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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Molecular Interlocking Multidimensional Modulations of Cathode‐Electrolyte Interface for Constructing High Energy Density Quasi‐Solid‐State Batteries

Gel polymers are regarded as a promising candidate electrolyte for lithium-metal quasi-solid-state batteries, primarily due to their high ionic conductivity and solid-liquid synergistic properties. However, challenges such as interfacial side reactions, limitations in Li + transport caused by interfacial issues, and leaching of transition metals from the cathode have yet to be effectively solved. Herein, a novel gel electrolyte modulation strategy based on electrostatic filler assembly is proposed to address the issues of ineffective capacity utilization and inadequate cycling stability of high-energy-density cathode materials in solid-state lithium-ion batteries. It constructs a 3D interpenetrating charge-bridge network that effectively tackles the phase-separation challenge between fillers and electrolytes at the molecular level. Meanwhile, the molecular interlocking structure effectively inhibits the electrolyte erosion. More critically, it optimizes and stabilizes the cathode-electrolyte interface film, which facilitates the conduction of Li + -ions through a size-sieving mechanism. Consequently, this strategy enables effective adaptation across diverse high-energy-density cathode materials with satisfactory capacity performance (170.4 mAh g −1 at 4.5 V/1 C for LiNi 0.6 Co 0.2 Mn 0.2 O 2 and 194.0 mAh g −1 at 4.3 V/1 C for LiNi 0.9 Co 0.08 Mn 0.02 O 2 ). In conclusion, this investigation offers a straightforward and effective reference for addressing the critical challenges of ionic transport and interface stabilization in the design of gel electrolytes.

cathode-electrolyte interface↗
DOE OSTI2023

Blind photovoltaic modeling intercomparison: A multidimensional data analysis and lessons learned

The Photovoltaic (PV) Performance Modeling Collaborative (PVPMC) organized a blind PV performance modeling intercomparison to allow PV modelers to blindly test their models and modeling ability against real system data. Measured weather and irradiance data were provided along with detailed descriptions of PV systems from two locations (Albuquerque, New Mexico, USA, and Roskilde, Denmark). Participants were asked to simulate the plane-of-array irradiance, module temperature, and DC power output from six systems and submit their results to Sandia for processing. The results showed overall median mean bias (i.e., the average error per participant) of 0.6% in annual irradiation and –3.3% in annual energy yield. While most PV performance modeling results seem to exhibit higher precision and accuracy as compared to an earlier blind PV modeling study in 2010, human errors, modeling skills, and derates were found to still cause significant errors in the estimates.

14 SOLAR ENERGY↗
DOE OSTI2019

Multidimensional sum-up rounding for integer programming in optimal experimental design

Here we present a numerical method for approximating the solution of convex integer programs stemming from optimal experimental design. The statistical setup consists of a Bayesian framework for linear inverse problems for which the direct relationship is described by a discretized integral equation. Specifically, we aim to find the optimal sensor placement from a set of candidate locations where data are collected with measurement error. The convex objective function is a measure of the uncertainty, described here by the trace or log-determinant of the posterior covariance matrix, for the discretized linear inverse problem solution. The resulting convex integer program is relaxed, producing a lower bound. An upper bound is obtained by extending the sum-up rounding approach to multiple dimensions. For this extension, we analyze its accuracy as a function of the discretization mesh size for a rectangular domain. We show asymptotic optimality of the integer solution defining the upper bound for different experimental design criteria (A- and D-optimal), by proving the convergence to zero of the gap between the upper and lower bounds as the mesh size goes to zero. The technique is illustrated on a two-dimensional gravity surveying problem for both A-optimal and D-optimal sensor placement where our designs yield better results compared with a thresholding rounding approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods

Metabolomics continues to make rapid progress through the development of new and better methods and their applications to gain insight into the metabolism of a wide range of different biological systems from a systems biology perspective. Customization of NMR databases and search tools allows the faster and more accurate identification of known metabolites, whereas the identification of unknowns, without a need for extensive purification, requires new strategies to integrate NMR with mass spectrometry, cheminformatics, and computational methods. For some applications, the use of covalent and non-covalent attachments in the form of labeled tags or nanoparticles can significantly reduce the complexity of these tasks.

Bingol, Kerem↗
DOE OSTI2025

A scalable multidimensional fully implicit solver for Hall magnetohydrodynamics

We propose an optimally performant fully implicit algorithm for the Hall magnetohydrodynamics (HMHD) equations based on multigrid-preconditioned Jacobian-free Newton-Krylov methods. HMHD is a challenging system to solve numerically because it supports stiff fast dispersive waves. The preconditioner is formulated using an operator-split approximate block factorization (Schur complement), informed by physics insight. We use a vector-potential formulation (instead of a magnetic field one) to allow a clean segregation of the problematic $\nabla$ x $\nabla$ x operator in the electron Ohm's law subsystem. This segregation allows the formulation of an effective damped block-Jacobi smoother for multigrid. We demonstrate by analysis that our proposed block-Jacobi iteration is convergent and has the smoothing property. The resulting HMHD solver is verified linearly with wave propagation examples, and nonlinearly with the GEM challenge reconnection problem by comparison against another HMHD code. We demonstrate the excellent algorithmic and parallel performance of the algorithm up to 16384 MPI tasks in two dimensions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

SNAPRed: Reduction of multidimensional neutron time-of-flight diffraction data

SNAP is a neutron time-of-flight diffractometer at the Spallation Neutron Source operated by Oak Ridge National Laboratory. It generates large arrays of neutron detection events that encode the crystalline atomic structure of materials under study. SNAPRed is an application that makes these datasets accessible to end users by orchestrating the process of data reduction while automatically managing the variable neutron instrumentation configuration. It supports arbitrary grouping and masking of individual detector pixels and includes custom-developed data compression approaches to accommodate the large volumes of data generated by the SNAP instrument.

Diffraction↗
DOE OSTI2016

Multidimensional solid-state NMR spectroscopy of plant cell walls

Plant biomass has become an important source of bio-renewable energy in modern society. The molecular structure of plant cell walls is difficult to characterize by most atomic-resolution techniques due to the insoluble and disordered nature of the cell wall. Solid-state NMR (SSNMR) spectroscopy is uniquely suited for studying native hydrated plant cell walls at the molecular level with chemical resolution. Significant progress has been made in the last five years to elucidate the molecular structures and interactions of cellulose and matrix polysaccharides in plant cell walls. These studies have focused on primary cell walls of growing plants in both the dicotyledonous and grass families, as represented by the model plants Arabidopsis thaliana, Brachypodium distachyon, and Zea mays. To date, these SSNMR results have shown that 1) cellulose, hemicellulose, and pectins form a single network in the primary cell wall; 2) in dicot cell walls, the protein expansin targets the hemicellulose-enriched region of the cellulose microfibril for its wall-loosening function; and 3) primary wall cellulose has polymorphic structures that are distinct from the microbial cellulose structures. This article summarizes these key findings, and points out future directions of investigation to advance our fundamental understanding of plant cell wall structure and function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Removal of Homogeneous Broadening from 1 H-Detected Multidimensional Solid-State NMR Spectra

1 H-detected magic-angle spinning (MAS) NMR experiments have revolutionized the NMR studies of biological and inorganic solids by providing unparalleled sensitivity and resolution. Despite these gains, homogeneous broadening, originating from the incomplete removal of homonuclear dipolar interactions under fast MAS, remains highly prevalent and limits the achievable resolution. In direct analogy to super-resolution microscopy methods, we show that resolution beyond that currently achievable by fast MAS alone can be obtained by experiment-driven deconvolution. Following the acquisition of a single 2D NMR spectrum to measure the frequency-dependent homogeneous lineshapes, any number of 1 H-detected spectra can be enhanced in resolution, yielding comparable spectra as obtained with twice the MAS frequency. In conclusion, the versatility of this approach is demonstrated in the enhancement of single- and double-quantum homonuclear correlation spectra, in addition to heteronuclear correlation spectra acquired on a surface organometallic complex and the protein GB1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Characterization of Silicon Nanocrystal Surfaces by Multidimensional Solid-State NMR Spectroscopy

The chemical and photophysical properties of silicon nanocrystals (Si NCs) are strongly dependent on the chemical composition and structure of their surfaces. Here we use fast magic angle spinning (MAS) and proton detection to enable the rapid acquisition of dipolar and scalar 2D 1 H– 29 Si heteronuclear correlation (HETCOR) solid-state NMR spectra and reveal a molecular picture of hydride-terminated and alkyl-functionalized surfaces of Si NCs produced in a nonthermal plasma. 2D 1 H– 29 Si HETCOR and dipolar 2D 1 H– 1 H multiple-quantum correlation spectra illustrate that resonances from surface mono-, di-, and trihydride groups cannot be resolved, contrary to previous literature assignments. Instead the 2D NMR spectra illustrate that there is large distribution of 1 H and 29 Si chemical shifts for the surface hydride species in both the as-synthesized and functionalized Si NCs. However, proton-detected 1 H– 29 Si refocused INEPT experiments can be used to unambiguously differentiate NMR signals from the different surface hydrides. Varying the 29 Si evolution time in refocused INEPT experiments and fitting the oscillation of the NMR signals allows for the relative populations of the different surface hydrides to be estimated. This analysis confirms that monohydride species are the predominant surface species on the as-synthesized Si NCs. A reduction in the populations of the di- and trihydrides is observed upon functionalization with alkyl groups, consistent with our previous hypothesis that the trihydride, or silyl (*SiH 3 ), group is primarily responsible for initiating surface functionalization reactions. Density functional theory (DFT) calculations were used to obtain quantum chemical structural models of the Si NC surface and reproduce the observed 1 H and 29 Si chemical shifts. Furthermore, the approaches outlined here will be useful to obtain a more detailed picture of surface structures for Si NCs and other hydride-passivated nanomaterials.

29Si NMR↗