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At least 577 records · Page 32

Kinetics and Mechanism of the Singlet Oxygen Atom Reaction with Dimethyl Ether

Here, we combine in situ laser spectroscopy, quantum chemistry, and kinetic calculations to study the reaction of a singlet oxygen atom with dimethyl ether. Infrared laser absorption spectroscopy and Faraday rotation spectroscopy are used for the detection and quantification of the reaction products OH, H 2 O, HO 2 , and CH 2 O on submillisecond time scales. Fitting temporal profiles of products with simulations using an in-house reaction mechanism allows product branching to be quantified at 30, 60, and 150 Torr. The experimentally determined product branching agrees well with master equation calculations based on electronic structure data and transition state theory. The calculations demonstrate that the dimethyl peroxide (CH 3 OOCH 3 ) generated via O-insertion into the C–O bond undergoes subsequent dissociation to CH 3 O + CH 3 O through energetically favored reactions without an intrinsic barrier. This O-insertion mechanism can be important for understanding the fate of biofuels leaking into the atmosphere and for plasma-based biofuel processing technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting and Controlling Corrosion (Abbreviated Final Report)

Corrosion accumulates significant replacement costs in the transportation, utility, manufacturing, and infrastructure sectors. It also underpins several of LLNL’s core missions in stockpile stewardship, defense, and energy security. Whereas most corrosion and aging models are empirically parameterized to describe well-defined conditions late in the reaction, the factors that determine the early stages of corrosion—during which mitigation could be most impactful— are poorly understood. This project addressed the critical need for new approaches to predict the kinetics of corrosion initiation based on firm physical and chemical understanding. The activities encompassed degradation of relevant metals in both hydrogen-rich and environmental corrosion scenarios. The team integrated state-of-the-art multiscale simulation, in situ characterization, and data science within three technical thrusts: hydriding of Ti alloys; aqueous corrosion of Al and Ni-Cr alloys; and degradation of additively manufactured 316L stainless steel. In each case, novel capabilities were developed to identify and track the impacts of key atomistic, compositional, and microstructural features on the metal systems. For hydriding, protocols were developed to tightly integrate multiscale models, advanced multimodal characterization, and machine learning to determine how hydrogen interacts with native passivating surface oxides and nucleates new undesired phases, shedding new light on the critical role of grain boundaries, interfaces, and atomically disordered regions. For aqueous corrosion, the project demonstrated methods to predict dissolution rates of metal surfaces in corrosive solutions, to measure and understand microstructural and grain orientation effects on corrosion susceptibility, and to investigate competing growth and dissolution kinetics of surface oxides. For additively manufactured metals, analysis using state-of-the-art microscopy techniques revealed the role of specific heterogeneities invoked during laser processing, including cellular structure, dislocations, and precipitates, on corrosion susceptibility. In addition to new capabilities and understanding, the project provided an avenue for workforce development, as well as key partnerships with stakeholders in corrosion science.

08 HYDROGEN↗

Enabling Entrained-Flow Gasification of Blends of Coal, Biomass and Plastics (Final Report)

This project demonstrated the technical feasibility of gasifying blends of coal, biomass and mixed waste plastics in a high pressure entrained-flow gasifier for production of hydrogen. This was achieved by creating slurries of coal, biomass pyrolysis liquids and liquefied plastic oil. Specific objectives of the project included (1) determining compositions of coal-biomass-plastic mixtures that produce a stable slurry suitable for pumping to high pressure, (2) designing and testing a novel burner to effectively atomize the mixed feedstock slurry in a pressurized gasifier, and (3) acquiring first-of-a-kind performance data for pressurized, oxygen-blown entrained-flow gasification of slurried blends of coal, biomass and plastic. A key focus of the project was preparation of mixtures of coal, biomass and plastic. To facilitate easy pumping to high pressure, slurries were created using (i) bioliquid resulting from a well-established rapid thermal treatment pyrolysis process, (ii) oil produced from waste plastic via an available thermal conversion process, and (iii) ground coal. Lab-scale tests were conducted to evaluate viscosity and stability/propensity for the mixtures to separate over time. Larger batches of the most promising slurry compositions were prepared and subjected to pumping studies. It was found that mixtures containing less than about 40% coal and less than about 30% plastic oil were stable and of low enough viscosity to facilitate pumping to high pressure. A high-performance hot oxygen burner (HOB) was designed and fabricated for use in an existing 1 ton/day pressurized entrained-flow gasifier. Ex-situ testing demonstrated that the HOB provides excellent atomization of the slurries and creates a very uniform and robust flame. Performance of the HOB in the gasifier was exceptional and resulted in better conversion to syngas than any previous generation of burner. Fabricating the HOB for this project was challenging due to the relatively small scale of the gasifier. Performance in larger-scale systems is expected to be even better. Gasification of mixtures of coal, bioliquid and plastic oil proved to be relatively easy. The gasifier was able to be started up, pressurized and transitioned to the blended slurry feedstock with no technical difficulty. Syngas rich in CO and H 2 , with relatively low concentrations of CO 2 , was produced. During startup and at low gasification temperatures, soot formation was observed, as is typical for gasification of petroleum-based feedstocks. No slag buildup was observed under the conditions tested. The project was successful in demonstrating the technical feasibility of the concept. Future development should broaden the range of feedstocks under consideration, more deeply explore performance of the gasifier, and evaluate scale-up and implementation strategies.

08 HYDROGEN↗

Embedding security into ferroelectric FET array via in situ memory operation

Non-volatile memories (NVMs) have the potential to reshape next-generation memory systems because of their promising properties of near-zero leakage power consumption, high density and non-volatility. However, NVMs also face critical security threats that exploit the non-volatile property. Compared to volatile memory, the capability of retaining data even after power down makes NVM more vulnerable. Existing solutions to address the security issues of NVMs are mainly based on Advanced Encryption Standard (AES), which incurs significant performance and power overhead. In this paper, we propose a lightweight memory encryption/decryption scheme by exploiting in-situ memory operations with negligible overhead. To validate the feasibility of the encryption/decryption scheme, device-level and array-level experiments are performed using ferroelectric field effect transistor (FeFET) as an example NVM without loss of generality. Besides, a comprehensive evaluation is performed on a 128 × 128 FeFET AND-type memory array in terms of area, latency, power and throughput. Compared with the AES-based scheme, our scheme shows ~22.6×/~14.1× increase in encryption/decryption throughput with negligible power penalty. Furthermore, we evaluate the performance of our scheme over the AES-based scheme when deploying different neural network workloads. Our scheme yields significant latency reduction by 90% on average for encryption and decryption processes.

47 OTHER INSTRUMENTATION↗

A laser ultrasonics-based approach for rapid screening of high entropy alloys

The primary objective of this seed project is to develop a laser ultrasonics-based characterization methodology for rapid metallic materials design and discovery via in situ determination of phases, microstructures and elastic properties with respect to temperature. Ultrasonic waves are strongly affected by material microstructure, and therefore, serve as a facile means to probe elastic properties, phase content and their size distributions and volume fractions. In this study, a laser ultrasonic technique will be used to systematically study the evolution of properties in a set of interrelated simple binary alloys and high entropy alloys (HEA). Phase transformations and microstructural changes inferred from the ultrasonic signals will be correlated with electron microscopy data and predictions using calculations of phase diagrams (CALPHAD). The non-contact and non-destructive ultrasonic testing approach developed in this study could overcome several limitations associated with current material characterization methods for materials discovery. It is expected that the products of the proposed work will be utilized to evaluate novel graded composition HEAs currently being developed at the Idaho National Laboratory (INL) using advanced manufacturing methods based on direct energy deposition and spark plasma sintering processes, and contribute to accelerate the discovery of HEAs.

36 MATERIALS SCIENCE↗

Swept-Lookback Deflectometry for High Performance Concentrating Solar Power Optical Metrology

This report describes an initial investigation into a proposed solution to the important problem of performing a detailed evaluation of heliostat optical performance, in situ in a heliostat field. Our approach is to place digital cameras in a position near the receiver where they look back toward the heliostat mirrors. The pixels of each camera sensor identify a set of small cells on the mirror surface, each corresponding to a “mixel.” By either passing reflected sunbeam over the camera or passing the camera through the reflected sunbeam, the cameras intercept sunlight reflected from each mixel. We then analyze the recorded video data to determine times when each mixel transitions from dark to light, and then back to dark. We then use these transitions to construct vectors from the camera to the mixel, and then from the mixel to the edge of the Sun at that moment. We then compute the surface normal at the mixel, which bisects the angle between these vectors. Performing this analysis for all mixels in the mirror yields a high-resolution map of slope across the mirror surface. We have implemented most of this process, successfully collecting data for an example heliostat facet and computing a preliminary estimated slope map. However, more work remains to complete this calculation, since certain factors and transformations are not yet included. Our observations so far support our hypothesis that such a system is possible, but we have not yet completed our quantitative evaluation of the concept.

14 SOLAR ENERGY↗

Dry in-pile fracture test (DRIFT) for separate-effects validation of ceramic fuel fracture models

Fracture is an important component of nuclear fuel behavior, and significant efforts have been invested into developing fuel performance models that are capable of accurately representing fracture. Usable data on the process of fracture propagation in nuclear fuel under realistic service conditions are very limited. To address this need, a series of separate-effects experiments were developed and performed at Idaho National Laboratory's Transient Reactor Test (TREAT) facility. These experiments employ a heat sink to radially remove heat from the fuel in a manner that approximates the effect of coolant in an operating light-water reactor (LWR). The test holder for these experiments is known as the Dry In-pile Fracture Test (DRIFT). A series of experiments employing DRIFT and TREAT were performed to provide data on the extent and nature of fracture in fresh fuel at various points during a ramp to full power. Novel aspects of these experiments include the way they employ a heat sink to replicate steady-state LWR conditions, as well as the use of fiber optic sensors for in-reactor thermal instrumentation. Details on the development of this experiment, experimental conditions, and resulting data (including in situ thermal measurements and post-irradiation imaging of fracture) are provided in this work. LWR-equivalent powers ranging from 10 to 25 kW/m were tested using this apparatus. Cracking was visible at all power levels, with increasing cracking extent as the power level increased, although there was little difference in the cracking between the two highest-power tests, which had LWR-equivalent powers of 20 and 25 kW/m.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Nonpyrophoric alternative to trimethylaluminum for the atomic layer deposition of Al 2 O 3

We have examined the atomic layer deposition (ALD) of Al 2 O 3 using a nonpyrophoric precursor, which possesses only Al–N bonds and no Al–C bonds: Al(N(CH 3 ) 2 ) 2 (–N(C 2 H 5 )–C 2 H 4 –N(C 2 H 5 ) 2 ), which we refer to as bis-dimethylamino-diamino-aluminum (BDMADA-Al). We employed a quartz crystal microbalance (QCM) to monitor ALD in situ and in real time, and the deposited thin films have been characterized using x-ray photoelectron spectroscopy, spectroscopic ellipsometry, x-ray reflectivity, and atomic force microscopy. Films deposited with BDMADA-Al result in near-stoichiometric Al2O3 at temperatures ranging from T = 120 to 285 °C using H 2 O as the coreactant and at T = 285 °C using t-BuOH as the coreactant. The properties of the films (density, C incorporation, stoichiometry, growth rates) are comparable using either BDMADA-Al or trimethylaluminum (TMA) as the precursor under similar reaction conditions. The N content in the films deposited with BDMADA-Al as the precursor is <1% at both T = 120 and 285 °C. Additionally, both BDMADA-Al|t-BuOH and TMA|t-BuOH processes deposit near-stoichiometric Al 2 O 3 at T = 285 °C, while neither process chemistry produces a constant growth rate per cycle at T = 120 °C. Close examination of single cycle QCM data from BDMADA-Al ALD indicates unique ligand exchange reaction mechanisms during each of the half-reactions. Experimentally, we have evidence supporting the mechanism in which upon the chemisorption of BDMADA-Al, the species on the surface retains the –N(CH 3 ) 2 ligands, while the diamine ligand is mostly lost on dissociative adsorption, except possibly at the higher temperature (285 °C). As a result, our work demonstrates that BDMADA-Al can be used as an effective alternative precursor to TMA for the ALD of Al 2 O 3 .

36 MATERIALS SCIENCE↗

A laser ultrasonics-based approach for rapid screening of high entropy alloys

This project demonstrates a laser ultrasonics-based characterization methodology for rapid metallic materials design and discovery via in situ determination of phases, microstructures and elastic properties with respect to temperature. Ultrasonic waves are strongly affected by material microstructure, and therefore serve as a facile means to probe elastic properties, phase content and their size distributions and volume fractions. In this study, a laser ultrasonic technique is used to systematically study the evolution of properties in a set of interrelated simple binary alloys and high entropy alloys (HEA). Phase transformations and microstructural changes inferred from the ultrasonic signals will be correlated with electron microscopy data and predictions using calculations of phase diagrams (CALPHAD). The non-contact and non-destructive ultrasonic testing approach developed in this study could overcome several limitations associated with current material characterization methods for materials discovery. It is expected that laser ultrasonics-based methodology developed in this work will be utilized to evaluate novel graded composition HEAs currently being developed at the Idaho National Laboratory (INL) using advanced manufacturing methods based on direct energy deposition and spark plasma sintering processes, and contribute to accelerate the discovery of HEAs.

36 MATERIALS SCIENCE↗

High-Temperature 2D Optical Relaxation Visualizes Enhanced Oxygen Exchange Kinetics at Metal-Mixed Conducting Oxide Interfaces

Solid-state heterointerfaces are of interest for emergent local behavior that is distinct from either bulk parent compound. One technologically relevant example is the case of mixed ionic/electronic conductor (MIEC)–metal interfaces, which play an important role in electrochemistry. Metal–MIEC composite electrodes can demonstrate improved catalytic activity vs single-phase MIECs, improving fuel cell efficiency. Similarly, MIEC surface reaction kinetics are often evaluated using techniques that place metal current collectors in contact with the surface under evaluation, potentially altering the response vs the native surface. Here, techniques enabling direct and local in situ observation of the behavior at and around such heterointerfaces are needed. Here, we develop a spatially resolved optical transmission relaxation (2D-OTR) method providing continuous evaluation of local, high-temperature, controlled atmosphere defect kinetics across a ~1 cm2 sample area simultaneously in a contact-free manner. We apply it to observe the spatial variance of oxygen incorporation and evolution rates at ~525–620 °C, in response to step changes in oxygen partial pressure, on MIEC SrTi 0.65 Fe 0.35 O 3–x films as a function of distance from porous Pt and Au layers. Using this model geometry, we find significant enhancements in kinetics adjacent to the metals that decay over a few millimeter distance. To extract kinetic parameters, we fit the short-term optical data (initial portion of relaxations) with an exponential decay function appropriate for surface-exchange-limited kinetics, yielding apparent surface exchange coefficients (k chem ) with spatial resolution, decreasing with distance from the metal. To understand the kinetic processes governing the complete (long-term) optical relaxations, we performed COMSOL simulations, which demonstrated that a combination of laterally varying k chem and in-plane diffusion controls the observed kinetics over the full time range. Further support for spatially varying kchem comes from demonstrations of changing surface and bulk chemistry vs distance from the metal–MIEC interface, by X-ray photoelectron and optical absorption spectroscopies, respectively. Although microporous Pt and Au are not excellent electrodes in isolation, both metals exert a synergistic effect on the oxygen surface exchange rate in the presence of the mixed conducting film.

36 MATERIALS SCIENCE↗

High-Resolution Sampling of a River Plume Front with Uncrewed Underwater and Aerial Vehicles

Sampling fast-propagating oceanic features is inherently challenging and demands versatile instrumentation and innovative strategies. This paper introduces a novel sampling strategy designed to capture such phenomena, exemplified by a river plume front. Our method revolves around modifying the preprogrammed pathway of an uncrewed underwater vehicle (UUV) to dynamically track and three-dimensionally sample the evolution of the front. To enable the UUV to follow the feature, we adapt the use of a drifting gateway buoy to be positioned and trapped at the front’s convergence zone, allowing underway navigation relative to the buoy. In our demonstration, we showcase the effectiveness of this strategy by successfully conducting over 30 crossings of a river plume front within a 6-h window. The UUV sensors allowed a comprehensive assessment of key front characteristics, including density, velocity, and turbulence. Supplemental drone footage contributed to the overall picture and facilitated the transformation of the dataset into a front-following reference frame. This article provides an in-depth description of the deployment strategy and required postcollection data processing, including frontal crossing detection, the assessment of the frontal orientation from drone footage, and defining the plume bottom boundaries using backscatter intensity contours.

autonomous observations↗

X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X

Mapping in situ eddy covariance measurements of terrestrial land–atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented upscaling framework, FLUXCOM-X, representing an advancement from the previous generation of FLUXCOM products in terms of flexibility and technical capabilities. The X-BASE products are comprised of estimates of CO 2 net ecosystem exchange (NEE), gross primary productivity (GPP), evapotranspiration (ET), and for the first time a novel, fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at −5.75 ± 0.33 Pg C yr −1 for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site years resulting in a wider coverage of bioclimatic conditions. However, X-BASE global net ecosystem exchange shows a very low interannual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C yr −1 for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7×10 3 ± 0.9×10 3 km 3 globally for the years 2001–2020 but exceeds precipitation in many dry areas, likely indicating overestimation in these regions. On average 57 % of evapotranspiration is estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous upscaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.

Nelson, Jacob A.↗

Mapping the Complete Reaction Energy Landscape of a Metal–Organic Framework Phase Transformation

Crystalline materials undergo valuable phase transformations, and the energetic processes that underlie these transformations can be fully characterized through a combination of thermodynamic and kinetic studies. Here, we report the first complete reaction energy landscape of metal–organic framework (MOF) interpenetration, specifically in the phase transformation of NU-1200 to its doubly interpenetrated counterpart, STA-26. We characterized the thermodynamics of this phase transformation by pairing experiments with density functional theory (DFT) calculations. This analysis revealed that factors such as the increase in crystal density likely drive Zr- and Hf-NU-1200 to STA-26 interpenetration, while other chemical interactions such as steric repulsions prevent Th-NU-1200 from interpenetrating. Using time-resolved in situ X-ray diffraction, we monitored phase transformation reaction profiles and extracted quantitative kinetic information using the Avrami-Erofe’ev model. As a result, we obtained activation energies for the Zr- and Hf-NU-1200 transformations to Zr- and Hf-STA-26, respectively, revealing slower phase change kinetics for MOFs with stronger bonds. Finally, we paired the kinetic data with experimental observations to classify the mechanistic model of this phase transformation as partial dissolution. Here, we anticipate that this thermodynamic, kinetic, and mechanistic understanding will broadly inform further studies on the energetics of crystallization.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Data for Bioprocessing, Recovery, and Mass Balance of Vegetative Lipids from Metabolically Engineered ‘Oilcane’ Demonstrates Its Potential as an Alternative Feedstock for Drop-In Fuel Production

Plant oils are increasingly in demand as renewable feedstocks for biodiesel and biochemicals. Currently, oilseeds are the primary source of plant oils. Although the vegetative tissues of plants express lipid metabolism pathways, they do not hyper-accumulate lipids. Elevated synthesis, storage, and accumulation of lipids in vegetative tissues have been achieved by metabolic engineering of sugarcane to produce “oilcane.” This study evaluates the potential of oilcane as a renewable feedstock for the co-production of lipids and fermentable sugars. Oilcane was grown under favorable climatic and field conditions in Florida (FLOC) as well as during an abbreviated growing season, outside its typical growing region, in Illinois (ILOC). The potential lipid yield of 0.35 tons/ha was projected from the hyperaccumulation of fatty acids in the stored vegetative biomass of FLOC, which is approaching the lipid yield of soybean (0.44 tons/ha). Processing of the vegetative tissues of oilcane recovered 0.20 tons/ha, which represents the recovery of 55% of the total lipids from FLOC. Chemical-free hydrothermal bioprocessing of ILOC and FLOC bagasse and leaves at 180 °C for 10 min prevented the degeneration of in situ plant lipids. This allowed the recovery of lipids at the end of the bioprocess with a major fraction of lipids remaining in the biomass residues after pretreatment and saccharification. Improvements through refined biomass processing, crop management, and metabolic engineering are expected to boost lipid yields and make oilcane a prime feedstock for the production of biodiesel.

Conversion↗

EdgeAI: Machine learning via direct attached accelerator for streaming data processing at high shot rate x-ray free-electron lasers

We present a case for low batch-size inference with the potential for adaptive training of a lean encoder model. We do so in the context of a paradigmatic example of machine learning as applied in data acquisition at high data velocity scientific user facilities such as the Linac Coherent Light Source-II x-ray Free-Electron Laser. We discuss how a low-latency inference model operating at the data acquisition edge can capitalize on the naturally stochastic nature of such sources. We simulate the method of attosecond angular streaking to produce representative results whereby simulated input data reproduce high-resolution ground truth probability distributions. By minimizing the mean-squared error between the decoded output of the latent representation and the ground truth distributions, we ensure that the encoding layers and resulting latent representation maintains full fidelity for any downstream task, be it classification or regression. We present throughput results for data-parallel inference of various batch sizes, some with throughput exceeding 100 k images per second. We also show in situ training below 10 s per epoch for the full encoder–decoder model as would be relevant for streaming and adaptive real-time data production at our nation’s scientific light sources.

97 MATHEMATICS AND COMPUTING↗

Dynamics of deuterium retention and desorption from plasma-facing materials in fusion reactor-relevant conditions

Hydrogen isotopes retention and desorption during and after discharges in fusion devices are still not well understood due to the complex device conditions and limitations of in-situ diagnostics and measurements. Here, we simulated well-diagnosed recent experiments at the DIII-D facility to benchmark our ITMC-DYN integrated package of modeling deuterium diffusion, retention, and desorption during and after D discharge irradiation. Modeling results were compared with detail experimental data of D desorption fluxes for various irradiation conditions. We predicted the temporal evolution of free and trapped D distribution in tungsten (W) plasma-facing material (PFM). Effects of key parameters namely diffusion coefficient, recombination rate, trapping energies against different defect types, were examined in these simulations. Existing experimental data of these parameters in literature varies significantly which makes it harder to identify key mechanisms and physics responsible for hydrogen isotope retention and desorption. The purpose of this work is to accurately simulate recent well-diagnosed reactor experiments given the uncertainties in such parameters and identify mechanisms responsible for the retention and desorption. We implemented the best identified diffusion, recombination, and trapping parameters in ITMC-DYN package that integrate both various collisional and thermal processes. We predicted, for example, that sample cooling between discharges in DIII-D operations can significantly affect the spatial distribution of trapped D in W under reactor irradiation conditions. Correct prediction of desorption spectra from samples irradiated during 10 DIII-D discharges showed that up to 35% of D can be retained in high binding energy defects such as vacancy clusters or voids.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Electrochemical Characterization of Dissolved Oxides in Molten FLiNaK

Molten fluoride salts have long been the subject of investigation given their application in a variety of industrial processes. Oxides are a common exogeneous impurity within these systems, and can lead to many operational and regulatory concerns. In recent studies, the electro-oxidation of dissolved metallic oxides has been attributed to a single step oxygen evolution reaction despite voltametric evidence suggesting otherwise. Here, we first use square wave voltammetry to confirm that the oxidation of dissolved oxides in fluorides proceeds via a two-electron transfer reaction and then demonstrate that the presence of a peroxide-mediated redox reaction better explains the electrochemical data. Numerical simulations were then used to support the determination of improved diffusion coefficients to enable electroanalytical measurements of the oxide concentration across at a variety of temperatures. A linear Arrhenius relationship was observed when the experimental data was corrected for ohmic resistance effects. Concentration measurements using the corrected square wave voltammetry data demonstrated high accuracy across a large range of concentrations, while the uncorrected data showed plateauing and high errors. In total, this work serves to rectify previously misconstrued electrochemical data of oxides in molten salts and demonstrate how accurate, in situ concentration measurements can be achieved in real-world systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Uncovering acoustic signatures of pore formation in laser powder bed fusion

Abstract We present a machine learning workflow to discover signatures in acoustic measurements that can be utilized to create a low-dimensional model to accurately predict the location of keyhole pores formed during additive manufacturing processes. Acoustic measurements were sampled at 100 kHz during single-layer laser powder bed fusion (LPBF) experiments, and spatio-temporal registration of pore locations was obtained from post-build radiography. Power spectral density (PSD) estimates of the acoustic data were then decomposed using non-negative matrix factorization with custom $$\varvec{k}$$ k -means clustering (NMF $$\varvec{k}$$ k ) to learn the underlying spectral patterns associated with pore formation. NMF $$\varvec{k}$$ k returned a library of basis signals and matching coefficients to blindly construct a feature space based on the PSD estimates in an optimized fashion. Moreover, the NMF $$\varvec{k}$$ k decomposition led to the development of computationally inexpensive machine learning models which are capable of quickly and accurately identifying pore formation with classification accuracy of supervised and unsupervised label learning greater than 95% and 90%, respectively. The intrinsic data compression of NMF k , the relatively light computational cost of the machine learning workflow, and the high classification accuracy makes the proposed workflow an attractive candidate for edge computing toward in-situ keyhole pore prediction in LPBF.

36 MATERIALS SCIENCE↗