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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 OSTI2025

Comparison of three measurement modalities for 3D characterization of manufactured features and process-induced porosity in titanium alloy additively manufactured parts

Nondestructive characterization of internal features and defects within complex components is vital for many industrial applications, particularly with the advent of additive manufacturing (AM) technologies. However, community understanding of the limitations of nondestructive methods such as X-ray Computed Tomography (CT) can be limited in certain industrial sectors as these may be emergent applications. In this paper, we investigate the limits of X-ray CT measurements and compare extracted data with mechanical polishing serial sectioning (MPSS) and confocal laser scanning microscopy (CLSM). The test object is an additively manufactured titanium alloy disk that contains both process-induced porosity and machined features, including focused ion beam milled features designed to probe the resolution limits of X-ray CT. Results show that each of these characterization techniques has advantages and disadvantages. We compare data acquisition times, spatial resolution, geometric measurement accuracy and defect visualization fidelity across these modalities to establish a practical framework.

Additive manufacturing↗
DOE OSTI2023

Engineering Self-Assembled Domain Asymmetry in Solvent Vapor Annealed Block Copolymer–Homopolymer Blend Films

Thin-film block copolymer (BCP) self-assembly is a powerful approach to generate highly uniform nanopatterns across large areas, yet the symmetries of these nanopatterns are constrained by the relative volume occupied by each polymer block. Here, we present a conceptually new approach to circumvent this limitation by combining homopolymer (HP) blending with solvent vapor annealing (SVA), demonstrated here for ternary blends of a near-symmetric BCP with athermal, low molar mass HPs. Screening of BCP–HP interactions by a weakly selective solvent promotes entropically driven delocalization of HP throughout both blocks and enables assembly of metastable lamellae for volume fractions as high as 0.78. Subsequent brief thermal annealing induces HPs to withdraw to their enthalpically favored domains, sharpening domain interfaces on a time scale much shorter than pattern coarsening. This renders lamellar nanopatterns with tunable widths that can be transferred to other materials with high fidelity. Furthermore, the persistence of the metastable asymmetric lamellae upon thermal annealing is sensitive to film confinement, as they are preserved in submonolayer films but transition to horizontal cylinders in films more than one monolayer thick. SVA using a strongly selective solvent results in assembled morphologies aligned closely with expectations based on the total polymer blend composition, underscoring the key role of BCP–HP interactions in dictating domain asymmetry. Overall, this work details important principles for using SVA to mediate BCP–HP interactions in thin films, thereby presenting opportunities to engineer pathways for the assembly of well-ordered nanopatterns with designer feature asymmetry for lithographic or nanotexturing applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Broadband Light Extraction from Near-Surface NV Centers Using Crystalline-Silicon Antennas

We use crystalline silicon (Si) antennas to efficiently extract broadband single-photon fluorescence from shallow nitrogen-vacancy (NV) centers in diamond into free space. Our design features relatively easy-to-pattern high-index Si resonators on the diamond surface to boost photon extraction by overcoming total internal reflection and Fresnel reflection at the diamond-air interface and providing modest Purcell enhancement, without etching or otherwise damaging the diamond surface. In simulations, ∼17 times more single photons are collected from a single NV center compared to the case without the antenna; in experiments, we observe an enhancement of ∼9 times, limited by spatial alignment between the NV and the antenna. Furthermore, our approach can be readily applied to other color centers in diamond, and more generally to the extraction of light from quantum emitters in wide-bandgap materials.

Antennas↗
DOE OSTI2024

Lithium Plating Characteristics in High Areal Capacity Li-Ion Battery Electrodes

Li-ion battery degradation and safety events are often attributed to undesirable metallic lithium plating. Since their release, Li-ion battery electrodes have been made progressively thicker to provide a higher energy density. However, the propensity for plating in these thicker pairings is not well understood. Herein, we combine an experimental plating-prone condition with robust mesoscale modeling to examine electrode pairings with capacities ranging from 2.5 to 6 mAh/cm 2 and negative to positive (N/P) electrode areal capacity ratio from 0.9 to 1.8 without the need for extensive aging tests. Using both experimentation and a mesoscale model, we identify a shift from conventional high state-of-charge (SOC) type plating to high overpotential (OP) type plating as electrode thickness increases. Further, these two plating modes have distinct morphologies, identified by optical microscopy and electrochemical signatures. We demonstrate that under operating conditions where these plating modes converge, a high propensity of plating exists, revealing the importance of predicting and avoiding this overlap for a given electrode pairing. Further, we identify that thicker electrodes, beyond a capacity of 3 mAh/cm 2 or thickness >75 μm, are prone to high OP, limiting negative electrode (NE) utilization and preventing cross-sectional oversizing the NE from mitigating plating. Here, it simply contributes to added mass and volume. The experimental thermal gradient and mesoscale model either combined or independently provide techniques capable of probing performance and safety implications of mild changes to electrode design features.

25 ENERGY STORAGE↗
DOE OSTI2023

Depolymerization of polyesters by a binuclear catalyst for plastic recycling

Plastics play an essential role in modern society, however, the relentless growth of their production is threatening both human health and ecosystems. As a result, there are intensive efforts in developing recycling technologies to repurpose waste plastics into the building blocks for valuable materials. Here we show a binuclear complex that can catalyze the degradation of polyethylene terephthalate (PET)-the most widely used polyester globally-and a wide spectrum of other plastics including polylactic acid (PLA), polybutylene adipate terephthalate (PBAT), polycaprolactone (PCL), polyurethane (PU) and Nylon 66. Inspired by hydrolases, the group of enzymes that catalyze bond cleavages with water, the present catalyst design features biomimetic Zn-Zn sites which activate the plastic, stabilize the key intermediate, and enable intramolecular hydrolysis. This synthetic catalyst delivers activities of 36 mg PET d -1 g catal -1 toward PET depolymerization at pH 8 and 40 oC, and of 577 g PET d -1 g catal -1 at pH 13 and 90 oC for scalable PET recycling. We further demonstrate the closed-loop production of a bottle-grade PET. This work presents a practical and viable solution to the sustainable management of plastics waste.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Proton-enabled biomimetic stabilization of small-molecule organic cathode in aqueous zinc-ion batteries

Small-molecule organic cathode materials offer flexible structural design features, high capacity and sustainable production. Nonetheless, the stability decrease due to the high solubility of the electrode materials especially under electrochemical cycling conditions limits their wide-range applications in energy storage technologies. Here we describe a nature-inspired strategy to address cathode stability via introduction of transient vinylogous amide hydrogen bond networks into the small-molecule organic electrode material hexaazatrianthranylene (HATA) embedded quinone (HATAQ). Thanks to the proton-enabled biomimetic mechanism, HATAQ exhibits unparalleled cycling stability, ultra-high capacity and rate capability in aqueous zinc-ion batteries, delivering 492 mA h g -1 at 50 mA g -1 and a reversible capacity of 199 mA h g -1 , corresponding to 99% retention at 20 A g -1 after 1000 cycles.

25 ENERGY STORAGE↗
DOE OSTI2026

Superionic conduction in solid polymer electrolytes – decoupling ion transport from segmental relaxation

Solvent-free, solid polymer electrolytes (SPEs) are promising candidates for next-generation, electrochemical energy storage systems due to their potential to enhance safety and performance, enable flexible device architectures, and streamline manufacturing processes. Conventional SPEs suffer from limited ionic conductivity due to the strong coupling between ion transport and (generally slow) polymer segmental relaxation. The realization of superionic conduction in SPEs, in which ions move faster than the structural relaxation of the polymers, requires a shift in design principles to promote this type of decoupled ion motion. In this perspective, we discuss how polymer architecture, ion–ion correlations, and ion–polymer interactions can unlock superionic behavior. We highlight several key design features, such as crystallinity, bulky side groups, high molecular weight, and percolating ionic aggregation, with a focus on creating low-barrier transport pathways in various polymer systems. We also demonstrate opportunities to combine polymer chemistry and data science through high-throughput and automated screening approaches to reveal how phase behavior, ion dynamics, and ionic interactions govern transport, thereby potentially enabling data-driven discovery of superionic polymer electrolyte materials.

Yang, Mengying [Univ. of Delaware, Newark, DE (Uni↗
DOE OSTI2023

A feasible path for the use of ferromagnetic josephson junctions in quantum circuits: The ferro-transmon

We discuss the capabilities of ferromagnetic (F) Josephson junctions (JJs) in a variety of layouts and configurations. The main goal is to demonstrate the potential of these hybrid JJs to disclose new physics and the possibility to integrate them in superconducting classical and quantum electronics for various applications. The feasible path towards the use of ferromagnetic Josephson junctions in quantum circuits starts from experiments demonstrating macroscopic quantum tunneling in NbN/GdN/NbN junctions with ferro-insulator barriers and with triplet components of the supercurrent, supported by a self-consistent electrodynamic characterization as a function of the barrier thickness. This has inspired further studies on tunnel ferromagnetic junctions with a different layout and promoted the first generation of ferromagnetic Al-based JJs, specifically Al/AlO x /Al/Py/Al. This layout takes advantage of the capability to integrate the ferromagnetic layer in the junction without affecting the quality of the superconducting electrodes and of the tunnel barrier. The high quality of the devices paves the way for the possible implementation of Al tunnel-ferromagnetic JJs in superconducting quantum circuits. These achievements have promoted the notion of a novel type of qubit incorporating ferromagnetic JJs. This qubit is based on a transmon design featuring a tunnel JJ in parallel with a ferromagnetic JJ inside a SQUID loop capacitively coupled to a superconducting readout resonator. In conclusion, the effect of an external RF field on the magnetic switching processes of ferromagnetic JJs has been also investigated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

VIPIR: A High-Throughput Drop-Weight Impact Instrument for Imaging the Initiation and Propagation of Reactions in Energetic Materials

Characterizing the handling safety and sensitivity of explosives has been a challenging area of study for over 60 years. Historically one of the most accessible and widely utilized experiments has been the drop-weight impact test, which involves dropping a weight on a small sample sandwiched between two anvils. Because this experiment generally only utilizes sound thresholds to determine whether or not a sample reacted, the physical and chemical properties governing sensitivity remain convolved. Better understanding of chemical and material characteristics is needed to give the chemistry and engineering communities a predictive tool to determine the handling sensitivity of explosives prior to pursuing expensive and potentially hazardous synthesis and formulation operations. Here, we are developing a high throughput drop tower instrument capable of imaging the deformation and flow of energetic materials during impact and the resulting thermal ignition and propagation events. This instrument is based on previous designs but has been modified for higher throughput and tailorable modifications in the future. Herein, we present key design features that enable high-speed visible and thermal imaging of explosive initiation by sub-shock impacts, as well as preliminary results in which ignition sites were observed in an erythritol tetranitrate sample.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Molecular dipole moment learning via rotationally equivariant derivative kernels in molecular-orbital-based machine learning

This study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) approach to modeling the contribution of electron correlation to dipole moments at the cost of Hartree–Fock computations. A MOB pairwise decomposition of the correlation part of the dipole moment is applied, and these pair dipole moments could be further regressed as a universal function of MOs. The dipole MOB features consist of the energy MOB features and their responses to electric fields. An interpretable and rotationally equivariant derivative kernel for Gaussian process regression (GPR) is introduced to learn the dipole moment more efficiently. The proposed problem setup, feature design, and ML algorithm are shown to provide highly accurate models for both dipole moments and energies on water and 14 small molecules. To demonstrate the ability of MOB-ML to function as generalized density-matrix functionals for molecular dipole moments and energies of organic molecules, we further apply the proposed MOB-ML approach to train and test the molecules from the QM9 dataset. The application of local scalable GPR with Gaussian mixture model unsupervised clustering GPR scales up MOB-ML to a large-data regime while retaining the prediction accuracy. In addition, compared with the literature results, MOB-ML provides the best test mean absolute errors of 4.21 mD and 0.045 kcal/mol for dipole moment and energy models, respectively, when training on 110 000 QM9 molecules. The excellent transferability of the resulting QM9 models is also illustrated by the accurate predictions for four different series of peptides.

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

Radiation drive designed to extend the pressure ranges measured in Gbar equation of state experiments at the National Ignition Facility

We present the design and demonstration of a Shock-Strengthening hohlraum radiation temperature drive in the Gbar experimental platform at the National Ignition Facility intended to increase the pressure range measured in a single experiment. Previously published experiments by Döppner et al. measured the equation of state in polystyrene from 25 to 60 Mbar. Recent experimental data of the Shock-Strengthening drive initially demonstrated a much larger pressure range from 15 to 110 Mbar using the same peak radiation temperature and experimental platform. The Shock-Strengthening drive starts with a low temperature foot that launches a weak shock into the sample and is followed by a continuous increase in radiation temperature to strengthen the leading shock. The additional strengthening increases the pressure within the sample beyond what is achievable by convergence alone. Design features of the Shock-Strengthening drive and accompanying radiation hydrodynamics simulations are used to illustrate the method by which the pressure range is increased from previous experiments. This method of modifying the radiation temperature drive can be used on the Gbar platform to significantly increase the range for equation of state data collected in a single experiment for many materials.

Physics - Plasma physics↗
DOE OSTI2022

$\mathrm{T}$ransient $\mathrm{CHI}$ System Design Studies for $\mathrm{P}$ EGASUS -$\mathrm{III}$

We report transient coaxial helicity injection (transient CHI), first developed on the Helicity Injected Torus-II (HIT-II) and later on the National Spherical Torus Experiment (NSTX) for implementing solenoid-free plasma current startup capability in a spherical tokamak (ST), is now planned to be tested on the Pegasus-III ST using a novel double-biased configuration. Such a configuration is likely needed for transient CHI deployment in a reactor. The transient CHI system optimization will be studied on Pegasus-III to enable startup toroidal persisting currents at the limits permitted by the external poloidal field coils. A transient CHI discharge is generated by driving injector current along magnetic field lines that connect the inner and outer divertor plates on one end of the ST. Simulations using the Tokamak Simulation Code are used to assess the transient CHI toroidal current generation potential and electrode gap location on the Pegasus-III. While past transient CHI systems have used high-voltage, oil-filled capacitors for driving the injector current, for improved safety, Pegasus-III will use a high-current capacitor bank based on low-voltage electrolytic capacitors. The designed and fabricated system is capable of over 32 kA. The modular design features permit the system to be upgraded to higher currents, as needed, to meet the future needs of the Pegasus-III facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Coupling Shared E-scooters and Public Transit: A Spatial and Temporal Analysis

The integration of shared e-scooters with public transit is a promising solution for urban mobility's first/last-mile challenge. This study explores spatiotemporal factors influencing this integration, using 35-day e-scooter trip data from Chicago. Employing a random-effect negative binomial approach, we modeled the frequency of e-scooter trips to access/egress to/from bus stops and train stations. Results indicate that weather conditions, design features like intersection density, and multimodal network density significantly influence usage. The transit system characteristics such as service frequency have a positive effect on the integration of e-scooters and trains while a similar effect for bus and e-scooter integration was not significant. Furthermore, safety-related variables such as accident and crime rates as well as demographic characteristics were also revealed to be significant factors in our study. These findings offer vital insights to urban planners and policymakers for infrastructure, safety enhancements, and interventions to encourage efficient e-scooter-public transit integration.

Chicago↗
DOE OSTI2022

CRISPR–Cas9-mediated nuclear transport and genomic integration of nanostructured genes in human primary cells

DNA nanostructures are a promising tool to deliver molecular payloads to cells. DNA origami structures, where long single-stranded DNA is folded into a compact nanostructure, present an attractive approach to package genes; however, effective delivery of genetic material into cell nuclei has remained a critical challenge. Here, we describe the use of DNA nanostructures encoding an intact human gene and a fluorescent protein encoding gene as compact templates for gene integration by CRISPR-mediated homology-directed repair (HDR). Our design includes CRISPR–Cas9 ribonucleoprotein binding sites on DNA nanostructures to increase shuttling into the nucleus. We demonstrate efficient shuttling and genomic integration of DNA nanostructures using transfection and electroporation. These nanostructured templates display lower toxicity and higher insertion efficiency compared to unstructured double-stranded DNA templates in human primary cells. Furthermore, our study validates virus-like particles as an efficient method of DNA nanostructure delivery, opening the possibility of delivering nanostructures in vivo to specific cell types. Together, these results provide new approaches to gene delivery with DNA nanostructures and establish their use as HDR templates, exploiting both their design features and their ability to encode genetic information. This work also opens a door to translate other DNA nanodevice functions, such as biosensing, into cell nuclei.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

182 W (𝑛,2⁢𝑛)⁢ 181 W cross-section data from threshold to 15 MeV

Measurements of the 182 W(n, 2n) 181 W cross section have been performed in the neutron energy range between 8 and 15 MeV using the activation technique. Such data are needed to help interpret results of laser shots at the National Ignition Facility using a new DT capsule design, featuring a high-Z inner shell, with tungsten as the favored material, and an outer shell made of a low-Z material. Our data are in very good agreement with the previous data of Frehaut et al., which are based on a different technique, and in fair agreement with the ENDF/B-VIII.0 and the JEFF-3.3 evaluations.

150 ≤ A ≤ 189↗
DOE OSTI2024

Power Profile Monitoring and Tracking Evolution of System-Wide HPC Workloads

The power & energy demands of HPC machines have grown significantly. Modern exascale HPC systems require tens of megawatts of combined power for computing resources and cooling facilities at full capacity. The current energy trend is not sustainable for future HPC systems, and there is a need to work toward the energy efficiency aspect of HPC performance. Energy awareness of the HPC applications at the job level is essential for running an efficient HPC system. This work aims to develop a pipeline to provide a production-level system-wide overview of the HPC workloads' power profile while handling evolving workloads exhibiting new power trends. We developed an open-set classification model for HPC jobs based on the properties of power profiles to continuously provide a system-wide holistic view of recently completed jobs. The pipeline helps continuously monitor the job-level power usage pattern of HPC and enables us to capture the new trends in applications' power behavior. We employed a comprehensive set of techniques to generate job-level data, custom-designed feature extraction methods to extract critical features from jobs' power profiles, clustering techniques powered by generative modeling, and open-set classification for identifying job profiles into known classes or an unknown set. With extensive evaluations, we demonstrate the effectiveness of each component in our pipeline. We provide an analysis of the resulting clusters that characterize the power profile landscape of the Summit supercomputer from more than 60K jobs executed in a year. The open-set classification classifies the known data sets into known classes with high accuracy and identifies unknown data noints with over 85% accuracy.

Karimi, Ahmad Maroof↗
DOE OSTI2024

Performance on HPC Platforms Is Possible Without C++

Computing at large scales has become extremely challenging due to increasing heterogeneity in both hardware and software. More and more scientific workflows must tackle a range of scales and use machine learning and AI intertwined with more traditional numerical modeling methods, placing more demands on computational platforms. These constraints indicate a need to fundamentally rethink the way computational science is done and the tools that are needed to enable these complex workflows. The current set of C++-based solutions may not suffice, and relying exclusively upon C++ may not be the best option, especially because several newer languages and boutique solutions offer more robust design features to tackle the challenges of heterogeneity. In June 2023, we held a mini symposium that explored the use of newer languages and heterogeneity solutions that are not tied to C++ and that offer options beyond template metaprogramming and Parallel. For for performance and portability. In conclusion, we describe some of the presentations and discussion from the mini symposium in this article.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

An Open-Source Python Package for CFD Solution Verification

Informed decision-making using computational fluid dynamics (CFD) results requires quantifying the errors and uncertainties of a simulation. Verification, validation, and uncertainty quantification (VVUQ) methods were developed to address this need and have matured. However, these VVUQ analyses are often non-trivial and require CFD analysts and practitioners to have specific skill sets. This has led to the uneven adoption of VVUQ analyses, in part, based on the availability of software tools to aid CFD analysts and practitioners. Solution verification, a procedure to evaluate the accuracy of a simulation by estimating potential errors arising from the computational model and computing the uncertainties without comparing to results from a physical system, is one of the lagging VVUQ analyses as the absence of software has forced CFD analysts and practitioners to develop their own codes or piece together incomplete software from across the internet. This work presents an opensource Python package, CFDverify, to lower the barrier of entry and fill in the technological gap in solution verification. CFDverify also provides a streamlined framework to remove some potential errors in post-processing CFD results. The hope is that CFDverify can improve the quality and quantity of CFD solution verification in scientific and research studies and attract interest in developing a communal tool. This paper describes the design, features, and an example use of CFDverify.

Weinmeister, Justin [ORNL] (ORCID:0000000160090237↗