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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Preliminary Look at the LBEG & MPEG Beam Transmissions between HPSim and Operation Data

This report summarizes recent work on estimating the transmission of LANSCE H- beams from the end of the present DTL to both the PSR stripper foil (LBEG) and WNR target 4 (MPEG). The LBEG beam might be considered a more typical LINAC beam and lends itself to continuous monitoring of transmission through the various stages of the accelerator. For the MPEG, however, the widely-spaced micropulses and lack of the requisite sensitivity current monitors throughout the accelerator make these measurements extremely difficult and more uncertain. Therefore, to assist in estimating the MPEG beam transmission, beam-dynamics simulations using HPSim were employed. These beam transmission estimates from the end of the Drift Tube Linac (DTL) to Target 4 (MPEG) and the PSR stripper foil (LBEG) are vital to determine the charge requirements for LAMP’s front end. In this technote, we demonstrate three major efforts in determining the transmission: (1) Convert the WNR beamline lattice from TRANSPORT to HPSim for use in the simulation; (2) Simulate the optimization process in the Central Control Room (CCR) that brings down the losses by up to a factor of 4000 between the end of the initial physics-based tuneup phase and production beam operation; (3) Analyze operational data to deduce measured transmissions. Table 1 shows the estimated losses with HPSim and operational analysis. Finally, a better measurement and other improvements to refine the results are also proposed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Integration and performance of large area picosecond photodetectors in the accelerator neutrino neutron interaction experiment

ANNIE, the Accelerator Neutrino Neutron Interaction Experiment, is a 26-ton Gadolinium-loaded water Cherenkov detector located at the Booster Neutrino beam line at Fermilab to mainly measure neutron multiplicity of neutrino interactions and test the performance of Large Area Picosecond Photodetectors (LAPPD). This thesis presents the integration of LAPPD at ANNIE and the preliminary performance analysis. LAPPDs achieved 2.48ns bunch structure resolution, even considering the time of flight and the intrinsic bunch width. The analysis also achieves better than 100ps intrinsic timing resolution, sub-mm position resolution for a single photoelectron, and cm-level resolution in conditional muon track reconstruction.

Feng, Yue [Iowa State U.] (ORCID:0000000332021351)↗
DOE OSTI2024

Refining HPCToolkit for application performance analysis at exascale

As part of the US Department of Energy’s Exascale Computing Project (ECP), Rice University has been refining its HPCToolkit performance tools to better support measurement and analysis of applications executing on exascale supercomputers. To efficiently collect performance measurements of GPU-accelerated applications, HPCToolkit employs novel non-blocking data structures to communicate performance measurements between tool threads and application threads. To attribute performance information in detail to source lines, loop nests, and inlined call chains, HPCToolkit performs parallel analysis of large CPU and GPU binaries involved in the execution of an exascale application to rapidly recover mappings between machine instructions and source code. To analyze terabytes of performance measurements gathered during executions at exascale, HPCToolkit employs distributed-memory parallelism, multithreading, sparse data structures, and out-of-core streaming analysis algorithms. To support interactive exploration of profiles up to terabytes in size, HPCToolkit’s hpcviewer graphical user interface uses out-of-core methods to visualize performance data. The result of these efforts is that HPCToolkit now supports collection, analysis, and presentation of profiles and traces of GPU-accelerated applications at exascale. These improvements have enabled HPCToolkit to efficiently measure, analyze and explore terabytes of performance data for executions using as many as 64K MPI ranks and 64K GPU tiles on ORNL’s Frontier supercomputer. HPCToolkit’s support for measurement and analysis of GPU-accelerated applications has been employed to study a collection of open-science applications developed as part of ECP. This paper reports on these experiences, which provided insight into opportunities for tuning applications, strengths and weaknesses of HPCToolkit itself, as well as unexpected behaviors in executions at exascale.

Adhianto, Laksono↗
DOE OSTI2024

Analyzing the impact of design factors on solar module thermomechanical durability using interpretable machine learning techniques

Solar modules in utility-scale systems are expected to maintain decades of lifetime to rival conventional energy sources. However, cyclic thermomechanical loading often degrades their long-term performance, highlighting the importance of effective design to mitigate thermal expansion mismatches between module materials. Given the complex composition of solar modules, isolating the impact of individual components on overall durability remains a challenging task. In this work, we analyze a comprehensive data set that comprises bill-of-materials (BOM) and thermal cycling power loss from 251 distinct module designs to identify the predominant design factors and their impacts on the thermomechanical durability of modules. The methodology of our analysis combines machine learning modeling (random forest) and Shapley additive explanation (SHAP) to correlate design factors with power loss and interpret the model’s decision-making. The interpretation reveals that silicon type (monocrystalline or polycrystalline), encapsulant thickness, busbar numbers, and wafer thickness predominantly influence the degradation. With lower power loss of around 0.6% on average in the SHAP analysis, monocrystalline cells present better durability than polycrystalline cells. This finding is further substantiated by statistical testing on our raw data set. The SHAP analysis also demonstrates that while thicker encapsulants lead to reduced power loss, further increasing their thickness over around 0.6 to 0.7 mm does not yield additional benefits, particularly for the front side one. In addition, other important BOM features such as the number of busbars are analyzed. This study provides a blueprint for utilizing explainable machine learning techniques in a complex material system and can potentially guide future research on optimizing the design of solar modules.

14 SOLAR ENERGY↗
DOE OSTI2024

A Review of the Lawrence Livermore Nuclear Accident Dosimeter 1980s-present

A Nuclear Accident Dosimetry program is a federal requirement for all facilities that have the potential to have a criticality accident. Personnel Nuclear Accident Dosimeter (PNAD) theory and analytical procedures are driven by various scientific needs and interacting regulations. A brief history of the status of USA Department of Energy (DOE) nuclear accident dosimetry regulations, recommendations, and performance testing criteria are given. Then, the history of the Lawrence Livermore National Laboratory (LLNL) PNAD is explored, including changes in the physical dosimeter and adjustments of the analysis method through the last four decades. Finally, the performance of LLNL’s PNAD at criticality accident intercomparison training exercises since 2009 is explored. In general, reported neutron doses have been within or close to DOE-STD-1098 performance criteria while reported gamma doses have been outside of DOE-STD-1098 performance criteria. Reported total absorbed doses have varied in meeting ANSI/HPS N13.3 and ANSI/HPS N13.3 (R2019) performance criteria. Dosimetry staff retirement and turnover have left historical knowledge gaps, yet provided opportunities within the NAD program at LLNL. This review paper serves as an overview of the history and status of the NAD program. Brief technical, procedural and programmatic recommendations to improve LLNL’s NAD program are given. Technical recommendations include investigating orientation factors through modeling or empirical experimentation, investigating gamma dosimetry methods for high-dose scenarios, and exploring other dosimetric methods for simpler, quicker NAD analysis. Procedural recommendations include better documentation of conversion factor (activity-to-fluence and fluence-to-dose) derivations and spectrum uses, and updated analysis spreadsheets or simple Graphic User Interfaces for dose calculations. In conclusion, programmatic recommendations include formalized training for NAD analysts, and having multiple SMEs trained on the NAD program.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Core-Shell Oxidative Aromatization Catalysts for Single Step Liquefaction of Distributed Shale Gas (Final Technical Report)

The objective of this project was to design and demonstrate a core-shell structured multifunctional catalyst to convert the light (dry) components of shale gas into liquid aromatic compounds (primarily benzene and toluene) in a single step. Operated in a modular oxidative aromatization system (OAS) under a cyclic redox scheme, the novel catalyst and process can significantly improve the value and transportability of distributed shale gas. Since the project started, each quarter addressed a different set of tasks related to the completion of the milestone detailed in the project award. The yearly summaries of these tasks are summarized below: Q1-Q4: • Conducted project planning and literature search. • Investigated a number of SHC redox catalysts using thermogravimetric analysis and fixed-bed reactor experiments. • Initiated process modeling towards generating two process models for the methane DHA base case and OAS process. • Developed DHA catalysts capable of producing >500 g/kg-cat-hr aromatics at 80% or greater aromatics selectivity at 700°C. Q5-Q8: • Developed alternative approaches with sequential bed configurations to enhance the aromatic yields based on OCM+DHA • Improved the zeolite synthesis efficiency by using the microwave-assisted technique and investigated the synthesis conditions on the zeolite yield, crystalline structure and morphology • Constructed a set of Aspen Plus process models with significant energy savings for OAS as compared to the base case non-oxidative DHA. • Adapted conventional hydrothermal method to be applicable to the microwave synthesizer unit for more efficient catalyst synthesis. • Studied the structure of the OCM catalyst and the dispersion of the carbonate in the redox reactions and in methane flow with Raman Spectroscopy. Q9-Q12: • Scaled up the catalyst synthesis with the microwave synthesis method. Based on its performance, procedural characterizations and catalytic performance testing were further conducted for the new microwave synthesized catalysts with the newly-developed product analysis procedure. • Developed the reaction system setup for the C2-DHA or OCM+DHA reaction product and achieved a better product collection-analysis method for the aromatic products with an improved carbon balance. The product from the OCM reaction exhibited complicated effects on the DHA catalyst. • Conducted additional OCM catalyst characterization using Near Ambient Pressure X-ray Photoelectron Spectroscopy and in situ Raman characterization • Validated the significant energy savings for OAS as compared to the base case non-oxidative DHA. Successfully set up the simulation model for the OCM+DHA+SHC reaction system based on the updated experimental results from NCSU. Q13-End of project: • Synthesized new zeolite catalysts by the microwave method, conducted characterizations (XRD, SEM, and TEM) and catalytic behavior testing. • Explored the “wet” C 2 H 6 and C 2 H 4 DHA reactions with using steam co-feed. A subsequent reduction as the regeneration step can regenerate the DHA catalyst and recover 99% activity of the fresh performance. • Achieved a 15.3% single-pass aromatic yield from methane by rationally combining the OCM and DHA at different temperatures. • Conducted a 105-hour stability test with an improved regeneration procedure, with an average aromatic yield of 13.8%. • Developed new catalyst and achieved a record-high 23.2% yield.

03 NATURAL GAS↗
DOE OSTI2026

A Probabilistic Approach to Load Modeling for Central HVAC Systems in Large Commercial Buildings for Retrofit Decisions Under Uncertainty

Retrofitting central HVAC systems in large commercial buildings with advanced technologies like heat recovery chillers (HRCs) offers a significant opportunity to enhance energy efficiency. However, analyzing these retrofits is challenging with traditional whole-building simulation tools, which require intensive calibration and struggle to model innovative system configurations and controls. To overcome these limitations, this study proposes a load profilebased retrofit analysis framework that provides better decisions under uncertainty. The main focus of this paper is the development of a probabilistic load profile model that can be used in the framework by using exploratory data analysis (EDA) of measured building data to properly quantify its inherent variability. A non-parametric Gaussian Process (GP) model was employed to capture the time- and weather-dependent characteristics of the heating load while explicitly modeling its uncertainty. The model's effectiveness is demonstrated through strong predictive performance on unseen data and physically interpretable insights into load behavior. This data-driven, probabilistic load profile serves as a robust and flexible input for subsequent system simulations, enabling a more confident and statistically sound analysis of retrofit potential.

Ham, S W↗
DOE OSTI2025

SEAFORML (Smart Exploration and Analysis For Optimal and Robust Machine Learning)

The poster discusses data analysis of the WAVgraph database and applied machine learning methods for it. The database is a long-term project that seeks to be a comprehensive repository of information on cyber threats and is updated regularly. It was previously unanalyzed and unexplored. The goal was to learn more about it and its contents in order to have a better understanding and enable better use. The data analysis and discovery enabled further exploration through natural language processing, similarity, and clustering methods. The poster shows some of the insights from the analysis and explains the methods used for the machine learning applications.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection

Abstract Background Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as difficult-to-treat breast cancers (DTBC). This study aims to delineate the proteogenomic landscape of DTBC tumors compared to luminal A (LumA) tumors. Methods We retrospectively collected a total of 117 untreated primary breast tumor specimens, focusing on DTBC subtypes. Breast tumors were processed by laser microdissection (LMD) to enrich tumor cells. DNA, RNA, and protein were simultaneously extracted from each tumor preparation, followed by whole genome sequencing, paired-end RNA sequencing, global proteomics and phosphoproteomics. Differential feature analysis, pathway analysis and survival analysis were performed to better understand DTBC and investigate biomarkers. Results We observed distinct variations in gene mutations, structural variations, and chromosomal alterations between DTBC and LumA breast tumors. DTBC tumors predominantly had more mutations inTP53,PLXNB3, Zinc finger genes, and fewer mutations inSDC2,CDH1,PIK3CA,SVIL, andPTEN. Notably, Cytoband 1q21, which contains numerous cell proliferation-related genes, was significantly amplified in the DTBC tumors. LMD successfully minimized stromal components and increased RNA–protein concordance, as evidenced by stromal score comparisons and proteomic analysis. Distinct DTBC and LumA-enriched clusters were observed by proteomic and phosphoproteomic clustering analysis, some with survival differences. Phosphoproteomics identified two distinct phosphoproteomic profiles for high relapse-risk and low relapse-risk basal-like tumors, involving several genes known to be associated with breast cancer oncogenesis and progression, includingKIAA1522,DCK,FOXO3,MYO9B,ARID1A,EPRS,ZC3HAV1, andRBM14. Lastly, an integrated pathway analysis of multi-omics data highlighted a robust enrichment of proliferation pathways in DTBC tumors. Conclusions This study provides an integrated proteogenomic characterization of DTBC vs LumA with tumor cells enriched through laser microdissection. We identified many common features of DTBC tumors and the phosphopeptides that could serve as potential biomarkers for high/low relapse-risk basal-like BC and possibly guide treatment selections.

Oncology↗
DOE OSTI2024

Performance and economic viability assessment of a novel CO 2 adsorbent for manufacturing and integration with coal power plants

Here, this study assesses the performance and economic feasibility of a novel CO 2 adsorbent for post-combustion capture in DOE/NETL’s 650 MWnet SubC PC power plant (case B11B). Bench-scale tests showed an initial adsorption capacity of 16.3 wt%, which decreased to 12.1 wt% after 41 adsorption–desorption cycles due to induced particle aggregation by over-humidification. With a conservative adsorption capacity of 8.8 wt% and 695 adsorption–desorption cycles, an adsorbent replenishment rate of 10 tonnes/h is necessary to capture 90% of CO 2 . The breakeven sale price of the adsorbent produced at this rate is $\$$1,293/tonne, which is 40 to 80 times lower than prices for K 2 CO 3 adsorbents reported in the literature (e.g., K 2 CO 3 /TiO 2 , K 2 CO 3 /ZrO 2 ) while providing better capture performances. Sensitivity analysis reveals that increasing the plant production rate from 10 to 40 tonnes/h reduces the sale price by 8%. The study also compares the CO 2 capture cost to Cansolv, an integrated solvent-based technology. The novel adsorbent requires 2.4 GJ/tonne of CO 2 for regeneration, lower than Cansolv’s 2.7 GJ/tonne. With conservative performance estimates, the capture cost is $\$$54/tonne of CO 2 , slightly higher than Cansolv’s $\$$45/tonne. To achieve lower or comparable capture costs to Cansolv, the adsorbent should meet one of the following conditions at a commercial scale: minimum 950 cycles, 16 wt% capture capacity, 50% of the adsorbent recovery, or a reduced cost to $\$$646/tonne by upscaling the manufactury to 75 tonnes/h.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Isotope-dependent Tafel analysis probes proton transfer kinetics during electrocatalytic water splitting

Proton transfer plays an important role in both hydrogen and oxygen evolution reactions during electrocatalytic water splitting to produce green hydrogen. However, directly adapting the conventional proton/deuterium kinetic isotope effect to study proton transfer in heterogeneous electrocatalytic processes is challenging. Here we propose using the shift in the Tafel slope between protic and deuteric electrolytes, or the Tafel slope isotope effect, as an effective probe of proton transfer characteristics. Comparison of the Tafel slope isotope effect for diverse hydrogen and oxygen evolution reaction electrocatalysts in different pH environments reveals that proton transfer is both pH and structure dependent. Using ruthenium oxide as an example, we show that local structure modification can change the rate-determining step from an electrochemical, concerted proton–electron transfer step to a chemical step and improve the oxygen evolution activity in acid. The isotope-dependent Tafel analysis will facilitate a better understanding of the proton transfer behaviours during electrocatalytic processes and provide guidance for designing efficient electrocatalysts.

Chemistry↗
DOE OSTI2024

Creep Degradation of Austenitic Steels in CO2 Environments

Steels have a proven track record of safe operation in steam power plants for decades. Interest in developing supercritical CO2 power cycles as a more efficient and sustainable alternative to steam cycles has driven a need to understand steel performance in these new environments. In particular, the potential of the high temperature CO2 environment to influence the creep behavior of the steel must be determined. Prior research on this topic between the 1960s and 1980s found conflicting conclusions, but nevertheless raised the possibility that carburization during CO2 exposure may strongly affect the creep behavior. This raises concerns particularly for thin-sectioned components such as compact heat exchangers, where even small rates of carburization can become problematic over long operating lifetimes. To shed light on this issue, this research investigates the creep behavior of austenitic stainless steel 347H and 309H (a higher Cr alternative) at 650°C. Specimens of 0.5, 1.0, and 2.0 mm thickness were tested to further assess the effect of steel thickness. Both steels show a reduction in creep life in CO2 relative to air, with 309H showing slightly better performance than 374H. Analysis is ongoing to determine the reason for degraded creep properties.

Rozman, Kyle A.↗
DOE OSTI2026

Improving Performance via Energy Efficiency JUSTIFI: Open-Source Software for Identifying and Quantifying Non-Energy Benefits

Energy efficiency is pivotal to achieving operational excellence, as it enhances value while reducing waste. This presentation explores the integration of non-energy benefits (NEBs) into energy efficiency projects, which can lead to risk reduction, value creation, and cost savings. By quantifying NEBs - such as improved safety, decreased pollution, and increased productivity - companies can strengthen their business cases for energy investments, ultimately improving payback periods and aligning with strategic goals. Designed for a diverse audience, from trained auditors to novices in energy assessments, we have developed open-source software called JUSTIFI, NEB finding methodology, and training materials which build on existing frameworks and leverages resources from the U.S. Department of Energy and Better Plants energy system analysis software suite such as MEASUR. This work aims to maximize ROI through NEB identification, utilizing tools like JUSTIFI and the NEBs Discovery Protocol.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Creep behavior of austenitic steels in CO2 and the effect of specimen thickness

Steels have a proven track record of safe operation in steam power plants for decades. Interest in developing supercritical CO2 power cycles as a more efficient and sustainable alternative to steam cycles has driven a need to understand steel performance in these new environments. In particular, the potential of the high temperature CO2 environment to influence the creep behavior of the steel must be determined. Prior research on this topic between the 1960s and 1980s found conflicting conclusions, but nevertheless raised the possibility that carburization during CO2 exposure may strongly affect the creep behavior. This raises concerns particularly for thin-sectioned components such as compact heat exchangers, where even small rates of carburization can become problematic over long operating lifetimes. To shed light on this issue, this research investigates the creep behavior of austenitic stainless steel 347H and 309H (a higher Cr alternative) at 650°C. Specimens of 0.5, 1.0, and 2.0 mm thickness were tested to further assess the effect of steel thickness. Both steels show a reduction in creep life in CO2 relative to air, with 309H showing slightly better performance than 374H. Analysis is ongoing to determine the reason for degraded creep properties.

Rozman, Kyle A.↗
DOE OSTI2024

Negative Medium-Voltage Direct Current Discharges in Air under Simulated Sub-Atmospheric Pressures for All-Electric Aircraft

The increase in the global temperature due to greenhouse gas emissions is a major concern to the world. To achieve the goal of zero emissions by 2050 in the USA the practical realization of all-electric vehicles, particularly all-electric aircraft (AEA), is important. For the design of electrical power systems (EPSs) in all-electric aircraft, a bipolar medium-voltage direct current (MVDC) system of ±5 kV is being investigated. However, several challenges manifest when using such voltages in a low-pressure environment. One of the main challenges is the partial discharge (PD) behavior of the insulation. It is important to study the PD behavior of the insulation by simulating the aviation environment in the lab. This work aimed to study the partial discharge behavior of air under a negative DC voltage in a needle-to-plane electrode geometry by simulating the aviation pressures in the lab. The partial discharge inception voltage (PDIV) and the breakdown voltage (BDV) show an obvious pressure-dependent variation. Regression analysis was performed to better understand the relationship between the PDIV and pressures. Plots were drawn for the average discharge current at each voltage step until breakdown. This paper’s findings can provide valuable insight into the design of EPS for an AEA. To the best of our knowledge, such a study has not been carried out to date.

air discharge↗
DOE OSTI2025

Examples of X-Ray Characterization Techniques in Energy Storage Research

Lithium-ion batteries have revolutionized the portable electronics and transportation sectors. Their performance is often critically dependent on the crystal structures of the anode and cathode electrode materials, which must enable the transport and reversible storage of lithium ions into and out of the lattice. Because lithium is a low-Z element, characterization of materials for lithium-ion batteries can be particularly challenging. Regardless, X-ray techniques enable analysis of material structures to better understand how battery materials perform and degrade, particularly when combined with other materials characterization and electrochemical characterization techniques. While X-ray techniques are most often used in battery research for phase identification of crystal structures, X-ray characterization techniques are also used for a wide variety of other purposes. I will discuss several examples from my research with various collaborators on several projects that highlight the impact that X-ray characterization techniques can have on battery research. The first example will focus on low-temperature microwave-assisted solvothermal synthesis of vanadium-doped LiFePO4 cathode materials for lithium-ion batteries. (1,2) Through a combination of electrochemical and materials characterization, we determined that low temperature synthesis resulted in metastable phases that enabled incorporation of higher dopant levels than resulting from high-temperature synthesis of thermodynamically stable phases. Rietveld refinement of X-ray diffraction data enabled understanding of how lattice parameters changed with doping levels and synthesis temperature. X-ray absorption near edge spectroscopy enabled understanding of the vanadium and iron oxidation states to confirm how vacancies in the structure caused by doping were charge compensated. This was important to understand because the literature suggests doping can improve LiFePO4 electrical conductivity, which improves battery charge and discharge rates. The second example will focus on understanding residual strain in lithium metal anodes. Lithium-ion batteries typically use graphite anodes, but the charge-storage capacity can be theoretically improved ~10x by using lithium metal as the anode material instead. However, lithium anodes suffer from growth of high-aspect-ratio features, such as dendrites, that can pierce nanoporous polymer separators and lead to short circuits and fires. External pressure is commonly applied to cells to enable better morphological control. We hypothesized that applied pressure may promote strain and possibly work hardening during electrochemical cycling, which motivated us to look for evidence of residual strain in lithium metal cycled under applied pressure using X-ray diffraction and sin2(..psi..) analysis. We found that lithium electrodeposited under high pressure exhibited in-plane compressive strain and that that lithium electrodeposited under low pressure did not. (3) The residual strain that accompanies electrodeposition under high pressure may lead to work hardening, which may explain how a soft metal like lithium can puncture separators and why higher pressure does not always decrease short circuits. (4-6) References: 1) Harrison, K. L.; Manthiram, A. Microwave-Assisted Solvothermal Synthesis and Characterization of Metastable LiFe1- x (VO) x PO4 Cathodes. Inorganic chemistry 2011, 50(8), 3613-3620. 2) Harrison, K. L.; Bridges, C. A.; Paranthaman, M. P.; Segre, C. U.; Katsoudas, J.; Maroni, V. A.; Idrobo, J. C.; Goodenough, J. B.; Manthiram, A. Temperature Dependence of Aliovalent-Vanadium Doping in LiFePO4 Cathodes. Chemistry of Materials 2013, 25(5), 768-781. 3) Rodriguez, M. A.; Harrison, K. L.; Goriparti, S.; Griego, J. J.; Boyce, B. L.; Perdue, B. R. Use of a Be-Dome Holder for Texture and Strain Characterization of Li Metal Thin Films via Sin2 (..psi..) Methodology. Powder Diffraction 2020, 35(2), 89-97. 4) Jungjohann, K. L.; Gannon, R. N.; Goriparti, S.; Randolph, S. J.; Merrill, L. C.; Johnson, D. C.; Zavadil, K. R.; Harris, S. J.; Harrison, K. L. Cryogenic Laser Ablation Reveals Short-Circuit Mechanism in Lithium Metal Batteries. ACS Energy Letters 2021, 6(6), 2138-2144. 5) Harrison, K. L.; Merrill, L. C.; Long, D. M.; Randolph, S. J.; Goriparti, S.; Christian, J.; Warren, B.; Roberts, S. A.; Harris, S. J.; Perry, D. L. Cryogenic Electron Microscopy Reveals That Applied Pressure Promotes Short Circuits in Li Batteries. Iscience 2021, 24(12). 6) Harrison, K. L.; Goriparti, S.; Merrill, L. C.; Long, D. M.; Warren, B.; Roberts, S. A.; Perdue, B. R.; Casias, Z.; Cuillier, P.; Boyce, B. L. Effects of Applied Interfacial Pressure on Li-Metal Cycling Performance and Morphology in 4 M LiFSI in DME. ACS Applied Materials & Interfaces 2021, 13(27), 31668-31679.

batteries↗
DOE OSTI2024

Exploring Ion Mobility Mass Spectrometry Data File Conversions to Leverage Existing Tools and Enable New Workflows

Ion mobility (IM) is often combined with LC-MS experiments to provide an additional dimension of separation for complex sample analysis. While highly complex samples are better characterized by the full dimensionality of LC-IM-MS experiments to uncover new information, downstream data analysis workflows are often not equipped to properly mine the additional IM dimension. For many samples the data acquisition benefits of including IM separations are all that is necessary to uncover sample information and the full dimensionality of the data is not required for data analysis. Post-acquisition reduction and adaptation of the dimensions of LC-IM-MS and IM-MS experiments into an LC-MS format opens the possibility to use a plethora of existing software tools. In this work, we developed data file conversion tools to reduce the complexity of IM data analysis. Three data file transformations are introduced in the PNNL PreProcessor software: 1) mapping the IM axis to the LC axis for IM-MS data, 2) converting the drift time vs. m/z space to CCS/z vs m/z space, and 3) transforming All Ions IM/MS mobility aligned fragmentation data to a standard LC-MS DDA data file format. Finally, these new data file conversions are demonstrated with corresponding lipidomics and proteomics workflows that leverage existing LC-MS data analysis software to highlight the benefits of the data transformations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Development for Integrated System-Level Analysis Capabilities in SAM for Molten Salt Reactors

In recent years, there has been renewed interest in Molten Salt Reactors (MSRs) for their potential advantages compared to reactors that rely on solid fuel. In response to such interest, many methods and codes have been developed to capture the unique features of MSRs. Among them, the System Analysis Module (SAM) is a modern system analysis tool that provides fast-running, modest-fidelity, whole-plant transient analysis capabilities, essential for fast-turnaround design scoping and engineering analyses of advanced reactor concepts. For liquid-fuel MSRs, the complex physics and chemistry involved in MSR operation—such as reactor kinetics, fluid flow, heat transfer, and salt composition dynamics—pose significant challenges for system-level modeling. Specific modeling capabilities are needed for system-level transient simulation. This paper presents recent advancements in SAM capability enhancements for system-level modeling of MSRs, focusing on improved simulation fidelity, computational efficiency, and multi-physics integration. Key enhancements include the development of species transport, Delayed Neutron Precursor (DNP) drift, modified Point Kinetics Equations (PKE), decay heat modeling, key fission product behavior, salt corrosion, and thermal-hydraulic coupling, as well as code robustness and performance enhancements for MSR applications. The code enhancement allows for better predictive accuracy in safety analysis, transient behavior, and operational optimization, thus supporting the design and licensing of next-generation MSRs. Results from case studies are presented to demonstrate the benefits of these enhancements in accurately capturing key reactor transient behaviors.

Hu, Rui (ORCID:0000000237712920)↗