Recovery of excreted n-butanol from genetically engineered cyanobacteria cultures: Process modelling to quantify energy and economic costs of different separation technologies

The photoautotrophic production of excreted biofuels from genetically engineered cyanobacteria and microalgae represents a new and promising alternative to conventional algal fuel technologies. N-butanol is a particularly promising fuel product, as it can be directly used in petroleum engines, and has been successfully expressed in species of Synechococcus elongates 7942 and Synechocystis sp. PCC 6803. However, the high energy requirements of recovering butanol from dilute mixtures can easily outweigh the energy content of the fuel and must be carefully assessed and optimized. Consequently, the recovery of butanol was modelled using four of the most promising butanol separation technologies (distillation, gas stripping, pervaporation and ionic liquid extraction) to calculate the minimum butanol culture concentrations required to render the process energy-positive. With a breakeven concentration of only 3.7 g L -1 , ionic liquid extraction proved much more efficient than the distillation base-case scenario (9.3 g L -1 ), whilst neither pervaporation (10.3 g L -1 ) nor gas stripping (16.9 g L -1 ) could compete on an energy basis with distillation. Despite this, due to the high costs of the ionic liquid solvent, the lowest capital costs are obtained for distillation (pilot plant scale, butanol culture concentrations of 10 g L -1 ), whilst pervaporation carries the lowest utility costs, as a result of its low electrical energy demand. Although currently achieved maximum n-butanol culture concentrations are significantly below the calculated break-even values for all four technologies, the present work provides an important threshold for future strain development. Moreover, the recovery of side-products from purged biomass could help to reduce the costs associated with biofuel production

Carbon capture from pulverized coal power plant (PCPP): Solvent performance comparison at an industrial scale

Coal is the most abundant fossil fuel on the planet. However, power generation from coal results in large amounts of greenhouse gas emissions. Solvent-based carbon capture is a relatively mature technology which can potentially mitigate these emissions. Although, much research has been done on this topic, single-point performance analysis of capture plant and ignoring operational characteristics of the upstream power plant may result in unrealistic performance assessments. This paper introduces a new methodology to assess the performance of CO2 capture solvents. The problem is posed as retrofitting an existing pulverized coal power plant with post-combustion carbon capture using two solvents: CDRMax, a recently developed amine-promoted buffer salt (APBS) solvent by Carbon Clean Solutions Limited (CCSL) and the monoethanolamine (MEA) baseline solvent. The features of interest include model development and validation using pilot plant data, as well as integrated design and control of the capture process. The emphasis is on design and operation of the capture plant, when integrated with the upstream coal-fired power plant, subject to variations in the electricity load. The results suggest that optimal design and operation of capture plant can significantly mitigate the energetic penalties associated with carbon capture form the flue gas, while providing effective measures for comparing solvent performances under various scenarios

Processing and characterization of nanostructured Grade 2 Ti processed by combination of warm isothermal ECAP and extrusion

In this study, combined multi pass equal channel angular pressing (ECAP), and subsequent warm extrusion at different temperatures are performed on commercial purity titanium. Mechanical and microstructural evolutions are then investigated. Since it was observed that the four passes ECAP processed sample showed the best strength and reasonable elongation, this sample was selected for studying the extrusion temperature effects on the structure and mechanical properties of Grade 2 titanium. Therefore, the 4th passes ECAP processed sample was extruded at different temperatures of 300 °C, 350 °C, 400 °C, 450 °C and 500 °C. The result revealed that the best mechanical properties were achieved from the specimen processed by four passes ECAP followed by warm extrusion at 300 °C. The strength, and hardness of this sample were considerably improved in comparison with that of the unprocessed sample. Also, its ultra-fine grained and nanograined microstructure were homogeneous, with a grain size ranged from 40 to 200 nm with an average grain size of about 123 nm. It was seen that the mechanical properties of some samples after applying this combined process (ECAP + warm extrusion) are comparable with those of Grade 5 titanium which is commonly used in medical applications but contains alloying elements that are toxic to human health

Benefit of magnesium-25 carrying porphyrin-fullerene nanoparticles in experimental diabetic neuropathy

Diabetic neuropathy (DN) is a debilitating disorder occurring in most diabetic patients without a viable treatment yet. The present work examined the protective effect of 25Mg-PMC16 nanoparticle (porphyrin adducts of cyclohexil fullerene-C60) in a rat model of streptozotocin (STZ)-induced DN. 25Mg-PMC16 (0.5 lethal dose50 [LD50]) was administered intravenously in two consecutive days before intraperitoneal injection of STZ (45 mg/kg). 24Mg-PMC16 and MgCl2 were used as controls. Blood 2,3-diphosphoglycerate (2,3-DPG), oxidative stress biomarkers, adenosine triphosphate (ATP) level in dorsal root ganglion (DRG) neurons were determined as biomarkers of DN. Results indicated that 2,3-DPG and ATP decreased whereas oxidative stress increased by induction of DN which all were improved in 25Mg-PMC16-treated animals. No significant changes were observed by administration of 24Mg-PMC16 or MgCl2 in DN rats. It is concluded that in DN, oxidative stress initiates injuries to DRG neurons that finally results in death of neurons whereas administration of 25Mg-PMC16 by release of Mg and increasing ATP acts protectively

The role of magnesium sulfate in the intensive care unit

Magnesium (Mg) has been developed as a drug with various clinical uses. Mg is a key cation in physiological processes, and the homeostasis of this cation is crucial for the normal function of body organs. Magnesium sulfate (MgSO4) is a mineral pharmaceutical preparation of magnesium that is used as a neuroprotective agent. One rationale for the frequent use of MgSO4 in critical care is the high incidence of hypomagnesaemia in intensive care unit (ICU) patients. Correction of hypomagnesaemia along with the neuroprotective properties of MgSO4 has generated a wide application for MgSO4 in ICU

PROTECTIVE EFFECT OF IRIS GERMANICA L. IN Β-AMYLOID-INDUCED ANIMAL MODEL OF ALZHEIMER’S DISEASE

Background: Alzheimer's disease (AD) is the most common cause of dementia that is an irretrievable chronic neurodegenerative disease. In the current study, we have examined the therapeutic effects of Iris germanica extract on Amyloid β (Aβ) induced memory impairment. Materials and Methods: Wistar rats were divided into five groups of 8 per each. Groups were as followed: control group which were normal rats without induction of AD, Aβ group which received Aβ (50 ng/side), iris 100 group which received Aβ + Iris (100 mg/kg), iris 200 group which received Aβ + Iris (200 mg/kg), and iris 400 group which received Aβ + Iris (400 mg/kg). AD was established by intrahippocampal injection of 50 ng/μl/side Aβ1-42. The day after surgery, animals in treatment groups received different doses of the aqueous extract of Iris by gavage for 30 days. Morris water maze test (MWM) was performed to assess the effects of I. germanica on learning and memory of rats with Aβ induced AD. Results: Data from MWM tests, including escape latency and traveled distance, demonstrated that I. germanica extract could markedly improve spatial memory in comparison to control. Moreover, the plant had a significantly better effect on the performance of AD rats in the probe test. Conclusion: I. germanica extract can successfully reverse spatial learning dysfunction in an experimental model of AD. Further neuro psyco-pharmacological studies are mandatory to reveal the mechanism of action of this natural remedy in the management of AD symptoms

Integrated design and control with a focus on control structures

The common practice is to design chemical processes and their control systems in sequence. However, process design and control share important decisions, and when the process design is fixed there is little room left to improve the control performance. These observations suggest process design and control should be integrated. The conventional framework for integrated design and control is to optimize the process, its control structure, and controllers, simultaneously. However, there are numerical as well as conceptual complexities associated with optimization of controllers. This research proposes integrated design and control based on perfect control. In the proposed optimization framework, an inversely controlled process model replaces the models of process and its controllers. Although the process and its control structure are optimized simultaneously, the complexities associated with controllers are disentangled from the problem formulation. The thesis starts with introduction of the relevant concepts and review of literature in Chapters 1 and 2. Then, in Chapter 3, the steady-state and dynamic formulations of the proposed framework are presented. A steady-state inversely controlled process model achieves a higher degree of complexity reduction and ensures regulatory steady-state operability. However, at the price of higher modelling efforts, a dynamic inversely controlled process model ensures functional controllability as well. The proposed steady-state and dynamic optimization frameworks are demonstrated using several case studies. The proposed steady-state framework was applied for optimal control structure selection of a distillation train in Chapter 4 and integrated design and control of a reactive distillation column in Chapter 5. The proposed dynamic optimization framework was applied for the case of two heat-integrated series reactors in Chapter 6. The proposed optimization frameworks were successful in establishing the trade-off between control and process objectives. Finally, the thesis concludes with discussions, critical evaluation of the research and suggestions for future research in Chapter 7