National Institute Of Standards And Technology Data Research Articles

Unified analytical formulation regarding thermodynamic properties subject to gaseous metal hydroxides

Analytical formulations concerning the Gibbs free energy for simple substances and compounds show important applications in dealing with many issues, but acquiring such a formulation with few adjustable parameters remains a challenging goal. Here, we report a unified analytical formulation regarding the Gibbs free energy subject to gaseous metal hydroxides MOH for (M=Al, Be, Cs, K, Li, Mg, Na, Sr, and Ca). It depends only on experimental data of atomic masses and six molecular constants except for an adjustable dimensionless pure number, while the temperature-dependent Gibbs free energy polynomial correlation provided in the National Institute of Standards and Technology (NIST) Chemistry WebBook has eight adjustable coefficients, which take different values in different temperature ranges for each species. The mean relative errors between the predicted Gibbs free energy values subject to nine metal hydroxides and the NIST data are within the range of 0.012 % to 0.078 %, and the predicted results of entropy, enthalpy and isobaric heat capacity are also in good agreement with the NIST data. The proposed unified model possesses the characteristics of high prediction accuracy and strong flexibility.

Unified non-fitting explicit formulation of thermodynamic properties for five compounds

The explicit formulations of the Gibbs free energy subject to the concerned species are useful to determine the conditions for minimizing the total Gibbs free energy of a system with a simple way. Here, we develop a unified non-fitting explicit formulation of the Gibbs free energy for five compounds, including N2O, ClBO, OBBr, HBO and HCN. The established Gibbs free energy formulation is correlative only with masses of atoms and experimental data of six molecular constants of triatomic molecules, and away from requirement of fitting a plenty of experimental spectroscopic data or calorimetric data in conventional empirical expressions. For five compounds under consideration, the average absolute deviations between the predicted Gibbs free energy values and the data provided in the National Institute of Standards and Technology (NIST) database are within the range of 0.098% to 0.146%. Employing the developed unified non-fitting Gibbs free energy formulation with high accuracy, the theoretically predicted values of the entropy, enthalpy, and isobaric heat capacity for the concerned five substances are acquired, and the coresponding average absolute deviations from the NIST data are within the ranges of 0.166% to 0.263%, 0.571% to 2.533%, and 1.059% to 1.936%, respectively.

Unified non-fitting formulation representation of thermodynamic properties for diatomic substances

We report a unified non-fitting formulization representation of the Gibbs free energy for diatomic substances. The present correlation with temperature and pressure as independent variables is significantly dependent on experimental data of four molecular constants. To prove the availability of the developed model, we apply it to predict Gibbs free energy and isobaric heat capacity values for 36 diatomic substances in broad temperature ranges. The average absolute deviations (AADs) between the predicted Gibbs free energy values and the National Institute of Standards and Technology (NIST) data are within 0.0145% and 0.1994% for the collected 36 substances. The AADs between the isobaric heat capacity values and the NIST data are within 0.7216% and 6.7765% for 36 substances.

Assessing the effectiveness of the NIST DART-MS Forensics Database and Data Interpretation Tool for designer drug screening with alternative instrumentation

The increasing prevalence of designer drugs has contributed towards the adoption of rapid screening techniques, such as direct analysis in real time-mass spectrometry (DART-MS). Recently, the National Institute of Standards and Technology (NIST) developed a DART-MS Forensics Database and Data Interpretation Tool (DIT) to assist practitioners with the interpretation of seized drug mixtures. However, this resource was only designed for DART ionization coupled with AccuTOF high-resolution mass spectrometers. This study assesses the effectiveness of the NIST DART-MS Forensics Database and DIT for mixture interpretation using other soft ionization sources, such as electrospray ionization (ESI), and coupling DART to an Agilent 6530 quadrupole time-of-flight (Q-TOF) mass spectrometer. As the seized drug community continues to shift towards the use of in-source collision-induced dissociation (IS-CID) with single-stage mass spectrometers coupled with soft ionization sources, it is imperative to understand the similarity of the generated IS-CID fragment ion spectra and the effectiveness of the DIT for seized drug screening using instrumentation other than the DART-AccuTOF.Pearson product-moment correlations (PPMCs) revealed a high degree of spectral similarity between the ESI-IS-CID and DART-IS-CID fragment ion spectra collected across a range of activation conditions. The 95% confidence interval for the average highest PPMC coefficient across the 12 designer drugs in this study was 0.9295 ± 0.0031. More importantly, nearly identical mixture interpretation results were obtained when the ESI-IS-CID and DART-IS-CID fragment ion spectra were analyzed with the DIT. In all cases, the DIT was able to identify a potential library match with at least two match types between the low and high IS-CID spectra for all compounds present in each mixture. Demonstrating the potential applicability of the NIST DART-MS Forensics Database and DIT for the screening of seized drug mixtures using instrumentation other than the DART-AccuTOF provides support for the expanded applicability of this freely available resource.

Corresponding-states model for the correlation and prediction of the surface tension of hydrocarbons

In this paper, a new corresponding state principle (CSP)-based model is proposed to calculate the surface tension of hydrocarbons based on the National Institute of Standards and Technology (NIST) database. This model requires the critical point temperature, the lowest temperature available for surface tension data and the corresponding maximum surface tension value as inputs. It includes two adjustable coefficients which are fitted by using NIST data of three hydrocarbons. To test the applicability of this model, we applied it to predict the surface tension values of other 16 hydrocarbons. For all the 19 hydrocarbons available in NIST database, the average absolute deviations of 16 hydrocarbons are less than 5%. We also compared this new proposed model with other three existing corresponding state models, and found that this model is the best in predicting the surface tension data of hydrocarbons.

Atomic structure for carbon-like ions from Na vi to Ar xiii

ABSTRACT We have calculated the energy levels, oscillator strengths, and transition probabilities for eight carbon-like ions (Na vi, Mg vii, Al viii, Si ix, P x, S xi, Cl xii and Ar xiii) using the Hartree–Fock pseudo-relativistic (HFR) and Thomas–Fermi–Dirac–Amaldi (TFDA) approaches. We used configuration expansions containing eight configurations, namely 2s2 2p2, 2s 2p3, 2s2 2p 3s, 2s2 2p 3p, 2s2 2p 3d, 2s2 2p 4s, 2s2 2p 4p, and 2s2 2p 5s. For each of the considered ions we obtained 59 energy levels, a number of which are not in the National Institute of Standards and Technology (NIST) data base. We compared our results with critically selected experimental data from NIST and with calculations made using the multiconfiguration Hartree–Fock (MCHF) method. We calculated weighted oscillator strengths and transition probabilities using two methods (HFR and TFDA) for the 2s2 2p2 and 2s 2p3 configurations for the eight C-like ions considered here. We analysed the atomic structure parameter trends, which allowed us to find missing data belonging to an isoelectronic sequence. The energy levels, oscillator strengths, and transition probabilities calculated here are in good agreement with the data from the NIST data base. Because emission and absorption features from C-like ions are often used for density and temperature diagnostics of various plasmas in astrophysics, and in studies of the solar corona, including solar flares, and of the coronae of other stars and of ionized outflows in active galactic nuclei etc., the obtained data will be useful for improving plasma diagnostics and modelling, in particular for the X-ray Universe.

Multiconfiguration Dirac-Hartree-Fock calculations of Landég-factors for ions of astrophysical interest: B II, C I−IV, Al I−II, Si I−IV, P II, S II, Cl III, Ar IV, Ca I, Ti II, Zr III, and Sn II

Aims.The Landég-factor is an important parameter in astrophysical spectropolarimetry, used to characterize the response of a line to a given value of the magnetic field. The purpose of this paper is to present accurate Landég-factors for states in B II, C I−IV, Al I−II, Si I−IV, P II, S II, Cl III, Ar IV, Ca I, Ti II, Zr III, and Sn II.Methods.The multiconfiguration Dirac-Hartree-Fock and relativistic configuration interaction methods, which are implemented in the general-purpose relativistic atomic structure package GRASP2K, are employed in the present work to compute the Landég-factors for states in B II, C I−IV, Al I−II, Si I−IV, P II, S II, Cl III, Ar IV, Ca I, Ti II, Zr III, and Sn II. The accuracy of the wave functions for the states, and thus the accuracy of the resulting Landég-factors, is evaluated by comparing the computed excitation energies and energy separations with the National Institute of Standards and Technology (NIST) recommended data.Results.All excitation energies are in very good agreement with the NIST values except for Ti II, which has an average difference of 1.06%. The average uncertainty of the energy separations is well below 1% except for the even states of Al I; odd states of Si I, Ca I, Ti II, Zr III; and even states of Sn II for which the relative differences range between 1% and 2%. Comparisons of the computed Landég-factors are made with available NIST data and experimental values. Analysing theLS-composition of the wave functions, we quantify the departures fromLS-coupling and summarize the states for which there is a difference of more than 10% between the computed Landég-factor and the Landég-factor in pureLS-coupling. Finally, we compare the computed Landég-factors with values from the Kurucz database.

Extended Calculations of Energy Levels and Transition Rates for Singly Ionized Lanthanide Elements. I. Pr–Gd

Abstract Lanthanide elements play important roles as an opacity source in the ejected material from neutron star mergers. Accurate and complete atomic data are necessary to evaluate the opacities and to analyze the observed data. In this paper, we perform extended, ab initio atomic calculations from Pr ii (Z = 59) to Gd ii (Z = 64). By using multiconfiguration Dirac–Hartree–Fock and relativistic configuration-interaction methods, implemented in the general-purpose relativistic atomic structure package (GRASP2K), we calculate the energy levels and transition data of electric dipole transitions. These computations are based on strategies (with small variations) of Nd ii published by Gaigalas et al. Accuracy of data is evaluated by comparing computed energy levels with the National Institute of Standards and Technology (NIST) database or other works. For the energy levels, we obtain the average relative accuracy of 8%, 12%, 6%, 8%, and 7% for Pr ii, Pm ii, Sm ii, Eu ii, and Gd ii ions, respectively, as compared with the NIST data. Accuracy of energy transfer to the wavelength is 3%, 14%, and 11% for Pr ii, Eu ii, and Gd ii. Our computed E1 type transition probabilities are in good agreement with experimental values presented by other authors especially for strong transitions.

Real-world application of machine-learning-based fault detection trained with experimental data

Buildings are responsible for a large portion of the overall energy consumption. With the rising penetration of renewable energies, the heating and cooling demand of buildings will be increasingly satisfied by heat pumps. However, faults in the heat pump systems reduce energy efficiency or cause system failure, leading to an increased demand for primary energy. Hence, fault detection algorithms (FDA) are used to identify faults before system failure or efficiency deterioration occurs.With the rise of artificial intelligence and big data as well as more detailed monitoring systems, data-driven FDA have become a focus of research in recent years, showing promising results with acceptable effort. However, studies often use specific training data sets, thus generating FDAs adapted to a specific experimental system.In this paper, we investigate whether FDAs trained on a fault data set gathered with a laboratory heat pump system can be deployed on a real-world application system without the need for expensive modifications. We also investigate a big data approach, in which we use data collected over an extended period of time to train the FDAs.To this end, we use a data set kindly provided by the National Institute of Standards and Technology (NIST) containing data for typical heat pump failures measured on a specially outfitted air-water heat pump. From this data, we extract a series of features as input for the FDAs and evaluate the importance of those features for the FDAs. We train the algorithms to detect faults on the NIST data set, and transfer the fitted FDAs to our own measurement data.The results show that the trained FDAs perform very well on the NIST data set, but poorly on the real-world data set. We identify several reasons for the FDAs’ poor performance and derive mitigating actions. We believe that big data approaches for FDAs are facing several issues beyond the simple gathering of large data quantities, especially the labelling of occurred faults and completeness of the data set.

Bragg peak characteristics of proton beams within therapeutic energy range and the comparison of stopping power using the GATE Monte Carlo simulation and the NIST data

AbstractPurpose:To examine detail depth dose characteristics of ideal proton beams using the GATE Monte Carlo technique.Methods:In this study, in order to improve simulation efficiency, we used pencil beam geometry instead of parallel broad-field geometry. Depth dose distributions for beam energies from 5 to 250 MeV in a water phantom were obtained. This study used parameters namedRpeak,R90,R80,R73,R50, full width at half maximum (FWHM), width of 80–20% distal fall-off (W(80–20)) and peak-to-entrance ratio to represent Bragg peak characteristics. The obtained energy–range relationships were fitted into third-order polynomial formulae. The present study also used the GATE Monte Carlo code to calculate the stopping power of proton pencil beams in a water cubic phantom and compared results with the National Institute of Standards and Technology (NIST) standard reference database.Results:The study results revealed deeper penetration, broader FWHM and distal fall-off and decreased peak-to-entrance dose ratio with increasing beam energy. Study results for monoenergetic proton beams showed thatR73can be a good indicator to characterise a range of incident beams. These also suggest FWHM is more sensitive thanW(80–20)distal fall-off in finding initial energy spread. Furthermore, the difference between the obtained stopping power from simulation and NIST data almost in all energies was lower than 1%.Conclusion:Detail depth dose characteristics for monoenergetic proton beams within therapeutic energy ranges were reported. These results can serve as a good reference for clinical practitioners in their daily practice.

Determination of water equivalent ratio for some dosimetric materials in proton therapy using MNCPX simulation tool

The water equivalent ratio (WER) was calculated for polypropylene (PP), paraffin, polyethylene (PE), polystyrene (PS), polymethyl methacrylate (PMMA), and polycarbonate materials with potential applications in dosimetry and medical physics. This was performed using the Monte Carlo simulation code, MCNPX, at different proton energies. The calculated WER values were compared with National Institute of Standards and Technology (NIST) data, available experimental and analytical results, as well as the FLUKA, SRIM, and SEICS codes. PP and PMMA were associated with the minimum and maximum WER values, respectively. Good agreement was observed between the MCNPX and NIST data. The biggest difference was 0.71% for PS at 150 MeV proton energy. In addition, a relatively large positive correlation between the WER values and the electron density of the dosimetric materials was observed. Finally, it was noted that PE presented the most analogous Depth Dose Characteristics to liquid water.

Validation of GATE Monte Carlo code for simulation of proton therapy using National Institute of Standards and Technology library data

AbstractAimTo validate the Geant4 Application for Tomographic Emission (GATE) Monte Carlo simulation code by calculating the proton beam range in the therapeutic energy range.Materials and methodsIn this study, the GATE code which is based on Geant4 was used for simulation. The proton beams in the therapeutic energy range (5–250 MeV) were simulated in a water medium, and then compared with the data from National Institute of Standards and Technology (NIST) in order to investigate the accuracy of different physics list available in the GATE code. In addition, the optimal value of SetCut was assessed.ResultsIn all energy ranges, the QBBC physics had a greater deviation in the ranges relative to the NIST data. With respect to the range calculation accuracy, the QGSP_BIC_EMY and QGSP_BERT_HP_EMY physics were in the range of statistical uncertainty; however, QGSP_BIC_EMY produced better results using the least squares. Based on an investigation into the range calculation precision and simulation efficiency, the optimal SetCut was set at 0·1 mm.FindingsBased on an investigation into the range calculation precision and simulation yield, the QGSP_BIC_EMY physics and the optimal SetCut was recommended to be 0·1 mm.

Photodegradation modeling based on laboratory accelerated test data and predictions under outdoor weathering for polymeric materials

Photodegradation, driven primarily by ultraviolet (UV) radiation, is the primary cause of failure for organic paints and coatings, as well as many other products made from polymeric materials exposed to sunlight. Traditional methods of service life prediction involve the use of outdoor exposure in harsh UV environments (e.g., Florida and Arizona). Such tests, however, require too much time (generally many years) to do an evaluation. To overcome the shortcomings of traditional methods, scientists at the U.S. National Institute of Standards and Technology (NIST) conducted a multiyear research program to collect necessary data via scientifically-based laboratory accelerated tests. This paper presents the statistical modeling and analysis of the photodegradation data collected at NIST, and predictions of degradation for outdoor specimens that are subjected to weathering. The analysis involves identifying a physics/chemistry-motivated model that will adequately describe photodegradation paths. The model incorporates the effects of explanatory variables which are UV spectrum, UV intensity, temperature, and relative humidity. We use a nonlinear mixed-effects model to describe the sample paths. We extend the model to allow for dynamic covariates and compare predictions with specimens that were exposed in an outdoor environment where the explanatory variables are uncontrolled but recorded. We also discuss the findings from the analysis of the NIST data and some areas for future research.

The NIST compilation of ionization potentials revisited (I): From He-like to Xe-like ions

The National Institute of Standards and Technology (NIST) database on ionization potentials for neutral atoms and ions is examined. For each isoelectronic sequence, we construct a regularized perturbative series based on the large-Z (heavy cations) and Z ≈ N – 1 (singly charged anion) behaviors. Comparison of the NIST data with this series allows the identification of problematic values in the reported data.

The curvature of the liquid–vapor reduced pressure curve and its relation with the critical region

For most fluids, there exist a maximum and a minimum in the curvature of the reduced vapor pressure curve, pr=pr(Tr) (with pr=p/pc and Tr=T/Tc,pc and Tc being the pressure and temperature at the critical point). By analyzing National Institute of Standards and Technology (NIST) data on the liquid-vapor coexistence curve for 105 fluids, we find that the maximum occurs in the reduced temperature range 0.5⩽Tr⩽0.8 while the minimum occurs in the reduced temperature range 0.980⩽Tr⩽0.995. Vapor pressure equations for which d2pr/dTr2 diverges at the critical point present a minimum in their curvature. Therefore, the point of minimum curvature can be used as a marker for the critical region. By using the well-known Ambrose–Walton (AW) vapor pressure equation we obtain the reduced temperatures of the maximum and minimum curvature in terms of the Pitzer acentric factor. The AW predictions are checked against those obtained from NIST data.

Limits of classical molecular simulation on the estimation of thermodynamic properties of cryogenic hydrogen

In this study, we investigated the limits of classical molecular simulation on the estimation of thermodynamic properties of cryogenic hydrogen. Three empirical potentials, the Lennard-Jones (LJ) potential, two-centre LJ (2CLJ) potential, and modified Buckingham (exp-6) potential and an ab initio potential model derived by the molecular orbital calculation were applied. Molecular dynamics (MD) simulations were performed across a wide density–temperature range. Using these data, the equation of state (EOS) was obtained by Kataoka's method, and they were compared with National Institute of Standards and Technology (NIST) data using the principle of corresponding states. As a result, it was confirmed that the potential model has a large effect on the estimated thermodynamic properties of cryogenic hydrogen. On the other hand, from the viewpoint of the principle of corresponding states, we obtained the same results from the empirical potential models as from the ab initio potential showing that the potential model has only a small effect on the reduced EOS: the classical MD results could not reproduce the NIST data in the high-density region. This difference is thought to arise from the quantum effect in actual liquid hydrogen.

Soot Measurement and Application on Diesel Exhaust Gas Using Laser-Induced Incandescence

In this study, we measured soot concentration by laser induced incandescence (LII). To obtain absolute soot volume fraction, laminar diffusion flames stabilized on a co-annual burner were used in calibration process. Our experimental conditions such as fuel and air flow rate were the same as those reported in the data base by National Institute of Standards and Technology (NIST). We used two types of Nd : YAG laser. One has powerful laser beam intensity, usually used in two-dimensional measurement. The other is small and portable, applicable for measurement in outer field. These systems are called system 1 and 2, respectively. For both cases, the LII signals were recorded by a ICCD camera. We applied this compact system to the soot measurement in diesel exhaust gas. For laminar diffusion flames, the measured instantaneous distributions of LII signals exhibit the similar profile of NIST data base. Since the calibrated soot volume fraction is the same as that measured by Artium LII 200, the reliability of our system is confirmed. In system 2, using the laser beam, the signal has enough S/N ratio. Results for diesel exhaust gas show that the monitored back pressure is larger when the engine speed (rpm) is increased, resulting in higher soot concentration. Additionally, the reduced soot concentration is recorded due to soot trap by a diesel particulate filer (DPF).

A comparative study of the reliability of nine statistical software packages

The reliabilities of nine software packages commonly used in performing statistical analysis are assessed and compared. The (American) National Institute of Standards and Technology (NIST) data sets are used to evaluate the performance of these software packages with regard to univariate summary statistics, one-way ANOVA, linear regression, and nonlinear regression. Previous research has examined various versions of these software packages using the NIST data sets, but typically with fewer software packages than used in this study. This study provides insight into a relative comparison of a wide variety of software packages including two free statistical software packages, basic and advanced statistical software packages, and the popular Excel package. Substantive improvements from previous software reliability assessments are noted. Plots of principal components of a measure of the correct number of significant digits reveal how these packages tend to cluster for ANOVA and nonlinear regression.

Recent developments in food-matrix Reference Materials at NIST.

Since 1996, the National Institute of Standards and Technology (NIST) has developed several food-matrix Standard Reference Materials (SRMs) characterized for nutrient concentrations. These include SRM 1544 Fatty Acids and Cholesterol in a Frozen Diet Composite, SRM 1546 Meat Homogenate, SRM 1548a Typical Diet, SRM 1566b Oyster Tissue, SRM 1846 Infant Formula, and SRM 2383 Baby Food Composite. Three additional materials--SRM 1946 Lake Superior Fish Tissue, SRM 2384 Baking Chocolate, and SRM 2385 Spinach--are in preparation. NIST also recently assigned values for proximate (fat, protein, etc.), individual fatty acid, and total dietary fiber concentrations in a number of existing SRMs and reference materials (RMs) that previously had values assigned for their elemental composition. NIST has used several modes for assignment of analyte concentrations in the food-matrix RMs, including the use of data provided by collaborating laboratories, alone and in combination with NIST data. The use of data provided by collaborating food industry and contract laboratories for the analysis of food-matrix RMs has enabled NIST to provide assigned values for many analytes that NIST does not have the resources or analytical expertise to measure.

NIST data resources for surface analysis by X-ray photoelectron spectroscopy and Auger electron spectroscopy

Abstract A description is given of data resources that are available from the National Institute of Standards and Technology (NIST) for X-ray photoelectron spectroscopy (XPS) and Auger-electron spectroscopy. NIST currently has three databases available: an XPS Database, an Electron Elastic-Scattering Cross-Section Database, and an Electron Inelastic-Mean-Free-Path Database. NIST also offers Standard Test Data (STD) for XPS, a set of simulated XPS data designed to evaluate algorithms and procedures for detecting, locating, and measuring the intensities of overlapping peaks in a doublet. The XPS database and the XPS-STD are available over the internet.