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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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Multi-Phenomenology Explosion Monitoring (MultiPEM) Toolbox provides a capability for post-detonation characterization focusing on yield estimation; Synthesize information from multiple sensor types; Leverage historical databases to inform statistical models; Allows for rapid or comprehensive analysis; Implemented in R code.
Due to the complexity and recalcitrance of lignin, its chemical characterization is a key factor preventing the valorization of this abundant material. Multi-angle light scattering (MALS) is becoming a sought-after technique for absolute molecular weight (MW) determination of polymers and proteins. Lignin is a suitable candidate for MW determination via MALS, yet further investigation is required to confirm its absolute MW values and molecular size. Studies aiming to break down lignin into a variety of renewable products will benefit greatly from a simple and reliable determination method like MALS. Recent pioneering studies, discussed in this review, addressed several key challenges in lignin’s MW characterization. Nevertheless, some lignin-specific issues still need to be considered for in-depth characterization. This study explores how MALS instrumentation manages the complexities of determining lignin’s MW, e.g., with simultaneous fractionation and fluorescence interference mitigation. Additionally, we rationalize the importance of a more detailed light scattering analysis for lignin characterization, including aspects like the second virial coefficient and radius of gyration.
During the catalytic step that precedes O–O bond formation in Photosystem II, a water molecule deprotonates and moves next to the water-splitting Mn 4 Ca cluster’s O5 oxo bridge. The relocated oxygen, known as O6 or Ox, may serve as a substrate, combining with O5 to form O 2 during the final step in the catalytic cycle, or may be positioned to become a substrate during the next catalytic cycle. Recent serial femtosecond X-ray crystallographic studies show that the flexibility of D1-E189 plays a critical role in facilitating the relocation of O 6 /Ox. In this study, the D1-E189G and D1-E189S mutations were characterized with FTIR difference spectroscopy. The data show that both mutations support Mn 4 Ca cluster assembly, substantially inhibit advancement beyond the S 2 state, and alter the network of H bonds that surrounds the Mn 4 Ca cluster. Previously, the D1-E189Q, D1-E189K, and D1-E189R mutations were shown to have little impact on the activity, electron transfer rates, or spectral properties of Photosystem II. A rationale for this behavior is presented. The residue D1-E329 interacts with water molecules in the O1 water network that has been suggested recently to supply substrate during the catalytic cycle. Characterization of the D1-E329A mutant with FTIR difference spectroscopy shows that this mutation does not substantially perturb the structure of PSII or the water molecules whose O–H stretching modes change during the catalytic cycle. Furthermore, this result provides additional evidence that the water molecules whose vibrational properties change during the S 1 to S 2 transition are confined approximately to the region bounded by D1-N87, D1-N298, and D2-K317.
X-ray absorption spectroscopy (XAS) is a powerful spectroscopic technique for characterizing catalytic active sites. In particular, X-ray Absorption Near Edge Structure (XANES) provides insights into the oxidation state and local coordination environment of the absorbing atom, shedding light on the catalytic structure. Computational XANES simulations provide one-on-one correspondence between the molecular structure and their corresponding spectra, making them an effective approach for interpreting experimental XANES features. This work outlines various theories used to simulate XANES spectra and highlights recent advancements in computational XANES applications for homogeneous, heterogeneous, and single-atom catalysts focusing on identifying the active site structures, the site heterogeneity, and the dynamic evolution of catalysts.
Cerium oxide (ceria) plays an important and fascinating role in heterogeneous catalysis as illustrated by its versatile use as a catalyst, a catalyst support, or a promotor in various oxidation and reduction reactions. Central to these reactions is the rich defect chemistry, facile redox capability, and unusual acid-base properties of ceria. Understanding the unique redox and acid-base properties of ceria is essential to build the structure-catalysis relationship so that improved catalytic functions can be achieved for ceria-based materials. Among the characterization toolbox, spectroscopic approach indisputably stands out for its unparalleled power in offering chemical insights into the surface properties of ceria at atomic and molecular level. In this review, we summarize advances in revealing the redox and acid-base properties of ceria via a variety of spectroscopic methods including optical, X-ray, neutron, electronic and nuclear spectroscopy. Both direct spectroscopy characterization and its coupling with probe molecules are analyzed to illustrate how the nature, strength and density of different surface sites are influenced by the pretreatment, the morphology and size of ceria nanoparticles. Further directions in taking advantage of in situ/operando spectroscopy for better understanding the catalysis of ceria-based materials are detailed in the summary and outlook section.
The role of inhomegeneity in determining the properties of correlated electron systems is poorly understood because of the dearth of structural probes of disorder at the nanoscale. Advances in both neutron and x-ray scattering instrumentation now allow comprehensive measurements of diffuse scattering in single crystals over large volumes of reciprocal space, enabling structural correlations to be characterized over a range of length scales from 5 to 200 angstroms or more. When combined with new analysis tools, such as three-dimensional difference pair-distribution functions, these advanced capabilities have produced fresh insights into the interplay of structural fluctuations and electronic properties in a broad range of correlated electron materials. This review describes recent investigations that have demonstrated the importance of understanding structural inhomogeneity pertaining to phenomena as diverse as superconductivity, charge density wave modulations, metal-insulator transitions, and multipolar interactions.
This project addresses the systematic lack of predictive capabilities by spray models within engine CFD codes. We develop a new modeling approach to predict the breakup of diesel sprays based on recent literature showing that liquid turbulence plays a fundamental role in spray atomization. A new body of quantitative validation data is also developed as a critical element of the project, leveraging the joint capabilities of Georgia Tech’s high-pressure continuous-flow spray chamber and Argonne National Lab’s near-nozzle x-ray diagnostics at the Advanced Photon Source. This project contributes spatially-resolved measurements of drop size distribution within well-characterized diesel injectors, Spray A and D, from the Engine Combustion Network (ECN) to the engine combustion community for the first time. Utilizing this new body of measurements, we validate and demonstrate a new spray model for diesel sprays, termed the KH-Faeth model, that predicts global and local spray characteristic more accurately than the widely adopted and employed KH model. Predicted drop size distributions are seen to predict measured drops sizes both quantitatively and predictively, with accurate response in droplet size distributions over a wide range of ambient density, injection pressure, and injector nozzle size (Spray A and D) without model tuning. The KH-Faeth model can reduce error in the predicted centerline droplet size profile by up to 80% for ECN Spray D simulations when compared to use of the widely employed KH model.
REBa 2 Cu 3 O 7-δ (REBCO, RE = rare earth) tapes with high critical current can be very impactful in high magnetic field applications at low temperatures and power applications at high temperatures. A pilot-scale Advanced Metal Organic Chemical Vapor Deposition (MOCVD) method was used to fabricate 50-m-long, 4+μm-thick REBCO tape in a single pass. Critical currents 3.3x that of commercial HTS tapes were achieved at 20 K, 12 T in these 50-m-long tapes. An in-line 2D X-ray Diffraction (XRD) system has been used to assess the quality of the long tapes in real-time, during manufacturing. The key peaks of REBCO, REO, and BZO phases were identified and utilized for tape quality analysis. Furthermore, a 20-m tape made by Advanced MOCVD was tested over its entire length by reel-to-reel (R2R) scanning Hall-probe microscopy (SHPM) at 65 K, 0.25 T, 2 T, and 4 T. 4-mm-wide strands of Advanced MOCVD tapes showed mean critical currents at 65 K of 530 A, 200 A, and 104 A at 0.25 T, 2 T, and 4 T respectively. The combined use of in-line and offline characterization techniques provides a reliable approach for assessing long REBCO tapes during manufacturing, serving as an effective feedback source for quality control in scaled-up REBCO tape deposition processes. This advancement contributes to the production of longer and more uniform high-performance REBCO tapes for large-scale, high-field superconducting applications
Tonga is facing a transportation sector characterized by private passenger vehicles, poorly maintained roads and walkways, and an inadequate public transit system. By understanding detailed global and regional trends for transport energy efficiency and electric vehicles (EVs) within this context, the Government of Tonga can proactively plan its future transportation systems. In addition to global and regional trends, this presentation also briefly examines Tonga's own transportation policies and actions. Jurisdictions leading in EV adoption have implemented policies such as reducing taxes on EVs compared to internal combustion engine (ICE) vehicles, providing subsidies and rebates for EV charger installation, instituting an age limit on imported ICE vehicles, and developing EV maintenance courses to expand the skill set of current automotive technicians. This presentation was developed for the Pacific Islands Workshop on Electric Mobility, held from November 28th to November 30th 2022 in Fiji. NREL presented virtually and the conference was sponsored by the Pacific Centre for Renewable Energy and Energy Efficiency (PCREEE).
CdTe is presently the cost-leading thin-film PV technology, directly competing with Si at scale, even when domestically manufactured. While an impressive technology, its efficiency remains much below the detailed balance limit with the largest cause due to its low photovoltage and fill factor. To realize gains, the carrier concentration, minority carrier lifetime, and interface recombination all need to be improved simultaneously over historic levels. Using a new defect chemistry (group V doping instead of copper) has been identified as a viable route using single crystal systems. This project focused on implementing this new defect chemistry in scalable, polycrystalline thin-film photovoltaic CdTe devices with tasks focusing improvements to the front interface, absorber, and rear interface as well as capability development & stakeholder engagement. The goal of the project was to establish a strategy using devices, test structures, detailed characterization, and modeling to quantify the sources of losses in state-of-the-art CdTe photovoltaic devices. Using this strategy and advanced synthesis, losses at the front interface, absorber, and rear interface were worked on in parallel. The final objective was to significantly improve the voltage deficit in CdTe devices to enable improvements in photovoltage and efficiency that can be implemented by industry in the near-term. Over the course of the project, the team developed new characterization techniques, analysis, and modeling which were then applied to state-of-the-art materials generated internally and collaboratively. In particular to enable rapid progress, NREL worked closely with First Solar where NREL grew complete devices as well as ones that interleaved process steps where First Solar had completed different steps such as absorber growth or absorber growth and activation using their baseline methods. Using detailed characterization and analysis including photoemission, photoluminescence, and scanning probe techniques enabled understanding of the loss pathways and area for improvements in our own and First Solar s materials. Ultimately, this contributed to the first series of new world record CdTe efficiencies since 2016, culminating in a 23.1% certified cell that was P-doped along with As-doped cells of similar performance. Internally, NREL improved the statistical variation in baseline As-doped devices and improved average photovoltage by over 100 mV. This was done through an improvement in absorber quality, changed front interface, and improved back contact. In addition to materially improving the fabrication processes at NREL, characterization, analysis, and modeling were developed and disseminated. NREL also played a pivotal role in community building over the course of this project working closely with the Cadmium Telluride Accelerator Consortium. NREL worked in a series of collaborations with academic and industry partners, leveraging knowledge and innovations from this project, as well as helped organize a series of workshops to ensure rapid progress in the field. Working closely with the academic community has led to a dissemination of knowledge; working with First Solar as increased US competitiveness First Solar expanded domestic production to ~10 GW and opened new facilities.
Abstract The field of two-dimensional (2D) and layered materials continues to excite many researchers around the world who are eager to advance and innovate viable routes for large scale synthesis, doping and integration of monolayers and the development of unique characterization approaches for studying and harnessing exotic properties that will enable novel device applications. There has been a large interest in 2D materials beyond graphene, with particular emphasis on monoelemental materials (phosphorene, silicene, tellurene, etc. ), 2D compounds (MXenes, oxides, nitrides, carbides and chalcogenides), their alloys and layered van der Waals heterostructures. This is not only indicated by the significant increase in the number of peer reviewed publications each year in this area of research, but also by the surging number of conference sessions focusing on 2D materials beyond graphene. This Perspective article highlights some of the recent advances in the field from a diverse international community of theoretical and experimental researchers who participated in the symposium ‘Beyond Graphene 2D Materials—Synthesis, Properties and Device Applications’ at the Materials Research Society (MRS) Fall 2019 meeting.
Despite the rapid growth of online shopping and research interest in the relationship between online and in-store shopping, national-level modeling and investigation of the demand for online shopping with a prediction focus remain limited in the literature. Here, this paper differs from prior work and leverages two recent releases of the U.S. National Household Travel Survey (NHTS) data for 2009 and 2017 to develop machine learning (ML) models, specifically gradient boosting machine (GBM), for predicting household-level online shopping purchases. The NHTS data allow for not only conducting nationwide investigation but also at the level of households, which is more appropriate than at the individual level given the connected consumption and shopping needs of members in a household. We follow a systematic procedure for model development including employing Recursive Feature Elimination algorithm to select input variables (features) in order to reduce the risk of model overfitting and increase model explainability. Among several ML models, GBM is found to yield the best prediction accuracy. Extensive post-modeling investigation is conducted in a comparative manner between 2009 and 2017, including quantifying the importance of each input variable in predicting online shopping demand, and characterizing value-dependent relationships between demand and the input variables. In doing so, two latest advances in machine learning techniques, namely Shapley value-based feature importance and Accumulated Local Effects plots, are adopted to overcome inherent drawbacks of the popular techniques in current ML modeling. The modeling and investigation are performed at the national level, with a number of findings obtained. The models developed and insights gained can be used for online shopping-related freight demand generation and may also be considered for evaluating the potential impact of relevant policies on online shopping demand.
Environmental challenges and development require plants to reallocate resources between primary and specialized metabolites to survive. Genome-scale metabolic models, which map carbon flux through metabolic pathways, are a valuable tool in the study of tradeoffs that arise at this interface. Due to annotation gaps, models that characterize all the enzymatic steps in individual specialized pathways and their linkages to each other and to central carbon metabolism are difficult to construct. Recent studies have successfully curated subsystems of specialized metabolism and characterized the interfaces where flux is diverted to the precursors of glucosinolates, terpenes, and anthocyanins. Although advances in metabolite profiling can help to constrain models at this interface, quantitative analysis remains challenging because of the different timescales on which specialized metabolites from constitutive and reactive pathways accumulate.
MXenes are a large family of two-dimensional materials that are attractive for energy storage due to their high-rate charging capabilities as well as for electrochemical actuators, water purification, and many other technologies. Ion intercalation during electrochemically driven charge and discharge processes is the fundamental process associated with MXene functionality, which we have characterized here using in situ and operando X-ray reflectivity (XRR). Experiments performed at the Advanced Photon Source at Argonne National Laboratory monitored the changes in the structure of a Ti 3 C 2 MXene film on a platinum current collector as a function of static applied potential between 0.3 and –0.7 V vs Ag/AgCl in an aqueous 0.1 M Li 2 SO 4 electrolyte. Negative potential sweeps lead to a contraction of 1.2 Å in the interlayer spacing and a loss of electron density between the layers, likely due to Li + ion insertion and water removal. The change in lattice spacing includes a continuous variation vs potential as well as an additional discrete contraction that occurs near –0.35 V that has the characteristics of a first-order transition. The continuous change in the MXene interlayer spacing is associated with the capacitive charge, while the discrete change in structure correlated to the weak feature in the cyclic voltammogram at –0.35 V can be interpreted as either a pseudocapacitive charging process or a potential-dependent change in capacity.
Catalytic allylic and propargylic C–H aminations present valuable opportunities for the late-stage modification of pharmacophores in drug discovery. However, modern methodology is limited by reliance on expensive transition metal catalysts or slow reactivity. While selenium-catalyzed methods avoid some of these issues, in their current state, they require high catalyst loadings (15 mol %), superstoichiometric quantities of the amine and oxidant source, and long reaction times. Furthermore, our understanding of the mechanism remains incomplete: e.g., what is the catalytically active species, how is the precatalyst converted to it, and what is the role of the ligand? Here, in this paper, we report an N-heterocyclic carbene selenide (NHC-Se) that allows for substantially reduced loadings of selenium without sacrificing reaction time, improves conversions and yields for challenging substrates, and even exhibits the capacity to catalyze 1,4-allylic diamination of alkenes. To understand the origin of the enhanced activity compared to the state-of-the-art NHC-Se precatalyst, we conducted a mechanistic study that supports ligand-free selenium diimide as the active enophile in these systems, while the NHC-derived byproducts, like the corresponding urea, facilitate turnover. We also isolate and structurally characterize NHC-Se mono- and diimido species and explore their mechanistic role. Thus, this work advances C–H amination methodology, our understanding of its mechanistic underpinnings, and selenium chemistry at large.
The testing effect refers to the benefits to retention that result from structuring learning activities in the form of a test. As educators consider implementing test-enhanced learning paradigms in real classroom environments, we think it is critical to consider how an array of factors affecting test-enhanced learning in laboratory studies bear on test-enhanced learning in real-world classroom environments. As such, this review discusses the degree to which test feedback, test format (of formative tests), number of tests, level of the test questions, timing of tests (relative to initial learning), and retention duration have import for testing effects in ecologically valid contexts (e.g., classroom studies). Attention is also devoted to characteristics of much laboratory testing-effect research that may limit translation to classroom environments, such as the complexity of the material being learned, the value of the testing effect relative to other generative learning activities in classrooms, an educational orientation that favors criterial tests focused on transfer of learning, and online instructional modalities. We consider how student-centric variables present in the classroom (e.g., cognitive abilities, motivation) may have bearing on the effects of testing-effect techniques implemented in the classroom. We conclude that the testing effect is a robust phenomenon that benefits a wide variety of learners in a broad array of learning domains. Still, studies are needed to compare the benefit of testing to other learning strategies, to further characterize how individual differences relate to testing benefits, and to examine whether testing benefits learners at advanced levels.
Flatbands, characterized by their dispersionless energy levels in electronic, magnetic, and phononic systems, hold substantial potential for advancements in electronics and quantum information processing. Most flatbands exist in thermal equilibrium and cannot be easily created or annihilated externally, limiting their flexibility as switchable knobs for use in microelectronics and quantum applications. In our work, we demonstrate the generation of a coherent phonon flatband in a GaAs/AlAs superlattice using 800 nm femtosecond laser pulses. This coherent phonon flatband does not correspond to a phonon eigenmode at equilibrium and exhibits strong coupling with two branches of coherently excited longitudinal phonon modes. With molecular dynamics simulations, we show more generally that the coherent phonon flatband can be induced by coherently and spatially modulated optical excitations of superlattice structures. Our results highlight a pathway for coherent phonon flatband creation in the time domain that can be generalized to various superlattice systems, potentially inspiring the realization of coherent flatband generation of other quasiparticles.
While MAX phases offer an exotic combination of ceramic and metallic properties, rendering them a unique class of materials, their applications remain virtually hypothetical. To overcome this shortcoming, a sol–gel based route is introduced that allows access to microwires in the range of tens of micrometers. Thorough structural characterization through XRD, SEM, EDS, and AFM demonstrates a successful synthesis of carbonaceous Cr2GaC wires, and advanced low temperature electronic transport measurements revealed resistivity behavior dominated by amorphous carbon. Here, the tunability of electronic behavior of the obtained microwires is shown by a halide post-synthesis treatment, allowing purposeful engineering of the microwires’ electrical conductivity. Raman studies revealed the polyanionic nature of the intercalated halides and a slow decrease in halide concentration was concluded from time-dependent conductivity measurements. Based on these findings, the process is considered a viable candidate for fabricating chemiresistive halogen gas sensors.