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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Processing and Analytics System for Microscopy Data Workflows: The Pycroscopy Ecosystem of Packages

Major advancements in fields as diverse as biology and quantum computing have relied on a multitude of microscopy techniques. Despite the considerable proliferation of these instruments, significant bottlenecks remain in terms of processing, analysis, storage, and retrieval of the acquired datasets. Aside from lack of file standards, individual domain-specific analysis packages are often disjoint from the underlying datasets, and thus keeping track of analysis and processing steps remains tedious for the end-user, hampering reproducibility. Here, in this study, the pycroscopy ecosystem of packages is introduced, an open-source python-based ecosystem underpinned by a common data model. The data model, termed the N-dimensional spectral imaging data format, is realized in pycroscopy's sidpy package. This package is built on top of dask arrays, thus leveraging dask array attributes, but expanding them to accelerate microscopy relevant analysis and visualization. Several examples of the use of the pycroscopy ecosystem to create workflows for data ingestion and analysis of scanning transmission electron microscopy (STEM) and scanning probe microscopy data are shown. Adoption of such standardized routines will be critical to usher in the next generation of autonomous instruments where processing, computation, and meta-data storage will be critical to overall experimental operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Scaling Ensembles of Data-Intensive Quantum Chemical Calculations for Millions of Molecules

Deep learning models are efficient computational tools that can accelerate the inverse design of molecules with desired functional properties by generating predictions at a fraction of the time required by traditional quantum chemical approaches. To ensure that a model maintains accuracy and transferability across broad regions of the chemical space explored during the inverse design, it must be trained on massively large volumes of simulation data. This requires running large-scale ensemble quantum chemical calculations on high-performance computing (HPC) systems for data collection. However, the efficient execution of such large ensemble calculations and the management of large volumes of output data require tools that can judiciously utilize computational resources and manage metadata overhead on the file system. Therefore, we present a high-performance, scalable, ensemble management framework for performing data-intensive quantum chemical electronic structure calculations for organic molecules. This framework provides abstractions to plug different ab initio, first principles, and first principles-based semi-empirical methods and executes them efficiently at large scale on HPC systems. It dynamically distributes tasks to resources and uses tiered storage for managing large collections of files. We employed this framework to process over ten million organic molecules and generate open-source datasets that provide UV-vis absorption spectra by running time-dependent density-functional tight-binding calculations. It is the largest database containing molecular optical spectra that were simulated with quantum chemical methods in a consistent manner.

Mehta, Kshitij↗
DOE OSTI2022

Optical quantum memory for noble-gas spins based on spin-exchange collisions

Optical quantum memories, which store and preserve the quantum state of photons, rely on a coherent mapping of the photonic state onto matter states that are optically accessible. Here we outline and characterize schemes to map the state of photons onto long-lived but optically inaccessible collective states of noble-gas spins. The mapping employs coherent spin-exchange interaction arising from random collisions with alkali vapor. We propose efficient storage strategies in two operating regimes and analyze their performance for several proposed experimental configurations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Does boron or nitrogen substitution affect hydrogen physisorption on open carbon surfaces?

Incorporation of heteroatoms in carbon materials is commonly expected to influence their physical or chemical properties. Furthermore, contrary to previous results for methane adsorption, no technologically significant effect was identified for the hydrogen physisorption energies (measured 4.1–4.6 kJ mol –1 and calculated q st = –ΔH ads = 4.1 ± 0.7 kJ mol –1 using a comprehensive set of levels of theory) as a function of B- and N-substitution of a mid-plane C-site on open carbon surfaces.

08 HYDROGEN↗
DOE OSTI2023

PV module spectral response measurements - Data and Resources

"This dataset includes spectral response curves for 12 commercial silicon module types that are deployed at SNL in Albuquerque. The modules chosen for evaluation were originally purchased by SNL for the PV Lifetime project (renamed to Systems Long-Term Evaluation [SLTE]). The majority of those modules are deployed outdoors for long-term evaluation, but several modules of each type were placed in storage for future comparison purposes. One stored module of each type was sent to NREL for the spectral response measurements. NREL used the recently developed Module Quantum Efficiency (QE) test bed. What makes this system unique is that it scans the entire module automatically, taking one or more measurements on each cell. Using the mean of these measurements at each wavelength leads to improvements in spectral mismatch correction and module power measurements but having the individual measurements also makes it possible to identify outlier cells, which could be useful for investigating underperforming modules. All measurements were performed nominally at 25°C"

14 SOLAR ENERGY↗
DOE OSTI2021

Effect of chemical substituents attached to the zwitterion cation on dielectric constant

Materials with high dielectric constant, ε s , are desirable in a wide range of applications including energy storage and actuators. Recently, zwitterionic liquids have been reported to have the largest ε s of any liquid and, thus, have the potential to replace inorganic fillers to modulate the material ε s . Although the large ε s for zwitterionic liquids is attributed to their large molecular dipole, the role of chemical substituents attached to the zwitterion cation on ε s is not fully understood, which is necessary to enhance the performance of soft energy materials. Here, we report the impact of zwitterionic liquid cation chemical substituents on ε s (50 < ε s < 300 at room temperature). Dielectric relaxation spectroscopy reveals that molecular reorientation is the main contributor to the high ε s . The low Kirkwood factor g calculated for zwitterionic liquids (e.g., 0.1–0.2) suggests the tendency for the antiparallel zwitterion dipole alignment expected from the strong electrostatic intermolecular interactions. With octyl cation substituents, the g is decreased due to the formation of hydrophobic-rich domains that restrict molecular reorientation under applied electric fields. In contrast, when zwitterion cations are functionalized with ethylene oxide (EO) segments, g increases due to the EO segments interacting with the cations, allowing more zwitterion rotation in response to the applied field. The reported results suggest that high ε s zwitterionic liquids require a large molecular dipole, compositionally homogeneous liquids (e.g., no aggregation), a maximized zwitterion number density, and a high g, which is achievable by incorporating polar chemical substituents onto the zwitterion cations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2003

Nanostructured Materials Development for Space Power

There have been many recent advances in the use of nanostructured materials for space power applications. In particular, the use of high purity single wall nanotubes holds promise for a variety of generation and storage devices including: thin film lithium ion batteries, microelectronic proton exchange membrane (PEM) fuel cells, polymeric thin film solar cells, and thermionic power supplies is presented. Semiconducting quantum dots alone and in conjunction with carbon nanotubes are also being investigated for possible use in high efficiency photovoltaic solar cells. This paper will review some of the work being done at RIT in conjunction with the NASA Glenn Research Center to utilize nanomaterials in space power devices.

Raffaelle, Ryne P.↗
DOE OSTI2025

Regioisomeric Engineering for Multicharge and Spin Stabilization in Two-Electron Organic Catholytes

Developing multicharge and spin stabilization strategies is fundamental to enhancing the lifetime of functional organic materials, particularly for long-term energy storage in multiredox organic redox flow batteries. Current approaches are limited to the incorporation of electronic substituents to increase or decrease the overall electron density or bulky substituents to sterically shield reactive sites. With the aim to further expand the molecular toolbox for charge and spin stabilization, we introduce regioisomerism as a scaffold-diversifying design element that considers the collective and cumulative electronic and steric contributions from all of the substituents based on their relative regioisomeric arrangements. Through a systematic study of regioisomers of near-planar aromatic cyclic triindoles and nonplanar nonaromatic cyclic tetraindoles, we demonstrate that this regioisomeric engineering strategy significantly enhances the H-cell cycling stability in the above two new classes of 2e – catholytes, even when current strategies failed to stabilize the multicharged species. Density functional theory calculations reveal that the strategy operates by redistributing the charge and spin densities while highlighting the role of aromaticity in charge stabilization. The most stable 2e – catholyte candidate was paired with a viologen derivative anolyte to achieve a proof-of-concept all-organic flow battery with 1.26–1.49 V, 98% capacity retention, and only 0.0117% fade/h and 0.00563% fade/cycle over 400 cycles (192 h), which is the highest capacity retention ever reported over 400 cycles in a multielectron all-organic flow battery setup. We anticipate regioisomeric engineering to be a promising strategy complementary to conventional electronic and steric approaches for multicharge and spin stabilization in other functional organic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

SOMAS: a platform for data-driven material discovery in redox flow battery development

Abstract Aqueous organic redox flow batteries offer an environmentally benign, tunable, and safe route to large-scale energy storage. The energy density is one of the key performance parameters of organic redox flow batteries, which critically depends on the solubility of the redox-active molecule in water. Prediction of aqueous solubility remains a challenge in chemistry. Recently, machine learning models have been developed for molecular properties prediction in chemistry and material science. The fidelity of a machine learning model critically depends on the diversity, accuracy, and abundancy of the training datasets. We build a comprehensive open access organic molecular database “Solubility of Organic Molecules in Aqueous Solution” (SOMAS) containing about 12,000 molecules that covers wider chemical and solubility regimes suitable for aqueous organic redox flow battery development efforts. In addition to experimental solubility, we also provide eight distinctive quantum descriptors including optimized geometry derived from high-throughput density functional theory calculations along with six molecular descriptors for each molecule. SOMAS builds a critical foundation for future efforts in artificial intelligence-based solubility prediction models.

25 ENERGY STORAGE↗
DOE OSTI2025

Dissociative electron recombination and rotational cooling of the deuterated triatomic hydrogen ions H 2 ⁡D + and D 2 ⁢H +

We have measured the dissociative recombination (DR) of the deuterated triatomic hydrogen ions H 2 ⁡D + and D 2 ⁢H + as a function of storage time at the Cryogenic Storage Ring (CSR). Both molecular ions were stored for up to 1000 s inside the cryogenic vacuum of the CSR prior to the electron recombination measurements, allowing them to cool to their lowest rotational states. We implement a comprehensive model for all relevant processes to predict the internal state evolution of the ions during storage inside the CSR, employing calculated radiative transition strengths and state-selective rate coefficients for electron collisions. Our DR rate coefficient measurements with deuterated triatomic hydrogen ions in defined quantum states allow for meaningful comparisons with state-of-the-art theoretical calculations, paving the way for a better understanding of the complex DR process for polyatomic molecular ions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Noninvasive measurements of spin transport properties of an antiferromagnetic insulator

Antiferromagnetic insulators (AFIs) are of substantial interest because of their potential in the development of next-generation spintronic devices. One major effort in this emerging field is to harness AFIs for long-range spin information communication and storage. Here, we report a noninvasive method to optically access the intrinsic spin transport properties of an archetypical AFI α-Fe 2 O 3 via nitrogen-vacancy (NV) quantum spin sensors. By NV relaxometry measurements, we successfully detect the frequency-dependent dynamic fluctuations of the spin density of α-Fe 2 O 3 along the Néel order parameter, from which an intrinsic spin diffusion constant of α-Fe 2 O 3 is experimentally measured in the absence of external spin biases. Our results highlight the significant opportunity offered by NV centers in diagnosing the underlying spin transport properties in a broad range of high-frequency magnetic materials such as two-dimensional magnets, spin liquids, and magnetic Weyl semimetals, which are challenging to access by the conventional measurement techniques.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules

Abstract Graph Convolutional Neural Network (GCNN) is a popular class of deep learning (DL) models in material science to predict material properties from the graph representation of molecular structures. Training an accurate and comprehensive GCNN surrogate for molecular design requires large-scale graph datasets and is usually a time-consuming process. Recent advances in GPUs and distributed computing open a path to reduce the computational cost for GCNN training effectively. However, efficient utilization of high performance computing (HPC) resources for training requires simultaneously optimizing large-scale data management and scalable stochastic batched optimization techniques. In this work, we focus on building GCNN models on HPC systems to predict material properties of millions of molecules. We use HydraGNN, our in-house library for large-scale GCNN training, leveraging distributed data parallelism in PyTorch. We use ADIOS, a high-performance data management framework for efficient storage and reading of large molecular graph data. We perform parallel training on two open-source large-scale graph datasets to build a GCNN predictor for an important quantum property known as the HOMO-LUMO gap. We measure the scalability, accuracy, and convergence of our approach on two DOE supercomputers: the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) and the Perlmutter system at the National Energy Research Scientific Computing Center (NERSC). We present our experimental results with HydraGNN showing (i) reduction of data loading time up to 4.2 times compared with a conventional method and (ii) linear scaling performance for training up to 1024 GPUs on both Summit and Perlmutter.

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

Maximizing Free Energy Gain

Maximizing the amount of work harvested from an environment is important for a wide variety of biological and technological processes, from energy-harvesting processes such as photosynthesis to energy storage systems such as fuels and batteries. Here, we consider the maximization of free energy—and by extension, the maximum extractable work—that can be gained by a classical or quantum system that undergoes driving by its environment. We consider how the free energy gain depends on the initial state of the system while also accounting for the cost of preparing the system. We provide simple necessary and sufficient conditions for increasing the gain of free energy by varying the initial state. We also derive simple formulae that relate the free energy gained using the optimal initial state rather than another suboptimal initial state. Finally, we demonstrate that the problem of finding the optimal initial state may have two distinct regimes, one easy and one difficult, depending on the temperatures used for preparation and work extraction. We illustrate our results on a simple model of an information engine.

Physics↗
DOE OSTI2025

Nanoscale Quantum Imaging of Field-Free Deterministic Switching of a Chiral Antiferromagnet

Recently, unconventional spin-orbit torques (SOTs) with tunable spin generation have opened new pathways for designing novel magnetization control for cutting-edge spintronics innovations. A leading research thrust is to develop field-free deterministic magnetization switching for implementing scalable and energy favorable magnetic recording and storage, which have been demonstrated in conventional ferromagnetic and antiferromagnetic material systems. Here, in this work, we extend this advanced magnetization control strategy to chiral antiferromagnet Mn 3 ⁢Sn using spin currents with out-of-plane canted polarization generated from low-symmetry van der Waals (vdW) material WTe 2 . Numerical calculations suggest that dampinglike SOT of spins injected perpendicular to the kagome plane of Mn 3⁢ Sn serves as a driving force to rotate the chiral magnetic order, while the fieldlike SOT of spin currents with polarization parallel to the kagome plane provides the bipolar deterministicity to the magnetic switching in the absence of an external magnetic field. We further introduce scanning quantum microscopy to visualize nanoscale evolutions of Mn 3 ⁢Sn magnetic domains during the field-free switching process, corroborating the exceptionally large magnetic switching ratio up to 90%. Our results highlight the opportunities provided by hybrid SOT material platforms consisting of noncollinear antiferromagnets and low-symmetry vdW spin source materials for developing next-generation spintronic logic devices.

2-dimesional systems↗
NASA NTRS1990

Efficiency of Nd laser materials with laser diode pumping

For pulsed laser-diode-pumped lasers, where efficiency is the most important issue, the choice of the Nd laser material makes a significant difference. The absorption efficiency, storage efficiency, and extraction efficiency for Nd:YAG, Nd:YLF, Nd:GSGG, Nd:BEL, Nd:YVO4, and Nd:glass are calculated. The materials are then compared under the assumption of equal quantum efficiency and damage threshold. Nd:YLF is found to be the best candidate for the application discussed here.

Barnes, Norman P.↗
DOE OSTI2022

Mid-Infrared Nonlinear Frequency Conversion Using Monolithic Barium Titanate on Silicon-on-Insulator

In this work, efficient nonlinear frequency conversion in the mid-infrared (mid-IR) region was demonstrated by a barium titanate (BTO) on a silicon-on-insulator (SOI) substrate. The BTO thin film was epitaxially grown by pulsed-laser deposition (PLD). The tensorial second order optical nonlinearity and the ferroelectric domain property of the BTO were characterized by the polarimetric mid-IR second harmonic generation (SHG) measurements. Azimuthal-dependent polarized SHG was modeled at different combinations of the nonlinear coefficient $d_{ij}$ and the domain fraction factor $ΔD^Y/ΔD^X$. Strong SHG intensity was experimentally observed over a broad spectrum at λ = 3.1 μm - 3.7 μm. A characteristic linear dependence between the SHG signal and the square of the pumping laser intensity was observed. The monolithic integration between the epitaxial BTO and the Si provides a compact platform for efficient on-chip light generation and quantum photonic technologies.

25 ENERGY STORAGE↗
DOE OSTI2022

Implementation of a Binary Neural Network on a Passive Array of Magnetic Tunnel Junctions

The increasing scale of neural networks and their growing application space have produced demand for more energy- and memory-efficient artificial-intelligence-specific hardware. Avenues to mitigate the main issue, the von Neumann bottleneck, include in-memory and near-memory architectures, as well as algorithmic approaches. In this report we leverage the low-power and the inherently binary operation of magnetic tunnel junctions (MTJs) to demonstrate neural network hardware inference based on passive arrays of MTJs. In general, transferring a trained network model to hardware for inference is confronted by degradation in performance due to device-to-device variations, write errors, parasitic resistance, and nonidealities in the substrate. To quantify the effect of these hardware realities, we benchmark 300 unique weight matrix solutions of a two-layer perceptron to classify the Wine dataset for both classification accuracy and write fidelity. Despite device imperfections, we achieve software-equivalent accuracy of up to 95.3% with proper tuning of network parameters in 15 x 15 MTJ arrays having a range of device sizes. The success of this tuning process shows that new metrics are needed to characterize the performance and quality of networks reproduced in mixed signal hardware.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Advanced Energy Storage for Extreme Conditions (AESTEC) (Abbreviated Final Report)

This project developed a new capability for designing and fabricating energy storage devices that function in extreme conditions detrimental to conventional devices (e.g. temperature, mechanical stress, etc.). This new toolset tackled critical phenomenological challenges which led to materials and designs that enable high performance energy storage in conditions relevant to national security missions and the broader energy storage community.

25 ENERGY STORAGE↗