Via mixed-culture fermentation, the MixAlcoTM produces carboxylic acids, which are chemically converted into industrial chemicals and hydrocarbon fuels. Using pilot fermentation data, The Continuum Particle Distribution Model (CPDM) overestimated acid concentration (30–90% error) but more closely estimated conversion (<15% error). Incorporating the effect of air into the model reduced the absolute error of all predictions by >50%. To analyze fermentation data with semi-continuous streams, the Slope method calculates the average flowrate of material from the slope of the moving cumulative sum with respect to time. Although the Slope method does not significantly improve accuracy, it dramatically reduces error compared to traditional techniques (>40% vs. <2%). Nutrients are essential for microbial growth and metabolism. For a four-bottle fermentation train, five nutrient contacting patterns (single-point nutrient addition to Fermentors F1, F2, F3, F4, and multi-point parallel addition) were investigated. Compared to the traditional nutrient contacting method (all nutrients fed to F1), the near-optimal feeding strategies improved exit yield, culture yield, process yield, exit acetate-equivalent yield, conversion, and total acid productivity by approximately 31%, 39%, 46%, 31%, 100%, and 19%, respectively. To estimate nitrogen concentration profiles, a segregated-nitrogen model uses separate mass balances for solid- and liquid-phase nitrogen; the nitrogen reaction flux between phases is assumed to be zero. Using five fermentation trains, each with a different nutrient contacting pattern, the model predictions capture basic behavior; therefore, it is a reasonable tool for estimating and controlling nitrogen profiles. To determine the optimal scenario for mixed-acid fermentations, an array of batch fermentations was performed that independently varied the C/N ratio and the blend of carbohydrate (office paper) and nutrient (wet chicken manure (CM)). Reactant was defined as non-acid volatile solids (NAVS). C/N ratios were based on non-acid carbon (CNA). A blend of 93% paper and 7% wet CM (dry basis) with a C/N ratio of 37 g CNA/g N had the highest culture yield (0.21 g acidproduced/g NAVSinitial), total acid productivity (0.84 g acidproduced/(Lliq·d)), and conversion (0.43 g NAVSconsumed/g NAVSinitial).

High nitrogen discharge from mining sites has been an environmental issue that has been closely studied in the recent years. The environmental effects of high nitrogen discharge are mainly eutrophication, but can also lead to changed species composition and algae blooms. Nitrogen is a highly abundant element and is the most abundant element in the atmosphere, where 78% by volume is present as dinitrogen (N2 ). Nitrogen is present in reduced form in all organic life as ammonium (NH4 + ). Nitrogen is also present in reduced form as nitrate (NO3 - ) or nitrite (NO2 - ) in most aquatic systems.  Both nitrate and ammonium is contributing to eutrophication problems worldwide and ammonia (NH3 ) is direct toxic in high concentration to certain sensitive aquatic species. Nitrate in high concentration is also direct toxic, both to humans but also to aquatic biota.  To trace and quantify different nitrogen transforming processes, their sources and their sinks is called tracing nitrogen cycling and is important due to the environmental effect of nitrogen. Nitrogen is available in many different species and oxidation states which all have their respective geochemistry. This thesis focuses on tracing the complex nitrogen cycle in two different cold climate mining systems in northern Sweden using two different methods. The two studied systems are: The LKAB underground iron ore mine in Kiruna Boliden Minerals AB open pit copper ore mine Aitik outside Gällivare  Two different approaches were used to trace the nitrogen cycling. The LKAB Kiruna mine was investigated using stable nitrogen isotopes. The isotope analysis showed high capability to trace nitrogen cycling, both quantative and qualitative. We also showed the origin of the isotope signals which gives indication to the different sources of nitrogen in the mine. The presented study shows presence of nitrification, ammonium volatilization and ammonium adsorption to waste rock to occur in the water transport system.  The nitrogen cycling in the Boliden Aitik mine was investigated using a nitrogen model which we developed as part of this thesis. The model is based on Yakushevs Redox Layer model (ROLM). The model contains the state variables ammonium, nitrate, nitrite, plankton, phosphate, dead organic material (both particulate and dissolved) as well as oxygen. The nitrogen concentrations in the Boliden Aitik mine was modeled for the clarification pond and showed, in general, low biological activity. The biological mediated reactions such as nitrification, denitrification, phytoplankton growth and grazing were low in relation to natural lake systems

In this study, yearly and seasonally nitrogen retention dynamics of reed beds surrounding Lake Mogan were investigated by comparing surface aerial nitrogen load and in-lake concentrations. The analyses were performed separately for nitrate-N, ammonium-N and dissolved inorganic nitrogen (sum of nitrate-N and ammonium-N) to reveal differences between them in terms of retention dynamics. 1998, 1999 and 2002 were relatively high-load years in terms of DIN-input to reed beds surrounding Lake Mogan, compared with the DIN-loadings of 1997, 2000 and 2001. A significant difference was observed between NO3-N input and output for the relatively high-load years to Lake Mogan reed beds indicating significantly high NO3-N retention rates for that periods, while no significant difference was observed in the relatively low-load years. Also, a clear linear relationship (R2 = 0.975) was found between amount of NO3-N retention and amount of NO3-N input to the system. NH4-N input and output were not significantly different in none of the study years. Then, a dynamic Wetland Nitrogen Model was utilized to model dissolved inorganic nitrogen removal capacity of the reed beds surrounding Lake Mogan. The model was firstly calibrated and validated using data sets of different study years and then used for prediction under wet and dry year scenarios. The model predictions revealed that NO3-N retention efficiency was distinctively higher in wet rather than the dry year conditions since the reed beds might have limited denitrification capacity in dry years due to unavailability of enough NO3-N load. Finally, the land-use changes occurred in the closer catchment of Lake Mogan and the potential risk areas for non-point nitrogen input to Lake Mogan were determined using aerial photos of the region and Geographical Information Systems (GIS). It was observed that highest potential risk area for non-point nitrogen input around the lake was north-east of the lake whereas, north end of the lake was least potential risk area.

Silicon nitride is a bulk and a coating material exhibiting excellent mechanical properties. The understanding of the complex processes at the nanometre scale gained through experimental research will be enhanced by the existence of a computationally efficient and accurate model that is able to describe the mechanical properties of silicon nitride. Such a model has yet to be proposed. In this thesis we present a transferable reduced tight-binding (TB) model for the silicon nitride system. More precisely, this model consists of a reduced TB model for elemental silicon, a reduced TB model for elemental nitrogen, and a reduced TB model for silicon nitride. These models are developed within the framework of coarse-graining the electronic structure from density functional theory (DFT) to tight binding (TB) to bond-order potentials (BOPs), and can therefore be used in the future as the stepping stone to develop BOPs for the application in large scale simulations. The bond integrals employed in the reduced TB models are obtained directly from mixed-basis DFT projections of wave functions onto a minimal basis of atom-centred orbitals. This approach reduces the number of overall parameters to be fitted and provides models which are transferable through the different coarse-graining levels. We provide an example by using the same bond integrals in the reduced TB model for silicon and the preliminary bond-based BOP for silicon. DFT binding energies of ground state and metastable crystal structures are used as the benchmark to which the TB and BOP repulsive parameters are fitted. In addition to model development, we present an improved methodology when going from TB to reduced TB. By weighting all four &sigma; TB bond integrals equally, we provide a new parameterisation (Eqs. (2.73) and (2.74)) and show that the quality of the silicon reduced TB model can be increased by choosing one of the reduced TB parameters to be distance invariant. The ingredients, the development methodology, and the quality of each of the four models are discussed in a separate chapter. The quality of the reduced TB models and BOP is demonstrated by comparing their predictions for the binding energies, heats of formation, elastic constants, and defect energies with DFT and experimental values.