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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 163 records · Page 9

Computational Screening of Cationic Zeolites for n -Butane/Methane Separations Using Quantitatively Accurate First-Principles-Derived Force Fields

We developed force fields for linear alkanes in Na and Ca-exchanged zeolites based on periodic first-principles calculations with coupled cluster corrections. These force fields were validated by comparing the simulated adsorption properties with extensive experimental data. As an example of using these force fields, we screened silica and aluminosilicate zeolites for separation of n-butane/methane mixtures in several different separation processes. A key step in this screening was the use of an interpolation method to create accurate zeolite structures that take account of the lattice constant changes for different Si/Al ratios for a given zeolite topology. We focused on zeolite structures that have known synthesis routes, so the materials selected from our calculations can be tested experimentally. Several promising materials that show good separation performance were selected for more detailed simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward Engineering of Solution Microenvironments for the CO 2 Reduction Reaction: Unraveling pH and Voltage Effects from a Combined Density-Functional–Continuum Theory

Engineering the electrolyte microenvironment represents an attractive route to tuning the selectivity of electrocatalytic reactions beyond catalyst composition and morphology. However, harnessing the full potential of this approach requires understanding the interplay between voltage, electrolyte composition, and adsorbate binding within the electrical double layer, which is absent from the usual theoretical approaches. In this study, we apply a recently developed density functional theory (DFT)–continuum approach based on the effective screening medium method and reference interaction site model (ESM–RISM) to explore electrolyte effects with an enhanced description of the electrochemical interface. Furthermore, applying this method to the binding of CO adsorbates in potassium-containing electrolytes on copper, a problem of direct relevance to CO 2 electroreduction to value-added products, we show that the interdependence of voltage and pH leads to an unexpected change in adsorption site preference on Cu(001) terraces. Our findings highlight the often-overlooked importance of the electrical double-layer structure for predicting catalyst operation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanoscale Amorphization of Poly(Triarylamine) for Efficient and Stable Inverted Perovskite Photovoltaics

Perovskite solar modules require hole-selective layers that combine efficient charge extraction, interfacial uniformity and scalable processing. Poly(triarylamine) (PTAA) is widely used in high-performance inverted perovskite photovoltaics, but its nanoscale crystallization and aggregation on indium tin oxide can disrupt film continuity, increase interfacial recombination and limit module stability. Here we show that 4-fluorobenzylphosphonic acid (4FBPA) modifies the surface of indium tin oxide to induce nanoscale amorphization of PTAA, forming a uniform sub-10-nm hole-selective layer. The molecule binds to indium tin oxide through a dehydration reaction, tunes the work function and surface free energy of the photoanode, and improves energy-level alignment with PTAA. The resulting amorphous PTAA film shows enhanced conductivity and hole extraction, suppresses non-radiative recombination at the buried interface and promotes more uniform perovskite growth. Inverted perovskite solar cells reach a power conversion efficiency of 26.63%, while blade-coated modules achieve a certified quasi-steady-state efficiency of 23.01%. The modules retain 95.9% of their initial efficiency after 2,600 hours of maximum-power-point operation under 1-sun illumination at 65 +- 5 degrees C in nitrogen. These results identify nanoscale amorphization of polymeric hole-selective layers as a route to efficient and stable inverted perovskite photovoltaics.

14 SOLAR ENERGY↗

Genomic insights into the origin, domestication and diversification of Brassica juncea

Despite early domestication around 3000 BC, the evolutionary history of the ancient allotetraploid species Brassica juncea (L.) Czern & Coss remains uncertain. Here, we report a chromosome-scale de novo assembly of a yellow-seeded B. juncea genome by integrating long-read and short-read sequencing, optical mapping and Hi-C technologies. Nuclear and organelle phylogenies of 480 accessions worldwide supported that B. juncea is most likely a single origin in West Asia, 8,000–14,000 years ago, via natural interspecific hybridization. Subsequently, new crop types evolved through spontaneous gene mutations and introgressions along three independent routes of eastward expansion. Selective sweeps, genome-wide trait associations and tissue-specific RNA-sequencing analysis shed light on the domestication history of flowering time and seed weight, and on human selection for morphological diversification in this versatile species. Our data provide a comprehensive insight into the origin and domestication and a foundation for genomics-based breeding of B. juncea.

59 BASIC BIOLOGICAL SCIENCES↗

Phase-based design of CO 2 capture, transport, and storage infrastructure via SimCCS 3.0

The design of optimal infrastructure is essential for the deployment of commercial and large-scale carbon capture and storage (CCS) technology. During the design process, it is important to consider CO 2 capture and storage locations and CO 2 transportation pipelines to minimize the total project cost. SimCCS, first introduced in 2009, is an integrated open-source tool to optimize CCS infrastructure. The core CCS infrastructure design problem in SimCCS is structured as a mixed-integer linear programming problem by selecting the optimal pipeline routes, searching CO 2 source capture and storage locations, and determining the corresponding CO 2 amounts to meet desired capture targets. Multiple important and practical features have been developed to the latest version of SimCCS, SimCCS 3.0 . One of these features is phase-based modeling which enables users to dynamically design the CCS infrastructure. We demonstrate the phased-based modeling capability using two CCS infrastructure optimization case studies. The results from these case studies reveal that the phase-based modeling capability in SimCCS is particularly useful to optimize the dynamic deployment of CCS projects.

54 ENVIRONMENTAL SCIENCES↗

Redox-active on-surface polymerization of single-site divalent cations from pure metals by a ketone-functionalized phenanthroline

Metallic iron, chromium, or platinum mixing with a ketone-functionalized phenanthroline ligand on a single crystal gold surface demonstrates redox activity to a well-defined oxidation state and assembly into thermally stable, one dimensional, polymeric chains. The diverging ligand geometry incorporates redox-active sub-units and bi-dentate binding sites. The gold surface provides a stable adsorption environment and directs growth of the polymeric chains, but is inert with regard to the redox chemistry. These systems are characterized by scanning tunnelling microscopy, non-contact atomic force microscopy, and X-ray photoelectron spectroscopy under ultra-high vacuum conditions. The relative propensity of the metals to interact with the ketone group is examined, and it is found that Fe and Cr more readily complex the ligand than Pt. The formation and stabilization of well-defined transition metal single-sites at surfaces may open new routes to achieve higher selectivity in heterogeneous catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The role of pressure in inverse design for assembly

Isotropic pairwise interactions that promote the self-assembly of complex particle morphologies have been discovered by inverse design strategies derived from the molecular coarse-graining literature. While such approaches provide an avenue to reproduce structural correlations, thermodynamic quantities such as the pressure have typically not been considered in self-assembly applications. In this work, we demonstrate that relative entropy optimization can be used to discover potentials that self-assemble into targeted cluster morphologies with a prescribed pressure when the iterative simulations are performed in the isothermal-isobaric ensemble. The benefits of this approach are twofold. First, the structure and the thermodynamics associated with the optimized interaction can be controlled simultaneously. Second, by varying the pressure in the optimization, a family of interparticle potentials that all self-assemble the same structure can be systematically discovered, allowing for a deeper understanding of self-assembly of a given target structure and providing multiple assembly routes for its realization. Selecting an appropriate simulation ensemble to control the thermodynamic properties of interest is a general design strategy that could also be used to discover interaction potentials that self-assemble structures having, for example, a specified chemical potential.

74 ATOMIC AND MOLECULAR PHYSICS↗

Evaluating the stability and activity of dilute Cu-based alloys for electrochemical CO 2 reduction

Cu-based catalysts currently offer the most promising route to actively and selectively produce value-added chemicals via electrochemical reduction of CO 2 (eCO 2 R); yet further improvements are required for their wide-scale deployment in carbon mitigation efforts. Here, we systematically investigate a family of dilute Cu-based alloys to explore their viability as active and selective catalysts for eCO 2 R through a combined theoretical–experimental approach. Using a quantum–classical modeling approach that accounts for dynamic solvation effects, we assess the stability and activity of model single-atom catalysts under eCO 2 R conditions. Our calculations identify that the presence of eCO2R intermediates, such as CO*, H*, and OH*, may dynamically influence the local catalyst surface composition. Additionally, we identify through binding energy descriptors of the CO*, CHO*, and OCCO* dimer intermediates that certain elements, such as group 13 elements (B, Al, and Ga), enhance the selectivity of C 2+ species relative to pure Cu by facilitating CO dimerization. The theoretical work is corroborated by preliminary testing of eCO 2 R activity and selectivity of candidate dilute Cu-based alloy catalyst films prepared by electron beam evaporation in a zero-gap gas diffusion electrode-based reactor. Of all studied alloys, dilute CuAl was found to be the most active and selective toward C 2+ products like ethylene, consistent with the theoretical predictions. Finally, we attribute the improved performance of dilute CuAl alloys to more favorable dimerization reaction energetics of bound CO species relative to that on pure Cu. In a broader context, the results presented here demonstrate the power of our simulation framework in terms of rational catalyst design.

30 DIRECT ENERGY CONVERSION↗

Embracing disorder in quantum materials design

Many of the most exciting materials discoveries in fundamental condensed matter physics are made in systems hosting some degree of intrinsic disorder. While disorder has historically been regarded as something to be avoided in materials design, it is often of central importance to correlated and quantum materials. This is largely driven by the conceptual and theoretical ease to handle, predict, and understand highly uniform systems that exhibit complex interactions, symmetries, and band structures. In this Perspective, we highlight how flipping this paradigm has enabled exciting possibilities in the emerging field of high entropy materials, focusing primarily on high entropy oxide and chalcogenide quantum materials. These materials host high levels of cation or anion compositional disorder while maintaining unexpectedly uniform single crystal lattices. The diversity of atomic scale interactions of spin, charge, orbital, and lattice degrees of freedom are found to emerge into coherent properties on much larger length scales. Thus, altering the variance and magnitudes of the atomic scale properties through elemental selection can open new routes to tune global correlated phases, such as magnetism, metal–insulator transitions, ferroelectricity, and even emergent topological responses. The strategy of embracing disorder in this way provides a much broader pallet from which functional states can be designed for next-generation microelectronic and quantum information systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Polarization-entangled source for flex-grid C+L-band quantum networks

We demonstrate an ultrabroadband polarization-entangled source integrating both C- and L-band wavelength-selective switches for spectral routing and allocation in a single fiberized setup, verifying high fidelity through tomography of all 150 pairs of 25 GHz-wide channels.

Alshowkan, Muneer↗

Audi e-tron Green Light Optimized Speed Advisory On-Road Data

To aid researchers in studying the capabilities and benefits of vehicle-to-infrastructure communication, Argonne National Laboratory collected a robust set of on-road driving data of the Audi Green Light Optimized Speed Advisory (GLOSA) system implemented in the e-tron battery electric vehicle. This dataset includes 33 tests, each roughly 27 miles in length and roughly 45 to 75 minutes in duration. The team selected Kane County Highway Route 34 from Main Street in Batavia, Illinois to Middlecreek Lane in St. Charles, Illinois as the route do to its high density of GLOSA-active lights and the most opportunities to observe the system per hour of test time. The data include parameters from the following sources: GLOSA system driving the dash indicators, multiple powertrain parameters including real-time battery power/energy consumption, GPS, front radar gap, and rear radar gap. ![audio-e-tron image](audi-e-tron.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Embracing Disorder in Quantum Materials Design

Many of the most exciting materials discoveries in fundamental condensed matter physics are made in systems hosting some degree of intrinsic disorder. While disorder has historically been regarded as something to be avoided in materials design, it is often of central importance to correlated and quantum materials. This is largely driven by the conceptual and theoretical ease to handle, predict, and understand highly uniform systems that exhibit complex interactions, symmetries, and band structures. In this Perspective, we highlight how flipping this paradigm has enabled exciting possibilities in the emerging field of high entropy materials, focusing primarily on high entropy oxide and chalcogenide quantum materials. These materials host high levels of cation or anion compositional disorder while maintaining unexpectedly uniform single crystal lattices. The diversity of atomic scale interactions of spin, charge, orbital, and lattice degrees of freedom are found to emerge into coherent properties on much larger length scales. Thus, altering the variance and magnitudes of the atomic scale properties through elemental selection can open new routes to tune global correlated phases, such as magnetism, metal–insulator transitions, ferroelectricity, and even emergent topological responses. The strategy of embracing disorder in this way provides a much broader pallet from which functional states can be designed for next-generation microelectronic and quantum information systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Barriers and Benefits: Understanding Riders’ Views on Pooled Rideshare in the U.S.

This manuscript provides actionable recommendations to enhance user satisfaction and address existing barriers regarding pooled rideshare (PR) in the United States. Despite PR’s intended benefits, such as reduced traffic congestion and cost savings, its adoption remains limited. To identify these actionable items, a U.S. nationwide survey with 5385 participants explored transportation preferences, barriers, and motivators for PR use in the summer of 2021. First, two factor analyses were conducted. The first factor analysis identified the five factors associated with one’s willingness to consider PR (time/cost, traffic/environment, safety, privacy, and service experience). The second factor analysis revealed the four factors related to ways to optimize one’s PR experience (comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety). Privacy concerns, for instance, were found to reduce the likelihood of PR adoption by 77%, and convenience had the potential to increase it by 156%. A structural equation model evaluated the relationships among these nine key factors influencing PR usage to develop the Pooled Rideshare Acceptance Model (PRAM). The privacy, safety, trust service, and convenience factors each had a significant large effect (Cohen’s f 2 > 0.35) on the model. PRAM was extended using multigroup analyses to reveal the nuanced impact of 16 demographics, including gender, generation, rideshare experience, etc., highlighting the need for tailored strategies to improve PR acceptance through the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMAs). Multiple workshops were held with diverse audiences to translate the team’s findings to date into 84 actionable recommendations, categorized across topical areas like safety, routing, driver and passenger selection, user education, etc. These findings are a foundation for a future study to determine which items resonate with different user groups. In the meantime, the actional items serve as a user-driven resource for policymakers, transportation network companies, and researchers, offering a roadmap to potential improvements to PR services to address existing concerns with the goal of increasing the usage of PR.

actionable recommendations↗

Flight experience with time-of-arrival control for STOL aircraft in the terminal area

A research program on STOL operating systems is underway at the Ames Research Center. One investigation is concerned with design, analysis, and flight test of promising four-dimensional RNAV systems. One promising system generates a capture flight path from the present aircraft position to a waypoint on a selected fixed STOL approach route. It predicts arrival time at the runway and controls time and position along the path. The system was flight tested using a digital avionics system on a Convair 340 and on an experimental powered-lift STOL airplane. Flight tests in the flight director mode show that the pilot can choose and change the desired time of arrival, and meet this time within a few seconds, in spite of navigation errors and varying winds. Initial tests of the automatic mode using a flight simulator and the NASA Augmentor Wing Jet STOL Research Aircraft (AWJSRA) show that good time control was achieved at the cost of excess throttle activity. This fault was later corrected.

Neuman, F.↗

High-power RF switch

Switch designed for vacuum environments can handle 5 kilowatts of microwave power. Arcing between conductors is prevented by filling gaps with Teflon rather than with inert gas as in conventional switches. Thus, switch is not susceptible to gas leakage, problem faced by conventional switches in high-vacuum applications. Compact three-port switch, developed for microwave radar transmitters aboard spacecraft, is operated by depressing spring-mounted insulating pins that can be remotely actuated by relay. When pin is depressed, it routes microwave signals to selected output port.

Caro, E. R.↗

Computing Proximity to Threat Along Uncertain Trajectory to Support Urban Air Mobility

Many airspace threats affect the selection of a flight route, such as terrain, physical obstacles, adverse weather, and special-use airspace, among others. Threat avoidance during Urban Air Mobility (UAM) and Low Altitude Mobility (LAM) flights is especially challenging due to their lower cruising altitudes. These operations may be exposed to buildings, towers, trees, terrain undulations, etc., along much of their flight route. Moreover, these low-altitude flights in urban environments are expected to encounter very busy airspace, increasing the workload associated with threat avoidance. The Proximity to Threat (PtT) function aims to support onboard or remote pilots by computing the risk from geospatial threats in the airspace along an aircraft’s flight path. The threats are both static entities and dynamic airspace restrictions that have been modeled and stored in geo-referenced mapping databases. The flight path may be specified by waypoints, airways, or similar discrete route elements or by a time series of closely spaced position and altitude points. Flight path uncertainty can also be taken into account by assuming both the position and altitude to be sampled from two normal distributions, each being specified by a mean and variance. PtT uses this additional information to verify that the flight path remains clear of threats along a wider path or if a position is reached earlier or later than anticipated, assuring the pilot or operator that there will be an available safety margin even if the aircraft deviates due to one or more occurrences of unexpected wind gusts, mechanical failures, airspeed changes, collision avoidance maneuvers, etc. The client can specify an uncertainty confidence level to bound the set of trajectories evaluated for threats so that the confidence level corresponds to the client’s risk tolerance under the expected conditions. PtT can be used as a pre-flight planning tool to determine a safe route through known threats and in-flight to avoid emerging or changing threats. In this report, we present the PtT function, discuss how the trajectory uncertainty is incorporated into the PtT function, and describe the use of this PtT function in a representative scenario.

urban air mobility↗

Concerted Bimetallic Nanocluster Synthesis and Encapsulation via Induced Zeolite Framework Demetallation for Shape and Substrate Selective Heterogeneous Catalysis

Abstract Bimetallic nanoparticle encapsulation in microporous zeolite crystals is a promising route for producing catalysts with unprecedented reaction selectivities. Herein, a novel synthetic approach was developed to produce PtZn x nanoclusters encapsulated inside zeolite micropores by introducing Pt 2+ cations into a zincosilicate framework via ion exchange, and subsequent controlled demetallation and alloying with framework Zn. The resulting zeolites featured nanoclusters with sizes of approximately 1 nm, having an interatomic structure corresponding to a PtZn x alloy as confirmed by pair distribution function (PDF) analysis. These materials featured simultaneous shape and substrate specificity demonstrated by the selective production of p ‐chloroaniline from the competitive hydrogenation of p ‐chloronitrobenzene and 1,3‐dimethyl‐5‐nitrobenzene.

Iida, Takayuki↗