Wind Plant System Engineering Through Optimization of Layout and Yaw Control
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The concerns about greenhouse gas emissions have triggered investigations among the scientific community. The accelerated carbonation curing has been used as a tool to capture CO 2 at early stages of cement-based material fabrication. In a previous study, the authors quantified the amount of CO 2 captured in portland cement pastes by thermal analysis, at high relative humidity precure conditions. In the present work, the authors quantified the amount of CO 2 captured in binary pastes derived from engineered cementitious composites (ECC), a family of composites worldwide used, whose one of their features is the precure at low relative humidity conditions. Two types of ECC pastes (1.2 and 2.2) were submitted to 4 h and 24 h of accelerated carbonation after 24 h of initial hydration. Using thermogravimetry and derivative thermogravimetry, the amounts of captured CO 2 and respective carbonation degrees were quantified. Furthermore, the results showed that ECC paste 1.2 presented the highest values of captured CO 2 and carbonation degree, considering all reactive components. In contrast, ECC paste 2.2 presented the highest values of these two parameters, when considering only portland cement as reactive component. For both pastes, the hydration degrees of the carbonated samples were higher than those of the non-carbonated references, indicating that in the used operating conditions, carbonation enhances ECC paste hydration.
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Domain walls (DWs) have become an essential component in nanodevices based on ferroic thin films. The domain configuration and DW stability, however, are strongly dependent on the boundary conditions of thin films, which make it difficult to create complex ordered patterns of DWs. Here, it is shown that novel domain structures, that are otherwise unfavorable under the natural boundary conditions, can be realized by utilizing engineered nanosized structural defects as building blocks for reconfiguring DW patterns. It is directly observed that an array of charged defects, which are located within a monolayer thickness, can be intentionally introduced by slightly changing substrate temperature during the growth of multiferroic BiFeO 3 thin films. These defects are strongly coupled to the domain structures in the pretemperature-change portion of the BiFeO 3 film and can effectively change the configuration of newly grown domains due to the interaction between the polarization and the defects. Thus, two types of domain patterns are integrated into a single film without breaking the DW periodicity. The potential use of these defects for building complex patterns of conductive DWs is also demonstrated.
Lactic acid represents an important class of commodity chemicals, which can be produced by microbial cell factories. However, due to the toxicity of lactic acid at lower pH, microbial production requires the usage of neutralizing agents to maintain neutral pH. Zygosaccharomyces bailii, a food spoilage yeast, can grow under the presence of organic acids used as food preservatives. This unique trait of the yeast might be useful for producing lactic acid. With the goal of domesticating the organic acid!tolerant yeast as a metabolic engineering host, seven Z. bailii strains were screened in a minimal medium with 10 g/L of acetic, or 60 g/L of lactic acid at pH 3. The Z. bailii NRRL Y7239 strain was selected as the most robust strain to be en- gineered for lactic acid production. By applying a PAN!ARS!based CRISPR!Cas9 system consisting of a transfer RNA promoter and NAT selection, we demonstrated the targeted deletion of ADE2 and site!specific integration of Rhizopus oryzae ldhA coding for lactate dehydrogenase into the PDC1 locus. The resulting pdc1::ldhA strain produced 35 g/L of lactic acid without ethanol production. Here, this study de- monstrates the feasibility of the CRISPR!Cas9 system in Z. bailii, which can be applied for a fundamental study of the species.
To further improve the energy conversion efficiency of internal combustion engine, the transient and complex air flow movement inside the cylinder needs to be better understood and controlled. Although the in-cylinder flow fields are highly stochastic with strong cycle-to-cycle fluctuations, machine learning can still provide an efficient way to learn and regress the complex flow movement process inside the cylinder. In this work, a bidirectional recurrent neural network (bi-RNN) model with long short-term memory was applied to predict the in-cylinder flow fields at different time steps using training data from mull-cycle particle image velocimetry (PIV) measurements. To evaluate the agreement between the true and predicted flow fields, structure and magnitude comparison indices are calculated both globally and locally. The comparison results show that the bi-RNN model can accurately predict the bulk flow and vortex motions from early intake stroke to compression stroke. This work demonstrates that the machine learning model has the potential to predict the underlying dynamics of the interaction between in-cylinder flows and provides a reliable way to improve temporal resolution in PIV flow data to better reveal transient in-cylinder flow features.
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Early in fiscal year 2016 (FY16), a fuel efficiency 'merit function' was developed to provide a simple tool to evaluate the potential thermal efficiency benefits of various fuels when multiple fuel properties or performance metrics are changing simultaneously. It has also proven to be useful for evaluating various fuel candidates and provides a useful framework for capturing and summarizing results from multiple projects within the Co-Optima Fuel Properties and Advanced Engine Development research portfolios. The objective of this report is to collect pertinent research results from FY16 and the first half of FY17, and to integrate them into an improved merit function.
A 3D graphene foam produced by the chemical vapor deposition (CVD) technique is recognized as an effective nanofiller material, as it does not agglomerate in the matrix. Though CVD facilitates pristine graphene foam production, the method poses limitations in developing large-scale 3D graphene composite foams as advanced engineering materials. In this paper, a freeze-drying (FD) process is used to produce a composite 3D foam, which is a mixture of graphene nanoplatelet (GNP) and a low-temperature co-fired ceramic (LTCC). The freeze-dried GNP-LTCC reticulated 3D composite foam has an average pore size ranging from 70 to 100 μm. Pore size is varied by regulating the heat transfer rate during the freezing process using a thermally conductive aluminum (Al) mold and a thermally insulating acrylonitrile butadiene styrene (ABS) mold. Computational thermal modeling is used to visualize the heat transfer and its effect on foam pore size. Subsequently, a freeze-dried GNP-LTCC composite foam is embedded into the LTCC matrix to form a hierarchical assembly by a spark plasma technique without compromising the 3D structure of the FD foam. This study established that a simple, eco-friendly, and scalable processing methodology can produce advanced graphene-based 3D composite foams as the future tailorable nanofillers for designing multimatrix materials.
Heteroepitaxial coupling at complex oxide interfaces introduces a powerful tool for engineering the charge degree of freedom in strongly correlated materials, which can be utilized to achieve tailored functionalities that are inaccessible in the bulk form. In this work, the charge-transfer effect between two strongly correlated oxides, Sm 0.5 Nd 0.5 NiO 3 (SNNO) and La 0.67 Sr 0.33 MnO 3 (LSMO), is exploited to realize a giant enhancement of the ferroelectric field effect in a prototype Mott field-effect transistor. By switching the polarization field of a ferroelectric Pb(Zr,Ti)O 3 (PZT) gate, nonvolatile resistance modulation in the Mott transistors with single-layer SNNO and bilayer SNNO/LSMO channels is induced. For the same channel thickness, the bilayer channels exhibit up to two orders of magnitude higher resistance-switching ratio at 300 K, which is attributed to the intricate interplay between the charge screening at the PZT/SNNO interface and the charge transfer at the SNNO/LSMO interface. X-ray absorption spectroscopy and X-ray photoelectron spectroscopy studies of SNNO/LSMO heterostructures reveal about 0.1 electron per 2D unit cell transferred between the interfacial Mn and Ni layers, which is corroborated by first-principles density functional theory calculations. The study points to an effective strategy to design functional complex oxide interfaces for developing high-performance nanoelectronic and spintronic applications.
Microstructure engineering is an effective strategy to reduce lattice thermal conductivity (JG) and enhance the thermoelectric figure of merit (zT). Through a new process based on melt-centrifugation to squeeze out excess eutectic liquid, microstructure modulation is realized to manipulate the formation of dislocations and clean grain boundaries, resulting in a porous network with a platelet structure. In this way, phonon transport is strongly disrupted by a combination of porosity, pore surfaces/junctions, grain boundaries, and lattice dislocations. These collectively result in a ≈60% reduction of JG compared to zone melted ingot, while the charge carriers remain relatively mobile across the liquid-fused grains. This porous material displays a zT value of 1.2, which is higher than fully dense conventional zone melted ingots and hot pressed (Bi,Sb) 2 Te 3 alloys. A segmented leg of melt-centrifuged Bi 0.5 Sb 1.5 Te 3 and Bi 0.3 Sb 1.7 Te 3 could produce a high device ZT exceeding 1.0 over the whole temperature range of 323-523 K and an efficiency up to 9%. Here, we demonstrate a method for synthesizing high-efficiency porous thermoelectric materials through an unconventional melt-centrifugation technique.
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