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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Radiative Forcing From the 2014–2022 Volcanic and Wildfire Injections

Abstract Volcanic and wildfire events between 2014 and 2022 injected ∼3.2 Tg of sulfur dioxide and 0.8 Tg of smoke aerosols into the stratosphere. With injections at higher altitudes and lower latitudes, the simulated stratospheric lifetime of the 2014–2022 injections is about 50% longer than the volcanic 2005–2013 injections. The simulated global mean effective radiative forcing (ERF) of 2014–2022 is −0.18 W m −2 , ∼40% of the ERF of the period of 1991–1999 with a large‐magnitude volcanic eruption (Pinatubo). Our climate model suggests that the stratospheric smoke aerosols generate ∼60% more negative ERF than volcanic sulfate per unit aerosol optical depth. Studies that fail to account for the different radiative properties of wildfire smoke relative to volcanic sulfate will likely underestimate the negative stratospheric forcings. Our analysis suggests that stratospheric injections offset 20% of the increase in global mean surface temperature between 2014–2022 and 1999–2002.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

On the Sensitivity of Coastal Hypoxia to Its External Physical Forcings

Abstract The development of low‐oxygen zones threatening marine life (hypoxia) occurs annually in multiple coastal regions of the world. The largest estuary of the continental United States, the Chesapeake Bay, typically has ≈10 km 3 of water with dioxygen concentrations <3 mg L −1 in July. As numerical methods for refining model resolutions in targeted areas are becoming common, there is interest in assessing the feasibility of simulating coastal hazards such as hypoxia in Earth System Models (ESMs). These coupled models are typically not constrained by observations and thus likely to feature systematic biases in their land, atmosphere, or ocean components. This study relies on four numerical experiments to evaluate the sensitivity of Chesapeake Bay hypoxia to changes or biases in its external physical forcings. Hypoxia exhibits only a minor decrease (−1.6%) after reducing the Bay's terrestrial freshwater discharge by 9.5% (but keeping terrestrial nutrient loadings the same). Changes in freshwater discharges have their largest impact on hypoxia during one extreme event (−37% during 2011 tropical storm Lee). Similarly, changing oceanic conditions on the shelf or their temporal frequency impact hypoxia by only 5%–6%, indicating that the latter is predominantly dictated by local conditions. Although these results are promising from the perspective of ESMs, additional components of ESMs will need to be evaluated before general conclusions can be reached. We notably speculate that the Bay's hypoxia would exhibit higher sensitivity to other forcings not examined here, notably air temperatures and nutrient loadings.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Active learning of reactive Bayesian force fields applied to heterogeneous catalysis dynamics of H/Pt

Abstract Atomistic modeling of chemically reactive systems has so far relied on either expensive ab initio methods or bond-order force fields requiring arduous parametrization. Here, we describe a Bayesian active learning framework for autonomous “on-the-fly” training of fast and accurate reactive many-body force fields during molecular dynamics simulations. At each time-step, predictive uncertainties of a sparse Gaussian process are evaluated to automatically determine whether additional ab initio training data are needed. We introduce a general method for mapping trained kernel models onto equivalent polynomial models whose prediction cost is much lower and independent of the training set size. As a demonstration, we perform direct two-phase simulations of heterogeneous H 2 turnover on the Pt(111) catalyst surface at chemical accuracy. The model trains itself in three days and performs at twice the speed of a ReaxFF model, while maintaining much higher fidelity to DFT and excellent agreement with experiment.

42 ENGINEERING↗
DOE OSTI2023

High-speed mapping of surface charge dynamics using sparse scanning Kelvin probe force microscopy

Unraveling local dynamic charge processes is vital for progress in diverse fields, from microelectronics to energy storage. This relies on the ability to map charge carrier motion across multiple length- and timescales and understanding how these processes interact with the inherent material heterogeneities. Towards addressing this challenge, we introduce high-speed sparse scanning Kelvin probe force microscopy, which combines sparse scanning and image reconstruction. This approach is shown to enable sub-second imaging (>3 frames per second) of nanoscale charge dynamics, representing several orders of magnitude improvement over traditional Kelvin probe force microscopy imaging rates. Bridging this improved spatiotemporal resolution with macroscale device measurements, we successfully visualize electrochemically mediated diffusion of mobile surface ions on a LaAlO 3 /SrTiO 3 planar device. Such processes are known to impact band-alignment and charge-transfer dynamics at these heterointerfaces. Furthermore, we monitor the diffusion of oxygen vacancies at the single grain level in polycrystalline TiO 2 . Through temperature-dependent measurements, we identify a charge diffusion activation energy of 0.18 eV, in good agreement with previously reported values and confirmed by DFT calculations. Together, these findings highlight the effectiveness and versatility of our method in understanding ionic charge carrier motion in microelectronics or nanoscale material systems.

25 ENERGY STORAGE↗
DOE OSTI2026

Impact of solvent forces and broken symmetry on the assembly of designed proteins at a liquid-solid interface

The era of protein design has enabled the creation of hybrid protein-inorganic interfaces, leading to both surface-directed self-assembly of de novo protein architectures and protein-directed formation of inorganic materials. However, the resulting patterns of protein assembly are often unexpected, implying that essential interactions are not accounted for in current design platforms. Here, we use high-speed atomic force microscopy (AFM) analyzed through machine learning to follow the assembly of protein nanorods in aqueous electrolytes on two types of mica exhibiting disparate symmetry elements, which are imprinted on the overlying hydration structure. Using Monte Carlo simulations, we reproduce the observed phases and show that an observed smectic phase, previously thought to be unstable for non-interacting rods in two dimensions, emerges when crystal symmetry introduces a directional bias. The findings demonstrate the importance of incorporating solvent forces as modulated by the hydration structure inherent to interfacial systems when designing protein assemblies at liquid-crystal interfaces. Coupling physics-based simulations that can account for these factors to de novo protein design algorithms can lead to improved design platforms for bio-inspired, hybrid materials.

bioinspired materials↗
DOE OSTI2020

Historical total ozone radiative forcing derived from CMIP6 simulations

Radiative forcing (RF) time series for total ozone from 1850 up to the present day are calculated based on historical simulations of ozone from 10 climate models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). In addition, RF is calculated for ozone fields prepared as an input for CMIP6 models without chemistry schemes and from a chemical transport model simulation. A radiative kernel for ozone is constructed and used to derive the RF. The ozone RF in 2010 (2005–2014) relative to 1850 is 0.35 W m -2 [0.08–0.61] (5–95% uncertainty range) based on models with both tropospheric and stratospheric chemistry. One of these models has a negative present-day total ozone RF. Excluding this model, the present-day ozone RF increases to 0.39 W m -2 [0.27–0.51] (5–95% uncertainty range). The rest of the models have RF close to or stronger than the RF time series assessed by the Intergovernmental Panel on Climate Change in the fifth assessment report with the primary driver likely being the new precursor emissions used in CMIP6. The rapid adjustments beyond stratospheric temperature are estimated to be weak and thus the RF is a good measure of effective radiative forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Reactive force fields for aqueous and interfacial magnesium carbonate formation

Here we develop Mg/C/O/H ReaxFF parameter sets for two environments: an aqueous force field for magnesium ions in solution and an interfacial force field for minerals and mineral–water interfaces. Since magnesium is highly ionic, we choose to fix the magnesium charge and model its interaction with C/O/H through Coulomb, Lennard-Jones, and Buckingham potentials. We parameterize the forcefields against several crystal structures, including brucite, magnesite, magnesia, magnesium hydride, and magnesium carbide, as well as Mg 2+ water binding energies for the aqueous forcefield. Then, we test the forcefield for other magnesium-containing crystals, solvent separated and contact ion-pairs and single-molecule/multilayer water adsorption energies on mineral surfaces. We also apply the forcefield to the forsterite–water and brucite–water interface that contains a bicarbonate ion. We observe that a long-range proton transfer mechanism deprotonates the bicarbonate ion to carbonate at the interface. Free energy calculations show that carbonate can attach to the magnesium surface with an energy barrier of about 0.22 eV, consistent with the free energy required for aqueous Mg–CO 3 ion pairing. Also, the diffusion constant of the hydroxide ions in the water layers formed on the forsterite surface are shown to be anisotropic and heterogeneous. These findings can help explain the experimentally observed fast nucleation and growth of magnesite at low temperature at the mineral–water–CO 2 interface in water-poor conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Machine learning inversion of interatomic force constants from single-crystal inelastic neutron scattering

Atomic vibrations govern many macroscopic properties of materials, but experiments to comprehensively probe them remain challenging. Inelastic neutron scattering (INS) is a powerful technique to map phonon dispersions in crystals, especially when leveraging modern time-of-flight (ToF) spectrometers with large detectors. However, efficiently and robustly extracting interatomic force constants (FCs) parameterizing phonon dynamics from experimental spectra remains a bottleneck due to the complexity and high dimensionality of ToF INS datasets. Here, we present a machine learning approach for the direct inversion of FCs from single-crystal INS measurements. The framework leverages synthetic training data generated using universal machine-learned force fields and an efficient physics-based forward model. We benchmark two neural architectures–one emphasizing structured latent representation learning and the other direct, supervised spectral regression–across simulated datasets for two materials under idealized and noisy conditions. The latent-representation model is subsequently applied to experimental single-crystal INS data on germanium. The model is shown to reproduce FCs derived from both first-principles simulations and from iterative optimization, and furthermore achieves reliable inference even from sparse, single-orientation measurements representing short data acquisitions. Analysis of the learned latent space reveals semantically continuous and physically interpretable encodings that support strong cross-domain generalization. By bridging theoretical and experimental domains, we establish a path toward rapid inversion of experimental spectra and data-driven interpretation of temperature-dependent lattice dynamics.

42 ENGINEERING↗
DOE OSTI2020

Mean force kinetic theory applied to self-diffusion in supercritical Lennard-Jones fluids

A new kinetic-theory-based calculation of the self-diffusion coefficient for dense supercritical Lennard-Jones fluids is presented. The mean force kinetic theory, which was recently developed for transport in dense plasmas, is applied for the calculation of diffusion in dense neutral fluids. The calculation only requires the pair distribution function, a quantity that is readily calculable from equilibrium statistical mechanics for many systems, including the Lennard-Jones fluid. The self-diffusion coefficients are compared with calculations from molecular dynamics simulations, and good agreement at high density is demonstrated, even in the vicinity of the solid–fluid coexistence line. A comparison of different kinetic models with molecular dynamics simulations demonstrates that the transport coefficients have important contributions due to particle interaction via a potential of mean force and local correlations, which increase the collision rate. The new calculations compare well to those from free-volume theory and overcome a limitation of this theory that prevents its use in systems that interact via long range monotonic potentials. It is expected that this approach will also apply to other systems, including neutral-plasma and neutral-electrolyte mixtures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Local characterization of a heavy-fermion superconductor via sub-Kelvin magnetic force microscopy

Using magnetic force microscopy operating at sub-Kelvin temperatures, we characterize the heavy fermion superconductor CeCoIn5. We pinpoint the absolute London penetration depth of λ(0)=435 ± 20 nm and report its temperature dependence, which is closely linked to the symmetry of the superconducting gap. In addition, we directly measure the pinning force of individual Abrikosov vortices and estimate the critical current density of jc=9×104 A/cm2. In contrast to the related, well-established tunnel diode oscillator technique, our method is capable of resolving inhomogeneities locally on the micrometer scale at ultra-low temperature.

Wulferding, Dirk (ORCID:0000000342792109)↗
DOE OSTI2021

Calculation of self-diffusion coefficients in supercritical carbon dioxide using mean force kinetic theory

This paper presents an application of mean force kinetic theory (MFT) to the calculation of the self-diffusivity of CO 2 in the supercritical fluid regime. Two modifications to the typical application of MFT are employed to allow its application to a system of molecular species. Therefore, the first is the assumption that the inter-particle potential of mean force can be obtained from the molecule center-of-mass pair correlation function, which in the case of CO 2 is the C–C pair correlation function. The second is a new definition of the Enskog factor that describes the effect of correlations at the surface of the collision volume. The new definition retains the physical picture that this quantity represents a local density increase, resulting from particle correlations, relative to that in the zero density homogeneous fluid limit. These calculations are facilitated by the calculation of pair correlation functions from molecular dynamics (MD) simulations using the FEPM2 molecular CO2 model. The self-diffusivity calculated from theory is in good agreement with that from MD simulations up to and slightly beyond the density at the location of the Frenkel line. The calculation is compared with and is found to perform similarly well to other commonly used models but has a greater potential for application to systems of mixed species and to systems of particles with long range interatomic potentials due to electrostatic interactions.

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

Resolving surface potential variation in Ge/MoS 2 heterostructures with Kelvin probe force microscopy

In this work, we employ an atomic force microscopy-based technique, Kelvin probe force microscopy, to analyze heterogeneities of four different 2D/3D Ge/MoS 2 heterostructures with Ge chemical vapor deposition (CVD) time. High-contrast spatially resolved contact potential difference (CPD) maps reveal the evolution of the samples by Ge deposition. The CPD map in an as-prepared sample does not display any heterogeneity, but CPD contrasts along the grain boundaries are obviously noticed as Ge is deposited on MoS 2 . With a sufficiently long Ge CVD deposition time, strong grain-to-grain CPD variations over the 2D/3D heterostructures are observed. The results show the variations of the work function from grain to grain that are attributed to the strain induced by the Ge island formation on the cracked MoS2 initiated by sulfur vacancies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Piezoelectric property of PZT nanofibers characterized by resonant piezo-force microscopy

Nano-piezoelectric materials have drawn tremendous research interest. However, characterization of their piezoelectric properties, especially measuring the piezoelectric strain coefficients, remains a challenge. Normally, researchers use an AFM-based method to directly measure nano-materials’ piezoelectric strain coefficients. But, the extremely small piezoelectric deformation, the influence from the parasitic electrostatic force, and the environmental noise make the measurement results questionable. In this paper, a resonant piezo-force microscopy method was used to accurately measure the piezoelectric deformation from 1D piezoelectric nanofibers. During the experiment, the AFM tip was brought into contact with the piezoelectric sample and set to work at close to its first resonant frequency. A lock-in amplifier was used to pick up the sample’s deformation signal at the testing frequency. By using this technique, the piezoelectric strain constant d 33 of the Lead Zirconate Titanate (PZT) nanofiber with a diameter of 76 nm was measured. The result showed that d 33 of this PZT nanofiber was around 387 pm/V. Meanwhile, by tracking the piezoelectric deformation phase image, domain structures inside PZT nanofibers were identified.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Near-cancellation of up- and down-gradient momentum transport in forced magnetized shear-flow turbulence

Visco-resistive magnetohydrodynamic turbulence, driven by a two-dimensional unstable shear layer that is maintained by an imposed body force, is examined by decomposing it into dissipationless linear eigenmodes of the initial profiles. The down-gradient momentum flux, as expected, originates from the large-scale instability. However, continual up-gradient momentum transport by large-scale linearly stable but nonlinearly excited eigenmodes is identified and found to nearly cancel the down-gradient transport by unstable modes. The stable modes effectuate this by depleting the large-scale turbulent fluctuations via energy transfer to the mean flow. This establishes a physical mechanism underlying the long-known observation that coherent vortices formed from nonlinear saturation of the instability reduce turbulent transport and fluctuations, as such vortices are composed of both the stable and unstable modes, which are nearly equal in their amplitudes. The impact of magnetic fields on the nonlinearly excited stable modes is then quantified. Furthermore, even when imposing a strong magnetic field that almost completely suppresses the instability, the up-gradient transport by the stable modes is at least two-thirds of the down-gradient transport by the unstable modes, whereas for weaker fields, this fraction reaches up to 98%. These effects are persistent with variations in magnetic Prandtl number and forcing strength. Finally, continuum modes are shown to be energetically less important, but essential for capturing the magnetic fluctuations and Maxwell stress. A simple analytical scaling law is derived for their saturated turbulent amplitudes. It predicts the falloff rate as the inverse of the Fourier wavenumber, a property which is confirmed in numerical simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Activation of atomic transport via vibrational coupling-induced force fluctuations

Vibrational coupling, although well-explored in many fields, has seldom been investigated in the context of mass transport. In this Letter, we examine the impact of vibrational coupling on atomic transport using simple molecular dynamics simulations. Our study shows that the atomic transport can be activated when the natural frequency of the atomic slit is close to the natural frequency of the atom being transported. We uncover the presence of fluctuating forces induced by vibrational coupling with higher amplitudes observed when the coupling is strong. We show that the transport activation mechanism is due to the high force fluctuations that arise during strong vibrational coupling allowing the atom to temporarily surpass the transport barrier of the slit. Our findings will serve as a foundation for the continued examination of vibrational coupling in the realm of mass transport.

Physics↗
DOE OSTI2024

Madrid-2019 force field: An extension to divalent cations Sr2+ and Ba2+

In this work, we present a parameterization of Sr2+ and Ba2+ cations, which expands the alkali earth set of cations of the Madrid-2019 force field. We have tested the model against the experimental densities of eight different salts, namely, SrCl2, SrBr2, SrI2, Sr(NO3)2, BaCl2, BaBr2, BaI2, and Ba(NO3)2. The force field is able to reproduce the experimental densities of all these salts up to their solubility limit. Furthermore, we have computed the viscosities for two selected salts, finding that the experimental values are overestimated, but the predictions are still reasonable. Finally, the structural properties for all the salts have been calculated with this model and align remarkably well with experimental observations.

Chemistry↗
DOE OSTI2024

Toward transferable empirical valence bonds: Making classical force fields reactive

The empirical valence bond technique allows classical force fields to model reactive processes. However, parametrization from experimental data or quantum mechanical calculations is required for each reaction present in the simulation. We show that the parameters present in the empirical valence bond method can be predicted using a neural network model and the SMILES strings describing a reaction. This removes the need for quantum calculations in the parametrization of the empirical valence bond technique. In doing so, we have taken the first steps toward defining a new procedure for enabling reactive atomistic simulations. This procedure would allow researchers to use existing classical force fields for reactive simulations, without performing additional quantum mechanical calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗