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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Battery anode design: From 1D nanostructure to 3D nanoarchitecture – Enabling next-generation energy storage technology

Recently, many studies have reported the efficacy of 1D silicon nanostructures as anode materials (mostly nanowires) due to their large surface to volume ratio which could be an advantage in terms of charging kinetics. Anode design is a crucial factor for the further development of lithium-ion battery (LIB) technology, especially in terms of achieving the high charging rate performance, as typically needed in electric vehicles (EV). 3D nanostructures have been identified as the key to dramatically enhanced charging rate of LIB, in addition to the change of materials (from carbon-based anode to silicon-based). However, existing fabrication methodologies for 3D nanostructures are inherently expensive – using advanced lithography techniques or other nanopatterning methodologies, as well as using additive manufacturing approaches. Electrospinning (as an integrated additive manufacturing methodology) may be used to produce low-cost 3D-printed fiber structures. Here, in the present study, we demonstrate the groundwork in this field of research in the past 3–4 years, which would allow the extension of this special additive manufacturing approach to reach nanoscale 3D-printed fiber structures more economically and with scalability for manufacturing. This would pave the way to achieve the order of magnitude increase in battery charging rate as needed to realize the vision of the electrification of mobility/transportation.

25 ENERGY STORAGE↗
DOE OSTI2020

Polymer informatics: Current status and critical next steps

Artificial intelligence (AI) based approaches are beginning to impact several domains of human life, science and technology. Polymer informatics is one such domain where AI and machine learning (ML) tools are being used in the efficient development, design and discovery of polymers. Surrogate models are trained on available polymer data for instant property prediction, allowing screening of promising polymer candidates with specific target property requirements. Questions regarding synthesizability, and potential (retro)synthesis steps to create a target polymer, are being explored using statistical means. Data-driven strategies to tackle unique challenges resulting from the extraordinary chemical and physical diversity of polymers at small and large scales are being explored. Other major hurdles for polymer informatics are the lack of widespread availability of curated and organized data, and approaches to create machine-readable representations that capture not just the structure of complex polymeric situations but also synthesis and processing conditions. Methods to solve inverse problems, wherein polymer recommendations are made using advanced AI algorithms that meet application targets, are being investigated. As various parts of the burgeoning polymer informatics ecosystem mature and become integrated, efficiency improvements, accelerated discoveries and increased productivity can result. Here in this paper, we review emergent components of this polymer informatics ecosystem and discuss imminent challenges and opportunities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Development of diamond-based diagnostics for next-generation XFELs

The composition and performance of three different diamond sensor based pass-through diagnostics are presented. A position-sensitive quadrant sensor was designed and characterized using the XPP beam at the SLAC LCLS, demonstrating a generated-charge resolution of 0.025 pC and a position sensitivity of 2 μm, measurable pulse-by-pulse at a repetition rate of up to 50 MHz. A compact signal path capable of repetition rates up to 1 GHz was used to characterize the charge collection properties of diamond sensors as a function of the density of electron-hole pairs created within the sensor, finding a limit of approximately 10 16 electron-hole pairs per cm 3 beyond which the collection efficiency and time began to degrade. Finally, a proposed scheme for measuring ionizing radiation at multi-GHz rates is presented, along with results preliminarily demonstrating signal transport capability in excess of 5 GHz.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Towards next-generation optical potentials for nuclear reactions and structure calculations

Optical-model potentials (OMPs) are critical ingredients for basic and applied nuclear physics. Present-day computational capabilities allow us to generate data-driven nucleon-nucleus OMPs that are non-local and exactly dispersive (as theoretically required to be), include statistically-sound uncertainty quantification, and are trained on both scattering and bound-state data from a wide area of the nuclear chart. Combined together, these features allow for significant improvement in fidelity and extrapolative power of the model. Here, we present preliminary work toward the development and training of such an OMP. The capability of the model to describe data at this first stage is encouraging.

Perrotta, Salvatore Simone [Lawrence Livermore Nat↗
DOE OSTI2023

Reliability of tandem solar cells and modules: what's next?

Hybrid tandem photovoltaic (PV) technology development has gained momentum in the last few years. This has been motivated by a need to push module efficiencies beyond what is theoretically capable with single-junction technologies to further accelerate total global PV deployment. Significant advances have been made with multiple material systems achieving tandem efficiencies over 30% in the last decade. All of the highest record efficiencies have been from laboratory-scale devices, with areas of 1 cm2 or less. Interestingly, there are multiple material combinations and terminal configurations that have demonstrated promising results. Despite these high laboratory efficiencies, reasonable service lifetimes (a useful operating lifetime of at least 25 years) are needed for tandems to compete with the levelized cost of energy (LCOE) of traditional single junction PV technologies. Existing commercial Si PV products have demonstrated performance in the field with an average of less than 1% relative annual degradation in module and system performance, and many manufacturers now provide 30 year warranties on their products.

14 SOLAR ENERGY↗
DOE OSTI2023

Next-generation poly-L-histidine formulations for miRNA mimic delivery

Many diseases, especially cancer, are caused by the abnormal expression of non-coding microRNAs (miRNAs), which regulate gene expression, leading to the development of miRNA-based therapeutics. Synthetic miRNA inhibitors have shown promising efficacy in blocking the activity of aberrant miRNAs that are upregulated in disease-specific pathologies. On the other hand, miRNAs that aid in preventing certain diseases and are reduced in expression in the disease state need different strategies. To tackle this, miRNA mimics, which mimic the activity of endogenous miRNAs, can be delivered for those miRNAs downregulated in different disease states. However, the delivery of miRNA mimics remains a challenge. Here, we report a cationic polylactic-co-glycolic acid (PLGA)-poly-L-histidine delivery system to deliver miRNA mimics. We chose miR-34a mimics as a proof of concept for miRNA delivery. miR-34a-loaded PLGA-poly-L-histidine nanoparticles (NPs) were formulated and biophysically characterized to analyze the structural properties of miRNA mimic-loaded NPs. In vitro efficacy was determined by investigating miR-34a and downstream target levels and performing cell viability and apoptosis assays. We confirmed in vivo efficacy through prolonged survival of miR-34a NP-treated A549-derived xenograft mice treated intratumorally. The results of these studies establish PLGA-poly-L-histidine NPs as an effective delivery system for miRNA mimics for treating diseases characterized by downregulated miRNAs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Review: The Next Steps in Crop Improvement: Adoption of Emerging Strategies to Identify Bottlenecks in Sugar Flux

We report sugar allocation in plants is the fundamental process that transports sugar from source to sink tissues and has a dramatic impact on crop yields. Controlling sugar allocation is required to increase crop yields, as well as biomass for biofuel production. Successful examples have demonstrated that genetic engineering of sugar partitioning offers a promising strategy to achieve this goal. However, improvement has thus far been limited by gaps in understanding of the underlying mechanisms controlling the allocation of sugars. The dynamics of sugar partitioning are minimally predictable under different conditions, between species, or in response to abiotic stresses. Here, we discuss four methodologies that have not been sufficiently exploited for the identification of bottlenecks in sugar flux. Furthermore, we suggest how these strategies can be used and combined to provide the insight needed to maximize crop yields or biomass, especially under conditions of environmental stress.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Progress and opportunities in corrosion mitigation in heat transfer fluids for next-generation concentrating solar power

Concentrating solar power (CSP) systems have gained considerable eminence in converting solar thermal energy into electrical power in recent years. According to the U.S. Department of Energy's Gen3 roadmap, the CSP system should operate > 700 °C, as its efficiency depends directly on the operating temperature of the heat transfer fluids (HTFs). A significant challenge, however, is the corrosion of containment materials by the HTFs that is exacerbated at the higher temperatures. A comprehensive review of the high temperature stable HTFs, their properties, corrosion mechanisms on different alloys, and corrosion mitigation measures is of much importance for directing a concerted research and development in the field, which forms the motivation for this compendium. First, molten salt HTFs and their thermophysical properties, along with liquid metals, are introduced. Corrosion of structural materials in different HTFs including molten salts, liquid metals, and supercritical carbon-di-oxide at various temperatures and the corrosion mechanisms are comprehensively reviewed. In addition, several corrosion mitigation methods are discussed. Finally, future directions for HTFs and corrosion mitigation methods in molten salts are proposed. As a result, the holistic review presented here will serve as the foundation for further research addressing relevant challenges and enabling the promise of achieving cost-competitive CSP.

14 SOLAR ENERGY↗
DOE OSTI2025

Next generation Arctic vegetation maps: Aboveground plant biomass and woody dominance mapped at 30 m resolution across the tundra biome

The Arctic is warming faster than anywhere else on Earth, placing tundra ecosystems at the forefront of global climate change. Plant biomass is a fundamental ecosystem attribute that is sensitive to changes in climate, closely tied to ecological function, and crucial for constraining ecosystem carbon dynamics. However, the amount, functional composition, and distribution of plant biomass are only coarsely quantified across the Arctic. Therefore, we developed the first moderate resolution (30 m) maps of live aboveground plant biomass (g m −2 ) and woody plant dominance (%) for the Arctic tundra biome, including the mountainous Oro Arctic. We modeled biomass for the year 2020 using a new synthesis dataset of field biomass harvest measurements, Landsat satellite seasonal synthetic composites, ancillary geospatial data, and machine learning models. Additionally, we quantified pixel-wise uncertainty in biomass predictions using Monte Carlo simulations and validated the models using a robust, spatially blocked and nested cross-validation procedure. Observed plant and woody plant biomass values ranged from 0 to ∼6000 g m −2 (mean ≈ 350 g m −2 ), while predicted values ranged from 0 to ∼4000 g m −2 (mean ≈ 275 g m −2 ), resulting in model validation root-mean-squared-error (RMSE) ≈ 400 g m −2 and R 2 ≈ 0.6. Our maps not only capture large-scale patterns of plant biomass and woody plant dominance across the Arctic that are linked to climatic variation (e.g., thawing degree days), but also illustrate how fine-scale patterns are shaped by local surface hydrology, topography, and past disturbance. By providing data on plant biomass across Arctic tundra ecosystems at the highest resolution to date, our maps can significantly advance research and inform decision-making on topics ranging from Arctic vegetation monitoring and wildlife conservation to carbon accounting and land surface modeling.

Climate change↗