those obtained by chemical (thermal) reduction method. The results showed that the smaller sizes of AgNPs were prepared with higher yields as the irradiation dose increased. The broadening of particle size distribution occurred by increasing of irradiation dose and dose rate. Chromatic parameters such as b* (yellow-blue coordinate), C* (chroma) and ΔE{sub ab} (total color difference) could characterize the nanoparticles with respect of their concentration. Hue angle h{sup o} was correlated to the particle size distribution. Experimental data of the irradiated samples were also subjected to factor analysis using principal component extraction and varimax rotation in order to reveal the relation between dependent variables and independent variables and to reduce their number. The radiation-based method provided silver nanoparticles with higher concentration and narrower size distribution than those produced by chemical reduction method. Therefore, the electron beam irradiation is effective for preparation of silver nanoparticles using starch aqueous solution as dispersion medium.

77 NANOSCIENCE AND NANOTECHNOLOGY↗