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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Oxy-functionalization of Group 9 and 10 transition metal methyl ligands: use of pyridine-based hemi-labile ligands

Hemi-labile ligands (HLLs) are interesting candidates for catalysts since they may facilitate bond activation and bond formation through facile ligand dissociation/association. DFT studies are reported of hemi-labile ligands in conjunction with Group 9 and 10 metals for oxygen atom insertion into metal–methyl bonds. Analysis of the reaction of pyridine- N -oxide with d 8 -[L n M (Me)(THF)] q + (M = Co, Rh, Ir, Ni, Pd, Pt; L n = 2-(CH 3 OCH 2 )Py; q = 0 and +1 for Group 9 and 10 metals, respectively; Py = pyridine; THF = tetrahydrofuran) indicates that oxy-insertion for Group 9 complexes occurs with lower free energy barriers than their Group 10 congeners. Analysis of structural changes along the reaction coordinate indicates that the initial oxygen atom transfer and subsequent methyl migration steps are favored by a reduction and increase, respectively, in coordination number. This emphasizes that HLLs could be uniquely positioned to assist both transformations within a single complex. Additionally, such ligands are worthy of experimental study due to their ability to meet the disparate coordination demands for two-step, redox-based oxy-insertion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Tunable Oxygen Functional Groups as Electrocatalysts on Graphite Felt Surfaces for All‐Vanadium Flow Batteries

Abstract A dual oxidative approach using O 2 plasma followed by treatment with H 2 O 2 to impart oxygen functional groups onto the surface of a graphite felt electrode. When used as electrodes for an all‐vanadium redox flow battery (VRB) system, the energy efficiency of the cell is enhanced by 8.2 % at a current density of 150 mA cm −2 compared with one oxidized by thermal treatment in air. More importantly, by varying the oxidative techniques, the amount and type of oxygen groups was tailored and their effects were elucidated. It was found that O−C=O groups improve the cells performance whereas the C−O and C=O groups degrade it. The reason for the increased performance was found to be a reduction in the cell overpotential after functionalization of the graphite felt electrode. This work reveals a route for functionalizing carbon electrodes to improve the performance of VRB cells. This approach can lower the cost of VRB cells and pave the way for more commercially viable stationary energy storage systems that can be used for intermittent renewable energy storage.

Estevez, Luis↗
DOE OSTI2021

Fourier Neural Networks as Function Approximators and Differential Equation Solvers

We present a Fourier neural network (FNN) that can be mapped directly to the Fourier decomposition. The choice of activation and loss function yields results that replicate a Fourier series expansion closely while preserving a straightforward architecture with a single hidden layer. The simplicity of this network architecture facilitates the integration with any other higher-complexity networks, at a data pre- or postprocessing stage. We validate this FNN on naturally periodic smooth functions and on piecewise continuous periodic functions. We showcase the use of this FNN for modeling or solving partial differential equations with periodic boundary conditions. The main advantages of the current approach are the validity of the solution outside the training region, interpretability of the trained model, and simplicity of use.

Fourier decomposition↗
DOE OSTI2020

Electronic Structures and Magnetism of Zr-, Th-, and U-based Metal-Organic Frameworks (MOFs) by Density Functional Theory

Metal-organic frameworks (MOFs) have recently gained wide interest as candidate materials for nuclear waste immobilization. While the fundamental thermodynamic properties, such as the substitution energies determine the favorability of radionuclide sequestration by utilization of a MOF matrix, the studies of MOF electronic structure reveal the role of d-, and/or f-electrons on changes in physical properties of actinide-containing materials. We use density functional theory (DFT) calculations to investigate the electronic structures of Zr-, Th-, and U-MOFs, including their electronic band structures and, where appropriate, their magnetic properties. We employ various DFT methods including DFT+U, collinear spin-polarization, spin-orbit coupling, and different flavors of exchange-correlation functionals to assess the robustness to the specific exchange-correlation functional. Unlike the Zr-, and Th-MOFs, the U-MOF is found to be sensitive to electron localization and spin; hence we explore the magnetic structure of the U-MOF in further detail.

Metal-Organic Framework, MOF, Actinides, DFT↗
DOE OSTI2016

Atomic to Nanoscale Investigation of Functionalities of an Al2O3 Coating Layer on a Cathode for Enhanced Battery Performance

Surface coating has been identified as an effective approach for enhancing the capacity retention of layered structure cathode. However, the underlying operating mechanism of such a thin coating layer, in terms of surface chemical functionality and capacity retention, remains unclear. In this work, we use aberration-corrected scanning transmission electron microscopy and high-efficiency spectroscopy to probe the delicate functioning mechanism of an Al2O3 coating layer on a Li1.2Ni0.2Mn0.6O2 cathode. We discovered that in terms of surface chemical function, the Al2O3 coating suppresses the side reaction between the cathode and the electrolyte during battery cycling. At the same time, the Al2O3 coating layer also eliminates the chemical reduction of Mn from the cathode particle surface, therefore preventing the dissolution of the reduced Mn into the electrolyte. In terms of structural stability, we found that the Al2O3 coating layer can mitigate the layer to spinel phase transformation, which otherwise will be initiated from the particle surface and propagate toward the interior of the particle with the progression of battery cycling. The atomic to nanoscale effects of the coating layer observed here provide insight into the optimized design of a coating layer on a cathode to enhance the battery properties.

Yan, Pengfei↗
DOE OSTI2017

Functional Enzyme-Based Approach for Linking Microbial Community Functions with Biogeochemical Process Kinetics

The kinetics of biogeochemical processes in natural and engineered environmental systems are typically described using Monod-type or modified Monod-type models. These models rely on biomass as surrogates for functional enzymes in microbial community that catalyze biogeochemical reactions. A major challenge to apply such models is the difficulty to quantitatively measure functional biomass for constraining and validating the models. On the other hand, omics-based approaches have been increasingly used to characterize microbial community structure, functions, and metabolites. Here we proposed an enzyme-based model that can incorporate omics-data to link microbial community functions with biogeochemical process kinetics. The model treats enzymes as time-variable catalysts for biogeochemical reactions and applies biogeochemical reaction network to incorporate intermediate metabolites. The sequences of genes and proteins from metagenomes, as well as those from the UniProt database, were used for targeted enzyme quantification and to provide insights into the dynamic linkage among functional genes, enzymes, and metabolites that are necessary to be incorporated in the model. The application of the model was demonstrated using denitrification as an example by comparing model-simulated with measured functional enzymes, genes, denitrification substrates and intermediates

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DOE OSTI2020

Spin Splitting Energy of Transition Metals: A New, More Affordable Wave Function Benchmark Method and Its Use to Test Density Functional Theory

Accurately predicting the spin splitting energy of chemical species is important for understanding their reactivity and magnetic properties, but it is very challenging, especially for molecules containing transition metals. One impediment to progress is the scarcity of accurate benchmark data. Here we report a set of calculations designed to yield reliable benchmarks for simple transition-metal complexes that can be used to test density functional methods that are affordable for large systems of more practical interest. Various wave function methods are tested against experiment for Fe 2+ , Fe 3+ , and Co 3+ , including CASSCF, CASPT2, CASPT3, MRCISD, MRCISD+Q, ACPF, AQCC, CCSD(T), and CASPT2/CCSD(T) and also a new method called CASPT2.5, which is performed by taking the average of the CASPT2 and CASPT3 energies. Furthermore, we find that MRCISD+Q, ACPF, and AQCC require smaller active spaces for good accuracy than are required by CASPT2 and CASPT3, and this aspect may be important for calculations on larger molecules; here we find that CASPT2.5 extrapolated to a complete basis set is the most suitable method—in terms of computational cost and in terms of accuracy on monatomic systems—and therefore we chose this method for molecular benchmarks. Then Kohn–Sham density functional calculations with 60 exchange-correlation functionals are tested for FeF 2 , FeCl 2 , and CoF 2 . We find that MN15-L, M06-SX, and revM06 have very good agreement with CASPT2.5 benchmarks in terms of both the spin splitting energy and the optimized geometry for each spin state. In addition, we recommend def2-TZVP as the most suitable basis set to perform density functional calculations for molecular spin splitting energies; extra polarization functions in the basis set do not help to increase the accuracy of the spin splitting energy in KS calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Approximate Green’s Function Coupled Cluster A Method Employing Effective Dimension Reduction

The Green’s function coupled cluster (GFCC) method, originally proposed in the early 1990s, is a powerful many-body tool for computing and analyzing the electronic structures of molecular structures and periodic systems, especially when electrons are strongly correlated. However, in order for the GFCC method to become an approach that can be routinely used in the electronic structure calculations, more robust linear algebraic techniques and approximations need to be employed to reduce its extremely high computational overhead. In our recent studies, we showed that the GFCC equation can be numerically solved by seeking solutions of multiple linear systems in the frequency regime of interest, which can be easily distributed in a massively parallel environment, and broaden the avenue for more state-of-the-art numerical linear algebraic tools associated with multiple linear systems to be kicked in to this field. In the present pursuit of this practice, we show a successful application of model order reduction (MOR) techniques in the GFCC framework. Briefly speaking, for a frequency regime of interest that requires a high resolution of spectral function, instead of solving GFCC linear equation in the original dimension for every single frequency point, an easily-solvable linear system model with reduced dimension can be built upon projecting the original GFCC linear system into a subspace, from which the interpolation and extrapolation can give a reasonable approximation to the results of the original GFCC linear equations. Here, we show that the subspace can be properly constructed in an iterative manner from the auxiliary vectors of the GFCC linear equations at some select frequencies inside the frequency regime. During the iterations, the quality of the subspace, as well as the linear system model, can be systematically improved. The approach is tested in this work in terms of the efficiency and accuracy of computing spectral functions for some typical molecular systems including carbon monoxide, 1,3-butadiene, benzene, and adenine molecules. As a byproduct, the high quality linear system model is also found to be able to provide high quality initial guess for the existing linear solver to improve the convergence performance.

Peng, Bo↗
DOE OSTI2019

M11plus: A Range-Separated Hybrid Meta Functional with Both Local and Rung-3.5 Correlation Terms and High Across-the-Board Accuracy for Chemical Applications

The way to improve Kohn–Sham density functional theory is to improve the exchange–correlation functionals, and functionals have been successively improved by adding new ingredients, especially local spin density gradients, nonlocal Hartree–Fock exchange, and local meta terms based on kinetic energy density. Here, we present a new kind of functional obtained by adding rung-3.5 terms to a functional including local gradients, local meta terms, and range-separated Hartree–Fock exchange. A rung-3.5 term has short-range nonlocality designed to account for nondynamic correlation; we add two kinds of rung-3.5 terms, one kind modeled on position-dependent Hartree–Fock exchange and another modeled on the spin density at a point interacting with the opposite-spin exchange hole at the same point. Here, optimization of the functional yields broad accuracy for both ground states and excited states with especially significant improvement for systems with strong correlation.

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