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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Molecular insights and future frontiers in cell photosensitization for solar-driven CO 2 conversion

The conversion of CO 2 to value-added products powered with solar energy is an ideal solution to establishing a closed carbon cycle. Combining microorganisms with light-harvesting nanomaterials into photosynthetic biohybrid systems (PBSs) presents an approach to reaching this solution. Metabolic pathways precisely evolved for CO 2 fixation selectively and reliably generate products. Nanomaterials harvest solar light and biocompatibly associate with microorganisms owing to similar lengths scales. Although this is a nascent field, a variety of approaches have been implemented encompassing different microorganisms and nanomaterials. To advance the field in an impactful manner, it is paramount to understand the molecular underpinnings of PBSs. In this perspective, we highlight studies inspecting charge uptake pathways and singularities in photosensitized cells. We discuss further analyses to more completely elucidate these constructs, and we focus on criteria to be met for designing photosensitizing nanomaterials. As a result, we advocate for the pairing of microorganisms with naturally occurring and highly biocompatible mineral-based semiconductor nanomaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Correlating the influence of porosity, tortuosity, and mass loading on the energy density of LiNi 0.6 Mn 0.2 Co 0.2 O 2 cathodes under extreme fast charging (XFC) conditions

Extreme fast charging capabilities along with high energy density of Li-ion batteries are the key factors to increase the adoption of electric vehicles while eliminating the problem of range anxiety. The U.S Department of Energy has a goal of <12 min charging time with energy density of > 200 Wh kg -1 . A combined improvement in the electrode architecture, electrolyte properties, and separator membrane is necessary to achieve this goal. Cells with thin electrodes are capable of extreme fast charging at the expense of low energy density and high cost. Electrode engineering can maximize energy density. In this work, the influence of porosity, mass loading and charging protocols on capacity and energy density and electrode kinetics are investigated under extreme fast charging conditions. Increasing the mass loading from 11.5 mg cm -2 to 25 mg cm -2 compromises the rate performance due to the mass transport limitation and underutilization of thick electrodes. Furthermore, reducing the electrode porosity from 50% to 35% improves the rate performance ascribed to shorter Li ion diffusion length. Symmetric cells are cycled to verify the performance of the half cells, suggesting that Li metal plating is the rate limiting step under high current density.

25 ENERGY STORAGE↗
DOE OSTI2022

High voltage stable cycling of all-solid-state lithium metal batteries enabled by top-down direct fluorinated poly (ethylene oxide)-based electrolytes

Poly (ethylene oxide) (PEO)-based solid-state polymer electrolytes (SPEs) show prospects in all-solid-state lithium metal batteries. However, they suffer from low ionic conductivity at room temperature and interfacial instability with high voltage cathodes for long-term cycling. In this work, top-down fluorinated PEOs (F-PEOs) for the all-solid-state electrolytes, which are scalable and cost-effective, are developed to improve the battery performance. We demonstrate, that by enhancing the disordering of the F-PEO matrix, the SPE achieves a maximum Li + conductivity of 1.1 x 10 -4 S cm -1 at 40 °C, which is 20 times higher than the baseline. By forming robust cathode/SPE and Li/SPE interfaces, the F-PEO-based SPEs demonstrate stable cycling in the LiFePO 4 /Li and LiNi 0·8 Mn 0·1 Co 0·1 O 2 /Li (3-4.4 V, 500 cycles, capacity retention of 91.6%) based all-solid-state batteries at 40 °C. Therefore, our work highlights the significance of "disordering engineering" for energy storage materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Aerodynamic characterization of two tandem wind turbines under yaw misalignment control using actuator line model

Yaw control has proven to be promising in alleviating the wake effects that plague the efficiency of wind farms. In this work, the actuator line modeling (ALM) method is adopted to simulate the flows over two tandem turbines distanced by 3–7 rotor diameters, with the yaw angle of the upstream rotor varying from γ 1 = 0° to 50°. The aim is to provide a comprehensive aerodynamic characterization of this simple wind farm under yaw misalignment control. With increasing yaw angle, the power generated by the downstream rotor increases, compensating the power loss in the upstream rotor, and resulting in significantly higher total power of the two turbines than that without yaw control. The maximum power output is achieved as the upstream wake of the yawed rotor is redirected away from the downstream rotor plane. Behind the downstream rotor, the secondary steering phenomenon is observed, where the wake is also redirected from the centerline. The use of the actuator line model also reveal unsteady aerodynamic characteristics that cannot be captured by lower-fidelity models. For the upstream rotor, the yaw misalignment results in time-varying change in the local angle of attack on the blade, giving rise to unsteady loading. The downstream rotor is partially submerged in the deflected wake incurred by the yawed upstream rotor. As the blade revolves into and out of the wake deficit, the blade experiences cyclic loading, leading to even stronger fluctuations in the aerodynamic loads than the upstream rotor. These analysis provides a comprehensive understanding of the yaw control effects on the two tandem rotors from the perspectives of aerodynamic performance, wake profiles, and unsteady characteristics. In conclusion, the insights gained from the present study can aid the design of collective yaw control strategies of wind farms, and lay the foundation for assessing the fatigue damage associated with yaw misalignment.

17 WIND ENERGY↗
DOE OSTI2021

Thermomechanical and sequential stress performance of photovoltaic backsheets

Photovoltaic backsheet technology is utilized to protect the interior components of solar modules from environmental stress as well as provide electrical insulation to the module. The growing demand for solar energy and longer module service life requirements have brought backsheet performance into focus. Despite being a protective packaging material, many backsheets have exhibited failure in the field, limiting the performance and service life of entire modules. Most backsheets consist of multiple polymeric layers laminated together using adhesives. A new backsheet, with a high performance polyamide structure, has been developed as the solution to module failure. Primarily, it contains a unique polyamide-ionomer alloy targeted at improved weather resistance. In this study, several photovoltaic industry standard backsheets, and the novel polyamide compositions of multilayered backsheets fabricated from the coextrusion process, were examined using thermomechanical analysis (TMA). The coefficient of thermal expansion (CTE) for entire backsheets and their constituent layers was used to model the thermomechanical behavior of various backsheet constructions. Subsequently, thermal cycling was performed in the TMA to examine the intrinsic thermal behavior of the backsheets. Thermal cycling in the TMA indicates the resilience and dimensional stability in the coextruded structures as opposed to the laminated structures. Lastly, results from a Module Accelerated Sequential Testing (MAST), are included to show the mechanical integrity of these backsheets after sequential exposure to stressors including damp heat, ultra-violet (UV) light radiation, and thermal cycling. The laminate backsheets deteriorated extensively after sequential exposure to these stressors, while the novel coextruded structures retained their physical properties.

14 SOLAR ENERGY↗
DOE OSTI2024

Utilizing waste heat in wastewater treatment plants for water desalination: Modeling and Multi-Objective optimization of a Multi-Effect desalination system using Decision Tree Regression and Pelican optimization algorithm

This paper examines the feasibility of using waste heat from wastewater treatment plants (WWTPs) for water desalination. A model was developed to utilize waste heat from the gensets at As Samra WWTP in Jordan, using real data and TRNSYS® software to calculate available waste heat. The desalination process was then modeled with ASPEN PLUS® software, focusing on multi-effect desalination (MED). Both series and parallel configurations for the MED system were compared. The study investigated the effects of system feeding flow rate, feeding pressure, and heat input on productivity, performance ratio, and recovery ratio. The study also introduces a novel optimization technique combining machine learning and modern optimization algorithms to maximize system productivity and performance. Initially, a decision tree regression (DTR) model is developed to establish relationships between key independent variables (flow rate, feed pressure, and heat input) and dependent variables (productivity, performance ratio, and recovery ratio). The Pelican Optimization Algorithm (POA) is then used to identify the optimal values of the independent variables for maximum productivity and performance. The results show that using a series configuration yields a system productivity of 3984.2 kg/hr, a performance ratio of 3.78, and a recovery ratio of 0.991 at a feed flow rate of 4000 kg/hr, feed pressure of 3 bars, and heat input of 719 kW. Optimal productivity (4421 kg/hr), performance ratio (3.81), and recovery ratio (0.851) are achieved at a feed flow rate of 5166 kg/hr, feed pressure of 3.2 bars, and heat input of 794 kW. In conclusion, the techno-economic assessment indicates a levelized cost of water of 1.63 USD/m 3 for parallel configurations and 1.65 USD/m 3 for series configurations, with a payback period of less than two years.

42 ENGINEERING↗
DOE OSTI2024

Stochastic modal velocity field in rough-wall turbulence

Stochastically generated instantaneous velocity profiles are used to reproduce the outer region of rough-wall turbulent boundary layers in a range of Reynolds numbers extending from the wind tunnel to field conditions. Each profile consists in a sequence of steps, defined by the modal velocities and representing uniform momentum zones (UMZs), separated by velocity jumps representing the internal shear layers. Height-dependent UMZ is described by a minimal set of attributes: thickness, mid-height elevation, and streamwise (modal) and vertical velocities. These are informed by experimental observations and reproducing the statistical behaviour of rough-wall turbulence and attached eddy scaling, consistent with the corresponding experimental datasets. Sets of independently generated profiles are reorganized in the streamwise direction to form a spatially consistent modal velocity field, starting from any randomly selected profile. The operation allows one to stretch or compress the velocity field in space, increases the size of the domain and adjusts the size of the largest emerging structures to the Reynolds number of the simulated flow. By imposing the autocorrelation function of the modal velocity field to be anchored on the experimental measurements, we obtain a physically based spatial resolution, which is employed in the computation of the velocity spectrum, and second-order structure functions. The results reproduce the Kolmogorov inertial range extending from the UMZ and their attached-eddy vertical organization to the very-large-scale motions (VLSMs) introduced with the reordering process. The dynamic role of VLSM is confirmed in the –u'w' co-spectra and in their vertical derivative, representing a scale-dependent pressure gradient contribution.

42 ENGINEERING↗
DOE OSTI2026

Anisotropic Exciton Transport in a Lamellar CsPbBr 3 Nanocrystal Superlattice

Colloidal self-assembly is one strategy for engineering anisotropic properties into otherwise isotropic materials. In this work, we demonstrate anisotropic exciton transport in an A 2 B-type superlattice containing columns of 5.3 nm CsPbBr 3 nanocubes assembled into a hexagonal lattice around 6.5 nm LaF 3 nanodisks. Using transient photoluminescence microscopy, we determined that the exciton diffusivity along the fast axis of the superlattice is more than twice as large as that along the slow axis at T = 5 K, but that anisotropy is greatly suppressed at room temperature. Calculations of the diffusivity anisotropy ratio based on Förster theory overestimate the measured values, highlighting the limitations of this theory in completely describing exciton transport. Overall, our results demonstrate how self-assembly of colloidal nanocrystals can be used to engineer directional energy transport, and raise more questions about the microscopic nature of dipole coupling in CsPbBr 3 NC superlattices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Alkali Cation-Mediated Modulation of CO 2 Reduction Activity on Tin Electrodes in [EMIM][BF 4 ]/H 2 O Electrolytes

The development of efficient CO 2 reduction technologies hinges upon a thorough understanding of the intricate interplay between solution cations and the characteristics of the electrode surface. Recently, ionic liquids (ILs) have emerged as promising electrolytes for the CO 2 reduction reaction. However, the effect of alkali cations on the electrochemical CO 2 reduction (CO 2 R) reaction remains unclear in ILs. Here, in this report, we studied alkali cation effects by assessing the electrocatalytic CO 2 R activity with the IL 1-ethyl-3-methylimidazolium tetrafluoroborate, [EMIM][BF 4 ], in water with alkali metal co-cations (i.e., Li + , Na + , and K + ) using a polycrystalline Sn catalyst. Contrary to previous findings in purely aqueous media with inorganic cations, where alkali cations strongly enhance CO 2 R via pH modulation and strengthening of interfacial electric fields, alkali cations in electrolytes containing the IL [EMIM][BF4] negatively impact CO 2 R activity on Sn electrodes. These results were attributed to the larger radius and higher concentration of the IL organic cation [EMIM] + that mitigates the impact of alkali cations. These findings highlight the complex interplay between IL cations and alkali metals in shaping CO 2 R performance.

Chemistry↗
DOE OSTI2022

Reconfigurable training and reservoir computing in an artificial spin-vortex ice via spin-wave fingerprinting

Strongly interacting artificial spin systems are moving beyond mimicking naturally occurring materials to emerge as versatile functional platforms, from reconfigurable magnonics to neuromorphic computing. Typically, artificial spin systems comprise nanomagnets with a single magnetization texture: collinear macrospins or chiral vortices. Here, by tuning nanoarray dimensions we have achieved macrospin–vortex bistability and demonstrated a four-state metamaterial spin system, the ‘artificial spin-vortex ice’ (ASVI). ASVI can host Ising-like macrospins with strong ice-like vertex interactions and weakly coupled vortices with low stray dipolar field. Vortices and macrospins exhibit starkly differing spin-wave spectra with analogue mode amplitude control and mode frequency shifts of Δf = 3.8 GHz. The enhanced bitextural microstate space gives rise to emergent physical memory phenomena, with ratchet-like vortex injection and history-dependent non-linear fading memory when driven through global magnetic field cycles. We employed spin-wave microstate fingerprinting for rapid, scalable readout of vortex and macrospin populations, and leveraged this for spin-wave reservoir computation. ASVI performs non-linear mapping transformations of diverse input and target signals in addition to chaotic time-series forecasting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

The challenges of electrolytic valorization of carbon dioxide

Electroreduction of carbon dioxide is an enabling technology that can produce valuable chemicals, such as C 1 (for example, formic acid and carbon monoxide) and C 2 chemicals (for example, ethylene and ethanol), with a minimal or even negative carbon footprint. Now, a techno-economic analysis shows that only the C 1 products can achieve competitive prices, while substantial improvements in process economics are needed for C 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗