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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Electronic Structure, Spectroscopy and Correlation Effects in Novel Materials

This project was targeted on electronic structure, spectroscopic studies, and correlation effects in a variety of novel materials of great current interest. Spectroscopies resolved highly in momentum, energy or spatial dimensions are playing a key role in unraveling the nature of the ground state and excitation properties in wide classes of novel materials. The seminal insights thus obtained are of critical importance not only for answering some of the fundamental questions facing condensed matter physics and materials science today, but also for understanding and thus helping to design and develop new materials with desirable properties, which will continue to be the key to the survival of mankind and its energy needs as a technological society long into the future. However, spectroscopies do not provide a direct map of electronic states, but act as a very complex ‘filter’ or ‘mapping’ of the underlying spectrum. This connection between the electronic states and measured spectra—called the ‘matrix element effect’—is in general an extremely complex function of the phase space of the experiment (e.g. energy/polarization of photons in photoemission), presenting both a challenge and an opportunity. So motivated, this project pursued techniques for realistic treatment of electronic spectra of a wide variety of materials, which served as a prelude to formulating and implementing methodologies for making direct connection with various spectroscopies such as ARPES, STS/STM, and inelastic light scattering. Specific systems are topological materials, including 2D ultrathin films beyond graphene, novel superconductors, and nanocrystals, among others. Our goal was to exploit the strengths of various spectroscopies to piece together the most complete picture of electronic states in systems of current interest, enabling direct and sharpened confrontations with theoretical models, and also to help advance the reach of various spectroscopies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

PhILMs: Collaboratory on Mathematics and Physics-Informed Learning Machines for Multiscale and Multiphysics Problems

The landscape of computational science and engineering is continually evolving, with the challenge of high-dimensional regression problems standing as a significant hurdle in numerous scientific endeavors. Addressing this challenge, our research, funded by this award, has led to the development of an innovative computational framework known as Probabilistic Partition of Unity Networks (PPOU-Nets). This initiative represents a collaborative effort to harness the potential of mathematics and physics-informed machine learning in tackling multiscale and multiphysics problems prevalent in high-dimensional spaces. Through this work, we have proposed a novel methodology that seamlessly integrates adaptive dimensionality reduction and a mixture of experts model, thereby facilitating a more efficient and accurate approximation of complex functions. This research effort has not only advanced the state of computational science but also opened new avenues for exploration in quantum computing and beyond. This report outlines the motivation, methodology, key findings, and implications of our work, underscoring our contributions to the broader scientific community and the potential pathways for future research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Understanding the Thermal Physics and Metallurgy of Metal Big Area Additive Manufacturing

The research goal of this EPSCoR-DOE partnership is to mitigate defects in parts made using a new type of additive manufacturing (AM) process called metal Big Area Additive Manufacturing (m-BAAM). To realize this goal, the PIs will detect and correct defects in the part as it is being printed by combining fundamental knowledge of the thermal physics and metallurgy of m-BAAM with in-process sensor data. Developed at the DOE-funded Manufacturing Demonstration Facility at Oak Ridge National Laboratory, the m-BAAM process involves one or more robots working together to produce a part by fusing metal wire layer-by-layer using arc welding. The process can print large metal parts such as turbine blades, which is not possible using other AM processes. In addition, m-BAAM production rates are more than ten times faster than other AM processes while requiring one-tenth of the material cost. Despite their potential to become a critical force multiplier in the energy generation industry, m-BAAM parts may fail to print accurately due to retention of heat and uneven cooling. Overheating and anomalous cooling rates in turn can cause inconsistencies in the microstructure, leading to sudden failure when used in safety-critical applications. In other words, flaw formation in m-BAAM parts is governed by the thermal history – intensity and spatial distribution of heat inside the part during printing. The thermal history is a complex function of the part shape and process settings such as welding energy, path taken by the welding torch for deposition (tool path), wire feed rate, among others.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Predicting Biomass Yields of Advanced Switchgrass Cultivars for Bioenergy and Ecosystem Services Using Machine Learning

The production of advanced perennial bioenergy crops within marginal areas of the agricultural landscape is gaining interest due to its potential to sustainably produce feedstocks for biofuels and bioproducts while also improving the sustainability and resilience of commodity crop production. However, predicting the biomass yields of this production system is challenging because marginal areas are often relatively small and spread around agricultural fields and are typically associated with various abiotic conditions that limit crop production. Machine learning (ML) offers a viable solution as a biomass yield prediction tool because it is suited to predicting relationships with complex functional associations. The objectives of this study were to (1) evaluate the accuracy of commonly applied ML algorithms in agricultural applications for predicting the biomass yields of advanced switchgrass cultivars for bioenergy and ecosystem services and (2) determine the most important biomass yield predictors. Datasets on biomass yield, weather, land marginality, soil properties, and agronomic management were generated from three field study sites in two U.S. Midwest states (Illinois and Iowa) over three growing seasons. The ML algorithms evaluated in the study included random forests (RFs), gradient boosting machines (GBMs), artificial neural networks (ANNs), K-neighbors regressor (KNR), AdaBoost regressor (ABR), and partial least squares regression (PLSR). Coefficient of determination (R 2 ) and mean absolute error (MAE) were used to evaluate the predictive accuracy of the tested algorithms. Results showed that the ensemble methods, RF (R 2 = 0.86, MAE = 0.62 Mg/ha), GBM (R 2 = 0.88, MAE = 0.57 Mg/ha), and GBM (R 2 = 0.78, MAE = 0.66 Mg/ha), were the most accurate in predicting biomass yields of the Independence, Liberty, and Shawnee switchgrass cultivars, respectively. This is in agreement with similar studies that apply ML to multi-feature problems where traditional statistical methods are less applicable and datasets used were considered to be relatively small for ANNs. Consistent with previous studies on switchgrass, the most important predictors of biomass yield included average annual temperature, average growing season temperature, sum of the growing season precipitation, field slope, and elevation. This study helps pave the way for applying ML as a management tool for alternative bioenergy landscapes where understanding agronomic and environmental performance of a multifunctional cropping system seasonally and interannually at the sub-field scale is critical.

09 BIOMASS FUELS↗
DOE OSTI2025

A Refined BISON-Griffin Workflow For Designing Targeted TRISO Transient Experiments In The Transient Reactor Test Facility

U.S. industry is expected to deploy tristructural isotropic (TRISO) particle fuel technologies for commercial reactors within the next decade. In our previous work, we defined a preliminary transient design space for TRISO fuels, identified potential gaps in the available data, and began to develop multiphysics modeling tools that could be applied to design targeted Transient Reactor Test Facility (TREAT) experiments to fill these gaps. This work builds on that foundation by (1) updating BISON fuel performance and Griffin reactor physics models to reflect the current TREAT experiment tube and capsule designs,(2) coupling the codes to improve the accuracy and usability of the transient design analyses, and (3) demonstrating their use over an expanded design space that includes fuel burnup. The simulated mechanical responses of the TRISO particles were complex functions of fission product accumulation, fission gas release, and irradiation-induced dimensional change in the pyrolytic carbon layers. Predicted tangential stresses in particle silicon carbide layers were least compressive for preheated tests involving fresh fuels but remained compressive throughout the ranges of temperature, heat rate, and burnup considered in this work. Finally, comparisons between the potential TREAT transients and historical test reactor irradiations showed that the TREAT tests would produce significantly lower average energy deposition rates, yielding less severe transients with greater relevance to near-term commercial applications. Use of these predictive capabilities has the potential to increase the value of each test, improving the overall efficiency and cost effectiveness of transient testing for TRISO and other advanced fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Real-space Kohn–Sham density functional theory for complex energy applications

Real-space Kohn-Sham density functional theory (real-space KS-DFT) enables large-scale electronic structure simulations that is particularly well-suited for the modern high-performance computing (HPC) architectures. This feature article reviews its theoretical foundations, highlights the algorithmic advances and recent developments, and showcases applications in complex nano systems. We aim to provide a perspective on the trajectory of real-space KS-DFT as an emerging tool for computational chemistry and materials science in the exascale era.

Zhang, Zeyi↗
DOE OSTI2023

Predicting Mössbauer Parameters of Nonheme Diiron Complexes with Density Functional Theory

Mössbauer spectroscopy provides significant insights into the electronic structure and environment of the metal centers. In this work, we investigate the electronic structures of a set of nonheme diiron complexes by evaluating two key parameters pertaining to Mössbauer spectroscopy, namely, the isomer shift (δ) and quadrupole splitting (|ΔE Q |), using different levels of density functional theory (DFT). The diiron systems investigated here span diverse oxidation states, bridging motifs, and spin coupling patterns, which present a challenging case for theoretical predictions. We demonstrate that the combination of B97-D3/def2-TZVP is an efficient approach in modeling both the δ and |ΔEQ| values with high accuracy for the representative nonheme diiron complexes. We also show that δ is accurately predicted irrespective of the choice of approximate density functional while the |ΔE Q | is sensitive to the level of theory employed. Further investigation shows that the present methodology assessed using synthetic nonheme diiron complexes could be extended to nonheme diiron enzyme active sites, featuring both ferromagnetic and antiferromagnetic coupling between the iron centers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Synthesis and Surface Attachment of Molecular Re(I) Complexes Supported by Functionalized Bipyridyl Ligands

Eleven 2,2'-bipyridine (bpy) ligands functionalized with attachment groups for covalent immobilization on silicon surfaces were prepared. Five of the ligands feature silatrane functional groups for attachment to metal oxide coatings on the silicon surfaces, while six contain either alkene or alkyne functional groups for attachment to hydrogen-terminated silicon surfaces. The bpy ligands were coordinated to Re(CO) 5 Cl to form complexes of the type Re(bpy)(CO) 3 Cl, which are related to known catalysts for CO 2 reduction. Six of the new complexes were characterized using X-ray crystallography. As proof of principle, four molecular Re complexes were immobilized on either a thin layer of TiO 2 on silicon or hydrogen-terminated silicon. The surface-immobilized complexes were characterized using X-ray photoelectron spectroscopy, IR spectroscopy, and cyclic voltammetry (CV) in the dark and for one representative example in the light. The CO stretching frequencies of the attached complexes were similar to those of the pure molecular complexes, but the CVs were less analogous. For two of the complexes, comparison of the electrocatalytic CO 2 reduction performance showed lower CO Faradaic efficiencies for the immobilized complexes than the same complex in solution under similar conditions. In particular, a complex containing a silatrane linked to bpy with an amide linker showed poor catalytic performance and control experiments suggest that amide linkers in conjugation with a redox-active ligand are not stable under highly reducing conditions and alkyl linkers are more stable. So a conclusion of this work is that understanding the behavior of molecular Re catalysts attached to semiconducting silicon is more complicated than related complexes, which have previously been immobilized on metallic electrodes.

14 SOLAR ENERGY↗
DOE OSTI2021

Accurate Thermochemistry of Complex Lignin Structures via Density Functional Theory, Group Additivity, and Machine Learning

A molecular-level understanding of lignin structures and bond dissociation energies could facilitate depolymerization technologies. Still, this information is currently limited due to the lack of databases and the simplification of surrogate models. Here, substitution effects on seven common linkages in lignin polymers are systematically investigated. An automated reaction network generator is employed to create a database of structures. A new group additivity (GA) model based on principal component analysis (PCA) descriptors is introduced and trained on gas-phase density functional theory data of 4100 species at the M06-2X/6-311++G(d,p) level. Hydrogen bonds, local steric, and nonaromatic ring contributions are also incorporated. Lastly, we improve the accuracy of the group additivity model to reach the G4 theory by computing a data set of 770 species at this level and using a data fusion approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Anatomy of an agricultural antagonist: Feeding complex structure and function of three xylem sap‐feeding insects illuminated with synchrotron‐based 3D imaging

Abstract Many insects feed on xylem or phloem sap of vascular plants. Although physical damage to the plant is minimal, the process of insect feeding can transmit lethal viruses and bacterial pathogens. Disparities between insect‐mediated pathogen transmission efficiency have been identified among xylem sap‐feeding insects; however, the mechanistic drivers of these trends are unclear. Identifying and understanding the structural factors and associated integrated functional components that may ultimately determine these disparities are critical for managing plant diseases. Here, we applied synchrotron‐based X‐ray microcomputed tomography to digitally reconstruct the morphology of three xylem sap‐feeding insect vectors of plant pathogens: Graphocephala atropunctata (blue‐green sharpshooter; Hemiptera, Cicadellidae) and Homalodisca vitripennis (glassy‐winged sharpshooter; Hemiptera, Cicadellidae), and the spittlebug Philaenus spumarius (meadow spittlebug; Hemiptera, Aphrophoridae). The application of this technique revealed previously undescribed anatomical features of these organisms, such as key components of the salivary complex. The visualization of the 3D structure of the precibarial valve led to new insights into the mechanism of how this structure functions. Morphological disparities with functional implications between taxa were highlighted as well, including the morphology and volume of the cibarial dilator musculature responsible for extracting xylem sap, which has implications for force application capabilities. These morphological insights will be used to target analyses illuminating functional differences in feeding behavior.

3D imaging↗
DOE OSTI2026

The solubility of NdPO 4 and DyPO 4 and stability of Nd and Dy chloride and hydroxyl complexes as a function of pH and salinity to 450 °C

The mobility of rare earth elements (REE) in geological systems is often controlled by the stability of monazite and xenotime, which are important hosts for the light and heavy REE. These REE phosphates constitute important resources and provide information on ore formation conditions and timing due to their uses as geothermometers and geochronometers. While the thermodynamic properties for these minerals are well-established up to high temperature and pressure, the properties for the aqueous REE complexes are not well constrained with limited information up to 300 °C. In this study, the solubility of synthetic NdPO 4 and DyPO 4 endmembers were measured in hydrothermal sub- to supercritical NaCl-bearing aqueous solutions from 350 at saturated water vapor pressure to 450 °C at 700 bar. The speciation of Nd and Dy was determined in acidic to alkaline solutions (pH 25 °C values from 2 to 10), and indicates that the hydroxyl species REE(OH) 2 + and REE(OH) 3 0 predominate at low salinity (0.01 mol/kg NaCl) with some contribution of REE chloride species REECl 2+ and REECl 2 + in acidic fluids. The REE phosphate solubility measured in these experiments is up to two orders of magnitude higher than predicted using existing thermodynamic properties from literature for aqueous species extrapolated from lower temperature data to supercritical conditions. To address this discrepancy, the thermodynamic properties of the REE aqueous species were optimized using GEMSFITS to derive the formation constants for the REE chloride (β Cl ) and hydroxyl (β OH ) complexes in the studied temperature range. This study highlights the importance of the hydroxyl species REE(OH) 2 + and REE(OH) 3 0 over a wide range of pH and temperature. As a result, the revised thermodynamic properties for Dy and Nd chloride and hydroxyl species more accurately predict the solubility of NdPO 4 and DyPO 4 and provide insight into the speciation and mobility of the light and heavy REE in hydrothermal supercritical fluids in the crust.

58 GEOSCIENCES↗
DOE OSTI2025

Adsorption of REEs to Kaolinite via Ion Exchange and Surface Complexation as a Function of Water Chemistry

Rare earth elements (REEs) are critical components of modern technology behind renewable energy, transportation, and electronics but have a limited current supply. A substantial portion of global REE production relies on ion adsorption deposits. A high abundance of kaolinite in REE enrichment zones within these deposits suggests that kaolinite controls the subsurface migration of REEs. This study aimed to improve the current understanding of REE binding to kaolinite under varying water chemistry conditions. We conducted batch experiments with kaolinite (KGa-2) and three REEs (Nd, Dy, and Yb) at varying pH, electrolyte concentration, dissolved inorganic carbon (DIC), low molecular weight organic acids (citric and oxalic acids), and total REE concentration conditions. Increasing electrolyte concentration inhibits REE adsorption at pH < 7, suggesting that ion exchange contributes to adsorption at these pH values. DIC affects adsorption above pH 7–8 by forming strong aqueous complexes with heavy REEs. Citric acid decreases REE adsorption via aqueous complexation of REEs at pH > 5 but does not affect adsorption at pH < 5. The surface complexation model captures the main adsorption trends with two mechanisms: ion exchange on basal planes at pH < ∼6 and inner-sphere surface complexation to edge sites at pH > ∼6. Equilibrium constants for surface complexation increase in the order of Yb > Dy > Nd, indicating a higher strength of adsorption for heavy REEs. This study demonstrates how water chemistry conditions control the adsorption mechanisms that may determine the mobility of REEs in subsurface environments rich in kaolinite.

58 GEOSCIENCES↗
DOE OSTI2023

Optimization Stability in Excited-State-Specific Variational Monte Carlo

Here, we investigate the issue of optimization stability in variance-based state-specific variational Monte Carlo, discussing the roles of the objective function, the complexity of wave function ansatz, the amount of sampling effort, and the choice of minimization algorithm. Using a small cyanine dye molecule as a test case, we systematically perform minimizations using variants of the linear method as both a standalone algorithm and in a hybrid combination with accelerated descent. We demonstrate that adaptive step control is crucial for maintaining the linear method's stability when optimizing complicated wave functions and that the hybrid method enjoys both greater stability and minimization performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Functional enzyme–polymer complexes

Significance The use of biological enzyme catalysts could have huge ramifications for chemical industries. However, these enzymes are often inactive in nonbiological conditions, such as high temperatures, present in industrial settings. Here, we show that the enzyme PETase (polyethylene terephthalate [PET]), with potential application in plastic recycling, is stabilized at elevated temperature through complexation with random copolymers. We demonstrate this through simulations and experiments on different types of substrates. Our simulations also provide strategies for designing more enzymatically active complexes by altering polymer composition and enzyme charge distribution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Development of sterically hindered siloxide-functionalized polyoxotungstates for the complexation of 5d-metals

In this study, we extend the family of organosilyl-functionalized trivacant Keggin polyoxotungstates, [PW 9 O 34 (RSiOH) 3 ] 3− (R = n Pr, i Pr, t Bu), through the introduction of bulky aryl and aliphatic silanol substituents, namely phenyl, cyclohexyl and biphenyl. This work was performed in order to study the impact of these large functional groups on the accessibility of the well-defined tridentate coordination site. Coordination of hafnium to these type II hybrid polyoxotungstates was conducted in order to study the ability of the bulkier ligand pockets to support larger cations in comparison to those previously reported (e.g. Ti 4+ , V 3+ , V 5+ , Ge 4+ ). Increased steric hindrance around the coordination site from the biphenyl groups resulted in much longer reaction times for the complexation reaction compared to the other functional groups used, but the impact of our design toward stabilizing reactive species proved limited, as all complexes easily undergo hydrolysis of the Hf-O t Bu bond in the presence of water. As a result, electrochemical investigations of the ligands and hafnium complexes reveal that the redox events centered on the polyoxotungstate core can be tuned by varying the substituents on the silyl fragment, and exhibit a cathodic shift after coordination of the redox inactive tetravalent cation.

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

Electronic structure analysis and DFT benchmarking of Rydberg-type alkali-metal-crown ether, -cryptand, and -adamanzane complexes

Density functional theory (DFT) and electron propagator theory (EPT) calculations were performed to study ground and excited electronic structures of alkali-metal (M) coordinated 9-crown-3, 24-crown-8, [2.1.1]cryptand, o-Me 2 -1.1.1, and 3 6 Adamanzane complexes. Each complex bears an expanded electron in the periphery and occupies diffuse 1p-, 1d-, 1f-type molecular orbitals (or superatomic 1P, 1D, 1F orbitals) in excited electronic states. The calculated superatomic shell model of the M(9-crown-3) 2 is 1S, 1P, 1D, 1F, 2S, 2P, 2D, 1G and it is held by all other complexes up to the studied 1F level. Due to the highly diffuse nature of the electron, the ionization energies of these complexes are significantly lower (1.6–2.0 eV) and hence these complexes belong to the superalkali category. Further, the ab initio EPT ionization energy and the excitation energies of the Li(9-crown-3) 2 were used to evaluate DFT errors associated with a series of exchange correlation functionals that span multiple rungs of Jacob's ladder (i.e., GGA, meta-GGA, global GGA hybrid, meta-GGA hybrid, range-separated hybrid, double-hybrid). Among these, the best performing functional is the range-separated hybrid CAM-B3LYP and the errors are within 6% of high-level ab initio EPT results. The accuracy of CAM-B3LYP is indeed transferable to similar complexes and hence the findings are expected to accelerate the progression of studies of Rydberg-type systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multiplexed Probing for Functional Capacity Measurements in Complex and Limited-Size Samples

A new strategy using glass as a solid support for functionalization with chemical probes has been recently developed with successful results. The next step in glass functionalization is to pair chemical probes with fluorescent glass microspheres. This approach gives us a way to directly quantify probe-bound protein using Fluorescence-Activated Cell Sorting (FACS). FACS has already shown to be amendable to glass microspheres, demonstrating changes in probe-bound protein concentration. Suitable probing conditions for gram-positive and negative microbes, complex microbial communities from myriad ecosystems, and eukaryotic cells/tissues have traditionally suffered from set-backs, such as limited protein per sample and conditions atypical for probing. To remedy this, we propose to: (1) Demonstrate probe functionalization specific to glass microspheres by paired fluorophore and use those activity probes successfully with proteomics. Probes that are currently available (CYP5, GSH/GST, Glycoside Hydrolase) can be easily prepared onto glass surfaces. Probe-bound microspheres can be tested in ratios, first with known amounts of purified protein and then complex microbiome lysates. (2) Our validated microspheres are then used to determine quantitative amounts of protein through FACS sorting. Complimenting these results by proteomics, prepared microspheres are then optimized and condensed into a user-friendly kit. Once successfully commercialized, this multiplexed assay can be used with little to no technical expertise, making this available to various industries users.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗