Experimental Investigation of Water Vapor Concentration on Fracture Properties of Asphalt Concrete.

The effect of moisture on the fracture resistance of asphalt concrete is a significant concern in pavement engineering. To investigate the effect of the water vapor concentration on the fracture properties of asphalt concrete, this study first designed a humidity conditioning program at the relative humidity (RH) levels of 2%, 50%, 80%, and 100% for the three types of asphalt concrete mixtures (AC-13C, AC-20C, and AC-25C).The finite element model was developed to simulate the water vapor diffusion and determine the duration of the conditioning period. The semi-circular bending (SCB) test was then performed at varying temperatures of 5 °C, 15 °C, and 25 °C to evaluate the fracture energy and tensile strength of the humidity-conditioned specimens. The test results showed that the increasing temperature and the RH levels resulted in a lower peak load but greater displacement of the mixtures. Both the fracture energy and tensile strength tended to diminish with the rising temperature. It was also found that moisture had a significant effect on the tensile strength and fracture energy of asphalt concrete. Specifically, as the RH level increased from 2% to 100% (i.e., the water vapor concentration rose from 0.35 g/m3 to 17.27 g/m3), the tensile strength of the three types of mixtures was reduced by 34.84% on average, which revealed that the water vapor led to the loss of adhesion and cohesion within the mixture. The genetic expression programming (GEP) model was developed to quantify the effect of water vapor concentrations and temperature on the fracture indices.

Dental Metal Matrix Composites: The Effects of the Addition of Titanium Nanoparticle Particles on Dental Amalgam.

Dental amalgams have been used by dentists for the restoration of posterior human teeth. However, there have been concerns about the release of mercury from amalgams into the oral cavity. The objective of the present research is to study the effect of titanium (Ti) nanoparticles on the microstructural mechanism of the release of mercury vapor in two commonly used brands of dental amalgam (the Dispersalloy: 11.8% Cu; the Sybralloy: 33% Cu). Ti powder was added to both the Dispersalloy and the Sybralloy in increments of 10 mg up to 80 mg. The addition of Ti powder to both brands of dental amalgam has been found to result in a considerable decrease in Hg vapor release. The decrease in the Hg vapor release due to Ti addition has been explained by the formation of strong Hg-Ti covalent bonds, which reduce the availability of Hg atoms for evaporation. The Ti atoms in excess of the solubility limit of Ti in Hg reside in the grain boundaries, which also reduces the evaporation of Hg from the amalgam. The binding of Hg with Ti via a strong covalent bond also results in a significant improvement in mechanical properties such as Vickers hardness.

Influence of Soil Moisture on Soil Gas Vapor Concentration for Vapor Intrusion.

Mathematical models have been widely used in analyzing the effects of various environmental factors in the vapor intrusion process. Soil moisture content is one of the key factors determining the subsurface vapor concentration profile. This manuscript considers the effects of soil moisture profiles on the soil gas vapor concentration away from any surface capping by buildings or pavement. The "open field" soil gas vapor concentration profile is observed to be sensitive to the soil moisture distribution. The van Genuchten relations can be used for describing the soil moisture retention curve, and give results consistent with the results from a previous experimental study. Other modeling methods that account for soil moisture are evaluated. These modeling results are also compared with the measured subsurface concentration profiles in the U.S. EPA vapor intrusion database.

Exploring the nonlinear partitioning mechanism of volatile organic contaminants between soil and soil vapor using machine learning.

Traditional phase equilibrium models usually depend on simplified assumptions and empirical parameters, which are difficult to obtain during regular site investigations. As a result, they often under- or over-estimate soil vapor concentrations for assessing the risks of volatile organic compound (VOC)-contaminated sites. In this study, we develop several machine learning models to predict soil vapor concentrations using 2225 soil-soil vapor data pairs collected from seven contaminated sites in northern China. Compared to the classic dual equilibrium desorption model, the random forest (RF) model can provide more accurate predictions of soil vapor concentrations by at least 1-2 orders of magnitude. Among the employed covariates, soil concentration and organic carbon-water partition coefficient are two of the most significant explanatory covariates affecting soil vapor concentrations. Further examination of the developed RF model reveals the phase equilibrium behavior of VOCs in soil is that: the soil vapor concentration increases with soil concentration at different rates in the first two intervals but remains almost unchanged in the last interval; the solid-vapor partitioning interface may still exist at up to 15% mass water content in our simulations. These findings can help site investigators perform more accurate risk assessments at VOC-contaminated sites.

Quantitative Distributions of Product Ions and Reaction Times with a Binary Mixture of VOCs in Ambient Pressure Chemical Ionization.

A model to quantitatively predict ion abundances from atmospheric pressure chemical ionization (APCI) between hydrated protons and a volatile organic compound (VOC) was extended to binary mixtures of VOCs. The model includes differences in vapor concentrations, rate coefficients, and reaction times and is enhanced with cross reactions between neutral vapors and protonated monomers. In this model, two specific VOCs were considered, a ketone, 6-methyl-5-hepten-2-one (M, and an amine, 2,6-di-tert-butyl-pyridine (N), with measured "conditional rate coefficients" (in cm3·s-1) of kM = 1.11 × 10-9 and kN = 9.17 × 10-10, respectively. The cross reaction of MH+(H2O)x to NH+(H2O)y was measured as kcr = 1.31 × 10-12 at 60 °C. Cross reactions showed an impact on ion abundances at t > 30 ms for equal vapor concentrations of 100 ppb for M and N. In contrast, this impact was negligible for vapor concentrations of 1 ppb and did not exceed 5% change in product ion abundance up to 1000 ms reaction times. The model was validated with laboratory measurements to within ∼10% using an ion mobility spectrometer and effective reaction time obtained from computational fitting of experimental findings. This was necessitated by complex flow patterns in the ion source volume and was determined as ∼10.5 ms. The model has interpretative and predictive value for quantitative analysis of responses with ambient pressure ion sources for mass spectrometry and ion mobility spectrometry.

Determination and Calculations of Mercury Vapor Concentration and Energy Released from Freshly Condensed Dental Amalgams Having Various Copper Percentages within the Alloy.

Dental amalgam is an alloy consisting of a mixture of fine metallic powder of silver, tin, zinc, copper, and a trace amount of palladium in combination with about fifty percent elemental mercury that forms a matrix phase. Dental amalgams consisting of a high-copper content are the most common types of alloys currently utilized for the restoration of decayed, broken, and fractured posterior human teeth. The present research objective was primarily to improve the material properties by determining and analyzing the amount of mercury vapor released from dental amalgam received from eight different commercial brands. The mechanical hardness of the alloys was found to increase with an increase in copper content in the amalgam. The effect of copper addition on material aging was also studied. During the release of mercury vapor, the corresponding energies associated with the release of mercury vapor from each sample were determined for each successive measurement. The results indicated that increasing the copper content of the amalgam counters the release of mercury vapor from posterior teeth and improves the hardness properties.

Radio Frequency Drying Behavior in Porous Media: A Case Study of Potato Cube with Computer Modeling.

To study the mechanism of heat and mass transfer in porous food material and explore its coupling effect in radio frequency (RF) drying processes, experiments were conducted with potato cubes subjected to RF drying. COMSOL Multiphysics® package was used to establish a numerical model to simulate the heat and mass transfer process in the potato cube and solved with finite element method. Temperature history at the sample center and the heating pattern after drying was validated with experiment in a 27.12 MHz RF heating system. Results showed the simulation results were in agreement with experiments. Furthermore, the temperature distribution and water vapor concentration distribution were correspondent with water distribution in the sample after RF drying. The water concentration within the food volume was non-uniform with a higher water concentration than the corner, the maximum difference of which was 0.03 g·cm-3. The distribution of water vapor concentration in the sample was similar to that of water content distribution since a pressure gradient from center to corner allowed the mass transfer from the sample to the surrounding in the drying process. In general, the moisture distribution in the sample affected the temperature and water vapor concentration distribution since the dielectric properties of the sample were mainly dependent on its moisture content during a drying process. This study reveals the mechanism of RF drying of porous media and provides an effective approach for analyzing and optimizing the RF drying process.

Numerical Simulation of the Water Vapor Separation of a Moisture-Selective Hollow-Fiber Membrane for the Application in Wood Drying Processes.

In this study, a simplified two-dimensional axisymmetric finite element analysis (FEA) model was developed, using COMSOL Multiphysics® software, to simulate the water vapor separation in a moisture-selective hollow-fiber membrane for the application of air dehumidification in wood drying processes. The membrane material was dense polydimethylsiloxane (PDMS). A single hollow fiber membrane was modelled. The mass and momentum transfer equations were simultaneously solved to compute the water vapor concentration profile in the single hollow fiber membrane. A water vapor removal experiment was conducted by using a lab-scale PDMS hollow fiber membrane module operated at constant temperature of 35 °C. Three operation parameters of air flow rate, vacuum pressure, and initial relative humidity (RH) were set at different levels. The final RH of dehydrated air was collected and converted to water vapor concentration to validate simulated results. The simulated results were fairly consistent with the experimental data. Both experimental and simulated results revealed that the water vapor removal efficiency of the membrane system was affected by air velocity and vacuum pressure. A high water vapor removal performance was achieved at a slow air velocity and high vacuum pressure. Subsequently, the correlation of Sherwood (Sh)-Reynolds (Re)-Schmidt (Sc) numbers of the PDMS membrane was established using the validated model, which is applicable at a constant temperature of 35 °C and vacuum pressure of 77.9 kPa. This study delivers an insight into the mass transport in the moisture-selective dense PDMS hollow fiber membrane-based air dehumidification process, with the aims of providing a useful reference to the scale-up design, process optimization and module development using hollow fiber membrane materials.

Parametric Sensitivity in a Generalized Model for Atmospheric Pressure Chemical Ionization Reactions.

Gas phase reactions between hydrated protons H+(H2O)n and a substance M, as seen in atmospheric pressure chemical ionization (APCI) with mass spectrometry (MS) and ion mobility spectrometry (IMS), were modeled computationally using initial amounts of [M] and [H+(H2O)n], rate constants k1 to form protonated monomer (MH+(H2O)x) and k2 to form proton bound dimer (M2H+(H2O)z), and diffusion constants. At 1 × 1010 cm-3 (0.4 ppb) for [H+(H2O)n] and vapor concentrations for M from 10 ppb to 10 ppm, a maximum signal was reached at 4.5 µs to 4.6 ms for MH+(H2O)x and 7.8 µs to 46 ms for M2H+(H2O)z. Maximum yield for protonated monomer for a reaction time of 1 ms was ∼40% for k1 from 10-11 to 10-8 cm3·s-1, for k2/k1 = 0.8, and specific values of [M]. This model demonstrates that ion distributions could be shifted from [M2H+(H2O)z] to [MH+(H2O)x] using excessive levels of [H+(H2O)n], even for [M] > 10 ppb, as commonly found in APCI MS and IMS measurements. Ion losses by collisions on surfaces were insignificant with losses of <0.5% for protonated monomer and <0.1% for proton bound dimer of dimethyl methylphosphonate (DMMP) at 5 ms. In this model, ion production in an APCI environment is treated over ranges of parameters important in mass spectrometric measurements. The models establish a foundation for detailed computations on response with mixtures of neutral substances.