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All sources NASA NTRS DOE OSTI

DOE OSTI2022

All Solid-State Li/LLZO/LCO Battery Enabled by Alumina Interfacial Coating

Li 7 La 3 Zr 2 O 12 (LLZO) garnet-type lithium-ion conductors are being investigated as a promising solid electrolyte for solid-state lithium batteries. To enable a functional all-solid-state configuration intensive investigations are needed to reduce the cathode/electrolyte interfacial resistance which contributes the most to cell performance loss. Among the commercial cathode materials investigated so far, LiCoO 2 (LCO) is one of the most stable with garnet electrolytes as only a superficial reaction has been detected between the two materials. However, even this minor reaction would block the Li-ion transport through the interface, resulting in deteriorated cell performance. In this work, we demonstrate that a thin aluminum oxide layer (5 nm) can be an effective interlayer to impede the formation of a harmful interphase and enable facile Li-ion transfer between LCO and the LLZO garnet. Room-temperature-sputtered LCO thin films were employed to form an interface with the garnet electrolyte and annealed at 800 °C to reveal the effect of the interfacial reaction on the Li-ion transfer across the interface. An aluminum oxide layer was then introduced between LCO and the garnet electrolyte by sputtering a metallic aluminum layer which is then annealed together with the upper LCO layer in oxygen, or by direct atomic layer deposition of the oxide. Compared to the LCO/LLZO/Li cells without an aluminum oxide interlayer, those with the interlayer exhibited improved performance, i.e., a stable discharge capacity of up to 90 mAh/(g LCO) at a C/10 rate, a rate capability up to 1.68C and a stable galvanostatic cycling at 0.1C for over 100 cycles with a discharge capacity fade rate of 0.15% per cycle. It was determined that aluminum diffused into the LCO layer after preventing the initial detrimental reaction between LCO and the LLZO garnet from happening during high temperature annealing, suggesting that the coating does not have to remain a physically blocking layer during cycling to function.

Electrochemistry↗

DOE OSTI2021

Artificial intelligence “sees” split electrons

Chemical bonds between atoms are stabilized by the exchange-correlation (xc) energy, a quantum-mechanical effect in which “social distancing” by electrons lowers their electrostatic repulsion energy. Kohn-Sham density functional theory (DFT) states that the electron density determines this xc energy, but the density functional must be approximated. Furthermore, this is usually done by satisfying exact constraints of the exact functional (making the approximation predictive), by fitting to data (making it interpolative), or both. Two exact constraints—the ensemble-based piecewise linear variation of the total energy with respect to fractional electron number and fractional electron z-component of spin —require hard-to-control nonlocality. On page 1385 of this issue, Kirkpatrick et al. have taken a big step toward more accurate predictions for chemistry through the machine learning of molecular data plus the fractional charge and spin constraints, expressed as data that a machine can learn.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2020

New Polarizability Functions for Calculating Atomic Hydrogen S State Spectral Lines in Exact Agreement with NIST Measurements

This paper presents a new approach to calculating atomic hydrogen energy levels which is simple, fast and accurate. One advantage of this new approach is the ability to explicitly incorporate the polarizability resulting from a scattering event between a hydrogen atom and a photon. The polarizability effect is small but significant, producing exact S state spectral energies. The general calculational approach is applicable to both atomic hydrogen and multi-electron energy levels. Although motivated by the multi-electron case for chemistry applications, the focus of this paper will be calculations that are specific to atomic hydrogen which include the polarizability.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

Energetic Basis and Design of Enzyme Function Demonstrated Using GFP, an Excited-State Enzyme

We report the past decades have witnessed an explosion of de novo protein designs with a remarkable range of scaffolds. It remains challenging, however, to design catalytic functions that are competitive with naturally occurring counterparts as well as biomimetic or nonbiological catalysts. Although directed evolution often offers efficient solutions, the fitness landscape remains opaque. Green fluorescent protein (GFP), which has revolutionized biological imaging and assays, is one of the most redesigned proteins. While not an enzyme in the conventional sense, GFPs feature competing excited-state decay pathways with the same steric and electrostatic origins as conventional ground-state catalysts, and they exert exquisite control over multiple reaction outcomes through the same principles. Thus, GFP is an “excited-state enzyme”. Herein we show that rationally designed mutants and hybrids that contain environmental mutations and substituted chromophores provide the basis for a quantitative model and prediction that describes the influence of sterics and electrostatics on excited-state catalysis of GFPs. As both perturbations can selectively bias photoisomerization pathways, GFPs with fluorescence quantum yields (FQYs) and photoswitching characteristics tailored for specific applications could be predicted and then demonstrated. The underlying energetic landscape, readily accessible via spectroscopy for GFPs, offers an important missing link in the design of protein function that is generalizable to catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Chronic obstructive pulmonary disease among former United States Department of Energy workers: comorbidities and lung function changes

Chronic Obstructive Pulmonary Disease (COPD) is a major cause of morbidity and mortality in the United States and is frequently associated with multiple comorbidities which lead to poor COPD outcomes in the general population. However, little is known regarding COPD comorbidities in occupational cohorts whose exposure experiences could result in differences in comorbidities compared to the general population. These differences may also be important for assessing COPD outcomes such as lung function changes or decline. Therefore, the objectives of this study were to: (1) identify and describe clusters of COPD comorbidities among Department of Energy (DOE) former workers; (2) assess if the attributes of the identified clusters differ from those identified among the general population based on the published literature, and (3) identify predictors of lung function changes and decline among DOE former workers.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Variational Neural-Network Ansatz for Continuum Quantum Field Theory

Physicists dating back to Feynman have lamented the difficulties of applying the variational principle to quantum field theories. In nonrelativistic quantum field theories, the challenge is to parametrize and optimize over the infinitely many n-particle wave functions comprising the state’s Fock-space representation. Here we approach this problem by introducing neural-network quantum field states, a deep learning ansatz that enables application of the variational principle to nonrelativistic quantum field theories in the continuum. Our ansatz uses the Deep Sets neural network architecture to simultaneously parametrize all of the n-particle wave functions comprising a quantum field state. We employ our ansatz to approximate ground states of various field theories, including an inhomogeneous system and a system with long-range interactions, thus demonstrating a powerful new tool for probing quantum field theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Effects of Composition and Oxidation States on the Structures of Chromium-Containing Sodium Silicate Glasses: Molecular Dynamics Simulations using Machine Learning Interatomic Potentials

Chromium represents a significant challenge for the vitrification of high-level nuclear waste into silicate and borosilicate glasses due to its low solubility and variable oxidation states, which can limit the waste loading due to promotion of crystallization or phase separation during processing. In this study, we modeled chromium containing silicate glasses using molecular dynamics simulations with three machine learning interatomic potentials (MLIPs), MACE, CHGNet, and PFP were employed, to gain insights on glass composition and oxidation states on the structures of these glasses. One of the goals is to evaluate their ability of these MLIPs to accurately represent the general structure of silicate glasses and chromium local environments as a function of chromium oxidation states. Density Functional Theory (DFT) based calculations and experimental data such as neutron structure factors were used to validate the structural models. It was found that the foundation models of all three MLIPs are able to reproduce general structural features of the sodium silicate glass structure consistent with experimental and DFT data, but only CHGNet and PFP can accurately capture the oxidation states and local environment of chromium: tetrahedral for Cr6+ and octahedral for Cr3+. Furthermore, we studied the effect of varying Cr3+/ Cr6+ (Cr3+/Crtotal) ratio and total chromium content using PFP. Our results show that Cr6+ enhances network polymerization by reducing non-bridging oxygens through Na? charge compensation required due to the formation of chromate (CrO42-) species, while Cr³? acts as a network modifier that disrupts connectivity. System size effects on the structural characteristics and chromium environments were also tested using the PFP potential. This work highlights the importance of careful validation on the precision, transferability, and potential of MLIPs for modeling glasses containing transition metal elements that can exist in multiple oxidation states. It is also encouraging to see the foundational models are all three MLFFs are able to reproduce the basic sodium silicate glass structures, while suggesting additional training or refining is needed to improve the description of more complex systems containing transition metals.

Puga, Christina L.↗

DOE OSTI2020

Theoretical phase diagram of two-component composite fermions in double-layer graphene

Theory predicts that double layer systems realize “two-component composite fermions,” which are formed when electrons capture both intra- and inter-layer vortices, to produce a wide variety of new strongly correlated liquid and crystal states as a function of the layer separation. Recent experiments in double layer graphene have revealed a large number of layer-correlated fractional quantum Hall states in the lowest Landau level, many of which have not been studied quantitatively in previous theoretical works. We consider the competition between various liquid and crystal states at several of these filling factors (specifically, the states at total filling factors ν = 3/7, 4/9, 6/11, 4/7, 3/5, 2/3, and 4/5) to determine the theoretical phase diagram as a function of the layer separation. We compare our results with experiments and identify various observed states. In particular, we show that at small layer separations the states at total fillings ν = 3/7 and ν = 3/5 are partially pseudospin polarized, where pseudospin refers to the layer index. For certain fractions, such as ν = 3/7, interlayer correlations are predicted to survive to surprisingly large interlayer separations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Tetraquark Production by Intrinsic Charm

A number of new four-quark states containing from one to four c or ̅c quarks have been observed recently. Many of these new states have been discovered at the LHC. The production of these states via intrinsic charm in the proton is investigated. The tetraquark masses obtained in this approach, agree well with the measured masses. These calculations can provide some insight into the nature of the tetraquark candidates, whether as a bound meson pair or as a looser configuration of four individual partons which can influence their interactions in nuclear medium, such as in heavy-ion collisions. The kinematic distributions of these states as a function of y and pT are also studied. The possible cross sections for these states are also considered.

Vogt, Ramona [Lawrence Livermore National Laborato↗

DOE OSTI2024

Coexistence of low and high spin states in La 18 Co 28 Pb 3

The electronic structure and magnetic properties of a newly predicted stable ternary compound La 18 ⁢Co 28 ⁢Pb 3 are studied using electronic structure analysis. The ground state of this compound is ferromagnetic, with three positions of nonequivalent magnetic Co atoms. A strong dependence of magnetic properties on volume shows that this system is situated near the point of magnetic instability. The coexistence of high- and low-spin ferromagnetic states as a function of volume near equilibrium was discovered. A corresponding spin tunneling splitting was estimated. The stability of the theoretically predicted magnetic ground state was tested by varying the Hubbard parameter. The thermal spin fluctuations were added to estimate the paramagnetic moment and a Curie temperature. Finally, the necessity of experimental verification of the obtained results is emphasized.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

High Speed Medium Voltage CHP System with Advanced Grid Support

The project was a collaboration between Clemson University and TECO Westinghouse Motor Company. The goal of the project was to develop a medium voltage commercial grid-tied system with advanced grid support functions. Current state-of-the-art in medium voltage, multi-megawatt power electronic systems do not support advanced grid functions, traditionally due to power electronic limitations and required applications. The developed system is capable of interacting with the power system at the distribution level to efficiently integrate gas turbine generation systems or any other ac generation system with up to 20MWe of power production capacity. This project demonstrated a high level of technical readiness of the 1MW, 500Hz, 15000 RPM high frequency Combined Heat and Power (CHP) generator and electric machine system, utilizing advanced grid support functions required by IEEE Std. 1547-2018.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Tetraquarks from intrinsic heavy quarks

A number of new tetraquark candidate states containing from one to four charm or anticharm quarks have been observed recently. Many of these new states have been discovered at the LHC. The production of these states via intrinsic charm in the proton is investigated. The tetraquark masses obtained in this approach, while dependent on the internal transverse momenta of the partons in the state, are shown to agree well with the measured masses. These calculations can provide some insight into the nature of the tetraquark candidates, whether as a bound meson pair or as a looser configuration of four individual partons. The kinematic distributions of these states as a function of rapidity and transverse momentum are also studied. The possible cross sections for these states are finally considered, with a comparison to the 𝑋⁡(3872) 𝑝 𝑇 distributions from 𝑝 +𝑝 collisions at $\sqrt{s}$ =13 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

An Observationally Trained Markov Model for MJO Propagation

A Markovian stochastic model is developed for studying the propagation of the Madden-Julian Oscillation (MJO). This model represents the daily changes in real time multivariate MJO (RMM) indices as random functions of their current state and background conditions. The probability distribution function of the RMM changes is obtained using a machine learning algorithm trained to maximize MJO forecast skills using observed daily indices of RMM and different modes of variability. Skillful forecasts are obtained for lead times between 8 and 27 days. Large ensemble simulations by the stochastic model show that with monsoonal changes in the background state, MJO propagation across the Maritime Continent (MC) is most likely to be disrupted in boreal spring and summer when MJO events propagate from favorable conditions over the Indian Ocean to unfavorable ones over the MC, and predictability is higher during spring and summer when MJO activity is away from the MC region.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Using intrusive approaches as a step towards accounting for stochasticity in wind turbine design

Current wind turbine design methods require tens of thousands of time-domain simulations and use different random seeds to account for the stochasticity of the environmental conditions. The account of stochasticity is nonintrusive because the sampling method calls a deterministic model multiple times without changing its underlying equations. In this work, we investigate and demonstrate using simple proof of concepts how intrusive approaches can be used to directly account for stochasticity in the equations representing a mechanical system. Our long term goal is to apply such methodology to the design of wind turbines without requiring an excessive number of simulations. Intrusive methods manipulate stochastic variables directly to provide the probability density functions (PDFs) of the states and outputs at any time as functions of the PDFs of the inputs. We illustrate how different methods can be used with a reduced-order model of a wind turbine with one degree of freedom and for linear and nonlinear models. We discuss how the methods can be extended and what it will take to apply them to a level of fidelity similar to current state-of-the-art wind turbine design tools.

17 WIND ENERGY↗

DOE OSTI2025

Forecasting constraints on the high-z IGM thermal state from the Lyman-α forest flux autocorrelation function

ABSTRACT The autocorrelation function of the Lyman-$\alpha$ (Ly $\alpha$) forest flux from high-z quasars probes the small-scale structure of the intergalactic medium (IGM). The thermal state of the IGM, determined by the physics of reionization, sets the small-scale power observed in the Ly $\alpha$ forest. To explore the sensitivity of the autocorrelation function to the IGM’s thermal state, we compute the autocorrelation function from a cosmological hydrodynamical simulation with an instantaneous reionization model and 135 post-processed thermal states. Using mock data sets of 20 quasars, we forecast constraints on $T_0$ and $\gamma$, which characterize the post-processed IGM thermal state, at $5.4 \le z \le 6$. While this model simplifies the IGM’s thermal state, it serves as a key first step in assessing future observational prospects. We also perform an inference test on mocks and re-weight out posterior distributions to guarantee that they exhibit statistically correct behaviour. At $z = 5.4$, we find that an idealized data set constrains $T_0$ to 59 per cent and $\gamma$ to 16 per cent at the 1$\sigma$ equivalent confidence level. To explore more realistic, non-instantaneous reionization scenarios, we analyse four models combining temperature and ultraviolet background (UVB) fluctuations at $z = 5.8$. We find that mock data generated from a model with both temperature and UVB fluctuations can rule out a model with only temperature fluctuations at the $> 1\sigma$ level 73.9 per cent of the time.

Wolfson, Molly↗

DOE OSTI2024

Monitoring Redox Processes in Lithium-Ion Batteries by Laboratory-Scale Operando X-ray Emission Spectroscopy

Tracking changes in the chemical state of transition metals in alkali-ion batteries is crucial to understanding the redox chemistry during operation. X-ray absorption spectroscopy (XAS) is often used to follow the chemistry through observed changes in the chemical state and local atomic structure as a function of the state-of-charge (SoC) in batteries. In this study, we utilize an operando X-ray emission spectroscopy (XES) method to observe changes in the chemical state of active elements in batteries during operation. Operando XES and XAS were compared by using a laboratory-scale setup for four different battery systems: LiCoO 2 (LCO), Li[Ni 1/3 Co 1/3 Mn 1/3 ]O 2 (NMC111), Li[Ni 0.8 Co 0.1 Mn 0.1 ]O 2 (NMC811), and LiFePO 4 (LFP) under a constant current charging the battery in 10 h (C/10 charge rate). We show that XES, despite narrower chemical shifts in comparison to XAS, allows us to fingerprint the battery SOC in real time. We further demonstrate that XES can be used to track the change in net spin of the probed atoms by analyzing changes in the emission peak shape. As a test case, the connection between net spin and the local chemical and structural environment was investigated by using XES and XAS in the case of electrochemically delithiated LCO in the range of 2–10% lithium removal.

25 ENERGY STORAGE↗

DOE OSTI2024

Triplet Management at Ligand-Perovskite Interface to Enhanced Photovoltaics Performance

Aromatic organic molecules are widely used as passivators in perovskite solar cells (PSCs). Efforts have been devoted to improving the energy alignments, band edge states, and defect passivation functionalities. However, potential energy loss through triplet states in such conjugated molecules has not been investigated in the past. Here, we report the observation of charge transfer from FAPbI 3 to the triplet state of a pyrene (Pyr)-based cationic ligand. Such a potential loss channel can be suppressed via delicate triplet management in polycyclic aromatic compounds. Interestingly, a subtle structural modification from Pyr to the triphenylene (TP) core gave rise to shallower triplets that prohibit electron transfer from perovskites. This strategy has led to TP-passivated PSCs achieving an enhanced power conversion efficiency (PCE) of 24.69% from 23.10% in Pyr-passivated counterparts. Moreover, the devices retained above 80% initial PCE after 4000 h of light soaking, which likely benefited from the reduced triplet electron trapping at the ligand-perovskite interface.

14 SOLAR ENERGY↗

DOE OSTI2022

Electronic structure of strongly correlated systems: recent developments in multiconfiguration pair-density functional theory and multiconfiguration nonclassical-energy functional theory

Strong electron correlation plays an important role in transition-metal and heavy-metal chemistry, magnetic molecules, bond breaking, biradicals, excited states, and many functional materials, but it provides a significant challenge for modern electronic structure theory. The treatment of strongly correlated systems usually requires a multireference method to adequately describe spin densities and near-degeneracy correlation. However, quantitative computation of dynamic correlation with multireference wave functions is often difficult or impractical. Multiconfiguration pair-density functional theory (MC-PDFT) provides a way to blend multiconfiguration wave function theory and density functional theory to quantitatively treat both near-degeneracy correlation and dynamic correlation in strongly correlated systems; it is more affordable than multireference perturbation theory, multireference configuration interaction, or multireference coupled cluster theory and more accurate for many properties than Kohn–Sham density functional theory. This perspective article provides a brief introduction to strongly correlated systems and previously reviewed progress on MC-PDFT followed by a discussion of several recent developments and applications of MC-PDFT and related methods, including localized-active-space MC-PDFT, generalized active-space MC-PDFT, density-matrix-renormalization-group MC-PDFT, hybrid MC-PDFT, multistate MC-PDFT, spin–orbit coupling, analytic gradients, and dipole moments. We also review the more recently introduced multiconfiguration nonclassical-energy functional theory (MC-NEFT), which is like MC-PDFT but allows for other ingredients in the nonclassical-energy functional. We discuss two new kinds of MC-NEFT methods, namely multiconfiguration density coherence functional theory and machine-learned functionals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗