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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Urbanization drives convergence in soil profile texture and carbon content

Urban development has driven extensive modification of the global landscape. This shift in land use and land cover alters ecological functioning, and thereby affects sustainable management agendas. Urbanization fundamentally reshapes the soils that underlay landscapes, and throughout the soil profile, extends impacts of urbanization far below the landscape surface. The impacts of urbanization on deeper soils that are beyond the reach of regular land management are largely unknown, and validation of general theories of convergent ecosystem properties are thwarted by a dearth of both level of measurement effort and the substantial heterogeneity in soils and urban landscapes. Here, we examined two soil properties with strong links to ecological functioning—carbon and mineral-fraction particle size—measured in urban soils, and compared them to their pre-urbanization conditions across a continental gradient encompassing global soil diversity. We hypothesized that urbanization drove convergence of soils properties from heterogeneous pre-urban conditions towards homogeneous urban conditions. Based on our observations, we confirm the hypothesis. Both soil carbon and particle size converged toward an intermediate value in the full data distribution, from pre-urban to urban conditions. These outcomes in urban soils were observed to uniformly be fine textured soils with overall lower carbon content. Although these properties are desirable for supporting urban infrastructure (e.g. buildings, pipes), they constrain the potential to render ecosystem services. Since soil profile texture and carbon content were convergent and observed across 11 cities, we suggest that these property profiles can be used as a universal urban soil profile to: 1) provide a clear prediction for how urbanization will shift soil properties from pre-urban conditions, 2) facilitate the adoption of commonly-accepted soil profiles for process models, and 3) offer a reference point to test against urban management strategies and how they impact soil resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

efam: an e xpanded, metaproteome-supported HMM profile database of viral protein fam ilies

Viruses infect, reprogram and kill microbes, leading to profound ecosystem consequences, from elemental cycling in oceans and soils to microbiome-modulated diseases in plants and animals. Although metagenomic datasets are increasingly available, identifying viruses in them is challenging due to poor representation and annotation of viral sequences in databases. Here, we establish efam, an expanded collection of Hidden Markov Model (HMM) profiles that represent viral protein families conservatively identified from the Global Ocean Virome 2.0 dataset. This resulted in 240 311 HMM profiles, each with at least 2 protein sequences, making efam >7-fold larger than the next largest, pan-ecosystem viral HMM profile database. Adjusting the criteria for viral contig confidence from ‘conservative’ to ‘eXtremely Conservative’ resulted in 37 841 HMM profiles in our efam-XC database. To assess the value of this resource, we integrated efam-XC into VirSorter viral discovery software to discover viruses from less-studied, ecologically distinct oxygen minimum zone (OMZ) marine habitats. This expanded database led to an increase in viruses recovered from every tested OMZ virome by ~24% on average (up to ~42%) and especially improved the recovery of often-missed shorter contigs (<5 kb). Additionally, to help elucidate lesser-known viral protein functions, we annotated the profiles using multiple databases from the DRAM pipeline and virion-associated metaproteomic data, which doubled the number of annotations obtainable by standard, single-database annotation approaches. Together, these marine resources (efam and efam-XC) are provided as searchable, compressed HMM databases that will be updated bi-annually to help maximize viral sequence discovery and study from any ecosystem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The mass profiles of dwarf galaxies from Dark Energy Survey lensing

We present a novel approach to extracting dwarf galaxies from photometric data to measure their average halo mass profile with weak lensing. We characterize their stellar mass and redshift distributions with a spectroscopic calibration sample. By combining the ${\sim} 5000\,\mathrm{deg}^2$ multiband photometry from the Dark Energy Survey and redshifts from the Satellites Around Galactic Analogs Survey with an unsupervised machine learning method, we select a low-mass galaxy sample spanning redshifts $z\lt 0.3$ and divide it into three mass bins. From low to high median mass, the bins contain [146 420, 330 146, 275 028] galaxies and have median stellar masses of $\log _{10}(M_*/\text{M}_\odot)=\left[8.52\substack{+0.57 -0.76},\, 9.02\substack{+0.50 -0.64},\, 9.49\substack{+0.50 -0.58}\right]$ . We measure the stacked excess surface mass density profiles, $\Delta \Sigma (R)$, of these galaxies using galaxy–galaxy lensing with a signal-to-noise ratio of [14, 23, 28]. Through a simulation-based forward-modelling approach, we fit the measurements to constrain the stellar-to-halo mass relation and find the median halo mass of these samples to be $\log _{10}(M_{\rm halo}/\text{M}_\odot)$ = [$10.67\substack{+0.2 -0.4}$, $11.01\substack{+0.14 -0.27}$, $11.40\substack{+0.08 -0.15}$]. The cold dark matter profiles are consistent with NFW (Navarro, Frenk, and White) profiles over scales ${\lesssim} 0.15 \, {h}^{-1}$ Mpc. We find that ${\sim} 20$ per cent of the dwarf galaxy sample are satellites. This is the first measurement of the halo profiles and masses of such a comprehensive, low-mass galaxy sample. The techniques presented here pave the way for extracting and analysing even lower mass dwarf galaxies and for more finely splitting galaxies by their properties with future photometric and spectroscopic survey data.

dark matter↗
DOE OSTI2024

Project Dinos I: A joint lensing–dynamics constraint on the deviation from the power law in the mass profile of massive ellipticals

The mass distribution in massive elliptical galaxies encodes their evolutionary history, thus providing an avenue to constrain the baryonic astrophysics in their evolution. The power-law assumption for the radial mass profile in ellipticals has been sufficient to describe several observables to the noise level, including strong lensing and stellar dynamics. In this paper, we quantitatively constrained any deviation, or the lack thereof, from the power-law mass profile in massive ellipticals through joint lensing–dynamics analysis of a large statistical sample with 77 galaxy–galaxy lens systems. We performed an improved and uniform lens modelling of these systems from archival Hubble Space Telescope imaging using the automated lens modelling pipeline dolphin. We combined the lens model posteriors with the stellar dynamics to constrain the deviation from the power law after accounting for the line-of-sight lensing effects, a first for analyses on galaxy–galaxy lenses. We find that the Sloan Lens ACS Survey lens galaxies with a mean redshift of 0.2 are consistent with the power-law profile within 1.1σ (2.8σ) and the Strong Lensing Legacy Survey lens galaxies with a mean redshift of 0.6 are consistent within 0.8σ (2.1σ), for a spatially constant (Osipkov–Merritt) stellar anisotropy profile. We adopted the spatially constant anisotropy profile as our baseline choice based on previous dynamical observables of local ellipticals. However, spatially resolved stellar kinematics of lens galaxies are necessary to differentiate between the two anisotropy models. Future studies will use our lens models to constrain the mass distribution individually in the dark matter and baryonic components.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Using strong lensing to detect subhaloes with steep inner density profiles

ABSTRACT The inner region of a subhalo’s density distribution is particularly sensitive to dark matter microphysics, with alternative dark matter models leading to both cored and steeply-rising inner density profiles. This work investigates how the lensing signature and detectability of dark matter subhaloes in mock HST-, Euclid-, and JWST-like strong lensing observations depend on the subhalo’s radial density profile, especially with regards to the inner power-law slope, $\beta$. We demonstrate that the minimum subhalo mass detectable along the Einstein ring of a system is strongly dependent on $\beta$. In particular, we show that subhaloes with $\beta = 2.2$ can be detected down to masses over an order-of-magnitude lower than their Navarro–Frenk–White (NFW) counterparts with $\beta = 1$. Importantly, we find that the detectability of subhaloes with steep inner profiles is minimally affected by increasing the complexity of the main lens galaxy’s mass model. This is a notable characteristic of these subhaloes, as those with NFW or shallower profiles become essentially undetectable when multipole perturbations are added to the lens model. The results of this work highlight how the underlying dark matter physics can significantly impact the expected number of subhalo detections from strong gravitational lensing observations. This is important for testing Cold Dark Matter against alternative models, such as Self-Interacting Dark Matter, that predict a diverse range of subhalo inner density profiles.

dark matter↗
DOE OSTI2021

Shock compression of silver to 300 GPa: Wave profile measurements and melting transition

Recent in-situ x-ray diffraction (XRD) measurements on laser-shock compressed Ag foils demonstrated a face-centered-cubic to body-centered-cubic transformation at ~150 GPa and melting between 172 and 197 GPa [Phys. Rev. Lett. 124, 235701 (2020)]. As a complement to the XRD work, we conducted plate impact experiments to obtain shock velocity and wave profile measurements on thicker Ag samples shock-compressed to peak stresses between 30 and 300 GPa. The shock velocity–particle velocity results were fitted very well by a linear relation over the entire stress range, providing an accurate determination of the Ag Hugoniot (locus of the stress-volume states achieved under shock compression). For peak stresses below 187 GPa and above 210 GPa—corresponding to the solid and liquid phases, respectively—the wave profiles show clean single waves. No wave profile features related to the fcc-bcc transformation at ~150 GPa were observed, implying minimal volume change for the transformation. For stresses between 187 and 210 GPa, an initial jump was followed by a time-dependent increase in the particle velocity (20–80 ns risetime) to the peak state—corresponding to the solid-liquid mixed phase response. Unlike the solid and liquid response, the mixed-phase response cannot be readily analyzed analytically. Instead, numerical simulations incorporating an accurate multiphase equation of state for Ag—not currently available—are required to analyze the wave profiles measured at 187–210 GPa stresses. Furthermore, the present work shows the potential for using wave profile measurements to examine the melting transition under shock compression.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Strong gravity extruding peaks in speed of sound profiles of massive neutron stars

The speed of sound squared (SSS) s 2 in massive neutron stars (NSs) characterizes not only the stiffness of supradense neutron-rich matter within but also equivalently properties of the curved geometry due to the strong-field gravity and matter-geometry coupling. A peaked density or radius profile of s 2 has been predicted for massive NSs using various NS equation of state (EOS) models. However, the nature, cause, location and size of the peak in s 2 profiles are still very EOS model dependent. In this work, we investigate systematically s 2 profiles in massive NSs in a new approach that is independent of the nuclear EOS model and without any presumption about the NS structure and/or composition. In terms of the small quantities (reduced radius, the energy density and pressure scaled by their central values), we perform double-element perturbative expansions in solving perturbatively the scaled Tolman-Oppenheimer-Volkoff (TOV) equations and analyzing s 2 profiles from the Newtonian limit to the general relativistic (GR) case. The GR term in the TOV equations plays a twofold role: it compresses NS matter and modifies the pressure/energy density ratio from small values in Newtonian stars showing no s 2 peak to large ones for massive NSs possessing a peak in their s 2 profiles, and eventually takes away the peak in extremely compact/massive NSs approaching the causality limit. In particular, the peaked behavior in s 2 is expected to emerge near the center of massive NSs like PSR J⁢0740+6620, while a sharp phase transition is unlikely to occur there. Furthermore, these features revealed from our analyses are universal as they are intrinsic properties of the GR stellar structure equations independent of the still very uncertain EOS of supradense neutron-rich matter in NSs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Self-consistent, high-order spatial profiles in a model for two-fluid turbulent mixing

A Reynolds-averaged Navier-Stokes model is presented with the property that it admits self-consistent, high-order spatial profiles in simulations of two-fluid turbulent mixing layers. Whereas previous models have been limited by the assumption of a linear mixing profile, the present paper relaxes this assumption and, as a result, is shown to achieve much better agreement with experimental profiles. Similarity analysis is presented to derive constraints on model coefficients to enforce desired self-similar growth rates that are fully consistent with the high-order spatial profiles. Through this similarity analysis, it is shown that care must be taken in model construction, as it is possible to construct certain terms in such a way as to leave growth rates unconstrained. This model, termed the k-Φ-L-a-V model, is then applied in simulations of Rayleigh-Taylor, Richtmyer-Meshkov, and Kelvin-Helmholtz mixing layers. Overall, these simulations confirm that the expected growth parameters are recovered and high-order spatial profiles are maintained.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Logarithmic profile of temperature in sheared and unstably stratified atmospheric boundary layers

The impact of buoyancy on the mean velocity, temperature, and scalar concentration profiles in the lower atmosphere is typically investigated within the framework of Monin-Obukhov similarity theory (MOST). MOST is the theoretical foundation for parametrizing surface-atmosphere exchanges in nearly all weather, climate, and hydrological models.According to MOST, the classic logarithmic profiles of mean velocity and temperature break down as the buoyancy effects become important. However, recent studies on turbulent Rayleigh-Bénard convection and natural convection along vertical walls suggest that the mean temperature in the near-surface region still follows a logarithmic profile.Motivated by these new results, we study the mean potential temperature profile in sheared and unstably stratified atmospheric boundary layers using direct numerical simulations and field observations. We find that the mean potential temperature profile remains logarithmic across a wide range of stability parameters, which characterizes the relative importance of buoyancy versus shear effects. Compared to MOST, our results suggest that the buoyancy force does not modify the logarithmic nature of the mean potential temperature profile, but instead modulates its slope, which is no longer universal and differs from 1/κ,whereκisthe von Kármán constant. Furthermore, this study provides another perspective on scalar turbulence in the atmospheric boundary layer

58 GEOSCIENCES↗
DOE OSTI2017

Main-ion intrinsic toroidal rotation profile driven by residual stress torque from ion temperature gradient turbulence in the DIII-D tokamak

Intrinsic toroidal rotation of the deuterium main ions in the core of the DIII-D tokamak is observed to transition from flat to hollow, forming an off-axis peak, above a threshold level of direct electron heating. Nonlinear gyrokinetic simulations show that the residual stress associated with electrostatic ion temperature gradient turbulence possesses the correct radial location and stress structure to cause the observed hollow rotation profile. Residual stress momentum flux in the gyrokinetic simulations is balanced by turbulent momentum diffusion, with negligible contributions from turbulent pinch. Finally, the prediction of the velocity profile by integrating the momentum balance equation produces a rotation profile that qualitatively and quantitatively agrees with the measured main-ion profile, demonstrating that fluctuation-induced residual stress can drive the observed intrinsic velocity profile.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Semi-Supervised Disaggregation of Load Profiles at Transmission Buses with Significant Behind-the-Meter Solar Generations

It is of imperative interests for regional transmission organizations (RTOs) to effectively extract daily load profiles at transmission buses, which remains a gap in existing technology paradigm. This digest proposes an explicit yet efficient linear estimator, to disaggregate metered load profiles at buses with significant behind-the-meter (BTM) solar generations in a data driven manner. The proposed estimator is based on utility zonal load profiles and proxy solar irradiance profiles, which in reality is the aggregated waveform at each transmission bus and equivalent to the mix of summed load profiles minus actual BTM solar generation. To overcome technical challenges in the lack of “ground truth” and validate the performance of supervised learning algorithms, we propose semi-supervised mechanisms with parameter tuning, and leverage the unique characteristics of zero-crossing points in BTM solar peaking behaviors.

machine leaning, behind-the-meter, power grid anal↗
DOE OSTI2024

Power Profile Monitoring and Tracking Evolution of System-Wide HPC Workloads

The power & energy demands of HPC machines have grown significantly. Modern exascale HPC systems require tens of megawatts of combined power for computing resources and cooling facilities at full capacity. The current energy trend is not sustainable for future HPC systems, and there is a need to work toward the energy efficiency aspect of HPC performance. Energy awareness of the HPC applications at the job level is essential for running an efficient HPC system. This work aims to develop a pipeline to provide a production-level system-wide overview of the HPC workloads' power profile while handling evolving workloads exhibiting new power trends. We developed an open-set classification model for HPC jobs based on the properties of power profiles to continuously provide a system-wide holistic view of recently completed jobs. The pipeline helps continuously monitor the job-level power usage pattern of HPC and enables us to capture the new trends in applications' power behavior. We employed a comprehensive set of techniques to generate job-level data, custom-designed feature extraction methods to extract critical features from jobs' power profiles, clustering techniques powered by generative modeling, and open-set classification for identifying job profiles into known classes or an unknown set. With extensive evaluations, we demonstrate the effectiveness of each component in our pipeline. We provide an analysis of the resulting clusters that characterize the power profile landscape of the Summit supercomputer from more than 60K jobs executed in a year. The open-set classification classifies the known data sets into known classes with high accuracy and identifies unknown data noints with over 85% accuracy.

Karimi, Ahmad Maroof↗
DOE OSTI2020

Understanding Measurement Artifacts Causing Inherent Cation Gradients in Depth Profiles of Perovskite Photovoltaics with TOF-SIMS

Time-of-flight secondary-ion mass spectrometry (TOF-SIMS) is one of the few techniques that can obtain chemical information from the hybrid organic-inorganic perovskite solar cells (PSCs) in one dimension (standard depth profiling), two dimensions (high-resolution 100-nm imaging), as well as three dimensions (tomography combining high-resolution imaging with depth profiling). We have very recently developed thermo-mechanical methods to cleave perovskite samples at the back transparent conducting oxide/PSC interface. This allowed for depth-profiling from the back of the device to the front. The resultant profiles answered the lingering question of the apparent A-site cation gradient typically seen in TOF-SIMS depth profiles. In fact, this gradient is a measurement artifact due to beam damage that the community should be informed of as TOF-SIMS data become more commonly employed. Methods of mitigating this artifact by altering the measurement conditions are also presented.

14 SOLAR ENERGY↗
DOE OSTI2025

Deep Factorization Machine Learning for Disaggregation of Transmission Load Profiles with High Penetration of Behind-The-Meter Solar

The ever-growing integration of distributed energy resources (DERs), especially behind-the-meter (BTM) solar generations, poses imperative operational challenges to system operators such as regional transmission organizations (RTOs). It is important for RTOs to effectively and accurately extract actual load profiles at the transmission level for a single node with significant BTM solar injection. This paper first illustrates the necessity of disaggregating the daily actual load profile of a single node. Furthermore, by segmenting nodes with selected timeseries features, nodes with significant BTM solar generation are identified. Lastly, a bi-level framework is proposed, comprising reference node disaggregation and DeepFM nodal disaggregation, aimed at disaggregating the nodal load profiles from which system operators require more information. By adopting a hybrid Deep Factorization Machine (DeepFM) model, the model achieve accurate results by extracting both linear and nonlinear relations between nodes in the same region and the zonal load and nodal load profile. To overcome the lack of ground truth, this paper segments the load profile into daytime, nighttime, and zero-crossing points and utilizes the latter two for evaluation purposes. The proposed disaggregation procedure is validated using real world, minute-level, normalized, and anonymized nodal data in the PJM service territory.

42 ENGINEERING↗
DOE OSTI2015

Technical Note: Measurement of bow tie profiles in CT scanners using radiochromic film

Purpose: To provide a noninvasive technique to measure the intensity profile of the fan beam in a computed tomography (CT) scanner that is cost effective and easily implemented without the need to access proprietary scanner information or service modes. Methods: The fabrication of an inexpensive aperture is described, which is used to expose radiochromic film in a rotating CT gantry. A series of exposures is made, each of which is digitized on a personal computer document scanner, and the resulting data set is analyzed to produce a self-consistent calibration of relative radiation exposure. The bow tie profiles were analyzed to determine the precision of the process and were compared to two other measurement techniques, direct measurements from CT gantry detectors and a dynamic dosimeter. Results: The radiochromic film method presented here can measure radiation exposures with a precision of ∼6% root-mean-square relative error. The intensity profiles have a maximum 25% root-mean-square relative error compared with existing techniques. Conclusions: The proposed radiochromic film method for measuring bow tie profiles is an inexpensive (∼$100 USD + film costs), noninvasive method to measure the fan beam intensity profile in CT scanners.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-TeP1-10: Predicting Photon Percentage Depth Dose From Profile Due to Changes in Beam Quality

Purpose: To predict photon percentage depth dose (PDD) from profile due to a change in flattened (FF) and flattening-filter-free (FFF) beam quality. Methods: 6MV photon beam PDDs and profiles in a 3D water tank (3DW) and profiles in an ionization chamber array (ICP) were collected for different field sizes and depths with FF and FFF beams in a Versa HD (Elekta Ltd.). The energy was adjusted by changing the bending magnet current (BMC) ±15% from the clinical beam (6MV) in 5% increments. For baseline establishment, PDDs(depth≥3cm) were parameterized with bi-exponential functions and the PDD 20 to 10cm ratios (PDD{sub 20,10}) were calculated. Then, the FF profile at 10cm from the central axis (Pr{sub 10}) and the slope of the FFF central linear region (SFFF) were calculated. Calibration curves were established: (1) change in Pr{sub 10} and SFFF as functions of the change in PDD{sub 20,10} and (2) change in PDD(depth=3, 15 and 30cm) as function of the change in PDD{sub 20,10}. The differences between Pr{sub 10} and SFFF from baseline were calculated and, from calibration curves, changes in PDD{sub 20,10} and PDD(depth=3, 15 and 30cm) were obtained. Then, absolute PDD(depth=3, 15 and 30cm) values were input into a least-square-optimization algorithm to calculate the bi-exponential function’s optimal coefficients and generate the PDD(depths≥3cm). Results: The change in PDD{sub 20,10} relative to baseline increased (<±4%) with BMC. Pr{sub 10} increased (±6%) and SFFF decreased (±11%) with BMC. Relative differences between measured and calculated (i.e. PDD calculation from Pr{sub 10} and SFFF) PDDs were less than 1%. Results apply to FF and FFF beams measured in 3DW and ICP. Conclusion: Pr{sub 10} and SFFF are more sensitive than PDD to changes in beam energy and PDD information can be accurately generated from them. With known 3DW and ICP profile relationship, ICP can be used to obtain PDD for current photon beam.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

MO-FG-CAMPUS-IeP2-01: Characterization of Beam Shaping Filters and Photon Spectra From HVL Profiles in CT

Purpose: Advanced dosimetry in CT (e.g. the Monte Carlo method) requires an accurate characterization of the shaped filter and radiation quality used during a scan. The purpose of this work was to develop a method where half value layer (HVL) profiles along shaped filters could be made. From the HVL profiles the beam shaping properties and effective photon spectrum for a particular scan can be inferred. Methods: A measurement rig was developed to allow determinations of the HVL under a scatter-free narrow-beam geometry and constant focal spot to ionization chamber distance for different fan angles. For each fan angle the HVL is obtained by fitting the transmission of radiation through different thicknesses of an Al absorber (type 1100) using an appropriate model. The effective Al thickness of shaped filters and effective photon spectra are estimated using a model of photon emission from a Tungsten anode. This method is used to obtain the effective photon spectra and effective Al thickness of shaped filters for a CT scanner recently introduced to the market. Results: This study resulted in a set of effective photon spectra (central ray) for each kVp along with effective Al thicknesses of the different shaped filters. The effective photon spectra and effective Al thicknesses of shaped filters were used to obtain numerically approximated HVL profiles and compared to measured HVL profiles (mean absolute percentage error = 0.02). The central axis HVL found in the vendor’s technical documentation were compared to approximated HVL values (mean absolute percentage error = 0.03). Conclusion: This work has resulted in a unique method of measuring HVL profiles along shaped filters in CT. Further the effective photon spectra and the effective Al thicknesses of shaped filters that were obtained can be incorporated into Monte Carlo simulations.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Algorithms in Diffraction Profile Analysis

This chapter introduces several approaches to crystallographic structure refinement from diffraction profile data including the Rietveld method, global optimization methods, and Bayesian modeling. First, the Rietveld method and related nonlinear least squares approaches to analyzing diffraction profiles are briefly discussed. We then review the most common algorithms within global optimization as alternative methods of structure solution: grid search, simulated annealing, and genetic algorithms. As the Rietveld method is the standard tool for analyzing diffraction profile data, we catalogue its challenges and limitations. A Bayesian approach to diffraction profile analysis is presented as an alternative, along with several sampling algorithms including Gibbs sampling, variants of Metropolis sampling, Hamiltonian Monte Carlo, and approximate Bayesian computing. These sampling algorithms are applied to the fitting of a neutron diffraction profile from a National Institute of Standards and Technology silicon standard reference material, and their results are compared.

Singh, Susheela↗