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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Mapping Glacier Basal Sliding Applying Machine Learning

During the RESOLVE project (“High-resolution imaging in subsurface geophysics: development of a multi-instrument platform for interdisciplinary research”), continuous surface displacement and seismic array observations were obtained on Glacier d’Argentière in the French Alps for 35 days in May 2018. The data set is used to perform a detailed study of targeted processes within the highly dynamic cryospheric environment. In particular, the physical processes controlling glacial basal motion are poorly understood and remain challenging to observe directly. Especially in the Alpine region for temperate based glaciers where the ice rapidly responds to changing climatic conditions and thus, processes are strongly intermittent in time and heterogeneous in space. Spatially dense seismic and Global Positioning System (GPS) measurements are analyzed applying machine learning to gain insight into the processes controlling glacial motions of Glacier d’Argentière. Using multiple bandpass-filtered copies of the continuous seismic waveforms, we compute energy-based features, develop a matched field beamforming catalog and include meteorological observations. Features describing the data are analyzed with a gradient boosting decision tree model to directly estimate the GPS displacements from the seismic noise. We posit that features of the seismic noise provide direct access to the dominant parameters that drive displacement on the highly variable and unsteady surface of the glacier. The machine learning model infers daily fluctuations and longer term trends. The results show on-ice displacement rates are strongly modulated by activity at the base of the glacier. The techniques presented provide a new approach to study glacial basal sliding and discover its full complexity.

58 GEOSCIENCES↗
DOE OSTI2022

Scattering-type scanning near-field optical microscopy with Akiyama piezo-probes

Recent developments of the scattering-type scanning near-field optical microscope at cryogenic temperatures (cryogenic s-SNOM or cryo-SNOM) have led to many breakthroughs in the studies of low energy excitations in quantum materials. However, the simultaneous demands on vibration isolation, low base temperature, precise nano-positioning, and optical access make the construction of a cryo-SNOM a daunting task. Adding to the overhead space required for a cryo-SNOM is the atomic force microscopy control, which predominantly utilizes a laser-based detection scheme for determining the cantilever tapping motion. In this work, we provide an alternative and straightforward route to performing s-SNOM using metal-coated Akiyama probes, where the cantilever tapping motion is detected through a piezoelectric signal. We show that the Akiyama-based cryo-SNOM attains high spatial resolution, good near-field contrast, and is able to perform imaging with a significantly more compact system compared to other cryo-SNOM implementations. Our results firmly establish the potential of s-SNOM based on self-sensing piezo-probes, which can easily accommodate far-infrared wavelengths and high magnetic fields in the future.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

HostSub_GP: Precise Galaxy Background Subtraction in Transient Long-slit Spectroscopy with Gaussian Processes

We present a novel host galaxy subtraction technique in long-slit spectroscopy for extragalactic transients. Unlike classic methods which generally estimate the background using simple interpolation of local galaxy flux in the 2D spectrum, our approach leverages multi-band archival images of the host galaxies to model the background emission from the galaxy in the 2D spectrum. Such imaging encodes the wavelength-dependent galaxy profile along the slit, and is readily accessible through wide-field imaging surveys. We construct a smooth prior for the 2D galaxy profile with a Gaussian process (GP) based on these reference images, and use another GP to model the correlated deviations from the prior in the observed spectrum. This enables accurate inference of the galaxy flux blended with the transient. On synthetic long-slit data of a spiral galaxy extracted from a Multi Unit Spectroscopic Explorer hyper-spectral cube, the GP method remains robust as long as the host galaxy is spatially resolved and consistently outperforms classic methods. We apply the method to archival Keck spectra of two real transients, SN 2019eix and AT 2019qiz, to further demonstrate how the method uniquely recovers weak spectral features amid strong galaxy contamination, enabling refined constraints on the properties of both transients. We have released the software implementation, HostSub_GP, a scalable toolkit that leverages JAX, with an MIT license.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Frontier nonequilibrium materials science enabled by ultrafast electron methods

Most innovation in materials science and engineering resides in our ability to understand and control the intimate relationship between the structure of materials and their properties. Conventionally, the only route to discovering innovative new material properties has been to explore the structural and compositional phase space that is accessible at (or near) thermodynamic equilibrium. The characterization, manipulation and, ultimately, control of material properties far from equilibrium offers almost completely untapped possibilities for uncovering novel states and phases of materials. Investigations of materials far from equilibrium require the development of new techniques, which are capable of following dynamic processes in materials with extreme spatiotemporal resolution. Thus, ultrafast electron-based methods have become a major new frontier in materials science due to the capability of following dynamics on time scales as short as femtoseconds with the high spatial resolution and sensitivity afforded by electrons. The articles in this issue provide an exciting cross section of the novel research directions that have been enabled at this frontier. Imaging on ultrafast time scales carries critical information on phase transitions, fundamental processes involved in light-harvesting, magnetic, and plasmonic dynamics, the coupling of electronic and nuclear degrees of freedom in materials and has revealed previously hidden, nonequilibrium metastable states of matter that have no equilibrium analog.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Illuminating Galaxy Evolution at Cosmic Noon with ISCEA: the Infrared Satellite for Cosmic Evolution Astrophysics

ISCEA (Infrared Satellite for Cosmic Evolution Astrophysics) is a small astrophysics mission whose Science Goal is to discover how galaxies evolved in the cosmic web of dark matter at cosmic noon. Its Science Objective is to determine the history of star formation and its quenching in galaxies as a function of local density and stellar mass when the Universe was 3-5 Gyrs old (1.2 10 Mpc in each of 50 protocluster (cluster and cosmic web) fields at 1.2 < z < 2.1. ISCEA measures the star formation quenching factor in those fields, and galaxy kinematics with a precision < 50 km/s to deduce the 3D spatial distribution in each field. ISCEA will transform our understanding of galaxy evolution at cosmic noon. ISCEA is a small satellite observatory with a 30cm equivalent diameter aperture telescope with a FoV of 0.32 deg^2, and a multi-object spectrograph with a digital micro-mirror device (DMD) as its programmable slit mask. ISCEA will obtain spectra of 1000 galaxies simultaneously at an effective resolving power of R=1000, with 2.8"x2.8" slits, over the NIR wavelength range of 1.1 to 2.0 microns, a regime not accessible from the ground without large gaps in coverage. ISCEA will achieve a pointing accuracy of <= 2" FWHM over 200s. ISCEA will be launched into a Low Earth Orbit, with a prime mission of 2.5 years. ISCEA's space-qualification of DMDs opens a new window for spectroscopy from space, enabling revolutionary advances in astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Elongated galactan side chains mediate cellulose–pectin interactions in engineered Arabidopsis secondary cell walls

SUMMARY The plant secondary cell wall is a thickened matrix of polysaccharides and lignin deposited at the cessation of growth in some cells. It forms the majority of carbon in lignocellulosic biomass, and it is an abundant and renewable source for forage, fiber, materials, fuels, and bioproducts. The complex structure and arrangement of the cell wall polymers mean that the carbon is difficult to access in an economical and sustainable way. One solution is to alter the cell wall polymer structure so that it is more suited to downstream processing. However, it remains difficult to predict what the effects of this engineering will be on the assembly, architecture, and properties of the cell wall. Here, we make use of Arabidopsis plants expressing a suite of genes to increase pectic galactan chain length in the secondary cell wall. Using multi‐dimensional solid‐state nuclear magnetic resonance, we show that increasing galactan chain length enhances pectin–cellulose spatial contacts and increases cellulose crystallinity. We also found that the increased galactan content leads to fewer spatial contacts of cellulose with xyloglucan and the backbone of pectin. Hence, we propose that the elongated galactan side chains compete with xyloglucan and the pectic backbone for cellulose interactions. Due to the galactan topology, this may result in comparatively weak interactions and disrupt the cell wall architecture. Therefore, introduction of this strategy into trees or other bioenergy crops would benefit from cell‐specific expression strategies to avoid negative effects on plant growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Probabilistic Modeling of Commercial Building Occupancy Patterns Using Location-Based Map Data: Preprint

Considering occupancy patterns is crucial to simulate buildings' energy use. Current energy models use inputs that simplify the actual diversity in occupancy into static occupancy patterns and are not able to represent the numerous variations in occupancy patterns between buildings and across different locations. Recently, inferring occupancy schedules from metered electricity consumption data was used to model occupancy in commercial buildings. However, the translation from metered data to occupancy schedules requires many assumptions that might not capture the reality, and the process is hindered by the availability of data from advanced metering infrastructure. With the development of information technologies, occupancy modeling should not be limited to traditional approaches. The prevalence of social networks and location services with real-time user feedback provides publicly accessible data via Maps Application Programming Interfaces (APIs) such as Google Maps, SafeGraph, Mapbox, Foursquare, etc. This paper presents an automated framework for modeling parametric occupancy patterns using such APIs to calibrate commercial district buildings' energy models. This process includes three main steps: data extraction and processing, parametric schedules generation, and schedules integration. We demonstrated this framework in districts where we used maps API to generate more accurate behavioral patterns for operations and electric vehicle charging events. We used these patterns to determine differences in energy use across key sociodemographic and spatial parameters. The presented method has the potential for worldwide applications. Users can utilize this framework to extract data for selected locations of interest to create more realistic behavioral patterns for commercial facilities across different districts.

building energy modeling↗
DOE OSTI2024

Accessing pluripotent materials through tempering of dynamic covalent polymer networks

Pluripotency, which is defined as a system not fixed as to its developmental potentialities, is typically associated with biology and stem cells. Here, inspired by this concept, we report synthetic polymers that act as a single “pluripotent” feedstock and can be differentiated into a range of materials that exhibit different mechanical properties, from hard and brittle to soft and extensible. To achieve this, we have exploited dynamic covalent networks that contain labile, dynamic thia-Michael bonds, whose extent of bonding can be thermally modulated and retained through tempering, akin to the process used in metallurgy. In addition, we show that the shape memory behavior of these materials can be tailored through tempering and that these materials can be patterned to spatially control mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Nanoscale Confinement of Photo-Injected Electrons at Hybrid Interfaces

A prerequisite for advancing hybrid solar light harvesting systems is a comprehensive understanding of the spatiotemporal dynamics of photoinduced interfacial charge separation. Here, we demonstrate access to this transient charge redistribution for a model hybrid system of nanoporous zinc oxide (ZnO) and ruthenium bipyridyl chromophores. The site-selective probing of the molecular electron donor and semiconductor acceptor by time-resolved X-ray photoemission provides direct insight into the depth distribution of the photoinjected electrons and their interaction with the local band structure on a nanometer length scale. Our results show that these electrons remain localized within less than 6 nm from the interface, due to enhanced downward band bending by the photoinjected charge carriers. This spatial confinement suggests that light-induced charge generation and transport in nanoscale ZnO photocatalytic devices proceeds predominantly within the defect-rich surface region, which may lead to enhanced surface recombination and explain their lower performance compared to titanium dioxide (TiO 2 )-based systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The State of Electric Vehicle Adoption in Colorado for Multifamily versus Single-Family Dwellings: A Methodology for Quantifying Deviation from Parity

Given that electric vehicle adoption is well underway, the spatial distribution of electric vehicle owners by housing type—single-family or multifamily— shows whether parity (equal adoption rates) is being achieved or to what extent adoption by housing type is over or undersaturated (i.e., over- or under-adoption). We use a proprietary dataset of vehicle registrations with modeled housing type to analyze saturation ratios in Colorado in 2022. We found significant single-family oversaturation and multifamily undersaturation in 14% and 23% of ZIP codes, respectively, suggesting Colorado can still mitigate disparities in electric vehicle adoption by housing type through accessible vehicles and charging.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

TRAILS Output Files

Overview This data repository contains ZIP files that store compressed versions of the output of running the WaterPaths utility planning and management tool in the DU Re-Evaluation mode (to download the tool, please see this GitHub repository). The tool was used to simulate the six-utility North Carolina Research Triangle problem. Details on the contents of each ZIP file can be seen below. Data details Temporal range: Weekly data for 2,344 weeks from 2015 to 2060 (45 years). Spatial range: Six water utilities in the North Carolina Research Triangle region (0: Chapel Hil/OWASA, 1: Durham, 2: Cary, 3: Raleigh, 4: Pittsboro, and 5: Chatham) File types: CSV and OUT Different solutions available The solution numbers correspond to the different pathway strategies (henceforth referred to as "solutions") discussed in paper's main and supporting text (abstract and link to the paper here). They are as follows: Sol92: The Durham-focused pathway strategy Sol132: The Raleigh-focused pathway strategy Sol140: The regionally-robust pathway strategy Objectives files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Objectives_RDMXX_solsXX_to_XX.csv files. Each CSV file will consist of a row representing all the objective values for that specific solution, while every six columns represents the reliability, restriction frequency, infrastructure net present value ($ mil), peak financial cost, worst-case cost, and unit cost ($ per MG; in that order) for each of the six utilities. There will be 1,000 such files, denoting the performance of the six utilities across the 1,000 deeply uncertain states of the world (DU SOWs). Pathway files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Pathways_sXX_RDMXX.out file. Each OUT corresponds to the set of infrastructure being triggered in a specific DU SOW, and each file will have the name file will consist of four tab-delimited columns that are described as follows: Realization: The realization in which an infrastructure options being triggered utility: The utility currently triggering infrastructure week: The week in which a specific infrastructure option is being triggered infra.: The infrastructure option being triggered If the OUT file contains only the header line, no infrastructure was triggered for that specific DU SOW. Policies files These files can be obtained by unzipping Policies.zip. Each of the 1,000 CSV files within the unzipped folder will contain weekly water use restriction policies for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: 0rest_m: restriction multiplier for utility 0 (values between 0 and 1) 1rest_m: restriction multiplier for utility 1 (values between 0 and 1) 2rest_m: restriction multiplier for utility 2 (values between 0 and 1) 3rest_m: restriction multiplier for utility 3 (values between 0 and 1) 4rest_m: restriction multiplier for utility 4 (values between 0 and 1) 5rest_m: restriction multiplier for utility 5 (values between 0 and 1) 0transf: transfer volume for utility 0 (in MGD) 1transf: transfer volume for utility 1 (in MGD) 2transf: transfer volume for utility 2 (in MGD) 3transf: transfer volume for utility 3 (in MGD) 4transf: transfer volume for utility 4 (in MGD) 5transf: transfer volume for utility 5 (in MGD) Water Sources files These files can be obtained by unzipping WaterSources_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each water source for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xvolume: available water volume from source X (in MGD) Xs_area: surface area of source X (in ACF) Xdemand: demand drawn from a water source from source X (in MGD) Xup_spill: upstream spillage from source X (in MGD) Xww_inflow: wastewater inflow from source X (in MGD) Xcatch_inflow: upstream catchment inflow to source X (in MGD) Xevap: evaporation multiplier for source X (values between 0 and 1) Xds_spill: downstream spillage from source X (in MGD) X_Y_alloc_cap: the allocated capacity from source X to utility Y (values between 0 and 1) X_Y_alloc_dem: the allocated demand from source X to utility Y (values between 0 and 1) Xtrmt_alloc_Y: the allocated treatment capacity from source X to utility Y (values between 0 and 1) Utilities files These files can be obtained by unzipping Utilities_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each utility for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xst_vol: total available storage volume of utility X (in MG) Xcapacity: total storage capacity of utility X (in MG) Xnet_inf: : net inflow for all storage infrastructure for utility X (in MGD) Xst_rof: short term ROF for utility X (values between 0 and 1) Xst_stor_rof: short-term storage ROF for utility X (values between 0 and 1) Xst_trmt_rof: short-term treatment ROF for utility X (values between 0 and 1) Xlt_rof: long-term ROF for utility X (values between 0 and 1) Xlt_stor_rof: long-term storage ROF for utility X (values between 0 and 1) Xlt_trmt_rof: long-term treatment ROF for utility X (values between 0 and 1) Xrest_demand: restricted demand for utility X (in MGD) Xunrest_demand: unrestricted demand for utility X (in MGD) Xunfulf_demand: unfulfilled demand for utility X (in MGD) Xwastewater: wastewater return for utility X (in MGD) Xtreat_capacity: total treatment capacity for utility X (in MG) Xcont_fund: reserve (contingency) fund balance for utility X Xins_pout: insurance payout for utility X (% annual volumetric revenue) Xins_price: insurance price for utility X (% annual volumetric revenue) Xinfra_npv: infrastructure net present value for utility ($mil) Xst_vol: total available storage volume of utility X (in MG) Xdebt_serv: debt service for utility X (usually once per year if the infrastructure is triggered; % annual volumetric revenue) Xstor_vol: total stored volume (in MGD) Xobs_ann_dem: observed annual demand for utility X (in MGD) Xproj_dem: projected annual demand for utility X (in MGD) Xpv_debt_serv: present value of debt service payments for utility X (% annual volumetric revenue) Xgross_rev: gross revenue for utility X ($mil) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

Artificial Intelligence↗
DOE OSTI2020

RSVP - Flu Like Illness and Respiratory Syndromes COVID-19 Syndromic Reporting Tool Prototype

Individuals infected with SARS-CoV-2, the virus that causes COVID-19, may be infectious between 1-3 days prior to symptom onset. People may delay seeking medical care after symptom development due to multiple determinants of health seeking behavior like availability of testing, accessibility of providers, and ability to pay. Therefore, understanding symptoms in the general public is important to better predict and inform resource management plans and engage in reopening. As the influenza season looms, the ability to differentiate between clinical presentation of COVID-19 and seasonal influenza will also be important to health providers and public health response efforts. This project has developed an algorithm that when used with captured syndromic trends can help provide both differentiation to various influenza-like illnesses (ILI) as well as provide public health decision makers a better understanding regarding spatial and temporal trends. This effort has also developed a web-based tool to allow for the capturing of generalized syndromic trends and provide both spatial and temporal outputs on these trends. This page left blank

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Equation-of-state Dependence of Gravitational Waves in Core-collapse Supernovae

Gravitational waves (GWs) provide unobscured insight into the birthplace of neutron stars and black holes in core-collapse supernovae (CCSNe). The nuclear equation of state (EOS) describing these dense environments is yet uncertain, and variations in its prescription affect the proto-neutron star (PNS) and the post-bounce dynamics in CCSN simulations, subsequently impacting the GW emission. In this study, we perform axisymmetric simulations of CCSNe with Skyrme-type EOSs to study how the GW signal and PNS convection zone are impacted by two experimentally accessible EOS parameters, (1) the effective mass of nucleons, m*, which is crucial in setting the thermal dependence of the EOS, and (2) the isoscalar incompressibility modulus, K sat . While K sat shows little impact, the peak frequency of the GWs has a strong effective mass dependence due to faster contraction of the PNS for higher values of m* owing to a decreased thermal pressure. These more compact PNSs also exhibit more neutrino heating, which drives earlier explosions and correlates with the GW amplitude via accretion plumes striking the PNS, exciting the oscillations. We investigate the spatial origin of the GWs and show the agreement between a frequency-radial distribution of the GW emission and a perturbation analysis. We do not rule out overshoot from below via PNS convection as another moderately strong excitation mechanism in our simulations. We also study the combined effect of effective mass and rotation. In all our simulations we find evidence for a power gap near ~1250 Hz; we investigate its origin and report its EOS dependence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Neutron scattering in photosynthesis research: recent advances and perspectives for testing crop plants

The photosynthetic performance of crop plants under a variety of environmental factors and stress conditions, at the fundamental level, depends largely on the organization and structural flexibility of thylakoid membranes. These highly organized membranes accommodate virtually all protein complexes and additional compounds carrying out the light reactions of photosynthesis. Most regulatory mechanisms fine-tuning the photosynthetic functions affect the organization of thylakoid membranes at different levels of the structural complexity. In order to monitor these reorganizations, non-invasive techniques are of special value. On the mesoscopic scale, small-angle neutron scattering (SANS) has been shown to deliver statistically and spatially averaged information on the periodic organization of the thylakoid membranes in vivo and/or, in isolated thylakoids, under physiologically relevant conditions, without fixation or staining. More importantly, SANS investigations have revealed rapid reversible reorganizations on the timescale of several seconds and minutes. In this paper, we give a short introduction into the basics of SANS technique, advantages and limitations, and briefly overview recent advances and potential applications of this technique in the physiology and biotechnology of crop plants. We also discuss future perspectives of neutron crystallography and different neutron scattering techniques, which are anticipated to become more accessible and of more use in photosynthesis research at new facilities with higher fluxes and innovative instrumentation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Driving energetically unfavorable dehydrogenation dynamics with plasmonics

Nanoparticle surface structure and geometry generally dictate where chemical transformations occur, with higher chemical activity at sites with lower activation energies. Here, we show how optical excitation of plasmons enables spatially modified phase transformations, activating otherwise energetically unfavorable sites. We have designed a crossed-bar Au-PdH x antenna-reactor system that localizes electromagnetic enhancement away from the innately reactive PdH x nanorod tips. Using optically coupled in situ environmental transmission electron microscopy, we track the dehydrogenation of individual antenna-reactor pairs with varying optical illumination intensity, wavelength, and hydrogen pressure. Our in situ experiments show that plasmons enable new catalytic sites, including dehydrogenation at the nanorod faces. Molecular dynamics simulations confirm that these new nucleation sites are energetically unfavorable in equilibrium and only accessible through tailored plasmonic excitation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) Activity for Continental Shallow Convection

The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility recently initiated the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) activity focused on shallow convection at ARM’s Southern Great Plains (SGP) atmospheric observatory in Oklahoma. LASSO is designed to overcome an oft-shared difficulty of bridging the gap from point-based measurements to scales relevant for model parameterization development, and it provides an approach to add value to observations through modeling. LASSO is envisioned to be useful to modelers, theoreticians, and observationalists needing information relevant to cloud processes. LASSO does so by combining a suite of observations, LES inputs and outputs, diagnostics, and skill scores into data bundles that are freely available, and by simplifying user access to the data to speed scientific inquiry. The combination of relevant observations with observationally constrained LES output provides detail that gives context to the observations by showing physically consistent connections between processes based on the simulated state. A unique approach for LASSO is the generation of a library of cases for days with shallow convection combined with an ensemble of LES for each case. The library enables researchers to move beyond the single-case-study approach typical of LES research. The ensemble members are produced using a selection of different large-scale forcing sources and spatial scales. Since large-scale forcing is one of the most uncertain aspects of generating the LES, the ensemble informs users about potential uncertainty for each date and increases the probability of having an accurate forcing for each case.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Spatial imaging of polarized deuterons at the Electron-Ion Collider

We study diffractive vector meson production at small-x in the collision of electrons and polarized deuterons e + d $\uparrow$ . We consider the polarization dependence of the nuclear wave function of the deuteron, which results in an azimuthal angular dependence of the produced vector meson when the deuteron is transversely polarized. The Fourier coefficients extracted from the azimuthal angular dependence of the vector meson differential cross-section exhibit notable differences between longitudinally and transversely polarized deuterons. The angular dependence of the extracted effective deuteron radius provides direct insight into the structure of the polarized deuteron wave function. Furthermore, we observe slightly increased gluon saturation effects when the deuteron is longitudinally polarized compared to the transversely polarized case. The small-x observables studied in this work will be accessible at the future Electron-Ion Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Highly Tunable Thiol-Ene Photoresins for Volumetric Additive Manufacturing

Volumetric additive manufacturing (VAM) forms complete 3D objects in a single photocuring operation without layering defects, enabling 3D printed polymer parts with mechanical properties similar to their bulk material counterparts. This study presents the first report of VAM-printed thiol-ene resins. With well-ordered molecular networks, thiol-ene chemistry accesses polymer materials with a wide range of mechanical properties, moving VAM beyond the limitations of commonly used acrylate formulations. Since free-radical thiol-ene polymerization is not inhibited by oxygen, the nonlinear threshold response required in VAM is introduced by incorporating 2,2,6,6-tetramethyl-1-piperidinyloxy (TEMPO) as a radical scavenger. Tuning of the reaction kinetics is accomplished by balancing inhibitor and initiator content. Coupling this with quantitative measurements of the absorbed volumetric optical dose allows control of polymer conversion and gelation during printing. Importantly, this work thereby establishes the first comprehensive framework for spatial–temporal control over volumetric energy distribution, demonstrating structures 3D printed in thiol-ene resin by means of tomographic volumetric VAM. Mechanical characterization of this thiol-ene system, with varied ratios of isocyanurate and triethylene glycol monomers, reveals highly tunable mechanical response far more versatile than identical acrylate-based resins. This broadens the range of materials and properties available for VAM, taking another step toward high-performance printed polymers.

36 MATERIALS SCIENCE↗