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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluation of hydrograph separation techniques with uncertain end-member composition

Hydrograph separation is one of many approaches used to analyse shifts in source water contributions to stream flow resulting from climate change in remote watersheds. Understanding these shifts is vital, as shifts in source water contributions to a stream can shape water management decisions. Because remote watersheds are often inaccessible and have poorly characterized contributing water sources, or end-members, it is critical to understand the implications of using different hydrograph separation techniques in these data-limited environments. To explore the uncertainty associated with different techniques, results from two hydrograph separation techniques, mass balance and principle component analysis, were compared using 3 years of aqueous geochemical data from the East River watershed located in the Elk Mountains of Central Colorado. Solute concentrations of the end-members were characterized by both a limited set of direct chemical measurements of different sources and detailed seasonal instream chemistry to examine the influences of uncertain end-member compositions in a data-limited environment. Annual volumetric end-member contributions to stream flow had relatively good agreement across separation techniques. Large variations in time were observed in the hydrograph separations, depending on the end-member type, and estimated flow contributions varied between the selected solutes. End-member concentrations characterized by stream chemistry showed several limitations including a reduced number of distinguishable end-members and differences in timing of flow contributions. Here the results highlight the benefits of using multiple hydrograph separation techniques by providing a ‘weight-of-evidence’ approach to environments with limited end-member concentration data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Ferromagnetism with in-plane magnetization, Dirac spin-gapless semiconducting properties, and tunable topological states in two-dimensional rare-earth metal dinitrides

Since the successful synthesis of bulk single crystals MoN 2 and ReN 2 , which have a layered structure, transition-metal dinitrides have attracted considerable attention in recent years. Here, we focus on rare-earth metal (Rem) elements, and propose seven stable Rem dinitride monolayers with a 1T structure, namely, 1T-RemN 2 . We use first-principles calculations, and find that these monolayers have a ferromagnetic ground state with in-plane magnetization. Without spin-orbit coupling (SOC), the band structures are spin-polarized with Dirac points at the Fermi level. Remarkably, the 1T-LuN 2 monolayer exhibits an isotropic magnetocrystalline anisotropy energy in the xy plane with in-plane magnetization, indicating easy tunability of the magnetization direction. Additionally, when rotating the magnetization vector in the xy plane, we propose a model that accurately describes the variation of the SOC band gap and the two possible topological states (Weyl-like semimetal and Chern insulator states) whose properties are tunable. The Weyl-like semimetal state is a critical point between the two Chern insulator states with opposite sign of the Chern numbers (±1). The nontrivial band gap (up to 60.3 meV) and the Weyl-like semimetal state are promising for applications in spintronic devices.

2-dimensional systems↗
DOE OSTI2020

First-principles calculation of spin and orbital contributions to magnetically ordered moments in Sr 2 IrO 4

Here, we show how an accurate first-principles treatment of the canted-anti-ferromagnetic ground state of Sr 2 IrO 4 , a prototypical 5d correlated spin-orbit coupled material, can be obtained without invoking any free parameters, such as the Hubbard $\textit{U}$ or tuning the spin-orbit coupling strength. Our theoretically predicted iridium magnetic moment of 0.250$μ_B$, canted by 12.6° off the $\textit{a}$ axis, is in accord with experimental results. By resolving the magnetic moments into their spin and orbital components, we show that our theoretically obtained variation of the magnetic scattering amplitude $\langle M_m \rangle$ as a function of the polarization angle is consistent with recent nonresonant magnetic x-ray scattering measurements. The computed value of the band gap (55 meV) is also in line with the corresponding experimental values. A comparison of the band structure to that of the cuprates suggests the presence of incommensurate charge-density wave phases in Sr 2 IrO 4 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Vacancy-driven variations in the phonon density of states of fast neutron irradiated nuclear graphite

Research examining radiation damage and its effects in graphite began in the 1940’s during the development of moderated nuclear reactors. Interest in this topic is expanding because of emerging applications associated with fullerenes and carbon nanostructures as well as its long-standing use as a fission moderator. In this work, we report the measurements of the full phonon density of states of irradiated nuclear graphite using inelastic neutron scattering experiments at room temperature. The samples were previously exposed to different levels of neutron doses and irradiation temperatures. The phonon density of states of perfect and defected graphite supercells including different configurations of vacancies and interstitials were calculated using first-principles direct method. Despite high neutron irradiation doses, the scattering measurements show that the induced damage is localized, and the layered structure is preserved. In conclusion, a comparison of the measured phonon densities of states of irradiated samples with those calculated of defected supercells indicates that the main changes observed are mainly attributed to formation of vacancies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Revealing the Chemical Bonding in Adatom Arrays via Machine Learning of Hyperspectral Scanning Tunneling Spectroscopy Data

The adatom arrays on surfaces offer an ideal playground to explore the mechanisms of chemical bonding via changes in the local electronic tunneling spectra. While this information is readily available in hyperspectral scanning tunneling spectroscopy data, its analysis has been considerably impeded by a lack of suitable analytical tools. Here we develop a machine learning based workflow combining supervised feature identification in the spatial domain and unsupervised clustering in the energy domain to reveal the details of structure-dependent changes of the electronic structure in adatom arrays on the Co 3 Sn 2 S 2 cleaved surface. This approach, in combination with first-principles calculations, provides insight for using artificial neural networks to detect adatoms and classifies each based on their local neighborhood comprised of other adatoms. These structurally classified adatoms are further spectrally deconvolved. The unexpected inhomogeneity of electronic structures among adatoms in similar configurations is unveiled using this method, suggesting there is not a single atomic species of adatoms, but rather multiple types of adatoms on the Co 3 Sn 2 S 2 surface. This is further supported by a slight contrast difference in the images (or slight size variation) of the topography of the adatoms.

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

Optimizing the Synthetic Potential of O 2 : Implications of Overpotential in Homogeneous Aerobic Oxidation Catalysis

Molecular oxygen is the quintessential oxidant for organic chemical synthesis, but many challenges continue to limit its utility and breadth of applications. Extensive historical research has focused on overcoming kinetic challenges presented by the ground-state-triplet electronic structure of O 2 and the various reactivity and selectivity challenges associated with reactive oxygen species derived from O 2 reduction. This Perspective will analyze thermodynamic principles underlying catalytic aerobic oxidation reactions, borrowing concepts from the study of the oxygen reduction reaction (ORR) in fuel cells. This analysis is especially important for "oxidase"-type liquid-phase catalytic aerobic oxidation reactions, which proceed by a mechanism that couples two sequential redox half-reactions: (1) substrate oxidation, and (2) oxygen reduction, typically affording H 2 O 2 or H 2 O. The catalysts for these reactions feature redox potentials that lie between the potentials associated with the substrate oxidation and oxygen reduction reactions, and changes in the catalyst potential lead to variations in effective overpotentials for the two half reactions. Catalysts that operate at low ORR overpotential retain more thermodynamic driving force for the substrate oxidation step, enabling O 2 to be used in more challenging oxidations. While catalysts that operate at high ORR overpotential have less driving force available for substrate oxidation, they often exhibit different or improved chemoselectivity relative to the high-potential catalysts. The concepts are elaborated in a series of case studies to highlight their implications for chemical synthesis. Examples include comparisons of (a) NO x /oxoammonium and Cu/nitroxyl catalysts, (b) high-potential quinones and amine oxidase biomimetic quinones, and (c) Pd aerobic oxidation catalysts, with or without NO x cocatalysts. In addition, we show how reductive activation of O 2 provides a means to access potentials not accessible with conventional oxidase-type mechanisms. Altogether, this analysis highlights the central role of catalyst overpotential in guiding the development of aerobic oxidation reactions.

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

Vibrational properties and thermal transport in quaternary chalcogenides: The case of Te-based compositions

Vibrational thermal properties of CuZn 2 InTe 4 , AgZn 2 InTe 4 , and Cu 2 CdSnTe 4 , derived from binary II-VI zinc-blendes, are reported based on first-principles calculations. While the chalcogenide atoms in these materials have the same lattice positions, the cation atom arrangements vary, resulting in different crystal symmetries and subsequent properties. The compositional differences have important effects on the vibrational thermal characteristics of the studied materials, which demonstrate that low-frequency optical phonons hybridize with acoustic phonons and lead to enhanced phonon-phonon scattering and low lattice thermal conductivities. The phonon density of states, mode Grüneisen parameters, and phonon scattering rates are also calculated, enabling deeper insight into the microscopic thermal conduction processes in these materials. Compositional variations drive differences among the three materials considered here; nonetheless, their structural similarities and generally low thermal conductivities (0.5–4 W/m K at room temperature) suggest that other similar II-VI zinc-blende derived materials will also exhibit similarly low values, as also corroborated by experimental data. Finally, this, combined with the versatility in designing a variety of motifs on the overall structure, makes quaternary chalcogenides interesting for thermal management and energy conversion applications that require low thermal conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Ionic conductive polymers as artificial solid electrolyte interphase films in Li metal batteries – A review

Lithium (Li) metal has been considered as the ultimate anode material for next-generation rechargeable batteries due to its ultra-high theoretical specific capacity (3860 mAh g -1 ) and the lowest reduction voltage (-3.04 V vs the standard hydrogen electrode). However, the dendritic Li formation, uncontrolled interfacial reactions, and huge volume variations lead to unstable solid electrolyte interphase (SEI) layer, low Coulombic efficiency and hence short cycling lifetime. Designing artificial solid electrolyte interphase (artificial SEI) films on the Li metal electrode exhibits great potential to solve the aforementioned problems and enable Li–metal batteries with prolonged lifetime. Polymer materials with good ionic conductivity, superior processability and high flexibility are considered as ideal artificial SEI film materials. In this review, according to the ionic conductive groups, recent advances in polymeric artificial SEI films are summarized to afford a deep understanding of Li ion plating/stripping behavior and present design principles of high-performance artificial SEI films in achieving stable Li metal electrodes. Perspectives regarding to the future research directions of polymeric artificial SEI films for Li–metal electrode are also discussed. The insights and design principles of polymeric artificial SEI films gained in the current review will be definitely useful in achieving the Li–metal batteries with improved energy density, high safety and long cycling lifetime toward next-generation energy storage devices.

25 ENERGY STORAGE↗
DOE OSTI2024

Semicoherent symmetric quantum processes: Theory and applications

Discovering pragmatic and efficient approaches to construct ε-approximations of quantum operators such as real (imaginary) time-evolution propagators in terms of the basic quantum operations (gates) is challenging. Prior ε-approximations are invaluable, in that they enable the compilation of classical and quantum algorithm modeling of, e.g., dynamical and thermodynamic quantum properties. In parallel, symmetries are powerful tools concisely describing the fundamental laws of nature; the symmetric underpinnings of physical laws have consistently provided profound insights and substantially increased predictive power. In this work, we consider the interplay between the ε-approximate processes and the exact symmetries in a semicoherent context—where measurements occur at each logical clock cycle. Here we draw inspiration from Pascual Jordan's groundbreaking formulation of nonassociative, but commutative, symmetric algebraic form. Our symmetrized formalism is then applied in various domains such as quantum random walks, real-time evolutions, variational algorithm ansatzes, and efficient entanglement verification. Our work paves the way for a deeper understanding and greater appreciation of how symmetries can be used to control quantum dynamics in settings where coherence is a limited resource.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

ABC -Auxetics: An Implicit Design Approach for Negative Poisson's Ratio Materials

A novel methodology is introduced for designing auxetic (negative Poisson's ratio) structures based on topological principles and is demonstrated by investigating a new class of auxetics based on two-dimensional (2D) textile weave patterns. Conventional methodology for designing auxetic materials typically involves determining a single deformable block (a unit cell) of material whose shape results in auxetic behavior. Consequently, patterning such a unit cell in a 2D (or 3D) domain results in a larger structure that exhibits overall auxetic behavior. Such an approach naturally relies on some prior intuition and experience regarding which unit cells may be auxetic. Second, tuning the properties of the resulting structures is typically limited to parametric variations of the geometry of a specific type of unit cell. Thus, most of the currently known auxetic structures belong to a selected few classes of unit cell geometries that are explicitly defined in accordance with a specified topological (i.e., grid structure). Herein, a new class of auxetic structures is demonstrated that, while periodic, can be generated implicitly, i.e., without reference to a specific unit cell design. The approach leverages weave-based parameters (A–B–C), resulting in a rich design space for auxetics that is previously unexplored.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Applying equity principles leads to higher carbon removal obligations in Canada

Despite net-zero pledges, consensus on national responsibilities for carbon dioxide removal (CDR) strategies is lacking. Here, we use integrated assessment modeling to examine equity-informed estimates of Canada’s remaining carbon budgets, exploring CDR’s role at net-zero and beyond. Gigaton-scale CDR efforts post-2050 are needed to address Canada’s carbon debt under various burden-sharing principles. Cumulative negative emissions (2050-2100) could increase from 7.5 GtCO 2 in the Net-Zero scenario to 20.3 GtCO 2 in equity-informed scenarios. By 2100, a CDR portfolio, including bioenergy with carbon capture and storage, direct air capture, and enhanced weathering could contribute up to ~500 MtCO 2 /year of removals. The projected average CDR growth rates, 2.8%-16%/year, align with the historical adoption rates of ammonia synthesis and biomass consumption in Canada, underscoring the importance of drawing lessons from past successes. Socio-economic and technological sensitivity analysis highlights that, despite variations in the role of individual CDR technologies, CDR remains essential for Canada’s post-net-zero commitments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Improving dynamic collision frequencies: Impacts on dynamic structure factors and stopping powers in warm dense matter

Simulations and diagnostics of high-energy-density plasmas and warm dense matter rely on models of material response properties, both static and dynamic (frequency-dependent). Here, in this work, we systematically investigate variations in dynamic electron–ion collision frequencies ν(ω) in warm dense matter using data from a self-consistent-field average-atom model. We show that including the full quantum density of states, strong collisions, and inelastic collisions lead to significant changes in ν(ω). These changes result in red shifts and broadening of the plasmon peak in the dynamic structure factor, an effect observable in x-ray Thomson scattering spectra, and modify stopping powers around the Bragg peak. These changes improve the agreement of computationally efficient average-atom models with first-principles time-dependent density functional theory in warm dense aluminum, carbon, and deuterium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Fast and accurate simulations of calorimeter showers with normalizing flows

In this study, we introduce caloflow, a fast detector simulation framework based on normalizing flows. For the first time, we demonstrate that normalizing flows can reproduce many-channel calorimeter showers with extremely high fidelity, providing a fresh alternative to computationally expensive geant4 simulations, as well as other state-of-the-art fast simulation frameworks based on generative adversarial networks (GANs) or variational autoencoders (VAEs). In addition to the usual histograms of physical features and images of calorimeter showers, we introduce a new metric for judging the quality of generative modeling: the performance of a classifier trained to differentiate real from generated images. We show that GAN-generated images can be identified by the classifier with nearly 100% accuracy, while images generated from caloflow are better able to fool the classifier. More broadly, normalizing flows offer several advantages compared to other state-of-the-art approaches (GANs and VAEs), including tractable likelihoods, stable and convergent training, and principled model selection. Normalizing flows also provide a bijective mapping between data and the latent space, which could have other applications beyond simulation, for example, to detector unfolding.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Multimodal Approach Reveals the Symmetry-Breaking Pathway to the Broken Helix in EuIn 2 ⁢As 2

Understanding and manipulating emergent phases, which are themes at the forefront of quantum-materials research, rely on identifying their underlying symmetries. This general principle has been particularly prominent in materials with coupled electronic and magnetic degrees of freedom, in which magnetic order influences the electronic band structure and can lead to exotic topological effects. However, identifying symmetry of a magnetically ordered phase can pose a challenge, particularly in the presence of small domains. Here we introduce a multimodal approach for determining magnetic structures, which combines symmetry-sensitive optical probes, scattering, and group-theoretical analysis. We apply it to EuIn 2 ⁢As 2 , a material that has received attention as a candidate axion insulator. While first-principles calculations predict this state on the assumption of a simple collinear antiferromagnetic structure, subsequent neutron-scattering measurements reveal a much more intricate magnetic ground state characterized by two coexisting magnetic wave vectors reached by successive thermal phase transitions. The proposed high- and low-temperature phases are a spin helix and a state with interpenetrating helical and Néel antiferromagnetic order termed a “broken helix,” respectively. Employing a multimodal approach, we identify the magnetic structure associated with these two phases of EuIn 2 ⁢As 2 . We find that the higher-temperature phase is characterized by a variation of the magnetic moment amplitude from layer to layer, with the moment vanishing entirely in every third Eu layer. The lower-temperature structure is similar to the broken helix, with one important difference: Because of local strain, the relative orientation of the magnetic structure and the lattice is not fixed. Consequently, the symmetry required to protect the axion phase is not generically protected in EuIn 2 ⁢As 2 , but we show that it can be restored if the magnetic structure is tuned with uniaxial strain. Finally, we present a spin Hamiltonian that identifies the spin interactions that account for the complex magnetic order in EuIn 2 ⁢As 2 . Our work highlights the importance of a multimodal approach in determining the symmetry of complex order parameters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Using metacommunity ecology to understand environmental metabolomes

Abstract Environmental metabolomes are fundamentally coupled to microbially-linked biogeochemical processes within ecosystems. However, significant gaps exist in our understanding of their spatiotemporal organization, limiting our ability to uncover transferrable principles and predict ecosystem function. We propose that a theoretical paradigm, which integrates concepts from metacommunity ecology, is necessary to reveal underlying mechanisms governing metabolomes. We call this synthesis between ecology and metabolomics ‘meta-metabolome ecology’ and demonstrate its utility using a mass spectrometry dataset. We developed three relational metabolite dendrograms using molecular properties and putative biochemical transformations and performed ecological null modeling. Based upon null modeling results, we show that stochastic processes drove molecular properties while biochemical transformations were structured deterministically. We further suggest that potentially biochemically active metabolites were more deterministically assembled than less active metabolites. Understanding variation in the influences of stochasticity and determinism provides a way to focus attention on which meta-metabolomes and which parts of meta-metabolomes are most likely to be important to consider in mechanistic models. We propose that this paradigm will allow researchers to study the connections between ecological systems and their molecular processes in previously inaccessible detail.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Unfolding of the Villin Headpiece Domain: Revealing Structural Heterogeneity with Time‐Resolved X‐Ray Solution Scattering and Markov State Modeling

Understanding protein folding pathways is crucial to deciphering the principles of protein structure and function. Here, the unfolding dynamics of the 35‐residue villin headpiece (HP35) and a norleucine‐substituted variant (2F4K) using a combination of experimental and computational techniques is investigated. Time‐resolved X‐ray solution scattering coupled with equilibrium molecular dynamics simulations and Markov state modeling reveals distinct unfolding mechanisms between the two variants: HP35 and 2F4K. Specifically, HP35 exhibits a two‐state unfolding process, whereas an intermediate state is identified for the 2F4K mutant. A Markov state model constructed from simulations is used to map atomic‐level transitions to experimental observations, providing insights into the role of sequence variations in modulating folding pathways. The findings underscore the importance of integrating experimental and computational approaches to unravel protein unfolding mechanisms between heterogenous structural ensembles.

Nijhawan, Adam K. [Department of Chemistry Northwe↗
DOE OSTI2025

Compressing Hamiltonians with ab initio downfolding for simulating strongly-correlated materials on quantum computers

The accurate first-principles description of strongly correlated materials is an important and challenging problem in condensed matter physics. Ab initio downfolding has emerged as a way of deriving compressed many-body Hamiltonians that maintain the essential physics of strongly correlated materials. The solution of these material-specific models is still exponentially difficult to generate on classical computers, but quantum algorithms allow for a significant speed-up in obtaining the ground states of these compressed Hamiltonians. Here, we demonstrate that using quantum algorithms to obtain the properties of downfolded Hamiltonians can indeed yield high-fidelity solutions. By combining ab initio downfolding and variational quantum eigensolvers, we correctly predict the antiferromagnetic state of one-dimensional cuprate Ca 2 Cu O 3 , the excitonic ground state of monolayer W Te 2 , and the charge-ordered state of correlated metal Sr VO 3 . Numerical simulations using a classical tensor network implementation of variational quantum eigensolvers allow us to simulate large models with up to 54 qubits and encompassing up to four bands in the correlated subspace, which is indicative of the complexity that our framework can address. Through these methods we demonstrate the potential of classical preoptimization and downfolding techniques for enabling efficient materials simulation using quantum algorithms.

Alvertis, Antonios M. [NASA, Ames; LBNL, Berkeley]↗
DOE OSTI2023

Data-Driven Refinement of Electronic Energies from Two-Electron Reduced-Density-Matrix Theory

The exponential computational cost of describing strongly correlated electrons can be mitigated by adopting a reduced-density-matrix (RDM)-based description of the electronic structure. While variational two-electron RDM (v2RDM) methods can enable large-scale calculations on such systems, the quality of the solution is limited by the fact that only a subset of known necessary N-representability constraints can be applied to the 2RDM in practical calculations. Here, we demonstrate that violations of partial three-particle (T1 and T2) N-representability conditions, which can be evaluated with knowledge of only the 2RDM, can serve as physics-based features in a machine-learning (ML) protocol for improving energies from v2RDM calculations that consider only two-particle (PQG) conditions. Proof-of-principle calculations demonstrate that the model yields substantially improved energies, relative to reference values from configuration-interaction-based calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗