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At least 451 records · Page 25

Building Interfaces with Echo Using R

The following report details the functionality that was developed to directly query the MongoDB and read in echo records from within R, and the ability to create a cinema database directly from echo records. Both of these efforts used the data collected under the MINOS project for development. The nuclear facility under consideration is the High-Flux Isotope Reactor (HFIR) and co-located Radiochemical Engineering Development Center (REDC) at Oak Ridge National Laboratory in Oak Ridge, TN. HFIR is an 85 MW research reactor and is used primarily for production of a medical radioisotopes, material irradiation experiments, neutron activation, and neutron scattering. Targets for the reactor are fabricated and processed and dissolved at REDC, in addition to other glove-box and hot-cell type activities. An overhead view of the facility is provided. The rest of the report is organized as follows: Section 2 describes how to query the MongoDB and load in echo records from within R, with background information on the database type, MongoDB, and the file format of echo records, hdf5, as well as lessons learned during the development phase. Section 3 details the functionality and usage of creating a cinema database directly from echo records within R. A series of appendixes display all the R code (Section 5), some example scripts where the code is used (Section 6), and useful links for further exploration (Section 7).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Cooperative Research and Development Agreement between National Energy Technology Laboratory and Princeton University (Abstract)

The National Energy Technology Laboratory (NETL) and Princeton University will collaborate in the development of microwave-plasma technology to convert methane into hydrogen and valuable solid carbon materials. The effort will combine NETL’s vast resources for microwave-enhanced process development, characterization, and design with Princeton University’s extensive expertise in the study of non-equilibrium plasmas employing supersonic nozzles. Lab-scale experiments will be conducted for different conditions to convert and compare their respective performance in hydrogen production. Computational modeling will be performed to verify results from experimental studies conducted in both labs.

08 HYDROGEN↗

Development of a Novel Magnesium Alloy for Thixomolding® of Automotive Components (Final Report)

Magnesium (Mg) alloy die-castings are increasingly used in the automobile industry to achieve cost effective mass reduction, especially in systems where multiple components can be integrated into a single thin wall die-casting. However, there are several component quality restrictions in thin-walled Mg die castings, including variability in dimensional accuracy, part-to-part variation in mechanical properties, and porosity in the final part, which has limited the continued growth of die-cast components in the automobile industry. An alternative to die-casting is the process of thixomolding®. While the die-casting process relies on filling a mold at high speeds with the alloy in the completely molten state, the thixomolding® process fills a mold with a thixotropic alloy in a semi-solid slurry state at a temperature between the liquidus and solidus temperatures. Ideally, the material should be ~30–65% solid rather than being completely liquid at the beginning of the injection process. Advantages of the thixomolding® process include a finer grain structure, lower porosity, improved dimensional accuracy, improved part-to part consistency, improved mechanical properties, particularly ductility in the component, the ability to reduce wall thickness for mass savings, and longer tool life due to lower process temperatures. The objective of this collaborative project between Oak Ridge National Laboratory, FCA US LLC, and Leggera Technologies was to develop one or more novel Mg alloys more suitable for thixomolding® automotive structural components than the current die-casting alloys used for this process. The primary interest was to improve ductility while maintaining tensile and fatigue strengths, as these are properties that are critical for use in body and chassis structural applications. Since good corrosion resistance is also desirable for this application, this property was also considered when evaluating promising alloy compositions. An initial evaluation of existing components thixomolded® using AM60 was performed and microstructure, and tensile properties were evaluated for the baseline alloy. Targets were established for ease of processing (characterized by the melting range defined as the difference between the liquidus and the solidus), strength, and ductility. Computational modeling was used to identify promising alloys and selected alloys were cast in laboratory scale heats. Properties measured from laboratory scale heats were used to down-select two alloys for further evaluation and component fabrication. Two alloys were prepared in industrial scale heats, cut into small pieces (chips), and thixomolding® trials were initiated. Trial components were successfully fabricated using one alloy composition, but it was concluded that further refinement of the thixomolding® process parameters are required to successfully fabricate component using second alloy. Microstructure and mechanical properties were evaluated on the material removed from the fabricated component and properties were compared to the baseline alloy. Although mechanical properties of the alloys showed improvement over the baseline alloy, it was determined that modifications to the thixomolding® process would result in better microstructure control with further improvement in properties leading to successful commercialization. A provisional patent application has already been filed on the new alloys developed as part of the project.

36 MATERIALS SCIENCE↗

Process Intensification for Nanostructure Aluminum Extrusions

A new technology called Shear Assisted Processing and Extrusion (ShAPE™), pioneered at the Pacific Northwest National Laboratory (PNNL), has the potential to revolutionize the US extrusion industry. Maturation of the ShAPE™ process would create a new cross cutting US manufacturing technology that advances three key the objectives within AMO; namely, nanomaterials processing, process intensification, and materials for extreme and harsh environments. PNNL and SCM Metals Products, Inc. (SCM), a division of Kymera International, will collaborate to mature the ShAPE™ extrusion process beyond TRL 3 to increase the likelihood of its adoption by industry. PNNL’s custom (one-of-a-kind in the world) ShAPE™ machine will be used to extrude round rods of high strength aluminum alloy feedstock powder provided by SCM. As proof-of-concept, PNNL has previously extruded 5 mm diameter rods with SCM aluminum alloy powder AL-12.4TM. This project aims to scale up the process to a diameter of 25 mm while retaining the excellent mechanical properties achieved for the 5 mm diameter rods. The degree of process intensification with ShAPE™ will also be estimated. The primary objectives of this project are as follows. 1) Fabricate 25 mm diameter nanostructured extrusions in bulk, directly from AL-12.4TM aluminum alloy powder without the need for canning, degassing, compaction, and other intermediate steps typical of powder metallurgy extrusion. 2) Achieve a microstructure with an ultrafine grained (UFG <1 µm) aluminum matrix having refined and homogenously distributed nanoscale second phases. 3) Show that the ram force can be significantly reduced compared to conventional powder metallurgy extrusion of the same material and estimate the extent of process intensification that may be possible with ShAPE™. 4) Demonstrate improved high-temperature mechanical properties compared to conventional extrusion of the same material. The following tasks will be undertaken to achieve these objectives. PNNL will develop the die set and process parameters necessary to fabricate Al-12.4TM extrusions with a 25 mm diameter. Microstructural analysis will be performed by PNNL while mechanical testing will be conducted by SCM. With information learned from the process development and characterization, PNNL will perform an estimate of the degree of process intensification that may be possible with ShAPE™.

42 ENGINEERING↗

"Soft" Catching high velocity projectiles and targets

In order to perform post mortem analysis on materials launched in gas guns and powder guns, various methods have been explored to soft catch these materials. The majority of the deformation profile must be from the initial impact during the experiment, not from the subsequent impact with the energy absorption material in the catch tank. This process becomes increasingly more difficult with increased velocities. This report explores a method to soft catch materials launched at velocities 3000 $\frac{m}{s}$.

42 ENGINEERING↗

Interconnect: Cooperative Research and Development Final Report, CRADA Number CRD-13-00507 (Project 4)

This CRADA modification involves analyses on a variety of CdTe-PV related materials, test structures, solar cells, and modules produced at FSLR and/or NLR and adds analysis related to module degradation and reliability. Materials will be provided by FSLR, NLR, and/or by interleaving FSLR and NLR layers and processes. Module reliability activities will include technical risk assessment, materials characterization, module and test structure characterization, modeling, accelerated test development, and outdoor testing.

14 SOLAR ENERGY↗

Microwave Plasma Flash Pyrolysis for Coal-to-Product Applications

Since 2010, the US coal industry has experienced a precipitous decline, with coal production volumes dropping by as much as 35% according to EIA. This decline is hardly surprising given that 90% of domestic coal use is allocated to electricity production: While coal generation supplied about 45% of the nation's power in 2010, its share is projected to fall to only 22% in 2020. Fortunately, alternative uses for coal as a feedstock rather than as energy source are available. Coal tar is an established feedstock for chemicals and high-value carbon products including carbon fiber and battery-grade graphites. At present, growth of these uses is constrained by the low availability, purity, and yields of currently available coal liquids, and high energy- and CO2-intensity of current methods of production (i.e. coking). Previously reported work conducted in a partnership with Pacific Northwest National Laboratory demonstrated technical and economic viability of flash pyrolysis of coal in a microwave plasma environment at bench scales targeting production of fuel feedstocks (synthetic oil). H Quest’s work since then indicated promise of microwave-derived coal liquids to be uniquely suited for the lower-cost production of carbon materials, including synthetic graphite, carbon fiber, and composites. Low bulk process temperatures, subsecond residence times, and ambient pressure operation enable small-scale deployment, reduce capital and operating costs, and suppress formation of impurities, including QI material, typical in conventional coal tars. With no inherent production of CO2 or water consumption, microwave plasma flash pyrolysis presents a viable route to the sustainable production of both platform chemicals and carbon-based materials. Most recently, H Quest developed a novel, ruggedized microwave plasma reactor, which departs from the proof-of-concept approach and addresses the problems typically encountered in scaling laboratory microwave plasma apparata (e.g. eliminating fragile quartz enclosures prone to coking and fouling). This reactor has been integrated with a 15kW microwave power supply, a pulverized coal injection system, and a product recovery system. A series of screening tests across a range of coals (including hv-, lv-bituminous and subbituminous PRB), entrainment gas flows and compositions and microwave energy inputs are performed to evaluate conversion rates within the novel, scaled-up system, confirm yields of liquid products, and to perform compositional (GC/MS and elemental) analyses of the products. Results of these tests will be presented and discussed.

Skoptsov, George↗

Creep Behavior of Friction Stir Processed Haynes 282

Haynes 282 is a nickel-based superalloy designed for use in hot sections of turbines for aircraft and power generation. In these applications, elevated temperature creep performance is critical. To that end, creep behavior of friction stir processed material was carried out to investigate the high-temperature performance of this alloy. Friction stir processing of Haynes 282 was successfully completed, and the processed region was found to be defect-free. Various mechanical property characterization approaches were carried out in post-heat treated condition. Transverse tensile samples repeatedly failed in the base metal indicating 100% joint efficiency. Creep property evaluation was completed at 760 °C and at various stress levels. The creep-rupture lifetime of the processed material was similar to the base metal. Detailed electron microscopy analysis of the failed sample was carried out to understand the microstructural evolution in various locations of the sample during creep.

creep↗

Additive manufacturing of high‐density silicon carbide ceramics through post‐processing spark plasma sintering

This research advances the field of additive manufacturing (AM) of silicon carbide (SiC) ceramics by integrating spark plasma sintering (SPS) to enhance material density, mechanical strength, and thermal properties. Traditional AM techniques struggle to achieve the high‐density SiC required for demanding applications, such as aerospace engineering, where high thermal conductivity and mechanical strength are paramount. Here, our study addresses these challenges by incorporating SPS as a post‐processing step, achieving near‐theoretical maximum densities and significantly reducing porosity, thereby resulting in outstanding thermal conductivity in SiC ceramics. We developed a specialized SiC ink optimized for 3D printing, ensuring structural integrity after deposition through tailored rheological properties. The application of SPS facilitates rapid, uniform sintering, essential for attaining superior density, mechanical properties, and thermal performance. Our experimental results, confirmed through scanning electron microscopy analysis, demonstrate significant microstructural properties, mechanical strength, and thermal conductivity, showcasing the effectiveness of integrating SPS in AM processes. This innovative approach not only expands the capabilities of AM in producing complex, high‐density ceramic structures but also broadens the potential applications of SiC in demanding environments.

36 MATERIALS SCIENCE↗

Effects of Temperature Fluctuations on Surface Mobility of Atomic Steps and Oxidation Dynamics in High-Temperature Alloys

In contrast to the traditional perspective that thermal fluctuations are insignificant in surface dynamics, here we report their influence on surface reaction dynamics. Using real-time low-energy electron microscopy imaging of NiAl(100) under both vacuum and O 2 atmospheres, we demonstrate that transient temperature variations substantially alter the direction of atom diffusion between the surface and bulk, leading to markedly different oxidation outcomes. During heating, substantial outward diffusion of atoms from the bulk to the surface results in step growth. Conversely, cooling induces considerable inward diffusion of adatoms, producing a distinct oxide morphology. In both scenarios, initially formed oxide islands impede local atomic step mobility, thereby increasing step length due to mass transfer between the surface and bulk, with atomic steps acting as adatom sinks during heating and sources during cooling. Furthermore, we show that this pinning effect on atomic step mobility can be mitigated by applying persistent temperature fluctuations. As a result, understanding these nuances is vital for accurately predicting and dynamically manipulating the performance of active materials in various chemical processes under transient thermal conditions.

36 MATERIALS SCIENCE↗

Catalytic Removal of Oxygen and Pollutants in Exhaust Gases from Pressurized Oxy-Combustors

The primary goal of this project was to develop and validate advanced catalytic materials and systems for purifying the flue gas generated from pressurized oxy-combustors in an effort to achieve the purity specifications of carbon dioxide (CO 2 ) streams required by the U.S. Department of Energy (USDOE) for application in enhanced oil recovery. The technology has shown great potential for improving energy efficiency, simplifying process complexity, and lowering costs compared with current state-of-the-art oxy-combustion flue gas purification technologies. Laboratory studies were conducted for the development, characterization, and screening of metal catalysts for residual oxygen (O 2 ) reduction with methane (CH 4 ) and multifunctional carbon catalysts for combined nitrogen oxides (NO x ), sulfur oxides (SO x ), and mercury (Hg) removal. A bench-scale reverse-flow fixed-bed (RFFB) reactor and a trickle-bed direct-contact cooler (DCC) reactor capable of treating 15 standard liters per min of pressurized oxy-combustion flue gas were fabricated and tested with both a simulated flue gas in the laboratory and a slipstream of actual flue gas at a 100 kW th Staged, Pressurized Oxy-Combustion (SPOC) pilot facility. Process simulation and techno-economic studies were performed to evaluate the energy efficiency and cost of the developed catalytic flue gas purification process integrated into a conceptual 550-MWe SPOC power plant. The goal and objectives of the project have been successfully accomplished. A cobalt-manganese (CoMn) oxide catalyst was developed and demonstrated in the bench-scale RFFB reactor in either a reverse-flow or one-direction flow mode of operation that met the success criterion of performance for residual O 2 reduction. A carbon catalyst was developed and demonstrated in the bench-scale DCC reactor that met the success criterion of performance for combined NO x /SO x /Hg removal. Slipstream testing of the integrated DCC-RFFB system at the SPOC pilot facility demonstrated stable operation and verified the superior performance obtained in the laboratory. The techno-economic analysis showed that a 550-MWe SPOC plant integrated with the catalytic flue gas purification process would result in costs of electricity of $\$$96.94/MWh and $\$$80.27/MWh in two assessed cases compared with $\$$91.07/MWh reported for the USDOE’s Current Technology Case, which generated only a partially pure CO 2 stream. On the basis of the results and findings from this project, scale-up studies of materials production and system demonstration and optimization studies of reactors and processes are recommended at the next stage of technology development.

20 FOSSIL-FUELED POWER PLANTS↗

Tailoring Fibre Structure Enabled by X-ray Analytics for Targeted Biomedical Applications

The rising interest in designing fibres via spinning techniques combining the properties of various polymeric materials into advanced functionalised materials is directed towards targeted biomedical applications such as drug delivery, wearable sensors or tissue engineering. Understanding how these functional polymers exhibit multiscale structures ranging from the molecular level to nano-, micro-and millimetre scale is a key prerequisite for their challenging applications that can be addressed by a non-destructive X-ray based analytical approach. X-ray multimodalities combining X-ray imaging, scattering and diffraction allow the study of morphology, molecular structure, and the analysis of nano-domain size and shape, crystallinity and preferential orientation in 3D arrangements. The incorporation of X-ray analytics in the design process of polymeric fibers via their nanostructure under non-ambient conditions (i.e. temperature, mechanical load, humidity…) allows for efficient optimization of the fabrication process as well as quality control along the product lifetime under operating environmental conditions. Here, we demonstrate the successful collaboration between the laboratory of Biomimetic Textiles and Membranes and the Center of X-ray Analytics at Empa for the design, characterisation and optimisation of advanced functionalised polymeric fibrous material systems.

60 APPLIED LIFE SCIENCES↗

Inverse design of photonic surfaces via multi fidelity ensemble framework and femtosecond laser processing

We demonstrate a multi-fidelity (MF) machine learning ensemble framework for the inverse design of photonic surfaces, trained on a dataset of 11,759 samples that we fabricate using high throughput femtosecond laser processing. The MF ensemble combines an initial low fidelity model for generating design solutions, with a high fidelity model that refines these solutions through local optimization. The combined MF ensemble can generate multiple disparate sets of laser-processing parameters that can each produce the same target input spectral emissivity with high accuracy (root mean squared errors < 2%). SHapley Additive exPlanations analysis shows transparent model interpretability of the complex relationship between laser parameters and spectral emissivity. Finally, the MF ensemble is experimentally validated by fabricating and evaluating photonic surface designs that it generates for improved efficiency energy harvesting devices. Our approach provides a powerful tool for advancing the inverse design of photonic surfaces in energy harvesting applications.

97 MATHEMATICS AND COMPUTING↗

The Effects of Beta Irradiation on the Performance of ATR Fiber Probes

The use of real-time inline monitoring to track the chemical composition of slurries is recognized as a promising method to reduce the processing time of Hanford tank waste. The conversion of waste into glass suitable for long-term storage requires adherence to waste acceptance criteria and process control limits that respectively ensure safe operation of the vitrification facility and suitable glass quality. Real-time measurements of blended waste materials can ensure that the various criteria are met or can be addressed in a timely manner.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A statistical representation of bond coating oxidation under environmental barrier coatings

Environmental barrier coatings (EBCs) protect SiC-based ceramic matrix composites (CMCs) in turbine hot sections from high-temperature volatilization in combustion gases. The formation of a SiO 2 thermally grown oxide (TGO) is expected under the EBC after long-term operation. The oxidation resistance of the EBC is understood as a life-limiting factor for the CMC, and this work predicts long-term oxidation behavior under EBCs through a simple statistical approach. Specimens were exposed to 1350°C isothermal conditions for 100-h thermal cycles in flowing steam for up to 1000 h. The EBC morphology, SiO 2 thickness, and SiO 2 cracking behavior were assessed. Using thousands of SiO 2 thickness measurements across many millimeters of the interface, a realistic representation of the entire TGO was captured via a lognormal distribution. The lognormal fit parameters were extrapolated out to 25 000 h to assess the degree of SiO 2 growth, the spread of SiO 2 thicknesses related to the rough oxidizing interface, and percentages of the intermediate bond coating consumed. In conclusion, local interfacial defects from the coating deposition process are identified as local failure points for EBC—CMC systems.

SiO 2↗

Advanced Electron Microscopy of Nanophased Synthetic Polymers and Soft Complexes for Energy and Medicine Applications

After decades of developments, electron microscopy has become a powerful and irreplaceable tool in understanding the ionic, electrical, mechanical, chemical, and other functional performances of next-generation polymers and soft complexes. The recent progress in electron microscopy of nanostructured polymers and soft assemblies is important for applications in many different fields, including, but not limited to, mesoporous and nanoporous materials, absorbents, membranes, solid electrolytes, battery electrodes, ion- and electron-transporting materials, organic semiconductors, soft robotics, optoelectronic devices, biomass, soft magnetic materials, and pharmaceutical drug design. For synthetic polymers and soft complexes, there are four main characteristics that differentiate them from their inorganic or biomacromolecular counterparts in electron microscopy studies: (1) lower contrast, (2) abundance of light elements, (3) polydispersity or nanomorphological variations, and (4) large changes induced by electron beams. Since 2011, the Center for Nanophase Materials Sciences (CNMS) at Oak Ridge National Laboratory has been working with numerous facility users on nanostructured polymer composites, block copolymers, polymer brushes, conjugated molecules, organic–inorganic hybrid nanomaterials, organic–inorganic interfaces, organic crystals, and other soft complexes. This review crystalizes some of the essential challenges, successes, failures, and techniques during the process in the past ten years. It also presents some outlooks and future expectations on the basis of these works at the intersection of electron microscopy, soft matter, and artificial intelligence. Machine learning is expected to automate and facilitate image processing and information extraction of polymer and soft hybrid nanostructures in aspects such as dose-controlled imaging and structure analysis.

36 MATERIALS SCIENCE↗

LaueMatching: an approach for rapid and robust indexing of Laue diffraction patterns

Traditional Laue diffraction pattern indexing often struggles with noisy data, weak signals, peak overlap and missing reflections, particularly from complex or deformed microstructures. Here, we introduce LaueMatching, a high-throughput indexing algorithm designed to overcome these limitations. LaueMatching utilizes a fundamentally different approach based on direct pattern correlation: experimentally pre-processed images are compared against a comprehensive pre-computed library of simulated diffraction patterns corresponding to a dense grid of possible orientations. This approach bypasses the need for explicit peak identification and fitting, steps that are often a failure point for traditional methods. The algorithm rapidly and robustly indexes multiple crystallographic orientations and crystal systems simultaneously, even from challenging patterns. LaueMatching's effectiveness and accuracy have been rigorously tested and validated on diverse experimental (Ni, Al, EuAl 2 O 4 ) and simulated diffraction patterns, demonstrating high-fidelity orientation refinement. Code to implement this approach on both CPU and GPU resources can be downloaded from https://github.com/AdvancedPhotonSource/LaueMatching.

36 MATERIALS SCIENCE↗

Data‐Driven Insights into Rare Earth Mineralization: Machine Learning Applications Using Functional Material Synthesis Data

Understanding rare‐earth element (REE) mineralization mechanisms is essential for developing efficient separation strategies. Although the geochemical pathways that generate REE deposits are qualitatively known, quantitative links between specific conditions and mineralization outcomes remain limited. Herein, the repurpose laboratory REE hydrothermal synthesis data—originally collected for functional‐materials fabrication—as a surrogate for studying mineralization with data‐driven methods. The compiled 1,200+ hydrothermal reaction records and trained three machine‐learning models—K‐nearest neighbors (KNN), random forest (RF), and extreme gradient boosting (XGB)—to predict product elements and phases from precursors, additives, reaction conditions, and engineered features. Validation shows XGB achieves the highest accuracy. Feature importance indicates thermodynamic properties of cations and anions dominate model decisions. Correlations reveal positive relationships among precursor concentration, reaction time, pH, and temperature, consistent with classical crystallization behavior. XGB‐based regressors are built to predict crystallization temperature and pH from precursor/product attributes. Performance is strongest when similar training examples exist, while accuracy declines for underrepresented reactions, notably REE carbonates and heavy‐REE systems. Overall, the study shows that functional‐materials datasets can illuminate REE mineralization and provide priors for exploration and processing. Expanding datasets with less‐studied chemistries and conditions will improve generality and support deposit discovery and more efficient REE recovery.

feature importance analysis↗