Entropic bounds for multi-scale and multi-physics coupling in earth sciences

The ability to understand and predict how thermal, hydrological,mechanical and chemical (THMC) processes interact is fundamental to many research initiatives and industrial applications. We present (1) a new Thermal– Hydrological–Mechanical–Chemical (THMC) coupling formulation, based on non-equilibrium thermodynamics; (2) show how THMC feedback is incorporated in the thermodynamic approach; (3) suggest a unifying thermodynamic framework for multi-scaling; and (4) formulate a new rationale for assessing upper and lower bounds of dissipation for THMC processes. The technique is based on deducing time and length scales suitable for separating processes using a macroscopic finite time thermodynamic approach. We show that if the time and length scales are suitably chosen, the calculation of entropic bounds can be used to describe three different types of material and process uncertainties: geometric uncertainties,stemming from the microstructure; process uncertainty, stemming from the correct derivation of the constitutive behavior; and uncertainties in time evolution, stemming from the path dependence of the time integration of the irreversible entropy production. Although the approach is specifically formulated here for THMC coupling we suggest that it has a much broader applicability. In a general sense it consists of finding the entropic bounds of the dissipation defined by the product of thermodynamic force times thermodynamic flux which in material sciences corresponds to generalized stress and generalized strain rates, respectively.

Physical, chemical, biological and ecotoxicological properties of wastewater discharged from Davis Station, Antarctica

The properties and toxicity of untreatedwastewater at Davis Station, East Antarctica,were investigated to inform decisions regarding the appropriate level of treatment for local discharge purposes and more generally, to better understand the risk associated with dispersal and impact of wastewaters in Antarctica. Suspended solids, nutrients (nitrogen, phosphorus), biological oxygen demand (BOD), metals, organic contaminants, surfactants and microbiological load were measured at various locations throughout the wastewater discharge system. Wastewater quality and properties varied greatly between buildings on station, each ofwhich has separate holding tanks. Nutrients, BOD and settleable solid levelswere higher than standard municipal wastewaters. Microbiological loads were typical of untreated wastewater. Contaminants detected in the wastewater included metals and persistent organic compounds, mainly polybrominated diphenyl ethers (PBDEs). The toxicity of wastewater was also investigated in laboratory bioassays using two local Antarctic marine invertebrates, the amphipod Paramoera walkeri and the microgastropod Skenella paludionoides. Animals were exposed to a range of wastewater concentrations from3% to 68% (test 1) or 63% (test 2) over 21 days with survival monitored daily. Significant mortality occurred in all concentrations of wastewater after 14 to 21 days, and at higher concentrations (50–68% wastewater) mortality occurred after only one day. Results indicate that the local receiving marine environment at Davis Station is at risk from existing wastewater discharges, and that advanced treatment is required both to remove contaminants shown to cause toxicity to biota, as well as to reduce the environmental risks associated with non-native micro-organisms in wastewater.

Stochastic chemical kinetics and the quasi-steady-state assumption : application to the stochastic simulation algorithm and chemical master equation

Recently the application of the quasi-steady-state approximation (QSSA) to the stochastic simulation algorithm (SSA) was suggested for the purpose of speeding up stochastic simulations of chemical systems that involve both relatively fast and slow chemical reactions [Rao and Arkin, J. Chem. Phys. 118, 4999 (2003)] and further work has led to the nested and slow-scale SSA. Improved numerical efficiency is obtained by respecting the vastly different time scales characterizing the system and then by advancing only the slow reactions exactly, based on a suitable approximation to the fast reactions. We considerably extend these works by applying the QSSA to numerical methods for the direct solution of the chemical master equation (CME) and, in particular, to the finite state projection algorithm [Munsky and Khammash, J. Chem. Phys. 124, 044104 (2006)], in conjunction with Krylov methods. In addition, we point out some important connections to the literature on the (deterministic) total QSSA (tQSSA) and place the stochastic analogue of the QSSA within the more general framework of aggregation of Markov processes. We demonstrate the new methods on four examples: Michaelis–Menten enzyme kinetics, double phosphorylation, the Goldbeter–Koshland switch, and the mitogen activated protein kinase cascade. Overall, we report dramatic improvements by applying the tQSSA to the CME solver.

Sources of ultrafine particles and chemical species along a traffic corridor : comparison of the results from two receptor models

Particulate matter is common in our environment and has been linked to human health problems particularly in the ultrafine size range. A range of chemical species have been associated with particulate matter and of special concern are the hazardous chemicals that can accentuate health problems. If the sources of such particles can be identified then strategies can be developed for the reduction of air pollution and consequently, the improvement of the quality of life. In this investigation, particle number size distribution data and the concentrations of chemical species were obtained at two sites in Brisbane, Australia. Source apportionment was used to determine the sources (or factors) responsible for the particle size distribution data. The apportionment was performed by Positive Matrix Factorisation (PMF) and Principal Component Analysis/Absolute Principal Component Scores (PCA/APCS), and the results were compared with information from the gaseous chemical composition analysis. Although PCA/APCS resolved more sources, the results of the PMF analysis appear to be more reliable. Six common sources identified by both methods include: traffic 1, traffic 2, local traffic, biomass burning, and two unassigned factors. Thus motor vehicle related activities had the most impact on the data with the average contribution from nearly all sources to the measured concentrations higher during peak traffic hours and weekdays. Further analyses incorporated the meteorological measurements into the PMF results to determine the direction of the sources relative to the measurement sites, and this indicated that traffic on the nearby road and intersection was responsible for most of the factors. The described methodology which utilised a combination of three types of data related to particulate matter to determine the sources could assist future development of particle emission control and reduction strategies.

Investigations of the physical and chemical properties of ambient fine particles in urban schools

This thesis reports a comprehensive study on the physical and chemical properties of airborne particles in Brisbane, especially around schools. The sources and potential toxicity of the particles were identified, enabling an assessment of the contributing factors to children's exposure at school. The results from this thesis give a quantitative estimate of the range of airborne particles that children are exposed to at urban schools with different traffic conditions.

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Controlled electronic transport in single-walled carbon nanotube networks : selecting electron hopping and chemical doping mechanisms

The electronic transport in both intrinsic and acid-treated single-walled carbon nanotube networks containing more than 90% semiconducting nanotubes is investigated using temperature-dependent resistance measurements. The semiconducting behavior observed in the intrinsic network is attributed to the three-dimensional electron hopping mechanism. In contrast, the chemical doping mechanism in the acid-treated network is found to be responsible for the revealed metal-like linear resistivity dependence in a broad temperature range. This effective method to control the electrical conductivity of single-walled carbon nanotube networks is promising for future nanoscale electronics, thermometry, and bolometry. © 2010 American Institute of Physics.

Observations on the formation, growth and chemical composition of aerosols in an urban environment

The charge and chemical composition of ambient particles in an urban environment were determined using a Neutral Particle and Air Ion Spectrometer and an Aerodyne compact Time-Of-Flight Aerosol Mass Spectrometer. Particle formation and growth events were observed on 20 of the 36 days of sampling, with eight of these events classified as strong. During these events, peaks in the concentration of intermediate and large ions were followed by peaks in the concentration of ammonium and sulphate, which were not observed in the organic fraction. Comparison of days with and without particle formation events revealed that ammonium and sulphate were the dominant species on particle formation days while high concentrations of biomass burning OA inhibited particle growth. Analyses of the degree of particle neutralisation lead us to conclude that an excess of ammonium enabled particle formation and growth. In addition, the large ion concentration increased sharply during particle growth, suggesting that during nucleation the neutral gaseous species ammonia and sulphuric acid react to form ammonium and sulphate ions. Overall, we conclude that the mechanism of particle formation and growth involved ammonia and sulphuric acid, with limited input from organics.

Particle emissions from biodiesels with different physical properties and chemical composition

Biodiesels produced from different feedstocks usually have wide variations in their fatty acid methyl ester (FAME) so that their physical properties and chemical composition are also different. The aim of this study is to investigate the effect of the physical properties and chemical composition of biodiesels on engine exhaust particle emissions. Alongside with neat diesel, four biodiesels with variations in carbon chain length and degree of unsaturation have been used at three blending ratios (B100, B50, B20) in a common rail engine. It is found that particle emission increased with the increase of carbon chain length. However, for similar carbon chain length, particle emissions from biodiesel having relatively high average unsaturation are found to be slightly less than that of low average unsaturation. Particle size is also found to be dependent on fuel type. The fuel or fuel mix responsible for higher particle mass (PM) and particle number (PN) emissions is also found responsible for larger particle median size. Particle emissions reduced consistently with fuel oxygen content regardless of the proportion of biodiesel in the blends, whereas it increased with fuel viscosity and surface tension only for higher diesel–biodiesel blend percentages (B100, B50). However, since fuel oxygen content increases with the decreasing carbon chain length, it is not clear which of these factors drives the lower particle emission. Overall, it is evident from the results presented here that chemical composition of biodiesel is more important than its physical properties in controlling exhaust particle emissions.

The influence of the gas environment on morphology and chemical composition of surfaces micro-machined with a femtosecond laser

We investigated the influence of different gas environments on the fabrication of surfaces, homogeneously covered with equally sized and spaced micro-structures. Two types of structures have been successfully micro-machined with a femtosecond laser on titanium surfaces in various atmospheres. The surface chemistry of samples machined in oxygen and helium shows TiO2, while machining in nitrogen leads to an additional share of TiN. The actual surface structure was found to vary significantly as a function of the gas environment. We found that the ablated particles and their surface triggered two consecutive events: The optical properties of the gas environment became non-isotropic which then led to the pulse intensity being redistributed throughout the cross section of the laser beam. Additionally, the effective intensity was further reduced for TiN surfaces due to TiN's high reflectivity. Thus, the settings for the applied raster-scanning machining method had to be adjusted for each gas environment to produce comparable structures. In contrast to previous studies, where only noble gases were found suitable to produce homogeneous patches, we obtained them in an oxygen environment.

Wetting, solubility and chemical characteristics of plasma-polymerized 1-isopropyl-4-methyl-1,4-cyclohexadiene thin films

Investigations on the wetting, solubility and chemical composition of plasma polymer thin films provide an insight into the feasibility of implementing these polymeric materials in organic electronics, particularly where wet solution processing is involved. In this study, thin films were prepared from 1-isopropyl-4-methyl-1,4-cyclohexadiene (γ-Terpinene) using radio frequency (RF) plasma polymerization. FTIR showed the polymers to be structurally dissimilar to the original monomer and highly cross-linked, where the loss of original functional groups and the degree of cross-linking increased with deposition power. The polymer surfaces were hydrocarbon-rich, with oxygen present in the form of O–H and C=O functional groups. The oxygen content decreased with deposition power, with films becoming more hydrophobic and, thus, less wettable. The advancing and receding contact angles were investigated, and the water advancing contact angle was found to increase from 63.14° to 73.53° for thin films prepared with an RF power of 10 W to 75 W. The wetting envelopes for the surfaces were constructed to enable the prediction of the surfaces’ wettability for other solvents. The effect of roughness on the wetting behaviour of the films was insignificant. The polymers were determined to resist solubilization in solvents commonly used in the deposition of organic semiconducting layers, including chloroform and chlorobenzene, with higher stability observed in films fabricated at higher RF power.

Optical and chemical properties of polyterpenol thin films deposited via plasma-enhanced chemical vapor deposition

The development of novel organic polymer thin films is essential for the advancement of many emerging fields including organic electronics and biomedical coatings. In this study, the effect of synthesis conditions, namely radio frequency (rf) deposition power, on the material properties of polyterpenol thin films derived from nonsynthetic environmentally friendly monomer was investigated. At lower deposition powers, the polyterpenol films preserved more of the original monomer constituents, such as hydroxy functional groups; however, they were also softer and more hydrophilic compared to polymers fabricated at higher power. Enhanced monomer fragmentation and consequent reduction in the presence of the polar groups in the structure of the high-power samples reduced their optical band gap value from 2.95 eV for 10 W to 2.64 eV for 100 W. Regardless of deposition power, all samples were found to be optically transparent with smooth, defect-free, and homogenous surfaces.

Sinteractivity, proton conductivity and chemical stability of BaZr 0.7In0.3O3-δ for solid oxide fuel cells (SOFCs)

In3+ was used as dopant for BaZrO3 proton conductor and 30 at%-doped BaZrO3 samples (BaZr0.7In 0.3O3-δ, BZI) were prepared as electrolyte materials for proton-conducting solid oxide fuel cells (SOFCs). The BZI material showed a much improved sinteractivity compared with the conventional Y-doped BaZrO 3. The BZI pellets reached almost full density after sintering at 1600 °C for 10 h, whereas the Y-doped BaZrO3 samples still remained porous under the same sintering conditions. The conductivity measurements indicated that BZI pellets showed smaller bulk but improved grain boundary proton conductivity, when compared with Y-doped BaZrO3 samples. A total proton conductivity of 1.7 × 10-3 S cm -1 was obtained for the BZI sample at 700 °C in wet 10% H 2 atmosphere. The BZI electrolyte material also showed adequate chemical stability against CO2 and H2O, which is promising for application in fuel cells.