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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 37 records · Page 2

Hemicellulose Modulates Nanoscale Lignin Architecture in Synthetic Plant Cell Walls

Cellulose, hemicellulose, and lignin─the most abundant biopolymers on Earth─compose the structural matrix of plant biomass, providing renewable resources critical to bioenergy and sustainable materials. Despite their importance, the nanoscale mechanochemical processes underlying lignocellulose assembly during plant secondary cell wall formation remain poorly understood, hindering advancements in biomass conversion technologies. Here, in this study, we synthesize a biomimetic model system comprising cellulose–hemicellulose nanofibrils (CHN) to examine guaiacyl lignin polymerization in a physiologically relevant context. Using advanced nanocharacterization─scattering-type scanning near-field optical microscopy (s-SNOM) with infrared nanospectroscopy coupled to solid-state nuclear magnetic resonance (NMR)─we reveal that hemicellulose presence considerably modulates lignin deposition and alters its interunit bond distribution. Specifically, hemicellulose-rich environments dramatically reduce lignin deposition by approximately 50% and yield highly condensed lignin structures characterized by severely reduced β–O–4′ linkages (<2%) and suppressed β–β′ linkages. Conversely, cellulose-alone scaffolds support notably higher β–O–4′ content (∼10%), resulting in a more uniform nanoscale lignin coating. Our work helps explain how accessible hemicellulose sites, both sterically and chemically, direct radical coupling during lignification, fundamentally reshaping lignin’s nanoscale architecture. These findings deepen our mechanistic understanding of plant cell wall biosynthesis and inform strategies aimed at enhancing biomass deconstruction efficiency for sustainable bioenergy applications.

NMR↗

Effects of Photovoltaic Module Materials and Design on Module Deformation Under Load

Static structural finite element models of an aluminum-framed crystalline silicon (c-Si) photovoltaic (PV) module and a glass-glass thin film PV module were constructed and validated against experimental measurements of deflection under uniform pressure loading. Parametric analyses using Latin Hypercube Sampling (LHS) were performed to propagate simulation input uncertainties related to module material properties, dimensions, and manufacturing tolerances into expected uncertainties in simulated deflection predictions. This exercise verifies the applicability and validity of finite element modeling for predicting mechanical behavior of solar modules across architectures and enables computational models to be used with greater confidence in assessment of module mechanical stressors and design for reliability. Sensitivity analyses were also performed on the uncertainty quantification data sets using linear correlation coefficients to elucidate the key parameters influencing module deformation. This information has implications on which materials or parameters may be optimized to best increase module stiffness and reliability, whether the key optimization parameters change with module architecture or loading magnitudes, and whether parameters such as frame design and racking must be replicated in reduced-scale reliability studies to adequately capture full module mechanical behavior.

14 SOLAR ENERGY↗

Techno-economic Analysis of Novel PV Plant Designs for Extreme Cost Reductions

A techno-economic analysis is underway examining the cost and performance of future large-scale photovoltaic (PV) plant components, including bifacial modules, tandem modules, increased plant voltage architectures, and module-level power electronics. Integration of these components into PV plant designs is compared with current PV technologies based on levelized cost of electricity (LCOE). Baseline models are developed and validated against recorded PV plant performance data. Expected cost and performance data of future PV technologies are incorporated into the baseline models. An evolutionary algorithm is utilized to optimize PV plant configuration, technology combination, and LCOE. Furthermore, this paper focuses on the bifacial module analysis.

14 SOLAR ENERGY↗

Evaluating Image Classification Deep Convolutional Neural Network Architectures for Remaining Useful Life Estimation of Turbofan Engines

Accurate estimation of the remaining useful life (RUL) is a key component of condition-based maintenance (CBM) and prognosis and health management (PHM). Data-based models for the estimation of RUL are of particular interest because expert knowledge of systems is not always available, and physical modeling is often not feasible. Additionally, using data-based models, which make decisions based on raw sensor data, allow features to be learned instead of manually determined. In this work, deep convolutional neural network (CNN) architectures are investigated for their ability to estimate the RUL of turbofan engines. To improve the accuracy of the models, CNN architectures, which have proven successful in image classification, are implemented and tested. Specifically, the blocks used in the Visual Geometry Group (VGG) architecture, inception modules used in the GoogLeNet architecture, and residual blocks used in the ResNet architecture are incorporated. To account for varying flight lengths, the input to the models is a window of time series data collected from the engine under test. Window locations at the climb, cruise, and descent stages are considered. To further improve the RUL estimations, multiple overlapping windows at each location are used. This increases the amount of training data available and is found to increase the accuracy of the resulting RUL estimations by averaging the estimates from all overlapping segments. The model is trained and tested using the new Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) data set, and high prognosis accuracy was achieved. Furthermore, this work expands on the model developed and used in the 2021 PHM Society Data Challenge, which received second place.

convolutional neural networks↗

UV‐induced degradation of high‐efficiency silicon PV modules with different cell architectures

Abstract Degradation from ultraviolet (UV) radiation has become prevalent in the front of solar cells due to the introduction of UV‐transmitting encapsulants in photovoltaic (PV) module construction. Here, we examine UV‐induced degradation (UVID) in various commercial, unencapsulated crystalline silicon cell technologies, including bifacial silicon heterojunction (HJ), interdigitated back contact (IBC), passivated emitter and rear contact (PERC), and passivated emitter rear totally diffused (PERT) solar cells. We performed UV exposure tests using UVA‐340 fluorescent lamps at 1.24 W·m −2 (at 340 nm) and 45°C through 4.02 MJ·m −2 (2000 h). Our results showed that modern cell architectures are more vulnerable to UVID, leading to a significant power decrease (−3.6% on average; −11.8% maximum) compared with the conventional aluminum back surface field (Al‐BSF) cells (<−1% on average). The power degradation is largely caused by the decrease in short‐circuit current and open‐circuit voltage. A greater power decrease is observed in bifacial cells with rear‐side exposure compared with those with front‐side exposure, indicating that the rear side is more susceptible to UV damage. Secondary ion mass spectroscopy (SIMS) confirmed an increase in hydrogen concentration near the Si/passivation interface in HJ and IBC cells after UV exposure; the excess of hydrogen could result in hydrogen‐induced degradation and subsequently cause higher recombination losses. Additionally, surface oxidation and hot‐carrier damage were identified in PERT cells. Using a spectral‐based analysis, we obtained an acceleration factor of 5× between unpackaged cells (containing a silicon nitride antireflective coating on the front) in the UV test and an encapsulated module (with the front glass and encapsulant blocking 90% of the UV at 294 nm and 353 nm, respectively) in outdoor conditions. From the analytical calculations, we show that a UV‐blocking encapsulant can reduce UV transmission in the module by an additional factor of ~50.

14 SOLAR ENERGY↗

Wavelength domain spatial frequency modulation imaging: enabling fiber optic delivery and detection

Spatial frequency modulation imaging (SPIFI) provides a simple architecture for modulating an extended illumination source that is compatible with single pixel imaging. We demonstrate wavelength domain SPIFI (WD-SPIFI) by encoding time-varying spatial frequencies in the spectral domain that can produce enhanced resolution images, like its spatial domain counterpart, spatial domain (SD) SPIFI. However, contrary to SD-SPIFI, WD-SPIFI enables remote delivery by single mode fiber, which can be attractive for applications where free-space imaging is not practical. Finally, we demonstrate a cascaded system incorporating WD-SPIFI in-line with SD-SPIFI enabling single pixel 2D imaging without any beam or sample scanning.

47 OTHER INSTRUMENTATION↗

Electric and Hydraulic Propel Torque Modulation for a Compact Track Loader With the Hybrid Hydraulic Electric Architecture (HHEA)

Abstract The Hybrid Hydraulic Electric Architecture (HHEA) has previously been proposed for off-highway vehicles to reap the efficiency and controllability benefits of electrification without needing very large electric motors. This is achieved with the use of a set of selectable common pressure rails to transmit the majority of power and small electric motors to modulate that power. Previous work has shown significant energy savings for the work circuits of a variety of machines. In this paper, the energy saving potential of HHEA for the propel circuit of a compact track loader is studied. The ports of the track hydraulic motors are selectably connected to the common pressure rails, and instead of using the electric assist motors to buck/boost pressure, as in HHEA for linear actuators, small electric assist motors are used to add/subtract torque directly. The interplay between the torque limits of the electric motors and the ability of the hydraulic motor to vary displacements is studied, along with the effect these factors have on energy saving potential. It is found that the ability to vary the displacement of the hydraulic motor allows for: more efficient electric motor operating conditions, reduced electric torque requirement, and reduced pressure rail switching events. All three of these advantages can be achieved at once using variable displacements; but trade-offs exist between these advantages (i.e. improved efficiency can be achieved at the expense of a larger electric torque requirement). Overall, the HHEA can reduce energy consumption by ∼ 36% compared to the stock machine, depending on the hydraulic motor’s ability to vary displacements, and assuming the electric motor torque is limited to 20% of that required in a direct electrification scheme.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Technoeconomic Analysis of Novel PV Plant Designs for Extreme Cost Reductions

This project sought to gain a deeper understanding of the cost and performance of future solar photovoltaic (PV) plant components, including bifacial PV modules, tandem PV modules, increased plant voltage architectures, and module-level power electronics, and how they may be integrated into new PV plant designs to significantly reduce the levelized cost of electricity (LCOE) of PV. This was done through extensive modeling of current PV plants and future technologies in three different locations, informed by a comprehensive literature review and informational interviews to develop performance and cost assumptions for these technologies. Sensitivities were conducted to understand tradeoffs between different design options, such as the added energy from increasing row spacing versus additional land costs. An optimization tool was then created utilizing an evolutionary algorithm to determine an optimal PV plant configuration for a given set of technologies that resulted in minimized plant LCOE based upon typical performance and cost inputs.

14 SOLAR ENERGY↗

Field‐Relevant Degradation Mechanisms in Metal Halide Perovskite Modules

Field testing, failure analysis, and understanding of degradation mechanisms are essential to advancing metal halide perovskite (MHP) photovoltaic (PV) technology toward commercialization. Here, we present performance data from up to 1 year of outdoor testing of MHP modules in Golden, Colorado. The module encapsulation architecture and encapsulant materials have a significant impact on module reliability, with modules containing a polyolefin elastomer (POE) in addition to a desiccated polyisobutylene (PIB) edge seal outlasting modules with only a PIB edge seal or PIB blanket. Nondestructive and destructive characterization of the field-tested modules points to module scribes and interfaces as areas of potential mechanical weakness and chemical migration, resulting in shunt pathways and increased series resistance. Finally, indoor accelerated stress testing with light and elevated temperatures is performed, demonstrating failure with similar scribe degradation signatures as compared to the field-tested modules. In conclusion, under both outdoor testing and light and elevated temperature conditions, electrochemical corrosion between the copper electrode and the mobile iodine ions appeared dominant, with a significant progression at the scribes that is speculated to result from an interplay between the initial laser damage and joule heating from enhanced ion diffusion under bias.

14 SOLAR ENERGY↗

Techno-economic Analysis of Novel PV Plant Designs for Extreme Cost Reductions

A techno-economic analysis is underway examining the cost and performance of future large-scale photovoltaic (PV) plant components, including bifacial modules, tandem modules, increased plant voltage architectures, and module-level power electronics. Integration of these components into PV plant designs is compared with current PV technologies based on levelized cost of electricity (LCOE). Baseline models are developed and validated against recorded PV plant performance data. Expected cost and performance data of future PV technologies are incorporated into the baseline models. An evolutionary algorithm is utilized to optimize PV plant configuration, technology combination, and LCOE. This paper focuses on the bifacial module analysis.

14 SOLAR ENERGY↗

Technoeconomic analysis of perovskite/silicon tandem solar modules

Tandem photovoltaic (PV) modules offer an opportunity to improve the efficiency and energy yield of available solar resources compared with single-junction devices. Here, we present a cost model and sensitivity analysis of perovskite/silicon (Si) tandem modules to understand how design choices impact overall module costs. We find a minimum sustainable price (MSP) of $\$$0.428/W DC for our baseline two-terminal design and $\$$0.423/W DC for our baseline four-terminal design, each at a module efficiency of 25% and module production of 3 GW per year in the United States. We find that the choice of Si cell architecture, overall module efficiency, and factory throughput have the most significant impacts on cost and competitiveness. The dynamic model provided is designed for researchers, companies, and interested individuals to use and edit as needed to better understand the trade-offs among PV module technologies and enable targeted research to improve module design and fabrication.

14 SOLAR ENERGY↗

Surface Stress Characterization and Trends in Thermally Strengthened Photovoltaic Module Glass

Simultaneous changes in photovoltaic (PV) module architecture-such as increased area, replacing the polymeric backsheet with a glass backsheet, and reducing glass thickness from 3.2 to 2.0 mm-have resulted in a novel failure called spontaneous glass breakage. Spontaneous glass breakage results in front and/or rear glass failure without any obvious cause. The resulting low-energy fracture patterns have raised concerns about the thermal strengthening in 2.0-mm glass. We present validation of a nondestructive method for measuring the glass surface stress in PV modules. We use a scattered light polariscope to examine the glass properties of 11 modules from 6 solar fields, with and without spontaneous glass breakage. Based on a Mann-Whitney test p-value of 1.4 x 10-6, we conclude that there is a correlation between lower surface stress and susceptibility to spontaneous breakage. A Kendall's Tau test p-value of 2.0 x 10-4 indicates a correlation between increased module area and lower surface stress. We find that 2.0-mm glass can be, and often is, fully tempered (surface stress ≥69 MPa), but inspecting the fracture pattern is not a reliable way to assess the amount of thermal strengthening. A combination of factors, not just surface stress, influences glass breakage.

14 SOLAR ENERGY↗

Diethylenetriamine-functionalized graphene oxide: Insights into ion adsorption and applications in rare earth element separation

The growing demand for critical minerals and materials requires atom- and energy-efficient, selective separations to overcome the challenges posed by the similar chemical and physical properties of the rare earth elements (REEs) and their low concentrations in unconventional domestic feedstocks. Here, in this study, we developed diethylenetriamine-functionalized graphene oxide (DETA-GO) as a membrane material for REE adsorption and separation. Synthesis conditions were optimized to maximize nitrogen incorporation while also preserving GO dispersibility for facile membrane fabrication. We investigated the mechanism of amine functionalization, the nitrogen-bonding configurations, the organization of the interlayer transport channels, and the resulting effects on ion and water transport for REE separations. Neat-GO and DETA-GO multilayer laminate membranes were fabricated by vacuum filtration onto polymer supports. To investigate the effects of amine functionalization, the membranes were characterized using scanning electron microscopy, Raman, Fourier transform infrared, and X-ray photoelectron spectroscopy, as well as grazing-incidence X-ray diffraction measurements. Ion permeation experiments with representative lanthanum (La 3+ ) and ytterbium (Yb 3+ ) solutions revealed enhanced ion adsorption and water transport through DETA-GO membranes compared to neat-GO. The strong affinity of the membranes for multivalent REEs was also validated with conductivity and inductively coupled plasma mass spectrometry measurements. Atomistic insight into the role of amine functionalization in modulating nanochannel architecture and long-term stability, optimizing adsorption sites, and regulating REE and water transport was obtained using classical molecular dynamics simulations. Collectively, our joint experimental and theoretical study demonstrates the potential of DETA-GO membranes for selective REE separations, offering insights into ion-binding mechanisms, water-transport properties, and nanochannel optimization for the recovery of critical materials from aqueous feedstocks.

Adsorbent↗

Sensory stimulation for upper limb amputations modulates adaptability of cortical large-scale systems and combination of somatosensory and visual inputs

Abstract Touch-like phantom limb sensations can be elicited through targeted transcutaneous electrical nerve stimulation (tTENS) in individuals with upper limb amputation. The corresponding impact of sensory stimulation on cortical activity remains an open question. Brain network research shows that sensorimotor cortical activity is supported by dynamic changes in functional connections between relevant brain regions. These groups of interconnected regions are functional modules whose architecture enables specialized function and related neural processing supporting individual task needs. Using electroencephalographic (EEG) signals to analyze modular functional connectivity, we investigated changes in the modular architecture of cortical large-scale systems when participants with upper limb amputations performed phantom hand movements before, during, and after they received tTENS. We discovered that tTENS substantially decreased the flexibility of the default mode network (DMN). Furthermore, we found increased interconnectivity (measured by a graph theoretic integration metric) between the DMN, the somatomotor network (SMN) and the visual network (VN) in the individual with extensive tTENS experience. While for individuals with less tTENS experience, we found increased integration between DMN and the attention network. Our results provide insights into how sensory stimulation promotes cortical processing of combined somatosensory and visual inputs and help develop future tools to evaluate sensory combination for individuals with amputations.

60 APPLIED LIFE SCIENCES↗

Final Report for ARPA-E LOCOMOTIVES Advanced Locomotive Technology and Rail Infrastructure Optimization System (ALTRIOS) Project

The Advanced Locomotive Technology and Rail Infrastructure Optimization System (ALTRIOS) is a unique, fully integrated, open-source software tool used to evaluate strategies for cost-effectively deploying advanced locomotive technologies and associated infrastructure. ALTRIOS simulates freight-demand-driven train scheduling, mainline meet-pass planning, locomotive dynamics, train dynamics, energy conversion efficiencies, and energy storage dynamics of line-haul train operations. Because new locomotives represent a significant long-term capital investment and new technologies must be thoroughly demonstrated before deployment, this tool provides guidance on the risk/reward trade-offs and operation integration of different technology rollout strategies. An open, integrated simulation tool is valuable for identifying future research needs and making decisions on technology development, routes, and train selection. This final report details the ALTRIOS software architecture, major modules and components, and data validation process. It demonstrates the software's utility through a 30-year rollout case study targeting high penetration of advanced powertrain technologies by 2050 for two BNSF Railway routes: loaded taconite ore trains from Hibbing, Minnesota, to Superior, Wisconsin, and mixed-freight trains from Superior to Minneapolis, Minnesota.

33 ADVANCED PROPULSION SYSTEMS↗

X-Ray and Particle Detection With the Si(Li) Tracker Module of the GAPS Experiment

Here, this work describes the architecture and the experimental results from the characterization of the lithium-drifted silicon (Si(Li)) detector module, which constitutes the building block of the tracker in the general antiparticle spectrometer (GAPS) experiment to search for dark matter. The instrument is designed for the identification of low-energy cosmic anti-nuclei (antiprotons, antideuterons, and antihelium) to be performed during an Antarctic long-duration balloon flight scheduled for late 2025. The GAPS Si(Li) tracker, that is the core of the instrument, is the assembly of 252 modules, each comprised of four Si(Li) detectors and a full custom-integrated circuit designed for detector readout and produced in a commercial 180-nm planar CMOS technology. A general overview of the detector module architecture and its components is provided, together with a description of the test setup and the experimental results obtained from the characterization of the low-noise analog readout channel. In order to verify the effective operation of the entire module, results concerning the detection of X-rays from a 241Am source and cosmic muons are also provided.

Manghisoni, Massimo [Università di Bergamo (Italy)↗

Method and system for compact efficient laser architecture

A laser amplifier module having an enclosure includes an input window, a mirror optically coupled to the input window and disposed in a first plane, and a first amplifier head disposed along an optical amplification path adjacent a first end of the enclosure. The laser amplifier module also includes a second amplifier head disposed along the optical amplification path adjacent a second end of the enclosure and a cavity mirror disposed along the optical amplification path.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Smart Silicon Carbide Power Module With Pulse Width Modulation Over Wi-Fi and Wireless Power Transfer-Enabled Gate Driver, Featuring Onboard State of Health Estimator and High-Voltage Scaling Capabilities

A wide range of utility applications require controllable switches with features such as high-voltage blocking and high-current carrying capacity, especially at high pulse width modulation (PWM) frequency. Low- and medium-voltage utility applications such as motor drives and flexible AC transmission systems as well as solid state transformers could also benefit from a low-cost high-voltage switching module. Wide-bandgap semiconductors such as silicon carbide (SiC) and gallium nitride (GaN) metal oxide semiconductor field effect transistors (MOSFETs) are considered to be the present and next-generation device choices, although they have limitations. For relatively high-voltage applications with demanding thermal management, SiC is still the only choice, and GaN dominates the low-voltage regime. This manuscript proposes a new half-bridge power MOSFET module that is suitable for conventional H-bridge of multilevel configurations used in high-voltage applications. Constructed from bare SiC dies, this half-bridge module takes advantage of (1) optimized MOSFET placement inside the module, (2) customized heat exchanger, manifold, and cooling, (3) integrated gate driver module with pulse width modulation (PWM) over wi-fi to eliminate the need for low-voltage signals, (4) wireless power transfer (WPT)-enabled gate driver and other ancillary circuits, (5) and the option to incorporate an onboard state-of-health (SOH) estimator module. The entire architecture has been designed and built at the National Renewable Energy Laboratory (NREL) in Golden, CO.

Ga2O3 devices↗