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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High‐Speed Embedded Ink Writing of Anatomic‐Size Organ Constructs

Embedded ink writing (EIW) is an emerging 3D printing technique that fabricates complex 3D structures from various biomaterial inks but is limited to a printing speed of ∼10 mm s −1 due to suboptimal rheological properties of particulate-dominated yield-stress fluids when used as liquid baths. In this work, a particle-hydrogel interactive system to design advanced baths with enhanced yield stress and extended thixotropic response time for realizing high-speed EIW is developed. In this system, the interactions between particle additive and three representative polymeric hydrogels enable the resulting nanocomposites to demonstrate different rheological behaviors. Accordingly, the interaction models for the nanocomposites are established, which are subsequently validated by macroscale rheological measurements and advanced microstructure characterization techniques. Filament formation mechanisms in the particle-hydrogel interactive baths are comprehensively investigated at high printing speeds. To demonstrate the effectiveness of the proposed high-speed EIW method, an anatomic-size human kidney construct is successfully printed at 110 mm s −1 , which only takes ∼4 h. This work breaks the printing speed barrier in current EIW and propels the maximum printing speed by at least 10 times, providing an efficient and promising solution for organ reconstruction in the future.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Embedded 3D printing of isotropically enhanced lattice structure with programmable elasticity via three-dimensional fiber alignment

Engineered composites with fiber orientation in a complete three-dimensional (3D) context are highly desired for maximizing structural performance as they mimic the well-organized fiber arrangement in natural composites. However, most fabrication techniques lack the capability for through-plane (z-axis) alignment, limiting the possibility for structural design and performance optimization. In this study, we present an embedded 3D printing approach that enables complete 3D fiber alignment, including region-specific alignment control along the through-plane direction. Our method utilizes the extrusion and suspension of composite inks within a supporting matrix. By regionally adjusting the ink extrusion rate and nozzle translation rate, we locally manipulated the fiber arrangement within the composite 3D architecture. Here, we demonstrate that the 3D alignment of carbon fibers in a structural composite significantly enhances both mechanical properties and thermal conductivity in the in-plane and through-plane directions. Furthermore, by strategically arranging regional fiber orientations within micro-architected materials, we fabricated metamaterial engineered composites with programmable anisotropy ratio and directional moduli.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A constrained-transport embedded boundary method for compressible resistive magnetohydrodynamics

Motivated by the increased interest in pulsed-power magneto-inertial fusion devices in recent years, we present a method for implementing an arbitrarily shaped embedded boundary on a Cartesian mesh while solving the equations of compressible resistive magnetohydrodynamics. The method is built around a finite volume formulation of the equations in which a Riemann solver is used to compute fluxes on the faces between grid cells, and a face-centered constrained transport formulation of the induction equation. The small time step problem associated with the cut cells is avoided by always computing fluxes on the faces and edges of the Cartesian mesh. We extend the method to model a moving interface between two materials with different properties using a ghost-fluid approach, and show some preliminary results including shock-wave-driven and magnetically-driven dynamical compressions of magnetohydrostatic equilibria. In conclusion, we present a thorough verification of the method and show that it converges at second order in the absence of discontinuities, and at first order with a discontinuity in material properties.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Street-level temperature estimation using graph neural networks: Performance, feature embedding and interpretability

Estimating street-level air temperature is a challenging task due to the highly heterogeneous urban surfaces, canyon-like street morphology, and the diverse physical processes in the built environment. Though pioneering studies have embarked on investigations via data-driven approaches, many questions remain to be answered. Here, in this study, we leveraged an innovative framework and redefined the street-level temperature estimation problem using Graph Neural Networks (GNN) with spatial embedding techniques. The results showed that GNN models are more capable and consistent of estimating street-level temperature among tested locations, benefiting from its unique strength in handling extensive data over unstructured graph topology. In addition, we conducted in-depth analysis of feature importance to enhance the model interpretability. Among the urban features analyzed in this study, the time-variant canopy density and meter-level land use data emerge as crucial factors. Our findings highlight GNN 's high potential in capturing the complex dynamics between urban elements and their impacts on microclimate, thus offering valuable insights for comprehensive urban data collection and urban climate modeling in general. Collectively, this study also contributes to urban planning and policy by providing avenues to enhance city resilience against climate change, thereby advancing the agenda for environmental stewardship and urban sustainability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Diabatization with Electrostatic Embedding for Studying Photophysics in Organic Molecular Crystals

Highly emissive organic molecular crystals find applications in several areas, such as organic electronics, solar cells, and sensors. Understanding the excited-state mechanisms underlying these applications is essential for optimizing and controlling them effectively. Exciton models coupled with nonadiabatic dynamics, particularly quantum dynamics, provide crucial insights into photochemical and photophysical processes in molecular crystals. Nevertheless, there remains a lack of general tools and automated workflows to facilitate such simulations. In this paper, we present a computational strategy to investigate the photoactivated dynamics of organic molecular crystals, bridging methodologies traditionally used for molecular systems and materials science, with a particular focus on the interplay between local excitations and charge transfer (CT) processes. We have implemented an interface between the fromage and Overdia programs, enabling the construction of vibronic Hamiltonians for molecular crystals within an excited-state ONIOM(QM:QM′) framework, incorporating long-range electrostatics through a RESP-based Ewald summation. Fragment-based diabatization provides a route to quantum dynamics simulations in weak-to-intermediate coupling regimes. The method was applied to the photophysics of dibenzo[g,p]chrysene (DBC) crystals using time-dependent DFT. The fromage/ Overdia interface was employed to compute the couplings of local excitations and CT states for 18 unique DBC dimers in the crystal and to quantify the influence of electrostatic embedding, which was found to be modest (10−20%). Simulations on π-stacked dimers reproduced the small red shift observed experimentally from solution to crystal, attributed to electronic interactions among fixed monomers rather than crystal electrostatics. Quantum dynamics simulations revealed ultrafast population transfer from bright local excitations to CT states. This approach establishes a robust framework linking molecular and solid-state excited-state dynamics, with potential applications for studying excitations, defects, and impurities in molecular crystals.

Crystals↗
DOE OSTI2025

Transfer learning nonlinear plasma dynamic transitions in low dimensional embeddings via deep neural networks

Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. Development of novel, data-driven model reduction methods, coupled with detection of abnormal modes with plasma physics, opens a unique opportunity to identify plasma instabilities through automated construction of parsimonious models that can be tuned to balance accuracy and cost. Our fusion transfer learning (FTL) model demonstrates success in rapidly reconstructing nonlinear kink mode structures by learning from a limited amount of nonlinear simulation data. The knowledge transfer process leverages a pre-trained neural encoder–decoder network, initially trained on linear simulations, to effectively capture nonlinear dynamics. The low-dimensional embeddings extract the coherent structures of interest, while preserving the inherent dynamics of the complex system. Experimental results highlight FTL’s capacity to capture transitional behaviors and dynamical features in plasma dynamics—a task often challenging for conventional methods. The model developed in this study is generalizable and can be extended broadly through transfer learning to address various magnetohydrodynamics modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Using AMReX's Embedded Boundaries to Support MFIX-Exa’s Geometry Capabilities

MFIX-Exa is an AMReX-based application used for the simulation of chemically reacting multiphase flows inside reactors. The reactor geometry is mostly a combination of primitive shapes such as cylinders, cubes and spheres of varying dimensions connected together with potentially a lot of dead space between them. Additionally, the reactors may have particle-laden jets introduced at different parts of their geometry to enhance reactant mixing. This talk presents how MFIX-Exa uses OpenSCAD’s csg format to allow users to define the embedded boundary (EB) geometry and how it supports specifying inflow through certain sections of the EB. The talk will describe how MFIX-Exa leverages the EB features of grid-pruning, restart files and redistribution. Finally, the talk goes over some capabilities which are currently not available in MFIX-Exa but planned for the future, such as moving parts of the reactor geometry.

embedded boundaries↗
NASA NTRS2006

Embedded Resistors and Capacitors in Organic and Inorganic Substrates

Embedded resistors and capacitors were purchased from two technology; organic PWB and inorganic low temperature co-fire ceramic (LTCC). Small groups of each substrate were exposed to four environmental tests and several characterization tests to evaluate their performance and reliability. Even though all passive components maintained electrical performance throughout environmental testing, differences between the two technologies were observed. Environmental testing was taken beyond manufacturers' reported testing, but general not taken to failure. When possible, data was quantitatively compared to manufacturer's data.

printed circuit board (PCB)↗
NASA NTRS2014

Drill Embedded Nanosensors For Planetary Subsurface Exploration

We have developed a carbon nanotube (CNT) sensor for water vapor detection under Martian Conditions and the miniaturized electronics can be embedded in the drill bit for collecting sensor data and transmit it to a computer wirelessly.This capability will enable the real time measurement of ice during drilling. With this real time and in-situ measurement, subsurface ice detection can be easy, fast, precise and low cost.

Planetary exploration↗
NASA NTRS2014

Scalable Asset Discovery, Vulnerability Scanning, and Penetration Testing for Remote Sites and Wireless Spectrums Utilizing an Embedded Linux Plug - PwniPlug and the Raspberry Pi B+ as a Sample Pen Test

All devices attached to the NASA KSC network are subject to security vulnerability scanning and/or penetration testing. In today's changing environment, vulnerable and/or unprotected systems can easily be overlooked. Systems that are not properly managed can become a potential threat to the operational integrity of our systems and networks. This includes all NASA (internal and external) information systems within NASA KSC Internet Protocol (IP) address space, and NASA KSC facilities. The Office of the Chief Information Officer (OCIO) recommends that all NASA Centers and information systems be subject to penetration testing on a regular interval in accordance with the guidelines identified by the National Institute of Standards and Technology (NIST). (ITS-HBK-2810.04-02A) Protecting information and equipment at NASA is an area of increasing concern. In addition to the CPU's on the network; Supervisory, Control and Data Acquisition (SCADA) systems are especially vulnerable because these systems have lacked standards, use embedded controllers with little computational power and informal software, are connected to physical processes, have few operators, and are increasingly also being connected to corporate networks. The scope of work is comprised of several individual components which together build upon previous work by Drew Branch, NASA KSC Intern. The Pwn Plug is the selected COTS (Commercial-Off-The-Shelf) device chosen to test simplification of mandatory IT Security tasks. The device will be utilized to provide services to NASA KSC and enable an assessment of infrastructure soundness and regulatory compliance in an efficient, economical, and business responsive manner. The Pwn Plug is designed as a pen testing appliance which provides a hardware platform that can support commercial penetration testing efforts at significantly reduced costs. The expected outcomes are: 1) External Penetration Testing, 2) Social Engineering, 3) Procedural Documentation, 4) Recommended Remediation Action Plan, 5) System Retest & Remediation Attestation and 6) Final Reports, out briefing and Presentation. Due to physical and material constraints beyond intern and mentor control, the project was redefined as a working pen-test scenario. Limitations of lab availability and tools dictated an academic exercise. This report was developed within the scenario guidelines suggested by the project mentor. The guidelines were to be creative in developing a Pen Test program for a client.

Penetration Testing↗
NASA NTRS2016

Challenges and Progress in Aerodynamic Design of Hybrid Wingbody Aircraft with Embedded Engines

We summarize the contributions to high-fidelity capabilities for analysis and design of hybrid wingbody (HWB) configurations considered by NASA. Specifically, we focus on the embedded propulsion concepts of the N2-B and N3-X configurations, some of the future concepts seriously investigated by the NASA Fixed Wing Project. The objective is to develop the capability to compute the integrated propulsion and airframe system realistically in geometry and accurately in flow physics. In particular, the propulsion system (including the entire engine core-compressor, combustor, and turbine stages) is vastly more difficult and costly to simulate with the same level of fidelity as the external aerodynamics. Hence, we develop an accurate modeling approach that retains important physical parameters relevant to aerodynamic and propulsion analyses for evaluating the HWB concepts. Having the analytical capabilities at our disposal, concerns and issues that were considered to be critical for the HWB concepts can now be assessed reliably and systematically; assumptions invoked by previous studies were found to have serious consequences in our study. During this task, we establish firmly that aerodynamic analysis of a HWB concept without including installation of the propulsion system is far from realistic and can be misleading. Challenges in delivering the often-cited advantages that belong to the HWB are the focus of our study and are emphasized in this report. We have attempted to address these challenges and have had successes, which are summarized here. Some can have broad implications, such as the concept of flow conditioning for reducing flow distortion and the modeling of fan stages. The design optimization capability developed for improving the aerodynamic characteristics of the baseline HWB configurations is general and can be employed for other applications. Further improvement of the N3-X configuration can be expected by expanding the design space. Finally, the support of the System Analysis and Integration Element under the NASA Fixed Wing Project has enabled the development and helped deployment of the capabilities shown in this report.

design optimization↗
NASA NTRSDate not supplied

Assured Performance of Additively Manufactured and Composite Parts through Embedded Sensing and Life Cycle Monitoring: An Enabler for in-Space Use

Lightweight composites have a range of applications in aerospace where operational costs and mission (payload) capabilities depend significantly on component weight. Additive manufacturing of the composite components expands the design and production space allowing for complex part geometries. A limiting factor to the utilization of the composites in high value applications, such as aerospace generally, and particularly for in-space applications, is the ability to determine the part quality both at the time of production as well as through the lifetime of the component. Work on monitoring the performance of additively manufactured and autoclaved composites that encompasses the design and manufacturing as well as use in operational environments will be discussed. Optimization of the component design for manufacturability, the use of process monitoring sensors during the component build as well as embedding of carbon nanotube yarn based structural sensors will be described.

Additive Manufacturing↗
NASA NTRSDate not supplied

Trust-Informed Large Language Models via Word Embedding-Knowledge Graph Alignment

A major weakness of a Large Language Model (LLM) is its tendency to accept information at face value, often leading to injection of erroneous information and inducing a greater probability of hallucinating non-existent information. While Retrieval Augmented Generation (RAG) uses external knowledge sources to bolster LLMs through grounded truth, this work seeks to explore methods to engender a LLM with an intrinsic capability to evaluate an input’s believability without relying on external knowledge sources. We investigate unifying a LLM with a Knowledge Graph (KG) and using the KG to reinforce the LLM’s internal word embedding while also maintaining belief metrics along the edge’s in the KG.

Large Language Model↗
DOE OSTI2025

Formation of Composite SiC/SiC Joints by Embedded Wire Chemical Vapor Deposition

The joining of ceramic monoliths or composites to date has primarily been limited to the formation of brittle monolithic joints using heterogeneous (dissimilar) materials, similar to brazing in metals. The development of a damage-tolerant joint layer by SiC fiber reinforcements is demonstrated here. Tube workpieces made of SiC fiber-SiC matrix composite are joined using a nonwoven SiC fiber mat densified by embedded wire chemical vapor deposition (EWCVD), creating a fiber-reinforced weld-like joint by homogeneous joining. EWCVD uses a localized heating method to target deposition and growth to the joint region specifically, while minimizing thermal damage to the surrounding composite tube material. X-ray computed tomography (XCT) is used to nondestructively characterize as-made joints for relative density, adhesion, and composition. In situ XCT analysis during mechanical testing revealed crack deflections in the bonding layer, which indicates a toughening mechanism typical of ceramic matrix composite phase. Gas permeation testing of these proof-of-concept composite joints identified relatively high leak rates in comparison to fully coated SiC/SiC composite tube workpieces. In conclusion, the novelty of the composite joining method and current technology challenges, including gas permeability, are discussed in comparison with traditional ceramic joints and materials.

SiC↗
DOE OSTI2024

Embedded Fluidic Sensing and Control with Soft Open‐Cell Foams

Abstract The synthesis of soft matter intelligence with circuit‐driven logic has enabled a new class of robots that perform complex tasks or conform to specialized form factors in unique ways that cannot be realized through conventional designs. Translating this hybrid approach to fluidic systems, the present work addresses the need for sheet‐based circuit materials by leveraging the innate porosity of foam—a soft material—to develop pneumatic components that support digital logic, mixed‐signal control, and analog force sensing in wearables and soft robots. Analytical tools and experimental techniques developed in this work serve to elucidate compressible gas flow through porous sheets, and to inform the design of centimeter‐sized foam resistors with fluidic resistances on the order of 10 9 Pa s m −3 . When embedded inside soft robots and wearables, these resistors facilitate diverse functionalities spanning both sensing and control domains, including digital logic using textile logic gates, digital‐to‐analog signal conversion using ladder networks, and analog sensing of forces up to 40 N via compression‐induced changes in resistance. By combining features of both circuit‐based and materials‐based approaches, foam‐enabled fluidic circuits serve as a useful paradigm for future hybrid robotic architectures that fully embody the sensing and computing capabilities of soft fluidic materials.

Rajappan, Anoop↗