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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 415 records · Page 23

A HPC Theory-Guided Machine Learning Cyberinfrastructure for Communicating Hydrometeorological Data Across Scales

High-resolution predictions of hydrometeorological variables are critical for supporting hydropower generation decisions and flood control at hydroelectric power plants. Traditional climate and hydrologic models rely on the numerical simulation of detailed physical processes. Therefore, running these simulations is time-, labor-, and computation-intensive. Improving the spatial and temporal resolution in these modeling outputs could lead to cubic increases in both the simulation time and computational demands, rendering high-resolution hydrometeorological predictions expensive and impractical. Many past studies apply the super resolution (SR) technique to downscale climate models using deep learners. However, deep learners are deemed “black-boxes,” as their derivation processes from low-resolution outputs to high-resolution outputs are often hidden. Their results are difficult for domain scientists to interpret and validate. Thus, there is a need for an exploratory machine learning approach that can partially integrate domain-specific theory and knowledge into the data-driven mapping process between simulation outputs of different spatial scales. The domain-specific theory and knowledge can be incorporated into the data model through an inductive approach in which process-related environmental variables are used and analyzed as key drivers (i.e., environmental surrogates) to reflect the complex physical processes. Many of these variables, such as land use land cover, soil types, topography, digital elevation, air temperature, and various watershed characteristics, can be directly measured through sensors or remote sensing techniques. Additionally, SR applications that can downscale hydrological and hydrodynamics models to efficiently produce high-resolution (1 m) flood depth grids are still rare. Since the flood depth grid can be used to support critical decisions for flood control operation at hydroelectric power plants, it is crucial to enable an SR-based capability for interpolating high-resolution flood inundation maps.

13 HYDRO ENERGY↗

Improved semiclassical model for real-time evaporation of matrix black holes

In this paper, we study real-time classical matrix mechanics of a simplified 2 × 2 matrix model inspired by the black hole evaporation problem. This is a step towards making a quantitative model of real-time evaporation of a black hole, which is realized as a bound state of D0-branes in string theory. The model we study is the reduction of Yang–Mills in 2 + 1 dimension to 0 + 1 dimensions, which has been corrected with an additional potential that can be interpreted as a zero-point energy for fermions. Our goal is to understand the lifetime of such a classical bound state object in the classical regime. To do so, we pay particular attention to when D-particles separate to check that the “off-diagonal modes” of the matrices become adiabatic and use that information to improve on existing models of evaporation. It turns out that the naive expectation value of the lifetime with the fermionic correction is infinite. This is a logarithmic divergence that arises from very large excursions in the separation between the branes near the threshold for classical evaporation. The adiabatic behavior lets us get some analytic control of the dynamics in this regime to get this estimate. This divergence is cutoff in the quantum theory due to quantization of the adiabatic parameter, resulting in a long lifetime of the bound state, with a parametric dependence of order log(1/ℏ).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Density functional theory-based surrogate kinetic models for heterogeneous reactions of hydrocarbon intermediates on silicon carbide

The increasing demand for high-performance materials in advanced technologies highlights the importance of achieving a fundamental understanding and potential control of silicon carbide (SiC) deposition processes. However, existing models often lack sufficient theoretical detail, relying heavily on empirical data and offering limited predictive capability. In particular, the complex surface chemistry governing SiC growth remains poorly understood. This study addresses these challenges by employing density functional theory (DFT) to investigate key heterogeneous reactions involving hydrocarbon intermediates on SiC surfaces, including dehydrogenation, hydrogenation, and carbon deposition. Transition state searches were conducted to identify reaction pathways and energy barriers. While first-principles calculations offer high accuracy, they are computationally intensive. To extend the utility of these first-principles results, vibrational analyses were performed using phonon-based statistical thermochemistry to compute temperature-dependent reaction rates which were used to develop Arrhenius-type surrogate kinetic models. Furthermore, the resulting framework provides a more rigorous, physically grounded basis for integrating atomistic insights into continuum-scale modeling, ultimately enabling improved prediction and optimization of SiC film growth in high-performance material systems.

Density Functional Theory↗

Alkali Metal Control of Triplet-Mediated C–H Activation in Iron-Mediated Coupling of Dinitrogen and Benzene

Direct coupling of N 2 with abundant feedstocks like benzene to form N-containing organic compounds is a promising strategy for N 2 fixation pathways. The challenge of coupling N 2 activation and C–H bond oxidative addition was recently solved by introducing a reversible benzene C–H bond activation process mediated by a low-valent Fe(0) complex, which gave an organometallic product that could couple with partially reduced N 2 . Interestingly, the energetics of the C–H oxidative addition/reductive elimination step depends on the choice of alkali metal. However, the reason why the alkali metal influences the C–H bond activation remained elusive. In this work, we present a comprehensive study on this Fe(0)-mediated reversible C–H activation. Through density functional theory combined with high-level coupled cluster calculations, we discovered that the intermediate-spin triplet (S = 1) controls the energy of the transition state for C–H cleavage, while the high-spin quintet (S = 2) controls the position of the equilibrium. Na + drives the equilibrium toward oxidative addition due to an electrostatic effect, while K + and Rb + are dominated by a steric effect that favors the iron(0) species. The key role played by nonbonding interactions in the Fe-mediated C–H activation provides a conceptual model for alkali control over organometallic transformations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Centrosymmetric or Noncentrosymmetric? Transition Metals Talking in K 2 TGe 3 S 8 (T = Co, Fe)

Two new quaternary sulfides K 2 TGe 3 S 8 (T=Co, Fe) have been synthesized by a high-temperature solid-state routine and flux growth method. The crystal growth process of K 2 TGe 3 S 8 (T=Co, Fe) was elucidated by in-situ powder X-ray diffraction and DSC thermal analysis. The mm-sized crystals of K 2 TGe 3 S 8 (T=Co, Fe) were grown. K 2 CoGe 3 S 8 crystallizes in a new structure type in centrosymmetric space group P1¯ (No. 2) with unit cell parameters of a = 7.016(1) Å, b = 7.770(1)Å, c = 14.342(1) Å, α = 93.80(1)°, β = 92.65(1)°, γ = 114.04(1)°. K 2 FeGe 3 S 8 crystallizes in K 2 FeGe 3 Se 8 structure type and the noncentrosymmetric space group P2 1 (No. 4) with unit cell parameters of a = 7.1089(5)Å, b = 11.8823(8)Å, c = 16.7588(11)Å, β = 96.604(2)°. There is a high structural similarity between K 2 CoGe 3 S 8 and K 2 FeGe 3 S 8 . The larger volume coupled with higher degrees of distortion of [FeS 4 ] tetrahedra compared to [CoS 4 ] tetrahedra accounts for the structure’s shift from centrosymmetric to noncentrosymmetric. The theory simulation confirms that [TS 4 ]T= Co or Fe tetrahedra play a crucial role in controlling the structure and properties of K 2 TGe 3 S 8 (T = Co, Fe). The measured optical bandgaps of K 2 CoGe 3 S 8 and K 2 FeGe 3 S 8 are 2.1(1) eV and 2.6(1) eV respectively. K 2 FeGe 3 S 8 shows antiferromagnetic ordering at 24K while no magnetic ordering was detected in K 2 CoGe 3 S 8 . In conclusion, the magnetic measurements also demonstrate the divalent nature of transition metals in K 2 TGe 3 S 8 (T = Co, Fe).

36 MATERIALS SCIENCE↗

Understanding Trigger Linkage Dynamics in Energetic Materials Using Mixed Picramide Nitrate Ester Explosives

The ability to predict the handling sensitivity of new organic energetic materials has been a longstanding goal. We report the synthesis and characterization of six new nitropicramide energetic materials with mixed functional groups that mimic known explosives such as nitroglycerin, erythritol tetranitrate (ETN), and pentaerythritol tetranitrate (PETN). The molecules have been studied theoretically using quantum molecular dynamics (QMD) simulations and density functional theory (DFT) calculations to identify the weakest bond in the reactants - the trigger-linkages - which control handling sensitivity, and to quantify their specific enthalpies of explosion. In good accord with the drop weight impact sensitivity data, our calculations predict that the sensitivities of the molecules are very similar owing to the small variations of the energy output and rates of trigger linkage rupture. In addition, both the QMD and DFT calculations point to the nitropicramide N–NO 2 bonds as the trigger linkages rather than the more typical O–NO 2 bonds. We propose that the switch of the trigger linkage from the nitrate esters to the nitramine groups arises from the strongly electron withdrawing character of the adjacent trinitrobenzene groups.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum simulation of conical intersections using trapped ions

Conical intersections often control the reaction products of photochemical processes and occur when two electronic potential energy surfaces intersect. Theory predicts that the conical intersection will result in a geometric phase for a wavepacket on the ground potential energy surface, and although conical intersections have been observed experimentally, the geometric phase has not been directly observed in a molecular system. Herein we use a trapped atomic ion system to perform a quantum simulation of a conical intersection. The ion’s internal state serves as the electronic state, and the motion of the atomic nuclei is encoded into the motion of the ions. The simulated electronic potential is constructed by applying state-dependent optical forces to the ion. We experimentally observe a clear manifestation of the geometric phase using adiabatic state preparation followed by motional state measurement. Our experiment shows the advantage of combining spin and motion degrees for quantum simulation of chemical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Operando identification of site-dependent water oxidation activity on ruthenium dioxide single-crystal surfaces

Understanding the nature of active sites is central to controlling (electro)catalytic activity. Here we employed surface X-ray scattering coupled with density functional theory and surface-enhanced infrared absorption spectroscopy to examine the oxygen evolution reaction on RuO 2 surfaces as a function of voltage. At 1.5 V RHE , our results suggest that there is an –OO group on the coordinatively unsaturated ruthenium (Ru CUS ) site of the (100) surface (and similarly for (110)), but adsorbed oxygen on the Ru CUS site of (101). Density functional theory results indicate that the removal of –OO from the Ru CUS site, which is stabilized by a hydrogen bond to a neighbouring –OH (–OO–H), could be the rate-determining step for (100) (similarly for (110)), where its reduced binding on (100) increased activity. A further reduction in binding energy on the Ru CUS site of (101) resulted in a different rate-determining step (–O + H 2 O – (H + + e - ) → –OO–H) and decreased activity. Our study provides molecular details on the active sites, and the influence of their local coordination environment on activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The hidden influence of terrestrial groundwater on salt marsh function and resilience

Salt marshes are hotspots of nutrient processing and carbon sequestration. So far, studies addressing spatiotemporal variability in and drivers of salt marsh biogeochemical function, carbon storage and resilience have focused on ocean-driven surface hydrologic influences, neglecting effects of terrestrial hydrology through subsurface connections. Here we evaluate drivers of salt marsh redox potential, a proxy for biogeochemical state, through wavelet analyses and information theory using data from seven marshes. The results point to terrestrial groundwater level as a dominant control on redox variability across all sites. Because redox is a key driver of biogeochemical processes, and specifically oxidation of organic matter that sequesters carbon and maintains marsh elevation, these terrestrial influences are critical to understanding marsh function and evolution. Further, the newly identified links between onshore groundwater levels and marsh redox conditions shift the traditional paradigm and suggest that terrestrial hydrology is a primary control on salt marsh carbon sequestration potential and resilience.

54 ENVIRONMENTAL SCIENCES↗

Ferroelectrics and photovoltaics in endohedral fullerenes-based van der Waals heterostructures

Using the density functional theory calculations, we studied the ferroelectric, electronic, and optical properties of a series of bias-controllable endohedral fullerene molecules (TM@C28, TM = Ti-Ni). One important finding is that Cr@C28 has a large electric dipole moment and an appropriate bandgap (∼1.2 eV). By sandwiching Cr@C28 molecules between two graphene or transition metal dichalcogenide layers, the heterostructures may combine strong ferroelectricity and excellent optical properties. This paves the way for the development of two-dimensional van der Waals ferroelectric-photovoltaic materials.

Li, Jie (ORCID:0000000237334587)↗

Surface deformation coupled with self-organized pattern on a liquid anode of 1 atm DC glow discharge

Intricate, self-organized plasma structures observed above the surface of a liquid anode of atmospheric DC glow discharge were found to give rise to coherent, organized surface deformation and mechanical wave formation at the plasma–liquid interface. This new phenomenon indicates that the liquid is closely coupled to the plasma by the anode sheath’s electrohydrodynamic (EHD) force. A scientific question then arises: Do surface perturbations, coupled with the nonuniform surface charge distribution, enhance the electric field and induce self-organization? Using the reflective background-oriented schlieren technique, the liquid surface profile under the plasma pattern was measured for the first time. The results show that surface distortions are driven by the repulsive Coulomb force of nonuniform net-negative surface charge acted by the anode sheath field. The impacts of various operating parameters on the patterns and surface waves were examined, revealing the significance of gas heating and liquid charge relaxation time in the pattern formation mechanism. Time-resolved dynamics of a pulsed DC discharge indicated that the surface deformation only appeared after the establishment of plasma patterns. Statistically, the surface wave under the plasma has high wave numbers (8000–16000 m −1 ) and small amplitudes ($<$ 10 µm), generally found in the capillary wave regime. Yet the motion of surface deformations is in tandem with the plasma pattern and exhibits a nondispersive nature of constant phase velocity (0.1–0.4 m s −1 ), suggesting the dominant role of EHD force over the surface tension in the observed surface wave. These results indicate that the deformed liquid surface is driven by the EHD force of the plasma sheath. Although they share a similar geometry, the deformation and wave dynamics of the liquid surface do not stimulate a plasma pattern. Importantly, the complex EHD coupling in the plasma–liquid system raises awareness and new challenges for plasma control engineering, and the quantitative characteristics of the nondispersive surface wave are informative for advancing relevant theory and modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effect of Intermediate Semiconducting TiOx Thin Films on Nanoparticle-Mediated Electron Transfer: Electrooxidation of CO

The concept of nanoparticle-mediated electron transfer (eT) across insulating thin films was elucidated theoretically by Allongue and Chazalviel in 2011. In their model, metal nanoparticles (NPs) are immobilized atop passivating, self-assembled monolayers (SAMs). They found that under certain conditions, related to the thickness of the SAM and the size of the NPs, efficient faradaic oxidation and reduction reactions could proceed at the NP surface. In the absence of NPs, however, eT was suppressed by the insulating SAM thin films. Allongue and Chazalviel concluded that, within certain bounds, eT is mediated by fast tunneling between the conductive electrode and the metal NPs, while the kinetics of the redox reaction are controlled by the NPs. This understanding has been confirmed using a variety of experimental models. The theory is based on electron tunneling; therefore, the nature of the intervening medium (the insulator in prior studies) should not affect the eT rate. In the present manuscript, however, we show that the theory breaks down under certain electrochemical conditions when the medium between conductors is an n-type semiconductor. Specifically, we find that in the presence of either Au or Pt NPs immobilized on a thin film of TiOx, CO electrooxidation does not proceed. In contrast, the exact same systems lead to the efficient reduction of oxygen. At present, we are unable to explain this finding within the context of the model of Allongue and Chazalviel.

Galyamova, Aigerim↗

Interpreting machine learning prediction of fire emissions and comparison with FireMIP process-based models

Annual burned areas in the United States have increased 2-fold during the past decades. With more large fires resulting in more emissions of fine particulate matter, an accurate prediction of fire emissions is critical for quantifying the impacts of fires on air quality, human health, and climate. This study aims to construct a machine learning (ML) model with game-theory interpretation to predict monthly fire emissions over the contiguous US (CONUS) and to understand the controlling factors of fire emissions. The optimized ML model is used to diagnose the process-based models in the Fire Modeling Intercomparison Project (FireMIP) to inform future development. Results show promising performance for the ML model, Community Land Model (CLM), and Joint UK Land Environment Simulator-Interactive Fire And Emission Algorithm For Natural Environments (JULES-INFERNO) in reproducing the spatial distributions, seasonality, and interannual variability of fire emissions over the CONUS. Regional analysis shows that only the ML model and CLM simulate the realistic interannual variability of fire emissions for most of the subregions (r >0.95 for ML and r =0.14~0.70 for CLM), except for Mediterranean California, where all the models perform poorly (r =0.74 for ML and r <0.30 for the FireMIP models). Regarding seasonality, most models capture the peak emission in July over the western US. However, all models except for the ML model fail to reproduce the bimodal peaks in July and October over Mediterranean California, which may be explained by the smaller wind speeds of the atmospheric forcing data during Santa Ana wind events and limitations in model parameterizations for capturing the effects of Santa Ana winds on fire activity. Furthermore, most models struggle to capture the spring peak in emissions in the southeastern US, probably due to underrepresentation of human effects and the influences of winter dryness on fires in the models. As for extreme events, both the ML model and CLM successfully reproduce the frequency map of extreme emission occurrence but overestimate the number of months with extremely large fire emissions. Comparing the fire PM 2.5 emissions from the ML model with process-based fire models highlights their strengths and uncertainties for regional analysis and prediction and provides useful insights into future directions for model improvements.

54 ENVIRONMENTAL SCIENCES↗

Excited-State and Nonadiabatic Molecular Dynamics Methods with Broad Applicability

Electronically excited states play a pivotal role in the capture, transformation, storage, and emission of radiative energy. Despite much recent progress for small model systems, excited state properties and dynamics in many larger molecular devices and materials have remained elusive for experiment and theory. Nonadiabatic transitions between electronic states turn radiative energy into heat and are particularly difficult to control. This project aims to develop new electronic structure and nonadiabatic molecular dynamics (NAMD) methods to simulate, predict, and ultimately control the flow and transformation of excitation energy in a wide-range of light-driven molecular devices such as dyes, photocatalysts, and fluorescence emitters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selective formation of metastable polymorphs in solid-state synthesis

Metastable polymorphs often result from the interplay between thermodynamics and kinetics. Despite advances in predictive synthesis for solution-based techniques, there remains a lack of methods to design solid-state reactions targeting metastable materials. Here, we introduce a theoretical framework to predict and control polymorph selectivity in solid-state reactions. This framework presents reaction energy as a rarely used handle for polymorph selection, which influences the role of surface energy in promoting the nucleation of metastable phases. Through in situ characterization and density functional theory calculations on two distinct synthesis pathways targeting LiTiOPO 4 , we demonstrate how precursor selection and its effect on reaction energy can effectively be used to control which polymorph is obtained from solid-state synthesis. A general approach is outlined to quantify the conditions under which metastable polymorphs are experimentally accessible. With comparison to historical data, this approach suggests that using appropriate precursors could enable targeted materials synthesis across diverse chemistries through selective polymorph nucleation.

36 MATERIALS SCIENCE↗

De Sitter decays to infinity

Bubbles of nothing are a class of vacuum decay processes present in some theories with compactified extra dimensions. We investigate the existence and properties of bubbles of nothing in models where the scalar pseudomoduli controlling the size of the extra dimensions are stabilized at positive vacuum energy, which is a necessary feature of any realistic model. We map the construction of bubbles of nothing to a four-dimensional Coleman-De Luccia problem and establish necessary conditions on the asymptotic behavior of the scalar potential for the existence of suitable solutions. We perform detailed analyses in the context of five-dimensional theories with metastable dS 4 x S 1 vacua, using analytic approximations and numerical methods to calculate the decay rate. We find that bubbles of nothing sometimes exist in potentials with no ordinary Coleman-De Luccia decay process, and that in the examples we study, when both processes exist, the bubble of nothing decay rate is typically faster. Our methods can be generalized to other stabilizing potentials and internal manifolds.

classical theories of gravity↗