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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Engineering mechanical and thermomechanical performance in additive manufacturing–Compression molded composites through multiplexed extrusion

Traditional extrusion-based additive manufacturing is limited to single material systems, restricting the multifunctional properties of composites. For this work to overcome this limitation, multiplexed additive manufacturing–compression molding (AM-CM) was employed to fabricate multi-material thermoplastic composites with spatially tailored architectures. Neat acrylonitrile butadiene styrene (ABS) and 20 wt% carbon-fiber reinforced ABS (CF-ABS) were co-extruded through a core–sheath nozzle to produce hybrid composites with neat ABS as sheath (30-50 wt%) and CF-ABS as core (50 – 70 wt%). The results show that the hybrid composites have balance of mechanical and thermomechanical performance. The tensile strength and modulus of hybrid composites exhibited a 61–95% and 173–473% increase compared to neat ABS with increases in CF-ABS content whereas the impact resistance improved by 41% compared to CF-ABS at 50 wt% ABS. Additionally, hybrid composites showed significant reduction (54 - 70%) in creep strain at 100 °C compared to neat ABS. These findings demonstrate that multiplexed AM-CM enables tunable structure–property relationships, reducing CF-ABS usage up to 50 wt% while maintaining balanced stiffness, toughness, and creep resistance.

Additive manufacturing↗
DOE OSTI2025

Modulating Oxide‐Based Quantum Materials by Ion Implantation

Ion implantation has emerged as a powerful tool for manipulating and investigating oxide quantum materials, where strong electron correlations give rise to exotic phases and functionalities. This Review examines how controlled ion bombardment enables targeted modulation of structural, electronic, and magnetic properties in complex oxides. Recent advances in ion beam techniques is analyzed that provide unprecedented control over defect profiles, from point defects to extended damage cascades. In application, ion irradiation has demonstrated the ability to tune quantum phenomena including metal‐insulator transitions, magnetism, and superconductivity through selective doping, defect creation, and lattice strain. The ability to write quantum states with nanoscale precision using focused ion beams is opening new paths for quantum device fabrication. Challenges in understanding radiation damage mechanisms in strongly correlated systems is discussed, and identify opportunities for designing quantum functionality through defect‐engineering approaches. The technique's demonstrated capability to write quantum states with nanoscale precision, combined with its compatibility with existing semiconductor processing infrastructure, suggests a clear pathway for translating fundamental discoveries in quantum materials into practical technological applications.

defect engineering↗
DOE OSTI2024

Shielding development for the spallation neutron source VENUS instrument

VENUS is a neutron imaging instrument that will use a broad range of neutron wavelengths, from epithermal to cold energies, and will include enhanced contrast mechanisms. It will offer novel energy-selective imaging techniques directly connecting complex engineering materials and systems’ structures, properties, and functions to reveal practical and fundamental answers about their real-world performance. Here, the instrument will be built at SNS beamline 10, facing the decoupled poisoned hydrogen moderator. The driving cost for the instrument is the beamline and instrument cave shielding. Final analyses were performed to evaluate the thickness and composition of shielding materials for the instrument cave and beamline to meet radiation safety criteria for the instrument to start up in 2024 after completing the SNS proton power upgrade.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Dynamic cycling enhances battery lifetime

Laboratory aging campaigns benchmark and elucidate the complex degradation behavior of lithium-ion batteries, and are critical not only for developing new battery chemistries and cell designs but also for engineering reliable battery management systems. Critically, these laboratory experiments aim to quantify and capture realistic aging mechanisms. In this study, we systematically compare dynamic discharge profiles representative of electric vehicle driving to the well-accepted constant-current profiles. Surprisingly, we discovered that dynamic discharge enhances lifetime substantially compared to constant current discharge. Specifically, for the same average current and voltage window, varying the dynamic discharge profile leads to an increase of up to 38 % in equivalent full cycles at end-of-life. Explainable machine learning reveals the importance of low-frequency current pulses as well as time-induced aging under these realistic discharge conditions. Our work quantifies the importance of evaluating new battery chemistries and designs with realistic load profiles, and highlights the opportunities to revisit our understanding of aging mechanisms at the chemistry, materials, and cell levels.

25 ENERGY STORAGE↗
DOE OSTI2025

A split ribozyme system for in vivo plant RNA imaging and genetic engineering

RNA plays a central role in plants, governing various cellular and physiological processes. Monitoring its dynamic abundance provides a discerning understanding of molecular mechanisms underlying plant responses to internal (developmental) and external (environmental) stimuli, paving the way for advances in plant biotechnology to engineer crops with improved resilience, quality and productivity. In general, traditional methods for analysis of RNA abundance in plants require destructive, labour-intensive and time-consuming assays. To overcome these limitations, we developed a transformative innovation for in vivo RNA imaging in plants. Specifically, we established a synthetic split ribozyme system that converts various RNA signals to orthogonal protein outputs, enabling in vivo visualisation of various RNA signals in plants. We demonstrated the utility of this system in transient expression experiments (i.e., leaf infiltration in Nicotiana benthamiana ) to detect RNAs derived from transgenes and tobacco rattle virus, respectively. Also, we successfully engineered a split ribozyme-based biosensor in Arabidopsis thaliana for in vivo visualisation of endogenous gene expression at the cellular level, demonstrating the feasibility of multi-scale (e.g., cellular and tissue level) RNA imaging in plants. Furthermore, we developed a platform for easy incorporation of different protein outputs, allowing for flexible choice of reporters to optimise the detection of target RNAs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Mechanisms Engineering Test Loop (METL) Experimenter's Guide - Revision 2

The Mechanisms Engineering Test Loop (METL) was built to streamline and accelerate the in-sodium testing of systems and components under conditions that simulate a sodium-cooled fast reactor pool environment. The METL team at Argonne National Laboratory (ANL) can assist experimenters in achieving their technical goals by providing liquid-metal expertise and access to infrastructure required for most alkali metal related research. This document offers a brief overview of METL and provides a basic design guide for researchers interested in conducting research at the facility. Additional information regarding the history and operations of METL can be found in §6.1. Furthermore, high resolution images found in this document as well as CAD files of aforementioned vessels can be provided upon request.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Early Fault Detection in Nuclear Systems: A Digital Engineering Approach

Nuclear energy systems present unique challenges in terms of ensuring safety, reliability, and efficiency during their design and operation. Early fault detection is critical for mitigating risks and fostering system resilience. However, current methods often fall short at identifying faults during early stages, potentially leading to costly delays and safety risks. The present work proposes a comprehensive digital engineering approach that leverages digital twins, digital threads, model-based systems engineering, artificial intelligence, and immersive extended reality to support early fault detection in nuclear systems. Through a series of case studies, we highlight specific gaps in the fault detection mechanisms of traditional nuclear design and operation processes, then demonstrate a suite of solutions we are working to implement to address these shortcomings in similar projects. Our findings suggest that a digital engineering approach to design and operation can significantly improve fault detection, ultimately leading to reductions in risk.

42 - ENGINEERING↗
DOE OSTI2025

Software For Advanced Large-scale Analysis Of Magnetic Confinement For Numerical Design, Engineering & Research (salamander)

As magnetic confinement fusion energy gains traction internationally to enable abundant energy production, designing components for fusion systems is a pressing challenge. During the planned lifetime of a fusion device, components evolve in extreme environments and must withstand large, repeated thermal loads and bombardment by 14 MeV neutrons, plasma ions, and neutral particles (deuterium, tritium, and helium), corrosive conditions, etc. All these physical processes take place simultaneously, interact in intricate ways, and impose important constraints that can affect performance. Experimental data is rare and costly to obtain, making design particularly challenging. Predictive computational frameworks must be an integral part of an accelerated and cost-effective design process by modeling fusion system performance in simulated environments. To better understand component degradation and operational impacts on their performance, the Software for Advanced Large-scale Analysis of MAgnetic confinement for Numerical Design, Engineering & Research (SALAMANDER) is designed as an open-source, fully integrated, multiphysics, multiscale, NQA-1 compliant framework facilitating 3D, high-fidelity fusion system modeling. To that end, SALAMANDER is a MOOSE-based framework, and therefore leverages MOOSE upstream libraries such as PETSc and libMesh to deliver sophisticated finite element, finite volume, and nonlinear solver technology for fusion energy simulations. SALAMANDER couples MOOSE physics module capabilities—such as thermal hydraulics, heat conduction, Navier-Stokes, and thermomechanics—with tritium transport via TMAP8, neutronics via Cardinal, and nascent particle-in-cell capabilities. Direct simulation Monte Carlo methods will be used to address neutral transport near the walls. By coupling all these physics in an integrated application, SALAMANDER will enable high-fidelity modeling of irradiation levels and plasma exposure conditions of plasma facing components and their impact on heat and tritium distributions, as well as the resulting mechanical constraints experienced by the plasma facing components and performance of blanket systems. Furthermore, SALAMANDER will be particularly suited for engineering studies thanks to the stochastic tool module readily available in MOOSE, allowing for extended uncertainty quantification and risk analysis studies. It is also able to use computer-aided design (CAD) meshes to model complex geometries, which is indispensable for fusion systems. SALAMANDER therefore supports design, safety, engineering, and research projects for magnetic confinement fusion systems

Simon, Pierre-Clement [Idaho National Laboratory (↗
DOE OSTI2024

Community Geothermal: Mechanical, Electrical, and Plumbing Design Report and Drawings - Wallingford, CT

Included here are the mechanical, electrical, and plumbing design report and drawings for the proposed community geothermal system at an affordable housing complex in Wallingford, Connecticut. The report and drawings were developed by LN Consulting, in partnership with the University of Connecticut, which completed the energy modeling that formed the basis of the design work. The drawings can be used as a basis for a Request for Proposals to procure entities to complete construction-ready design documents.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

CIE Analysis Process for Engineered Systems

"CIE Analysis Process for Engineered Systems" outlines a comprehensive methodology for integrating Cyber-Informed Engineering (CIE) principles into both new and existing engineered systems. Sponsored by the U.S. Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (DOE CESER), the process aims to achieve cyber-informed decisions by producing functional security requirements for new systems and retrofitting existing systems to mitigate digital risks. The document details a step-by-step approach, including mission and function definition, digital asset awareness, consequence analysis, and mitigation analysis. It emphasizes the importance of documenting mechanical, electrical, programmable, and network components to protect system functions and provides examples and considerations for each step. The ultimate goal is to ensure that engineered systems remain resilient against cyber threats, maintaining safety, performance, and reliability.

42 - ENGINEERING↗
DOE OSTI2025

Time-Resolved Stochastic Dynamics of Quantum Thermal Machines

Steady-state quantum thermal machines are typically characterized by a continuous flow of heat between different reservoirs. However, at the level of discrete stochastic realizations, heat flow is unraveled as a series of abrupt quantum jumps, each representing an exchange of finite quanta with the environment. Here, in this work, we present a framework that resolves the dynamics of quantum thermal machines into cycles classified as enginelike, coolinglike, or idle. We analyze the statistics of individual cycle types and their durations, enabling us to determine both the fraction of cycles useful for thermodynamic tasks and the average waiting time between cycles of a given type. Central to our analysis is the notion of intermittency, which captures the operational consistency of the machine by assessing the frequency and distribution of idle cycles. Our framework offers a novel approach to characterizing thermal machines, with significant relevance to experiments involving mesoscopic transport through quantum dots.

full counting statistics↗
DOE OSTI2024

Mechanical Engineering Safety Note 1012910313-AA: CEA LTIC Structural Integrity

The LRU Target Insert Cryostat (LTIC) is the end effector of the NIF Cryogenic Target Positioner (CryoTarpos), which houses a cooling system to support cryogenic target experiments at NIF. The LTIC maintains a target at micron level positional stability and millikelvin level temperature stability during a NIF shot and is also subject to a portion of the blast load governed by the solid angle subtended by the blast shield at the front of the system. This MESN evaluates loading of the CEA LTIC, a redesigned LTIC to be fielded at Laser Megajoule (LMJ) in France, which has been designed to lay out requirements agreed upon between LLNL and CEA personnel. The LMJ version of CryoTarpos is referred to as the PCC. A high-level system overview of the LTIC on the PCC is shown.

42 ENGINEERING↗
DOE OSTI2025

Graphene oxide gluing layer enabling macroscale tribology applications of pristine graphene

In recent studies of two-dimensional (2D) nanomaterial-based solid lubricants, the importance of durability has been emerging for real engineering-scale applications. To achieve this, a transfer layer formation is essential to prevent the wear of the mechanical systems. However, it has been challenging for pristine graphene (PG) to induce a material transfer due to chemical inertness. In this study, we suggest an easy-to-process strategy to promote the huge material transfer of the PG onto the counterpart contacting material. We utilized graphene oxide (GO) as a gluing layer between the PG film and the counterpart contact surface to realize the superior tribological performance. The high interaction energy of the GO from its functional groups makes a contribution to the material transfer of PG, which is unveiled by a systematic analysis of the counterpart contact surface and the wear track. The huge solid transfer layer not only makes a wear-resistant contact interface between the transfer layer and the underlying film by densification and oxidation, but also reduces surface interaction energies, finally resulting in a significant improvement in durability.

graphene oxide (GO)↗
DOE OSTI2024

Bayesian Analysis of TRISO Fuel: Quantifying Model Inadequacy, Incorporating Lower-Length-Scale Effects, and Developing Parallel Active Learning Capabilities

The U.S. Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel-cycle systems. This program has been providing engineering-scale support for the continued development of BISON, a high-fidelity, high-resolution fuel performance tool. Fuel behavior in nuclear reactors is governed by a complex network of mechanisms that interact with various other physics aspects in the reactor system. Any model developed to represent fuel behavior will likely be idealized, resulting in uncertainties when comparing their predictions against the observed data. In Fiscal Year (FY)-23, we initiated the Uncertainty Quantification (UQ) work by using Bayesian methods to establish a level of model trustworthiness and further improve it, with a particular emphasis on TRI-Structural isOtropic (TRISO) nuclear fuel. This year, we further expanded on that UQ work by investigating an approach to quantifying model inadequacy and accounting for lower-length scale (LLS) effects in TRISO silver (Ag) release modeling. Furthermore, we are implementing parallel active learning capabilities to reduce the computational cost (i.e., required computational resources and elapsed time) of performing UQ. Specifically, we utilized The Kennedy O’Hagan framework for Bayesian uncertainty quantification (KOH) to account for model inadequacy in TRISO Ag release predictions made by BISON. The KOH framework represents an improvement over the standard Bayesian framework used in FY-23. Explicitly accounting for model inadequacy in the Bayesian framework helps establish the level of experimental noise uncertainty in the Advanced Gas Reactor (AGR) data. We compared the inverse UQ results obtained from both the standard Bayesian and KOH frameworks in light of the AGR-2/3/4 data, and also compared the predictive UQ results obtained from these two frameworks in light of the AGR-1 data. Next, we investigated the impact of considering LLS effects in the Ag release simulations. We developed an expanded database of LLS simulated effective diffusivities for Ag, covering a wide range of microstructures and temperatures. Using this database, we developed a framework for incorporating LLS effects into the engineering-scale Ag release UQ. We developed both parametric and non-parametric approaches for bridging the length scales. We then investigated the inverse UQ results in light of the AGR-2/3/4 data and the predictive UQ results in light of the AGR-1 data, and compared the LLS-informed approach and the Arrhenius equation, which does not include microstructure information. Finally, we discussed implementing parallel active learning capabilities in the Multiphysics Object Oriented Simulation Environment (MOOSE)/BISON to reduce the computational cost (i.e., computational resources and elapsed time) of Bayesian UQ. For verification purposes, we first tested these new capabil ities on a species interaction problem. We then demonstrated them on the TRISO Ag release application, showing that parallel active learning capabilities can enhance the accuracy of UQ while also substantially reducing the computational cost in comparison to the reference methods developed in FY-23.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Cement and concrete as carbon sinks: Transforming a climate challenge into a carbon storage opportunity

Cement and concrete, while traditionally recognized as the main contributors to anthropogenic CO 2 emissions, also have untapped capacity to serve as substantial and scalable carbon sinks. This perspective examines how engineered mineral carbonation can transform cement-based materials into functional carbon storage systems, generating both environmental and economic value. We review the fundamental mechanisms of CO 2 uptake in cementitious systems, highlighting current limitations in reaction kinetics, phase control, and durability under varying environmental conditions. Emphasis is placed on the utilization of alkaline industrial residues and emerging magnesium-based cements, which offer synergistic pathways for carbon sequestration and circular resource use. We further assess the performance trade-offs associated with CO 2 uptake and the feasibility of deploying these technologies on industrial scales. A strategic roadmap is proposed that integrates scientific innovation, regulatory alignment, and carbon accounting in the life cycle to accelerate the adoption of carbon-storing concrete. This perspective provides a comprehensive framework to advance cement and concrete as engineered carbon sinks and supports the transition to a climate-positive construction industry.

Carbon storage↗
DOE OSTI2026

Learning from nature’s plant engineers: Hijacking metabolism and development beyond genetics

Plant metabolism underpins the food, fiber, and fuel that support our economy, driving strong interest in new strategies to rewire plant metabolism for emerging applications. While most synthetic biology efforts are reliant on genetic engineering, plants can be manipulated in many other ways that remain comparatively underexplored. Across nature, diverse organisms, including bacteria, fungi, and insects, have evolved sophisticated mechanisms to exploit plant metabolic richness, reshaping it for purposes that span from basic nutrition to the construction of complex, novel structures for shelters. These interspecies interactions and non-model systems represent unique manners in which plants can be reprogrammed or hijacked by other organisms, offering inspiration for novel approaches to engineering plant metabolism. By better understanding the basis of how organisms induce these remarkable transformations in plants, we can expand the conceptual boundaries of synthetic biology and reveal alternative routes to manipulating plants for the production of a diverse array of valuable compounds and materials. Deeper insight into these mechanisms will yield novel blueprints for rethinking the scope and breadth in which we can redesign plant metabolism across many applications.

Sarkiss, Anthony E. [University of California, Ber↗
DOE OSTI2025

Quantum Software Engineering (Dagstuhl Seminar 24512)

The Dagstuhl Seminar 24512 on "Quantum Software Engineering" was held from December 15 to 20, 2024. It brought together 26 participants from industry and academia from 13 different countries, including senior and junior researchers as well as practitioners in the field of Quantum Software Engineering. The aim of the seminar was to advance software engineering methods and tools for the engineering of hybrid quantum systems by promoting personal interaction and open discussion among researchers who are already working in this emerging area of knowledge. The first day of the seminar was devoted to the topic "When software engineering meets quantum mechanics", while the second day focused on "Quantum software engineering and its challenges." During both days, 16 invited presentations were given. The rest of the seminar was organized into three working groups to address the topics "Quantum Software Design, Modelling and Architecturing", "Adaptive Hybrid Quantum Systems", and "Quantum Software Quality Assurance". The seminar was a very fruitful experience for all participants both in terms of scientific outcomes and in terms of the personal relationships that were generated to jointly address future experiences.

97 MATHEMATICS AND COMPUTING↗