Kinetic modelling of growth and storage molecule production in microalgae under mixotrophic and autotrophic conditions.

In order to improve algal biofuel production on a commercial-scale, an understanding of algal growth and fuel molecule accumulation is essential. A mathematical model is presented that describes biomass growth and storage molecule (TAG lipid and starch) accumulation in the freshwater microalga Chlorella vulgaris, under mixotrophic and autotrophic conditions. Biomass growth was formulated based on the Droop model, while the storage molecule production was calculated based on the carbon balance within the algal cells incorporating carbon fixation via photosynthesis, organic carbon uptake and functional biomass growth. The model was validated with experimental growth data of C. vulgaris and was found to fit the data well. Sensitivity analysis showed that the model performance was highly sensitive to variations in parameters associated with nutrient factors, photosynthesis and light intensity. The maximum productivity and biomass concentration were achieved under mixotrophic nitrogen sufficient conditions, while the maximum storage content was obtained under mixotrophic nitrogen deficient conditions.

Kinetic modelling of growth and storage molecule production in microalgae under mixotrophic and autotrophic conditions

In order to improve algal biofuel production on a commercial-scale, an understanding of algal growth and fuel molecule accumulation is essential. A mathematical model is presented that describes biomass growth and storage molecule (TAG lipid and starch) accumulation in the freshwater microalga Chlorella vulgaris, under mixotrophic and autotrophic conditions. Biomass growth was formulated based on the Droop model, while the storage molecule production was calculated based on the carbon balance within the algal cells incorporating carbon fixation via photosynthesis, organic carbon uptake and functional biomass growth. The model was validated with experimental growth data of C. vulgaris and was found to fit the data well. Sensitivity analysis showed that the model performance was highly sensitive to variations in parameters associated with nutrient factors, photosynthesis and light intensity. The maximum productivity and biomass concentration were achieved under mixotrophic nitrogen sufficient conditions, while the maximum storage content was obtained under mixotrophic nitrogen deficient conditions. © 2014 Elsevier Ltd.

Kinetic modelling for photosynthesis of hydrogen and Methane through catalytic reduction of carbon dioxide with water vapour

In a photocatalytic reduction process when products formed are not effectively desorbed, they could hinder the diffusion of intermediates on the surface of the catalyst, as well as increase the chance of collisions among the products, resulting photo-oxidation in a reserve reaction on the surface. This paper analyses a simple kinetic model incorporating the coupled effect of the adsorptive photocatalytic reduction and oxidation. The development is based on Langmuir–Hinshelwood mechanism to model the formation rates of hydrogen and methane through photocatalytic reduction of carbon dioxide with water vapour. Experimental data obtained from literatures have achieved a very good fit. Such model could aid as a tool for related areas of studies. A comparative study using the model developed, showed that product concentration in term of ppm would be an effective measurement of product yields through photocatalytic reduction of carbon dioxide with water vapour.

Thermodynamic and kinetic modelling hydrogenation of titanium particles and sheets

Use of hydrogen as a temporary alloying element in titanium alloys is an attractive approach to improve the mechanical properties of the materials, enhance processability and thereby reduce manufacturing costs. In this paper, the hydrogen diffusion process and the phase transformation both between titanium particles and in titanium sheets were computationally simulated to analyze the mechanism of hydrogen diffusion in different phases (α-Ti, β-Ti and TiHx). With the simulation based on the thermodynamics and kinetics, quantitative behaviors of the hydrogen diffusion and the phase transformation were analyzed. The simulation results provide an insight into the diffusion process and improve the fundamental understanding of the mechanism of diffusion and phase transformation.

Thermodynamic and kinetic modelling hydrogenation of titanium particles and sheets

Use of hydrogen as a temporary alloying element in Ti alloys is an attractive approach to improve the mechanical properties of the materials, enhance processability and thereby reduce manufacturing costs. In this paper, the hydrogen diffusion process and the phase transformation both between Ti particles and in Ti sheets were simulated to analyze the mechanism of hydrogen diffusion in different phases (α-Ti, β-Ti and TiHx). With the simulation based on the kinetics and thermodynamics, quantitative behaviors of the hydrogen diffusion and the phase transformation were analyzed. The simulation results provide an insight into the diffusion process and improve the fundamental understanding of the mechanism of diffusion and phase transformation.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Kinetic modelling of in vitro data of PI3K, mTOR1, PTEN enzymes and on-target inhibitors Rapamycin, BEZ235, and LY294002

The phosphatidylinositide 3-kinases (PI3K) and mammalian target of rapamycin-1 (mTOR1) are two key targets for anti-cancer therapy. Predicting the response of the PI3K/AKT/mTOR1 signalling pathway to targeted therapy is made difficult because of network complexities. Systems biology models can help explore those complexities but the value of such models is dependent on accurate parameterisation. Motivated by a need to increase accuracy in kinetic parameter estimation, and therefore the predictive power of the model, we present a framework to integrate kinetic data from enzyme assays into a unified enzyme kinetic model. We present exemplar kinetic models of PI3K and mTOR1, calibrated on in vitro enzyme data and founded on Michaelis-Menten (MM) approximation. We describe the effects of an allosteric mTOR1 inhibitor (Rapamycin) and ATP-competitive inhibitors (BEZ2235 and LY294002) that show dual inhibition of mTOR1 and PI3K. We also model the kinetics of phosphatase and tensin homolog (PTEN), which modulates sensitivity of the PI3K/AKT/mTOR1 pathway to these drugs. Model validation with independent data sets allows investigation of enzyme function and drug dose dependencies in a wide range of experimental conditions. Modelling of the mTOR1 kinetics showed that Rapamycin has an IC50 independent of ATP concentration and that it is a selective inhibitor of mTOR1 substrates S6K1 and 4EBP1: it retains 40% of mTOR1 activity relative to 4EBP1 phosphorylation and inhibits completely S6K1 activity. For the dual ATP-competitive inhibitors of mTOR1 and PI3K, LY294002 and BEZ235, we derived the dependence of the IC50 on ATP concentration that allows prediction of the IC50 at different ATP concentrations in enzyme and cellular assays. Comparison of the drug effectiveness in enzyme and cellular assays showed that some features of these drugs arise from signalling modulation beyond the on-target action and MM approximation and require a systems-level consideration of the whole PI3K/PTEN/AKT/mTOR1 network in order to understand mechanisms of drug sensitivity and resistance in different cancer cell lines. We suggest that using these models in systems biology investigation of the PI3K/AKT/mTOR1 signalling in cancer cells can bridge the gap between direct drug target action and the therapeutic response to these drugs and their combinations.

Modelling of the time-dependent flow behaviour of lead-free solder pastes used for flip-chip assembly applications

The market for solder paste materials in the electronic manufacturing and assembly sector is very large and consists of material and equipment suppliers and end users. These materials are used to bond electronic components (such as flip-chip, CSP and BGA) to printed circuit boards (PCB's) across a range of dimensions where the solder interconnects can be in the order of 0.05mm to 5mm in size. The non-Newtonian flow properties exhibited by solder pastes during its manufacture and printing/deposition phases have been of practical concern to surface mount engineers and researchers for many years. The printing of paste materials through very small-sized stencil apertures is known to lead to increased stencil clogging and incomplete transfer of paste to the substrate pads. At these very narrow aperture sizes the paste rheology and particle-wall interactions become crucial for consistent paste withdrawal. These non-Newtonian effects must be understood so that the new paste formulations can be optimised for consistent printing. The focus of the study reported in this paper is the characterisation of the rheological properties of solder pastes and flux mediums, and the evaluation of the effect of these properties on the pastes' printing performance at the flip-chip assembly application level. Solder pastes are known to exhibit a thixotropic behaviour, which is recognised by the decrease in apparent viscosity of paste material with time when subjected to a constant shear rate. The proper characterisation of this time-dependent theological behaviour of solder pastes is crucial for establishing the relationships between the pastes' structure and flow behaviour; and for correlating the physical parameters with paste printing performance. In this paper, we present a number of methods which have been developed for characterising the time-dependent and non-Newtonian rheological behaviour of solder pastes and flux mediums as a function of shear rates. We also present results of the study of the rheology of the solder pastes and flux mediums using the structural kinetic modelling approach, which postulates that the network structure of solder pastes breaks down irreversibly under shear, leading to time and shear dependent changes in the flow properties. Our results show that for the solder pastes used in the study, the rate and extent of thixotropy was generally found to increase with increasing shear rate. The technique demonstrated in this study has wide utility for R&D personnel involved in new paste formulation, for implementing quality control procedures used in solder paste manufacture and packaging; and for qualifying new flip-chip assembly lines

A 330-360 GHz spectral survey of G34.3+0.15 .2. Chemical modelling

We describe a detailed depth-and time-dependent model of the molecular cloud associated with the ultracompact H II region G 34.3+0.15. Previous work on observations of NH3 and CS indicates that the molecular cloud has three distinct physical components:- an ultracompact hot core, a compact hot core and an extended halo. We have used the physical parameters derived from these observations as input to our detailed chemical kinetic modelling. The results of the model calculations are discussed with reference to the different chemistries occuring in each component and are compared with abundances derived from our recent spectral line survey of G 34.3+0.15 (Paper I).

Limitations of Global Kinetic Parameters for Automotive Application

With emission legislation becoming ever more stringent, automotive companies are forced to invest heavily into solutions to meet the targets set. To date the most effective way of treating emissions is through the use of catalytic converters. Current testing methods of catalytic converters whether being tested on a vehicle or in a lab reactor can be expensive and offer little information about what is occurring within the catalyst. It is for this reason and the increased price of precious metal that kinetic modelling has become a popular alternative to experimental testing.

A kinetic analysis methodology to elucidate the roles of metal, support and solvent for the hydrogenation of 4-phenyl-2-butanone over Pt/TiO2

The rate and, more importantly, selectivity (ketone vs aromatic ring) of the hydrogenation of 4-phenyl-2-butanone over a Pt/TiO2 catalyst have been shown to vary with solvent. In this study, a fundamental kinetic model for this multi-phase reaction has been developed incorporating statistical analysis methods to strengthen the foundations of mechanistically sound kinetic models. A 2-site model was determined to be most appropriate, describing aromatic hydrogenation (postulated to be over a platinum site) and ketone hydrogenation (postulated to be at the platinum–titania interface). Solvent choice has little impact on the ketone hydrogenation rate constant but strongly impacts aromatic hydrogenation due to solvent-catalyst interaction. Reaction selectivity is also correlated to a fitted product adsorption constant parameter. The kinetic analysis method shown has demonstrated the role of solvents in influencing reactant adsorption and reaction selectivity.