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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

3D printed polymer gaskets for custom-form batteries

Additive manufacturing (AM) processes, like 3D printing, help to facilitate complex and customizable battery geometries which can provide design freedom and enhance volumetric energy density within electronic devices. AM materials must have the thermal and mechanical properties that enable printability, and when used in batteries, AM materials must also be chemically and electrochemically compatible with the battery chemistry. The compatibility between AM materials and the battery is of particular importance for the cell packaging materials which must be inert and are often overlooked. This study systematically studies AM-compatible polymeric materials for use as gaskets in lithium-ion cells. The materials investigated include three thermoplastics suitable for material extrusion printing: polylactic acid (PLA), polycarbonate, and polypropylene/polyethylene copolymer (PPPEC); and two photoresins suitable for vat photopolymerization (VPP) printing: an acrylate-based photoresin and a polyethylene glycol diacrylate photoresin. The AM gasket materials were tested in comparison to a conventional commercial polypropylene gasket. Mechanical testing (swell measurements and material stiffness) and electrochemical testing (linear sweep voltammetry and galvanostatic cycling of full cells) demonstrated that PLA and the VPP polymers were the least compatible with the lithium-ion battery chemistry, despite their prevalent use in studies of AM batteries, and that PPPEC was the most compatible.

3D printing↗
DOE OSTI2020

Active-Site Environmental Factors Customize the Photophysics of Photoenzymatic Old Yellow Enzymes

The development of non-natural photoenzymatic systems has reinvigorated the study of photoinduced electron transfer (ET) within protein active sites, providing new and unique platforms for understanding how biological environments affect photochemical processes. Here, we use ultrafast spectroscopy to compare the photoinduced electron transfer in known photoenzymes. 12-Oxophytodienoate reductase 1 (OPR1) is compared to Old Yellow Enzyme 1 (OYE1) and morphinone reductase (MR). The latter enzymes are structurally homologous to OPR1. We find that slight differences in the amino acid composition of the active sites of these proteins determine their distinct electron-transfer dynamics. Our work suggests that the inside of a protein active site is a complex/heterogeneous dielectric network where genetically programmed heterogeneity near the site of biological ET can significantly affect the presence and lifetime of various intermediate states. Our work motivates additional tunability of Old Yellow Enzyme active-site reorganization energy and electron-transfer energetics that could be leveraged for photoenzymatic redox approaches.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Forced Crowding of Colloids by Thermophoresis and Convection in a Custom Liquid Clusius–Dickel Microdevice

Here, we report a study demonstrating that simultaneous induction of a steady-state convection current and temperature gradient in a confined geometry can be an effective way to force crowding of dissolved particulates. To investigate this thermogravitationally driven concentration of particles in-situ, we developed a micro-device capable of sustaining controlled transverse temperature gradients within a 5 cm long, 0.1 mm inner diameter capillary that allowed visualization of particle movement with standard optical microscopy. Experiments were conducted on two material systems representative of nano-scale small molecules and micro-scale particles. With the small molecules (aromatic dyes, 530-790 g/mol, 1-1.5 nm) thermophoretic and gravitational effects in the micro-device resulted in an asymmetrical 2x concentration change along the capillary height over 3 days. In contrast, the concentration change under similar conditions for 40-micron diameter latex colloids is 50-fold in 30 minutes. This dramatic difference in separation times is consistent with simulations and models of thermophoresis where the thermophoretic effect scales with particle size. Induced crowding of particulates leads to formation of accumulation and depletion zones in at the bottom and top of the capillary respectively. Both the concentration of dye molecules over time in the depletion zone and spatial distribution of colloids over the entire capillary length were found to be good fits to simple first-order exponential decay functions. Furthermore, these results suggest potential applications of thermogravitational separation in developing new functional materials via thermophoretic and convective effects.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Customized metallodielectric colloids and their behavior in dielectrophoretic fields

A synthetic strategy for fabricating colloidal particles with spatially segregated amine-functionalized lobes enables regioselective coating with gold to afford metallodielectric particles with a variety of shapes and lobe sizes. This approach can produce either dissymmetric dumbbell-shaped two-lobed Au-TPM particles (Au-T) or dissymmetric or symmetric three-lobed particles with gold coating on one (Au-T-T and T-Au-T) or two lobes (Au-T-Au). Dielectrophoretic (DEP) forces exerted by an AC field confined between two opposing electrodes generate aggregates ranging from 1D chains to 2D close-packed lattices, depending on the particle shape and lobe arrangement. Furthermore, the aggregate structures reflect the lowest energy configurations resulting from the induced dipole moments created in particle lobes within the confined electric field.

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

Time-tagging data acquisition system for testing superconducting electronics based on an RFSoC and custom analog frontend

Novel electronic devices can often be operated in a plethoraof ways, which makes testing circuits comprised of them difficult.Often, no single tool can simultaneously analyze the operatingmargins, maximum speed, and failure modes of a circuit, particularlywhen the intended behavior of subcomponents of the circuit is notstandardized. This work demonstrates a cost-effective time-domaindata acquisition system for electronic circuits that enables moreintricate verification techniques than are practical withconventional experimental setups. We use high-speeddigital-to-analog converters and real-timemulti-gigasample-per-second waveform processing to push experimentalcircuits beyond their maximum operating speed. Our customtime-tagging data capture firmware reduces memory requirements andcan be used to determine when errors occur. The firmware iscombined with a thermal-noise-limited analog frontend with50 dB of dynamic range. Compared to currentlyavailable commercial test equipment that is seven times moreexpensive, this data acquisition system was able to operate asuperconducting shift register at a nearly three-times-higher clockfrequency (200 MHz vs. 80 MHz).

Foster, Reed A. [MIT] (ORCID:0000000231002127)↗
DOE OSTI2024

Training custom light curve models of SN Ia subpopulations selected according to host galaxy properties

ABSTRACT Type Ia supernova (SN Ia) cosmology analyses include a luminosity step function in their distance standardization process to account for an observed yet unexplained difference in the post-standardization luminosities of SNe Ia originating from different host galaxy populations [e.g. high-mass ($M \gtrsim 10^{10} \, {\rm M}_{\odot }$) versus low-mass galaxies]. We present a novel method for including host-mass correlations in the SALT3 (Spectral Adaptive Light curve Template 3) light curve model used for standardizing SN Ia distances. We split the SALT3 training sample according to host-mass, training independent models for the low- and high-host-mass samples. Our models indicate that there are different average Si ii spectral feature strengths between the two populations, and that the average spectral energy distribution of SNe from low-mass galaxies is bluer than the high-mass counterpart. We then use our trained models to perform an SN cosmology analysis on the 3-yr spectroscopically confirmed Dark Energy Survey SN sample, treating SNe from low- and high-mass host galaxies as separate populations throughout. We find that our mass-split models reduce the Hubble residual scatter in the sample, albeit at a low statistical significance. We do find a reduction in the mass-correlated luminosity step but conclude that this arises from the model-dependent re-definition of the fiducial SN absolute magnitude rather than the models themselves. Our results stress the importance of adopting a standard definition of the SN parameters (x0, x1, c) in order to extract the most value out of the light curve modelling tools that are currently available and to correctly interpret results that are fit with different models.

Taylor, G. (ORCID:0000000157563259)↗
DOE OSTI2020

Building a custom high-throughput platform at the Joint Genome Institute for DNA construct design and assembly—present and future challenges

Abstract The rapid design and assembly of synthetic DNA constructs have become a crucial component of biological engineering projects via iterative design–build–test–learn cycles. In this perspective, we provide an overview of the workflows used to generate the thousands of constructs and libraries produced each year at the U.S. Department of Energy Joint Genome Institute. Particular attention is paid to describing pipelines, tools used, types of scientific projects enabled by the platform and challenges faced in further scaling output.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Customized Bayesian optimization for efficient beam tuning at the facility for rare isotope beams

Bayesian optimization (BO) has recently emerged as a powerful approach for on-line beam tuning, and it is rapidly gaining adoption across accelerator facilities due to its flexibility and efficiency in handling complex optimization tasks. At the Facility for Rare Isotope Beams, rapid and reliable tuning is essential to support the delivery of diverse ion species. To improve the practicality of BO in this setting, we implemented several enhancements, including scalarized composite objective construction for multicriteria optimization, asynchronous evaluation for better resource utilization, prior-mean-assisted optimization to accelerate convergence, and a local search strategy for rapid completion of the task. We present the details of these methods, discuss challenges-encountered, and share our experience applying them to specific beam-tuning tasks.

Accelerators & storage rings↗
DOE OSTI2021

A Machine Learning-Based Method to Estimate Transformer Primary-Side Voltages with Limited Customer-Side AMI Measurements

Distribution control applications such as volt/var optimization, network reconfiguration, and distribution automation require accurate knowledge of the distribution system state. The lack of sufficient sensors on the primary side of distribution networks often limits the accuracy of the control decisions by these applications. The deployment of advanced metering infrastructure (AMI) provides utilities an opportunity to translate the AMI data on the secondary onto the primary so that it can be used as pseudo-measurements to augment the limited existing measurements on the primary. This paper develops a machine learning based approach for estimating service transformer primary-side voltages by using limited secondary-side AMI measurement. The machine learning model is developed by using random forest algorithm. The estimated primary-side voltages can be used by utilities as pseudo-measurements for distribution control applications. The detailed secondary model topology, which is an essential input data for many existing algorithms, is not required for the proposed method. The performance of the proposed method is validated by using AMI measurements from the field and an actual distribution feeder model of San Diego Gas & Electric Company.

advanced metering infrastructure↗
DOE OSTI2020

The Case for Custom TMY's: Examples Using the NSRDB

A typical meteorological year (TMY) data set essentially represents an hourly compilation of median months constructed using multi-year datasets. Although TMY data sets are generated from irradiance data in the horizontal plane, they are used in photovoltaic (PV) modeling for systems inclined to various angles. This paper demonstrates that a POA TMY (plane of array TMY) generated by selecting median months from a multi-year POA irradiance timeseries dataset produces significantly different results than a POA TMY generated by transposing a TMY dataset constructed from horizontal data. In some months the differences can be more than 3%. These results point to the need for generating TMY's using POA irradiance timeseries representing the orientation at which PV panels will be deployed.

14 SOLAR ENERGY↗