The Thermodynamics of Fluid-Phase Benzene via Molecular Simulation

Accurate values for thermodynamic properties throughout the fluid phase are a requirement for the design of separation processes. To date, very few pure substances have been completely characterized because of time and monetary constraints. Low cost computing power now permits complete determination of the thermodynamic properties of pure substances via molecular simulation. Molecular simulation is computational statistical mechanics. Benzene is an important industrial chemical and pharmaceutical precursor. It is the prototypical, symmetric, hexagonal molecule and is an ideal candidate for molecular simulation. The molecular models of three researchers in the field are submitted for Monte Carlo simulation in the virtual laboratories at All claim that their models best represent real benzene. The MC code used for experimentation measures 12 thermodynamic properties with associated errors, and derivatives of the residual Helmholtz energy with respect to density and temperature to order 4. The thermodynamic properties are used to generate a multiparameter fundamental equation of state that represents the model throughout the fluid phase. Thermodynamic properties from the three models are compared to the values from the Goodwin equation of state for benzene. A single model is chosen as the best representative of real benzen

The Thermodynamics of Fluid-Phase Benzene via Molecular Simulation

Accurate values for thermodynamic properties throughout the fluid phase are a requirement for the design of separation processes. To date, very few pure substances have been completely characterized because of time and monetary constraints. Low cost computing power now permits complete determination of the thermodynamic properties of pure substances via molecular simulation. Molecular simulation is computational statistical mechanics. Benzene is an important industrial chemical and pharmaceutical precursor. It is the prototypical, symmetric, hexagonal molecule and is an ideal candidate for molecular simulation. The molecular models of three researchers in the field are submitted for Monte Carlo simulation in the virtual laboratories at All claim that their models best represent real benzene. The MC code used for experimentation measures 12 thermodynamic properties with associated errors, and derivatives of the residual Helmholtz energy with respect to density and temperature to order 4. The thermodynamic properties are used to generate a multiparameter fundamental equation of state that represents the model throughout the fluid phase. Thermodynamic properties from the three models are compared to the values from the Goodwin equation of state for benzene. A single model is chosen as the best representative of real benzen

The production, properties and applications of the zinc imidazolate, ZIF-8.

Venna, Carreon, and Jasinski produced and characterized the first samples of the zinc imidazolate framework ZIF-8 at the University of Louisville in 2010. In this dissertation the production, properties, and applications of this unique metal-organic framework are explored. Previously, only minute laboratory amounts (1/4 gram), of ZIF-8 were produced via time-consuming and expensive processes. Production quantities have been synthesized via both a continuous and a batch process using a spray drying operation to effect separation of the solid product (ZIF-8) from the mother liquor. Approximately 85% of the mother liquor (methanol), can be recovered from the spray dryer resulting in magnitude-of-order savings in time and money. Before any engineering applications could be suggested it was necessary to quantify important physical properties of ZIF-8 not currently available. The density, thermal conductivity, specific heat, and BET surface area were measured via strict ASTM procedures and reported. It was hoped that the massive surface area of ZIF-8 (~ 1300 m2/g), would effect enhanced heat transfer in engineering applications. The Heat Transfer Laboratories at the University of Louisville, served as the testing site for the use of the microparticle ZIF-8 as an agent for enhanced heat transfer when mixed in small vol% in synthetic oil. Unfortunately ZIF-8 delivered no such enhancement

Indicators and Benchmarks for Wind Erosion Monitoring, Assessment and Management

Wind erosion and blowing dust threaten food security, human health and ecosystem services across global drylands. Monitoring wind erosion is needed to inform management, with explicit monitoring objectives being critical for interpreting and translating monitoring information into management actions. Monitoring objectives should establish quantitative guidelines for determining the relationship of wind erosion indicators to management benchmarks that reflect tolerable erosion and dust production levels considering impacts to, for example, ecosystem processes, species, agricultural production systems and human well-being. Here we: 1) critically review indicators of wind erosion and blowing dust that are currently available to practitioners; and 2) describe approaches for establishing benchmarks to support wind erosion assessments and management. We find that while numerous indicators are available for monitoring wind erosion, only a subset have been used routinely and most monitoring efforts have focused on air quality impacts of dust. Indicators need to be related to the causal soil and vegetation controls in eroding areas to directly inform management. There is great potential to use regional standardized soil and vegetation monitoring datasets, remote sensing and models to provide new information on wind erosion across landscapes. We identify best practices for establishing benchmarks for these indicators based on experimental studies, mechanistic and empirical models, and distributions of indicator values obtained from monitoring data at historic or existing reference sites. The approaches to establishing benchmarks described here have enduring utility as monitoring technologies change and enable managers to evaluate co-benefits and potential trade-offs among ecosystem services as affected by wind erosion management

Enhancing wind erosion monitoring and assessment for U.S. rangelands

Wind erosion is a major resource concern for rangeland managers because it can impact soil health, ecosystem structure and function, hydrologic processes, agricultural production, and air quality. Despite its significance, little is known about which landscapes are eroding, by how much, and when. The National Wind Erosion Research Network was established in 2014 to develop tools for monitoring and assessing wind erosion and dust emissions across the United States. The Network, currently consisting of 13 sites, creates opportunities to enhance existing rangeland soil, vegetation, and air quality monitoring programs. Decision-support tools developed by the Network will improve the prediction and management of wind erosion across rangeland ecosystems. © 2017 The Author(s)The Rangelands archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information

Indicators and benchmarks for wind erosion monitoring, assessment and management

Wind erosion and blowing dust threaten food security, human health and ecosystem services across global drylands. Monitoring wind erosion is needed to inform management, with explicit monitoring objectives being critical for interpreting and translating monitoring information into management actions. Monitoring objectives should establish quantitative guidelines for determining the relationship of wind erosion indicators to management benchmarks that reflect tolerable erosion and dust production levels considering impacts to, for example, ecosystem processes, species, agricultural production systems and human well-being. Here we: 1) critically review indicators of wind erosion and blowing dust that are currently available to practitioners; and 2) describe approaches for establishing benchmarks to support wind erosion assessments and management. We find that while numerous indicators are available for monitoring wind erosion, only a subset have been used routinely and most monitoring efforts have focused on air quality impacts of dust. Indicators need to be related to the causal soil and vegetation controls in eroding areas to directly inform management. There is great potential to use regional standardized soil and vegetation monitoring datasets, remote sensing and models to provide new information on wind erosion across landscapes. We identify best practices for establishing benchmarks for these indicators based on experimental studies, mechanistic and empirical models, and distributions of indicator values obtained from monitoring data at historic or existing reference sites. The approaches to establishing benchmarks described here have enduring utility as monitoring technologies change and enable managers to evaluate co-benefits and potential trade-offs among ecosystem services as affected by wind erosion management

U.S. Billion-ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry

The Report, Biomass as Feedstock for a Bioenergy and Bioproducts Industry: The Technical Feasibility of a Billion-Ton Annual Supply (generally referred to as the Billion-Ton Study or 2005 BTS), was an estimate of “potential” biomass within the contiguous United States based on numerous assumptions about current and future inventory and production capacity, availability, and technology. In the 2005 BTS, a strategic analysis was undertaken to determine if U.S. agriculture and forest resources have the capability to potentially produce at least one billion dry tons of biomass annually, in a sustainable manner—enough to displace approximately 30% of the country’s present petroleum consumption. To ensure reasonable confidence in the study results, an effort was made to use relatively conservative assumptions. However, for both agriculture and forestry, the resource potential was not restricted by price. That is, all identified biomass was potentially available, even though some potential feedstock would more than likely be too expensive to actually be economically available. In addition to updating the 2005 study, this report attempts to address a number of its shortcoming

The Thermodynamics of Fluid-Phase Benzene via Molecular Simulation

Accurate values for thermodynamic properties throughout the fluid phase are a requirement for the design of separation processes. To date, very few pure substances have been completely characterized because of time and monetary constraints. Low cost computing power now permits complete determination of the thermodynamic properties of pure substances via molecular simulation. Molecular simulation is computational statistical mechanics. Benzene is an important industrial chemical and pharmaceutical precursor. It is the prototypical, symmetric, hexagonal molecule and is an ideal candidate for molecular simulation. The molecular models of three researchers in the field are submitted for Monte Carlo simulation in the virtual laboratories at All claim that their models best represent real benzene. The MC code used for experimentation measures 12 thermodynamic properties with associated errors, and derivatives of the residual Helmholtz energy with respect to density and temperature to order 4. The thermodynamic properties are used to generate a multiparameter fundamental equation of state that represents the model throughout the fluid phase. Thermodynamic properties from the three models are compared to the values from the Goodwin equation of state for benzene. A single model is chosen as the best representative of real benzen

Comparison Of The Weibull Model With Measured Wind Speed Distributions For Stochastic Wind Generation

Wind is the principal driver of the Wind Erosion Prediction System (WEPS), which is a process−based computer model for the simulation of wind−blown sediment loss from a field. WEPS generates wind using a stochastic wind generator. The objectives of this study were to improve the stochastic generation of wind speed and direction and to update the wind statistics used by the generator with statistics derived from more recent, quality−controlled data for the 48 contiguous states of the U.S. Erosive wind power density (WPD) was chosen to evaluate how well wind is generated, since it is proportional to sediment transport by wind. It is important that WPD calculated from stochastically generated data (WPDg) closely reproduces WPD calculated from the underlying measured data (WPDm). The commonly used two−parameter Weibull model did not fit wind speed distributions well enough for application in wind erosion models. WPDg deviated more than 20% from WPDm for 168 out of the 332 stations having WPDm \u3e 5 W m−2. Fitting the model to the high wind speeds only, with the expectation of a better curve fit, resulted in some generated wind speeds exceeding 100 m s−1, which is unacceptable. A more direct method uses the wind speed distributions themselves instead of the Weibull model that describes them. Wind speeds are then generated directly from the distributions using linear interpolation between data points. With this more robust direct approach, there was only one station (down from 168 stations) where WPDg deviated more than 20% from WPDm. The direct method of wind speed generation reproduces wind speeds more accurately than the Weibull model, which is important for wind erosion prediction and may be important for other applications as well

Comparison Of The Weibull Model With Measured Wind Speed Distributions For Stochastic Wind Generation

Wind is the principal driver of the Wind Erosion Prediction System (WEPS), which is a process−based computer model for the simulation of wind−blown sediment loss from a field. WEPS generates wind using a stochastic wind generator. The objectives of this study were to improve the stochastic generation of wind speed and direction and to update the wind statistics used by the generator with statistics derived from more recent, quality−controlled data for the 48 contiguous states of the U.S. Erosive wind power density (WPD) was chosen to evaluate how well wind is generated, since it is proportional to sediment transport by wind. It is important that WPD calculated from stochastically generated data (WPDg) closely reproduces WPD calculated from the underlying measured data (WPDm). The commonly used two−parameter Weibull model did not fit wind speed distributions well enough for application in wind erosion models. WPDg deviated more than 20% from WPDm for 168 out of the 332 stations having WPDm \u3e 5 W m−2. Fitting the model to the high wind speeds only, with the expectation of a better curve fit, resulted in some generated wind speeds exceeding 100 m s−1, which is unacceptable. A more direct method uses the wind speed distributions themselves instead of the Weibull model that describes them. Wind speeds are then generated directly from the distributions using linear interpolation between data points. With this more robust direct approach, there was only one station (down from 168 stations) where WPDg deviated more than 20% from WPDm. The direct method of wind speed generation reproduces wind speeds more accurately than the Weibull model, which is important for wind erosion prediction and may be important for other applications as well