A facile, one-step, template-less, surfactant-free hydrothermal process, using a metal salt as the precursor, is developed to prepare submicrometer sized mesoporous TiO 2 nanoparticle aggregates (NPGs). The as-prepared TiO 2 NPGs are crystalline of the anatase phase, with a high specific surface area of 166 m 2 /g, an average pore size of 8.9 nm, and an average NPG size of 840 nm. With these NPGs, a new form of composite photoanode, consisting of the mesoporous TiO 2 NPGs and xerogels, is proposed for high efficiency dye-sensitized solar cells (DSSCs). TiO 2 xerogels are incorporated into the TiO 2 NPGs layer with an impregnation process to form the TiO 2 NPGs/xerogels composite. A high power conversion efficiency of 8.41% is achieved for DSSCs based on the TiO 2 NPGs/xerogels composite photoanode, representing a 38% efficiency boost over the efficiency of 6.11% achieved with a P25 TiO 2 based cell. The success of the present composite TiO 2 nanostructure can be attributed to the effective utilization of the inter-NPG space with the infiltration of the TiO 2 xerogels, the excellent structural connectivity within and across the NPG and xerogel domains for fast electron transport, the high specific surface areas of both the NPGs and xerogels for providing abundant dye adsorption for generation of photoinduced electrons, the formation of a TiO 2 xerogel blocking layer on top of the photoanode substrate, and the submicrometer size of the NPGs for much improved light harvesting efficiency. This new type of composite photoanode, different from the 0D/1D nanostructure based ones, proves effective by taking structural advantages from both constituent nanostructures, the mesoprous NPGs and xerogels, and opens up a new way of thinking in the structural design of the photoanodes.
. A generic GIS-based method for small Pumped Hydro Energy Storage (PHES) potential evaluation at large scale. Applied Energy, Elsevier, 2017, 197, pp.241 -253 AbstractThe increasing share of weather-dependent renewable energies in power systems creates a need for energy storage technologies to reduce the impacts of variable production. The most mature technology to store energy on the grid remains Pumped Hydro Energy Storage (PHES). The potential of high-energy sites has already been assessed in Europe by the EU JRC, considering mostly dams and reservoirs from global European databases which include only massive water bodies. This paper focuses on estimating the potential for small-PHES, proven to have lower environmental impact and an positive impact on grid balance and reliability. A generic method is designed, able to evaluate a global PHES storage capacity at large scale. It considers both existing lakes and natural depressions suitable to be filled for PHES purposes. The volume of filled lakes is estimated using the surrounding topography. The method is organized so that the "heavy" calculations, i.e. sink detection, volume evaluation, constraints verification etc. are run only once. Consequently, the actual potential estimation phase only includes fast calculations and can be integrated in a loop for carrying out a sensitivity analysis. The proposed method is then applied considering France as a test case. Suitable environmental, land-use and structural constraints are applied to eliminate irrelevant sites. The analysis leads to an estimated value of the small-PHES potential in France, which ranges from 14 GWh when only existing lakes are considered to 33 GWh when lakes and depressions are considered. These estimations represent respectively 8% and 18% of the current hydro storage capacity in France. Thanks to a global sensitivity analysis, factors like the maximum distance between lakes, the maximum altitude of the sites, and the distance to the electrical grid are shown to have the most influence on the global evaluated potential, which is further sensitized. Lastly, another application is suggested that makes it possible to select the connections to be built first within a restricted area, based on a cost-per-energy-like approach. It uses the connections between reservoirs detected at large geographical scale.
Reduction of energy consumption in the building sector has been identified as a major instrument to tackle global climate change and improve sustainability. In this paper, we propose a methodology to address a retrofit planning problem at a community level, with a building resolution. The resulting tool helps local decision-makers identify pertinent actions to improve the environmental behavior of their territories. Two building retrofit levers are considered, namely envelope insulation and heating systems replacement. Retrofit planning is treated here as a single-objective optimization problem aimed at reducing the total costs of retrofit actions by minimizing their net present value. A multidimensional multiple-choice knapsack problem formulation is proposed through the adoption of adequate decision variables. It suitably balances the complexity induced by the large number of potential retrofit action combinations and the number of variables in the problem and permits a linear formulation. An optimization of virtual building stocks is performed to highlight the developed model's capacity to tackle large problems (5,000 buildings) in a few minutes. Finally, three analyses finally are led on a real case-study territory, featuring both appropriate retrofit solutions and building stock information. Long-term evaluation of retrofit strategies over the shortterm results in an additional 10% reduction of energy consumption and greenhouse gases emissions and encourages thermal insulation. When targeting a 40% reduction in energy demand, retrofit costs ranging from 20 to 800e/m 2 are observed. Finally, the developed method was used to draw a CO 2 abatement cost curve at territory level. A 70% reduction of emissions can be achieved with costs under 50 e/tCO 2 e.
In the last decades, renewable energy sources have been increasing their shares in the world energy market. In addition to the ecological benefits, this trend can have adjunct benefits, for example for distribution system operators: a gain in their grid sizing. Indeed, installation of decentralized production, when used in a selfconsumption approach, can lead to reduction of the consumption peaks. This work is willing to quantify what grid sizing reduction a distribution system operator can expect, knowing the renewable energies penetration rate on a MV feeder. To do so, a description of the actual sizing strategy is first described. Estimation of electricity demand is performed using a bottom-up simulation method while photovoltaics and wind power production are evaluated with reanalysis data coupled with a new method to inject variability to the smooth curves. This procedure leads to a new sizing power which can be used, guaranteeing an equivalent quality of supply for consumers. For the tested MV feeders, a maximum reduction of about 4 % of the sizing power is observed. Lastly, an analysis of the under-sizing risk is carried out, characterizing the error in the new sizing power estimation with the number of scenarios taken into account.
Reduction of the energy consumption is a key lever to tackle climate change, but identification of the retrofit actions to undertake within a building stock remains a challenging scientific problem. This paper presents a complete methodology able to design action plans at a territory level with a building resolution. The economic and energetic modeling of the retrofit context is detailed before introducing a linear 0-1 optimization formulation which is used to arbitrate between both building envelope insulation and heating system replacement measures. A 500 buildings territory study case is then presented to illustrate the potential of the developed tool.
Background Prostate cancer is one of the most common forms of cancer in men. An imaging technique for its diagnosis is [68Ga]-prostate specific membrane antigen (68Ga-PSMA-11) positron emission tomography (PET). Gallium 68 (68Ga) is typically obtained using a germanium 68/gallium 68 (68Ge/68Ga) generator, allowing for the diagnostic drug to be made readily available in the nuclear medicine department through elution. To meet the increasing demand for 68Ga labeled peptides and to reduce the cost of radiosynthesis, it is therefore necessary to optimize the elution process of 68Ge/68Ga generators. This study aims to identify the most effective approach for optimizing radiosynthesis using double elution in parallel of two 68Ge/68Ga generators. Two methods have been tested: one using prepurification, and the other using fractionated elution. Results Five synthesis sequences were conducted using each method. The mean labeling yields for double elution with prepurification were 45.8 ± 29.4 (mean ± standard deviation) and none met the required criteria. The mean labeling yields for the fractionated double elution were 97.5 ± 1.9 (mean ± standard deviation) meeting the criteria, significantly superior to the prepurification method (p=0.012), and similar to those of simple elution. There was no significant difference in the elution yields of both methods. Conclusions This study showed that fractionated double elution from 68Ge/68Ga generators produced a significantly higher labeling yield than double elution with prepurification, resulting in a larger activity recovered by radiosynthesis, and thereby allowing for more diagnostic tests to be performed. Additionally, this method does not add complexity or synthesis time compared to simple elution labeling, and could also be applied to other 68Ga labeled peptides.
This paper participates in the challenging data science opportunity offered by the growing number of databases made available to public institutions. It presents an innovative method to match household-scale databases using address information. The developed algorithm authorizes different matching qualities, depending on the reliability of the link between the paired elements. This work was carried out in collaboration with the French DSO Enedis, which provided valuable customer information that was matched with a national database describing dwellings. The matching algorithm performances are analyzed, and adjustments are proposed to improve the matching quality in urban, suburban and rural contexts. Lastly, two basic characterization analyses were made to highlight the potential of these consolidated databases.
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