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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Guanosine Dianions Hydrated by One to Four Water Molecules

Intermolecular interactions as those present in molecule…water complexes may profoundly influence the physico-chemical properties of molecules. Here, we carried out an experimentally-computational study on the doubly-deprotonated guanosine monophosphate…water clusters, [dGMP-2H] 2- •nH 2 O (n=1–4), using a combination of negative anion photoelectron spectroscopy (NIPES) with molecular dynamics (MD) and quantum chemical (QM) calculations. Successive addition of water molecules to [dGMP-2H] 2- increases the experimental adiabatic detachment (ADE) and vertical detachment energy (VDE) by 0.5 to 0.1 eV, depending on the cluster size. In order to choose the representative conformations, we combined MD simulations with a clustering procedure to identify low energy geometries for which ADEs and VDEs were computed at the CAM-B3LYP/6-31++G(d,p) level. Our results demonstrate that the assumed approach lead to the sound geometries and energetics of the studied micro-solvates since the calculated ADEs and VDEs are in pretty good agreement with the experimental characteristics. The evolution of hydrogen bonding with cluster size indicates possibility of the occurrence of proton transfer for clusters comprising a larger number of water molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

High-fidelity wind farm simulation methodology with experimental validation

The complexity and associated uncertainties involved with atmospheric-turbine-wake interactions produce challenges for accurate wind farm predictions of generator power and other important quantities of interest (QoIs), even with state-of-the-art high-fidelity atmospheric and turbine models. A comprehensive computational study was undertaken with consideration of simulation methodology, parameter selection, and mesh refinement on atmospheric, turbine, and wake QoIs to identify capability gaps in the validation process. For neutral atmospheric boundary layer conditions, the massively parallel large eddy simulation (LES) code Nalu-Wind was used to produce high-fidelity computations for experimental validation using high-quality meteorological, turbine, and wake measurement data collected at the Department of Energy/Sandia National Laboratories Scaled Wind Farm Technology (SWiFT) facility located at Texas Tech University’s National Wind Institute. The wake analysis showed the simulated lidar model implemented in Nalu-Wind was successful at capturing wake profile trends observed in the experimental lidar data.

17 WIND ENERGY↗
DOE OSTI2021

High frequency impedance characteristics of a tunable microplasma device

Computational studies on high frequency impedance characteristics of a microplasma device are reported. While microplasma is ignited using a primary excitation signal, frequency response of plasma impedance is determined by a secondary high frequency probe signal with significantly lower voltage amplitude such that it does not influence the plasma parameters. Here, the computational model utilizing the drift–diffusion approximation is first validated by comparing with experimental data for microplasmas ignited at pressures ranging from 1 to 5 Torr. In spite of quantitative discrepancies, good overall agreement is obtained between the measured frequency response of impedance of the discharge. Comparisons are also presented for various plasma parameters including mean electron number density, sheath thickness, mean electron temperature, and collision frequency that were inferred from the impedance measurements. The computational model is then used to perform simulations of near-atmospheric pressure microplasmas with the probe signal frequency ranging from 3 to 20 GHz. The simulations demonstrate the presence of a resonance frequency at which the impedance vanishes. More importantly, it is shown that this resonant frequency can be tuned effectively by suitably modifying the operating parameters (gap size, pressure, and excitation voltage). The simulated impedance characteristics are used to determine the effective plasma inductance and capacitance using a non-linear fitting approach, thereby showing the dependence of these electrical parameters on the plasma operating conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Evidence of a magnetic transition in atomically thin Cr 2 TiC 2 T x MXene

Two-dimensional (2D) transition metal carbides and nitrides known as MXenes have shown attractive functionalities such as high electronic conductivity, a wide range of optical properties, versatile transition metal and surface chemistry, and solution processability. Although extensively studied computationally, the magnetic properties of this large family of 2D materials await experimental exploration. 2D magnetic materials have recently attracted significant interest as model systems to understand low-dimensional magnetism and for potential spintronic applications. Here, we report on synthesis of Cr 2 TiC 2 T x MXene and a detailed study of its magnetic as well as electronic properties. Using a combination of magnetometry, synchrotron X-ray linear dichroism, and field- and angular-dependent magnetoresistance measurements, we find clear evidence of a magnetic transition in Cr 2 TiC 2 T x at approximately 30 K, which is not present in its bulk layered carbide counterpart (Cr 2 TiAlC 2 MAX phase). Overall, this work presents the first experimental evidence of a magnetic transition in a MXene material and provides an exciting opportunity to explore magnetism in this large family of 2D materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Use of current-potential patches to obtain fundamental improvements to the coils of magnetic fusion devices

A central issue in the design of tokamaks or stellarators is the coils that produce the external magnetic fields. The freedom that remains unstudied in the design of coils is enormous. This freedom could be quickly studied computationally at low cost with high reliability. In particular, the space between toroidal field and modular coils that blocks access to the plasma chamber could be increased by a large factor. The concept of current-potential patches, which was developed in Todd Elder's thesis, provides a method for separating the study of the feasibility of coils with attractive physics properties from the engineering design of specific coils. In addition to enhanced accessibility, coils can be designed for increased plasma-coil separation, insensitivity to coil position errors, and plasma control.

Boozer, Allen H. [Columbia Univ., New York, NY (Un↗
DOE OSTI2020

Data on the comprehensive first-principles diffusion study of the aluminum-magnesium system

First-principles calculation of diffusion coefficients between Mg and Al is investigated comprehensively using density functional theory (DFT). The effect of different uncertainty sources arising from first principles calculations has been investigated systematically. These sources include the diffusion model, energetic, entropic and attempt frequency calculations. Variation in self and impurity diffusion coefficients of Mg and Al in stable phases are quantified using different DFT settings and compared with the experiments. Using the optimal DFT settings, diffusion coefficients in metastable phases of Al and Mg are predicted. The dataset refers to “An integrated experimental and computational study of diffusion and atomic mobility of the aluminum-magnesium system” [1].

36 MATERIALS SCIENCE↗
DOE OSTI2020

Distributionally robust facility location problem under decision-dependent stochastic demand

While the traditional facility location problem considers exogenous demand, in some applications, locations of facilities could affect the willingness of customers to use certain types of services, e.g., carsharing, and therefore they also affect realizations of random demand. Moreover, a decision maker may not know the exact distribution of such endogenous demand and how it is affected by location choices. In this paper, we consider a distributionally robust facility location problem, in which we interpret the moments of stochastic demand as functions of facility-location decisions. We reformulate a two-stage decision-dependent distributionally robust optimization model as a monolithic formulation, and then derive exact mixed-integer linear programming reformulation as well as valid inequalities when the means and variances of demand are piecewise linear functions of location solutions. We conduct extensive computational studies, in which we compare our model with a decision-dependent deterministic model, as well as stochastic programming and distributionally robust models without the decision-dependent assumption. Here, the results show superior performance of our approach with remarkable improvement in profit and quality of service under various settings, in addition to computational speed-ups given by formulation enhancements. These results draw attention to the need of considering the impact of location decisions on customer demand within this strategic-level planning problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Basin-Size Mapping: Prediction of Metastable Polymorph Synthesizability Across TaC–TaN Alloys

The sizes of the basins of attraction on the potential energy surface are helpful indicators in determining the experimental synthesizability of metastable phases. In principle, these basins can be controlled with changes in thermodynamic conditions such as composition, pressure, and surface energy. Herein, we use random structure sampling to computationally study how alloying smoothly perturbs basin of attraction sizes. The TaC 1-x N x pseudobinary is an ideal test system given the structural and polymorphic contrast of its parent compounds and their technological relevance as epitaxial substrates for Al 1-x Ga x N. While we find limited thermodynamic stability across all computationally observed phases, random structure sampling shows a significant composition region where the rocksalt basin dominates. As such, we predict the potential for the nonequilibrium synthesis of metastable rocksalt TaC 1-x N x alloys as substrates for Al 1-x Ga x N. At higher nitrogen concentrations, other low-energy metastable polymorphs emerge that continue to retain the hexagonal close packing suitable for III-N growth. Confidence in these trends was established through uncertainty quantification of the basin sizes and energy distributions; such analysis utilized the Beta and Dirichlet distributions. In conclusion, we also find (a) polymorph basin sizes can be rationalized in terms of energetic preferences for different coordination environments; and (b) basin sizes universally shrink with increasing nitrogen content, making the system more prone to amorphous growth.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Computational design of passivants for CdTe grain boundaries

CdTe is the second most-widely deployed photovoltaic (PV) material due to its high efficiency and low manufacturing costs. Currently, polycrystalline CdTe (poly-CdTe) has a record efficiency of similar to 22%, which is still well below the theoretical limit (similar to 30%). Polycrystalline CdTe films that have incorporated Cl or Se show higher efficiency, possibly due to the segregation of these ions to the grain boundaries (GBs), where they may passivate the dangling bonds. However, the efficiency enhancement mechanisms of passivants in CdTe GBs, and the feasibility of employing alternative passivants, have not been well explored. Here, we present a systematic computational study of CdTe GBs with potential passivants, namely S, P, As, Se, and Sb on Te sites, and Na, Mg, Al, Sc, Cu, and Zn on Cd sites. Density functional theory (DFT) calculations were performed on GB dislocation core structures derived from scanning transmission electron microscopy (STEM) images of a model GB (bicrystal). We computed the segregation thermodynamics, electronic density of states, and charge variations near doped CdTe GBs. We find that segregation of impurities to GBs is thermodynamically favorable. For a Te-terminated core, Se, S, and P on Te sites effectively reduce midgap states. For both Cd-and Te-terminated dislocation cores, Sc and Al reduce midgap states when substituted for Cd atoms. Overall, the greatest improvement was achieved with co-doping, i.e. simultaneously substituting Te with Se and substituting Cd with Cu or Al. The elimination of midgap states is predicted to increase the photovoltaic efficiency of CdTe by reducing the recombination at grain boundaries.

14 SOLAR ENERGY↗
DOE OSTI2023

Surface Chemistry and Reactions for Bimetallic Au Catalysis (Final Report)

Gold-based catalysts offer tremendous opportunities for developing new technologies for selective oxidation reactions that directly use gas-phase oxygen as a benign reagent and produce either no byproducts or water as the only byproduct. These processes are urgently needed and critical for achieving the sustainable production of chemicals. While recent studies demonstrate that the catalytic properties of gold can be significantly enhanced by addition of other metals, the development of these catalysts with sufficient performance for commercialization is hindered by a lack of fundamental understanding of how the catalytic properties of gold can be controlled and tailored. This project addressed this need by synergistically combining experimental and computational studies to establish fundamental composition-structure-activity relationships for gold-based catalysts for several industrially important reactions. Results from surface spectroscopy, atomic imaging and thermal desorption experiments were combined with molecular models and reaction mechanisms from quantum chemical calculations to link observable reaction rates to the structure and composition of surfaces at the molecular level. The results were used to develop improved catalyst formulations and identify optimized reaction conditions for gold-based catalysts. For broader impacts, the developed methodology was extended to other metallic catalysts, such as silver, platinum-molybdenum and nickel-tin, for improved catalytic efficiency and sustainable production of specialty and commodity chemicals.

36 MATERIALS SCIENCE↗
DOE OSTI2023

SyReNN: A tool for analyzing deep neural networks

Deep Neural Networks (DNNs) are rapidly gaining popularity in a variety of important domains. Unfortunately, modern DNNs have been shown to be vulnerable to a variety of attacks and buggy behavior. This has motivated recent work in formally analyzing the properties of such DNNs. Furthermore, this paper introduces SyReNN, a tool for understanding and analyzing a DNN by computing its symbolic representation. The key insight is to decompose the DNN into linear functions. Our tool is designed for analyses using low-dimensional subsets of the input space, a unique design point in the space of DNN analysis tools. We describe the tool and the underlying theory, then evaluate its use and performance on three case studies: computing Integrated Gradients, visualizing a DNN’s decision boundaries, and repairing buggy DNNs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Actinide N-Donor Thermodynamics: Expanding the f-element Covalency Dialogue. Final report

Resolving the chemistry and physics of f-electrons is one of the grand challenges of science for energy technology. A central component of this challenge is describing covalency in actinide-ligand interactions. Crystallography, x-ray spectroscopy and computational techniques have provided reasonable, and in some cases remarkable, support for covalency in actinide-ligand interactions. Courtesy the quality of the results obtained, a significant portion of the covalency dialogue has been forwarded through solid-state and computational studies of the more stable actinides (Th, U, Pu, Np). However; recent reports have questioned whether covalency in actinide interactions increases or decreases across the series. Examination of less-stable trans-actinides (Am, Cm, Bk, Cf and Es) by the aforementioned approaches can be rapidly limited due to material availability, radiological hazards and experimental data to validate computational models. Furthermore, limited thermodynamic data exists to confirm covalency in actinide solution phase interactions that are highly relevant to the remediation and reprocessing of used nuclear fuel. The best-defined interactions of actinides with soft donors in aqueous solutions involve (poly)aminopolycarboxylate (APC) ligands. The chelate effect and binding affinity with the acetic acid APCs subgroups encourages amine interactions with the actinide metal center. In the absence of these factors, amine interactions with actinides are too weak to overcome the protective hydration shell of the dissolved ion. The ability for APCs to force actinide interactions with soft nitrogen donors (as defined by Pearson’s Hard Soft Acid Base theory) encourages the application of these ligands in a variety of processes for actinide recovery from nearly chemically identical lanthanides. The ability to functionalize the amine center of the ligand in a variety of capacities (adding additional amine groups, exchanging the conventional acetate group for an acetate group, etcetera), allows for the APC ligand to serve as a thermodynamic probe for actinide-nitrogen interactions. Perhaps the single most significant breakthrough during the previous funding cycle was the observation that covalency for the transplutonium part of the actinide series can be increasingly influenced with energy degeneracy driven covalency as the actinides become heavier. This was observed most predominantly with dipicolinic acid, but extensions of f-orbital degeneracy were found to affect aliphatic aminopolycarboxylate-actinide complexes through einsteinium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Reference solutions for linear radiation transport: the Hohlraum and Lattice Benchmarks

Radiation transport describes the propagation of energetic particles through space as they interact with a surrounding material medium. In a kinetic description, radiation transport is modeled by a radiation transport equation (RTE) that prescribes the density of the radiation in position-momentum phase space. The purpose of this dataset is to provide highly resolved solutions to two benchmark problems. These two benchmarks do not possess exact solutions; moreover, the construction of a manufactured solution may require a non-physical source that is not desirable, especially if it spoils the physical nature of the solution. Thus the goal of this computational study is to provide a highly resolved reference solution for testing newer, more cost efficient methods that are currently being developed in the research community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Managing autonomous materials labs with multi-agent AI and its implications for the science of science

Self-driving lab systems (aka, autonomous experimentation) accelerate research - letting scientists learn faster, spend less resources, and fail smarter in well defined, narrow studies. The next-generation materials lab combines self-driving systems to tackle broader challenges - orchestrating complex research campaigns while optimizing lab resources. We propose that agent-based and agentic artificial intelligence will be an integral part of next-generation lab management and discuss potential implementation scenarios. Additionally, digital and physical sandboxes will allow scientists to evaluate diverse and dynamic research and lab management strategies. Beyond the immediate benefit to lab optimization, such sandboxes will enable realistic computational studies of the philosophy of science (i.e., science of science) to achieve higher level scientific efficiencies.

Computer science↗
DOE OSTI2023

Effects of magnetic field annealing on the hard magnetic properties of milled Nd-Fe-B powders

In this study, we report the effect of magnetic field annealing (MA) in relieving the stress induced during the milling of Nd-Fe-B sintered magnets. The effect of MA processing parameters and particle size on the magnetic properties were investigated. Based on the results, magnetic field annealing is more effective in improving the magnetic properties of larger size particles, compared to finer particles. Our computational study on the role of particle surface defects in bi-modal particle distribution agrees with results obtained experimentally. In conclusion, magnetic field annealed powder has been successfully used to develop 4.6 g.cm -3 density bonded magnets with 75 vol% of magnetic powder and polyamide 12 (nylon 12) polymer binder resulting in 11.3 MGOe energy product.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗
DOE OSTI2022

High Temperature Polymer Electrolyte Membrane Fuel Cells with High Phosphoric Acid Retention

Phosphoric acid loss poses immense hurdles for the durability of high-temperature polymer electrolyte membrane fuel cells (HT-PEMFCs). Here we report quaternary ammonium-biphosphate ion-pair HT-PEMFCs that do not lose phosphoric acids under normal and accelerated stress conditions. Additionally, our energetics study explains the acid loss behavior of the conventional phosphoric acid-polybenzimidazole (PA-PBI) system by two mechanisms. If PA loss occurs via acid evaporation, the acid loss is constant over time. On the other hand, when water activity in the PA-PBI system is high, exponential decay of PA loss occurs via the water replacement mechanism. Combined 31 P NMR and computational studies show that the proposed ion-pair system has six times higher interaction energy, which allows for containing all PAs in the membrane electrode assemblies under a broad range of operating conditions. In addition, polar interactions between the phosphonic acid ionomer and phosphoric acid explain acid retention in the electrodes of the ion-pair HT-PEMFCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Discovery of tunable and soluble organic emitters for solid-state lasers with a self-driving laboratory

We have recently demonstrated the ability of using self-driving laboratories for AI-driven searches of organic emitters for solid-state lasing devices. Our past workflow featured solubility challenges for such large molecular moieties. In this next-generation study, we return to the drawing board to explore a family of com-pounds that are much solution processable and composed of a set of electronic cores that provide a broader color response. Out of 252 potential candidates,and with guidance from DFT calculations, we selectively perform a compre-hensive study exploring 51 fluorene-based A-B-A type organic laser oligomers, armed with our self-driving lab. The candidates range from simple hydrocarbon molecules to complex hetero atom-mixed molecules. As a result of this study, we highlight diketopyrrolopyrrole and benzodiazole derivatives for their largely red-shifted emissions. Furthermore, we investigate the effect of color change aris-ing from hetero atom permutation, fluorine addition, thiophene coupling, and a combination of fluorine addition and thiophene coupling. Amplified spontaneous emission (ASE) measurements in the solid state further corroborate the lasing potential of selected candidates, reinforcing their suitability for future device applications. The computational study with density functional theory confirms the experimental results.

fluorescence↗