Wavelet-based convolutional neural network for non-intrusive load monitoring of next generation shipboard Power Systems
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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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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.
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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.
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.
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.
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.
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.
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With the growing adoption of solar energy as a key component of the global energy transition and its new industrial policy (the Inflation Reduction Act and others), the United States is witnessing a significant increase in solar investments. This surge in installations and domestic and reshored manufacturing of solar photovoltaic (PV) panels brings with it a pressing issue: the proper management of end-of-life (EoL) PV panels. As these panels are decommissioned, either due to reaching the end of their lifespans or due to breakage across the various stages of the forward supply chain, it becomes crucial to establish efficient reverse supply chain logistics systems to address the challenges associated with their disposal, while also unlocking the value of the inherent materials that are of critical value for other forward supply chains. This perspective article examines the challenges regarding EoL PV panels and relevant reverse supply chain and logistics networks, and proposes future research directions based on the gaps observed among academic research, industry, and policy-making challenges. We identify the main bottlenecks and hurdles including, among others, the lack of supportive regulations and absence of structured, optimized recycling infrastructure. To this end, it is proposed that the key to achieving a sustainable reverse supply chain network for solar PV panels lies in relentless end-to-end supply chain cost optimization efforts supported by enabling policies. Moreover, it is proposed that designing systematic decision-making modeling frameworks is vital for examining different possibilities and scenarios for state, region or nation-wide optimization of solar PV reverse supply chain networks. Indicative to this effect, we discuss the development of a Resource-Task-Network (RTN)-based model and demonstrate its application and benefits through a case study. We wrap up with conclusions and future research directions.
A techno-economic and environmental life cycle assessment was conducted for manufacturing two novel types of solid sorbents used for direct air CO 2 capture (DAC). One type of solid sorbent comprised Polyacrylonitrile (PAN)/Organopolysilizane (OPSZ)/nanoscale organic hybrid materials (NOHM)(, and the other comprised polymers of intrinsic microporosity (PIM)/NOHM. These solid sorbents were assumed to be manufactured via an unconventional route: electrospinning as fibers. Economic analyses revealed that manufacturing costs for a 0.73 MT/year capacity plant was $\$$831 and $\$$1398/kg of electrospun fiber in the case ofPAN/OPSZ/NOHM and PIM/NOHM, respectively. The costs were higher for PIM/NOHM owing to high raw material prices (Spirobisindane and tetrafluoroterephthalonitrile), that are used only in manufacturing PIM. Scaling up the plant capacity from 0.73 to 30 MT/year plant decreased the manufacturing cost by nearly half from $\$$831 to $\$$379 in the case of PAN/OPSZ/NOHM, depicting the economies of scale of effect. An LCA of both types of solid sorbent was performed using OpenLCA software, the Ecoinvent v 3.5 database, and the TRACI LCI assessment method. The Global Warming Potential (GWP) ofPAN/OPSZ/NOHM and PIM/NOHM was observed to be 151 × 10 -3 and 166 × 10 -3 kg CO 2 per kg CO 2 captured in the DAC plant, respectively. In conclusion, these GWP values were nearly five times as high as those observed for other solid sorbents existing in the literature such as PEI on silica gel, carbonate on silica, and carbonate on activated carbon owing to large amounts of electricity used in electrospinning unit operation.
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The high lateral resolution and sensitivity of the NanoSIMS 50 and 50L series of dynamic SIMS instruments have enabled numerous scientific advances over the past 25 years. Here, in this study, we report on the NanoSIMS-HR, the first major upgrade to the series, and analytical tests in a suite of sample types, including an aluminum sample containing silicon crystals, microalgae, and plant roots colonized with a symbiotic fungus. Significant improvements have been made in the Cs + ion source, high voltage (HV) control, stage reproducibility, and other aspects of the instrument that affect performance. The modified design of the NanoSIMS-HR thermal-ionization Cs + source enables a 5 pA primary ion beam to be focused into a 100 nm spot, a ~2.5-fold increase compared to Cs + sources on previous instruments (~2 pA at 100 nm). The brightness of the new Cs + source enables an ultimate lateral resolution as high as 30 nm and improved detection limits for a given analysis area. Sample stage movement accuracy is higher than 500 nm, enabling many-fold higher throughput automated analyses. With the new HV control, the primary ion beam impact energy can be reduced from 16 to 2 keV, which enables higher depth resolution during depth profiling (a 2-fold improvement), albeit with a 5-fold decrease in lateral resolution. In the NanoSIMS-HR, the secondary ion column and detection system are identical to those used in the previous series, and the isotopic analysis performance is as precise as in previous NanoSIMS instruments.
The tremendous improvement in performance and cost of lithium-ion batteries (LIBs) have made them the technology of choice for electrical energy storage. While established battery chemistries and cell architectures for Li-ion batteries achieve good power and energy density, LIBs are unlikely to meet all the performance, cost, and scaling targets required for energy storage, in particular, in large-scale applications such as electrified transportation and grids. The demand to further reduce cost and/or increase energy density, as well as the growing concern related to natural resource needs for Li-ion have accelerated the investigation of so-called "beyond Li-ion" technologies. In this review, we will discuss the recent achievements, challenges, and opportunities of four important "beyond Li-ion" technologies: Na-ion batteries, K-ion batteries, all-solid-state batteries, and multivalent batteries. Here, the fundamental science behind the challenges, and potential solutions toward the goals of a low-cost and/or high-energy-density future, are discussed in detail for each technology. While it is unlikely that any given new technology will fully replace Li-ion in the near future, "beyond Li-ion" technologies should be thought of as opportunities for energy storage to grow into mid/large-scale applications.