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At least 541 records · Page 30

Assessment of Outliers in Alloy Datasets Using Unsupervised Techniques

We report advancements in data analytics techniques have enabled complex, disparate datasets to be leveraged for alloy design. Identifying outliers in a dataset can reduce noise, identify erroneous and/or anomalous records, prevent overfitting, and improve model assessment and optimization. In this work, two alloy datasets (9-12% Cr ferritic martensitic steels, and austenitic stainless steels) have been assessed for outliers using unsupervised techniques and supplemented with domain knowledge. Principal component analysis and k-means clustering were applied to the data, and points were assessed as outliers based on their distance away from other points in the cluster and from other points in the dataset. The outlier characteristics were investigated to determine both cluster-specific and overall trends in the properties of the outlier points. The approach demonstrated here is extensible to other alloy datasets for outlier identification and evaluation to improve the reliability of machine learning and modeling predictions for advanced alloy design.

36 MATERIALS SCIENCE↗

Rapid Assessment of Sulfate Resistance in Mortar and Concrete

Extensive research has been conducted on the sulfate attack of concrete structures; however, the need to adopt the use of more sustainable materials is driving a need for a quicker test method to assess sulfate resistance. This work presents accelerated methods that can reduce the time required for assessing the sulfate resistance of mixtures by 70%. Class F fly ash has historically been used in concrete mixtures to improve sulfate resistance. However, environmental considerations and the evolving energy industry have decreased its availability, requiring the identification of economically viable and environmentally friendly alternatives to fly ash. Another challenge in addressing sulfate attack durability issues in concrete is that the standard sulfate attack test (ASTM C1012) is time-consuming and designed for only standard mortars (not concrete mixtures). To expedite the testing process, accelerated testing methods for both mortar and concrete mixtures were adopted from previous work to further the development of the accelerated tests and to assess the feasibility of testing the sulfate resistance of mortar and concrete mixtures rapidly. This study also established criteria for interpreting sulfate resistance for each of the test methods used in this work. A total of 14 mortar mixtures and four concrete mixtures using two types of Portland cement (Type I and Type I/II) and various supplementary cementitious materials (SCMs) were evaluated in this study. The accelerated testing methods significantly reduced the evaluation time from 12 months to 21 days for mortar mixtures and from 6 months to 56 days for concrete mixtures. The proposed interpretation method for mortar accelerated test results showed acceptable consistency with the ACI 318-19 interpretations for ASTM C1012 results. The interpretation methods proposed for the two concrete sulfate attack tests demonstrated excellent consistency with the ASTM C1012 results from mortar mixtures with the same cementitious materials combinations. Metakaolin was shown to improve sulfate resistance for both mortar and concrete mixtures, while silica fume and natural pozzolan had a limited impact. Using 15% metakaolin in mortar or concrete mixtures with Type I/II cement provided the best sulfate resistance.

Chemistry↗

Clear as mud redefined: Tunable transparent mineral scaffolds for visualizing microbial processes below ground

Microbes inhabiting complex porous microenvironments in sediments and aquifers catalyze reactions that are critical to global biogeochemical cycles and ecosystem health. However, the opacity and complexity of porous sediment and rock matrices have considerably hindered the study of microbial processes occurring within these habitats. Here, we generated microbially compatible, optically transparent mineral scaffolds to visualize and investigate microbial colonization and activities occurring in these environments, in laboratory settings and in situ. Using inexpensive synthetic cryolite mineral, we produced optically transparent scaffolds mimicking the complex 3D structure of sediments and rocks by adapting a suspension-based, freeze-casting technique commonly used in materials science. Fine-tuning of parameters, such as freezing rate and choice of solvent, provided full control of pore size and architecture. The combined effects of scaffold porosity and structure on the movement of microbe-sized particles, tested using velocity tracking of fluorescent beads, showed diverse yet reproducible behaviors. The scaffolds we produced are compatible with epifluorescence microscopy, allowing the fluorescence-based identification of colonizing microbes by DNA-based staining and fluorescence in situ hybridization (FISH) to depths of 100 µm. Additionally, Raman spectroscopy analysis indicates minimal background signal in regions used for measuring deuterium and 13 C enrichment in microorganisms, highlighting the potential to directly couple D 2 O or 13 C stable isotope probing and Raman-FISH for quantifying microbial activity at the single-cell level. To demonstrate the relevance of cryolite scaffolds for environmental field studies, we visualized their colonization by diverse microorganisms within rhizosphere sediments of a coastal seagrass plant using epifluorescence microscopy. The tool presented here enables highly resolved, spatially explicit, and multimodal investigations into the distribution, activities, and interactions of underground microbes typically obscured within opaque geological materials until now.

36 MATERIALS SCIENCE↗

Process damping identification using Bayesian learning and time domain simulation

Process damping can provide improved machining productivity by increasing the stability limit at low spindle speeds. However, existing methods for identifying process damping models experimentally require specialized setups and/or multiple cutting tests. While the phenomenon is well known, the modeling challenges limit pre-process parameter selection that leverages the potential increases in material removal rates. This paper proposes a physics-informed Bayesian method that can identify the cutting force and process damping models from a limited set of test cuts without requiring direct measurements of cutting force or vibration. The method uses time domain simulation to incorporate process damping and provide a basis for test selection. Here, new strategies for efficient sampling and dimensionality reduction are applied to lower computation time and minimize the effect of model error. The proposed method is demonstrated and the identified cutting and damping force coefficients are compared to values obtained using machining tests and least-squares fitting.

42 ENGINEERING↗

Multi-Level Structural Damage Characterization Using Sparse Acoustic Sensor Networks and Knowledge Transferred Deep Learning

Standard structural health monitoring techniques face well-known difficulties for comprehensive defect diagnosis in real-world structures that have structural, material, or geometric complexity. This motivates the exploration of machine-learning-based structural health monitoring methods in complex structures. However, creating sufficient training data sets with various defects is an ongoing challenge for data-driven machine (deep) learning algorithms. The ability to transfer the knowledge of a trained neural network from one component to another or to other sections of the same component would drastically reduce the required training data set. Also, it would facilitate computationally inexpensive machine learning based inspection systems. In this work, a machine-learning-based multi-level damage characterization is demonstrated with the ability to transfer trained knowledge within the sparse sensor network. A novel network spatial assistance and an adaptive convolution technique are proposed for efficient knowledge transfer within the deep learning algorithm. Proposed structural health monitoring method is experimentally evaluated on an aluminum plate with artificially induced defects. It was observed that the method improves the performance of knowledge transferred damage characterization by 50% during localization and 24% during severity assessment. Further, experiments using time windows with and without multiple edge reflections are studied. Results reveal that multiply scattered waves contain rich and deterministic defect signatures that can be mined using deep learning neural networks, improving the accuracy of both identification and quantification. In the case of a fixed sensor network, using multiply scattered waves shows 100% prediction accuracy at all levels of damage characterization.

36 MATERIALS SCIENCE↗

Measurements of attenuation and scattering properties of water-based liquid scintillator

Water-based liquid scintillator (WbLS) is a hybrid detector medium which has been proposed as a fill material for future large-volume rare event searches, including ν − detectors. This family of scintillating suspensions promises waterlike attenuation and scattering behavior, while offering scintillation light yield for sub-Cherenkov-threshold events. These features may allow for improved vertex and energy resolution, and concomitant improvements in background rejection and particle identification. While subscale measurements of light yield, timing and pulse-shape have been performed in several WbLS formulations, detailed measurements of the attenuation and scattering properties of WbLS remain a critical, unresolved step along the pathway to deployment. In pursuit of a better understanding of these parameters, a “long-arm” attenuation and scattering instrument has been developed at Lawrence Livermore National Laboratory, dubbed LASE (Livermore Attenuation and Scattering Experiment). Optical property measurements have been performed using LASE in DI water, Gd-water, WbLS and Gd-WbLS. Measurements of the optical properties of WbLS (1% LAB-PPO scintillator) provided by Brookhaven National Laboratory demonstrate an attenuation minimum of 4.87 × 10 − 4 ± 1.42 × 10 − 4 cm − 1 at 450 nm, while Gd-loaded WbLS (1% LAB-PPO scintillator, 0.1% Gd) demonstrated a minimum attenuation coefficient of 4.77 × 10 − 4 ± 1.27 × 10 − 4 cm − 1 at the same wavelength. Measurements of scattering in WbLS show a scattering coefficient of 3.39 × 10 − 4 ± 1.98 × 10 − 5 cm − 1 at the 450 nm attenuation minimum, while Gd-WbLS has a scattering coefficient of 2.8 × 10 − 4 ± 1.63 × 10 − 5 cm − 1 at that wavelength. These scattering and attenuation coefficients are significantly larger than measured for DI water at similar wavelengths ( 8.8 × 10 − 5 cm − 1 ± 3.8 × 10 − 5 attenuation at 430 nm, 2.2 × 10 − 5 ± 1.28 × 10 − 6 cm − 1 scattering). Though the WbLS attenuation and scattering coefficients measured are lower than the corresponding values published for ultrapure oils and LAB-PPO liquid scintillator, the material tested attenuates significantly more than water across the blue and green portions of the visible spectrum. This attenuation is markedly stronger at wavelengths under 430 nm. Published by the American Physical Society 2025

47 OTHER INSTRUMENTATION↗

Prioritizing Countries by Concern Regarding Access to Weapons of Mass Destruction Materials

This article presents a global prioritization methodology that evaluates the relative risks of non-state actor acquisition of materials that could be used in chemical, biological, radiological, nuclear and high explosive Weapons of Mass Destruction (WMD) from the country’s relevant infrastructure. Prioritization is based on three domains: 1. Assessing relative scale of materials in each country, 2. The country’s corresponding security posture, and 3. The presence of threat actors. The output is a list of countries prioritized from greatest risk to least. Rather than providing an overall 1 to N ranking, however, the results are placed into tiers based upon their natural groupings within the three domains. The countries in the highest tiers are flagged as potential US national security concern; those scoring in the middle and at the bottom are flagged as posing lower US national security concern. A systematic approach assesses each country by leveraging many disciplines, such as risk and decision analysis, as well as expert judgement. A quantitative value model based on Multi-Attribute Value Theory (MAVT) organizes the objectives scoring criteria into a value tree using lessons learned from previous studies, published literature, and expert judgement. The article presents the prioritization categories and corresponding value model scoring criteria to include measurement type, weight, range, and value preference. Country names and data are notional in order to share the details on the underlying methodology and model without identification of actual security risks. A deliberative process addresses factors external to the model and scrutinizes inputs, methodology, model, and results.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

In Situ Identification of Reaction Intermediates and Mechanistic Understandings of Methane Oxidation over Hematite: A Combined Experimental and Theoretical Study

Effective methane utilization for either clean power generation or value-added chemical production has been a subject of growing attention worldwide for decades, yet challenges persist mostly in relation to methane activation under mild conditions. Here, we report hematite, an earth-abundant material, to be highly effective and thermally stable to catalyze methane combustion at low temperatures (<500 °C) with a low light-off temperature of 230 °C and 100% selectivity to CO 2 . The reported performance is impressive and comparable to those of precious-metal-based catalysts, with a low apparent activation energy of 17.60 kcal·mol –1 . Our theoretical analysis shows that the excellent performance stems from a tetra-iron center with an antiferromagnetically coupled iron dimer on the hematite (110) surface, analogous to that of the methanotroph enzyme methane monooxygenase that activates methane at ambient conditions in nature. Isotopic oxygen tracer experiments support a Mars van Krevelen redox mechanism where CH 4 is activated by reaction with a hematite surface oxygen first, followed by a catalytic cycle through a molecular-dioxygen-assisted pathway. Surface studies with in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and density functional theory (DFT) calculations reveal the evolution of reaction intermediates from a methoxy CH 3 –O–Fe, to a bridging bidentate formate b-HCOO–Fe, to a monodentate formate m-HCOO–Fe, before CO 2 is eventually formed via a combination of thermal hydrogen-atom transfer (HAT) and proton-coupled electron transfer (PCET) processes. Finally, the elucidation of the reaction mechanism and the intermediate evolutionary profile may allow future development of catalytic syntheses of oxygenated products from CH 4 in gas-phase heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemical mechanisms and kinetic modeling of calcium aluminate cements hydration in diluted systems: Role of aluminium hydroxide formation

Calcium aluminate cements are niche cements used in the refractory industry and in non-structural applications for building chemistry with short return-to-service delay. The later applications use theses cements in combination with calcium sulfates for long-term stability. By being niche cements, the knowledge of calcium aluminate cements hydration is not as extensive as that of Portland cement. In the present paper, the calcium aluminate cements are studied in diluted suspensions as a function of different parameters such as the suspension concentration or the quantity of added calcium sulfates. The objective is to identify their baseline chemical mechanisms. This work demonstrates the essential role of hydroxide ions fluxes, i.e. quantity going in and out of the liquid phase per unit of time. The main quantitative flux is the formation of aluminium hydroxide but the activation of this reaction is difficult. This difficulty allows calcium aluminate to be used as cement by creating a dormant period (workability) for the overall reactivity. The identification of the key role of aluminium hydroxide formation explains the influence of the temperature, some mechanisms of setting admixtures and the early age of calcium aluminate cements.

36 MATERIALS SCIENCE↗

TEM-based phase characterization of $\mathrm{U–19Pu–10Zr}$ irradiated in ATR

We report the results of the microstructural examination of the irradiated U–19Pu–10Zr fuel. New insights gained using selective area electron diffraction analysis in a transmission electron microscope provide crystallographic information on the phases previously identified based primarily on the chemical compositions. After irradiation, the microstructure of the fuel separates into γ-(U, Pu, Zr) in the central region with a secondary nanocrystalline UO 2 phase, γ-(U, Pu, Zr) with a secondary ZrO 2 phase in the intermediate, and ζ-(U, Pu) in the outer regions. While the surface microstructural features and porosity indicate separation into three concentric zones consistent with the existing constituent redistribution model, crystallographically the fuel consists of two zones: inner (with γ-(U, Pu, Zr) as a matrix phase) and outer (with ζ-(U, Pu) as a matrix phase). Our results highlight the importance of crystal structure in phase identification and can be used to supplement the existing constituent redistribution model.

extreme environment↗

Choose Your Own Adventure: Fabrication of Monolithic All-Perovskite Tandem Photovoltaics

Metal halide perovskites (MHPs) have transfixed the photovoltaic (PV) community due to their outstanding and tunable optoelectronic properties coupled to demonstrations of high-power conversion efficiencies (PCE) at a range of bandgaps. This has motivated the field to push perovskites to reach the highest possible performance. One way to increase the efficiency is by fabricating multijunction solar cells, which can split the solar spectrum, reducing thermalization loss. Low-cost all-perovskite tandems have a real chance to soon exceed 30% PCE, which could transform the PV industry. Achieving this goal requires the identification of perovskite sub-cells that are both highly efficient and can be effectively integrated. In this review, it is discussed how to navigate the multiple-choice adventure in choosing between the myriad of options and considerations present when deciding what perovskite materials, contact layers, and processing tools to use. Some of the potential fabrication pitfalls often encountered in MHP based tandem PVs are highlighted, so that they can hopefully be avoided in the future.

14 SOLAR ENERGY↗

Raman signatures of detonation soot

Soot generated from the detonation of nine explosives was investigated with Raman microspectroscopy and high-resolution transmission electron microscopy (HRTEM). The first order bands, located at approximately 1,580 (G), 1,350 (D1), 1,620 cm –1 (D2), 1,500 (D3), and 1,200 (D4), are used to provide information on the carbon allotropes and defects. The intensity ratios and the full-width at half-maximum provide an indication of the disorder in the material. The Raman spectra of soot acquired from the detonation of nine explosives showed differences which can be used to identify the precursor explosive. Overall, most differences in the spectra were correlated with the presence of amorphous carbon in the soot. In additional to identification of distinct bands in the spectra via deconvolution, principal component analysis was also used to differentiate the different types of soot. HRTEM performed on soot samples with different explosive precursors identified several distinct allotropes of carbon such as nanodiamonds, carbon onions, graphite fibers, and amorphous carbon.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Neutron activation analysis using gamma-gamma coincidence to eliminate spectral interferences

The use of neutron activation analysis (NAA) sometimes has limitations with the identification of specific gamma ray peaks due to spectral interferences. The implementation of gamma-gamma coincidence techniques using the XIA Pixie-16 system has demonstrated the ability reduce many of these challenges. In this work, experiments were performed on two different NIST reference materials using gamma-gamma coincidence techniques to identify long-lived radionuclides that are often difficult to evaluate due to various spectral interferences. The experiments have shown that utilizing gamma-gamma coincidence with the XIA Pixie-16 system for 177m Lu, 124 Sb, 160 Tb, 175 Yb, and 153 Sm can eliminate spectral interferences and high backgrounds due to Compton scattering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synchrotron X-ray diffraction analysis of constituent phases in transition joint between nickel alloy 738LC and a MnFeCoNiCu alloy

Synchrotron x-ray diffraction (XRD) analysis was performed on transition joints between a single-phase MnFeCoNiCu alloy and Ni-base Alloy 738LC to efficiently identify the constituent phases across the interface, with different levels of material intermixing generated by laser-welding with variable power. Here, the intermixing extent was quantified by postmortem energy dispersive x-ray spectroscopy mapping. Diffraction-based analyses on complex composition spaces with limited prior data present significant challenges because elemental substitution in both disordered and ordered phases is more extensive than in conventional alloy spaces, which may effectuate relatively large shifts in the observed lattice parameters that convolute the analysis. Therefore, thermodynamic simulations and crystallographic literature data were employed to construct a system-specific diffraction library of twelve prospective phases for the composition space investigated. Subsequently, for predicted disordered cubic phases, statistical hard-sphere models were established to estimate the lattice parameters and predict diffraction peak positions for inclusion in the library. The library was then employed to analyze diffraction profiles measured from the variably intermixed transition joints, with focus on accounting for both high and low-intensity peaks. 99.0 % of diffraction peaks with relative intensity greater than 0.001 were assigned to phases from the system-specific library, exemplifying rigorous peak accounting and indicating that no unexpected phases were present. Up to six of the twelve library phases were experimentally found in the transition joints. The lattice parameters predicted by the statistical hard-sphere model based upon thermodynamic simulations agree reasonably well with the measured values for the disordered FCC matrix phase.

36 MATERIALS SCIENCE↗

Probing growth of metal–organic frameworks with X-ray scattering and vibrational spectroscopy

Nucleation and crystallization arising from liquid to solid phase are involved in a multitude of processes in fields ranging from materials science to biology. Controlling the thermodynamics and kinetics of growth is advantageous to help tune the formation of complex morphologies. In this report, we harness wide-angle X-ray scattering and vibrational spectroscopy to elucidate the mechanism for crystallization and growth of the metal–organic framework Co-MOF-74 within microscopic volumes enclosed in a capillary and an attenuated total reflection microchip reactor. The experiments reveal molecular and structural details of the growth processes, while the results of plane wave density functional calculations allow identification of lattice and linker modes in the formed crystals. Synthesis of the metal–organic framework with microscopic volumes leads to monodisperse and micron-sized crystals, in contrast to those typically observed under bulk reaction conditions. Reduction in the volume of reagents within the microchip reactor was found to accelerate the reaction rate. The coupling of spectroscopy with scattering to probe reactions in microscopic volumes promises to be a useful tool in the synthetic chemist's kit to understand chemical bonding and has potential in designing complex materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fracture Toughness and Fatigue Crack Growth Rate Testing of Baffle-Former Bolts Harvested from a Westinghouse Two-Loop Downflow Type PWR

As one of the pressurized water reactor (PWR) internal components, baffle-former bolts (BFBs) are subjected to significant mechanical stress and neutron irradiation from the reactor core during the plant operation. Over the long operation period, these conditions lead to potential degradation and reduced load-carrying capacity of the bolts. In support of evaluating long-term operational performance of materials used in core internal components, the Oak Ridge National Laboratory (ORNL), through the Department of Energy (DOE), Light Water Reactor Sustainability (LWRS) Program, Materials Research Pathway (MRP) has harvested two high fluence BFBs from a commercial Westinghouse two-loop downflow type PWR. The two bolts of interest, i.e. bolts # 4412 and 4416, were withdrawn from service in 2011 as part of a preventative replacement plan. No identification of cracking or potential damage was found for these bolts during their removal in 2011. However, the bolts required a lower torque for removal from the baffle structure than the original torque specified during installation. Irradiation displacement damage levels in the bolts range from 15 to 41 displacements per atom. The goal of this project is to perform detailed microstructural and mechanical property characterization of BFBs following in-service exposures. The information from these bolts will be integral to the LWRS program initiatives in evaluating end of life microstructure and properties. Furthermore, valuable data will be obtained that can be incorporated into model predictions of long-term irradiation behavior and compared to results obtained in high flux experimental reactor conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Optimal Adsorbents for Low-Cost Storage of Natural Gas and Hyd: Computational Identification, Experimental Demonstration, and System-Level Projection

This research program will develop best-in-class natural gas (NG) and hydrogen adsorbents based on metal-organic frameworks (MOFs). More specifically, high-throughput computational screening coupled to machine learning will be used to identify MOFs that simultaneously achieve high usable gravimetric and volumetric capacities for methane and hydrogen. The most promising materials pinpointed by computation will be synthesized and characterized experimentally. In addition, the final stage of the project will critically evaluate the use of methane as a model for NG and consider which structural features are most important in making a viable NG storage system.

03 NATURAL GAS↗