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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Adaptive mesh refinement versus subgrid friction interpolation in simulations of Antarctic ice dynamics

At least in conventional hydrostatic ice-sheet models, the numerical error associated with grounding line dynamics can be reduced by modifications to the discretization scheme. These involve altering the integration formulae for the basal traction and/or driving stress close to the grounding line and exhibit lower – if still first-order – error in the MISMIP3d experiments. MISMIP3d may not represent the variety of real ice streams, in that it lacks strong lateral stresses, and imposes a large basal traction at the grounding line. We study resolution sensitivity in the context of extreme forcing simulations of the entire Antarctic ice sheet, using the BISICLES adaptive mesh ice-sheet model with two schemes: the original treatment, and a scheme, which modifies the discretization of the basal traction. The second scheme does indeed improve accuracy – by around a factor of two – for a given mesh spacing, but $\lesssim 1$ km resolution is still necessary. For example, in coarser resolution simulations Thwaites Glacier retreats so slowly that other ice streams divert its trunk. In contrast, with $\lesssim 1$ km meshes, the same glacier retreats far more quickly and triggers the final phase of West Antarctic collapse a century before any such diversion can take place.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Polyurethanes Based on Unmodified and Refined Technical Lignins: Correlation between Molecular Structure and Material Properties

The structural complexity and robust intermolecular interactions have challenged the incorporation of technical lignin into value-added polymeric materials for decades. To study the correlation between lignin molecular structure and material properties of lignin-based polyurethanes, we applied co-solvent enhanced lignocellulosic fractionation pretreatment followed by sequential precipitation to produce three distinct lignin preparations with narrowly distributed (molecular weight dispersity <2) and comparatively low molecular weight (<1500 g/mol) from poplar biomass. Structural characterization indicated that these lignin preparations differed in average molecular chain length and stiffness as well as hydroxyl group distribution. Secondary hydroxyl group providers such as aliphatic diols and polyethers were incorporated as building blocks into the lignin-based polyurethanes to provide additional hydrogen capacity to improve the dispersion of lignin in the polyurethane network. The selected aliphatic diols and polyethers interacted with lignin molecules at different levels of strength depending on their molecular structure, and their impacts were ultimately reflected in the mechanical and thermal properties of the resulting lignin-based polyurethanes. The copolymerization of technical lignin with tailored structure and secondary hydroxyl providers could provide new strategies in formulating lignin-based/containing polyurethanes for various functional applications.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Large-Scale Refinement of Metal-Organic Framework Structures Using Density Functional Theory

Efforts to computationally characterize large numbers of nanoporous materials often rely on databases of experimentally resolved crystal structures. The accuracy of experimental crystal structures used in such calculations has a significant impact on the reliability of the results. Here in this work, we report structures optimized using periodic density functional theory (DFT) for more than 800 experimentally synthesized metal-organic frameworks (MOFs). Many MOFs changed significantly upon structural optimization, particularly materials that were crystallographically resolved in their solvated form. For each MOF, we simulated the adsorption of CH 4 and CO 2 using grand canonical Monte Carlo both before and after DFT optimization. The DFT optimization has a large impact on simulated gas adsorption in some cases – for example, CO 2 loading at 1 bar changed by more than 25% in over 25% of the MOFs we considered.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Well-Defined Nanoparticle Electrocatalysts for the Refinement of Theory

The relationship between experiment and theory in electrocatalysis is one of profound importance. Until fairly recently, the principal role of theory in this field was interpreting experimental results. Over the course of the past decade (roughly the period covered by this review), however, that has begun to change, with theory now frequently leading the design of electrocatalytic materials. Though rewarding, this has not been a particularly easy union. For one thing, experimentalists and theorists have to come to grips with the fact that they rely on different models. Theorists make predictions based on individual, perfect structural models, while experimentalists work with more complex and heterogeneous ensembles of electrocatalysts. As discussed in this review, computational capabilities have improved in recent years, so that theory is better represented by the structures that experimentalists are able to prepare. Likewise, synthetic chemists are able to make ever more complex electrocatalysts with high levels of control, which provide a more extensive palette of materials for testing theory. Finally, the goal of this review is to highlight research from the last ~10 years that focuses on carefully controlled electrocatalytic experiments which, in combination with theoretical predictions, bring us closer to bridging the gap between real catalysts and computational models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Collisional Excitation of HCN by CO to Refine the Modeling of Cometary Comae

Here, we present the first dataset of collisional (de)-excitation rate coefficients of HCN induced by CO, one of the main perturbing gases in cometary atmospheres. The dataset spans the temperature range of 5–50 K. It includes both state-to-state rate coefficients involving the lowest ten and nine rotational levels of HCN and CO, respectively, and the so-called “thermalized” rate coefficients over the rotational population of CO at each kinetic temperature. The derivation of these coefficients exploited the good performance of the statistical adiabatic channel model (SACM) on top of an accurate interaction potential computed at the CCSD(T)-F12b/CBS level of theory. The reliability of the SACM approach was validated by comparison with full quantum calculations restricted at the lowest total angular momentum of the system. These results provide essential input to accurately model the distribution among the rotational energy levels and the abundance of HCN in cometary atmospheres, accounting for deviations from local thermodynamic equilibrium that typically occurs in such environments.

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

Electronic Rearrangement in Steps of Reductive Elimination of Polar Electrophiles Leads to Refinement of Redox Events

The oxidative addition/reductive elimination of polar molecules such as methyl iodide at late metal centers has a strongly supported $S_{N^2}$ mechanism for many key organometallic complexes, including important industrial catalysts. In the reductive elimination direction, it is proposed that a ligand initially dissociates, typically a halide, followed by subsequent nucleophilic attack at the ligand trans to the now vacant site. The prevailing view is the metal reduction occurs upon transferring the electrophile in the $S_{N^2}$ step. Herein, we report the use of an ensemble of computational techniques to characterize the electronic structure of the reactants and intermediates along this reductive elimination pathway. These calculations demonstrate, unexpectedly, that the initiating loss of an anionic ligand from the octahedral highly oxidized structure leads to an electronic rearrangement that shifts electron density from the apical ligand back toward the metal resulting in an inversion of the electron flow between the metal and apical ligand. The anisotropic shift in electron density to the metal disproportionately affects the apical position, which is best described as a Pt → Me dative bond. With this Pt → Me bonding description, our interpretation of the IUPAC oxidation state formalism would assign the intermediate as Pt ΙΙ . Although counterintuitive, the formal and functional reduction of the metal thus occurs upon halide dissociation.

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

Refining Planetary Boundary Layer Height Retrievals From Micropulse‐Lidar at Multiple ARM Sites Around the World

Abstract Knowledge of the planetary boundary layer height (PBLH) is crucial for various applications in atmospheric and environmental sciences. Lidar measurements are frequently used to monitor the evolution of the PBLH, providing more frequent observations than traditional radiosonde‐based methods. However, lidar‐derived PBLH estimates have substantial uncertainties, contingent upon the retrieval algorithm used. In addressing this, we applied the Different Thermo‐Dynamic Stabilities (DTDS) algorithm to establish a PBLH data set at five separate Department of Energy's Atmospheric Radiation Measurement sites across the globe. Both the PBLH methodology and the products are subject to rigorous assessments in terms of their uncertainties and constraints, juxtaposing them with other products. The DTDS‐derived product consistently aligns with radiosonde PBLH estimates, with correlation coefficients exceeding 0.77 across all sites. This study delves into a detailed examination of the strengths and limitations of PBLH data sets with respect to both radiosonde‐derived and other lidar‐based estimates of the PBLH by exploring their respective errors and uncertainties. It is found that varying techniques and definitions can lead to diverse PBLH retrievals due to the inherent intricacy and variability of the boundary layer. Our DTDS‐derived PBLH data set outperforms existing products derived from ceilometer data, offering a more precise representation of the PBLH. This extensive data set paves the way for advanced studies and an improved understanding of boundary‐layer dynamics, with valuable applications in weather forecasting, climate modeling, and environmental studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Refined Understanding of the Ice Cloud Longwave Scattering Effects in Climate Model

Abstract Because longwave (LW) absorption by greenhouse gases and clouds is more significant than the LW scattering effect by clouds, most climate models neglect cloud LW scattering to save computational costs. Ignoring cloud LW scattering directly overestimates outgoing longwave radiation (OLR). This study included ice‐cloud LW scattering treatment in the Exascale Energy Earth System Model (E3SM) version 2 and ran fully‐coupled simulations, prescribed sea surface temperature simulations, and offline radiative transfer calculations to comprehensively assess the impact of ice‐cloud LW scattering on global climate simulation. The instantaneous effect due to ice‐cloud LW scattering reduces the OLR by ∼1 W/m 2 on the global average and 2 W/m 2 on the tropical average. Tropospheric warming and high cloud amount reduction act to partially compensate for such instantaneous OLR reduction caused by the inclusion of LW scattering. When the simulation reaches the equilibrium, the surface warms by 0.66 K on average with respect to the simulation without LW scattering, with the Arctic surface temperature differences more than twice as large as that of the global mean. The impact of including LW scattering on the simulated climate change in response to 4 × CO 2 is also assessed. While including the cloud LW scattering does not significantly modify radiative forcing and total radiative feedback under such a scenario, it results in a 10% more positive cloud feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Novel Emergent Constraint Approach for Refining Regional Climate Model Projections of Peak Flow Timing

Abstract Global climate models (GCMs) are unable to produce detailed runoff conditions at the basin scale. Assumptions are commonly made that dynamical downscaling can resolve this issue. However, given the large magnitude of the biases in downscaled GCMs, it is unclear whether such projections are credible. Here, we use an ensemble of dynamically downscaled GCMs to evaluate this question in the Sierra‐Cascade mountain range of the western US. Future projections across this region are characterized by earlier seasonal shifts in peak flow, but with substantial inter‐model uncertainty (−25 ± 34.75 days, 95% confidence interval (CI)). We apply the emergent constraint (EC) method for the first time to dynamically downscaled projections, leading to a 39% (−28.25 ± 20.75 days, 95% CI) uncertainty reduction in future peak flow timing. While the constrained results can differ from bias corrected projections, the EC is based on GCM biases in historical peak flow timing and has a strong physical underpinning.

54 ENVIRONMENTAL SCIENCES↗