Iterative Linearized Density Matrix Propagation for Modeling Coherent Energy Transfer in Photosynthetic Light Harvesting

We present results of calculations [1] that employ a new mixed quantum classical iterative density matrix propagation approach (ILDM , or so called Is‐Landmap) [2] to explore the survival of coherence in different photo synthetic models. Our model studies confirm the long lived quantum coherence , while conventional theoretical tools (such as Redfield equation) fail to describe these phenomenon [3,4]. Our ILDM method is a numerical exactly propagation scheme and can be served as a bench mark calculation tools[2]. Result get from ILDM and from other recent methods have been compared and show agreement with each other[4,5]. Long lived coherence plateau has been attribute to the shift of harmonic potential due to the system bath interaction, and the harvesting efficiency is a balance between the coherence and dissipation[1]. We use this approach to investigate the excitation energy transfer dynamics in various light harvesting complex include Fenna‐Matthews‐Olsen light harvesting complex[1] and Cryptophyte Phycocyanin 645 [6]. [1] P.Huo and D.F.Coker ,J. Chem. Phys. 133, 184108 (2010) . [2] E.R. Dunkel, S. Bonella, and D.F. Coker, J. Chem. Phys. 129, 114106 (2008). [3] A. Ishizaki and G.R. Fleming, J. Chem. Phys. 130, 234111 (2009). [4] A. Ishizaki and G.R. Fleming, Proc. Natl. Acad. Sci. 106, 17255 (2009). [5] G. Tao and W.H. Miller, J. Phys. Chem. Lett. 1, 891 (2010). [6] P.Huo and D.F.Coker in preparation

Transport energy demand: techno-economic modelling and scenarios for Irish climate policy

The case for energy policy modelling is strong in Ireland, where stringent EU climate targets are projected to be overshot by 2015. Policy targets aiming to deliver greenhouse gas and renewable energy targets have been made, but it is unclear what savings are to be achieved and from which sectors. Concurrently, the growth of personal mobility has caused an astonishing increase in CO2 emissions from private cars in Ireland, a 37% rise between 2000 and 2008, and while there have been improvements in the efficiency of car technology, there was no decrease in the energy intensity of the car fleet in the same period. This thesis increases the capacity for evidenced-based policymaking in Ireland by developing techno-economic transport energy models and using them to analyse historical trends and to project possible future scenarios. A central focus of this thesis is to understand the effect of the car fleet‘s evolving technical characteristics on energy demand. A car stock model is developed to analyse this question from three angles: Firstly, analysis of car registration and activity data between 2000 and 2008 examines the trends which brought about the surge in energy demand. Secondly, the car stock is modelled into the future and is used to populate a baseline “no new policy” scenario, looking at the impact of recent (2008-2011) policy and purchasing developments on projected energy demand and emissions. Thirdly, a range of technology efficiency, fuel switching and behavioural scenarios are developed up to 2025 in order to indicate the emissions abatement and renewable energy penetration potential from alternative policy packages. In particular, an ambitious car fleet electrification target for Ireland is examined. The car stock model‘s functionality is extended by linking it with other models: LEAP-Ireland, a bottom-up energy demand model for all energy sectors in the country; Irish TIMES, a linear optimisation energy system model; and COPERT, a pollution model. The methodology is also adapted to analyse trends in freight energy demand in a similar way. Finally, this thesis addresses the gap in the representation of travel behaviour in linear energy systems models. A novel methodology is developed and case studies for Ireland and California are presented using the TIMES model. Transport Energy

Electrical machine characterisation and analysis for renewable energy applications

There has been an increased use of the Doubly-Fed Induction Machine (DFIM) in ac drive applications in recent times, particularly in the field of renewable energy systems and other high power variable-speed drives. The DFIM is widely regarded as the optimal generation system for both onshore and offshore wind turbines and has also been considered in wave power applications. Wind power generation is the most mature renewable technology. However, wave energy has attracted a large interest recently as the potential for power extraction is very significant. Various wave energy converter (WEC) technologies currently exist with the oscillating water column (OWC) type converter being one of the most advanced. There are fundemental differences in the power profile of the pneumatic power supplied by the OWC WEC and that of a wind turbine and this causes significant challenges in the selection and rating of electrical generators for the OWC devises. The thesis initially aims to provide an accurate per-phase equivalent circuit model of the DFIM by investigating various characterisation testing procedures. Novel testing methodologies based on the series-coupling tests is employed and is found to provide a more accurate representation of the DFIM than the standard IEEE testing methods because the series-coupling tests provide a direct method of determining the equivalent-circuit resistances and inductances of the machine. A second novel method known as the extended short-circuit test is also presented and investigated as an alternative characterisation method. Experimental results on a 1.1 kW DFIM and a 30 kW DFIM utilising the various characterisation procedures are presented in the thesis. The various test methods are analysed and validated through comparison of model predictions and torque-versus-speed curves for each induction machine. Sensitivity analysis is also used as a means of quantifying the effect of experimental error on the results taken from each of the testing procedures and is used to determine the suitability of the test procedures for characterising each of the devices. The series-coupling differential test is demonstrated to be the optimum test. The research then focuses on the OWC WEC and the modelling of this device. A software model is implemented based on data obtained from a scaled prototype device situated at the Irish test site. Test data from the electrical system of the device is analysed and this data is used to develop a performance curve for the air turbine utilised in the WEC. This performance curve was applied in a software model to represent the turbine in the electro-mechanical system and the software results are validated by the measured electrical output data from the prototype test device. Finally, once both the DFIM and OWC WEC power take-off system have been modeled succesfully, an investigation of the application of the DFIM to the OWC WEC model is carried out to determine the electrical machine rating required for the pulsating power derived from OWC WEC device. Thermal analysis of a 30 kW induction machine is carried out using a first-order thermal model. The simulations quantify the limits of operation of the machine and enable thedevelopment of rating requirements for the electrical generation system of the OWC WEC. The thesis can be considered to have three sections. The first section of the thesis contains Chapters 2 and 3 and focuses on the accurate characterisation of the doubly-fed induction machine using various testing procedures. The second section, containing Chapter 4, concentrates on the modelling of the OWC WEC power-takeoff with particular focus on the Wells turbine. Validation of this model is carried out through comparision of simulations and experimental measurements. The third section of the thesis utilises the OWC WEC model from Chapter 4 with a 30 kW induction machine model to determine the optimum device rating for the specified machine. Simulations are carried out to perform thermal analysis of the machine to give a general insight into electrical machine rating for an OWC WEC device.

The impact of whey protein isolate on energy balance regulation

Using C57BL/6J mice fed whey protein isolate (WPI) enriched high fat (HFD) or low-fat diets (LFD), this study tested the hypothesis that WPI directly impacts on adiposity by influencing lipid metabolism. WPI suppressed HFD-induced body fat and increased lean mass at 8 weeks of dietary challenge despite elevated plasma triacylglycerol (TAG) levels, suggesting reduced TAG storage. WPI reduced HFD-associated hypothalamic leptin and insulin receptor (IR) mRNA expression, and prevented HFD-associated reductions in adipose tissue IR and glucose transporter 4 expression. These effects were largely absent at 21 weeks of HFD feeding, however WPI increased lean mass and cause a trend towards decreased fat mass, with notable increased Lactobacillus and decreased Clostridium gut bacterial species. Increasing the protein to carbohydrate ratio enhanced the above effects, and shifted the gut microbiota composition away from the HFD group. Seven weeks of WPI intake with a LFD decreased insulin signalling gene expression in the adipose tissue in association with an increased fat accumulation. WPI reduced intestinal weight and length, suggesting a potential functional relationship between WPI, gastro-intestinal morphology and insulin related signalling in the adipose. Extending the study to 15 weeks, did not affect adipose fat weight, but decreased energy intake, weight gain and intestinal length. The functionality of protein sensing lysophosphatidic acid receptor 5 (LPA5) in 3T3-L1 pre-adipocytes was assessed. Over-expression of the receptor in 3T3-L1 pre-adipocytes provided a growth advantage to the cells and suppressed cellular differentiation into mature fat cells. In conclusion, the data demonstrates WPI impacts on adiposity by influencing lipid metabolism in a temporal manner, resulting possibly due to changes in lean mass, hypothalamic and adipose gene expression, gut microbiota and gastrointestinal morphology. The data also showed LPA5 is a novel candidate in regulating of preadipocyte growth and differentiation, and may mediate dietary protein effects on adipose tissue.

Development of a triple stage heat transformer for the recycling of low temperature heat energy

Absorption heat transformers are thermodynamic systems which are capable of recycling industrial waste heat energy by increasing its temperature. Triple stage heat transformers (TAHTs) can increase the temperature of this waste heat by up to approximately 145˚C. The principle factors influencing the thermodynamic performance of a TAHT and general points of operating optima were identified using a multivariate statistical analysis, prior to using heat exchange network modelling techniques to dissect the design of the TAHT and systematically reassemble it in order to minimise internal exergy destruction within the unit. This enabled first and second law efficiency improvements of up to 18.8% and 31.5% respectively to be achieved compared to conventional TAHT designs. The economic feasibility of such a thermodynamically optimised cycle was investigated by applying it to an oil refinery in Ireland, demonstrating that in general the capital cost of a TAHT makes it difficult to achieve acceptable rates of return. Decreasing the TAHT's capital cost may be achieved by redesigning its individual pieces of equipment and reducing their size. The potential benefits of using a bubble column absorber were therefore investigated in this thesis. An experimental bubble column was constructed and used to track the collapse of steam bubbles being absorbed into a hotter lithium bromide salt solution. Extremely high mass transfer coefficients of approximately 0.0012m/s were observed, showing significant improvements over previously investigated absorbers. Two separate models were developed, namely a combined heat and mass transfer model describing the rate of collapse of the bubbles, and a stochastic model describing the hydrodynamic motion of the collapsing vapour bubbles taking into consideration random fluctuations observed in the experimental data. Both models showed good agreement with the collected data, and demonstrated that the difference between the solution's temperature and its boiling temperature is the primary factor influencing the absorber's performance.

Dual-energy computed tomography with advanced postimage acquisition data processing: improved determination of urinary stone composition.

INTRODUCTION: The characterization of urinary calculi using noninvasive methods has the potential to affect clinical management. CT remains the gold standard for diagnosis of urinary calculi, but has not reliably differentiated varying stone compositions. Dual-energy CT (DECT) has emerged as a technology to improve CT characterization of anatomic structures. This study aims to assess the ability of DECT to accurately discriminate between different types of urinary calculi in an in vitro model using novel postimage acquisition data processing techniques. METHODS: Fifty urinary calculi were assessed, of which 44 had >or=60% composition of one component. DECT was performed utilizing 64-slice multidetector CT. The attenuation profiles of the lower-energy (DECT-Low) and higher-energy (DECT-High) datasets were used to investigate whether differences could be seen between different stone compositions. RESULTS: Postimage acquisition processing allowed for identification of the main different chemical compositions of urinary calculi: brushite, calcium oxalate-calcium phosphate, struvite, cystine, and uric acid. Statistical analysis demonstrated that this processing identified all stone compositions without obvious graphical overlap. CONCLUSION: Dual-energy multidetector CT with postprocessing techniques allows for accurate discrimination among the main different subtypes of urinary calculi in an in vitro model. The ability to better detect stone composition may have implications in determining the optimum clinical treatment modality for urinary calculi from noninvasive, preprocedure radiological assessment.

Cost of wind energy: comparing distant wind resources to local resources in the midwestern United States.

The best wind sites in the United States are often located far from electricity demand centers and lack transmission access. Local sites that have lower quality wind resources but do not require as much power transmission capacity are an alternative to distant wind resources. In this paper, we explore the trade-offs between developing new wind generation at local sites and installing wind farms at remote sites. We first examine the general relationship between the high capital costs required for local wind development and the relatively lower capital costs required to install a wind farm capable of generating the same electrical output at a remote site,with the results representing the maximum amount an investor should be willing to pay for transmission access. We suggest that this analysis can be used as a first step in comparing potential wind resources to meet a state renewable portfolio standard (RPS). To illustrate, we compare the cost of local wind (∼50 km from the load) to the cost of distant wind requiring new transmission (∼550-750 km from the load) to meet the Illinois RPS. We find that local, lower capacity factor wind sites are the lowest cost option for meeting the Illinois RPS if new long distance transmission is required to access distant, higher capacity factor wind resources. If higher capacity wind sites can be connected to the existing grid at minimal cost, in many cases they will have lower costs.

Exact analytical expressions for the potential of electrical double layer interactions for a sphere-plate system.

Exact, closed-form analytical expressions are presented for evaluating the potential energy of electrical double layer (EDL) interactions between a sphere and an infinite flat plate for three different types of interactions: constant potential, constant charge, and an intermediate case as given by the linear superposition approximation (LSA). By taking advantage of the simpler sphere-plate geometry, simplifying assumptions used in the original Derjaguin approximation (DA) for sphere-sphere interaction are avoided, yielding expressions that are more accurate and applicable over the full range of κa. These analytical expressions are significant improvements over the existing equations in the literature that are valid only for large κa because the new equations facilitate the modeling of EDL interactions between nanoscale particles and surfaces over a wide range of ionic strength.

Finite size effects in the presence of a chemical potential: A study in the classical nonlinear O(2) sigma model

In the presence of a chemical potential, the physics of level crossings leads to singularities at zero temperature, even when the spatial volume is finite. These singularities are smoothed out at a finite temperature but leave behind nontrivial finite size effects which must be understood in order to extract thermodynamic quantities using Monte Carlo methods, particularly close to critical points. We illustrate some of these issues using the classical nonlinear O(2) sigma model with a coupling β and chemical potential μ on a 2+1-dimensional Euclidean lattice. In the conventional formulation this model suffers from a sign problem at nonzero chemical potential and hence cannot be studied with the Wolff cluster algorithm. However, when formulated in terms of the worldline of particles, the sign problem is absent, and the model can be studied efficiently with the "worm algorithm." Using this method we study the finite size effects that arise due to the chemical potential and develop an effective quantum mechanical approach to capture the effects. As a side result we obtain energy levels of up to four particles as a function of the box size and uncover a part of the phase diagram in the (β,μ) plane. © 2010 The American Physical Society.

Where does energy R&D come from? Examining crowding out from energy R&D

Recent efforts to endogenize technological change in climate policy models demonstrate the importance of accounting for the opportunity cost of climate R&D investments. Because the social returns to R&D investments are typically higher than the social returns to other types of investment, any new climate mitigation R&D that comes at the expense of other R&D investment may dampen the overall gains from induced technological change. Unfortunately, there has been little empirical work to guide modelers as to the potential magnitude of such crowding out effects. This paper considers both the private and social opportunity costs of climate R&D. Addressing private costs, we ask whether an increase in climate R&D represents new R&D spending, or whether some (or all) of the additional climate R&D comes at the expense of other R&D. Addressing social costs, we use patent citations to compare the social value of alternative energy research to other types of R&D that may be crowded out. Beginning at the industry level, we find no evidence of crowding out across sectors-that is, increases in energy R&D do not draw R&D resources away from sectors that do not perform R&D. Given this, we proceed with a detailed look at alternative energy R&D. Linking patent data and financial data by firm, we ask whether an increase in alternative energy patents leads to a decrease in other types of patenting activity. While we find that increases in alternative energy patents do result in fewer patents of other types, the evidence suggests that this is due to profit-maximizing changes in research effort, rather than financial constraints that limit the total amount of R&D possible. Finally, we use patent citation data to compare the social value of alternative energy patents to other patents by these firms. Alternative energy patents are cited more frequently, and by a wider range of other technologies, than other patents by these firms, suggesting that their social value is higher. © 2011 Elsevier B.V.

Cost-effectiveness of electricity energy efficiency programs

We analyze the cost-effectiveness of electric utility ratepayer-funded programs to promote demand-side management (DSM) and energy efficiency (EE) investments. We specify a model that relates electricity demand to previous EE DSM spending, energy prices, income, weather, and other demand factors. In contrast to previous studies, we allow EE DSM spending to have a potential longterm demand effect and explicitly address possible endogeneity in spending. We find that current period EE DSM expenditures reduce electricity demand and that this effect persists for a number of years. Our findings suggest that ratepayer funded DSM expenditures between 1992 and 2006 produced a central estimate of 0.9 percent savings in electricity consumption over that time period and a 1.8 percent savings over all years. These energy savings came at an expected average cost to utilities of roughly 5 cents per kWh saved when future savings are discounted at a 5 percent rate. Copyright © 2012 by the IAEE. All rights reserved.

The potential of natural, photosynthetic pigments to improve the efficiency of dye-sensitized solar cells

Gemstone Team Grenergy

Analysis of ocean power extraction capabilites of a rotary wave energy conversion system

Gemstone Team WAVES (Water and Versatile Energy Systems)

Energy recovery in individuals with knee osteoarthritis.

OBJECTIVE: Pathological gaits have been shown to limit transfer between potential (PE) and kinetic (KE) energy during walking, which can increase locomotor costs. The purpose of this study was to examine whether energy exchange would be limited in people with knee osteoarthritis (OA). METHODS: Ground reaction forces during walking were collected from 93 subjects with symptomatic knee OA (self-selected and fast speeds) and 13 healthy controls (self-selected speed) and used to calculate their center of mass (COM) movements, PE and KE relationships, and energy recovery during a stride. Correlations and linear regressions examined the impact of energy fluctuation phase and amplitude, walking velocity, body mass, self-reported pain, and radiographic severity on recovery. Paired t-tests were run to compare energy recovery between cohorts. RESULTS: Symptomatic knee OA subjects displayed lower energetic recovery during self-selected walking speeds than healthy controls (P = 0.0018). PE and KE phase relationships explained the majority (66%) of variance in recovery. Recovery had a complex relationship with velocity and its change across speeds was significantly influenced by the self-selected walking speed of each subject. Neither radiographic OA scores nor subject self-reported measures demonstrated any relationship with energy recovery. CONCLUSIONS: Knee OA reduces effective exchange of PE and KE, potentially increasing the muscular work required to control movements of the COM. Gait retraining may return subjects to more normal patterns of energy exchange and allow them to reduce fatigue.

PDLA a potential new potent topical analgesic: a case report.

Polymer D-lactic acid (PDLA) is a hydrogel that has been shown to sequester L-lactate (lactate). This reaction is rapid, spontaneous, and non-enzymatic. Lactate has been shown to have many functions within the nervous system including its use as a secondary fuel to sustain neural activity and as a neuromodulator. In the central nervous system, lactate is produced in glial cells and shuttled to neurons to be used mostly as a fuel. Lactate dehydrogenase (LDH)1 is the predominant LDH isoform within neurons and unlike LDH5, it preferentially converts lactate to pyruvate which can be used to produce adenosine triphosphate (ATP). Considering that lactate is intimately involved in the sustenance of neural activity, PDLA was applied to an open wound and its effects were examined. The results showed that the application of PDLA induced topical analgesia. This may be the first report to demonstrate that sequestering lactate, a source of energy required to sustain the firing of action potentials in neurons, may produce analgesia.