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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Stable electrolyte for high voltage electrochemical double-layer capacitors

A simple electrolyte consisting of NaPF 6 salt in 1,2-dimethoxyethane (DME) can extend the voltage window of electric double-layer capacitors (EDLCs) to >3.5 V. DME does not passivate carbon electrodes at very negative potentials (near Na/Na + ), extending the practical voltage window by about 1.0 V compared to standard, non-aqueous electrolytes based on acetonitrile. The voltage window is demonstrated in two- and three-electrode cells using a combination of electrochemical impedance spectroscopy (EIS), charge-discharge cycling, and measurements of leakage current. DME-based electrolytes cannot match the high conductivity of acetonitrile solutions, but they can satisfy applications that demand high energy density at moderate power. The conductivity of NaPF 6 in DME is comparable to commercial lithium-ion battery electrolytes and superior to most ionic liquids. Lastly, factors that limit the voltage window and EDLC energy density are discussed, and strategies to further boost energy density are proposed.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2018

Selecting the Best Graphite for Long-Life, High-Energy Li-Ion Batteries

Here, most lithium-ion batteries still rely on intercalation-type graphite materials for anodes, so it is important to consider their role in full cells for applications in electric vehicles. Here, we systematically evaluate the chemical and physical properties of six commercially-available natural and synthetic graphites to establish which factors have the greatest impact on the cycling stability of full cells with nickel-rich LiNi0.8Mn0.1Co0.1O2 (NMC811) cathodes. Electrochemical data and post-mortem characterization explain the origin of capacity fade. The NMC811 cathode shows large irreversible capacity loss and impedance growth, accounting for much of full cell degradation. However, six graphite anodes demonstrate significant differences with respect to structural change, surface area, impedance growth, and SEI chemistry, which impact overall capacity retention. We found long cycle life correlated most strongly with stable graphite crystallite size. In addition, graphites with lower surface area generally had higher coulombic efficiencies during formation cycles, which led to more stable long-term cycling. The best graphite screened here enables a capacity retention around 90% in full pouch cells over extensive long-term cycling compared to only 82% for cells with the lowest performing graphite. The results show that optimal graphite selection improves cycling stability of high energy lithium-ion cells.

25 ENERGY STORAGE↗
DOE OSTI2017

Mixed polyanion glass cathodes: Effect of polyanion content

Mixed polyanion glass cathodes in lithium-ion batteries have very high capacities (200-500 mAh/g), but currently these materials have fundamental problems with 1 st -cycle irreversible loss, cycling efficiency, and capacity fade. It is well established that polyanion substitutions into glasses can dramatically affect their physical properties, but the effect of polyanion content on the electrochemical performance has not been previously established. The proper amount of lithium and borate substitution in copper phosphate/vanadate glasses was shown to nearly eliminate 1 st -cycle irreversible loss and improve cycling efficiency. As a result, Raman and IR spectroscopy were used to identify polyanions that correlated with electrochemical performance changes.

25 ENERGY STORAGE↗
DOE OSTI2018

Probing Electrode-Electrolyte Interfaces Using Nano-Gap Surface-Enhanced Raman Spectroscopy and Imaging

Performance of portable electronic devices and electric vehicles is currently limited by the energy density, lifetime and safety of lithium rechargeable batteries. Overcoming those limitations requires in-depth understanding of the electrode-electrolyte interfaces. Surface-enhanced Raman spectroscopy (SERS) can provide a critical component to this effort as an in situ technique with ultrahigh surface sensitivity that provides quantitative molecular specificity. SERS relies on local electromagnetic field amplification generated by surface plasmon resonance (SPR) at the surface of metal nanoparticles (NPs) with sub-wavelength dimensions. The most significant Raman enhancements have been observed when the local SPRs of multiple NPs interact. This occurs when the NPs are in close proximity (less than 10 nm), which could be achieved in ordered NP monolayers if they could be assembled reproducibly. Methods to assemble gold NPs into large area (cm2) monolayers will be presented. The interparticle gap can be tuned between 1 and 4 nm by using surface ligands of different sizes. The Au NP monolayers exhibit high SERS sensitivity (enhancement factor greater than 107). This allows for the measurement of electrolyte components across a broad range of concentrations. Components include lithium hexafluorophosphate (LiPF6), fluoroethylene carbonate (FEC), ethylene carbonate (EC) and diethyl carbonate (DEC). The investigation of solutions of LiPF6 in EC + DEC binary solvents using SERS allows for the determination of the solvent coordination numbers, which range from 2 to 5. This result is in sharp contrast to the bulk values calculated from infrared spectroscopy, which range from 3 to 7. Numerical simulations show that the electromagnetic field is concentrated in the nanogap, indicating the information of the aprotic electrolyte solution structures is obtained from the immediately adjacent area of the solid substrate. Our findings facilitate a better understanding of the structure of solvated ions in close proximity to the electrode surface.

Yang, Guang↗
DOE OSTI2015

Fabrication and Characterization of CNT‐Based Smart Tips for Synchrotron Assisted STM

Determination of chemical composition along with imaging at the atomic level provides critical information towards fundamental understanding of the surface of materials and, hence, yields the capability to design new materials by tailoring their ultimate functionalities. Synchrotron X‐ray assisted scanning tunneling microscopy (SX‐STM) is a promising new technique to achieve real space chemically specific atomic mapping. Chemical sensitivity of SX‐STM relies on excitation of core electrons by incident X‐rays when their energy is tuned to an absorption edge of a particular element. However, along with core‐level electrons, photoelectrons are also excited, which yield additional current and interfere with the tunneling current. To reduce the background photoelectron current and to improve ultimate resolution of SX‐STM, we have developed and fabricated multiwalled carbon nanotubes (MWCNT) based “smart tips” using plasma enhanced chemical vapor deposition and focused ion beam milling. The newly developed CNT‐based smart tips, characterized step by step by scanning electron microscopy (SEM) during the fabrication process, demonstrate good performance and provide opportunity for realizing atomic chemical mapping.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Single-particle imaging without symmetry constraints at an X-ray free-electron laser

Coherent soft X-ray diffraction images and reconstructions of coliphage PR772 virus, collected at the Atomic Molecular Optics (AMO) beamline with pnCCD detectors in the LAMP instrument at the Linac Coherent Light Source. The data is classified into single particle hits. The original unclassified dataset can be found in [http://cxidb.org/id-58.html](http://cxidb.org/id-58.html).

AMO↗
DOE OSTI2019

Bead-Tracking Toolbox for MATLAB

A collection of MATLAB scripts forming a toolbox for video (frame by frame) detection and tracking of beads imaged with fluorescence microscope for estimating bead flow and location tracks. Scripts accept tiff image stacks of video frames and provide bead locations and tracked positions over frames in stack. Various utility functions are also provided to assist in data I/O. A custom solution for specific data source - specifically, the software works well for noisy/out of focus florescence microscopy images.

Rose, DerekC.↗
DOE OSTI2025

PickerXL

Python scripts for using the PickerXL model, which operates on seismic single station data to pick primary and secondary waves.

Chai, Chengping [Oak Ridge National Laboratory (OR↗
DOE OSTI2025

viral_fam_classifier

This code applies publicly available Hidden Markov Model (HMM) profiles to publicly available reference genomes of viruses. It parses the output of these searches to determine bitscore cut-offs for viral taxonomic lineages that may be represented by each HMM. Subsequently, the code will allow the user to classify novel viral sequences using these bitscore cut-offs. This code is a work-in-progress.

Kantor, Rose [Lawrence Livermore National Laborato↗
DOE OSTI2025

WaveDenoiser

We developed a robust deep learning model to effectively reduce background noise in the time domain from seismic waveforms. The deep learning model processes a 57-second three-component seismogram to predict and generate a denoised seismogram. The training was conducted using the benchmark STEAD dataset, which comprises globally distributed earthquake signals recorded at local distances ranging from 0 to 350 kilometers.

Chai, Chengping [Oak Ridge National Laboratory (OR↗
DOE OSTI2026

WaveDP

We developed a robust deep learning model designed to effectively reduce background noise and measure signal arrival times from seismic waveforms. This model processes a 57-second, three-component seismogram to predict the probability of Primary (P) and Secondary (S) waves for each timestamp, while also generating a denoised seismogram. Training was conducted using the benchmark STEAD dataset, which includes globally distributed earthquake signals recorded at local distances ranging from 0 to 350 kilometers.

Chai, Chengping [Oak Ridge National Laboratory (OR↗
DOE OSTI2026

wastewater_virus

This repo contains software used to clean and assemble high-throughput sequencing data containing viruses. The input is raw illumina sequencing reads and the output is a database of high-quality viral genomes. The specific application is to wastewater viral concentrates but it is not restricted to that sample type. The software is composed of Nextflow workflows and a set of custom Python and bash scripts that call publicly available bioinformatics tools to accomplish obvious tasks in data analysis in a high performance computing environment. For detailed information, please see the repo's README file.

Kantor, Rose [Lawrence Livermore National Laborato↗
DOE OSTI2022

A MUC 5 B Gene Polymorphism, rs35705950-T, Confers Protective Effects Against COVID-19 Hospitalization but Not Severe Disease or Mortality

A common MUC5B gene polymorphism, rs35705950-T, is associated with idiopathic pulmonary fibrosis (IPF), but its role in severe acute respiratory syndrome coronavirus 2 infection and disease severity is unclear. To assess whether rs35705950-T confers differential risk for clinical outcomes associated with coronavirus disease (COVID-19) infection among participants in the Million Veteran Program (MVP). The MUC5B rs35705950-T allele was directly genotyped among MVP participants; clinical events and comorbidities were extracted from the electronic health records. Associations between the incidence or severity of COVID-19 and rs35705950-T were analyzed within each ancestry group in the MVP followed by transancestry meta-analysis. Replication and joint meta-analysis were conducted using summary statistics from the COVID-19 Host Genetics Initiative (HGI). Sensitivity analyses with adjustment for additional covariates (body mass index, Charlson comorbidity index, smoking, asbestosis, rheumatoid arthritis with interstitial lung disease, and IPF) and associations with post–COVID-19 pneumonia were performed in MVP subjects. The MUC5B variant rs35705950-T may confer protection in COVID-19 hospitalizations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

A Global Repository for Planet-Sized Experiments and Observations

Greenland’s ice loss doubled between 1996 and 2005. Nine of the ten warmest years on record have occurred since 2000. Carbon dioxide levels in the air are at their highest in 650,000 years. Are these phenomena related, and if so, what can they tell us about the Earth’s climate in the coming years and decades? The answer will require sophisticated computer models—and a way of dealing with the data they produce. Past climate patterns can be discerned by examining variables such as temperature and precipitation records, lake sediments, tree rings, and ice cores. Projecting future regional and global climate patterns, however, requires computer models that can simulate the complex interplay between physical, chemical, and biological processes occurring in the atmosphere, ocean, and on land and sea ice. These models are extremely computationally demanding. Over the past several decades, an ongoing revolution in high-capacity, high-performance computing has accelerated climate modeling. In 1998, a 1-year simulation of global climate using a 300- kilometer grid could be run in a day. In 2002, it took 4 or 5 hours. In 2015, this same model can be run on a high-end desktop in minutes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

The Global Aerosol Synthesis and Science Project (GASSP): Measurements and Modeling to Reduce Uncertainty

The largest uncertainty in the historical radiative forcing of climate is caused by changes in aerosol particles due to anthropogenic activity. Sophisticated aerosol microphysics processes have been included in many climate models in an effort to reduce the uncertainty. However, the models are very challenging to evaluate and constrain because they require extensive in situ measurements of the particle size distribution, number concentration, and chemical composition that are not available from global satellite observations. The Global Aerosol Synthesis and Science Project (GASSP) aims to improve the robustness of global aerosol models by combining new methodologies for quantifying model uncertainty, to create an extensive global dataset of aerosol in situ microphysical and chemical measurements, and to develop new ways to assess the uncertainty associated with comparing sparse point measurements with low-resolution models. GASSP has assembled over 45,000 hours of measurements from ships and aircraft as well as data from over 350 ground stations. The measurements have been harmonized into a standardized format that is easily used by modelers and nonspecialist users. Available measurements are extensive, but they are biased to polluted regions of the Northern Hemisphere, leaving large pristine regions and many continental areas poorly sampled. The aerosol radiative forcing uncertainty can be reduced using a rigorous model–data synthesis approach. Nevertheless, our research highlights significant remaining challenges because of the difficulty of constraining many interwoven model uncertainties simultaneously. Although the physical realism of global aerosol models still needs to be improved, the uncertainty in aerosol radiative forcing will be reduced most effectively by systematically and rigorously constraining the models using extensive syntheses of measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Investigation of the Residual in Column-Integrated Atmospheric Energy Balance Using Cloud Objects

Observationally based atmospheric energy balance is analyzed using Clouds and the Earth’s Radiant Energy System (CERES)-derived TOA and surface irradiance, Global Precipitation Climatology Project (GPCP)-derived precipitation, dry static and kinetic energy tendency and divergence estimated from ERA-Interim, and surface sensible heat flux from SeaFlux. The residual tends to be negative over the tropics and positive over midlatitudes. A negative residual implies that the precipitation rate is too small, divergence is too large, or radiative cooling is too large. The residual of atmospheric energy is spatially and temporally correlated with cloud objects to identify cloud types associated with the residual. Spatially, shallow cumulus, cirrostratus, and deep convective cloud-object occurrence are positively correlated with the absolute value of the residual. The temporal correlation coefficient between the number of deep convective cloud objects and individual energy components, net atmospheric irradiance, precipitation rate, and the sum of dry static and kinetic energy divergence and their tendency over the western Pacific are 0.84, 0.95, and 0.93, respectively. However, when all energy components are added, the atmospheric energy residual over the tropical Pacific is temporally correlated well with the number of shallow cumulus cloud objects over tropical Pacific. Because shallow cumulus alters not enough atmospheric energy compared to the residual, this suggests the following: 1) if retrieval errors associated with deep convective clouds are causing the column-integrated atmospheric energy residual, the errors vary among individual deep convective clouds, and 2) it is possible that the residual is associated with processes in which shallow cumulus clouds affect deep convective clouds and hence atmospheric energy budget over the tropical western Pacific.

54 ENVIRONMENTAL SCIENCES↗