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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Ad Hoc File Systems for High-Performance Computing

Storage backends of parallel compute clusters are still based mostly on magnetic disks, while newer and faster storage technologies such as flash-based SSDs or non-volatile random access memory (NVRAM) are deployed within compute nodes. Including these new storage technologies into scientific workflows is unfortunately today a mostly manual task, and most scientists therefore do not take advantage of the faster storage media. One approach to systematically include nodelocal SSDs or NVRAMs into scientific workflows is to deploy ad hoc file systems over a set of compute nodes, which serve as temporary storage systems for single applications or longer-running campaigns. This paper presents results from the Dagstuhl Seminar 17202 “Challenges and Opportunities of User-Level File Systems for HPC” and discusses application scenarios as well as design strategies for ad hoc file systems using node-local storage media. The discussion includes open research questions, such as how to couple ad hoc file systems with the batch scheduling environment and how to schedule stage-in and stage-out processes of data between the storage backend and the ad hoc file systems. Also presented are strategies to build ad hoc file systems by using reusable components for networking and how to improve storage device compatibility. Various interfaces and semantics are presented, for example those used by the three ad hoc file systems BeeOND, GekkoFS, and BurstFS. Their presentation covers a range from file systems running in production to cutting-edge research focusing on reaching the performance limits of the underlying devices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Understanding the Value of Energy Storage for Power System Reliability and Resilience Applications

Abstract Purpose of Review The need for energy storage in the electrical grid has grown in recent years in response to a reduced reliance on fossil fuel baseload power, added intermittent renewable investment, and expanded adoption of distributed energy resources. While the methods and models for valuing storage use cases have advanced significantly in recent years, the value of enhanced resilience remains an open research question. Recent Findings The findings of the recent research indicate that energy storage provides significant value to the grid, with median benefit values for specific use cases ranging from under $10/kW-year for voltage support to roughly $100/kW-year for capacity and frequency regulation services. While the value of lost load is used widely to estimate the benefits of mitigating short-duration outages, reaching as high as $719/kilowatt-year, there is no consensus when it comes to monetizing the value of improving grid resilience. Summary This paper presents a use case taxonomy for energy storage and uses the taxonomy to conduct a meta-analysis of an extensive set of energy storage valuation studies. It reviews several approaches for monetizing reliability and resiliency services and presents a proposed approach for valuing resiliency for energy storage investments.

25 ENERGY STORAGE↗
DOE OSTI2023

Ce nanoparticles and sol-gel hybrid organic-inorganic coatings maximize corrosion protection in the anodized AA2024-T3

Herein we demonstrate that the corrosion resistance of the AA2024-T3 alloy can be maximized with the application of top protective sol-gel hybrid organic-inorganic coatings. Samples combining Ce nanoparticles within the pores of the anodic layer with the top sol-gel coatings were observed to outperform samples featuring only the coating. This research unravels the self-healing capability against corrosion of the sol-gel coating when Ce nanoparticles are present, as well as a good coverage of defective regions within the oxide by the hybrid layer. This research opens a paradigm aiming at maximizing the corrosion resistance for non-ferrous anodized alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Anisotropic thermal-conductivity degradation in the phase-field method accounting for crack directionality

Dynamic loads applied to metals may lead to brittle or ductile fracture depending on the imposed strain rates, material properties, and specimen geometry. With an increase in the applied velocity, brittle to ductile failure mode transition may also be observed. Furthermore, at high strain rates, ductile fracture may be preceded by shear bands, which are narrow bands of intense plastic deformation, typically accompanied by a significant rise in temperature. Reliable models are needed to predict the response of metals subject to dynamic loads. In particular, capturing the interplay between heat conduction and crack propagation using the phase-field fracture method is still an open research field. To accurately capture the heat transfer physics across crack surfaces, damage models degrading thermal-conductivity are necessary. While isotropic thermal-conductivity degradation models were proposed, they may lead to errors as they are indifferent to crack directionality. In our current work, a new anisotropic approach is proposed in which thermal-conductivity, which depends on the phase-field gradient, is degraded solely across the crack. Here, it is shown that this approach improves the near-field approximation of temperature and heat flux compared with isotropic degradation, when taking the discontinuous crack solutions as reference. Additionally, the anisotropic degradation approach is implemented in a unified dynamic fracture model and a couple of examples demonstrate the viability of this approach.

42 ENGINEERING↗
DOE OSTI2021

Deep learning for Alzheimer's disease: Mapping large-scale histological tau protein for neuroimaging biomarker validation

Abnormal tau inclusions are hallmarks of Alzheimer's disease and predictors of clinical decline. Several tau PET tracers are available for neurodegenerative disease research, opening avenues for molecular diagnosis in vivo. However, few have been approved for clinical use. Understanding the neurobiological basis of PET signal validation remains problematic because it requires a large-scale, voxel-to-voxel correlation between PET and (immuno) histological signals. Large dimensionality of whole human brains, tissue deformation impacting co-registration, and computing requirements to process terabytes of information preclude proper validation. We developed a computational pipeline to identify and segment particles of interest in billion-pixel digital pathology images to generate quantitative, 3D density maps. The proposed convolutional neural network for immunohistochemistry samples, IHCNet, is at the pipeline's core. We have successfully processed and immunostained over 500 slides from two whole human brains with three phospho-tau antibodies (AT100, AT8, and MC1), spanning several terabytes of images. Our artificial neural network estimated tau inclusion from brain images, which performs with ROC AUC of 0.87, 0.85, and 0.91 for AT100, AT8, and MC1, respectively. Introspection studies further assessed the ability of our trained model to learn tau-related features. We present an end-to-end pipeline to create terabytes-large 3D tau inclusion density maps co-registered to MRI as a means to facilitate validation of PET tracers.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Stability and control of power systems with high penetrations of inverter-based resources: An accessible review of current knowledge and open questions

As power system renewable energy penetrations increase, the ways in which key renewable technologies such as wind and solar photovoltaics (PV) differ from thermal generators become more apparent. Many studies have examined the variability and uncertainty of such generators and described how generation and load can be balanced for a wide variety of annual energy penetrations, at timescales from seconds to years. Another important characteristic of these resources is asynchronicity, the result of using inverters to interface the prime energy source with the power system as opposed to synchronous generators. Unlike synchronous generators, whose frequency of alternating current (AC) injection is physically coupled to the rotation of the machine itself, inverter based asynchronous generators do not share the same physical coupling with the generated frequency. These subtle differences impact the operations of power systems developed around the characteristics of synchronous generators. In this paper we review current knowledge and open research questions concerning the interplay between asynchronous inverter-based resources (IBRs) and cycle- to second-scale power system dynamics, with a focus on how stability and control may be impacted or need to be achieved differently when there are high instantaneous penetrations of IBRs across an interconnection. This work does not seek to provide a comprehensive review of the latest developments, but is instead intended to be accessible to any reader with an engineering background and an interest in power systems and renewable energy. As such, the paper includes basic material on power electronics, control schemes for IBRs, and power system stability; and uses this background material to describe potential impacts of IBRs on power system stability, operational challenges associated with large amounts of distributed IBR generation, and modern power system simulation trends driven by IBR characteristics.

14 SOLAR ENERGY↗
DOE OSTI2022

Atomic Edge-Guided Polyethylene Crystallization on Monolayer Two-Dimensional Materials

In this report we combine an advanced synthesis of two-dimensional (2D) materials (MoSe 2 ) having well-defined atomic edge configurations with ab initio and atomistic molecular dynamics (MD) simulations to study how atomic edges interact with polyethylene (HDPE) chains in a dilute solution assembly process. Our results reveal that Mo-terminated zigzag (Mo-ZZ) edges act as preferred nucleation sites and strongly interact with HDPE chains. The HDPE chains align in parallel with the Mo-ZZ edges and form arrays of lamellae that are perpendicular to the edges. Interestingly, atomic edge configurations are observed to dramatically change such interactions. The crystallization discrepancy at different edges was demonstrated on the same piece of MoSe 2 with different types of edges. The ab initio and MD simulations between n-alkane (n = 5 and 25), a segment of HDPE, and MoSe 2 suggest that the atomic structures of MoSe 2 can affect their interactions with n-alkane chains. Following the Mo-ZZ edge preferred nucleation principle, controlled long-range alignment of HDPE lamellae can be realized by creating multilayer MoSe 2 with parallel atomic steps. This research opens a pathway toward an atomic level understanding of polymer–2D nanomaterial interactions. It also bridges the gap between atomic-level and long-range mesoscopic structures and introduces a novel strategy for long-range structural control.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Size-Dependent Thermal Shifts to MOF Nanocrystal Optical Gaps Induced by Dynamic Bonding

Conventional semiconductor nanocrystals exhibit wide-ranging optical behavior, whereas the size-dependent photophysical properties of metal–organic framework (MOF) nanocrystals remain an open research frontier. Furthermore, we present size- and temperature-dependent optical absorption spectra of common MOFs with particle sizes ranging from tens of nanometers to several micrometers. All materials exhibit optical gaps that decrease at elevated temperatures, which we attribute to the dynamic nature of MOF metal–linker bonds. Accordingly, whereas the labile titanium–carboxylate bonds of MIL-125 give rise to bandgaps that red-shift by ~600 meV over 300 K, the more rigid zinc–imidazolate bonds of ZIF-8 produce a red-shift of only ~10 meV. Furthermore, smaller particles induce far larger decreases to optical gaps. Taken together, these results suggest MOF bonding becomes more flexible with smaller nanocrystal sizes, offering a powerful tool for manipulating optical behavior through composition, temperature, and dimensionality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Tackling the Capacity Fading Issue of Li–S Battery by a Functional Additive—Hexafluorobenzene

Due to the strong electron-withdrawing fluorine groups, the aromatic ring of hexafluorobenzene (HFB) becomes more electron-deficient and strongly interacts with the lone-pair electrons of the medium. When used as an electrolyte additive for Li-S cell, HFB preferably coordinates with low-order lithium sulfides Li 2 S and Li 2 S 2 and subsequently reacts and converts both into active aromatic sulfides-bis(pentafluorophenyl) disulfides and bis-(pentafluorophenyl) polysulfides in situ-thus facilitating the utilization of the electronically insulating Li 2 S and Li 2 S 2 and improving the cycling stability of the Li-S cell. Finally, this research opens a new avenue to tackle the inherent issues associated with the Li-S chemistry.

25 ENERGY STORAGE↗
DOE OSTI2022

Enabling Silicon Anodes with Novel Isosorbide-Based Electrolytes

Silicon is seen as one of the most promising anode candidates for next-generation lithium-ion batteries, due to its high theoretical capacity and energy density. However, many technical barriers remain to its implementation, due to its high chemical/electrochemical reactivities with standard electrolytes and incomplete passivation from large volume changes. Herein, we report an isosorbide dimethyl ether (IDE) based electrolyte, which exhibits greatly improved stability, as evidenced by long cycle life and calendar life. An analysis of the cycled silicon surface shows minimal decomposition of organic species from IDE solvent, confirming that the electrolyte maintains a limited chemical reactivity with nucleophilic lithiated silicon (Li x Si). Here, this research opens up new avenues for designing new electrolytes which could ultimately enable the practical application of silicon anodes.

25 ENERGY STORAGE↗
DOE OSTI2024

Molecular Engineering Enabled Stable Deep Eutectic Amide-Based Electrolyte for High-Temperature Lithium–Metal Batteries

The development of advanced lithium-metal batteries (LMBs), such as high-temperature LMBs and high-energy-density LMBs, has critical requirements for electrolytes. However, conventional electrolytes suffer from thermal instability and insufficient electrolyte/Li interfacial compatibility, severely limiting their utilization in high-temperature LMBs. Herein, we design a high-temperature N-methylacetamide (NMAc)-based deep eutectic electrolyte (DEE) by molecular engineering on a solvation structure via a sacrificial additive of vinyl ethylene carbonate (VEC). Specifically, VEC interacts with the Li prior to NMAc, facilitating the formation of a solid electrolyte interphase to inhibit the reaction between Li and NMAc. The stable VEC-DEE effectively suppresses the growth of lithium dendrites and ensures the battery a cycling stability of 550 cycles at 80 °C. Additionally, we also demonstrate the application of VEC-DEE in high-energy-density LMBs with a high mass loading of 2.5 mAh/cm 2 . In conclusion, this research opens a new avenue for the rational design of advanced high-temperature electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2023

A “Floatilla” of Airborne Seismometers for Venus

Abstract Barometers floating on high‐altitude balloons in the relatively clement cloud layer on Venus could detect and characterize acoustic waves generated by seismic activity, avoiding the need for high‐temperature electronics required for surface seismology. Garcia et al. (2022, https://doi.org/10.1029/2022GL098844 ) recently demonstrated the detection of low‐frequency sound (infrasound) caused by earthquakes of magnitudes 7.3 and 7.5 from stratospheric balloons nearly 3,000 km away from the epicenter. They provided a preliminary demonstration of earthquake magnitude and location inversion, and the determination of S‐ and Rayleigh wave velocities using only their acoustic signature. Large earthquakes produce low‐frequency seismic waves that penetrate the interiors of planets; their detection at continental‐scale distances from a high‐vantage point demonstrates the feasibility of balloon‐based investigations of Venus' interior. We contextualize these results within the effort to perform seismology on Venus from balloons, discuss its limitations, and share perspectives on open research questions in this area.

Krishnamoorthy, Siddharth↗
DOE OSTI2026

Crowdsourcing the Frontier: Advancing Hybrid Physics‐ML Climate Simulation via a $\$$50,000 Kaggle Competition

Subgrid machine-learning (machine learning [ML]) parameterizations have the potential to introduce a new generation of climate models that incorporate the effects of higher-resolution physics without incurring the prohibitive computational cost associated with more explicit physics-based simulations. However, important issues, ranging from online instability to inconsistent online performance, have limited their operational use for long-term climate projections. To more rapidly drive progress in solving these issues, domain scientists and ML researchers opened up the offline aspect of this problem to the broader ML and data science community with the release of ClimSim, a NeurIPS Data sets and Benchmarks publication, and an associated Kaggle competition. This paper reports on the downstream results of the Kaggle competition by coupling emulators inspired by the winning teams' architectures to an interactive climate model (including full cloud microphysics, a regime historically prone to online instability) and systematically evaluating their online performance. Our results demonstrate that online stability in the low-resolution real-geography setting is reproducible across multiple diverse architectures, which we consider a key milestone. All tested architectures exhibit strikingly similar offline and online biases, though their responses to architecture-agnostic design choices (e.g., expanding the list of input variables) can differ significantly. Multiple Kaggle-inspired architectures achieve state-of-the-art results on certain metrics such as zonal mean bias patterns and global Root Mean Squared Error, indicating that crowdsourcing the essence of the offline problem is one path to improving online performance in hybrid physics-AI climate simulation.

Environmental sciences↗
DOE OSTI2025

Opening doors to physical sample tracking and attribution in Earth and environmental sciences

Physical samples and their associated data and metadata underpin scientific discoveries across disciplines and can enable new science when appropriately archived. However, there are significant gaps in current practices and infrastructure that prevent accurate provenance tracking, reproducibility, and attribution. For most samples, descriptive metadata are often sparse, inaccessible, or absent. Samples and associated data and metadata may also be scattered across numerous physical collections, data repositories, laboratories, data files, and papers with no clear linkage or provenance tracking as new information is generated over time. The Earth Science Information Partners (ESIP) Physical Samples Curation Cluster has therefore developed guidance for scientific authors on ‘Publishing Open Research Using Physical Samples.’ This involved synthesizing existing practices, gathering community feedback, and assessing real-world examples. We identified improvements needed to enable authors to efficiently cite and link Earth science samples and related data, and track their use. Our goal is to help improve discoverability, interoperability, and reuse of physical samples, and associated data and metadata. Though primarily focused on the needs of Earth and environmental sciences, these guidelines are broadly applicable.

58 GEOSCIENCES↗
DOE OSTI2021

Design and evaluation of a cyber‐physical testbed for improving attack resilience of power systems

Abstract A power system is a complex cyber‐physical system whose security is critical to its function. A major challenge is to model, analyse and visualise the communication backbone of the power systems concerning cyber threats. To achieve this, the design and evaluation of a cyber‐physical power system (CPPS) testbed called Resilient Energy Systems Lab (RESLab) are presented to capture realistic cyber, physical, and protection system features. RESLab is architected to be a fundamental platform for studying and improving the resilience of complex CPPS to cyber threats. The cyber network is emulated using Common Open Research Emulator (CORE), which acts as a gateway for the physical and protection devices to communicate. The physical grid is simulated in the dynamic time frame using Power World Dynamic Studio (PWDS). The protection components are modelled with both PWDS and physical devices including the SEL Real‐Time Automation Controller (RTAC). Distributed Network Protocol 3 (DNP3) is used to monitor and control the grid. Then, the design is exemplified and the tools are validated. This work presents four case studies on cyberattack and defence using RESLab, where we demonstrate false data and command injection using Man‐in‐the‐Middle and Denial of Service attacks and validate them on a large‐scale synthetic electric grid.

Sahu, Abhijeet↗
DOE OSTI2021

A boundary value “reservoir problem” and boundary conditions for multi-moment multifluid simulations of sheaths

Multifluid simulations of plasma sheaths are increasingly used to model a wide variety of problems in plasma physics ranging from global magnetospheric flows around celestial bodies to plasma–wall interactions in thrusters and fusion devices. For multifluid problems, accurate boundary conditions to model an absorbing wall that resolves a classical sheath remain an open research area. This work justifies the use of vacuum boundary conditions for absorbing walls to show comparable accuracy between a multifluid sheath and lower moments of a continuum-kinetic sheath.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Ion irradiation and modification: The role of coupled electronic and nuclear energy dissipation and subsequent nonequilibrium processes in materials

Understanding material responses to energy deposition from energetic charged particles is important for defect engineering, ion-beam processing, ion-beam analysis and modification, geologic aging, space exploration, and nuclear applications. As an incident ion penetrates a solid, its energy is transferred to electrons and to atomic nuclei of the solid. Much of this electronic energy deposition is subsequently transferred to the atomic structure via electron–phonon (e–ph) coupling, leading to local inelastic thermal spikes in which energy dissipation is influenced by the local environment. In addition, intense ionization can lead to high densities of localized electronic excitations in wide-bandgap materials and ceramics that can affect defect dynamics and atomic mobility. Specifically, energy exchange between electrons and atomic nuclei, along with localized electronic excitations, can lead to substantial competitive (ionization-induced annealing), additive (both electronic and nuclear energy depositions contributing to damage production), and synergistic (more damage than the sums of separate damage processes) effects. Although nonmonotonic effects of the e–ph coupling strength and athermal processes are demonstrated for pre-existing defects and residual damage during ion–solid interactions, there is limited understanding of when such electronic effects must be considered in atomic-scale models of damage production and evolution in a broad variety of materials. Complex ceramics and chemically disordered solid solution alloys with different constituent elements allow a systematic evaluation of defect dynamics and irradiation performance with increasing complexity. Current knowledge regarding tuning of bonding characteristics and chemical disorder to control atomic-level dynamics is reviewed. Although a lack of fundamental understanding obstructs the advancement of reliable predictions for ion beam material modification, it highlights challenges and opens research opportunities. Insights into the complex electronic and atomic correlations with extreme energy deposition will strengthen our ability to design materials and predict ion-irradiation-induced damage in a radiation environment, and they may pave the way to better control fundamental processes and design new material functionalities for advanced technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Near total reflection x-ray photoelectron spectroscopy: quantifying chemistry at solid/liquid and solid/solid interfaces

Near total reflection regime has been widely used in x-ray science, specifically in grazing incidence small angle x-ray scattering and in hard x-ray photoelectron spectroscopy (XPS). In this work, we introduce some practical aspects of using near total reflection (NTR) in ambient pressure XPS and apply this technique to study chemical concentration gradients in a substrate/photoresist system. Experimental data are accompanied by x-ray optical and photoemission simulations to quantitatively probe the photoresist and the interface with the depth accuracy of ~1 nm. Together, our calculations and experiments confirm that NTR XPS is a suitable method to extract information from buried interfaces with highest depth-resolution, which can help address open research questions regarding our understanding of concentration profiles, electrical gradients, and charge transfer phenomena at such interfaces. Furthermore, the presented methodology is especially attractive for solid/liquid interface studies, since it provides all the strengths of a Bragg-reflection standing-wave spectroscopy without the need of an artificial multilayer mirror serving as a standing wave generator, thus dramatically simplifying the sample synthesis.

solid/solid interface↗