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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

First characterisation of the MAGO cavity, a superconducting RF detector for kHz–MHz gravitational waves

Heterodyne detection using microwave cavities is a promising method for detecting high-frequency gravitational waves (GWs) or ultralight axion dark matter. In this work, we report on studies conducted on a spherical 2-cell cavity developed by the MAGO collaboration for high-frequency GWs detection. Although fabricated around 20 years ago, the cavity had not been used since. Due to deviations from the nominal geometry, we conducted a mechanical survey and performed room-temperature plastic tuning. Measurements and simulations of the mechanical resonances and electromagnetic properties were carried out, as these are critical for estimating the cavity’s GW coupling potential. Based on these results, we plan further studies in a cryogenic environment. The cavity characterisation does not only provide valuable experience for a planned physics run but also informs the future development of improved cavity designs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Sustainable production of plastic-degrading enzymes in Chlamydomonas pacifica

AbstractThe discovery of a new extremophile alga,Chlamydomonas pacifica, provides an opportunity to expand on heterologous protein expression beyond the traditionalChlamydomonas reinhardtii. C. pacificais a unicellular extremophile capable of surviving at high pH, high temperatures, and high salinity. These various growth conditions allow C. pacifica to outcompete any invading contaminants in open-air environments. Developing this novel species as a platform for recombinant protein production could significantly advance commercial microalgal recombinant protein production. We have previously shown thatC. reinhardtiican secrete a plastic-degrading enzyme: a PETase known as PHL7. This PETase is capable of cleaving ester bonds and has been used commercially for the degradation of PET plastics. However, the expression of such an enzyme has yet to be done in open raceway ponds and on a large scale. Here, we describe the culturing of PHL7 transgenic C. pacifica strain in three 80L raceway ponds and the measurements of recombinant enzymatic expression and activity found in the culture media. Our work provides proof of concept that this new organism can produce functional PHL7 enzymes in addition to producing the valuable components that inherently exist in theC. pacificaalgae biomass.Graphical Abstract

Diaz, Crisandra Jade (ORCID:0000000173429041)↗
DOE OSTI2023

Optimization of C. ljungdahlii for the Valorization of Combustion Off-Gas

One of the largest problems that faces the realization of the circular economy is the gap between waste streams and usable commodities. Synthetic biology enables a toolkit where this gap can begin to be addressed and closed. This work focuses on using synthetic biology techniques to optimize C. ljungdahlii for the valorization of combustion off-gas waste streams and navigates how to produce 3-hydroxybutyrate, a polymer precursor off of similar-composition syn-gas streams. If successful, these techniques can realize a carbon-negative solution to producing plastics.

3-hydroxybutyrate↗
DOE OSTI2021

Towards stacking fault energy engineering in FCC high entropy alloys

Stacking Fault Energy (SFE) is an intrinsic alloy property that governs much of the plastic deformation mechanisms observed in fcc alloys. While SFE has been recognized for many years as a key intrinsic mechanical property, its inference via experimental observations or prediction using, for example, computationally intensive first-principles methods is challenging. This difficulty precludes the explicit use of SFE as an alloy design parameter. In this work, we combine DFT calculations (with necessary configurational averaging), machine-learning (ML) and physics-based models to predict the SFE in the fcc CoCrFeMnNiV-Al high-entropy alloy space. The best-performing ML model is capable of accurately predicting the SFE of arbitrary compositions within this 7-element system. Finally, this efficient model along with a recently developed model to estimate intrinsic strength of fcc HEAs is used to explore the strength–SFE Pareto front, predicting new-candidate alloys with particularly interesting mechanical behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response

Composite materials with different microstructural material symmetries are common in engineering applications where grain structure, alloying and particle/fiber packing are optimized via controlled manufacturing. In fact these microstructural tunings can be done throughout a part to achieve functional gradation and optimization at a structural level. To predict the performance of particular microstructural configuration and thereby overall performance, constitutive models of materials with microstructure are needed. In this work we provide neural network architectures that provide effective homogenization models of materials with anisotropic components. These models satisfy equivariance and material symmetry principles inherently through a combination of equivariant and tensor basis operations. We demonstrate them on datasets of stochastic volume elements with different textures and phases where the material undergoes elastic and plastic deformation, and show that the these network architectures provide significant performance improvements.

anisotropy↗
DOE OSTI2024

Additive Friction Stir Deposition of a Tantalum–Tungsten Refractory Alloy

Additive friction stir deposition (AFSD) is a solid-state metal additive manufacturing technique, which utilizes frictional heating and plastic deformation to create large deposits and parts. Much like its cousin processes, friction stir welding and friction stir processing, AFSD has seen the most compatibility and use with lower-temperature metals, such as aluminum; however, there is growing interest in higher-temperature materials, such as titanium and steel alloys. In this work, we explore the deposition of an ultrahigh-temperature refractory material, specifically, a tantalum–tungsten (TaW) alloy. The solid-state nature of AFSD means refractory process temperatures are significantly lower than those for melt-based additive manufacturing techniques; however, they still pose difficult challenges, especially in regards to AFSD tooling. In this study, we perform initial deposition trials of TaW using twin-rod-style AFSD with a high-temperature tungsten–rhenium-based tool. Many challenges arise because of the high temperatures of the process and high mechanical demand on AFSD machine hardware to process the strong refractory alloy. Despite these challenges, successful deposits of the material were produced and characterized. Mechanical testing of the deposited material shows improved yield strength over that of the annealed reference material, and this strengthening is mostly attributed to the refined recrystallized microstructure typical of AFSD. These findings highlight the opportunities and challenges associated with ultrahigh-temperature AFSD, as well as provide some of the first published insights into twin-rod-style AFSD process behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Separation of High Purity Oxygenated Aromatics from Catalytic Fast Pyrolysis Organic Streams

Thermochemical conversion of lignocellulosic biomass offers an attractive route to produce fuels and chemicals. Specifically, catalytic fast pyrolysis (CFP) oils have been shown to contain a high concentration of oxygenated aromatics, which can be isolated as value-added co-products. Purification of oxygenated aromatics can be a viable pathway to more economically competitive biorefineries, yet the isolation of highly pure coproduct streams remains technically challenging due to the high chemical heterogeneity of thermochemical process steams. Here, we demonstrate an industrially scalable process for isolating phenol, a widely used precursor to plastics, from CFP oil. Importantly, we leverage standard industrial processes, such as distillation, liquid-liquid extraction, and crystallization, to achieve phenol with 97% purity. In addition, the primary distillation of the CFP oil yielded several other fractions that contain chemicals with the potential to be isolated (e.g. cyclic ketones, cresols, and guaiacols). This work provides a technically feasible path to high purity oxygenated aromatics that has the potential to offset fuel production costs in a biorefinery.

09 BIOMASS FUELS↗
DOE OSTI2025

Recycling Disassembled Automotive Plastic Components for New Vehicle Components: Enabling the Automotive Circular Economy

As the automotive industry increasingly relies on plastic components to meet fuel efficiency and emissions targets, the challenge of managing end-of-life vehicle (ELV) plastics continues to grow. Currently, more than 80% of ELV plastics in the U.S. are landfilled due to limited economic incentives and technical barriers to recycling. This study examines a mechanical recycling pathway for thermoplastic components disassembled from ELVs and assesses their usability for reintegration into new vehicle parts. Four representative materials were chosen based on material labels embedded in recovered parts and aligned with their virgin industrial equivalents: polypropylene (PP), 10% talc-filled PP (PP-T10), 20% talc-filled PP (PP-T20), and a 20% glass-/mineral-filled polyamide (PA6 + GF7 + MF13). The materials underwent shredding, drying, and injection molding before being characterized by particle size analysis, density measurement, thermal analysis (TGA, DSC), mechanical testing, and heat deflection temperature (HDT) evaluation. The results in this work indicated that minor differences in crystallinity were observed and small differences between model materials and ELV materials could have contributed to these changes. Mechanical testing revealed that neat polypropylene suffered a 15–20% reduction in stiffness and tensile strength, but talc-filled polypropylene and glass/mineral-filled nylon retained >90% of their modulus, strength, and heat deflection temperature values relative to virgin controls. Differences between virgin and ELV materials could have been attributed to use life degradation, contamination during use life, or even chemical/processing differences in model materials and ELV materials. However, these findings suggest that mechanically recycled, disassembled ELV plastics can retain sufficient structural performance to support circularity efforts in the automotive sector.

automotive recycling↗
DOE OSTI2020

Microstructure, hardness and cavitation erosion resistance of different cold spray coatings on stainless steel 316 for hydropower applications

There is an urgent need for repair of hydropower components that have undergone damage due to cavitation. Conventional repair methods involve melting of materials and can deteriorate material properties and cause distortion. This study investigated the relevant properties of different materials using solid phase processing—cold spray technology. Stainless steel (SS) 316, Inconel 625 and CrC-NiCr materials were cold spray deposited onto base metal SS 316, respectively. Cold spray achieved dense uniform deposits with low level porosity, and intimate contact between the deposit and the base metal was observed. Severe plastic deformation imparted during the cold spray process resulted in significant grain size refinement, nanostructured regions were observed in the deposits across the interfacial area. Cold sprayed deposits exhibited elevated hardness in contrast to that of the base metal SS 316. The cavitation erosion resistance of the deposits was evaluated with a cavitation erosion jet adhering to ASTM G134. Both SS 316 and Inconel 625 achieved better cavitation erosion resistance when compared to that of the SS 316 base metal, with the former exhibiting close to a 4 times improvement.

Jiang, Xiujuan↗
DOE OSTI2024

Strain Field Around Individual Dislocations Controls Failure

Understanding material failure on a fundamental level is a key aspect in the design of robust structural materials, especially for metals and alloys capable to undergo plastic deformation. In the last decade, significant progress is made in quantifying the stresses associated with failure in both experiments and simulations. Nonetheless, the processes occurring on the most essential level of individual dislocations that govern semi-brittle and ductile fracture are still experimentally not accessible, limiting the failure prediction capabilities. Therefore, in the present work, a one-of-a-kind nanoscale fracture experiment is conducted on a single crystalline Cr bending beam in situ in the transmission electron microscope and for the first time quantify the transient strains around individual dislocations, as well as of the whole dislocation network during crack opening. The results reveal the importance of both pre-existing and newly emitted dislocations for crack-tip shielding via their intrinsic strain field and provide guidelines to design more damage tolerant materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Measuring thermal profiles in high explosives using neural networks

We present a new method for calculating the temperature profile of high explosive (HE) material using a Convolutional Neural Network (CNN). To train/test the CNN, we have developed a hybrid experiment/simulation method for collecting acoustic and temperature data. We experimentally heat cylindrical containers of HE material until detonation/deflagration, where we continuously measure the acoustic bursts through the HE using multiple acoustic transducers lined around the exterior container circumference. However, measuring the temperature profile in the HE in an experiment would require inserting a large number of thermal probes, which would disrupt the heating process. Thus, we use two thermal probes, one at the HE center and one at the wall. We then use numerical simulation of the heating process to calculate the temperature distribution and correct the simulated temperatures based on the experimental center and wall temperatures. We calculate temperature errors on the order of 15 °C, which is ∼12% of the range of temperatures in the experiment. We also investigate how the algorithm’s accuracy is affected by the number of acoustic receivers used to collect each measurement and the resolution of the temperature prediction. This work provides a means of assessing the safety status of HE material, which cannot be achieved using existing temperature measurement methods. In addition, it has implications for a range of other applications where internal temperature profile measurements would provide critical information. These applications include detecting chemical reactions, observing thermodynamic processes such as combustion, monitoring metal or plastic casting, determining the energy density in thermal storage capsules, and identifying abnormal battery operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Measuring thermal profiles in high explosives using neural networks

We present a new method for calculating the temperature profile of high explosive (HE) material using a Convolutional Neural Network (CNN). To train/test the CNN, we have developed a hybrid experiment/simulation method for collecting acoustic and temperature data. We experimentally heat cylindrical containers of HE material until detonation/deflagration, where we continuously measure the acoustic bursts through the HE using multiple acoustic transducers lined around the exterior container circumference. However, measuring the temperature profile in the HE in an experiment would require inserting a large number of thermal probes, which would disrupt the heating process. Thus, we use two thermal probes, one at the HE center and one at the wall. We then use numerical simulation of the heating process to calculate the temperature distribution and correct the simulated temperatures based on the experimental center and wall temperatures. We calculate temperature errors on the order of 15 °C, which is ~12% of the range of temperatures in the experiment. We also investigate how the algorithm’s accuracy is affected by the number of acoustic receivers used to collect each measurement and the resolution of the temperature prediction. This work provides a means of assessing the safety status of HE material, which cannot be achieved using existing temperature measurement methods. In addition, it has implications for a range of other applications where internal temperature profile measurements would provide critical information. These applications include detecting chemical reactions, observing thermodynamic processes such as combustion, monitoring metal or plastic casting, determining the energy density in thermal storage capsules, and identifying abnormal battery operations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Screening green solvents for multilayer plastic film recycling processes

Multilayer (ML) plastic films are essential packaging materials that help protect products from diverse external factors; however, only 5% of all ML films are recycled in the United States. Solvent-based technologies are a promising alternative for recycling ML films because they enable recovery of constituent polymer resins. For example, the Solvent Targeted Recovery and Precipitation (STRAPTM) process sequentially dissolves and separates polymer components using a series of targeted solvent washes. A crucial design aspect of this process is the impact of selected solvents on human health and on the environment. Here, this work introduces a computational framework that integrates molecular modeling, process modeling, techno-economic analysis (TEA), and life-cycle analysis (LCA) to quickly screen green solvents for solvent-based ML recycling processes. Initial screening for solvents based on selectivity is performed by estimating temperature-dependent solubilities using molecular-scale models. Subsequent screening uses basic estimates of energy use and octanol-water partition coefficients (logP) as key measures of health, safety, and environmental hazards. Detailed process modeling, TEA, and LCA are used on a reduced set of promising solvents identified in early screening steps to more accurately determine how solvent selection and associated operating conditions impact overall economics and environmental impacts. The framework is used for the identification of green solvents (from a database of 1,000 solvents) that separate an industrial ML film composed of polyethylene (PE), ethylene vinyl alcohol (EVOH), and polyethylene terephthalate (PET). Our analysis shows the effectiveness of the framework and reveals fundamental trade-offs between solvent greenness, solubility, and economics. Our work emphasizes the importance of taking a holistic systems view during solvent design and aims to inform the development of new processes for ML film recycling and the identification of new ML films that are easier to recycle.

economics↗
DOE OSTI2021

A microstructure-based modeling approach to predict the mechanical properties of Zr alloy with hydride precipitates

In nuclear reactors, hydrides can form in fuel cladding due to hydrogen absorption in ZIrcaloy and cause embrittlement. This work presents a microstructure-based finite element model to predict the stress-strain response of Zircaloy containing hydrides. Quantitative microstructural details extracted from scanning electron microscopy (SEM) images were used to generate heterogeneous microstructures including the morphology and spatial distribution of hydrides. The constitutive material model for zircaloy in this study is based on crystal plasticity theory which considers the hexagonal close-packed (HCP) atomic structure of Zircaloy material. The hydrides were modeled as brittle material along with a damage model. Hydride formation inside the zircoloy matrix results in residual stress. This phenomenon is also captured in this model. A parametric study has been conducted to understand the effect of volume fraction, orientation, and lamellae thickness of the hydride phase on the mechanical properties of the overall material.

Kulkarni, Shank S.↗
DOE OSTI2019

Toward Long-Life, Ultrahigh-Nickel Layered Oxide Cathodes for Lithium-Ion Batteries: Optimizing the Interphase Chemistry with a Dual-Functional Polymer

Boosting the Ni content in LiMO 2 (M = Ni, Co, Mn, etc.) layered oxides is a promising way to establish high-energydensity, low-cost cathodes, but the poor cathode surface stability is a daunting challenge for their practical viability. Herein, by constructing a dual-functional binder framework with a conductive polymer - polyaniline (PANI), the ultrahigh-Ni layered oxide cathode (LiNi 0.94 Co 0.06 O 2 ) exhibits significantly improved cyclability, with a capacity retention greatly increased from 47% to 81% over 1,000 cycles in full cells. It is demonstrated that the acidic species (e.g. HF) in the electrolyte can be efficiently scavenged through a protonation process of PANI, hence the cathode surface reactivity is greatly suppressed and the rock-salt phase propagation into bulk structure is considerably alleviated. Furthermore, the PANI binder system effectively prevents both the cathode-electrolyte interphase (CEI) and anode-electrolyte interphase (AEI) from degrading to a thick “triple-layer” architecture upon extensive cycling, resulting in more robust, thinner CEI and AEI with regulated interphasial chemistry. Moreover, the delocalized π-conjugated electrons along the backbone of PANI facilitate fast electron transfer and promote rate capability even at low temperatures (-20 °C). Finally, this work sheds light on rational binder engineering for developing high-energy-density lithium-ion batteries with acceptable cycle life.

25 ENERGY STORAGE↗
DOE OSTI2020

Modular Linear Thermoviscoelastic Model

Time-dependent, viscoelastic responses of materials like polymers and glasses have long been studied. As such, a variety of models have been put forth to describe the behavior including simple rheological models (e.g. Maxwell, Kelvin), linear "fading memory" theories, and hereditary integral based linear thermal viscoelastic approaches as well as more recent nonlinear theories that are either integral, fictive temperature, or differential internal state variable based. The current work details a new LINEAR_THERMOVISCOELASTIC model that has been added to LAME. This formulation represents a viscoelastic theory that neglects some of the phenomenological details of the PEC/SPEC models in favor of efficiency and simplicity. Furthermore, this new model is a first step towards developing "modular" viscoelastic capabilities akin to those available with hardening descriptions for plasticity models in LAME. Specifically, multiple different (including user-defined) shift-factor forms are implemented with each being easily selected via parameter specification rather than requiring distinct material models.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Interpenetration and kinetic effects in converging, high-energy plasma jets

In this work, we report on numerical simulations of laser-driven convergent plasma fusion targets. These “inverted corona” fusion targets are useful for the study of counter-streaming and converging rarefied plasma flows, and previous experiments have demonstrated their potential as neutron sources. The scheme consists of a fuel layer lined along the interior surface of a hollow plastic shell that is laser-ablated and expands inward towards the target center. The plasma streams generated in these targets are initially nearly collisionless as they converge, leading to wide interaction length scales and long interaction time scales as the jets interpenetrate. Such kinetic effects impact mixing of constituent ions - a phenomenon not properly captured by single-fluid hydrodynamic simulations. Here we conduct numerical simulations using two different methods: (1) single-fluid simulations in HYDRA, and (2) kinetic-ion, fluid-electron hybrid particle-in-cell (PIC) simulations in the code Chicago. It is shown that the initially nearly collisionless plasma fronts interpenetrate deeply and lead to broader interaction regions in space and time resulting in significant beam-beam fusion. The two approaches make different, testable predictions for the effect of fuel-layer thickness on neutron yield.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Tuning of Multicell Superconducting Accelerating Cavities Using Pressurized Balloons

Plastic tuning of multicell superconducting accelerating cavities is crucial in the development cycle of cavities for particle accelerators. Cavities must meet stringent requirements regarding the operating mode frequency, field flatness, and eccentricity before lining them up in a cryomodule string. After dressing bare cavities with helium vessels, the welded vessel prevents access to individual cavity cells disallowing any further localized tuning. Currently, there is no straightforward way to tune dressed cavities other than cutting the vessel and then tuning the bare cavity and dressing it back, which would significantly impact cost and schedule. In this work, we present a novel tuning technique for already jacketed cavities that is non-invasive and cost-effective. The proposed scheme employs pressurized balloons to be temporarily deployed inside the cavity as a means to localize mechanical deformation in specific cells. The proposed tuning technique was successfully utilized to recover a 9-cell 1.3 GHz tesla-style cavity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗