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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Alloying Effects on the Transport Properties of Refractory High-entropy Alloys

Additive Manufacturing (AM) has opened new frontiers for the design of refractory high-entropy alloys (HEAs) for high-temperature applications. The thermal conductivity of the AM feedstock is among the most important thermo-physical properties that control the melting and solidification process. Despite its significance, there remains a notable gap in both computational and experimental research concerning the thermal conductivity of HEAs. Here, we use density functional theory (DFT) to systematically investigate the alloying effects on the transport properties of Ti-Cr-Mo-W-V-Nb-Ta RHEAs, including electrical and thermal conductivities and Seebeck coefficient. The relaxation time of charge carriers is a key underlying parameter determining thermal conductivity that is exceedingly challenging to predict from first principles alone, and we thus follow the approach by Mukherjee, Satsangi, and Singh [Chem Mater 32, 6507 (2022)] to optimize the relaxation time for RHEAs. Here we validated thermal conductivity predictions on elemental solids, binary and ternary alloys, and RHEAs and compared them against thermodynamic (CALPHAD) predictions and our experiments with good correlations. To understand observed trends in thermal conductivity, we assessed the phase stability, electronic structure, phonon, and intrinsic- and tensile strength of down-selected RHEAs. Our electronic structure and phonon results connect well with the observed compositional trends for thermal transport in RHEAs. Our DFT assessment and CALPHAD predictions provide a unique design guide for RHEAs with tailored thermal conductivity, a critical consideration for AM and thermal-management applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

G4Boost: a machine learning-based tool for quadruplex identification and stability prediction

Background: G-quadruplexes (G4s), formed within guanine-rich nucleic acids, are secondary structures involved in important biological processes. Although every G4 motif has the potential to form a stable G4 structure, not every G4 motif would, and accurate energy-based methods are needed to assess their structural stability. Here, we present a decision tree-based prediction tool, G4Boost, to identify G4 motifs and predict their secondary structure folding probability and thermodynamic stability based on their sequences, nucleotide compositions, and estimated structural topologies. Results: G4Boost predicted the quadruplex folding state with an accuracy greater then 93% and an F1-score of 0.96, and the folding energy with an RMSE of 4.28 and R 2 of 0.95 only by the means of sequence intrinsic feature. G4Boost was successfully applied and validated to predict the stability of experimentally-determined G4 structures, including for plants and humans. Conclusion: G4Boost outperformed the three machine-learning based prediction tools, DeepG4, Quadron, and G4RNA Screener, in terms of both accuracy and F1-score, and can be highly useful for G4 prediction to understand gene regulation across species including plants and humans.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Characterizing the Stability of NISQ Devices

In this study, we focus on the question of stability of NISQ devices. The parameters that define the device stability profile are motivated by the work of DiVincenzo in [9] where the requirements for physical implementation of quantum computing are discussed. We develop the metrics and theoretical framework to quantify the DiVincenzo requirements and study the stability of those key metrics. The basis of our assessment is histogram similarity (in time and space). For identical experiments, devices which produce reproducible histograms in time, and similar histograms in space, are considered more reliable. To investigate such reliability concerns robustly, we propose a moment-based distance (MBD) metric. We illustrate our methodology using data collected from IBM's Yorktown device. Two types of assessments are discussed: spatial stability and temporal stability.

Dasgupta, Samudra↗
DOE OSTI2023

Experimental Investigation of Thermodynamic Stabilization in Boron Imidazolate Frameworks (BIFs) Synthesized by Mechanochemistry

This study experimentally explores the energetics for the formation of boron–imidazolate frameworks (BIFs), which are synthesized by mechanochemistry. The topologically similar frameworks employ the same tetratopic linker based on tetrakis(imidazolyl)boric acid but differ in the monovalent cation metal nodes. This permits assessment of the stabilizing effect of metal nodes in frameworks with sodalite (SOD) and diamondoid (dia) topologies. The enthalpy of formation from endmembers (metal oxide and linker), which define thermodynamic stability of the structures, has been determined by use of acid solution calorimetry. The results show that heavier metal atoms in the node promote greater energetic stabilization of denser structures. Overall, in BIFs the relation between cation descriptors (ionic radius and electronegativity) and thermodynamic stability depends on framework topology. Thermodynamic stability increases with the metallic character of the cation employed as the metal node, independent of the framework topology. In conclusion, the results suggest unifying aspects for thermodynamic stabilization across MOF systems.

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

Analysis of neoclassical tearing mode stabilization experiment by electron cyclotron injection in KSTAR

We report the neoclassical tearing mode (NTM) stabilization experimental results by injection of the electron cyclotron (EC) beam in KSTAR, and its analysis with integrated modelling. In the KSTAR experiment, NTM was intentionally induced and the EC beam was injected by the plasma control system (PCS) to stabilize it. Here, the EC angle was controlled based on the minimum seeking algorithm for the island growth rate. Although the EC angle was not changed significantly, the island width significantly decreased towards the end of the experiment followed by the recovery of plasma performance. To assess the NTM stabilization experiment from a stability perspective, we performed integrated modelling with TRIASSIC utilizing the reconstructed equilibrium with magnetic diagnostics and motional stark effect diagnostics. As a result, we observed that the NTM is stabilized by EC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Fabrication of Freestanding Metallic Ni-Mo-W Microcantilever Beams With High Dimensional Stability

Recent studies have elucidated a promising balance of physical and mechanical properties of sputter deposited nickel-molybdenum-tungsten (Ni-Mo-W) films that have a unique nanotwinned microstructure and promising potential for use in high temperature microelectromechanical systems (MEMS). Here, the current study was undertaken to establish the feasibility of making nanotwinned Ni-Mo-W microcantilevers with standard micro- fabrication processing, to assess their dimensional stability, and to demonstrate the possibility of using nanotwinned Ni-Mo-W in metal MEMS devices. Deposition of Ni-Mo-W films in commercial sputtering chambers revealed a wide processing window for the formation of the requisite nanotwinned microstructure. Conventional photolithography and etchants were employed to shape blanket Ni-Mo-W films into freestanding microcantilever beams. Monitoring microcantilever deflections via interferometry provided a direct measure of residual stresses and overall dimensional stability. Heat treatments of 200° C and 400° C were used to mimic wafer bonding temperatures. At 400°C, microcantilevers exhibited modest stress relaxation, yielding beam deflection profiles on the nanometer scale and portending dimensional stability and control for future metal MEMS devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Comparison of the Effects of Bipolar Membrane Preparation Conditions on the Mechanical Durability and Electrochemical Performance for Electrodialysis Applications

Bipolar membranes (BPMs) are enabling materials for electrochemical conversion technologies such as water electrolysis, fuel cells, CO 2 electrolysis, and electrodialysis (ED) for direct air/ocean capture of CO 2 . However, current BPM durability can suffer from chemical, mechanical, and performance degradation when operated at high current density (ion flux) and physical scale. Therefore, this limits its adoption in a wider applications space. BPMs have several known degradation mechanisms, including chemical breakdown of ion-exchange polymers, loss of junction adhesion, or physical breakdown due to shearing force and pressure swings in an electrodialysis cell. To assess the electrochemical stability and mechanical durability of BPMs under operational conditions, we investigated how fabrication conditions (including preconditioning, hot-pressing temperature and pressure, and catalyst loading) impact the adhesion of custom-made BPMs. T-peel studies were performed ex situ to quantify adhesive forces of BPMs, and bipolar membrane electrodialysis (BPMED) experiments were performed to assess the electrochemical performance of the corresponding BPMs. The results of this systematic comparison indicate that hydration and heated pressing create improved adhesion during the fabrication of BPMs, and BPMED testing shows that these fabrication techniques are not detrimental to the electrochemical performance of the BPMs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Review of the Literature on the Radiolytic Stability of the Next-Generation Solvent

The Original Caustic-Side Solvent Extraction (CSSX) solvent (based on the BOBCalixC6 extractant) currently in use at the Salt Waste Processing Facility (SWPF) is set to be replaced by the Next-Generation Solvent (NGS, based on the MaxCalix extractant). Current SWPF flammability safety controls use G-values for volatile gases obtained from radiolysis studies with the Original CSSX solvent. A review of past irradiation tests of both solvent systems was performed to assess the radiolytic stability of NGS with respect to flammable gas generation from radiolysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

In silico discovery of active, stable, CO-tolerant and cost-effective electrocatalysts for hydrogen evolution and oxidation

Various databases of density functional theory (DFT) calculations for materials and adsorption properties are currently available. Using the Materials Project and GASpy databases of material stability and binding energies (H* and CO*), respectively, we evaluate multiple aspects of catalysts to discover active, stable, CO-tolerant, and cost-effective hydrogen evolution and oxidation catalysts. Finally, we suggest a few candidate materials for future experimental validations. We highlight that the stability analysis is easily obtainable but provides invaluable information to assess thermodynamic and electrochemical stability, bridging the gap between simulations and experiments. Furthermore, it reduces the number of expensive DFT calculations required to predict catalytic activities of surfaces by filtering out unstable materials.

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

A framework for quantifying uncertainty in DFT energy corrections

In this work, we demonstrate a method to quantify uncertainty in corrections to density functional theory (DFT) energies based on empirical results. Such corrections are commonly used to improve the accuracy of computational enthalpies of formation, phase stability predictions, and other energy-derived properties, for example. We incorporate this method into a new DFT energy correction scheme comprising a mixture of oxidation-state and composition-dependent corrections and show that many chemical systems contain unstable polymorphs that may actually be predicted stable when uncertainty is taken into account. We then illustrate how these uncertainties can be used to estimate the probability that a compound is stable on a compositional phase diagram, thus enabling better-informed assessments of compound stability.

42 ENGINEERING↗
DOE OSTI2020

Ab Initio Study of Stability, Local Order, and Phase Diagram For a Series of bcc-based Transition Metal Alloys

In this work, a parameter-free electronic structure approach is applied to the study of stability and chemical order in the 15 substitutional body-centered cubic (bcc)-based alloys made of the six transition metals of groups 5 (V, Nb, Ta) and 6 (Cr, Mo, W) of the periodic table. The method is based on a Green’s function description of the electronic structure of the random alloys. Configurational order is treated within the generalized perturbation method, and temperature effects are examined with a generalized mean-field approach. In contrast to the results summarized in the assessed phase diagrams, stability and ordering trends are predicted in a broad range of alloy composition for at least seven alloys, and explanation is found in their electronic structure properties. Short-range order results, thermodynamics analysis, and bcc-based phase diagrams are also presented.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High–Resolution Maps of Near–Surface Permafrost for Three Watersheds on the Seward Peninsula, Alaska Derived From Machine Learning

Permafrost soils are a critical component of the global carbon cycle and are locally important because they regulate the hydrologic flux from uplands to rivers. Furthermore, degradation of permafrost soils causes land surface subsidence, damaging infrastructure that is crucial for local communities. Regional and hemispherical maps of permafrost are too coarse to resolve distributions at a scale relevant to assessments of infrastructure stability or to illuminate geomorphic impacts of permafrost thaw. Here we train machine learning models to generate meter–scale maps of near–surface permafrost for three watersheds in the discontinuous permafrost region. The models were trained using ground truth determinations of near–surface permafrost presence from measurements of soil temperature and electrical resistivity. We trained three classifiers: extremely randomized trees (ERTr), support vector machines (SVM), and an artificial neural network (ANN). Model uncertainty was determined using k–fold cross validation, and the modeled extents of near–surface permafrost were compared to the observed extents at each site. At–a–site near–surface permafrost distributions predicted by the ERTr produced the highest accuracy (70%–90%). However, the transferability of the ERTr to the sites outside of the training data set was poor, with accuracies ranging from 50% to 77%. The SVM and ANN models had lower accuracies for at–a–site prediction (70%–83%), yet they had greater accuracy when transferred to the non–training site (62%–78%). These models demonstrate the potential for integrating high–resolution spatial data and machine learning models to develop maps of near–surface permafrost extent at resolutions fine enough to assess infrastructure vulnerability and landscape morphology influenced by permafrost thaw.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Toward a standardization of cryostructure and cryogenic soil structure terminology for the field description of permafrost‐affected soils

This paper establishes standardized terminology and field documentation protocols for cryostructures and cryogenic soil structures in permafrost‐affected soils and provides brief guidance on descriptions of ground ice morphology and ice volume estimates. We consolidate permafrost terminology from Russian and North American literature, clarify long‐standing ambiguities, and provide explicit guidelines that align with US Department of Agriculture‐Natural Resources Conservation Service soil description standards. Our scheme makes critical distinctions between cryostructure, the distribution of ice within soil, and cryogenic soil structure, the morphological structure of soil resulting from ice formation. The scheme organizes cryostructures into three main categories: non‐segregated ice, visible segregated ice, and ice matrices. We introduce standardized codes and parameters for field descriptions of ice and soil that enable machine‐readable data collection compatible with existing soil information systems. This standardization will significantly enhance the integration of field observations into landscape‐scale assessments of permafrost stability, infrastructure vulnerability, and ecosystem response to permafrost thaw, addressing an urgent need for quantitative data to inform modeling and decision‐making in rapidly changing Arctic and subarctic environments.

Andersen, Megan L. [University of Minnesota, Saint↗
DOE OSTI2021

Monitoring leaf phenology in moist tropical forests by applying a superpixel-based deep learning method to time-series images of tree canopies

Tropical leaf phenology-particularly its variability at the tree-crown scale-dominates the seasonality of carbon and water fluxes. However, given enormous species diversity, accurate means of monitoring leaf phenology in tropical forests is still lacking. Time series of the Green Chromatic Coordinate (GCC) metric derived from tower-based red-green-blue (RGB) phenocams have been widely used to monitor leaf phenology in temperate forests, but its application in the tropics remains problematic. To improve monitoring of tropical phenology, we explored the use of a deep learning model (i.e. superpixel-based Residual Networks 50, SP-ResNet50) to automatically differentiate leaves from non-leaves in phenocam images and to derive leaf fraction at the tree-crown scale. To evaluate our model, we used a year of data from six phenocams in two contrasting forests in Panama. Here, we first built a comprehensive library of leaf and non-leaf pixels across various acquisition times, exposure conditions and specific phenocams. We then divided this library into training and testing components. We evaluated the model at three levels: 1) superpixel level with a testing set, 2) crown level by comparing the model-derived leaf fractions with those derived using image-specific supervised classification, and 3) temporally using all daily images to assess the diurnal stability of the model-derived leaf fraction. Finally, we compared the model-derived leaf fraction phenology with leaf phenology derived from GCC. Our results show that: 1) the SP-ResNet50 model accurately differentiates leaves from non-leaves (overall accuracy of 93%) and is robust across all three levels of evaluations; 2) the model accurately quantifies leaf fraction phenology across tree-crowns and forest ecosystems; and 3) the combined use of leaf fraction and GCC helps infer the timing of leaf emergence, maturation and senescence, critical information for modeling photosynthetic seasonality of tropical forests. Collectively, this study offers an improved means for automated tropical phenology monitoring using phenocams.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Durability of ionomer encapsulants in photovoltaic modules

Ethylene vinyl acetate (EVA) has for decades been the preferred material for photovoltaic (PV) module encapsulation. However, while it is relatively inexpensive and initially adheres well to module components, EVA discolors with age and - as interfacial adhesion degrades - becomes susceptible to delamination, ultimately resulting in reduced module efficiency and shortened service lifetimes. As potential replacements for EVA, ionomer thermoplastic materials cure faster, are more resistant to discoloration and potential induced degradation, and do not evolve corrosive acetic acid, making them compatible with new device materials such as perovskites. Since there is limited information on ionomer durability for PV module applications, a series of field and accelerated laboratory aging studies were conducted to assess ionomer interface stability in the presence of terrestrial environmental stressors. It is shown that adhesion to the glass and cell interfaces of PV modules is inferior to EVA, both before and after aging, rendering ionomers particularly susceptible to delamination after short timeframes. Potential solutions to improve ionomer adhesion are discussed.

14 SOLAR ENERGY↗
DOE OSTI2023

Metallic Cation-Mediated Entrapment of Nucleic Acids on Mesoporous Silica Surface: Application in Castration-Resistant Prostate Cancer

The use of exogenous nucleic acid technologies to modulate aberrant protein expression resulting from genetic mutations is a promising therapeutic approach for the treatment of diseases such as advanced prostate cancer (PC). The promise of nucleic-based therapeutics is dependent on the development of platforms that effectively protect nucleic acids from nuclease degradation and deliver the nucleic acids to the cytosol of target cells. In this work, we present the development of a divalent metal-mediated nucleic acid entrapment strategy with a porous silica matrix. This simple strategy results in efficient loading percentages of both siRNA (>60%) and mRNA (>80%) as well as their release within relevant biological environments (80%). Additionally, our data supports that the current method reduces endosomal entrapment and supports the lipid coating of mesoporous silica nanoparticles (LC-MSNs). Finally, the metal-enhanced nanosystem is assessed for biocompatibility, stability, and circulation within in vitro, ex ovo, and in vivo models of PC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Venturing into Unexplored Phase Space: Synthesis, Structure, and Properties of MgCo 3 B 2 Featuring a Rumpled Kagomé Network

MgCo 3 B 2 , a novel ternary boride in a previously unexplored phase space, was synthesized using the hydride route. In situ powder X-ray diffraction and DFT calculations aided in the discovery of this compound, whose structure was then determined by single-crystal X-ray diffraction. Like the closely related CeCo 3 B 2 , MgCo 3 B 2 crystallizes in centrosymmetric space group P6/mmm (a = 4.883(2) Å, c = 2.926(2) Å at 210 K, Z = 1). Unlike CeCo 3 B 2 , however, it adopts a disordered structure that features a rumpled Kagomé network of Co atoms, and Mg atoms fill the channels of a Co–B framework. Although the structural disorder leads to motifs that are similar to those observed in MgNi 3 B 2 and other related ternary borides, no evidence of an ordered superstructure was found by single-crystal X-ray diffraction or high-resolution powder X-ray diffraction. In the case of CeCo 3 B 2 , boron atoms occupy the center of regular Co 6 trigonal prisms; in MgCo 3 B 2 , boron atoms are shifted from the center of the prism to form B–B dimers with roughly the same length as those found in MgNi 3 B 2 . Magnetic susceptibility data exhibit an unusual temperature dependence that cannot be convincingly modeled by the modified Curie–Weiss equation, consistent with DFT calculations predicting a nonmagnetic ground state. Intrinsic susceptibility at 300 K is 1.42 × 10 –3 emu/mol Oe, which is comparable to that of paramagnetic YCo 3 B 2 and CeCo 3 B 2 with a similar structure and composition. Here, this study showcases the efficacy of combining several methodologies to discover new solids in unexplored phase spaces. This approach includes in situ PXRD data to monitor reactions of precursors upon heating, a diffusion-enhanced synthesis method, and DFT assessment of compound stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗