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At least 181 records · Page 10

Versatile Cell Design for Molten Fluoride Salt Spectroscopy: Investigating Metal-Ion Speciation in Molten Fluoride Salts

Fluoride-based molten salts are widely used in industrial applications including aluminum production, thermal energy storage, optical crystal growth, and advanced nuclear reactor designs. Despite the wide range of uses, fundamental understandings of coordination chemistry and methods for probing molten fluorides are scarce, likely due to the difficulty of probing fluoride melts with spectroscopic techniques. Performing spectroscopic measurements of fluoride-based salts is challenging due to the highly corrosive nature of these salts, which can degrade many common optical materials. Here, in this work, we present a versatile optical cell design that enables spectroscopic measurements of corrosive melts. This innovative cell design overcomes the challenges posed by the corrosive nature of the salts, allowing for an accurate and consistent spectroscopic analysis. This work reports temperature-dependent absorption measurements for Co 2+ , Ni 2+ , and Cr 3+ analytes in LiF-NaF-KF eutectic salt (i.e., FLiNaK), which are common corrosion products originating from structural alloys in molten-fluoride handling. Absorption spectra were used to understand interactions of these analytes with FLiNaK, particularly ligand field coordination. The analysis of absorption spectra was complemented by structural analyses using ab initio molecular dynamics (AIMD) simulations, providing deeper insights into the behavior of the analytes in FLiNaK. Our findings indicate that the analytes studied in this work exist in octahedral or near-octahedral coordination states that remain stable across the temperature range of 500–600 °C. This work not only highlights an applied solution to performing optical spectroscopy in corrosive, high-temperature melts but also provides important fundamental insight on coordination behavior of transition-metal species in molten fluorides.

Fluoride salt spectroscopy↗

xSDK: Building an ecosystem of highly efficient math libraries for exascale

Current efforts to build increasingly powerful computer architectures are opening up new avenues for more complex and higher fidelity simulations coupled with data analytics and learning, leading to new scientific insights and deeper understanding. At one extreme, exascale computers will be much faster than previous computer generations (performing 10 18 operations per second—that is, 1,000 times faster than petascale). To achieve these performance improvements, computer architectures are becoming increasingly complex, with deep memory hierarchies, very high node and core counts, and heterogeneous features such as graphics processing units (GPUs). Such architectural changes impact the full breadth of computing scales, as heterogeneity pervades even current-generation laptops, workstations, and moderate-sized clusters. While emerging advanced architectures provide unprecedented opportunities, they also present significant challenges for developers of scientific applications, such as multiphysics and multiscale codes, who must adapt their software to handle disruptive changes in architectures and new programming models that have not yet stabilized. Developers must consider increasing concurrency while reducing communication and synchronization, and other complexities such as the potential for using mixed precision to leverage the compute power available in low-precision tensor cores. On one hand, developers must implement new scientific capabilities, which in turn increase code complexity. On the other hand, the codes must be ported to new architectures, requiring the inclusion of new programming models and the restructuring of code to achieve good performance. Addressing these issues is beyond the capability of any single person or team—leading to the need for collaboration among many teams, who encapsulate their expertise in reusable software and work together to create sustainable software ecosystems.

97 MATHEMATICS AND COMPUTING↗

Comparative Studies of Optoelectrical Properties of Prominent PV Materials: Halide Perovskite, CdTe, and GaAs

We compare three representative high performance PV materials: halide perovskite MAPbI3, CdTe, and GaAs, in terms of photoluminescence (PL) efficiency, PL lineshape, carrier diffusion, and surface recombination and passivation, over multiple orders of photo-excitation density or carrier density appropriate for different applications. An analytic model is used to describe the excitation density dependence of PL intensity and extract the internal PL efficiency and multiple pertinent recombination parameters. A PL imaging technique is used to obtain carrier diffusion length without using a PL quencher, thus, free of unintended influence beyond pure diffusion. Our results show that perovskite samples tend to exhibit lower Shockley-Read-Hall (SRH) recombination rate in both bulk and surface, thus higher PL efficiency than the inorganic counterparts, particularly under low excitation density, even with no or preliminary surface passivation. PL lineshape and diffusion analysis indicate that there is considerable structural disordering in the perovskite materials, and thus photo-generated carriers are not in global thermal equilibrium, which in turn suppresses the nonradiative recombination. This study suggests that relatively low point-defect density, less detrimental surface recombination, and moderate structural disordering contribute to the high PV efficiency in the perovskite. This comparative photovoltaics study provides more insights into the fundamental material science and the search for optimal device designs by learning from different technologies.

14 SOLAR ENERGY↗

Deliberate Motion Analytics Fused Radar and Video Test Results Deployed Beyond the Perimeter Fence in a High Noise Environment

Security systems that protect the nation’s critical facilities must be capable of detecting physical intrusions in all weather conditions. Intrusion detection sensors in a perimeter with a high nuisance alarm rate (NAR) significantly undermine detection performance and degrade security system effectiveness. This research demonstrated a fused sensor system that can differentiate foliage and weather-induced nuisance alarms from those caused by intruders, providing reliable detection within a two-fence perimeter or beyond the fence. A key element of this work is the creation and application of a “deliberate motion algorithm” that fuses alarm data from radar and video analytics to create video motion detection fused radar system. The two-layer architecture of the algorithm uses machine learning, multi-hypothesis tracking, and Dynamic Bayes Nets to differentiate intruder alarms from weather induced alarms.

47 OTHER INSTRUMENTATION↗

Catalyzing the future: recent advances in chemical synthesis using enzymes

Biocatalysis has the potential to address the need for more sustainable organic synthesis routes. Pro-tein engineering can tune enzymes to perform in cascade reactions and for efficient synthesis of en-antiomerically enriched compounds, using both natural and new-to-nature reaction pathways. This review highlights recent achievements in biocatal-ysis, especially the development of novel enzymatic syntheses to access versatile small molecule inter-mediates and complex biomolecules. Biocatalytic strategies for the degradation of persistent pollu-tants and approaches for biomass valorization are also discussed. Here, the transition of chemical synthesis to a greener future will be accelerated by imple-menting enzymes and engineering them for high performance and new activities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Separation of rare earth element radioisotopes by reverse-phase high-speed counter-current chromatography

Analytical scale purification of rare earth element (REE) radioisotopes is typically accomplished using cation-exchange resins (e.g. AG 50W-X8) and high-performance liquid chromatography (HPLC). Despite the variety of improvements made since the development of this separation process in the 1950s, nearest neighbor separations remain a challenge, as does the issue of irreversible sample adsorption. Herein, we report a study that evaluates the potential of high-speed counter-current chromatography (HSCCC) as an alternative method for purifying REE elements, with specific reference to separations of fission product REE of interest to nuclear forensics. Complementary HSCCC REE separation experiments, one spiked with radiotracer and REE fission product activity, allowed for in depth analysis of resulting fractions from both an elemental (inductively coupled plasma atomic emission spectroscopy, ICP-AES) and radiological (gamma-ray spectrometry, beta counting) purity perspective. The highly reproducible nature of separation profiles generated from HSCCC instruments was leveraged to simplify work-up of samples containing radioisotopes. Subsequent radioanalytical evaluation revealed minimal carryover of Eu into neighboring Sm and Tb fractions (as indicated by presence of 150Eu), and trace contamination of the Tb fraction with Y (as indicated by presence of 91Y). Subtle differences in stationary phase retention across the two columns were reflected in significant variations in decontamination factors of duplicate parallel separations. Furthermore, these differences paired with obtained distribution of radioisotopes provided valuable insights into future improvements. Collectively, this study represents a significant step forward in development of HSCCC technology for task specific REE radioisotope purification.

07 ISOTOPE AND RADIATION SOURCES↗

Experimental characterization of a triply periodic minimal surface PCM-to-air thermal energy storage device

Here, the expansion of energy production has intensified research into thermal energy storage (TES) to manage variability and improve system efficiency. Heat exchanger design is critical to achieving high power densities in TES systems. This study presents a high-surface-area phase change material (PCM)-to-air heat exchanger fabricated via resin-based stereolithography with a novel gyroid-based geometry tailored for enhanced performance. Material properties of the commercial PCM and resin were characterized using analytical techniques. A controlled air loop was used to evaluate heat transfer and pressure drop at various flow rates and inlet temperatures. Results show a strong dependence on the inlet temperature difference (ΔT) relative to the PCM melting point. During charging at the highest flow rate, increasing the inlet air temperature from ΔT = 5 °C to 20 °C above the melting point increased the average heat transfer rate by 187%. During discharging, decreasing the inlet temperature by the same ΔT below the melting point led to a 232% increase. Notably, the high-surface-area design enabled nearly symmetric charging and discharging behavior, a novel result for PCM-based TES systems which are often restricted by natural convection and other effects. The overall heat transfer coefficient was calculated and compared to values from standard design correlations. The maximum thermal effectiveness reached 95% at ΔT = 20 °C and a moderate flow rate of 34 m 3 /h. Peak coefficients of performance (COP) of 7 during charging and 6.4 during discharging were observed at ΔT = 20 °C and a low flow rate of 20 m 3 /h. These results demonstrate the viability of additively manufactured geometries for advanced TES applications.

25 ENERGY STORAGE↗

Effects of chemical segregation on ductility-anisotropy in high strength Fe-Mn-Al-C lightweight austenitic steels

Ductile Fe-Mn-Al-C lightweight steels offer great potential as high specific strength materials for weight critical applications. In the present work, very high yield (~1 GPa) and ultimate tensile strength levels (~1.5 GPa) were obtained along the rolling and transverse directions of Fe-30Mn-8.5Al-0.9Si-0.9C-0.5Mo (wt.%), with high tensile elongation to failure of ~35%. This excellent mechanical behavior was attributed to the nanoscale, ordered κ-carbide precipitates formed during aging after rolling. However, tensile ductility was not isotropic through all directions of the rolled plate. In particular, the ductility was consistently lower than 5% true strain along the normal direction. Upon detailed microstructural investigations, micro-scale lamellar chemical micro-segregation bands were detected, which caused the observed anisotropic embrittlement along certain plate directions. These bands resulted in low failure strains along the normal direction since it is oriented perpendicular to these chemical segregation bands, resulting in a failure type reminiscent of delamination-induced cleavage fracture. Chemical segregation causes an inhomogeneous κ-carbide precipitate distribution upon aging, producing more pronounced mechanical anisotropy after peak-aging as compared to the solution heat treated samples. Surprisingly, deformation twinning was observed after tensile deformation of solution-heat treated specimens via electron-backscatter diffraction experiments, which is anomalous for a high stacking faulty energy (SFE) material. Further, it was proposed that chemical micro-segregation promotes locally different SFE regions, leading to deformation twinning in this nominally high SFE material. Overall, this work demonstrates the effects of chemical segregation on mechanical properties and microstructural evolution in a high performance, lightweight Fe-Mn-Al-C steel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Batch Scale Production of 3D Printed Extraction Sorbents Using a Low-Cost Modification to a Desktop Printer

This study reports a simple modification to a commercial resin 3D printer that significantly reduces the amount of prepolymer material needed for the production of extraction sorbents. Here, the modified printing platform is demonstrated in the printing of two imidazolium-based ionic liquid (IL) monomers. Two geometries resembling a blade-type polymeric ionic liquid (PIL) sorbent used in thin-film microextraction and a fiber-type sorbent used in solid-phase microextraction (SPME) were printed. The SPME PIL sorbents were used to extract 10 organic contaminants, including plasticizers, antimicrobial agents, UV filters, and pesticides, from water followed by high-performance liquid chromatographic (HPLC) analysis. To compare the extraction performance of the SPME sorbents, seven fibers printed with the same prepolymer composition from the same printing batch as well as different batches were evaluated. The results revealed highly reproducible extraction efficiencies for all tested sorbents with no statistical difference in their extraction performance. Method validation showed acceptable linearity ($R$ 2 > 0.92) for all analytes with limits of detection and limits of quantification ranging from 0.13 to 45 μg L –1 and 0.43 to 150 μg L –1 , respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-energy ballistic electrons in low-pressure radio-frequency plasmas

This study demonstrates the presence of a small number of high-energy ballistic electrons (HEBEs) that originate from secondary electrons in low-pressure radio-frequency (rf) plasmas. The kinetic behaviors of the HEBEs are illustrated through electron energy probability functions from the fully kinetic particle-in-cell simulations, showing two wavy high-energy tails and two bifurcations during one rf cycle. Test-particle simulations and a semi-analytical method associated with nonlocal electron kinetics are performed to characterize the HEBE trajectories, which reveal the ballistic nature of the HEBEs and their typical bouncing features between the rf sheaths. Parameter dependence of the HEBEs on the discharge conditions (e.g., gas pressure, gap distance, and rf frequency) are identified, which is relevant to the plasma collisionality. With a pronounced presence of HEBEs, the overall impacts of the secondary electron emission on discharge parameters, such as electron power absorption and ionization rate, are also illustrated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Conceptual design of a high reactive-power ferroelectric fast reactive tuner

We present a novel design of a ferroelectric fast reactive tuner (FE-FRT) capable of modulating mega-VAR reactive power on a submicrosecond timescale. The high reactive power capability of our design extends the range of applications of reactive tuners to numerous applications. We present a detailed analytical model of the performance of a megawatt-class reactive power device and benchmark it against finite-element method eigenmode and frequency domain electromagnetic simulations. We introduce new features, including an annulus design for the ferroelectric capacitors and capacitive window coupling to the cavity. We consider thermal design issues and nonlinear effects in the ferroelectric. The model covers several configurations, allowing control of the frequency of superconducting and normal-conducting cavities in a variety of applications and frequencies. We calculate that the FE-FRT designed should be capable of handling around 0.45 MVAR of reactive power with around 3 kW of resistive losses, providing a frequency tuning range of 8 kHz in an example of 400 MHz cavity geometry. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers

The current practice for fusion scientists running first principle simulations on high performance computing plat-forms is to either run their simulations and output their data for post-hoc analysis, or to place in situ analytics into their code. In this paper we examine a complex workflow using XGC fusions simulation run on the Oak Ridge Leadership Computing Facility's supercomputer Summit, which also involve three anal-yses as part of the results necessary for scientific discovery. We discuss the challenges faced when implementing these algorithms and present an original hybrid staging technique to help enable the physicists to make discoveries during the execution of the simulation. By creating this infrastructure, we can examine complicated physics results, which may not have been possible without the infrastructure. For example, our work enables the online visualization of turbulent homoclinic tangle around the magnetic X-point, breaking the last confinement surface. This visualization could help fusion scientists to better understand and improve the turbulence spread of plasma exhaust heat, which is crucial toward realizing plasmas beyond the currently accessible physics regimes of present-day tokamak reactors. The physics of turbulent homoclinic tangle will be reported in a future physics publication, by utilizing the original online analysis/visualization framework presented in this paper.

Suchyta, Eric↗

Quantifying Uncertainty in HPC Job Queue Time Predictions

High Performance Computing (HPC) has developed at an unprecedented pace in recent decades. This growth has demanded corresponding development in the area of HPC Operational Data Analytics (ODA), which encompasses a wide range of data analysis techniques, ML/AI efforts, tools, and visualizations. Published studies in ODA offer a variety of practical ways to inform HPC users, administrators, procurement managers, and other stakeholders. Uncertainty analysis, however, is rare in the related published literature. For instance, we identify only 1 out of 14 existing studies focused on job queue time prediction that investigates the uncertainty aspect of their proposed predictions. We recognize the utmost importance uncertainty quantification can have in such predictive analytics solutions, with consequences in how users interpret information they receive, and attempt to bridge this gap. With the goal of improving access to such insights, we develop a process for determining upper and lower bounds of the predicted queue times of a regression model at a specified confidence level. Our current research is focused on the uncertainty in predicting job queue times, yet our approach may be employed in predicting other metrics.

HPC↗

Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication

There is a growing interest in custom spatial accelerators for machine learning applications. These accelerators employ a spatial array of processing elements (PEs) interacting via custom buffer hierarchies and networks-on-chip. The efficiency of these accelerators comes from employing optimized dataflow (i.e., spatial/temporal partitioning of data across the PEs and fine-grained scheduling) strategies to optimize data reuse. The focus of this work is to evaluate these accelerator architectures using a tiled general matrix-matrix multiplication (GEMM) kernel. To do so, we develop a framework that finds optimized mappings (dataflow and tile sizes) for a tiled GEMM for a given spatial accelerator and workload combination, leveraging an analytical cost model for runtime and energy. Our evaluations over five spatial accelerators demonstrate that the tiled GEMM mappings systematically generated by our framework achieve high performance on various GEMM workloads and accelerators.

43 PARTICLE ACCELERATORS↗

Data-Driven Discovery of Linear Molecular Probes with Optimal Selective Affinity for PFAS in Water

Approaches to tackle the wide and growing variety of highly persistent per- and polyfluoroalkyl substances (PFAS) are of pressing global need because of their detrimental human health effects, such as cancer, birth defects, and hormone imbalance. Sensitive, selective, and easy-to-use real-time sensors to monitor and detect PFAS and sorbents to extract them are critical to meeting government-mandated environmental concentrations. In this work, we combine all-atom molecular dynamics simulations, enhanced sampling, deep representational learning, and Bayesian optimization to perform high-throughput virtual screening for highly sensitive and selective molecular probes. Our molecular design space consists of 3850 linear hydrocarbon chains with varying degrees of halogenation with and without amine- and phosphine-based headgroups. By employing a data-driven search process, we efficiently explore the molecular design space to optimize the sensitivity to perfluorooctanesulfonic acid (PFOS) as a prototypical PFAS analyte and selectivity relative to a sodium dodecyl sulfate (SDS) interferent. We calculate 504 Gibbs free energies of probe-analyte and probe-interferent interactions and identify probes with PFOS association free energies of up to (-ΔG PFOS ) = 9.8 ± 0.2 kJ/mol and selectivities relative to SDS of (-ΔΔG PFOS–SDS ) = 3.1 ± 1.5 kJ/mol. A C 11 Br 23 P(CH 3 ) 2 probe containing 11 backbone brominated carbons and a tertiary phosphine headgroup possesses the most sensitive binding constant to PFOS within the defined search space of K b PFOS = 177.4 ± 12.7, and a semibrominated probe C 5 H 11 C 7 Br 14 N(CH 3 ) 2 containing 12 backbone carbons and a tertiary amine headgroup possesses the highest selectivity relative to SDS of K b PFOS /K b SDS = 4.6 ± 1.7. A retrospective analysis of our data to extract interpretable design rules reveals that the sensitivity of linear hydrogenated probes increases by approximately 1 kJ/mol per C–C bond. The addition or removal of halogen atoms and amine or phosphine headgroups produces nonmonotonic changes in both sensitivity and selectivity with changes to the sensitivity of up to 2.5 kJ/mol. Finally, this work places empirical limitations on the performance of a wide range of linear probes for PFOS detection and offers a generic strategy for high-throughput computational screening to promote selective and sensitive binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polymer Entrapment Flash Pyrolysis for the Preparation of Nanoscale Iridium-Free Oxygen Evolution Electrocatalysts

This paper describes the use of a new polymer entrapment flash pyrolysis (PEFP) method for making nanoscale yttrium ruthenate (Y 2 Ru 2 O 7-δ ) electrocatalysts. Here, this approach effectively reduced the synthesis temperature of phase-pure pyrochlore catalysts from 1000 °C to 550 °C, and greatly suppressed the sintering of catalyst particles. The supported nanocrystalline Y 2 Ru 2 O 7-δ catalysts showed enhanced activity towards oxygen evolution reaction (OER) in acidic electrolyte and were stable at 1.50 V for the comparative study (>20 h) under the current density of 10 mA/cm 2 geo in chronopotentiometry testing. This is equivalent to an overpotential value of 270 mV, about half of that of the reference IrO 2 catalyst. X-ray absorption spectroscopy (XAS) and transmission electron microscopy (TEM) analysis showed that the high-surface-area Y 2 Ru 2 O 7-δ catalyst had an oxygen-deficient structure. This study provides a route to the synthesis of fine ceramic (or oxide)-based electrocatalysts for making high-performing electrocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interpretable Models for Workflow Differentiation in High-Performance Scientific Networks

Scientific workflows in high-performance networks spawn hundreds of interdependent flows that must be managed collectively—yet existing network classifiers treat each flow in isolation, leading to fragmented QoS decisions and missed interflow patterns. We present a novel traffic classification solution that operates at the workflow level, distinguishing entire filetransfer operations from streaming analytics by capturing how concurrent flows interact and burst together. We introduce a workflow identification window (WIW) that ingests raw packet headers from parallel flows into unified tensors, preserving the spatial-temporal patterns that differentiate scientific workflows. This approach achieves 98.7% accuracy using CNN, LSTM, and hybrid architectures, while maintaining 84% accuracy on production traffic collected a week later—demonstrating robustness to temporal drift. By integrating SHAP and GradCAM explainability, we reveal that early-packet timing patterns and cross-flow correlations drive classification decisions, providing operators with interpretable insights. Our system enables coherent workflow-level QoS enforcement and dynamic bandwidth allocation in scientific networks, eliminating manual per-flow configuration while maintaining classification latency at millisecond level.

Giannakou, Anna [LBL, Berkeley]↗

Electron transfer calculations between edge sharing octahedra in hematite, goethite, and annite

A key reaction underlying the charge transport in iron containing oxides, clays, micas is the Fe$^{2+}$-Fe$^{3+}$ exchange reaction between edge-sharing iron octahedra. These reactions facilitate conduction in these minerals by the thermally-activated hopping of small polarons across the lattice. Depending on the mineral and local charge state the small polaron can either encase an electron or hole. The probability for conduction of small polarons depends strongly on the height and adiabicity of the reaction barrier, with larger and more diabatic barriers yielding slow conduction associated with either weak coupling or a large prerequisite rearrangement of the lattice during charge transport. To model these reactions, a first principle electron transfer (ET) method was developed to model the small polaron hopping between the edge-sharing octahedra sites in hematite ($e^{-}$ polaron), goethite ($e^{-}$ polaron), and annite ($h^{+}$ polaron) bulk structures. The ET method is based on electronic structure methods (i.e., plane-wave Density Functional Theory) capable of performing calculations with periodic cells and large size systems efficiently while at the same time being accurate enough to be used in the estimation of the electron-transfer coupling matrix element, $V_{AB}$, and the electron transfer transmission factor, $\kappa_{el}$. Additionally, the calculations confirmed the existence of small polarons in all three minerals, and the reactions were predicted to be strongly adiabatic. It was found that transfer of a hole in the octahedral layer of annite had an adiabatic barrier of $0.311$ eV, and the transfer of an extra electron in hematite and goethite had adiabatic barriers of $0.242$ eV and $0.232$ eV respectively. The electronic coupling parameters,$V_{AB}$, were found to be $0.188$ eV, $0.196$ eV, and $0.102$ eV respectively for hematite, goethite, and annite. While similar bonding topologies pertain, the underlying basis for the differences is the subtle differences in local structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗