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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 109 records · Page 6

The structure and migration of twin boundaries in tetragonal β -Sn: An application of machine learning based interatomic potentials

Although atomistic simulations have contributed significantly to our understanding of twin boundary structure and migration in metals and alloys with hexagonal close packed (HCP) crystal structures, few direct atomistic studies of twinning have been conducted for other types of low symmetry materials, in large part due to a lack of reliable interatomic potentials. In this work, we examine twin boundary structure and migration in a tetragonal material, β-Sn, comparing high resolution Transmission Electron Microscopy (TEM) images of deformation twins in β-Sn to the results of direct atomistic simulations using multiple interatomic potentials. ML-based potentials developed in this work are found to give results consistent with our experimental data, revealing faceted twin boundary structures formed by the nucleation and motion of twinning disconnections. We use bicrystallographic methods in combination with atomistic simulations to analyze the structure, energy and shear coupled migration of observed twin facets in β-Sn. In analogy to Prismatic-Basal (PB/BP) interfaces in HCP metals, we discover low energy asymmetric Prismatic-A-plane (PA/AP) interfaces important to twin growth in β-Sn. Finally, a Moment Tensor Potential (MTP) and Rapid Artificial Neural Network (RANN) interatomic potential suitable for studying twinning and phase transformations in Sn are made publicly available as part of this work.

36 MATERIALS SCIENCE↗

PowderJet: Spherical metal powder production via multi-orifice droplet-on-demand metal jetting

Leading metal additive manufacturing techniques, such as laser powder bed fusion and directed energy deposition, rely on high-quality spherical metal powders. However, traditional powder production methods like gas atomization face limitations, including low in-spec yield, asphericity, and internal porosity. We introduce PowderJet, a powder production platform that uses electromagnetic pulses to eject liquid metal droplets from a multi-orifice nozzle. Unlike stochastic methods, PowderJet tightly controls powder size, distribution, and purity through a droplet-on-demand approach. We detail the system’s design, operation, and performance using a combined experimental and computational fluid dynamics (CFD) framework. Initial results with Al4008 and Cu110 alloys demonstrate successful production, yielding unsieved aluminum powder batches with a mean diameter of 200 µm and a narrow size distribution (15 µm standard deviation). The produced powders are highly spherical, achieving a roundness > 0.95. PowderJet operates with a small melt volume (3 mL) and supports continuous refilling, enabling production rates between 30 and 140 cm³/hr depending on jetting frequency, number of orifices and particle size. CFD simulations show that future systems could achieve rates exceeding 1000 cm³/hr for particle sizes as small as 40 µm. PowderJet’s high yield of in-spec powder makes it ideal for producing precious or hazardous materials that are inefficient to manufacture using conventional methods. This platform offers a scalable, precise, and efficient solution for producing high-quality powders tailored for advanced manufacturing applications.

Atomization↗

Description of a novel extremophile green algae, Chlamydomonas pacifica , and its potential as a biotechnology host

We present the comprehensive characterization of a newly identified microalga, Chlamydomonas pacifica , originally isolated from a soil sample in San Diego, CA, USA. This species showcases remarkable biological versatility, including a broad pH range tolerance (6–11.5), high thermal tolerance (up to 42 °C), and salinity resilience (up to 2 % NaCl). Its amenability to genetic manipulation and sexual reproduction via mating, particularly between the two opposing strains CC-5697 & CC-5699, now publicly available through the Chlamydomonas Resource Center, underscores its potential as a biotechnological chassis. The biological assessment of C. pacifica revealed versatile metabolic capabilities, including diverse nitrogen assimilation capability, motility and phototaxis. Genomic and transcriptomic analyses identified 17,829 genes within a 121 Mb genome, featuring a GC content of 61 %. The codon usage of C. pacifica closely mirrors that of C. reinhardtii , indicating a conserved genetic architecture that supports a trend in codon preference with minor variations. Phylogenetic analyses position C. pacifica within the core-Reinhardtinia clade yet distinct from known Volvocales species. The lipidomic data revealed an abundance of triacylglycerols (TAGs), promising for biofuel applications and lipids for health-related benefits. Our investigation lays the groundwork for exploiting C. pacifica in biotechnological applications, from biofuel generation to synthesizing biodegradable plastics, positioning it as a versatile host for future bioengineering endeavors.

Alkali tolerant↗

Autonomous anomaly detection of proliferation in the AGN-201 nuclear reactor digital twin

The expansion of global nuclear power necessitates advanced methods for analyzing proliferation indicators. This study introduces a novel application of the Isolation Forest Machine Learning (IFML) algorithm within a digital twin (DT) of the AGN-201 nuclear reactor to autonomously detect anomalies. Leveraging real-time operational data from the AGN-201 DT, the IFML algorithm identifies outliers without prior data labeling and operates as a lightweight, complementary approach to traditional physics-based anomaly detection methods for nuclear safeguards. In a simulated Red vs. Blue team exercise, the IFML algorithm successfully detected six significant unseen anomalies related to reactivity changes, achieving an accuracy of 99% for identifying operational deviationxs. These anomalies, caused by deliberate perturbations, were detected alongside known physics-based models, underscoring the potential of IFML to enhance real-time monitoring without displacing traditional methods. Further, this study highlights the applicability of IFML in nuclear environments by providing an additional, redundant layer of anomaly detection to improve safeguards and operational safety in complex systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The AGN-201 Digital Twin: A test bed for remotely monitoring nuclear reactors

Research reactors have historically provided researchers and scientists with a means for testing and understanding the workings of nuclear phenomena. With the lack of new research reactors built in the past decades, it is important now more than ever to utilize and provide evidence for the usefulness of research reactors. Here, this work explores the use of the AGN-201 research reactor at Idaho State University as a test bed for developing a digital twin (named the AGN-201 DT) to realize remote monitoring for nuclear reactors. The goal of the AGN-201 DT is to monitor the AGN-201 reactor and detect when undeclared events take place to provide information for a monitoring agency. The AGN-201 DT was able to detect (without a priori knowledge) when multiple undeclared experiments were placed in the core using on-the-fly machine learning and reactor physics analysis. The AGN-201 reactor provided a test bed for developing, deploying, and testing a digital twin for monitoring nuclear reactors.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Parameter Study of the Running-In Process for the Generic Pebble Bed Reactor (GPBR200)

The run-in period of a pebble bed reactor is complex and difficult to model given significant heterogeneity in core composition, power, and temperature. While it is understood that the initial composition of the core should eventually result in the same equilibrium core composition, the approach to equilibrium can vary significantly depending on factors such as start-up fuel enrichment and power ramp rate. To explore this, a high-fidelity model of the General Pebble Bed Reactor was used to vary power ramp schemes and start-up core compositions. It was found that both the initial core composition and power ramp rate had a significant impact on the flow rate of pebbles during early time steps, with higher ramp rates and low enrichment resulting in non-physical flow rates. Power ramp rate alone was found to dictated maximum pebble power peaking observed during the run-in process, with higher ramp rates resulting in greater peak pebble powers. Start-up fuel enrichment and power ramp were found to both impact total fuel consumption, although the impact of start-up fuel enrichment was generally secondary to ramp rate.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Migration of Al within dealuminated beta extruded catalysts influences olefin distribution during ethanol upgrading

Zeolites serve as essential catalytic platforms for many industrial processes, including emerging ethanol-to-olefins (ETO) upgrading technologies. Although metal-loaded (Cu, Zn, Y) dealuminated beta (deAlBeta) zeolite powders are promising catalysts for direct ETO conversion with high selectivity to butene-rich C3+ olefins necessary for production of sustainable aviation fuels (SAF), development of these materials as shaped technical bodies through the incorporation of binders is required for scale-up and commercial viability. Here, we report the ethanol upgrading performance of Cu-Zn-Y/deAlBeta extruded catalysts formulated with either alumina or kaolin clay binders. Both extrudates exhibit high ethanol dehydration reactivity which competes with the initial ethanol dehydrogenation step in the direct ETO reaction network. Consequently, elevated selectivity to dehydration side products (ethylene, diethyl ether) at ∼100% ethanol conversion is observed on Cu-Zn-Y/deAlBeta extrudates compared to the powder catalyst, which inhibits production of desired C3+ olefins. Utilizing microscopy and spectroscopic characterizations, we attribute this to Al migration from binder to zeolite particles within the extrudates, thus re-aluminating the zeolite and generating Brønsted acid sites active for dehydration reactions. This work elucidates the effects of binder incorporation on ETO product distributions and emphasizes that binder selection must be carefully considered during design of extruded zeolite catalysts.

Jacobs, Hunter [ORNL] (ORCID:000000016190874X)↗

Understanding and mitigating degradation in amine-based sorbents for CO 2 direct air capture

The success of direct air capture (DAC) of CO 2 depends on sorbents that combine high capacity, low energy requirements, and long-term durability. Amine-based sorbents-including solid-supported aminopolymers, grafted amines, and amine-functionalized resins-remain the leading candidates, but their limited lifetimes drive up costs and constrain deployment. In this review, we outline the current understanding of amine-based sorbent degradation with an emphasis on clearly identifying what is known about structure-property-performance relationships, as well as important knowledge gaps. More specifically, we discuss how polymer chemistry, sorbent design variables, and environmental and process conditions contribute to performance loss. In parallel, we outline how advances in spectroscopy, modeling, and accelerated testing are beginning to illuminate chemical and physical degradation mechanisms. Looking forward, we identify future research directions that will be critical for gaining a deeper understanding of degradation, as well as opportunities for developing innovative mitigation strategies for improving the lifetime of amine-based sorbents.

organic↗

Numerical simulation for the design of induction heating based radio frequency reactor for ethylene production

Ethylene is a vital petrochemical compound produced in vast amounts yearly by manufacturers that have enough scale to overcome the inherent thermodynamic inefficiencies of the process. In order to address the inefficiencies that prevent smaller scale or intermittent production ethylene, investigation of new production methods are required. In this work, we investigate the use of a radio frequency (RF) based reactor system that generates heat internally as opposed to applying heat externally via steam or direct combustion of fossil fuels. In order to guide the design of an electromagnetic based reactor system, we have created a macroscale model capable of capturing heat generation at the susceptors from a produced electromagnetic field and subsequent chemical reactions. Several susceptor and induction coil designs were investigated to better understand the performance of the system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Insights into the soft brittle-to-ductile transition from discrete dislocation dynamics

The Brittle-to-ductile transition (BDT) in body centered cubic metals exhibits a soft transition wherein the fracture toughness gradually rises to before the onset of ductility. The resultant brittle-to-ductile transition temperature can be described with an Arrhenius relationship whose activation energy is related to plasticity in the material. To provide further insight into the nature of the BDTT, in this work we utilized a discrete dislo- cation dynamics model with a crack to simulate the BDT and how it depends on the thermally activated nature of plasticity. The interrelationship between the BDT activation energy and the dislocation mobility parameters were determined via the calculation of first order sensitivity coefficients. This analysis allows us to demonstrate that the activation energy for the BDT is directly related to the activation energy for plasticity through an effective stress that defines this relationship. This effective stress physically is the average stress on the dislocations that move out of the crack. Lastly, we are able to show that this effective stress is dictated by the low temperature fracture toughness or cleave energy of the material and the source position, the latter of which can be affected by processing. Collectively, these results provide new insight into what controls the thermal activation of the BDT and what are the important parameters to control it.

36 MATERIALS SCIENCE↗

The EGS Collab project: Outcomes and lessons learned from hydraulic fracture stimulations in crystalline rock at 1.25 and 1.5 km depth

With the goal of better understanding stimulation in crystalline rock for improving enhanced geothermal systems (EGS), the EGS Collab Project performed a series of stimulations and flow tests at 1.25 and 1.5 km depths. The tests were performed in two well-instrumented testbeds in the Sanford Underground Research Facility in Lead, South Dakota, United States. The testbed for Experiment 1 at 1.5 km depth contained two open wells for injection and production and six instrumented monitoring wells surrounding the targeted stimulation zone. Four multi-step stimulation tests targeting hydraulic fracturing and nearly year-long ambient temperature and chilled water flow tests were performed in Experiment 1. The testbed for Experiments 2 and 3 was at 1.25 km depth and contained five open wells in an outwardly fanning five-spot pattern and two fans of well-instrumented monitoring wells surrounding the targeted stimulation zone. Experiment 2 targeted shear stimulation, and Experiment 3 targeted low-flow, high-flow, and oscillating pressure stimulation strategies. Hydraulic fracturing was successful in Experiments 1 and 3 in generating a connected system wherein injected water could be collected. However, the resulting flow was distributed dynamically, and not entirely collected at the anticipated production well. Thermal breakthrough was not observed in the production well, but that could have been masked by the Joule-Thomson effect. Shear stimulation in Experiment 2 did not occur - despite attempting to pressurize the fractures most likely to shear - because of the inability to inject water into a mostly-healed fracture, and the low shear-to-normal stress ratio. The EGS Collab experiments are described to provide a background for lessons learned on topics including induced seismicity, the correlation between seismicity and permeability, distributed and dynamic flow systems, thermoelastic and pressure effects, shear stimulation, local geology, thermal breakthrough, monitoring stimulation, grouting boreholes, modeling, and system management.

15 - GEOTHERMAL ENERGY↗

Hydrogen from low-density polyethylene via nonthermal plasma: Effects of energy density and process parameters

Nonthermal plasma processes are promising for the modular valorization of plastic waste, especially into hydrogen and carbon materials, due to their high intensity, lack of reliance on catalysts or consumables, and suitability to be directly powered by electricity. We investigate the production of hydrogen from low-density polyethylene (LDPE) as a plastic waste model using streamer Dielectric Barrier Discharge (sDBD) plasma in nitrogen at atmospheric pressure. Here, we examine the effects of process energy density (energy input per unit of feedstock mass), feedstock mass, and plasma intensity (electric voltage) on plasma properties, hydrogen yield and energy efficiency via gas chromatography, optical emission spectroscopy, and electrical diagnostics, together with reactor-scale and nonlinear electric circuit modeling. The characteristic temperature of free electrons in the sDBD plasma is approximately 15000 K (1.3 eV), and that of gas species 10 times lower, demonstrating strong thermal non-equilibrium that can lead to molecular bond scission via charged species impact rather than direct heating. Experimental results show that higher energy density leads to greater hydrogen production and diminishing energy efficiency, and that higher plasma intensity and larger feedstock mass lead to greater hydrogen yield due to higher plasma temperatures and enhanced energy fluxes to the feedstock.

08 HYDROGEN↗

Modeling inter- and intra-granular dislocation transport using crystal plasticity

Here, this work presents the development of a crystal plasticity material model that incorporates both dislocation transport within grains and dislocation transfer across grain boundaries. This model has been implemented in the open-source finite element code MOOSE. In addition, a novel geometry-based criterion is developed to determine the direction of dislocation transfer across grain boundaries. The transfer criterion incorporates the geometric features of the grain boundary, such as the grain boundary plane normal, and its misorientation, which is accounted for through the orientation of the incoming and outgoing slip systems. The model is tested with several cases, including a copper single crystal, bi-crystal, and polycrystal. The development of the transfer criterion, implementation of the model, and its application to these test cases are discussed in detail.

36 MATERIALS SCIENCE↗