Sustainable Catalysis : Rational Pd Loading on MIL-101Cr-NH2 for More Efficient and Recyclable Suzuki-Miyaura Reactions

Palladium nanoparticles have been immobilized into an amino-functionalized metal-organic framework (MOF), MIL-101Cr-NH2, to form Pd@MIL-101Cr-NH2. Four materials with different loadings of palladium have been prepared (denoted as 4-, 8-, 12-, and 16wt%Pd@MIL-101Cr-NH2). The effects of catalyst loading and the size and distribution of the Pd nanoparticles on the catalytic performance have been studied. The catalysts were characterized by using scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier-transform infrared (FTIR) spectroscopy, powder X-ray diffraction (PXRD), N-2-sorption isotherms, elemental analysis, and thermogravimetric analysis (TGA). To better characterize the palladium nanoparticles and their distribution in MIL-101Cr-NH2, electron tomography was employed to reconstruct the 3D volume of 8wt%Pd@MIL-101Cr-NH2 particles. The pair distribution functions (PDFs) of the samples were extracted from total scattering experiments using high-energy X-rays (60keV). The catalytic activity of the four MOF materials with different loadings of palladium nanoparticles was studied in the Suzuki-Miyaura cross-coupling reaction. The best catalytic performance was obtained with the MOF that contained 8wt% palladium nanoparticles. The metallic palladium nanoparticles were homogeneously distributed, with an average size of 2.6nm. Excellent yields were obtained for a wide scope of substrates under remarkably mild conditions (water, aerobic conditions, room temperature, catalyst loading as low as 0.15mol%). The material can be recycled at least 10times without alteration of its catalytic properties.

Making the user more efficient: Design for sustainable behaviour

User behaviour is a significant determinant of a product’s environmental impact; while engineering advances permit increased efficiency of product operation, the user’s decisions and habits ultimately have a major effect on the energy or other resources used by the product. There is thus a need to change users’ behaviour. A range of design techniques developed in diverse contexts suggest opportunities for engineers, designers and other stakeholders working in the field of sustainable innovation to affect users’ behaviour at the point of interaction with the product or system, in effect ‘making the user more efficient’. Approaches to changing users’ behaviour from a number of fields are reviewed and discussed, including: strategic design of affordances and behaviour-shaping constraints to control or affect energyor other resource-using interactions; the use of different kinds of feedback and persuasive technology techniques to encourage or guide users to reduce their environmental impact; and context-based systems which use feedback to adjust their behaviour to run at optimum efficiency and reduce the opportunity for user-affected inefficiency. Example implementations in the sustainable engineering and ecodesign field are suggested and discussed.

Adsorption Calorimetry for Energy Conversion Technologies: Applications in Organic Photovoltaics, Catalysis, and Atomic Layer Deposition

Thesis (Ph.D.)--University of Washington, 2016-07

Simplified design method for energy dissipating devices in retrofitting of seismically isolated bridges

Abstract: Highway bridges have great values in a country because in case of any natural disaster they may serve as lines to save people’s lives. Being vulnerable under significant seismic loads, different methods can be considered to design resistant highway bridges and rehabilitate the existing ones. In this study, base isolation has been considered as one efficient method in this regards which in some cases reduces significantly the seismic load effects on the structure. By reducing the ductility demand on the structure without a notable increase of strength, the structure is designed to remain elastic under seismic loads. The problem associated with the isolated bridges, especially with elastomeric bearings, can be their excessive displacements under service and seismic loads. This can defy the purpose of using elastomeric bearings for small to medium span typical bridges where expansion joints and clearances may result in significant increase of initial and maintenance cost. Thus, supplementing the structure with dampers with some stiffness can serve as a solution which in turn, however, may increase the structure base shear. The main objective of this thesis is to provide a simplified method for the evaluation of optimal parameters for dampers in isolated bridges. Firstly, performing a parametric study, some directions are given for the use of simple isolation devices such as elastomeric bearings to rehabilitate existing bridges with high importance. Parameters like geometry of the bridge, code provisions and the type of soil on which the structure is constructed have been introduced to a typical two span bridge. It is concluded that the stiffness of the substructure, soil type and special provisions in the code can determine the employment of base isolation for retrofitting of bridges. Secondly, based on the elastic response coefficient of isolated bridges, a simplified design method of dampers for seismically isolated regular highway bridges has been presented in this study. By setting objectives for reduction of displacement and base shear variation, the required stiffness and damping of a hysteretic damper can be determined. By modelling a typical two span bridge, numerical analyses have followed to verify the effectiveness of the method. The method has been used to identify equivalent linear parameters and subsequently, nonlinear parameters of hysteretic damper for various designated scenarios of displacement and base shear requirements. Comparison of the results of the nonlinear numerical model without damper and with damper has shown that the method is sufficiently accurate. Finally, an innovative and simple hysteretic steel damper was designed. Five specimens were fabricated from two steel grades and were tested accompanying a real scale elastomeric isolator in the structural laboratory of the Université de Sherbrooke. The test procedure was to characterize the specimens by cyclic displacement controlled tests and subsequently to test them by real-time dynamic substructuring (RTDS) method. The test results were then used to establish a numerical model of the system which went through nonlinear time history analyses under several earthquakes. The outcome of the experimental and numerical showed an acceptable conformity with the simplified method.

Efficient daylighting approach by means of light-shelve device adequate for habitat program in Aarhus City

The concepts of light shelves consist of windows that have face towards the sun, which receive a vast quantity of energy that could be used for healthy day lighting. This paper debates a main assessment, investigates the optimization of daylight requirement by means of light shelves system. An experimental test was carried out assessing the measurements and lighting simulations of a model of a building in order to elucidate the characteristics of indoor lighting. Light shelf is an architectural element that permits daylight to enter deep into a building. It constitutes an optimal solution for an incorrect building orientation and less sunny days. The essential objective of this study is to highlight the vital role of light shelves in residential buildings in northern Europa where the requirement is to improve the daylight in the interior functional spaces. The main objects of this paper are to investigate the effect of daylight in the interior functional spaces using light shelves, the effect of natural light diffusion in interior space in the period of low daylight season, and glare effect in this field. This paper investigates a procedure for analysing the daylight performance using software habitat function

How to design the surface of peptide-loaded nanoparticles for efficient oral bioavailability?

International audience

Sustainability of protein production by bioreactor processes using wind and solar power as energy sources

Food production account for significant share of global environmental impacts. Impacts are global warming, fresh water use, land use and some non-renewable substance consumption like phosphorous fertilizers. Because of non-sustainable food production, the world is heading to different crises. Both food- and freshwater crises and also land area and phosphorous fertilizer shortages are one of many challenges to overcome in near future. The major protein sources production amounts, their impacts on environment and uses are show in this thesis. In this thesis, a more sustainable than conventional way of biomass production for food use is introduced. These alternative production methods are photobioreactor process and syngas-based bioreactor process. The processes’ energy consumption and major inputs are viewed. Their environmental impacts are estimated. These estimations are the compared to conventional protein production’s impacts. The outcome of the research is that, the alternative methods can be more sustainable solutions for food production than conventional production. However, more research is needed to verify the exact impacts. Photobioreactor is more sustainable process than syngas-based bioreactor process, but it is more location depended and uses more land area than syngas-based process. In addition, the technology behind syngas-based application is still developing and it can be more efficient in the future.

Modelling of an efficient dynamic smart solar photovoltaic power grid system

A smart solar photovoltaic grid system is an advent of innovation coherence of information and communications technology (ICT) with power systems control engineering via the internet [1]. This thesis designs and demonstrates a smart solar photovoltaic grid system that is selfhealing, environmental and consumer friendly, but also with the ability to accommodate other renewable sources of energy generation seamlessly, creating a healthy competitive energy industry and optimising energy assets efficiency. This thesis also presents the modelling of an efficient dynamic smart solar photovoltaic power grid system by exploring the maximum power point tracking efficiency, optimisation of the smart solar photovoltaic array through modelling and simulation to improve the quality of design for the solar photovoltaic module. In contrast, over the past decade quite promising results have been published in literature, most of which have not addressed the basis of the research questions in this thesis. The Levenberg-Marquardt and sparse based algorithms have proven to be very effective tools in helping to improve the quality of design for solar photovoltaic modules, minimising the possible relative errors in this thesis. Guided by theoretical and analytical reviews in literature, this research has carefully chosen the MatLab/Simulink software toolbox for modelling and simulation experiments performed on the static smart solar grid system. The auto-correlation coefficient results obtained from the modelling experiments give an accuracy of 99% with negligible mean square error (MSE), root mean square error (RMSE) and standard deviation. This thesis further explores the design and implementation of a robust real-time online solar photovoltaic monitoring system, establishing a comparative study of two solar photovoltaic tracking systems which provide remote access to the harvested energy data. This research made a landmark innovation in designing and implementing a unique approach for online remote access solar photovoltaic monitoring systems providing updated information of the energy produced by the solar photovoltaic module at the site location. In addressing the challenge of online solar photovoltaic monitoring systems, Darfon online data logger device has been systematically integrated into the design for a comparative study of the two solar photovoltaic tracking systems examined in this thesis. The site location for the comparative study of the solar photovoltaic tracking systems is at the National Kaohsiung University of Applied Sciences, Taiwan, R.O.C. The overall comparative energy output efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic monitoring system as observed at the research location site is about 72% based on the total energy produced, estimated money saved and the amount of CO2 reduction achieved. Similarly, in comparing the total amount of energy produced by the two solar photovoltaic tracking systems, the overall daily generated energy for the month of July shows the effectiveness of the azimuthal-altitude tracking systems over the 450 stationary solar photovoltaic system. It was found that the azimuthal-altitude dual-axis tracking systems were about 68.43% efficient compared to the 450 stationary solar photovoltaic systems. Lastly, the overall comparative hourly energy efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic energy system was found to be 74.2% efficient. Results from this research are quite promising and significant in satisfying the purpose of the research objectives and questions posed in the thesis. The new algorithms introduced in this research and the statistical measures applied to the modelling and simulation of a smart static solar photovoltaic grid system performance outperformed other previous works in reviewed literature. Based on this new implementation design of the online data logging systems for solar photovoltaic monitoring, it is possible for the first time to have online on-site information of the energy produced remotely, fault identification and rectification, maintenance and recovery time deployed as fast as possible. The results presented in this research as Internet of things (IoT) on smart solar grid systems are likely to offer real-life experiences especially both to the existing body of knowledge and the future solar photovoltaic energy industry irrespective of the study site location for the comparative solar photovoltaic tracking systems. While the thesis has contributed to the smart solar photovoltaic grid system, it has also highlighted areas of further research and the need to investigate more on improving the choice and quality design for solar photovoltaic modules. Finally, it has also made recommendations for further research in the minimization of the absolute or relative errors in the quality and design of the smart static solar photovoltaic module.

ESSAYS IN ENERGY, ENVIRONMENT AND TECHNOLOGICAL CHANGE

This dissertation studies technological change in the context of energy and environmental economics. Technology plays a key role in reducing greenhouse gas emissions from the transportation sector. Chapter 1 estimates a structural model of the car industry that allows for endogenous product characteristics to investigate how gasoline taxes, R&D subsidies and competition affect fuel efficiency and vehicle prices in the medium-run, both through car-makers' decisions to adopt technologies and through their investments in knowledge capital. I use technology adoption and automotive patents data for 1986-2006 to estimate this model. I show that 92% of fuel efficiency improvements between 1986 and 2006 were driven by technology adoption, while the role of knowledge capital is largely to reduce the marginal production costs of fuel-efficient cars. A counterfactual predicts that an additional $1/gallon gasoline tax in 2006 would have increased the technology adoption rate, and raised average fuel efficiency by 0.47 miles/gallon, twice the annual fuel efficiency improvement in 2003-2006. An R&D subsidy that would reduce the marginal cost of knowledge capital by 25% in 2006 would have raised investment in knowledge capital. This subsidy would have raised fuel efficiency only by 0.06 miles/gallon in 2006, but would have increased variable profits by $2.3 billion over all firms that year. Passenger vehicle fuel economy standards in the United States will require substantial improvements in new vehicle fuel economy over the next decade. Economic theory suggests that vehicle manufacturers adopt greater fuel-saving technologies for vehicles with larger market size. Chapter 2 documents a strong connection between market size, measured by sales, and technology adoption. Using variation consumer demographics and purchasing pattern to account for the endogeneity of market size, we find that a 10 percent increase in market size raises vehicle fuel efficiency by 0.3 percent, as compared to a mean improvement of 1.4 percent per year over 1997-2013. Historically, fuel price and demographic-driven market size changes have had large effects on technology adoption. Furthermore, fuel taxes would induce firms to adopt fuel-saving technologies on their most efficient cars, thereby polarizing the fuel efficiency distribution of the new vehicle fleet.

Energy norm a-posteriori error estimation for hp-adaptive discontinuous Galerkin methods for elliptic problems in three dimensions

We develop the energy norm a-posteriori error estimation for hp-version discontinuous Galerkin (DG) discretizations of elliptic boundary-value problems on 1-irregularly, isotropically refined affine hexahedral meshes in three dimensions. We derive a reliable and efficient indicator for the errors measured in terms of the natural energy norm. The ratio of the efficiency and reliability constants is independent of the local mesh sizes and weakly depending on the polynomial degrees. In our analysis we make use of an hp-version averaging operator in three dimensions, which we explicitly construct and analyze. We use our error indicator in an hp-adaptive refinement algorithm and illustrate its practical performance in a series of numerical examples. Our numerical results indicate that exponential rates of convergence are achieved for problems with smooth solutions, as well as for problems with isotropic corner singularities.

Design and Pilot Study for an Efficient High-Throughput Automated Computer-Vision Guided Intelligent De-Calyxing Machine for Post-Harvest Strawberry Processing

Strawberries harvested for processing as frozen fruits are currently de-calyxed manually in the field. This process requires the removal of the stem cap with green leaves (i.e. the calyx) and incurs many disadvantages when performed by hand. Not only does it necessitate the need to maintain cutting tool sanitation, but it also increases labor time and exposure of the de-capped strawberries before in-plant processing. This leads to labor inefficiency and decreased harvest yield. By moving the calyx removal process from the fields to the processing plants, this new practice would reduce field labor and improve management and logistics, while increasing annual yield. As labor prices continue to increase, the strawberry industry has shown great interest in the development and implementation of an automated calyx removal system. In response, this dissertation describes the design, operation, and performance of a full-scale automatic vision-guided intelligent de-calyxing (AVID) prototype machine. The AVID machine utilizes commercially available equipment to produce a relatively low cost automated de-calyxing system that can be retrofitted into existing food processing facilities. This dissertation is broken up into five sections. The first two sections include a machine overview and a 12-week processing plant pilot study. Results of the pilot study indicate the AVID machine is able to de-calyx grade-1-with-cap conical strawberries at roughly 66 percent output weight yield at a throughput of 10,000 pounds per hour. The remaining three sections describe in detail the three main components of the machine: a strawberry loading and orientation conveyor, a machine vision system for calyx identification, and a synchronized multi-waterjet knife calyx removal system. In short, the loading system utilizes rotational energy to orient conical strawberries. The machine vision system determines cut locations through RGB real-time feature extraction. The high-speed multi-waterjet knife system uses direct drive actuation to locate 30,000 psi cutting streams to precise coordinates for calyx removal. Based on the observations and studies performed within this dissertation, the AVID machine is seen to be a viable option for automated high-throughput strawberry calyx removal. A summary of future tasks and further improvements is discussed at the end.

A Framework for Energy-Efficiency in Smart Home Environments

Part 7: Cyber-Physical Systems

Modeling and analysis of thermoelectric energy conversion efficiency in nanostructures.

116 p.

HIGH VOLTAGE ELECTROPHORETIC DEPOSITION FOR ELECTROCHEMICAL ENERGY STORAGE AND OTHER APPLICATIONS

High voltage electrophoretic deposition (HVEPD) has been developed as a novel technique to obtain vertically aligned forests of one-dimensional nanomaterials for efficient energy storage. The ability to control and manipulate nanomaterials is critical for their effective usage in a variety of applications. Oriented structures of one-dimensional nanomaterials provide a unique opportunity to take full advantage of their excellent mechanical and electrochemical properties. However, it is still a significant challenge to obtain such oriented structures with great process flexibility, ease of processing under mild conditions and the capability to scale up, especially in context of efficient device fabrication and system packaging. This work presents HVEPD as a simple, versatile and generic technique to obtain vertically aligned forests of different one-dimensional nanomaterials on flexible, transparent and scalable substrates. Improvements on material chemistry and reduction of contact resistance have enabled the fabrication of high power supercapacitor electrodes using the HVEPD method. The investigations have also paved the way for further enhancements of performance by employing hybrid material systems and AC/DC pulsed deposition. Multi-walled carbon nanotubes (MWCNTs) were used as the starting material to demonstrate the HVEPD technique. A comprehensive study of the key parameters was conducted to better understand the working mechanism of the HVEPD process. It has been confirmed that HVEPD was enabled by three key factors: high deposition voltage for alignment, low dispersion concentration to avoid aggregation and simultaneous formation of holding layer by electrodeposition for reinforcement of nanoforests. A set of suitable parameters were found to obtain vertically aligned forests of MWCNTs. Compared with their randomly oriented counterparts, the aligned MWCNT forests showed better electrochemical performance, lower electrical resistance and a capability to achieve superhydrophpbicity, indicating their potential in a broad range of applications. The versatile and generic nature of the HVEPD process has been demonstrated by achieving deposition on flexible and transparent substrates, as well as aligned forests of manganese dioxide (MnO2) nanorods. A continuous roll-printing HVEPD approach was then developed to obtain aligned MWCNT forest with low contact resistance on large, flexible substrates. Such large-scale electrodes showed no deterioration in electrochemical performance and paved the way for practical device fabrication. The effect of a holding layer on the contact resistance between aligned MWCNT forests and the substrate was studied to improve electrochemical performance of such electrodes. It was found that a suitable precursor salt like nickel chloride could be used to achieve a conductive holding layer which helped to significantly reduce the contact resistance. This in turn enhanced the electrochemical performance of the electrodes. High-power scalable redox capacitors were then prepared using HVEPD. Very high power/energy densities and excellent cyclability have been achieved by synergistically combining hydrothermally synthesized, highly crystalline α-MnO2 nanorods, vertically aligned forests and reduced contact resistance. To further improve the performance, hybrid electrodes have been prepared in the form of vertically aligned forest of MWCNTs with branches of α-MnO2 nanorods on them. Large- scale electrodes with such hybrid structures were manufactured using continuous HVEPD and characterized, showing further improved power and energy densities. The alignment quality and density of MWCNT forests were also improved by using an AC/DC pulsed deposition technique. In this case, AC voltage was first used to align the MWCNTs, followed by immediate DC voltage to deposit the aligned MWCNTs along with the conductive holding layer. Decoupling of alignment from deposition was proven to result in better alignment quality and higher electrochemical performance.

Developing an Enhanced Model for Combined Heat and Air Infiltration Energy Simulation

The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building’s energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.