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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Preliminary design analysis workflow for Division 5 HHA-3200 requirements for graphite core components

This report presents a design analysis workflow for graphite core components and assemblies, based on the design rules of ASME Boiler Pressure and Vessel Code, Section III, Division 5, Article HHA-3000. The workflow contains three stages: developing the design of the graphite core component, modeling the component with the finite element software MOOSE, and assessing if the component passes/fails the criteria of the HHA-3000 design rules. Since the design rules use probabilistic metrics specifically established to evaluate brittle materials, we developed a python library that performs all the statistical calculations necessary for the evaluations of the HHA-3000 criteria.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Deep Learning and Natural Language Processing for Accelerated Inverse Design of Optical Metamaterials

Optical metamaterial device design has enjoyed a long track of success over the past 50 years leading to the manipulation of light over a wide range of wavelengths spanning the ultraviolet to the far infrared. The manipulation of light over such wavelengths has already led to many technological advancements such as the design of selective radiative absorbers for solar energy, daytime passive cooling using deep space, and optical invisibility cloaks for defense applications. Further disruptive advancements in energy, defense, computing, and biomedical fields could be enabled or enhanced by future optical metamaterial devices. These technologies could lead to increased energy efficiency and hence reduced national primary energy consumption, cheap long duration energy storage, and next generation solid-state heat engines. But historically the methods to invent and develop all of these devices have been time- consuming and based mostly on intuition and iteration. Finding an optimal design can take years. In this project we developed a machine learning-based algorithm capable of automatically generating device designs to produce desired optical properties, reducing the design cycle life in certain situations to be almost instantaneous.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Random 3D Interpenetrating Electrode Design for Energy Storage Applications

We introduce the concept of random interpenetrating electrode structures, inspired by spinodal decomposition, as a transformative approach for energy storage applications. While ordered architectures, such as double gyroids and Kelvin cell structures, have long been favored for their structural uniformity and surface area utilization, we demonstrate that random structures offer distinct advantages including shorter diffusion pathways, higher packing density, and enhanced reaction kinetics, particularly at low temperatures. Using a combination of computational and electrochemical analysis, we show that random architecture outperforms their ordered counterparts in scenarios where diffusion dominates. This work represents the first systematic exploration of random structures in energy storage, highlighting their potential to overcome limitations of traditional designs. However, challenges such as structural reproducibility and scalability remain, necessitating further investigation into fabrication techniques and material selection. By establishing a framework to optimize random electrode architectures, we provide critical insights into the interplay between geometry, diffusion, and reaction kinetics. This study not only introduces a new design principle for 3D electrodes but also opens pathways for next-generation energy storage systems that demand both high performance and adaptability to a range of operating conditions.

Materials science↗
DOE OSTI2024

Electron-Withdrawing meso -Substituents Turn On Magneto-Optical Activity in Porphyrins

A series of square planar metalloporphyrins (M(TPP), TPP is 5,10,15,20-tetraphenylporphyrin and M(TPFPP), TPFPP is 5,10,15,20-tetrapentafluorophenylporphyrin; M is Zn 2+ , Ni 2+ , Pd 2+ , or Pt 2+ ) with distinct meso-substituents were prepared, and their magneto-optical activity (MOA) was characterized by magnetic circular dichroism (MCD) and magneto-optical rotary dispersion spectroscopy (MORD; also known as Faraday rotation spectroscopy). MOA is crucial in the development of next-generation magneto-optical devices and quantum computing. Here, the data show that the presence of meso-pentafluorophenyl substituents results in significant increase in MOA in comparison to the homologous phenyl group. Differences in the MOA of these metalloporphyrins are rationalized using the Gouterman four-orbital model and pave the way for rational design of improved and tailorable magneto-optical materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Transferring a Molecular Foundation Model for Polymer Property Predictions

Transformer-based large language models have remarkable potential to accelerate design optimization for applications such as drug development and material discovery. Self-supervised pretraining of transformer models requires large-scale data sets, which are often sparsely populated in topical areas such as polymer science. Further, state-of-the-art approaches for polymers conduct data augmentation to generate additional samples but unavoidably incur extra computational costs. In contrast, large-scale open-source data sets are available for small molecules and provide a potential solution to data scarcity through transfer learning. In this work, we show that using transformers pretrained on small molecules and fine-tuned on polymer properties achieves comparable accuracy to those trained on augmented polymer data sets for a series of benchmark prediction tasks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Single-Molecule Electron Transport in Peptoids

Peptoids are structural analogs of peptides in which side chains are appended to the backbone nitrogen rather than the α-carbon. The sequence-defined modularity of peptoids enables precise control over structure−function relationships, enabling applications in energy storage and biomedical materials. Despite recent progress, the role of sequence and conformation on electron transport in peptoid molecules is not fully understood. Here, we synthesize a library of peptoid oligomers and characterize their molecular electronic properties using the scanning tunneling microscope-break junction (STM-BJ) technique. Our results show well-defined electron transport behavior for peptoid sequences containing aromatic side groups lacking hydrogen bonds (H-bonds) and without chemical substitutions at the N−C α position. This behavior fundamentally differs from electron transport in peptides, where H-bond interactions give rise to higher conductance states. All-atom molecular dynamics (MD) simulations are used to understand the conformational heterogeneity of peptoids, and molecular conformations obtained from MD simulations are used in quantum mechanical calculations based on the nonequilibrium Green’s function−density functional theory (NEGF-DFT) formalism. In all cases, computational results are in reasonable qualitative agreement with experiments. Our work demonstrates that the conductance behavior of peptoids depends on monomer identity, including side-chain aromaticity and substitution at the N−C α position. Overall, this work provides new insights into the structure−function relationships governing electron transport in peptoid-based materials and establishes design rules for peptoid-based molecular junctions.

Charge transport↗
DOE OSTI2021

Science and Technology Review June 2021

When the COVID-19 pandemic hit, Lawrence Livermore National Laboratory scientists came together, leveraging many different disciplines and technologies to address this global challenge. Livermore focused on three areas of research: creating alternatives for medical equipment in short supply, such as ventilators and nasal swabs; developing methods to help detect the SARS-CoV-2 virus responsible for COVID-19; and designing medical countermeasures such as antibodies and antivirals to combat the disease.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Literary review and modeling outlook for radiation damage in fused-silica optical fibers

The purpose of this document is to distill, from literature, the effects of radiation damage in fused-silica optical fibers. This information will be used to design a theoretical framework capable of predictive modeling that will be published elsewhere. By inspection of the relevant literature, the devised method is calculation of defect amorphous structures by molecular dynamic techniques, and computation of the macroscopic dielectric function using density functional theory. The dielectric function is then used to directly compute the transmittance of the core material before and after irradiation via solution of Maxwell’s equations in a homogeneous medium.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Extrapolation of the Rainflow-Counted Load Ranges for Fatigue Assessment of the Wind Turbine's Blades

Wind turbine design standards recommend the use of statistical modeling coupled with extrapolation of the short-term load data to long-term periods for fatigue reliability assessment. However, statistical error and computational expense can limit the accuracy of such approaches. In the case of wind turbine blades, the errors are more significant because of the high material fatigue exponent that makes the damage estimations more sensitive to variations. In addition, due to different excitation sources, the flapwise load range histogram is not unimodal, and thus its statistical modeling is complex. In the present work, we provide three methods for statistical modeling of the flapwise bending moment ranges including a novel approach based on frequency-based separation of the modes. The first two methods are simplified approaches for modeling the most crucial load ranges using unimodal distributions and the third method involves multimodal distribution fitting. The research is based on 3600 10-minute aeroelastic simulations of DTU 10MW case study wind turbine from which a benchmark damage equivalent load (DEL) is calculated. The DEL calculated by each of the three proposed methods is compared to this reference. The results show that the conventional approach based on using 6 seeds as well as using mixture models fitted on the limited data lead to under-conservative results with errors up to 23%. On the other hand, the simplified unimodal approaches provided in this work can provide conservative estimations of the fatigue damage with mean values 5% and 12% higher than the benchmark. However, the variability of the DEL estimates is higher when using unimodal extrapolation of the load ranges, and the data can be conservative by 17.5%. The proposed unimodal fits suggested for modeling and extrapolation of the blade's load ranges provide less errors relatively and most importantly conservative DEL estimations while maintaining computational efficiency.

blade fatigue↗
DOE OSTI2023

Multiple Critical Unresolved Region Integral Experiment (MCURIE): A Proposed Integral Critical Experimental Framework for Unresolved Region and Intermediate Energies

The Critical Unresolved Region Integral Experiment (CURIE) critical experiment was performed at the National Criticality Experiments Research Center (NCERC) at the Device Assembly Facility (DAF) at the Nevada Nuclear Security Sites (NNSS) in 2020. The objective of CURIE was to improve the quality of integral nuclear data in the uranium-235 ( 235 U) unresolved resonance region (URR) by performing benchmark integral experiments that were sensitive to the URR energy ranges. The CURIE experiment was evaluated for the International Criticality Safety Benchmark Evaluation Project (ICSBEP) handbook and the benchmark evaluation was accepted in 2022. The URR is a region within the intermediate neutron energy range (the intermediate energy ranges from 0.7 eV to 100 keV). The observed resonance structure in neutron cross sections is due to discrete energy levels in the nucleus and are characterized by resonance parameters. In the URR region, the resonance parameters are only partially resolved as the resolution of the experiment techniques becomes comparable to the average width of the resonances themselves, and the resonances are so close to one another that the structure cannot be determined empirically. The ENDF/B-VIII.0 and JEFF-3.3 nuclear data libraries define the URR as beginning at 2.25 keV and continuing until 25 keV. There are minimal intermediate neutron energy benchmarks available in the ICSBEP benchmark handbook, and aside from CURIE there are none that are highly sensitive in the URR energy region. There is a current need for additional experiments sensitive to the URR energy region. There is a new proposed subgroup for the Organization for Economic Co-operation and Development and Nuclear Energy Agency (OECD NEA) Working Party on International Nuclear Data Evaluation Cooperation (WPEC), so any new models or information will need experimental validation and testing. The NEA Working Party on Nuclear Criticality Safety (WPNCS) recent experimental needs and priority list includes intermediate energy 235 U and 238 U experiments, as does the recent Integral Experiments to Address Nuclear Criticality Safety Needs Meeting (May 2023). A variant on the original CURIE experiment called the Multiple Critical Unresolved Region Integral Experiment (MCURIE) is proposed to provide further investigation of the intermediate and URR energy region for uranium. MCURIE will utilize existing fuels at NCERC but use alternative moderators and reflectors to modify the neutron absorption, scattering, and fission spectra of the experiments, allowing for precise targeting of nuclear data sensitivities. The overall goal of MCURIE is to develop a framework for designing and performing integral benchmark experiments with high sensitivities in the intermediate and URR energy regions for nuclear data validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Dual-Purpose Canister Filling Demonstration Project Progress Report

This report discusses the initial progress made at the Oak Ridge National Laboratory to support direct disposal of dual-purpose canisters (DPCs) using filler materials to demonstrate that the probability of criticality in DPCs during disposal to be below the probability for inclusion in a repository performance assessment. In the initial phase of a multi-phase effort that will result in a full-scale demonstration, a computational fluid dynamics (CFD) model was developed to gauge the filling process and to uncover any unforeseen issues. The initial filling simulations of the lower region (mouse holes) of a prototypic DPC show successful removal of the inner space voids and smooth, even progression of the liquid level. In the initial phase, flow through a pipe that is similar to the drain pipe in a DPC will be investigated separately to gain valuable insight of flow regime inside a pipe. The initial experimental setups for validating the computational filling model have been designed, and the various assembly parts are being procured. The experience gained from the initial experiments will be applied to the next steps toward a full-scale demonstration and to the validation of multiphysics filling simulation models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Design of Next-Gen Cathode Materials With Both Cation and Anion Redox

Among all candidates of positive electrode materials for lithium ion batteries, the lithium rich layered oxides have gained growing research interests in recent years. Their energy density can reach closely to 700-900Wh/g (at materials level), making them the positive electrode materials with highest energy density among all known intercalation compounds for cathode materials. Combining both first principles computation, advanced electron and X-ray based imaging, we demonstrated that in the Li-rich materials oxygen vacancies are present and assist the transition metal ion migration through a facile mechanism. This means it is critically important to control the oxygen activities in these compounds for high voltage operations. In addition, the NiMn spinel oxides show little oxygen activities and under optimized synthesis condition the electrolyte/electrode interface showed superior stability. Combining the strengths of materials synthesis and the advanced characterization, I will discuss in details the strategies for stabilizing the anion redox for higher voltage electrode materials for lithium ion batteries.

Meng, Ying Shirley↗
DOE OSTI2026

Cost-Benefit Assessment of Additive Manufacturing for Injection Molds

This report presents an additive-manufacturing (AM) technology, where AM Cyclic Olefin Resin (COR) molds would be used for injection molding. The National Laboratory of the Rockies (NLR) team has focused on the costs and economics of this developing technology. This report presents a cost-benefit analysis of using the polySpectra AM COR molds made of COR, at the start of the project (Present') and the potential lifetime, cost-effectiveness, and performance by the end of the project period (Period 3'). The analysis of the AM COR molds is compared to traditional Computer Numerical Control (CNC) machined aluminum molds across the time periods. A cost-benefit model framework has been developed to evaluate AM COR molds. This model accounts for mold delivery to customers, current and future levels of technology readiness, the type of material injected, and various business cases. AM COR molds offer a major advantage in lead time, reducing production setup from weeks or months (with CNC machining) to as little as two to five days. This enables faster prototyping, quicker design cycles, and accelerated time-to-market, critical in industries like electronics, aerospace, medical devices, and automotive. Even modest improvements in the durability of polySpectra AM COR molds show the potential for these molds to complement traditional tooling. With further development, AM COR mold technology could provide significant time and cost savings while supporting increased domestic manufacturing capacity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Constructing Water‐Stable Porous Organic Salts via Suppressed Proton Integration Using Fluorinated Tetrazole Tectons

Porous organic salts (POSs) are an emerging class of materials with ordered ionic architectures, offering excellent proton transfer and water uptake properties. However, conventional POS synthesis via strong acid–base neutralization (e.g., ─SO₃H and ─NH₂) leads to extensive hydrogen bonding with water, compromising stability in aqueous and water-lean environments. Here, we address this challenge by designing POSs with hydrophobic porous channels and minimal hydrogen bonding formation. Our key innovation is the use of fluorinated tetrazole as a weak acid tecton and a tetra-substituted imidazole precursor devoid of active protons as the base. Single-crystal analysis and computational modeling reveal that the structural integrity of the synthesized POSs arises primarily from cation–anion interactions, with water confined as clusters in the pores, independent of hydrogen bonding with the scaffold. Robustness of the POS structure under aqueous and water-lean conditions is confirmed by X-ray and neutron scattering, as well as computational modeling, confirming preserved packing and crystal structures. The stability of POS is further demonstrated in aqueous iodine capture, with imidazolium cations and C–F functionalizations serving as strong adsorption sites. As a result, the approach developed herein further pushes the boundary of POS materials to withstand both aqueous and water-lean conditions.

Fluorinated tecton↗
DOE OSTI2024

Liquid metal walls

Here, the plasma performance of fusion devices depends strongly on the chosen wall materials. Solid plasma-facing components (PFCs) are predominantly used in present devices, and are the most investigated candidates for fusion designs. High-Z materials such as tungsten (W) are the leading solid PFC material candidates. To date, a material choice that scales to steady-state reactor conditions has not been identified. Moreover, if plasma transient events such as edge-localized modes and disruptions cannot be altogether avoided or sufficiently mitigated, the projected peak heat and particle loads far exceed the power exhaust capabilities of solids. Liquid metal (LM) PFCs represent an intrinsic self-healing boundary that are both resilient to surface damage from transients, and that could handle high steady-state heat and particle fluxes. Flowing LM PFCs can be designed to remove “slag,” the buildup of material erosion due to plasma-material interactions, including charge exchange sputtering in the main chamber. Further, LM offer the prospect to manage hydrogenic species otherwise retained in the PFCs, which is important from a safety and inventory standpoint. The two most promising LMs are lithium (Li) and tin (Sn), although Sn–Li eutectics may be considered. While Sn offers a higher temperature window with low vapor pressure and low hydrogen retention, Li offers the prospect of enhanced energy confinement and higher acceptable core contamination limits, and this section focuses on Li PFCs. An LM PFC development research program developed LM PFC concepts for a nuclear fusion device via engineering design calculations, single-effect experiments, and staged prototypical experiments. A self-consistent design window was identified with liquid Li flow speeds ~5–10 m/s; plasma contamination was negligible for predicted Li evolution rates. While these preconceptual designs hold promise, there is substantial R&D needed to advance the technical readiness levels of LM PFCs for application to fusion power plants.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Phase Selection Rules of Multi‐Principal Element Alloys

Abstract Computational prediction of phase stability of multi‐principal element alloys (MPEAs) holds a lot of promise for rapid exploration of the enormous design space and autonomous discovery of superior structural and functional properties. Regardless of many plausible works that rely on phenomenological theory and machine learning, precise prediction is still limited by insufficient data and the lack of interpretability of some machine learning algorithms, e.g., convolutional neural network. In this work, a comprehensive approach is presented, encompassing the development of a complete dataset that contains 72 387 density functional theory calculations, as well as a predictive global phenomenological descriptor. The phase selection descriptor, based on atomic electronegativity and valence electron concentration, significantly outperforms the widely used valence electron concentration, excelling in both accuracy (with an f1 score of 63% compared to 47%) and its ability to predict the HCP phase (0.48 recall compared to 0). The comprehensive data mining on the global design space of 61 425 quaternary MPEAs made from 28 possible metals, together with the phenomenological theory and physical interpretation, will set up a solid computational science foundation for data‐driven exploration of MPEAs.

Chemistry↗
DOE OSTI2024

Additive manufacturing of LiCoO 2 electrodes via vat photopolymerization for lithium ion batteries

Additive manufacturing has the potential to revolutionize the fabrication of lithium-ion batteries for a diversity of applications including in portable, biomedical, aerospace, and the transportation fields. Standard commercial batteries consist of stacked layers of various components (current collectors, cathode, anode, separator and electrolyte) in a two-dimensional manner. By leveraging the latest advances in additive manufacturing and computer-aided design, an improved geometric and electrochemical configuration of these batteries can maximize energy efficiency while allowing design optimization to reduce dead space for a given application. In this work, a composite UV photosensitive resin was prepared and used as feedstock in a vat photopolymerization system. The resin was loaded with LiCoO 2 acting as electrochemically active material for the cathode of a lithium-ion battery, and was further improved with the addition of conductivity-enhancing carbonaceous additives. Challenges to additive manufacturing arise from the opacity and high viscosity of the composite nature of these electrochemically-active resins, which cause light refraction during selective UV curing. Subsequently, items were printed and subjected to a thermal post-processing step to obtain an adequate compromise between electrochemical performance and mechanical integrity. Both sintered and green state 3D printed cathodes were assembled into half-cell lithium-ion batteries using lithium metal as a reference and counter electrode. Electrochemical cycling of these batteries yielded satisfactory results approaching commercial LiCoO 2 cathodes’ performance, with the potential advantages of additive manufacturing – high surface area anode–cathode configurations for power performance as well as shape conformability.

25 ENERGY STORAGE↗
DOE OSTI2020

Assessment of Critical Experiment Benchmark Applicability to a Large-Capacity HALEU Transportation Package Concept

This work presents an assessment of the applicability of existing benchmark critical experiments to the criticality safety code validation for a large-capacity high-assay low-enriched uranium (HALEU) transportation package concept. Numerous next-generation nuclear reactor designs require HALEU fuel, which is characterized by an enrichment between 5 and 20 wt% 235 U. The U.S. Department of Energy (DOE) has proposed to recover and downblend highly enriched uranium from DOE-owned used nuclear fuel to accelerate the demonstration of commercially viable microreactor technologies. One element of the infrastructure needed to demonstrate HALEU-fueled reactors is the ability to safely transport enriched product to be used for fuel fabrication. There is uncertainty as to whether existing critical benchmark experiment data are sufficient to support criticality safety code validation for HALEU transportation applications. The anticipated chemical form of the HALEU in the proposed transportation concept is UO 2 with 20 wt% 235 U/U. The concept uses a combination of an existing transportation packaging design and a novel basket design, including borated aluminum flux traps. The basket provides space for 18 reusable, stainless steel canisters that contain the HALEU. In 10 CFR 71, normal conditions of transport (NCTs) and hypothetical accident conditions (HACs) are defined for fissile material transportation packages. NCT and HAC KENO-VI models of the transportation package were developed using the Standardized Computer Analyses for Licensing Evaluation (SCALE) 6.2.3 computer code package, and optimum moderation conditions were determined using the SCALE SAMPLER sequence. The SCALE Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI) sequences were then used to compare the neutronic characteristics of 1584 International Criticality Safety Benchmark Evaluation Project benchmark critical experiments with the NCT and HAC HALEU transportation models. The TSUNAMI integral correlation coefficient c k was the criterion used to rank neutronic similarity. Thirty-four experiments were identified as similar (c k ≥ 0.9) to the NCT model, and 55 experiments were identified as similar to the HAC model. Hundreds of experiments were also identified as at least marginally similar (c k ≥ 0.8) to both models. The results indicate that additional critical experiments are unlikely to be needed to support HALEU transportation criticality safety analyses for package concepts similar to the concept package analyzed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗