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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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NASA NTRS2017

Engineering, Life Sciences, and Health/Medicine Synergy in Aerospace Human Systems Integration: The Rosetta Stone Project

In the realm of aerospace engineering and the physical sciences, we have developed laws of physics based on empirical and research evidence that reliably guide design, research, and development efforts. For instance, an engineer designs a system based on data and experience that can be consistently and repeatedly verified. This reproducibility depends on the consistency and dependability of the materials on which the engineer works and is subject to physics, geometry and convention. In life sciences and medicine, these apply as well, but individuality introduces a host of variables into the mix, resulting in characteristics and outcomes that can be quite broad within a population of individuals. This individuality ranges from differences at the genetic and cellular level to differences in an individuals personality and abilities due to sex and gender, environment, education, etc.

Medicine↗
NASA NTRS2016

International Research Results and Accomplishments From the International Space Station - A New Compilation

In 2016, the International Space Station (ISS) partnership published the first-ever compilation of international ISS research publications resulting from research performed on the ISS through 2011 (Expeditions 0 through 30). International Space Station Research Accomplishments: An Analysis of Results. From 2000-2011 is a collection of over 1,200 journal publications that describe ISS research in the areas of biology and biotechnology; Earth and space science; educational activities and outreach; human research; physical sciences; technology development and demonstration; and, results from ISS operations. This paper will summarize the ISS results publications obtained through 2011 on behalf of the ISS Program Science Forum that is made up of senior science representatives across the international partnership. NASA's ISS Program Science office maintains an online experiment database (www.nasa.gov/iss- science) that tracks and communicates ISS research activities across the entire ISS partnership, and it is continuously updated by cooperation and linking with the results tracking activities of each partner. It captures ISS experiment summaries and results and includes citations to the journals, conference proceedings, and patents as they become available. This content is obtained through extensive and regular journal and patent database searches, and input provided by the ISS international partners ISS scientists themselves. The International Space Station Research Accomplishments: An Analysis of Results From 2000-2011 is a testament to the research that was underway even as the ISS laboratory was being built. It rejects the scientific knowledge gained from ISS research, and how it impact the fields of science in both space and traditional science disciplines on Earth. Now, during a time when utilization is at its busiest, and with extension of the ISS through at least 2024, the ISS partners work together to track the accomplishments and the new knowledge gained in a way that will impact humanity like no laboratory on Earth. Examples of the highest pro le publications to date from each discipline will also be presented. As ISS research activities and operations continue, scientific data derived from earlier experiments will continuously be re-examined, refined, and assembled with new data and findings, including data from other fields never considered. New results will be produced, allowing breakthroughs in new areas of research and innovative solutions to problems on Earth. The ISS Program Science Forum will continue to capture and report on these results in the form of journal publications, conference proceedings, and patents. We anticipate that successful ISS research will continue to contribute to the science literature in a way that helps to formulate new hypotheses and conclusions that will enable science advancements across a wide range of scientific disciplines both in space and on Earth.

Ruttley, Tara↗
NASA NTRS2016

International Research Results and Accomplishments From the International Space Station

In 2016, the International Space Station (ISS) partnership published the first-ever compilation of international ISS research publications resulting from research performed on the ISS through 2011. The International Space Station Research Accomplishments: An Analysis of Results From 2000-2011 is a collection of summaries of over 1,200 journal publications that describe ISS research in the areas of biology and biotechnology; Earth and space science; educational activities and outreach; human research; physical sciences; technology development and demonstration; and, results from ISS operations. This paper will summarize the ISS results publications obtained through 2011 on behalf of the ISS Program Science Forum that is made up of senior science representatives across the international partnership. NASA's ISS Program Science office maintains an online experiment database (www.nasa.gov/issscience) that tracks and communicates ISS research activities across the entire ISS partnership, and it is continuously updated. It captures ISS experiment summaries and results and includes citations to the journals, conference proceedings, and patents as they become available. The International Space Station Research Accomplishments: An Analysis of Results From 2000-2011 is a testament to the research that was underway even as the ISS laboratory was being built. It reflects the scientific knowledge gained from ISS research, and how it impact the fields of science in both space and traditional science disciplines on Earth. Now, during a time when utilization is at its busiest, and with extension of the ISS through at least 2024, the ISS partners work together to track the accomplishments and the new knowledge gained in a way that will impact humanity like no laboratory on Earth. The ISS Program Science Forum will continue to capture and report on these results in the form of journal publications, conference proceedings, and patents. We anticipate that successful ISS research will continue to contribute to the science literature in a way that helps to formulate new hypotheses and conclusions that will enable science advancements across a wide range of scientific disciplines both in space and on Earth.

Ruttley, Tara M.↗
NASA NTRSDate not supplied

Habitable Working and Living Spaces in the Deep Space Science Vessel

The Deep Space Science Vessel (DSSV) is a conceptual design of a very large spacecraft intended as a mobile microgravity science platform. It represents an effort to conceptualize the systems and internal architectures needed to support a forty-eight-person crew for multi-year missions throughout the inner solar system and potentially beyond. The general arrangement of the DSSV is a modular spacecraft. Considering only the pressurized, habitable elements, the DSSV includes two large pressurized modules (Hab and Lab) docked together along with eight smaller node modules completing the habitable configuration. The Hab and Lab modules are docked side by side, with the longitudinal axes parallel to each other and a single docking port connecting them. A node module is docked to each dome on the Hab and Lab modules, such that the two small node modules on each end of the large Hab and Lab domes are docked both to each other and to the Hab and Lab. This creates a “racetrack” translation path on the interior. The other four node modules are docked at the center of the Hab and Lab modules, two on each side, creating another “racetrack” translation path perpendicular to the first one. The DSSV has a generally vertical orientation. Within the Hab and Lab modules the decks are perpendicular to the longitudinal axis. The node modules are oriented with their longitudinal axes perpendicular to those of the Hab and Lab modules, so the nodes have a horizontal internal orientation. Decks are numbered one through nine, with decks two and eight representing the “top” and “bottom” domes of the Hab and Lab modules. The Hab Module decks encompass the ship’s galley, crew quarters, waste, hygiene, portions of crew exercise, and group recreation. The Lab Module contains food production facilities, the life science lab, the ship’s infirmary, the physical science lab, and the maintenance and fabrication workshop. The Node Modules serve a number of different functions. The two Exercise Nodes are docked to deck five of both the Hab and Lab modules and contain most of the aerobic and resistive exercise devices. Also docked to deck five but on the opposite side of the Hab and Lab modules are the Observation Deck and Space Café. These two node modules provide social gathering space for small numbers of crew. The Mission Operations Node is on deck nine directly above the Galley and contains spacecraft monitoring and commanding capabilities. Docked to it is the EVA Operations Node, which contains suit maintenance and storage. (The airlock is a separate, external element docked to the EVA Operations Node.) The Subsystems Node is on deck one beneath the maintenance and fabrication workshop. Docked to it is the Stowage Node. This node does not house DSSV primary stowage, but is a staging point where stowage brought in from logistics modules can be sorted, unpacked, or repacked as needed prior to distribution to the appropriate sections of the spacecraft.

Deep Space Habitat↗
NASA NTRS2001

Microgravity Combustion Science and Fluid Physics Experiments and Facilities for the ISS

At the NASA Glenn Research Center, the Microgravity Science Program supports both ground-based and flight experiment research in the disciplines of Combustion Science and Fluid Physics. Combustion Science research includes the areas of gas jet diffusion flames, laminar flames, burning of droplets and misting fuels, solids and materials flammability, fire and fire suppressants, turbulent combustion, reaction kinetics, materials synthesis, and other combustion systems. The Fluid Physics discipline includes the areas of complex fluids (colloids, gels, foams, magneto-rheological fluids, non-Newtonian fluids, suspensions, granular materials), dynamics and instabilities (bubble and drop dynamics, magneto/electrohydrodynamics, electrochemical transport, geophysical flows), interfacial phenomena (wetting, capillarity, contact line hydrodynamics), and multiphase flows and phase changes (boiling and condensation, heat transfer, flow instabilities). A specialized International Space Station (ISS) facility that provides sophisticated research capabilities for these disciplines is the Fluids and Combustion Facility (FCF). The FCF consists of the Combustion Integrated Rack (CIR), the Fluids Integrated Rack (FIR) and the Shared Accommodations Rack and is designed to accomplish a large number of science investigations over the life of the ISS. The modular, multiuser facility is designed to optimize the science return within the available resources of on-orbit power, uplink/downlink capacity, crew time, upmass/downmass, volume, etc. A suite of diagnostics capabilities, with emphasis on optical techniques, will be provided to complement the capabilities of the subsystem multiuser or principal investigator-specific experiment modules. The paper will discuss the systems concept, technical capabilities, functionality, and the initial science investigations in each discipline.

Lauver, Richard W.↗
DOE OSTI2021

Physics guided machine learning using simplified theories

Recent applications of machine learning, in particular deep learning, motivate the need to address the generalizability of the statistical inference approaches in physical sciences. In this Letter, we introduce a modular physics guided machine learning framework to improve the accuracy of such data-driven predictive engines. The chief idea in our approach is to augment the knowledge of the simplified theories with the underlying learning process. To emphasize their physical importance, our architecture consists of adding certain features at intermediate layers rather than in the input layer. To demonstrate our approach, we select a canonical airfoil aerodynamic problem with the enhancement of the potential flow theory. We include the features obtained by a panel method that can be computed efficiently for an unseen configuration in our training procedure. By addressing the generalizability concerns, our results suggest that the proposed feature enhancement approach can be effectively used in many scientific machine learning applications, especially for the systems where we can use a theoretical, empirical, or simplified model to guide the learning module.

42 ENGINEERING↗
NASA NTRS2001

ISS Microgravity Research Payload Training Methodology

The NASA Microgravity Research Discipline has multiple categories of science payloads that are being planned and currently under development to operate on various ISS on-orbit increments. The current program includes six subdisciplines; Materials Science, Fluids Physics, Combustion Science, Fundamental Physics, Cellular Biology and Macromolecular Biotechnology. All of these experiment payloads will require the astronaut various degrees of crew interaction and science observation. With the current programs planning to build various facility class science racks, the crew will need to be trained on basic core operations as well as science background. In addition, many disciplines will use the Express Rack and the Microgravity Science Glovebox (MSG) to utilize the accommodations provided by these facilities for smaller and less complex type hardware. The Microgravity disciplines will be responsible to have a training program designed to maximize the experiment and hardware throughput as well as being prepared for various contingencies both with anomalies as well as unexpected experiment observations. The crewmembers will need various levels of training from simple tasks as power on and activate to extensive training on hardware mode change out to observing the cell growth of various types of tissue cultures. Sample replacement will be required for furnaces and combustion type modules. The Fundamental Physics program will need crew EVA support to provide module change out of experiment. Training will take place various research centers and hardware development locations. It is expected that onboard training through various methods and video/digital technology as well as limited telecommunication interaction. Since hardware will be designed to operate from a few weeks to multiple research increments, flexibility must be planned in the training approach and procedure skills to optimize the output as well as the equipment maintainability. Early increment lessons learned will be addressed.

Schlagheck, Ronald↗
DOE OSTI2021

Materials representation and transfer learning for multi-property prediction

The adoption of machine learning in materials science has rapidly transformed materials property prediction. Hurdles limiting full capitalization of recent advancements in machine learning include the limited development of methods to learn the underlying interactions of multiple elements as well as the relationships among multiple properties to facilitate property prediction in new composition spaces. To address these issues, we introduce the Hierarchical Correlation Learning for Multi-property Prediction (H-CLMP) framework that seamlessly integrates: (i) prediction using only a material's composition, (ii) learning and exploitation of correlations among target properties in multi-target regression, and (iii) leveraging training data from tangential domains via generative transfer learning. The model is demonstrated for prediction of spectral optical absorption of complex metal oxides spanning 69 three-cation metal oxide composition spaces. H-CLMP accurately predicts non-linear composition-property relationships in composition spaces for which no training data are available, which broadens the purview of machine learning to the discovery of materials with exceptional properties. This achievement results from the principled integration of latent embedding learning, property correlation learning, generative transfer learning, and attention models. The best performance is obtained using H-CLMP with transfer learning [H-CLMP(T)] wherein a generative adversarial network is trained on computational density of states data and deployed in the target domain to augment prediction of optical absorption from composition. H-CLMP(T) aggregates multiple knowledge sources with a framework that is well suited for multi-target regression across the physical sciences.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping

Application of artificial intelligence (AI), and more specifically machine learning, to the physical sciences has expanded significantly over the past decades. In particular, science-informed AI, also known as scientific AI or inductive bias AI, has grown from a focus on data analysis to now controlling experiment design, simulation, execution and analysis in closed-loop autonomous systems. The CAMEO (closed-loop autonomous materials exploration and optimization) algorithm employs scientific AI to address two tasks: learning a material system’s composition-structure relationship and identifying materials compositions with optimal functional properties. By integrating these, accelerated materials screening across compositional phase diagrams was demonstrated, resulting in the discovery of a best-in-class phase change memory material. Key to this success is the ability to guide subsequent measurements to maximize knowledge of the composition-structure relationship, or phase map. In this work we investigate the benefits of incorporating varying levels of prior physical knowledge into CAMEO’s autonomous phase-mapping. This includes the use of ab-initio phase boundary data from the AFLOW repositories, which has been shown to optimize CAMEO’s search when used as a prior.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Photoelectron spectroscopy with entangled photons; enhanced spectrotemporal resolution

In this theoretical study, we show how photoelectron signals generated by time-energy entangled photon pairs can monitor ultrafast excited state dynamics of molecules with high joint spectral and temporal resolutions, not limited by the Fourier uncertainty of classical light. This technique scales linearly, rather than quadratically, with the pump intensity, allowing the study of fragile biological samples with low photon fluxes. Since the spectral resolution is achieved by electron detection and the temporal resolution by a variable phase delay, this technique does not require scanning the pump frequency and the entanglement times, which significantly simplifies the experimental setup, making it feasible with current instrumentation. Application is made to the photodissociation dynamics of pyrrole calculated by exact nonadiabatic wave packet simulations in a reduced two nuclear coordinate space. This study demonstrates the unique advantages of ultrafast quantum light spectroscopy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Rippled metamaterials with scale-dependent tailorable elasticity

Thermally induced ripples are intrinsic features of nanometer-thick films, atomically thin materials, and cell membranes, significantly affecting their elastic properties. Despite decades of theoretical studies on the mechanics of suspended thermalized sheets, controversy still exists over the impact of these ripples, with conflicting predictions about whether elasticity is scale-dependent or scale-independent. Experimental progress has been hindered so far by the inability to have a platform capable of fully isolating and characterizing the effects of ripples. This knowledge gap limits the fundamental understanding of thin materials and their practical applications. Here, we show that thermal-like static ripples shape thin films into a class of metamaterials with scale-dependent, customizable elasticity. Utilizing a scalable semiconductor manufacturing process, we engineered nanometer-thick films with precisely controlled frozen random ripples, resembling snapshots of thermally fluctuating membranes. Resonant frequency measurements of rippled cantilevers reveal that random ripples effectively renormalize and enhance the average bending rigidity and sample-to-sample variations in a scale-dependent manner, consistent with recent theoretical estimations. The predictive power of the theoretical model, combined with the scalability of the fabrication process, was further exploited to create kirigami architectures with tailored bending rigidity and mechanical metamaterials with delayed buckling instability.

Applied Physical Sciences↗
DOE OSTI2025

Multistage nucleation pathway in LiF molten salt mirrors the crystal–melt interface structure

Despite over a century of studies, fundamental questions remain about the processes governing crystal nucleation from melts or solutions. Research over the past three decades has presented mounting evidence for kinetic pathways of crystal nucleation that are more complex than envisioned by the simplest forms of classical theory. Such observations have been presented for colloidal and elemental systems with covalent and metallic bonding. Despite the technological and geochemical importance of molten salts, similar studies for these ionically bonded systems are currently lacking. Here we develop a machine learning interatomic potential for a model ionic system: LiF. The potential features quantum-level accuracy for both liquid and multiple solid polymorphs over wide temperature and pressure ranges and accurately reproduces experimentally measured properties. Thanks to the efficiency of the potential, which enables microsecond-scale molecular dynamics simulations, induction times for nucleation of LiF solids from their melts are computed over a range of undercoolings. With the aid of a set of robust local order parameters established here, the simulations reveal that homogeneous crystal nucleation in undercooled melts preferentially initiates from liquid regions showing slow dynamics and high bond orientational order simultaneously, and the second-shell order of both precritical nuclei and the surface of postcritical nuclei is dominated by hexagonal close packing and body-centered cubic local structure, even though the nucleus core is dominated by face-centered cubic structure corresponding to the stable rocksalt crystal structure. Finally, we establish a connection between the crystallization pathway and the equilibrium crystal-melt interface structure.

Applied Physical Sciences↗
DOE OSTI2025

Flat-band tuning and emergent itinerant magnetism in Sr(Co 1− x Pd x ) 2 As 2

The interplay between magnetism and flat-band (FB) instability is a central theme in quantum materials research. A striking example is the emergence of magnetic order in a nominally nonmagnetic compound when a flat band is tuned near the Fermi energy (E F ). Here, in this study, we investigate this phenomenon in the Pauli paramagnet SrCo 2 As 2 , where an FB associated with Co e g orbitals lies close to E F . Remarkably, a minute substitution of the nonmagnetic element Pd onto the Co site (~2%) induces antiferromagnetic order with a transition temperature as high as T N = 25 K. Temperature- and magnetic-field-dependent magnetic and transport measurements, complemented by zero-field neutron diffraction, reveal a helical magnetic order for x ≤ 0.10 in Sr(Co 1−x Pd x ) 2 As 2 , transitioning to a complex ferromagnetic state at higher Pd concentrations. Spectroscopic evidence and theoretical band structure calculations demonstrate that electron doping shifts the flat band closer to E F , significantly enhancing the Stoner parameter. This enhancement drives a strong ferromagnetic instability, leading to helical magnetic ordering dominated by in-plane ferromagnetic interactions. The emergence of robust magnetic ordering through substitution with nonmagnetic elements is a unique phenomenon that underscores the pivotal role of flat-band instability in tuning magnetism in itinerant systems.

36 MATERIALS SCIENCE↗
NASA NTRS2023

SMD Technology Highlights

Three technology highlights from the Science Mission Directorate (SMD) Astrophysics Division, Biological and Physical Sciences Division, and Planetary Science Division are featured: a) A new class of X-ray detector with unprecedented energy resolution and array size could help transform our understanding of the cosmos through unparalleled vision into the otherwise invisible universe. b) An autonomous microfluidic culturing system with CubeSat heritage is teaming up with two state-of-the-art radiation detectors to measure how biology responds to the radiation and reduced gravity environment on the lunar surface. c) Several core technologies developed via the Hot Operating Temperature Technology (HOTTech) Program were recently tested in the Glenn Extreme Environment Rig (GEER), which simulates the conditions on the surface of Venus.

yeast↗
NASA NTRSDate not supplied

Open Science for Plants in Space: Data Sharing, Standards, and Informatics for Reuse and Knowledge Discovery

Upcoming deep space missions will rely on plants for crew and ecosystem health. Open access space biology data enables scientists to examine the biological responses of plants to ionizing radiation, altered gravity, low atmospheric pressure, elevated CO2, altered photoperiods and many other abiotic stressors. Open Science is the practice of making research available to all, while respecting diverse cultures, to foster collaborations with equity. NASA has declared 2023 as the ‘Year of Open Science’ and created a 5-year Transform to Open Science (TOPS) initiative designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) within the Biological and Physical Sciences Division provides access to data from space-relevant biological experiments. OSDR combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. GeneLab started in 2014 with the creation of the first space-relevant FAIR (Findable, Accessible, Interoperable, Reusable) biological ‘omics repository, providing detailed metadata on investigation, sample, and assay levels. The addition of ALSDA to OSDR expands plant data analysis capabilities across both phenotypic and ‘omics data. Today, OSDR hosts 62+ plant datasets and has enabled 58 peer-reviewed publications. Most of these publications were collaboration efforts under the OSDR Analysis Working Groups (AWGs). AWGs provide great opportunities for investigators to collaborate with community members and set new standards for space-relevant data and metadata. The AWGs welcome any ASGSR members interested in contributing plant expertise for space biology, and to serve as subject matter experts as we establish the framework for modern plant data archiving. Investigators are encouraged to submit their space-relevant plant datasets to OSDR and visit the site to learn about the tools OSDR has to offer (osdr.nasa.gov/bio).

FAIR↗
NASA NTRS2009

International Space Station Science Research Accomplishments During the Assembly Years: An Analysis of Results from 2000-2008

This report summarizes research accomplishments on the International Space Station (ISS) through the first 15 Expeditions. When research programs for early Expeditions were established, five administrative organizations were executing research on ISS: bioastronautics research, fundamental space biology, physical science, space product development, and space flight. The Vision for Space Exploration led to changes in NASA's administrative structures, so we have grouped experiments topically by scientific themes human research for exploration, physical and biological sciences, technology development, observing the Earth, and educating and inspiring the next generation even when these do not correspond to the administrative structure at the time at which they were completed. The research organizations at the time at which the experiments flew are preserved in the appendix of this document. These investigations on the ISS have laid the groundwork for research planning for Expeditions to come. Humans performing scientific investigations on ISS serve as a model for the goals of future Exploration missions. The success of a wide variety of investigations is an important hallmark of early research on ISS. Of the investigations summarized here, some are completed with results released, some are completed with preliminary results, and some remain ongoing.

Evans, Cynthia A.↗
NASA NTRSDate not supplied

Open Science for Plants in Space: Data Sharing, Standards, and Informatics for Reuse and Knowledge Discovery

Upcoming deep space missions will rely on plants for crew and ecosystem health. Open access space biology data enables scientists to examine the biological responses of plants to ionizing radiation, altered gravity, low atmospheric pressure, elevated CO2, altered photoperiods and many other abiotic stressors. Open Science is the practice of making research available to all, while respecting diverse cultures, and fostering collaborations with equity. 2023 is the ‘Year of Open Science’, and NASA has a 5-year Transform to Open Science (TOPS) initiative designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) within NASA’s Biological and Physical Sciences Division provides access to data from space-relevant biological experiments. OSDR combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. GeneLab started in 2014 with the creation of the first space-relevant FAIR (Findable, Accessible, Interoperable, Reusable) biological ‘omics repository, providing detailed metadata on investigation, sample, and assay levels. The addition of ALSDA to OSDR expands plant data analysis capabilities across both phenotypic and ‘omics data. Today, OSDR hosts 62+ plant datasets and has enabled 58 peer-reviewed publications. Most of these publications were collaboration efforts under the OSDR Analysis Working Groups (AWGs). AWGs provide great opportunities for investigators to collaborate and set new standards for space-relevant data and metadata. The AWGs welcome any ASPB members interested in contributing plant expertise for space biology, and to serve as subject matter experts as we establish the framework for modern plant data archiving. Investigators are invited to submit their space-relevant plant datasets to OSDR and visit the site to learn about the tools OSDR has to offer (osdr.nasa.gov/bio).

FAIR↗
NASA NTRSDate not supplied

The Science Discovery Engine: Connecting Heterogeneous Scientific Data and Information

Transformative science often occurs at the boundaries of different disciplines. Making interdisciplinary science data, software and documentation discoverable and accessible is essential to enabling transformative science. However, connecting this diverse and heterogeneous information is often a challenge due to several factors including the dispersed and sometimes isolated nature of data and the semantic differences between topical areas. NASA’s Science Discovery Engine (SDE) has developed several approaches to tackling these challenges. The SDE is a unified, insightful search experience that enables discovery of NASA’s open science data across five topical areas: astrophysics, biological and physical sciences, Earth science, heliophysics and planetary science. In this presentation, we will discuss our efforts to develop a systematic scientific curation workflow to integrate diverse content into a single search environment. We will also share lessons learned from our work to create a metadata crosswalk across the five disciplines.

Kaylin Bugbee↗