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Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Spectroscopy and dynamics of the v = 1 levels derived from the OH(D) stretching modes in the I‾∙HDO complex using CW and time-resolved, resonant two-photon infrared excitation of the cryogenically cooled ions

The vibrational energy levels of the two isotopomers adopted by the I‾∙HDO ion-molecule complex occur such that the OH(D) stretching fundamentals span its dissociation energy, thus enabling a spectroscopic investigation of the dynamics displayed by a system prepared in the vicinity of the dissociation threshold. This regime is explored using infrared photoexcitation of the mass-selected complexes cooled in a cryogenic radiofrequency (Paul) ion trap. Survey spectra are obtained at modest resolution using two-color, IR-IR photodissociation with nanosecond lasers to establish the level structure and unimolecular decay dynamics of the v = 1 and 2 levels of the bound OH(D) oscillator. The v = 1 levels are prepared by fixed frequency excitation in the trap and the absorption spectra arising from this excited state are probed by photofragmentation of the complex with a second pulsed IR laser after a variable delay time (0 to 20 ms). The transitions to levels above the dissociation threshold for I‾ + HDO formation are observed to be sharp (~5 cm -1 FWHM). At low pressure, the bound OD (v = 1) population relaxes very slowly (~3 ms), consistent with resonant fluorescence in the IR. The collisional quenching rate constants of this level by the He buffer gas were estimated to be on the order 3 x 10 -12 cm 3 /s based on a crude Stern-Volmer analysis. Here, the rotational fine structure and linewidths (≲0.01 cm -1 FWHM) arising from transitions of the non-bonded OH stretch fundamental of the OD-bound isotopomer that lies just above the dissociation energy are determined using single photon photodissociation by excitation of the 10 K ions with a single-frequency, CW IR laser in the ion trap.

Cryogenic ion infrared spectroscopy

Low Melting Temperature Gallium–Indium Liquid Metal Anode for Solid-State Li-Ion Batteries

Solid-state Li-ion batteries are attracting attention for their enhanced safety features, higher energy density, and broader operational temperature range compared to systems based on liquid electrolytes. However, current solid-state Li-ion batteries face performance challenges, such as suboptimal cycling and poor rate capabilities, often due to inadequate interfacial contact between the solid electrolyte and electrodes. To address this issue, we incorporated a gallium–indium (Ga–In) liquid metal as the anode in a solid-state Li-ion battery setup, employing Li 6 PS 5 Cl as the solid electrolyte. Operating at room temperature, this configuration achieved an initial capacity of 389 mAh g –1 and maintained 88% of this capacity after 30 cycles at a 0.05 C rate. It also demonstrated a capacity retention of 66% after 500 cycles at a 0.5 C rate. In comparison to solid anode materials, such as tin, the Ga–In liquid metal exhibited superior cycling stability and rate capacity, which is due to the self-healing and fluid properties of the alloy that ensure stable interfacial contact with solid electrolytes. In situ X-ray diffraction (XRD) and ex situ scanning electron microscope (SEM) analyses revealed that indium does not directly participate in the lithiation/delithiation process. Instead, it helps maintain the alloy’s low melting point, facilitating its return to a liquid state after delithiation. In a comparative analysis of stack pressure during cycling in cells utilizing Ga–In liquid metal and tin, the Ga–In liquid metal cell demonstrated an ability to buffer pressure increases associated with deformation. In conclusion, these findings suggest a promising approach for enhancing solid-state batteries by integrating liquid metal anodes, which improve interfacial contact and stability.

Alloys

Electrolyte-Dependent, “Microscopically Irreversible” H-Atom Transfer Kinetics of Ce-Based Metal–Organic Framework, Ce-MOF-808

Redox reactions at the interface of metal oxides and protic electrolytes almost always involve protons and electrons in equal amounts. Given the stoichiometry, these proton-coupled electron transfer (PCET) reactions are thermochemically equivalent to net H-atom transfer (HAT) reactions. The correlation between the chemical nature of solid catalysts and HAT kinetics has been employed for decades as the design principle for energy-relevant reactions (e.g., reactions of 2H + /H 2 ). More recently, chemists have experimentally determined that a change in liquid electrolytes that alters the microenvironment at the redox-active sites has an equally profound impact on electrocatalysis involving PCET/HAT. Yet, precise correlations between the chemical nature of electrolytes and the PCET kinetics are, to date, rare in the literature. Herein, we report our findings using the Ce-based metal−organic framework, Ce-MOF-808, as a model system. Each Ce 6 (μ 3 −O) 4 (μ 3 − OH) 4 (OH) 6 (H 2 O) 6 node of this MOF undergoes a 1H + /1e − redox reaction. Using chronoamperometry and the Cottrell analysis, we have determined that the PCET hopping kinetics within the pores of Ce-MOF-808 can change by orders of magnitude by altering the buffer species and the proton activity of the electrolyte. Furthermore, in all buffers, reductive reactions were ∼3−10 times faster in kinetics than the reverse oxidative reaction with the same electrochemical driving force, suggesting that the system, at first glance, violates the principle of microscopic reversibility. Isothermal titration calorimetry (ITC) and computational simulations corroborated that the buffer-node binding thermodynamics are quite distinct, depending on the chemical nature of the buffer and the oxidation state of the node. Together, these results suggest that the substrate and the product during the oxidative vs reductive reaction of Ce-MOF-808 are chemically different species, which explains the apparent ‘microscopic irreversibility.’ Thus, the rational modulation of electrolytes can dramatically enhance PCET kinetics, even though the solid electrodes remain identical. Implications of these findings are contrasted with the electrochemical/electrocatalytic behavior of other redox-active MOFs, heterogeneous catalysts, and enzymatic systems at the solid−liquid interface.

Ce-based MOF

Evaluating inkjet dispenser/liquid vortex capture-mass spectrometry for single-cell metabolomics in Hep G2 steatosis caused by tamoxifen

Single-cell mass spectrometry (MS) is advancing our understanding of metabolic pathways in heterogeneous cell populations; however, many techniques are slow or require disruptive sample preparations. This study evaluated coupling a modified HP D100 single-cell inkjet dispenser with liquid vortex capture-mass spectrometry (D100/LVC-MS). The D100 is a single-cell inkjet dispenser capable of titrating solutions and isolating single cells via disposable cassettes equipped with microfluidic channels and an impedance sensor. The LVC-MS enables high-throughput capture, lysis, and ionization of analytes for mass spectrometric analysis. The D100/LVC-MS system was characterized through titration and single-cell experiments. Propranolol titration demonstrated linearity across a broad concentration range using the D100/LVC-MS system. Additionally, Hep G2 hepatocarcinoma cells and Chlamydomonas reinhardtii algae were used to showcase the D100’s high-throughput or low-buffer-volume single-cell dispensing strategies. The D100/LVC-MS system’s performance was validated by evaluating tamoxifen-induced steatosis in Hep G2 cells. Tamoxifen, associated with nonalcoholic fatty liver disease in breast cancer patients following long-term use, was tested in Hep G2 cells at 20 µM for 72 h against DMSO-treated controls. High-throughput analysis of 500 cells per condition, completed in 25 min per run, demonstrated the system’s efficiency. The D100/LVC-MS system simultaneously quantified tamoxifen and measured triglycerides and phosphatidylcholines. Triglycerides were upregulated in the tamoxifen-treated cells and the results indicated two distinct cell populations, differing in tamoxifen and phosphatidylcholines levels, suggesting heterogeneity within the treated population. In conclusion, these findings highlight the D100/LVC-MS system as a cost-effective, high-throughput platform for single-cell metabolomics and lipidomics, with significant potential for evaluating metabolic alterations.

Chromatography

Field-dependent carrier transport in implanted isolation region of GaN lateral power devices

Among GaN lateral power devices, with proper E-field management, the breakdown occurs in the device isolation region rather than the active region. In this paper, we investigate field-dependent carrier transport in the isolation structures. Isolation test structures with variations in buffer doping, un-intentionally doped (UID) GaN thickness, and implantation conditions were fabricated. Electrical characterization was performed over a wide range of voltage and temperature. With varying UID GaN thickness and buffer doping, the leakage current and breakdown characteristics remain the same for a specific implantation condition, indicating that the leakage conduction and breakdown are governed by the implanted GaN region. Analysis of the temperature-dependent I–V reveals that carrier transport in the implanted GaN can be well explained by hopping conduction, involving three distinctive regions of operation depending on the E-field. At low E-field, carrier transport is ohmic, consistent with variable range hopping, driven by thermal activation. At medium E-field, a field enhanced thermally activated hopping is observed, following σ ∼ σ(T)exp(E). At high E-field, activation-less hopping is visible, following σ ∼ exp(−1/E), which occurs above a critical E-field limited by localization length.

Sadek, Mansura (ORCID:0000000322588338)

Developing a media formulation to sustain ex vivo chloroplast function

Chloroplasts are critical organelles in plants and algae responsible for accumulating biomass through photosynthetic carbon fixation and cellular maintenance through metabolism in the cell. Chloroplasts are increasingly appreciated for their role in biomanufacturing, as they can produce many useful molecules, and a deeper understanding of chloroplast regulation and function would provide more insight for the biotechnological applications of these organelles. However, traditional genetic approaches to manipulate chloroplasts are slow, and generation of transgenic organisms to study their function can take weeks to months, significantly delaying the pace of research. To develop chloroplasts themselves as a quicker and more defined platform, we isolated chloroplasts from the green algae, Chlamydomonas reinhardtii, and examined their photosynthetic function after extraction. Combined with a metabolic modeling approach using flux-balance analysis, we identified key metabolic reactions essential to chloroplast function and leveraged this information into reagents that can be used in a “chloroplast media” capable of maintaining chloroplast photosynthetic function over time ex vivo compared to buffer alone. We envision this could serve as a model platform to enable more rapid design-build-test-learn cycles to study and improve chloroplast function in combination with genetic modifications and potentially as a starting point for the bottom-up design of a synthetic organelle-containing cell.

Chlamydomonas reinhardtii

Expected occurrence of wildlife in US Atlantic offshore wind areas

Offshore wind energy has entered a pivotal phase of development for the U.S. Atlantic Outer Continental Shelf (OCS), a region that supports critical habitats, migratory corridors and flyways for many marine species. Assessing where and when marine wildlife occurs is a crucial first step in developing a risk assessment framework to evaluate potential risks and impacts of offshore wind development. In this study, we perform this initial assessment by evaluating the expected occurrence of marine mammal, seabird and sea turtle taxa in areas of interest to identify patterns and potential areas of concern. Specifically, this work depicts the expected monthly density of 84 marine species and taxa within each of the 29 active wind energy lease areas plus a 10 km buffer to account for nearby activity. We then compare these densities to subregional thresholds, evaluated as the 90th percentile of the subregion’s monthly density, to provide comparisons across the shelf region. This analysis synthesizes the most recent spatial distribution models of 31 marine mammal taxa (26 species and 5 guilds), 49 seabird species and 4 sea turtle species to provide a unified evaluation of the major marine wildlife in the region. Out of the 84 species and taxa analyzed, 56 exhibit levels of expected density in wind energy areas that exceed the corresponding 90th percentile subregional threshold at some point throughout the year. These results represent an initial assessment in the broader Occurrence, Exposure, Response, and Consequence (OERC) framework, originally developed by the U.S. Navy for marine species risk assessments. These results offer valuable guidance to marine spatial planners, management agencies and offshore wind developers on the expected locations and timing of interaction risk to wildlife species in or near wind energy areas across the region.

17 WIND ENERGY

Machine learning enhanced characterization and optimization of photonic cured MAPbI 3 for efficient perovskite solar cells

Photonic curing (PC) can facilitate high-speed perovskite solar cell (PSC) manufacturing because it uses high-intensity light pulses to crystallize perovskite films in milliseconds. However, optimizing PC conditions is challenging due to its many variables, and using power conversion efficiency (PCE) as the optimization metric is both time-consuming and labor-intensive. This work presents a machine learning (ML) approach to optimize PC conditions for fabricating methylammonium lead iodide (MAPbI 3 ) films by quantitatively comparing their ultraviolet-visible (UV-vis) absorbance spectra to thermal annealed (TA) films using four similarity metrics. We perform Bayesian optimization coupled with Gaussian process regression (BO-GP) to minimize the similarity metrics. Refining PC conditions using active learning based on BO-GP models, we achieve a PC MAPbI3 film with an absorbance spectrum closely matching a TA reference film, which is further verified by its crystalline and morphological properties. Thus, we demonstrate that the UV-vis absorption spectrum can accurately proxy film quality. Additionally, we use an AI-based segmentation model for a more efficient grain size analysis. However, when we use the optimized PC condition to fabricate PSCs, we find that interaction between MAPbI 3 and the hole transport layer (HTL) during PC critically degrades the PSC performance. By adding a buffer layer between the HTL and MAPbI 3 , the optimized PC PSCs produce a champion PCE of 11.8%, comparable to the TA reference of 11.7%. Using UV-vis similarity metrics instead of device PCE as the objective in our BO-GP method accelerates the optimization of PC processing conditions for MAPbI 3 films.

14 SOLAR ENERGY

Functionalized Metal–Organic Framework Thin Films for Stable and Efficient Electrochemical Water Oxidation under Near-Neutral Conditions

The development of molecularly modified metal− organic frameworks (MOFs) for electrochemical water oxidation has emerged as a promising strategy for efficient artificial photosynthesis. In this study, a ruthenium-based water oxidation catalyst (WOC) was incorporated into the UiO-67 framework, forming RuM−UiO-67 films grown directly on conductive FTO substrates. These modified films demonstrate efficient water oxidation activity at near-neutral pH (pH 6), operating at a low overpotential of ∼600 mV. The catalyst exhibits a turnover frequency (TOF) of (0.32 ± 0.02) s −1 at 1.5 V versus the normal hydrogen electrode (NHE) in buffered solution (pH 6) for the oxygen evolution reaction. Notably, incorporation into the MOF results in a 12-fold increase in electroactive surface coverage compared to a monolayer of the same catalyst on bare FTO. Faradaic efficiency analysis revealed incomplete conversion to O 2 , and follow-up iodometric analysis confirmed the formation of H 2 O 2 as a competing two-electron oxidation product during electrocatalysis. These results highlight the utility of MOF-based architectures for maximizing the catalyst accessibility and stability under electrochemical water oxidation conditions.

catalysts

Trade can buffer climate-induced risks and volatilities in crop supply

Climate change is intensifying the frequency and severity of extreme events, posing challenges to food security. Corn, a staple crop for billions, is particularly vulnerable to heat stress, a primary driver of yield variability. While many studies have examined climate impact on average corn yields, little attention has been given to the climate impact on production volatility. This study investigates the future volatility and risks associated with global corn supply under climate change, evaluating the potential benefits of two key adaptation strategies: irrigation and market integration. A statistical model is employed to estimate corn yield response to heat stress and utilize NEX-GDDP-CMIP6 climate data to project future production volatility and risks of substantial yield losses. Three metrics are introduced to quantify these risks: Sigma (σ), the standard deviation of year-on-year yield change, which reflects overall yield volatility; Rho (ρ), the risk of substantial loss, defined as the probability of yield falling below a critical threshold; and Beta (β), a relative risk coefficient that captures the volatility of a region's corn production compared to the globally integrated market. The analysis reveals a concerning trend of increasing year-on-year yield volatility (σ) across most regions and climate models. This volatility increase is significant for key corn-producing regions like Brazil and the United States. While irrigated corn production exhibits a smaller rise in volatility, suggesting irrigation as a potential buffer against climate change impacts, it is not a sustainable option as it can cause groundwater depletion. On the other hand, global market integration reduces overall volatility and market risks significantly with less sustainability concerns. Furthermore, these findings highlight the importance of a multidimensional approach to adaptation in the food sector. While irrigation can benefit individual farmers, promoting global market integration offers a broader solution for fostering resilience and sustainability across the entire food system.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Evaluation of desiccation cracking characteristics of inorganic micro-fiber-reinforced engineered barrier material (IMEBM) for geological repository

Abstract Buffer material is crucial for the engineering barrier system to dispose of high-level radioactive waste in a geological repository. A reliable buffer material should be able to maintain good sealing characteristics and minimize desiccation cracking. In this study, the effectiveness of inorganic fiber-reinforced engineering barrier material in reducing desiccation cracks in bentonite was evaluated via desiccation tests, image analysis, and air permeability tests. The effects of fiber type (E-glass fiber and basalt fiber) and fiber content (0.0%, 0.5%, 1.0%, 1.5%, 3.0%, and 5.0% of dry weight of the bentonite) on the development of desiccation cracks in the fiber–bentonite mixtures with the same given initial moisture content were evaluated. The results indicated that the addition of fibers could significantly reduce the crack size and area in bentonite during the drying. Basalt fibers showed a slightly better reinforcement effect than E-glass fibers when the fiber content was lower than 3.0%. The addition of fibers prevented the development of penetrating cracks and significantly reduced the permeability of the bentonite after drying. The permeabilities of basalt fiber- and E-glass fiber-reinforced bentonite composites with 3% reinforcement were 5.81 × 10 –11 m 2 and 7.24 × 10 –11 m 2 , respectively, which were 64 and 51 times smaller than that of pure bentonite. X-ray–CT observation of the internal structure of the samples after drying showed that the addition of fibers significantly changed the crack morphology and potentially increased the tortuosity.

Feng, Yuan

Cathode-Confined Polysulfide Retention-Release Reprograms Li 2 S Deposition in High-Loading Li–S Batteries

High-loading lithium-sulfur (Li-S) cells operated with lean electrolyte are limited by polysulfide crossover to Li metal and by transport-limited liquid-solid conversion that forms passivating Li 2 S films. Here, we show that a cathode-facing separator coating of carboxylated multiwalled carbon nanotubes acts as a cathode-confined polysulfide reservoir with intermediate binding. Early in discharge it captures newly generated polysulfides at the separator interface, suppressing shuttle reactions. As polysulfides are consumed, the reservoir buffers concentration gradients and feeds reactants back to the cathode, shifting Li 2 S deposition from burst-like film growth to progressive, three-dimensional, porous formation. Synchrotron XRD and S K-edge XANES, together with Scharifker–Hills nucleation analysis and depth-of-discharge EIS/DRT, substantiate this coupled transport–reaction control. With 4.3 mg S cm -2 and E/S = 5, cells reach 4.2 mAh cm -2 and retain 90% capacity over 100 cycles at 20 °C.

25 ENERGY STORAGE

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 1. Characterizing Thermal–Hydrological–Mechanical Processes

Abstract Bentonite clay is widely used in engineered barrier systems for the permanent disposal of high‐level radioactive waste due to its low permeability, high swelling capacity, and thermal stability. However, the complex thermal‐hydrological‐mechanical (THM) processes induced by heating from decaying radioactive waste and hydration from surrounding rock can lead to heterogeneous changes that are difficult to measure and predict. This study develops an Electrical Resistivity Tomography (ERT)‐based framework for monitoring THM processes, progressing from sample‐scale to bench‐scale tests, to inform field‐scale applications. Sample‐scale tests analyzed small bentonite samples under controlled variations in water content, temperature, and porosity to establish fundamental resistivity relationships. Bench‐scale tests involved larger bentonite columns subjected to heating (up to 200°C) and hydration under controlled pressure, simulating repository conditions. ERT measurements, complemented by X‐ray CT imaging, temperature monitoring, and tracing sensors, revealed coupled THM processes, such as hydration‐induced compression, swelling, and thermal gradients, leading to complex resistivity patterns. The results demonstrate the potential of ERT for capturing THM‐induced resistivity changes, though challenges remain in upscaling and quantitative analysis. This study evaluates laboratory test capabilities and proposes future improvements for understanding THM‐induced resistivity responses. A conceptual framework for ERT implementation in field‐scale monitoring is presented, synthesizing findings from both scales and exploring how ERT data can inform long‐term modeling and reduce prediction uncertainties. Overall, this ERT‐based framework offers a robust method for monitoring bentonite buffers, aiding in early issue detection and supporting the safe long‐term disposal of radioactive waste in geological repositories, while highlighting the need for future development. Plain Language Summary Bentonite clay is crucial in engineered barrier systems (EBS) for containing high‐level radioactive waste due to its ability to absorb water, swell, seal and remain stable under high temperatures. When bentonite absorbs water and heats up from radioactive decay, it experiences complex changes in its physical and mechanical properties. Understanding these changes is important for ensuring the long‐term safety and effectiveness of EBS. This study used Electrical Resistivity Tomography (ERT), a non‐invasive method that measures electrical conductivity to monitor these changes during laboratory experiments. The ERT data revealed significant variations in resistivity corresponding to changes in water content, temperature, and density, providing detailed spatial and temporal insights into the behavior of bentonite. These findings enhance our ability to predict the long‐term performance of bentonite barriers, ensuring the safe containment of radioactive waste. By improving our understanding of bentonite's behavior, this research supports the development of more reliable and effective barrier systems for radioactive waste disposal, protecting the environment and public health. Key Points ERT monitoring was employed to capture resistivity changes in bentonite during controlled heating and hydration experiments, providing insights into THM processes ERT data reveal significant resistivity changes correlated with water content, temperature, and mechanical effects, enhancing the understanding of THM dynamics in bentonite This study explores the potential of the framework for application in field‐scale EBS monitoring, emphasizing the need for integrating additional geophysical methods for comprehensive subsurface imaging

Chen, Hang

Archive of AGR-5/6/7 Particle Radiographs for Identification of Particles with Defective IPyC

As a part of fuel quality control characterization, 2D radiographs of large numbers of particles produced by the Advanced Gas Reactor Fuel Development and Qualification (AGR) Program’s AGR-5/6/7 irradiation were acquired. These radiographs were used for the identification of particles with excessive uranium dispersion from the kernel into the surrounding buffer layer caused by chlorine infiltration through a defective inner pyrolytic carbon (IPyC) layer during silicon carbide (SiC) deposition. Additional features of interest associated with fabrication anomalies were also catalogued. Raw radiography images, along with the noted defective IPyC defects found by analysis at Oak Ridge National Laboratory are reported herein.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Structural and Electronic Complexities of a Sulfur‐Bridged Di‐Iron Complex Composed of Mono‐ and Di‐Nitrosyl Units

The delocalized, thermodynamically stable cation, [(N 2 S 2 )Fe(NO)•Fe(NO) 2 ] + , an adduct of mono-nitrosyl and dinitrosyl iron units, is analyzed to address the unusual stability of the sulfur-bridged diiron complex in its three overall redox levels, +, 0, and −. X-ray diffraction and myriad spectroscopic techniques probe products of sequential electron uptake in the corresponding neutral and anionic species. Conundrums include unified blueshifts of the overall 3-band, ν(NO), pattern with added electrons. One-electron reduction changes the anti-ferromagnetically coupled, S = 0, cationic diiron species to the neutral analog, S = ½, with unpaired spin mainly localized on the MNIU, which decreases its ∠Fe–N–O angle by 10 degrees in response to the extra electron density. Subsequent reduction to the anionic species, S = 1, involves a major geometric change at the MNIU, which moves the Fe in {Fe(NO)} 8 out of the N 2 S 2 plane. Site-specific 15 N labeling of nitrosyl in the MNIU confirms the IR analysis and shows rapid NO exchange between the MNIU/DNIU (mono-nitrosyl iron unit/dinitrosyl iron unit) pairs during its synthesis at RT. Mössbauer spectroscopy, S K-edge XAS, and molecular orbital calculations confirm the ability of NO and the versatility of sulfur bridges to buffer and distribute electrons, a key to their major importance in metalloenzymes.

DNIC

Comparing Liquid Vortex Capture & the Rapid Droplet Sampling Interface for Single Cell Mass Spectrometry

High-throughput single-cell mass spectrometry is a rapidly evolving field that requires innovative sampling and ionization techniques to balance speed, sensitivity, and reliability for metabolomic and lipidomic analyses. This study provides a comparative analysis of two cutting-edge ionization platforms for single-cell analysis: Liquid Vortex Capture (LVC) and Rapid Droplet Sampling Interface (RDSI). The performance was benchmarked by testing pharmaceuticals, EquiSPLASH, and single-cell experiments. RDSI demonstrated up to 100-fold improvements in sensitivity for drugs and lipids such as propranolol, amiodarone, atorvastatin, and phosphocholines in water and phosphate-buffered solutions. This was attributed to its low-flow rate operation (3 μL/min) and reduced dilution. Conversely, LVC excelled in handling higher liquid volumes with greater reproducibility due to its higher solvent flow rate (200 μL/min), enabling increased dilution, solubility, and cleaning. Single-cell uptake of atorvastatin incubated for 10 min, or amiodarone incubated for 24 h in HepG2 cells, similarly revealed up to 85-fold enhancement in sensitivity by RDSI for drugs and lipids. These findings highlight the potential of RDSI for enhancing sensitivity in single-cell drug monitoring and lipidomics.

Cahill, John [ORNL] (ORCID:0000000298664010)

Machine Learning-Based Extreme Data Reduction for Prompt Supernova Pointing at DUNE

One of the goals of the Deep Underground Neutrino Experiment (DUNE) is to use the massive underground liquid argon time projection chamber (LArTPC) detectors at its far site for multimessenger astronomy (MMA), in the detection of neutrinos from core-collapse supernovae (SNe). Its current baseline trigger strategy detects activity in the detector that is consistent with supernova (SN) neutrinos and saves the raw data for further offline analysis but provides no prompt pointing information crucial for optical follow-ups by other observatories. This approach is based on the assumption that prompt pointing determination using raw data is computationally prohibitive. In this article, we demonstrate a proof-of-concept based on applying extreme data reduction on the buffered SN data in the DUNE data acquisition (DAQ) system’s front-end computers using a machine learning (ML) workflow. This reduces the data by ~5 orders of magnitude, allowing a full track reconstruction to be carried out quickly on a single server. The total time to perform the ML-based data reduction and the full track reconstruction is less than the time to transfer the SN data back to Fermilab or a high-performance computing (HPC) center. This shows that prompt processing of raw SN data is possible and, in fact, trivial once the data have been reduced to reject radiological backgrounds, paving the way to a high-quality SN pointing trigger that is based on fully reconstructed data instead of trigger primitives (TPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND