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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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Correlating Experimentally Determined Hydrogen Binding Energy with Hydrogen Evolution Activity over Metal Monolayers on Molybdenum Nitride

It is well established that hydrogen binding energy (HBE) is a key descriptor for hydrogen evolution reaction (HER) activity, and such a relationship is a useful tool for searching efficient and cost-effective HER catalysts. However, in almost all cases, the HBE values are obtained from density functional theory (DFT) calculations. Here in this study, temperature programmed desorption (TPD) was used to experimentally determine the HBE values of metal monolayers supported on molybdenum nitride (Mo 2 N), and electrochemical measurements were performed on the same surfaces. Combined DFT and kinetic Monte Carlo (kMC) simulations were used to validate the trend observed with TPD and the electrochemical HER activity. Depositing one monolayer of Pt on Mo 2 N led to similar HBE values seen for bulk Pt, and electrochemical measurements showed that monolayer Pt on Mo 2 N had similar HER activity to that of bulk Pt. Similar studies were also performed for monolayer Pd on Mo 2 N to confirm the correlation. This work also demonstrates that Mo 2 N is a promising support to reduce precious metal loading in HER catalysts.

08 HYDROGEN↗
DOE OSTI2024

Theoretical Prediction and Experimental Verification of IrO x Supported on Titanium Nitride for Acidic Oxygen Evolution Reaction

Reducing iridium (Ir) catalyst loading for acidic oxygen evolution reaction (OER) is a critical strategy for large-scale hydrogen production via proton exchange membrane (PEM) water electrolysis. However, simultaneously achieving high activity, long-term stability, and reduced material cost remains challenging. To address this challenge, we develop a frame-work by combining density functional theory (DFT) prediction using model surfaces and proof-of-concept experimental ver-ification using thin films and nanoparticles. DFT results predict that oxidized Ir monolayers over titanium nitride (IrO x /TiN) should display higher OER activity than IrO x while reducing Ir loading. Further, this prediction is verified by depositing Ir monolayers over TiN thin films via physical vapor deposition. The promising thin film results are then extended to commercially viable powder IrO x /TiN catalysts, which demonstrate a lower overpotential and higher mass activity than commercial IrO 2 , and a long-term stability of 250 hours to maintain a current density of 10 mA cm -2 . The superior OER performance of IrO x /TiN is further confirmed using proton exchange membrane water electrolyzer (PEMWE), which shows a lower cell voltage than commercial IrO 2 to achieve a current density of 1 A cm -2 . Both DFT and in situ X-ray absorption spectroscopy reveal that the high OER performance of IrO x /TiN strongly depends on the IrO x - TiN interaction via direct Ir-Ti bonding. This study highlights the importance of close interaction between theoretical prediction based on mechanistic understanding and experimental verification based on thin film model catalysts to facilitate the development of more practical powder IrO x /TiN catalysts with high activity and stability for acidic OER.

08 HYDROGEN↗
DOE OSTI2023

Aerosol jet printing of piezoelectric surface acoustic wave thermometer

Abstract Surface acoustic wave (SAW) devices are a subclass of micro-electromechanical systems (MEMS) that generate an acoustic emission when electrically stimulated. These transducers also work as detectors, converting surface strain into readable electrical signals. Physical properties of the generated SAW are material dependent and influenced by external factors like temperature. By monitoring temperature-dependent scattering parameters a SAW device can function as a thermometer to elucidate substrate temperature. Traditional fabrication of SAW sensors requires labor- and cost- intensive subtractive processes that produce large volumes of hazardous waste. This study utilizes an innovative aerosol jet printer to directly write consistent, high-resolution, silver comb electrodes onto a Y-cut LiNbO 3 substrate. The printed, two-port, 20 MHz SAW sensor exhibited excellent linearity and repeatability while being verified as a thermometer from 25 to 200 ∘ C. Sensitivities of the printed SAW thermometer are $$-96.9\times 1{0{}^{-6}}^{\circ }$$ − 96.9 × 1 0 − 6 ∘ C −1 and $$-92.0\times 1{0{}^{-6}}^{\circ }$$ − 92.0 × 1 0 − 6 ∘ C −1 when operating in pulse-echo mode and pulse-receiver mode, respectively. These results highlight a repeatable path to the additive fabrication of compact high-frequency SAW thermometers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Catlas: an automated framework for catalyst discovery demonstrated for direct syngas conversion

Catalyst discovery is paramount to support access to energy and key chemical feedstocks in a post fossil fuel era. Exhaustive computational searches of large material design spaces using ab initio methods like density functional theory (DFT) are infeasible. We seek to explore large design spaces at relatively low computational cost by leveraging large, generalized, graph-based machine learning (ML) models, which are pretrained and therefore require no upfront data collection or training. We present Catlas, a framework that distributes and automates the generation of adsorbate-surface configurations and ML inference of DFT energies to achieve this goal. Catlas is open source, making ML assisted catalyst screenings easy and available to all. To demonstrate its efficacy, we use Catlas to explore catalyst candidates for the direct conversion of syngas to multi-carbon oxygenates. For this case study, we explore 947 stable/metastable binary, transition metal intermetallics as possible catalyst candidates. On this subset of materials, we are able to predict the adsorption energy of key descriptors, *CO and *OH, with good accuracy (0.16, 0.14 eV MAE, respectively). Using the projected selectivity towards C 2+ oxygenates from an existing microkinetic model, we identified 144 candidate materials. For 10 promising candidates, DFT calculations reveal a good correlation with our assessment using ML. Finally, among the top elemental combinations were Pt–Ti, Pd–V, Ni–Nb, and Ti–Zn, all of which appear unexplored experimentally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Advanced thermal/environmental barrier coatings of high-entropy rare earth disilicates tuned by strong anharmonicity of Eu 2 Si 2 O 7

Advancing thermal/environmental barrier coating (TEBC) materials with integrated thermal-mechanical functions is paramount for safeguarding SiC-based ceramic matrix composites (CMCs) in high-efficiency gas turbines. Herein, we employ a synergistic approach, combining density functional theory (DFT) methods and combinatorial chemistry techniques, to design high-performance and low-cost RE 2 Si 2 O 7 (RE = rare earth elements) TEBC materials tailored for enhanced compatibility with SiC-based CMCs. Expanding on phase stability of alloying pure RE 2 Si 2 O 7 , the investigation extends to the mechanical and thermal properties of solid solution systems, including Er 1/2 Y 3/4 Yb 3/4 Si 2 O 7 , Gd 1/4 Er 1/4 Y 3/4 Yb 3/4 Si 2 O 7 , and Eu 1/4 Er 1/4 Y 3/4 Yb 3/4 Si 2 O 7 . The solid solution systems exhibit a major reduction in lattice thermal conductivity relative to their pure counterparts, achieving ultralow values of 0.25 to 0.39 W m −1 K −1 at 1500 K. Furthermore, the coefficients of thermal expansion (CTE) of these solid solutions are precisely tuned within the desired range for SiC (4.4 to 5.5 × 10 −6 K −1 ), while maintaining good mechanical properties. Here, in particular, the addition of Eu 2 Si 2 O 7 demonstrates to be an important variable to the tuning of CTE and lattice thermal conductivity by leveraging its strong anharmonicity, presenting a pioneering avenue for fine-tuning material properties. In summary, this research not only identifies promising TEBC materials with superior thermal properties, but also introduces a valuable computational material design methodology for the rapid discovery of complex materials for harsh environments.

36 MATERIALS SCIENCE↗
DOE OSTI2023

AL4GAP: Active learning workflow for generating DFT-SCAN accurate machine-learning potentials for combinatorial molten salt mixtures

Machine learning interatomic potentials have emerged as a powerful tool for bypassing the spatiotemporal limitations of ab initio simulations, but major challenges remain in their efficient parameterization. We present AL4GAP, an ensemble active learning software workflow for generating multicomposition Gaussian approximation potentials (GAP) for arbitrary molten salt mixtures. The workflow capabilities include: (1) setting up user-defined combinatorial chemical spaces of charge neutral mixtures of arbitrary molten mixtures spanning 11 cations (Li, Na, K, Rb, Cs, Mg, Ca, Sr, Ba and two heavy species, Nd, and Th) and 4 anions (F, Cl, Br, and I), (2) configurational sampling using low-cost empirical parameterizations, (3) active learning for down-selecting configurational samples for single point density functional theory calculations at the level of Strongly Constrained and Appropriately Normed (SCAN) exchange-correlation functional, and (4) Bayesian optimization for hyperparameter tuning of two-body and many-body GAP models. Here, we apply the AL4GAP workflow to showcase high throughput generation of five independent GAP models for multicomposition binary-mixture melts, each of increasing complexity with respect to charge valency and electronic structure, namely: LiCl–KCl, NaCl–CaCl 2 , KCl–NdCl 3 , CaCl 2 –NdCl 3 , and KCl–ThCl 4 . Our results indicate that GAP models can accurately predict structure for diverse molten salt mixture with density functional theory (DFT)-SCAN accuracy, capturing the intermediate range ordering characteristic of the multivalent cationic melts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A Comfort Model Simplification for Tight Integration with Grid Service Optimizations

Localized generation, storage, and intelligent power electronics are increasingly being integrated into building. The excess storage, thermal, and generation capacity can be used to develop new markets for ancillary services such as peak reduction, voltage and frequency support, or load flattening. Widespread participation in these markets will make the power grid more resilient. However, widespread participation in these markets will require a simple and intuitive control over the excess capacity by the building occupants. Most importantly for adopting these technologies, participation in these markets should not require sacrificing occupant comfort. Many of the proposed control and optimization technologies for supplying the ancillary services do not explicitly incorporate occupant comfort into their models and when they do, generally utilize a rigid constraint on the indoor air temperature set a priori. This reduces flexibility in using excess thermal capacity. It also cannot take into account uncertainties in local factors that affect thermal comfort such as clothing insulation or relative humidity. In this paper we present and justify some assumptions that simplify the standard predictors of thermal comfort. We also develop a regression model of the thermal comfort that is linear with respect to the indoor air temperature. Next we develop the concept of thermal comfort variation that eliminates the dependence of the thermal comfort on uncertain thermal comfort factors. Then, we present a quadratic program utilizing the thermal comfort variation in both the objective function and as a constraint. Finally, we show the results of a time-of-use cost optimization that utilizes the simplified thermal comfort model.

Melin, Alexander↗
DOE OSTI2024

Machine learning and TDDFT software for stopping power computation

(SF-24-012) Stopping power describes the rate that a material slows radiation particles passing through it and is useful in designing many technologies. Few organizations can perform new measurements, which require significant resources and rare equipment, and all others rely on coarse approximations rendered from pre-existing data. Methods for computing stopping power in new materials, such as time-dependent density functional theory (TD-DFT), have only recently (circa-2015) become available but are too computationally costly to use frequently enough to have a pronounced impact. We have created a method that opens a pathway to computing stopping power without any need for experimental data by combining electronic structure computations and machine learning.

Ward, Logan↗
DOE OSTI2021

In vitro evolution-enabled selection of affinity reagents against bio/chem-threats [Slides]

Affinity reagent are molecules whose function depends on specific recognition of a target. The function can allow therapeutic and/or diagnostic applications. The support CBDP pillars are--Understand: high accuracy/sensitivity, low cost, deployable detection; Protect: pre-event treatment of soldiers; and Mitigate: post-event treatment of soldiers; help identifying the need for specific decontamination protocols. The Los Alamos affinity reagents team (LA-ART) can can obtain affinity reagents to any target, on demand, using a well-established in vitro evolution platform. Recent success stories are shared.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Enabling Data Exchange and Data Integration with the Common Information Model: An Introduction for Power Systems Engineers and Application Developers

The Common Information Model (CIM) is an open-source information model that is used to model an electrical network and the various equipment used on the network. CIM is widely used for data exchange of bulk transmission power systems and is finding increasing use for distribution systems. Use of a non-proprietary information model (such as CIM) that has been agreed upon and adopted by numerous utilities, vendors, and researchers allows significant reduction in the effort and cost of data integration. Likewise, adoption of open data platforms built around the CIM increases available functionalities for managing and optimizing the smart grid of the future. This report is intended as an introduction to CIM for utility engineers, power systems researchers, and application developers, providing a broad view of the CIM and how particular profiles can be adapted for various use cases. Unlike most other CIM introduction documents and the International Electrotechnical Commission (IEC) standards (which are mostly targeted to an audience of data scientists, enterprise database managers, and platform developers), this report is intended for users of traditional power systems analysis software and other readers without any prior experience with canonical information models, data profiles, or UML modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Orbital-Free Quantum Simulation Methods for Application to Warm Dense Matter (Final Technical Report)

Predictive simulations for prediction of condensed system behavior in state conditions far from ambient is increasingly crucial to DOE priorities. Warm dense matter (WDM) is the paradigm: temperature T > 1-15 eV, pressures P to 1 Mbar or greater. Experiments under such state conditions are difficult and costly. We summarize work driven by the need and opportunity to make free-energy density functional theory (DFT) as powerful a tool for ab initio simulation of matter under such extreme conditions as ground state DFT is for ordinary matter Advancing orbital-free DFT (OF-DFT) to eliminate the Kohn-Sham (KS) scaling bottleneck in such simulations is the other priority. The concurrent challenge for both goals is the intrinsic complexity of WDM. We summarize 15 years of successes and major progress on (1) free energy exchange-correlation functionals; (2) non-interacting free energy functionals (counterpart to T=0 Kohn-Sham kinetic energy density functionals); (3) rigorous results and constraints for free-energy DFT; (4) software for free energy DFT calculations in both conventional Kohn-Sham and OF-DFT form; (5) de-orbitalization of advanced orbital-dependent ground state functionals for use in OF-DFT; (6) demonstration calculations; (7) ancillary achievements (e.g. major review articles, secondary explorations motivated by primary goals).

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Two-Level Model Predictive Control-Based Approach for Building Energy Management including Photovoltaics, Energy Storage, Solar Forecasting and Building Loads

This paper uses a two-level model predictive control-based approach for the coordinated control and energy management of an integrated system that includes photovoltaic (PV) generation, energy storage, and building loads. Novel features of the proposed local controller include (1) the ability to simultaneously manage building loads and energy storage to achieve different operational objectives such as energy efficiency, economic cost efficiency, demand response and grid optimization through the design of specific power trajectory tracking performance functionals, (2) an energy trim function that minimizes the impact of solar forecasting errors on system performance, and (3) the design of a state of charge controller that uses day-ahead forecast of solar power and building loads to intialize energy storage at the start of each day. The local controller is tested in simulation using an exemplary system with PV generation, energy storage and dispatchable building loads. Two sample days with different PV forecasts and multiple case scenarios are considered, and the performance of the algorithm in managing the real and reactive net building load trajectories and the ramp rate of PV injections into the utility network are evaluated. The simulations are based on actual forecasted and measured PV data, and the results show that the local controller meets the tracking requirements for real and reactive power within the operating constraints of the building.

14 SOLAR ENERGY↗
NASA NTRS1968

Low-cost, fast-response drive circuit for electromagnetic torque motors

Fast-response coil drive circuit, for electromagnetic torque motors, reduces the inductive coil time constant with a minimum of circuit sophistication. The low-cost modulator servoamplifier is used with a compatible preamplifier stage which provides the servo-loop function of summing, adjustable gain and compensation.

Zeller, J. R.↗
NASA NTRS1971

Improved wax mold technique forms complex passages in solid structures

Low-cost fabricating technique produces minute, complex air passages in fluidic devices. Air jet interactions in these function as electronic and electromechanical control systems. Wax cores are fabricated without distortion by two-wax process using nonsoluble pattern-wax and water-soluble wax. Significant steps in fabrication process are discussed.

Hellbaum, R. F.↗
NASA NTRS1975

Spinning solid perigee stage

If the Space Transportation System is to serve in the 1980's for launching geostationary satellites that presently use the Delta and Centaur boosters, the cost of STS launches must be competitive. This can be accomplished through the provision of a multiple-launch capability in the orbiter, combined with the design of a low cost, spinning solid perigee kick motor (PKM). The PKM will be attached to the spacecraft and function essentially as the Delta third stage does today.

Rose, H. A.↗
NASA NTRS1975

A cost effective data management subsystem for the LST

The paper outlines the approach used in developing DMS (Data Management Subsystem) alternatives for the LST (Large Space Telescope) and in selecting the concept considered to be the most cost effective means of implementing the LST DMS requirements. Two candidate DMS concepts are discussed: a functionally integrated and a functionally separated one. For the single vehicle LST program, separation of the DMS functions best provides high reliability, operations flexibility, minimal interface complexity, and the least complex software development and verification task. The use of available hardware and NASA standard components is stressed.

Dougherty, J. A.↗
NASA NTRS1980

Technology alternatives for the SPS

Emerging technologies may offer advantages over those selected for the reference design adopted for the SPS. While it is not possible to list all the technological innovations that may affect the SPS, it is feasible to develop a systematic methodology for assessing technical alternatives. This may be of value in evaluating proposed technologies and identifying high priority areas for research. Such a methodology includes involves (1) variation of guidelines; (2) analysis of system functions; (3) analysis of system sensitivity; (4) analysis of technology status and risk; and (5) external costs, problem areas, and criticisms of the SPS concept. The methodology is a first step towards the creation of a formal decision analytic framework which can support design choices and program decisions as development proceeds.

Glaser, P.↗