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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 757 records · Page 42

Tuning transition metal nanoparticles on a non-traditional support via experimental design

The ability to control metal nanoparticle size and morphology on supported catalysts is crucial for optimizing catalytic performance in targeted applications. Here, this work presents a systematic approach for tuning Ni particle and crystallite size on an unconventional, low-porosity silica fume support through select thermal treatments. The catalyst was synthesized via the deposition of nickelocene onto silica fume, resulting in well-dispersed Ni nanoparticles. A face-centered central composite design was employed to systematically assess the effects of time, temperature, and sintering gas environment on metal particle growth. The results demonstrate that the sintering gas environment is the primary factor governing particle and crystallite evolution, with temperature as the next most significant influence. Nickel nanoparticles sintered at temperatures of 650 °C and above under inert conditions exhibited substantial growth and polycrystalline structures, whereas samples treated in oxidative environments formed NiO, restricting particle mobility. Minimally oxidative (500 ppm O₂) environments facilitated rapid sintering while effectively removing residual ligands from the one-step nickelocene deposition process. Extensive structural characterization via a combination of scanning transmission electron microscopy, X-ray diffraction, hydrogen temperature programmed reduction, and small-angle X-ray scattering revealed that oxidative treatments enhanced metal-support interactions, as evidenced by increased reduction temperatures and narrower particle size distributions. These findings establish quantitative relationships between sintering parameters and Ni nanoparticle characteristics, providing a framework for rational catalyst design through controlled thermal treatments. This methodology is broadly applicable to other catalytic systems and provides a quantitative foundation for catalyst design.

CVD↗

Crack nucleation from non-metallic inclusions in aluminum alloys described by peridynamics simulations

Conventional engineering methods oftentimes have challenges in the quantification of crack nucleation processes from manufacturing defects that are relevant for engineering component lifing. In this work, we present peridynamic simulation framework for the description of the crack nucleation process from cluster of non-metallic inclusions in aluminum alloys. Our non-local simulation framework characterizes crack nucleation process as multiple micro-crack nucleation events from individual inclusions, and eventually one micro-crack dominates. We define individual stages of the crack nucleation process, i.e., nucleation, micro-crack, technical, and crack initiation, that allow a quantification and meta model development of both the individual stages and the entire crack nucleation process.

36 MATERIALS SCIENCE↗

Multi-phase characterization of pitch-carbon coated nano-silicon anodes for lithium-ion batteries

Silicon (Si) is a leading next-generation Li-ion battery anode candidate that meets rigorous performance demands for portable power including enhanced power and energy density with robust cycling performance. However, a series of complex and interrelated reactions lead to reduced calendar life in Si-containing systems and therefore challenge practical adoption. In the present work, we probe the mechanisms underlying observed performance improvements by adding a pitch-carbon coating onto nano-Si material. We pair solid-phase (X-ray photoemission spectroscopy, Fourier-transform infrared), semi-volatile phase (solid-phase microextraction-gas chromatography-mass spectrometry), and gas-phase (gas chromatography-flame-ionization detector) characterization signals to comprehensively evaluate the impact of pitch-carbon coating on the evolution of the Si solid-electrolyte interphase (SEI) and the associated impacts on electrode/electrolyte reactivity. The pitch-carbon is found to serve as a physicochemical barrier, reducing the electro-active surface area for Si/electrolyte reactivity and preventing Si oxidation. Further, the pitch-carbon coating promotes the evolution of a more-favorable SEI by subsuming substantial functionality typically associated with the fluoroethylene carbonate (FEC) electrolyte additive - such as alkoxide scavenging and suppression of transesterification pathways - and by shifting the competitive electrolyte degradation pathways' favorability. The multi-phase characterization approach enables holistic end-products evaluation from complex (electro)chemical interfacial reactions, which informs a robust interpretation of the carbon coating's role in electrochemical performance improvements. The present mechanistic evaluation aids the rational design for improved nano-Si materials.

25 ENERGY STORAGE↗

On the Cutting of Metals: A Mechanics Viewpoint

The mechanics of large-strain deformation in cutting of metals is discussed, primarily from viewpoint of recent developments in in situ analysis of plastic flow and microstructure characterization. It is shown that a broad range of deformation parameters can be accessed in chip formation—strains of 1–10, strain rates of 10–10 5 /s, and temperatures up to 0.7T m —and controlled. This range is far wider than achievable by any other single-stage, severe plastic deformation (SPD) process. The resulting extreme deformation conditions produce a rich variety of microstructures in the chip. Four principal types of chip formation—continuous, shear-localized, segmented, and mushroom-type—as elucidated first by Nakayama (1974, “The Formation of ‘Saw-Toothed Chip’ in Metal Cutting,” Proceedings of International Conference on Production Engineering, Tokyo, pp. 572–577) are utilized to emphasize the diverse plastic flow phenomena, especially unsteady deformation modes that prevail in cutting. These chip types are intimately connected with the underlying flow, each arising from a distinct mode and triggered by an instability phenomenon. The role of plastic flow instabilities such as shear banding, buckling, and fracture in mediating unsteady flow modes is expounded, along with consequences of the flow modes and chip types for the cutting. Sinuous flow is shown to be the reason why gummy (highly strain-hardening) metals, although relatively soft, are so difficult to cut. Synthesizing the various observations, a hypothesis is put forth that it is the stability of flow modes that determines the mechanics of cutting. Furthermore, this leads to a flow-stability phase diagram that could provide a framework for predicting chip types and process attributes.

42 ENGINEERING↗

Single-Step Shear-Based Deformation Processing of Electrical Conductor Wires

Commercial electrical conductor wires are currently produced from aluminum alloys by multi-step deformation processing involving rolling and drawing. These processes typically require 10 to 20 steps of deformation, since the plastic strain or reduction that can be imposed in a single step is limited by material workability and process mechanics. Here, we demonstrate a fundamentally different, single-step approach to produce flat wire aluminum products using machining-based deformation that also ensures adequate material workability in the formed product. Two process routes are proposed: (1) chip formation by free-machining (FM), with a post-machining, light drawing reduction (<20%) to achieve desired finish and (2) constrained chip formation by large strain extrusion machining (LSEM). Using commercially pure aluminum conductor alloys (Al 1100 and EC1350) as representative material systems, we demonstrate key features of the machining-based processing, including (a) single-step processing to achieve flat wire geometries, (b) surface finish (Ra = 0.2 to 1.0 μm) comparable to that of commercial wire products made by drawing/rolling, (c) deformation control independent of wire size, and (d) hardness increases of 50–150% over that of annealed wires, while retaining high electrical conductivity (>56% IACS). Here, the wire microstructure, which can also be varied via the large-strain deformation parameters, is correlated with mechanical and electrical properties. Implications for commercial manufacture of flat wire products are discussed.

36 MATERIALS SCIENCE↗

Shallow EGS Regional Resource Potential and Map - Snake River Plain

SMU Geothermal Lab developed a methodology to estimate shallow (1 km to 4 km) Enhanced Geothermal Systems (EGS) resource potential using an approach that utilizes recent geology and geophysical research along with new well data to improve the thermal conductivity model, mitigate impacts from groundwater flow in the thermal model, and examine radioactivity data variations. By incorporating the results of the most recent projects with the SMU shallow methodology, we developed a more accurate, updated resource estimate for the Snake River Plain (SRP). The resulting maps and resource estimates can be used by the National Renewable Energy Lab (NREL), Bureau of Land Management (BLM), and the public to determine how best to move forward with future project development.

15 GEOTHERMAL ENERGY↗

Purdue University: Results of B-Value Tests for Rock Saturation

This dataset includes an Excel file with the results of B-value tests to determine the magnitude of the back pressure required for full saturation of Sierra White granite samples. Test were conducted on cylindrical rock specimens of Sierra White granite in a custom water pressurized chamber. Dimensions and properties of Sierra White granite specimens are summarized in the PDF file. The PDF file also includes a description of the B-value tests, experimental procedure, and results.

15 GEOTHERMAL ENERGY↗

Laboratory Experiments Examining the Effect of Thermal and Mechanical Processes on Hydraulic Transmissivity Evolution

Using laboratory slide-hold-slide experiments, at temperatures from 22 to 200 degrees C, to examine effects of fracture reactivation and quasi-static loading on the evolution of fluid transport properties of simulated fractures in Westerly granite. At all temperatures, the in-plane hydraulic transmissivity consistently decays during hold periods resulting in an overall reduction in transmissivity. During the first three to fifteen hours of an experiment, transmissivity decreases rapidly due to the generation of wear products, development of a sliding surface, and compaction of the resulting gouge. Once the sliding surface has developed, the long-term transmissivity decay rate at 22 and 100 degrees C is significantly lower than the transmissivity decay rate during the initial 3-15 hours of the experiment. However, at 200 degrees C, the decay of hydraulic transmissivity remains high throughout the experiment. The long-term decay of hydraulic transmissivity can be fitted with a power law model with more rapid reduction of hydraulic transmissivity at higher temperature. Periods of sliding on the fracture surface result in transient increases in the transmissivity, due to shear dilation, as is expected for Coulomb materials. These transients are superimposed on the long-term decay. When sliding ceases and a new hold period commences, there is a rapid reduction in transmissivity and return to the long-term rate of transmissivity decay. The rate of decay of the transmissivity transients is inversely correlated with temperature, in contrast to the long-term decay and the expected behavior for processes like subcritical crack growth and indentation creep. The higher decay rates that are observed during the initial 3-15 hours of the tests and following sliding, are associated with times that the porosity of the gouge is expected to be high. The difference in decay rates suggests that when the gouge is driven far from equilibrium by active shearing, densification may be dominated by a different mechanism from long-term compaction.

15 GEOTHERMAL ENERGY↗

EGS Collab: Modeling and Simulation Working Group Teleconference Series (129-130)

This submission contains the presentation slides and recordings from EGS Collab Modeling and Simulation Working Group (MSWG) teleconferences number 129 through 130. These teleconferences served three objectives for the project: 1) share simulation results, 2) communicate field activities and results to the simulation teams, and 3) hold open scientific discussions on EGS topics.

15 GEOTHERMAL ENERGY↗

Digital system provides superregulation of nanosecond amplifier-discriminator circuit

Feedback system employing a digital logic comparator to detect and correct amplifier drift provides stable gain characteristics for nanosecond amplifiers used in counting applications. Additional anticoincidence logic enables application of the regulation circuit to the amplifier and discriminator while they are mounted in an operable circuit.

Forges, K. G.↗

Improving the Accessibility and Usability of Geothermal Information with Data Lakes and Data Pipelines on the Geothermal Data Repository: Preprint

The Geothermal Data Repository (GDR) provides universal access to data and information resulting from research and development activities funded by the Department of Energy (DOE). The GDR has extended this universal access to big data through integration with data lakes developed by the Open Energy Data Initiative (OEDI). Previously, large datasets such as seismic waveform or distributed acoustic sensing (DAS) data could only be accessed by institutions with high performance data storage and compute capabilities, effectively limiting the accessibility of big data to national labs, larger universities, and major corporations. Moreover, the time and resources needed to transport big data and configure them can produce additional barriers to use. Many of the standard formats used for structured data models (also known as content models) are incapable of handling big data and can introduce additional usability problems, often requiring data to be reformatted prior to use. This paper will explore how recent integrations between the GDR and the OEDI data lake have improved the accessibility and usability of geothermal data in a big way, making the data available to a broader audience, and enabling collaborative analysis and innovation across the greater geothermal industry.

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Improving the Accessibility and Usability of Geothermal Information with Data Lakes and Data Pipelines on the Geothermal Data Repository

The Geothermal Data Repository (GDR) provides universal access to data and information resulting from research and development activities funded by the Department of Energy (DOE). The GDR has extended this universal access to big data through integration with data lakes developed by the Open Energy Data Initiative (OEDI). Previously, large datasets such as seismic waveform or distributed acoustic sensing (DAS) data could only be accessed by institutions with high performance data storage and compute capabilities, effectively limiting the accessibility of big data to national labs, larger universities, and major corporations. Moreover, the time and resources needed to transport big data and configure them can produce additional barriers to use. Many of the standard formats used for structured data models (also known as content models) are incapable of handling big data and can introduce additional usability problems, often requiring data to be reformatted prior to use. This paper will explore how recent integrations between the GDR and the OEDI data lake have improved the accessibility and usability of geothermal data in a big way, making the data available to a broader audience, and enabling collaborative analysis and innovation across the greater geothermal industry.

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GOOML - Finding Optimization Opportunities for Geothermal Operations: Preprint

Geothermal Operational Optimization with Machine Learning (GOOML) is a transferable and extensible component-based geothermal asset modeling framework that considers complex steamfield relationships and identifies optimization prospects using a data-driven approach. We have used this framework to develop digital twins that provide steamfield operators with an operational environment to analyze and understand historical and forecasted power production, explore new steamfield configuration possibilities, and seek optimal asset management for real world applications. The GOOML modeling software is built on a generic component-based systems framework that allows for both historical and forecast analysis. A GOOML model can perform historical data-assimilation using first-principal thermodynamics to create a meaningful data model. Historical production data can then be coupled with a forecast framework to train machine-learning models of steamfield components to predict future outputs. This modeling environment enables digital exploration of steamfield design configurations and operational scenarios. GOOML digital twins have been developed for steamfields in New Zealand and the United States representing differing power generation and field conditions. These digital twins have been validated by comparing hindcast predictions against historical production data. Reinforcement learning experiments were conducted to demonstrate the ability to programmatically explore the operations space using machine learning agents. Our initial results are compelling; two to five percent increases in annual energy production were demonstrated by the GOOML models with no additional infrastructure build required. GOOML offers a new approach to geothermal operations by applying state-of-the-art machine learning algorithms, comprehensive data analytics, and interaction with digital twins. Through application of these tools, operators will realize greater availability and higher net generation which will increase the cost effectiveness of geothermal energy projects.

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