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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Operando pair distribution function analysis of nanocrystalline functional materials: the case of TiO 2 -bronze nanocrystals in Li-ion battery electrodes

Structural modelling of operando pair distribution function (PDF) data of complex functional materials can be highly challenging. To aid the understanding of complex operando PDF data, this article demonstrates a toolbox for PDF analysis. The tools include denoising using principal component analysis together with the structureMining , similarityMapping and nmfMapping apps available through the online service `PDF in the cloud' ( PDFitc , https://pdfitc.org/). The toolbox is used for both ex situ and operando PDF data for 3 nm TiO 2 -bronze nanocrystals, which function as the active electrode material in a Li-ion battery. The tools enable structural modelling of the ex situ and operando PDF data, revealing two pristine TiO 2 phases (bronze and anatase) and two lithiated Li x TiO 2 phases (lithiated versions of bronze and anatase), and the phase evolution during galvanostatic cycling is characterized.

Chemistry↗
DOE OSTI2020

Functional materials and devices by self-assembly

The field of self-assembly has moved far beyond early work, where the focus was primarily the resultant beautiful two- and three-dimensional structures, to a focus on forming materials and devices with important properties either otherwise not available, or only available at great cost. Over the last few years, materials with unprecedented electronic, photonic, energy-storage, and chemical separation functionalities were created with self-assembly, while at the same time, the ability to form even more complex structures in two and three dimensions has only continued to advance. Self-assembly crosscuts all areas of materials. Functional structures have now been realized in polymer, ceramic, metallic, and semiconducting systems, as well as composites containing multiple classes of materials. Finally, as the field of self-assembly continues to advance, the number of highly functional systems will only continue to grow and make increasingly greater impacts in both the consumer and industrial space.

Materials for Devices↗
DOE OSTI2023

A Combined Wave Function and Density Functional Approach for K-Edge X-ray Absorption Near-Edge Spectroscopy: A Case Study of Hydrated First-Row Transition Metal Ions

The prediction of X-ray absorption spectra (XAS) of transition metal complexes has important and broad application areas in chemistry and biology. In this letter, we have investigated the predictive ability of multiconfiguration pair-density functional theory (MC-PDFT) for X-ray absorption spectra by calculating the metal K pre-edge features of aquated 3d transition metal ions in common oxidation states. MC-PDFT results were compared with experimentally measured spectra as well as analyzed against results from restricted active-space second-order perturbation theory (RASPT2) and time-dependent density functional theory (TDDFT). As expected, TDDFT performs well for excited states that can be accurately represented by singly excited configurations but fails for excited states where higher order excitations become important. On the other hand, both RASPT2 and MC-PDFT provide quantitatively accurate results for all excited states irrespective of their character. While core-level spectroscopy with RASPT2 is accurate, it is computationally expensive. Finally, our results show that MC-PDFT performs equally well with significantly lower computational cost and is an encouraging alternate approach for X-ray spectroscopies.

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

Electrochemical CO2 Reduction over Metal-/Nitrogen-Doped Graphene Single-Atom Catalysts Modeled Using the Grand-Canonical Density Functional Theory

Renewably driven, electrochemical conversion of carbon dioxide into value-added products is expected to be a critical tool in global decarbonization. However, theoretical studies based on the computational hydrogen electrode largely ignore the nonlinear effects of the applied potential on the calculated results, leading to inaccurate predictions of catalytic behavior or mechanistic pathways. Here, we use grand canonical density functional theory (GC-DFT) to model electrochemical CO2 reduction (CO2R) over metal- and nitrogen-doped graphene catalysts (MNCs) and explicitly include the effects of the applied potential. We used GC-DFT to compute the CO2 to CO reaction intermediate energies at -0.3, -0.7, and -1.2 VSHE catalyzed by MNCs each doped with 1 of the 10 3d block metals coordinated by four pyridinic nitrogen atoms. Our results predict that Sc-, Ti-, Co-, Cu-, and Zn-N4Cs effectively catalyze CO2R at moderate to large reducing potentials (-0.7 to -1.2 VSHE). ZnN4C is a particularly promising electrocatalyst for CO2R to CO both at low and moderate applied potentials based on our thermodynamic analysis. Our findings also explain the observed pH independence of CO production over FeN4C and predict that the rate-determining step of CO2R over FeN4C is not *CO2- formation but rather *CO desorption. Additionally, the GC-DFT-computed density of states analysis illustrates how the electronic states of MNCs and adsorbates change non-uniformly with applied potential, resulting in a significantly increased *CO2- stability relative to other intermediates and demonstrating that the formation of the adsorbed *CO2- anion is critical to CO2R activation. This work demonstrates how GC-DFT paves the way for physically realistic and accurate theoretical simulations of reacting electrochemical systems.

CO2 reduction↗
DOE OSTI2021

A Flexible and Generic Functional Mock-up Unit Based Threat Injection Framework for Grid-interactive Efficient Buildings: A Case Study in Modelica

Grid-interactive efficient buildings (GEBs) have been considered as an important asset to support the power grid reliability by utilizing the demand flexibility offered by GEBs. GEBs are enabled by advances in sensors and controls, and the communication between building equipment, whole buildings, and the grid. The integration of different building technologies and network-based communication system makes GEBs vulnerable to passive threats such as equipment failure and active threats such as cyber-attacks. Modeling and simulation is an effective way to evaluate the impact of threats on the system performance. This paper proposes a generic and flexible threat injection framework for commonly-used building energy simulators such as EnergyPlus and Modelica to support threat modeling and evaluation. This framework leverages functional mock-up unit (FMU) to develop a general modeling interface for threat injection and simulation. A numerical case study using Modelica as a building energy simulator is conducted to demonstrate the capability of the framework for supporting single/multiple-order threat modeling and simulation of a GEB. Four threats and their combinations are injected on a Modelica-based threat-free building energy and control system, including operating supply fan at its full speed, remotely cycling the chiller on and off, blocking the chiller from receiving the chilled water supply temperature setpoints, and hijacking the global zone air temperature setpoint. Simulation results show that the cyber-attack that leads to short-term signal blocking has small effects on the system operation due to the "self-healing" feature of the heating, ventilation, and air-conditioning (HVAC) interactive control system. The threat that takes control of resetting the global zone air temperature setpoints has the most adverse impact on the system energy use, peak power demand, thermal comfort and the provision of demand flexibility. The combination of four threats have aggregative effects on the system but the effects are less than the additive effects of the individual threat.

Fu, Yanyang↗
DOE OSTI2023

Curing the Divergence in Time-Dependent Density Functional Quadratic Response Theory

While time-dependent density functional theory has emerged as a method of choice for computing electronic spectra and response of molecules and materials, its reliability is hindered by the adiabatic approximation that is commonly made. In this work, we address one problematic aspect that arises from this approximation: an incorrect pole structure in the quadratic response function, leading to unphysical divergences in excited state-to-state transition probabilities and hyperpolarizabilties. We find the form of the exact quadratic response kernel and derive a practical and accurate approximation that cures the divergence. Here, we demonstrate our results on excited state-to-state transition probabilities of a model system and of the LiH molecule.

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

Bypassing the Energy Functional in Density Functional Theory: Direct Calculation of Electronic Energies from Conditional Probability Densities

Density functional calculations can fail for want of an accurate exchange-correlation approximation. The energy can instead be extracted from a sequence of density functional calculations of conditional probabilities (CP DFT). Simple CP approximations yield usefully accurate results for two-electron ions, the hydrogen dimer, and the uniform gas at all temperatures. CP DFT has no self-interaction error for one electron, and correctly dissociates H2, both major challenges. For warm dense matter, classical CP DFT calculations can overcome the convergence problems of Kohn-Sham DFT.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Symmetry-mode analysis for local structure investigations using pair distribution function data

Symmetry-adapted distortion modes provide a natural way of describing distorted structures derived from higher-symmetry parent phases. Structural refinements using symmetry-mode amplitudes as fit variables have been used for at least ten years in Rietveld refinements of the average crystal structure from diffraction data; more recently, this approach has also been used for investigations of the local structure using real-space pair distribution function (PDF) data. Here, the value of performing symmetry-mode fits to PDF data is further demonstrated through the successful application of this method to two topical materials: TiSe2, where a subtle but long-range structural distortion driven by the formation of a charge-density wave is detected, and MnTe, where a large but highly localized structural distortion is characterized in terms of symmetry-lowering displacements of the Te atoms. Here, the analysis is performed using fully open-source code within the DiffPy framework via two packages developed for this work: isopydistort, which provides a scriptable interface to the ISODISTORT web application for group theoretical calculations, and isopytools, which converts the ISODISTORT output into a DiffPy-compatible format for subsequent fitting and analysis. These developments expand the potential impact of symmetry-adapted PDF analysis by enabling high-throughput analysis and removing the need for any commercial software.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Inverter Reliability Estimation for Advanced Inverter Functionality

In the near future, grid operators are expected to regularly use advanced distributed energy resource (DER) functions, defined in IEEE 1547-2018, to perform a range of grid-support operations. Many of these functions adjust the active and reactive power of the device through commanded or autonomous modes, which will produce new stresses on the grid-interfacing power electronics components, such as DC/AC inverters. In previous work, multiple DER devices were instrumented to evaluate additional component stress under multiple reactive power setpoints. We utilize quasi-static time-series simulations to determine voltage-reactive power mode (volt-var) mission profile of inverters in an active power system. Mission profiles and loss estimates are then combined to estimate the reduction of the useful life of inverters from different reactive power profiles. It was found that the average lifetime reduction was approximately 0.15% for an inverter between standard unity power factor operation and the IEEE 1547 default volt-var curve based on thermal damage due to switching in the power transistors. For an inverter with an expected 20-year lifetime, the 1547 volt-var curve would reduce the expected life of the device by 12 days. This framework for determining an inverter's useful life from experimental and modeling data can be applied to any failure mechanism and advanced inverter operation.

component degradation↗
DOE OSTI2023

Minimizing Optimal Transport for Functions with Fixed-Size Nodal Sets

Consider the class of zero-mean functions with fixed L ∞ and L 1 norms and exactly N ϵ N nodal points. Which functions f minimize W p (f + ,f – ), the Wasserstein distance between the measures whose densities are the positive and negative parts? We provide a complete solution to this minimization problem on the line and the circle, which provides sharp constants for previously proven “uncertainty principle”-type inequalities, i.e., lower bounds on N • W p (f + ,f – ). We further show that, while such inequalities hold in many metric measure spaces, they are no longer sharp when the non-branching assumption is violated; indeed, for metric star-graphs, the optimal lower bound on W p (f + ,f – ) is not inversely proportional to the size of the nodal set, N. Here, based on similar reductions, we make connections between the analogous problem of minimizing W p (f + ,f – ) for f defined on Ω C R d with an equivalent optimal domain partition problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Natural Charge-Transfer Analysis: Eliminating Spurious Charge-Transfer States in Time-Dependent Density Functional Theory via Diabatization, with Application to Projection-Based Embedding

For many types of vertical excitation energies, linear-response time-dependent density functional theory (LR-TDDFT) offers a useful degree of accuracy combined with unrivaled computational efficiency, although charge-transfer excitation energies are often systematically and dramatically underestimated, especially for large systems and those that contain explicit solvent. As a result, low energy electronic spectra of solution-phase chromophores often contain tens to hundreds of spurious charge-transfer states, making LR-TDDFT needlessly expensive in bulk solution. More nefariously, intensity borrowing by the low-energy charge-transfer states can affect intensities of the valence excitations even if those excitation energies are accurate. At higher excitation energies, it is difficult to distinguish spurious CT states from genuine charge-transfer-to-solvent (CTTS) excitations. In this work, we introduce an automated diabatization scheme that enables fast and effective screening of the CTTS acceptor space in bulk solution. Our procedure introduces the concept of “natural charge-transfer orbitals”, which provide a means to isolate characteristic pairs of orbitals that are most likely to participate in a CTTS excitation. The projection of these orbitals onto solvent-centered virtual orbitals provides a criterion for defining the most important solvent molecules in a given excitation. We apply this method to analyze an ab initio molecular dynamics (MD) trajectory of I-(aq) and report the lowest-energy CTTS band in the absorption spectrum. Our results are in excellent agreement with experimental measurements for bulk I-(aq), and only one-third of the water molecules in the I-(H2O)96 simulation cell need to be described with LR-TDDFT in order to obtain excitation energies that are converged to < 0.1 eV. The tools introduced herein will improve the accuracy, efficiency, and usability of LR-TDDFT in solution-phase environments

Carter-Fenk, Kevin D.↗
DOE OSTI2021

Uncertainty Quantification and Error Propagation in the Enthalpy and Entropy of Surface Reactions Arising from a Single DFT Functional

Accounting for parametric uncertainty in models is essential for quantifying the models’ predictive ability. Recently, approaches have been introduced to estimate parametric uncertainty in kinetic models while accounting for correlations among energy parameters. However, correlations have been estimated indirectly and correlations in entropies have not been accounted for. For surface-catalyzed microkinetic models of >C2 (more than two carbon-containing) molecules, which consist of thousands of reaction steps and intermediate surface species, first-principles density functional theory (DFT) is costly, and thus, estimation of thermochemistry and reaction barriers requires surrogate methods of DFT, such as group additivity and Brønsted–Evans–Polanyi relationships, respectively. For such parametrization, model uncertainty is unclear. This work develops a framework to overcome these gaps using group additivity and a single DFT functional. We estimate correlations in parameters of kinetic models and quantify uncertainty for thermochemistry, reaction barriers, reaction paths, and ultimately reaction rates, accounting also for the contribution of entropic uncertainty. Furthermore, the approach is illustrated on propane combustion and ethane oxidative dehydrogenation reactions.

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

Impact of Confinement and Zwitterionic Ligand Chemistry on Ion–Ion Selectivity of Functionalized Nanopores

Membranes incorporating zwitterionic chemistries have recently emerged as promising candidates for facilitating challenging ion–ion separations. Transport of ions in such membranes predominantly occurs in hydrated nanopores lined with zwitterionic monomers. Here, to shed light on the physics of ion–ion selectivity underlying such materials, we conducted molecular dynamics simulations of sodium halide transport in model nanopores grafted with sulfobetaine methacrylate molecules. Our results reveal that in both functionalized and unfunctionalized nanopores smaller ions prefer to reside near the pore center, while the larger ions tend to reside near the pore walls. An enhancement in the selective transport of larger anions is observed within the unfunctionalized nanopores relative to that in salt-in-water solutions. Upon functionalization of the nanopores with zwitterions (ZIs), the disparities in the anionic distribution profiles within the pores coupled with differences in the anion-ZI interactions result in a slowdown of larger anions relative to smaller anions. Increasing the ZI grafting density exacerbates these effects, further promoting the selective transport of smaller anions. Our results suggest that selectivity toward large anions can be realized by using nanoporous membranes with ZI content that is high enough to facilitate ion/water partitioning into the pores while preserving the characteristic tendency of the unfunctionalized pores to facilitate faster transport of the larger anions. On the other hand, selectivity toward smaller anions can be achieved by targeting ZI content within the pores that is high enough to significantly slow down the transport of large anions but not high enough to hinder the partitioning of ions/water molecules into the pore due to steric effects.

anions↗
DOE OSTI2022

Cation–Ligand Interactions Dictate Salt Partitioning and Diffusivity in Ligand-Functionalized Polymer Membranes

Membranes are an attractive alternative to current thermal separations due to their scalability and energy efficiency in desalinating water. Unfortunately, many of the conventional membrane materials available today are unable to differentiate between ionic solutes, especially alkali cations, compromising their use in ion–ion separations. Inspired by the ion-specific interactions exhibited by biological ion channels, recent research efforts have focused on synthesizing and characterizing new polymeric materials that incorporate ligands into polymer networks to bias solubility and/or diffusivity of one cationic species over another. Despite these efforts, little is known about the influence of incorporating ligands into polymer membranes on solubility and diffusivity of the complexing species. In this study, we first build a qualitative model of salt partitioning, diffusivity, and permeability in generic cation-complexing ligand-functionalized polymer membranes. Next, to validate our model and hypotheses, we perform atomistic molecular dynamics simulations of a 12-crown-4-functionalized membrane in the presence of alkali halide salts at low concentration. Generally, cation complexation enhances cation solubility but decreases diffusivity. Interestingly, the reduction in diffusivity is predicted to be larger than the enhancement in solubility for materials which operate by the mechanisms proposed in our physical picture, ultimately resulting in a reduction in the permeability of the selectively complexing ion.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nanoconfinement of Molecular Magnesium Borohydride Captured in a Bipyridine-Functionalized Metal-Organic Framework

The lower limit of metal hydride nanoconfinement is demonstrated through the coordination of a molecular hydride species to binding sites inside the pores of a metal-organic framework (MOF). Magnesium borohydride, which has a high hydrogen capacity, is incorporated into the pores of UiO-67bpy (Zr6O4(OH)4(bpydc)6 with bpydc2- = 2,2'-bipyridine-5,5'- dicarboxylate) by solvent impregnation. The MOF retained its long-range order, and transmission electron microscopy and elemental mapping confirmed the retention of the crystal morphology and revealed a homogeneous distribution of the hydride within the MOF host. Notably, the B-, N-, and Mg-edge XAS data confirm the coordination of Mg(II) to the N atoms of the chelating bipyridine groups. In situ 11B MAS NMR studies helped elucidate the reaction mechanism and revealed that complete hydrogen release from Mg(BH4)2 occurs as low as 200 °C. Sieverts and thermogravimetric measurements indicate an increase in the rate of hydrogen release, with the onset of hydrogen desorption as low as 120 °C, which is approximately 150 °C lower than that of the bulk material. Furthermore, density functional theory calculations support the improved dehydrogenation properties and confirm the drastically lower activation energy for B-H bond dissociation.

Nanoconfinement, Metal Hydrides, Metal-Organic Fra↗