The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Samuel H. Yalkowsky - One of the best experts on this subject based on the ideXlab platform.
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comparison of two methods for estimation of melting points of organic compounds
Industrial & Engineering Chemistry Research, 2007Co-Authors: Akash Jain, Samuel H. YalkowskyAbstract:This study compares the melting point predictions of UPPER to MPBPWIN for over 2200 organic compounds. The Average Absolute Error (AAE) and root-mean-square Error (RMSE) in melting point prediction using UPPER are 30.1 deg and 39.7 deg, while MPBPWIN gives an AAE of 44.5 deg and RMSE of 58.4 deg. UPPER provides more accurate melting point predictions because it accounts for both the additive enthalpic and nonadditive entropic contributions to melting.
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Estimation of Melting Points of Organic Compounds
Industrial & Engineering Chemistry Research, 2004Co-Authors: Akash Jain, Gang Yang, Samuel H. YalkowskyAbstract:A combination of additive group contributions and nonadditive molecular parameters is employed to estimate the normal melting points of 1215 organic compounds. The melting points are calculated from the ratio of the total phase change enthalpy and entropy of melting. The total phase change enthalpy of melting is calculated from the enthalpic group contributions, whereas the total phase change entropy of melting is estimated using a semiempirical equation based on only two nonadditive molecular parameters. The Average Absolute Error in estimating the melting points of these organic compounds is 33.2 K. This is a relatively low value considering the wide range of pharmaceutically and environmentally relevant organic compounds included in this data set.
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prediction of drug solubility by the general solubility equation gse
Journal of Chemical Information and Computer Sciences, 2001Co-Authors: Samuel H. YalkowskyAbstract:The revised general solubility equation (GSE) proposed by Jain and Yalkowsky is used to estimate the aqueous solubility of a set of organic nonelectrolytes studied by Jorgensen and Duffy. The only inputs used in the GSE are the Celsius melting point (MP) and the octanol water partition coefficient (Kow). These are generally known, easily measured, or easily calculated. The GSE does not utilize any fitted parameters. The Average Absolute Error for the 150 compounds is 0.43 compared to 0.56 with Jorgensen and Duffy's computational method, which utilitizes five fitted parameters. Thus, the revised GSE is simpler and provides a more accurate estimation of aqueous solubility of the same set of organic compounds. It is also more accurate than the original version of the GSE.
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prediction of drug solubility by the general solubility equation gse
Journal of Chemical Information and Computer Sciences, 2001Co-Authors: Samuel H. YalkowskyAbstract:The revised general solubility equation (GSE) proposed by Jain and Yalkowsky is used to estimate the aqueous solubility of a set of organic nonelectrolytes studied by Jorgensen and Duffy. The only inputs used in the GSE are the Celsius melting point (MP) and the octanol water partition coefficient (Kow). These are generally known, easily measured, or easily calculated. The GSE does not utilize any fitted parameters. The Average Absolute Error for the 150 compounds is 0.43 compared to 0.56 with Jorgensen and Duffy's computational method, which utilitizes five fitted parameters. Thus, the revised GSE is simpler and provides a more accurate estimation of aqueous solubility of the same set of organic compounds. It is also more accurate than the original version of the GSE.
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a combined group contribution and molecular geometry approach for predicting melting points of aliphatic compounds
Industrial & Engineering Chemistry Research, 1999Co-Authors: Luwei Zhao, Samuel H. YalkowskyAbstract:A combined approach that utilizes both group contribution and simple molecular geometric parameters is employed to predict normal melting points for a variety of aliphatic compounds. The melting points are estimated from the ratio of the enthalpy and the entropy of melting. The former is calculated from the sum of enthalpic group contributions and correction factors, whereas the latter is calculated using a modification of Walden's rule. Approximately 1040 melting point data were compiled and analyzed by multiple regression. The root-mean-square Error of the estimation is 34.4 K. This is relatively low given the complexity of melting and the diversity of the database used. A comparison of the proposed method with the method of Joback and Reid8 was performed on 50 aliphatic compounds that were not used in the training set. The Average Absolute Error for this method is approximately 20%, whereas that for the Joback and Reid data is 34%. The higher prediction accuracy of the proposed method suggests that the...
Guangmin Wang - One of the best experts on this subject based on the ideXlab platform.
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analytical modeling the multi core shared cache behavior with considerations of data sharing and coherence
IEEE Access, 2021Co-Authors: Ming Ling, Guangmin WangAbstract:To mitigate the ever worsening “Power wall” and “Memory wall” problems, multi-core architectures with multi-level cache hierarchies have been widely accepted in modern processors. However, the complexity of the architectures makes modeling of shared caches extremely complex. In this article, we propose a data-sharing aware analytical model for estimating the miss rates of the downstream shared cache under multi-core scenarios. To avoid time-consuming full simulations of the cache architecture required by conventional approaches, the proposed model can also be integrated with our refined upstream cache analytical model, which also evaluates coherence misses with similar accuracies of state-of-the-art approach with only one tenth time overhead. We validate our analytical model against gem5 simulation results under 13 applications from PARSEC 2.1 benchmark suites. Compared to the results from gem5 simulations under 8 hardware configurations including dual-core and quad-core architectures, the Average Absolute Error of the predicted shared L2 cache miss rates is less than 2% for all configurations. After integrated with the refined upstream model with coherence misses, the overall Average Absolute Error in 4 hardware configurations is degraded to 4.82% due to the Error accumulations. As an application case of the integrated model, we also evaluate the miss rates of 57 different multi-core and multi-level cache configurations.
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analytical modeling the multi core shared cache behavior with considerations of data sharing and coherence
arXiv: Hardware Architecture, 2020Co-Authors: Ming Ling, Guangmin WangAbstract:To mitigate the ever worsening "Power wall" and "Memory wall" problems, multi-core architectures with multilevel cache hierarchies have been widely accepted in modern processors. However, the complexity of the architectures makes modeling of shared caches extremely complex. In this paper, we propose a data-sharing aware analytical model for estimating the miss rates of the downstream shared cache under multi-core scenarios. Moreover, the proposed model can also be integrated with upstream cache analytical models with the consideration of multi-core private cache coherent effects. This integration avoids time consuming full simulations of the cache architecture that required by conventional approaches. We validate our analytical model against gem5 simulation results under 13 applications from PARSEC 2.1 benchmark suites. Compared to the results from gem5 simulations under 8 hardware configurations including dual-core and quad-core architectures, the Average Absolute Error of the predicted shared L2 cache miss rates is less than 2% for all configurations. After integrated with the refined upstream model with coherence misses, the overall Average Absolute Error in 4 hardware configurations is degraded to 8.03% due to the Error accumulations. The proposed coherence model can achieve similar accuracies of state of the art approach with only one tenth time overhead. As an application case of the integrated model, we also evaluate the miss rates of 57 different multi-core and multi-level cache configurations.
Henry F Schaefer - One of the best experts on this subject based on the ideXlab platform.
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electron affinities of the oxides of aluminum silicon phosphorus sulfur and chlorine
Journal of Chemical Physics, 1999Co-Authors: Nicole R Brinkmann, Gregory S Tschumper, Henry F SchaeferAbstract:The adiabatic electron affinities of five second row atoms (Al, Si, P, S, Cl) and their monoxides and dioxides were determined using six different density functional or hybrid Hartree–Fock/density functional methods. The 15 species selected form a convenient closed set for which reliable experimental electron affinities exist for 13 of the species. Zero-point vibrational energy corrected electron affinities are also reported. Equilibrium geometries and vibrational frequencies were determined with each density functional method. The method based on the Becke exchange functional and the Lee–Yang–Parr correlation (BLYP) functional reproduced the experimental electron affinities most accurately, having an Average Absolute Error of 0.15 eV. Using this functional, the electron affinities were predicted for SiO and SiO2, molecules for which electron affinities are not known experimentally, as 0.11 eV and 2.03 eV, respectively. It is concluded that the accuracy observed for density functional theory methods appli...
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predicting electron affinities with density functional theory some positive results for negative ions
Journal of Chemical Physics, 1997Co-Authors: Gregory S Tschumper, Henry F SchaeferAbstract:The atomic electron affinities of the eight first row (H,Li,…,F) atoms as well as the adiabatic electron affinities of 12 first row diatomic and 15 first row triatomic molecules were determined using six different density functional or hybrid Hartree–Fock/density functional methods. The 35 species were selected for having relatively well-established experimental electron affinities. Harmonic zero-point vibrational energy corrected electron affinities are also reported for the diatomic and triatomic molecules. Equilibrium geometries and harmonic vibrational frequencies are given for the 27 molecules and their anions as determined with each density functional method. Discussion focuses on comparison of theoretical and experimental electron affinities. For the atomic, diatomic, and triatomic electron affinities the Average Absolute Error is reported for each exchange–correlation functional. Since many of the molecular anion structures and vibrational frequencies are unknown, the work suggests new experimental directions.
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the weakly bound dinitrogen tetroxide molecule high level single reference wavefunctions are good enough
Journal of Chemical Physics, 1997Co-Authors: Steve S Wesolowski, Justin T Fermann, Daniel T Crawford, Henry F SchaeferAbstract:Ab initio studies of dinitrogen tetroxide (N2O4) have been performed to predict the equilibrium geometry, harmonic vibrational frequencies, and fragmentation energy (N2O4→2 NO2). The structure was optimized at the self-consistent field, configuration interaction, and coupled-cluster levels of theory with large basis sets. At the highest level of theory, the N–N bond distance was 1.752 A, in excellent agreement with the experimental value of 1.756±0.01 A. In addition, the harmonic vibrational frequencies were predicted with an Average Absolute Error of 51 cm−1 relative to experimental fundamental values with differences largely attributed to anharmonic effects. The fragmentation energy corrected for zero point vibrational energy and basis set superposition Error was 7.2 kcal/mol, in fair agreement with the experimental value of 12.7 kcal/mol. Despite the suggestion that a multireference wavefunction may be necessary to accurately describe the biradical nature of N2O4, single reference treatments with large...
Aref Lashin - One of the best experts on this subject based on the ideXlab platform.
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improved oil formation volume factor bo correlation for volatile oil reservoirs an integrated non linear regression and genetic programming approach
Journal of King Saud University: Engineering Sciences, 2016Co-Authors: K A Fattah, Aref LashinAbstract:Abstract In this paper, two correlations for oil formation volume factor ( B o ) for volatile oil reservoirs are developed using non-linear regression technique and genetic programming using commercial software. More than 1200 measured values obtained from PVT laboratory analyses of five representative volatile oil samples are selected under a wide range of reservoir conditions (temperature and pressure) and compositions. Matching of PVT experimental data with an equation of state (EOS) model using a commercial simulator (Eclipse Simulator), was achieved to generate the oil formation volume factor ( B o ). The obtained results of the B o as compared with the most common published correlations indicate that the new generated model has improved significantly the Average Absolute Error for volatile oil fluids. The hit-rate ( R 2 ) of the new non-linear regression correlation is 98.99% and the Average Absolute Error (AAE) is 1.534% with standard deviation (SD) of 0.000372. Meanwhile, correlation generated by genetic programming gave R 2 of 99.96% and an AAE of 0.3252% with a SD of 0.00001584. The importance of the new correlation stems from the fact that it depends mainly on experimental field production data, besides having a wide range of applications especially when actual PVT laboratory data are scarce or incomplete.
Farhad Gharagheizi - One of the best experts on this subject based on the ideXlab platform.
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A simple accurate model for prediction of flash point temperature of pure compounds
Journal of Thermal Analysis and Calorimetry, 2012Co-Authors: Farhad Gharagheizi, Mohammad Hossein Keshavarz, Mehdi SattariAbstract:In this study, a simple three-parameter linear model is presented for estimation of flash point (FP) of pure compounds. The parameters of the model contain experimental normal boiling point of the compound and two chemical structure-based parameters. A comprehensive database of FPs containing 1472 pure compounds of various chemical structures was used to develop the model. The squared correlation coefficient and Average Absolute Error of the model calculation results for all of the compounds presented in the database are evaluated to be 0.982 and 7.2 K, respectively.
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prediction of upper flammability limit percent of pure compounds from their molecular structures
Journal of Hazardous Materials, 2009Co-Authors: Farhad GharagheiziAbstract:In this study, a quantitative structure-property relationship (QSPR) is presented to predict the upper flammability limit percent (UFLP) of pure compounds. The obtained model is a five parameters multi-linear equation. The parameters of the model are calculated only from chemical structure. The Average Absolute Error and squared correlation coefficient of the obtained model over all 865 pure compounds used to develop the model are 9.7%, and 0.92, respectively.
