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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 973 records · Page 54

An optimized top contact design for solar cell concentrators

A new grid optimization scheme is developed for point focus solar cell concentrators which employs a separated grid and busbar concept. Ideally, grid lines act as the primary current collectors and receive all of the current from the semiconductor region. Busbars are the secondary collectors which pick up current from the grids and carry it out of the active region of the solar cell. This separation of functions leads to a multithickness metallization design, where the busbars are made larger in cross section than the grids. This enables the busbars to carry more current per unit area of shading, which is advantageous under high solar concentration where large current densities are generated. Optimized grid patterns using this multilayer concept can provide a 1.6 to 20 percent increase in output power efficiency over optimized single thickness grids.

Desalvo, Gregory C.↗

Machine learning with knowledge constraints for process optimization of open-air perovskite solar cell manufacturing

Perovskite photovoltaics (PV) have achieved rapid development in the past decade in terms of power conversion efficiency of small-area lab-scale devices; however, successful commercialization still requires further development of low-cost, scalable, and high-throughput manufacturing techniques. One of the critical challenges of developing a new fabrication technique is the high-dimensional parameter space for optimization, but machine learning (ML) can readily be used to accelerate perovskite PV scaling. Herein, we present an ML-guided framework of sequential learning for manufacturing process optimization. We apply our methodology to the Rapid Spray Plasma Processing (RSPP) technique for perovskite thin films in ambient conditions. With a limited experimental budget of screening 100 process conditions, we demonstrated an efficiency improvement to 18.5% as the best-in-our-lab device fabricated by RSPP, and we also experimentally found 10 unique process conditions to produce the top-performing devices of more than 17% efficiency, which is 5 times higher rate of success than the control experiments with pseudo-random Latin hypercube sampling. Our model is enabled by three innovations: (a) flexible knowledge transfer between experimental processes by incorporating data from prior experimental data as a probabilistic constraint; (b) incorporation of both subjective human observations and ML insights when selecting next experiments; (c) adaptive strategy of locating the region of interest using Bayesian optimization first, and then conducting local exploration for high-efficiency devices. Furthermore, in virtual benchmarking, our framework achieves faster improvements with limited experimental budgets than traditional design-of-experiments methods (e.g., one-variable-at-a-time sampling). This framework shows the capability of incorporating researchers’ domain knowledge into the ML-guided optimization loop; therefore, it has the potential to facilitate the wider adoption of ML in scaling to perovskite PV manufacturing.

14 SOLAR ENERGY↗

Optimization of lamp spectrum for vegetable growth

An increase in the demand for and production of vegetables in the winter, mainly in northern and Siberian regions, inevitably leads to mass building of structures for growing plants under completely artificial conditions. An industrial lighting technology is required whose main parameters (spectrum, irradiance, photoperiod) should be assigned carefully and should uniquely determine, along with other important characteristics of the artificial climate, the productivity of the plant-production facility. The most widespread crops grown in our country under indoor conditions are cucumber and tomato plants, which account for more than 98% of the area in greenhouses. These plants are good prospects for growing completely under intense artificial lighting conditions (photocultures). Optimization of the main parameters of optical radiation when growing these plants is the most important task of achieving their profitable production. At present, considerable experience has been gained in studying the dependence of productivity of cucumber and tomato communities on irradiation conditions. Fundamental studies of the Agrophysical Research Institute of the Russian Academy of Sciences, Timiryazev Institute of Plant Physiology of the Russian Academy of Sciences, Timiryazev Agricultural Academy, and other institutes create a good basis for a detailed study of the given problem. Commercial sources of radiation substantially differing in spectral characteristics in the region of photosynthetically active radiation (PAR) were used in the studies.

Prikupets, L. B.↗

Multidisciplinary Optimization Methods for Aircraft Preliminary Design

This paper describes a research program aimed at improved methods for multidisciplinary design and optimization of large-scale aeronautical systems. The research involves new approaches to system decomposition, interdisciplinary communication, and methods of exploiting coarse-grained parallelism for analysis and optimization. A new architecture, that involves a tight coupling between optimization and analysis, is intended to improve efficiency while simplifying the structure of multidisciplinary, computation-intensive design problems involving many analysis disciplines and perhaps hundreds of design variables. Work in two areas is described here: system decomposition using compatibility constraints to simplify the analysis structure and take advantage of coarse-grained parallelism; and collaborative optimization, a decomposition of the optimization process to permit parallel design and to simplify interdisciplinary communication requirements.

Kroo, Ilan↗

PowerMappeR: Power-Optimized Mapping of SNNs onto ReRAM Crossbars coupled via Packet-Switched NoCs

Many recent efforts in developing hardware-accelerated spiking neural networks (SNNs) are characterized by deep co-design between algorithms, architectures, and devices. Architectural advances overcome device constraints by coupling together many small resistive-RAM (ReRAM) crossbars via a network-on-chip (NoC) for neuromorphic component operation. Concurrently, improved SNN training methods increase accuracy and structural sparsity in networks despite growing problem sizes. Finally, compilers leverage these attributes to minimize area and inter-crossbar communication while mapping large SNNs to sophisticated architectures. However, for compiler-driven co-design to realize increasingly complex and profitable optimizations, a compile-time view of power consumption is critical. We present PowerMappeR to express and optimize over mapping-, architecture-, and device-specific power consumption information. By modeling the dynamic power of well-established components, we develop an integer linear programming (ILP)-based, encoding-agnostic, parametric power estimation model. Using this model, we demonstrate practical improvements in area and inter-crossbar communication by 0%–9.5% and 1.4%–5.1%, respectively. We also limit hotspot formation during optimization, achieving comparable or better results in targeted metrics with up to 96.4%–97.1% restriction of hotspot magnitude. Finally, we introduce profile-guided formulations to reduce worst-case and expected-case hotspot magnitude by 40.7%–69.5% and 40.6%–56.3%, respectively. Optimizing worst-case hotspot magnitude incidentally improves expected-case magnitude by 10.85%–33.45%. Reciprocally, optimizing expected-case magnitude incidentally improves worst-case magnitude by 4.33%–39.87%. Validation against hardware simulators confirms that PowerMappeR can decrease dynamic power consumption by 12.6%–27.3%.

Pohl, Devin [ORNL] (ORCID:0009000040149027)↗

Altimeter and gravity data analysis

The studies carried out under this grant fell into two broad areas. The first area was the analysis of surface gravity data with the ultimate goal of providing normal equations that could be used in combination with normal equations from the analysis of satellite orbit perturbations to obtain an optimal estimate of the gravitational potential coefficients of the Earth. The second main research activity was the estimation of gravity anomalies in ocean areas from satellite altimeter data. Such anomalies could enable the improved calibration of potential coefficient models derived solely from the analysis of orbital perturbation information. The studies in these two areas are discussed.

Rapp, Richard H.↗

K-Band Reflectarray Antenna Based on Ferroelectric Thin Films: What Have We Learned so Far

The Applied RF Technology Branch of the NASA Glenn Research Center, Cleveland, Ohio, has an on-going effort in the area of thin film ferroelectric technology for microwave applications. Particular attention has been given to developing ferroelectric phase shifters for the implementation and experimental demonstration of an electronically steerable reflectarray antenna. In the process of optimizing these material to fit the implementation requirements of the aforementioned antenna, we have accumulated a great deal of information and knowledge in areas such as the effect of the composition of the ferroelectric thin films on phase shifter performance, self assembled monolayers (SAMs) in the metallic/ferroelectric interface and their impact on phase shifter performance, correlation between microstructure and microwave properties, and the effect of selective etching on the overall performance of a thin film-ferroelectric based microwave component, amongst others. We will discuss these issues and will provide an up-dade of the current development status of the reflect-array antenna.

Miranda, Felix A.↗

Design and Development of Low Weight, Titanium Aluminide Airfoils for High Performance Industrial Gas Turbines meeting 65% Combined Cycle Efficiency (Final Report)

This project funded under DOE-FOA-0001816 was performed with the intent of evaluating the potential of utilizing a low density, high specific strength Titanium Aluminide (TiAl) alloy in a large annulus last stage gas turbine blade with the intent of improving combined cycle gas turbine efficiency toward a goal of reaching 65% efficiency. The project consisted of identifying a potentially suitable TiAl material for manufacture of such a large blade by investment casting. This included estimation of design properties for the selected alloy, trade studies using a baseline design created for a nickel based alloy cast in the TiAl alloy to evaluate potential design changes required for the use of this material and optimization of a prototype design for the same baseline application using the selected TiAl alloy. Several rounds of optimization were completed with the intent of meeting the baseline design targets with a resulting design that showed at least equivalent performance in terms of creep, LCF/TMF, HCF and aerodynamic damping potential. While it was found that significant reductions in blade loading on the disk were possible, the design resulting from the optimization met most lifing targets at the baseline size, but showed a reduction in margins in some areas in comparison to the Ni-based baseline design. Additionally, it was found that the low strain tolerance of the TiAl alloy for temperatures at and below the operational temperature of the attachment resulted in marginal, although still acceptable, creep rupture performance of the design. Due to results indicating the reduced potential for increasing turbine annulus compared to expectations a Phase II award was not proposed and it is not recommended to pursue additional design optimization efforts until further material advances with TiAl materials are achieved.

03 NATURAL GAS↗

Optimization of the compositions of polyanionic sodium-ion battery cathode NaFe 2-x V x (PO 4 )(SO 4 ) 2

Sodium (Na) super ionic conductor (NASICON) polyanionic compounds have recently attracted much attention from the battery community because of their electroactive properties and reasonably high ionic conductivities, leading to their use as a cathode in sodium-ion batteries. This article describes the compositional optimizations, crystallographic evaluations, and electrochemical behavior of a new mixed NASICON polyanionic compound, NaFe 2-x V x (PO 4 )(SO 4 ) 2 . By doping the characteristic Fe 3+ sites of the FeO 6 octahedrons with varying amounts of V 3+ , the electrochemical stability and charge transport in NaFe 2 (PO 4 )(SO 4 ) 2 were enhanced. The resulting best composition, with crystal structure NaFe 1.4 V 0.6 (PO 4 )(SO 4 ) 2 resolved through the Rietveld method, exhibited a stable capacity compared with the other synthesized compositions. In situ powder x-ray diffraction measurements, a single-phase intercalation/deintercalation mechanism of the NASICON structure in the measured sodium concentration window was observed with no impurity phase formation. Further electrochemical assessments revealed the interfacial charge transfer kinetics to be the rate-limiting step in the sodium concentration window. Also, the measured sodium-ion diffusivity values in the range of 6 × 10 -11 to 7 × 10 -11 cm 2 /s in the measured sodium concentration range. The results reported here highlight the potential of compositionally and morphologically optimized NaFe 1.4 V 0.6 (PO 4 )(SO 4 ) 2 with higher particle surface areas as a cathode material for high-performance sodium-ion batteries.

25 ENERGY STORAGE↗

Development of nickel-incorporated MCM-41–carbon composites and their application in nitrophenol reduction

MCM-41–carbon composites were obtained by soft-templating strategy by adding resorcinol and formaldehyde as carbon precursors during the synthesis of MCM-41. The synthesis of these composites was optimized until mesoporous MCM-41 domains remained highly ordered and the overall specific surface area and pore volume remained relatively high. The one-pot synthetic procedure was further extended to obtain the Ni-containing MCM-41–carbon composites using nickel nitrate as an additive. A homogeneous distribution of nickel nanoparticles in the composites was achieved by adding histidine to the reaction mixture, which was able to form a complex with nickel ion. Carbonization of organic components in the composites produced carbon that was responsible for in situ reduction of nickel(II) to metallic nickel (Ni0) at elevated temperatures, eliminating the post-synthesis reduction step carried out in the presence of hydrogen gas or other reducing agent. Furthermore, the resulting composites showed enhanced catalytic activity toward nitrophenol reduction obeying the zero-order kinetics. Three unique features of the resulting composites, namely mesoporous channels of MCM-41, carbon-induced in situ reduction of Ni ions to metallic Ni nanoparticles, and abundance of highly active Ni sites due to high dispersion of Ni0, make this strategy applicable for the synthesis of other transition metal-based catalysts. XRD and STEM analyses revealed a homogeneous distribution of nickel nanoparticles in the composites without significant distortion of their ordered mesoporosity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Socially-aware evaluation framework for transportation

Technological advancements are rapidly changing traffic management in cities. Navigation applications, in particular, have impacted cities in many ways by rerouting traffic. As different routing strategies distribute traffic differently, understanding these disparities across multiple city-relevant dimensions is extremely important for decision-makers. We develop a multi-themed framework called Socially- Aware Evaluation Framework for Transportation (SAEF), which assists in understanding how traffic routing and the resultant dynamics affect cities. The framework is presented for four Bay Area cities, for which we compare three routing strategies - user equilibrium travel time, system optimal travel time, and system optimal fuel. The results demonstrate that many neighborhood impacts, such as traffic load on residential streets and around minority schools, degraded with the system-optimal travel time and fuel routing in comparison to the user-equilibrium travel time routing. The findings also show that all routing strategies subject the city's disadvantaged neighborhoods to disproportionate traffic exposure. Our intent with this work is to provide an evaluation framework that enables reflection on the consequences of traffic routing and management strategies, allowing city planners to recognize the trade-offs and potential unintended consequences.

99 GENERAL AND MISCELLANEOUS↗

Fabrication and characterization of a full-size ultra-precise lamellar grating for the Cosmic beamline at ALS-U

We have developed a new process for the production of ultra-precise variable line spacing (VLS) lamellar diffraction gratings through nanofabrication. The process enables the fabrication of full-size X-ray gratings with sub-nanometre accuracy in groove depth, an optimal land-to-groove ratio, and uniform groove depth across the entire grating area. We also established a method for evaluating VLS groove density variation using stitched Fizeau interferometry. The measurements confirmed the exceptionally high accuracy of the VLS groove density in the fabricated gratings, which is well within the specification tolerances while the residual groove density errors are vanishingly small. The gold-coated grating demonstrated near-theoretical diffraction efficiency across the energy range of 100–1200 eV.

36 MATERIALS SCIENCE↗

A Perspective on the Impact of Group Delay Dispersion in Future Terahertz Wireless Systems

This article discusses the challenges and opportunities of managing group delay dispersion (GDD), and its relation to the performance standards of future sixth-generation (6G) wireless communication systems utilizing terahertz frequency waves. The unique susceptibilities of 6G systems to GDD are described, along with a quantitative description of the sources of GDD, including multipath, rough surface scattering, intelligent reflecting surfaces, and propagation through the atmosphere. An experimental case-study is presented that confirms previous models quantifying the impact of atmospheric GDD. Several GDD manipulation strategies are presented, illustrating their hindered effectiveness in the 6G context. Conversely, some benefits of leveraging GDD to enhance 6G systems, such as improved security and simplified hardware, are also discussed. Finally, a perspective on using photonic GDD control devices is provided, revealing quantitative benefits that may unburden existing equalization schemes. Here, the article argues that GDD will uniquely and significantly impact some 6G systems, but that its careful consideration along with new mitigation strategies, including photonic devices, will help optimize system performance. The conclusion provides a perspective to guide future research in this area.

Strecker, Karl↗

Flex-PCB Quench Antenna Developments at FNAL

We report flexible printed-circuit-board-based quench antenna arrays have been developed at FNAL since 2017. They proved to be low-noise, low-cost, sensitive, and non-invasive sensors for quench characterization in superconducting magnets, having the potential to extend even to quench detection. Starting with applications of small area sensors of this type, we have explored feasibility for operations at high pressure, and have invested in multi-channel quench antenna arrays covering the complete area of the innermost magnet layer of the conductor. We've also tested and optimized sensor geometry and relative orientations to increase sensitivity and spatial resolution. Beyond developments of warm and cold bore antennas, we've progressed to concepts which attach quench antennas to the conductor surfaces of accelerator magnets. Multiple programs and projects at FNAL and collaborating institutions benefited from this work already and our plans target further extensions of capabilities and applicability of these devices. In this paper we present the logic behind the development steps taken so far, status of our work and direction of near-term research on quench antennas at Fermilab.

43 PARTICLE ACCELERATORS↗

The ITensor Software Library for Tensor Network Calculations

ITensor is a system for programming tensor network calculations with an interface modeled on tensor diagrams, allowing users to focus on the connectivity of a tensor network without manually bookkeeping tensor indices. The ITensor interface rules out common programming errors and enables rapid prototyping of algorithms. After discussing the philosophy behind the ITensor approach, we show examples of each part of the interface including Index objects, the ITensor product operator, tensor factorizations, tensor storage types, algorithms for matrix product state (MPS) and matrix product operator (MPO) tensor networks, quantum number conserving block sparse tensors, and the NDTensors library. We also review publications that have used ITensor for quantum many-body physics and for other areas where tensor networks are increasingly applied. To conclude we discuss promising features and optimizations to be added in the future.

Fishman, Matthew↗

Codebase release 0.3 for ITensor

ITensor is a system for programming tensor network calculations with an interface modeled on tensor diagrams, allowing users to focus on the connectivity of a tensor network without manually bookkeeping tensor indices. The ITensor interface rules out common programming errors and enables rapid prototyping of algorithms. After discussing the philosophy behind the ITensor approach, we show examples of each part of the interface including Index objects, the ITensor product operator, tensor factorizations, tensor storage types, algorithms for matrix product state (MPS) and matrix product operator (MPO) tensor networks, quantum number conserving block sparse tensors, and the NDTensors library. We also review publications that have used ITensor for quantum many-body physics and for other areas where tensor networks are increasingly applied. To conclude we discuss promising features and optimizations to be added in the future.

Fishman, Matthew↗

Mask Projection Stereolithography for Manufacturing Ceramic Parts for CO 2 Capture and Sequestration

With increased CO 2 in the atmosphere and climate change becoming central in today’s political climate, it is important to make attempts to alleviate climate change. CO 2 capture is possible at the source of some of the larges CO 2 producers – industrial firms – where it can be collected via separation membranes. While current state-of-the-art technology is amine gas treatment or polymer membranes, ceramic membranes infilled with hydroxide offer a more energetically efficient solution. Stereolithography offers a unique manufacturing technique to create uniquely-shaped ceramic parts that will maximize carbon capture while maintaining low energy needs and low cost. High-loading ceramic slurries can be more difficult to manufacture using stereolithography due to high viscosity and opacity, but produce stronger pieces when sintered. The current challenge is optimizing high-load ceramic slurries for stereolithography to print pieces with large surface areas and parts on the micrometer-scale.

36 MATERIALS SCIENCE↗

Industry Fire Modeling Enhancement Tools and Methods. Light Water Reactor Sustainability Program report

Modeling and implementing fire safety for nuclear power plants is a costly activity. Because of the complexity of fire phenomenon and multiple operational procedures, it is difficult to computationally provide assurance that the mitigation methods are adequate for critical areas using current analysis methods. An economical method to provide more accurate modeling and optimize mitigation methods is needed to improve nuclear power viability. This report describes the background of current fire model strategy; the first stage of a tool to help reduce resources needed in fire analysis and the plan for the next step in advancing fire. The report lays out the path decided upon by Idaho National Laboratory and Industry representatives to best help reduce costs and improve realism in Fire Probabilistic Risk Analysis.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗