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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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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Optimization of screw design for continuous wet granulation: A case study of metoprolol succinate ER tablets

This study aimed at understanding the effect of screw design on the critical characteristics of granules and tablets of an extended-release (ER) formulation for twin screw granulation process. The screw design parameters assessed included number of kneading elements (KEs) per kneading zone, distance separating kneading zones, staggering angle (SA) of kneading elements and number of sizing elements (SEs). These input variables were varied using a design of experiment (DoE) approach to manufacture granules. Particle size distribution (PSD), flow and bulk properties of the granules, breaking strength and dissolution of tablets manufactured using these granules were characterized. The results of least square fitting showed that KEs, SA, and SEs of the screws significantly (p -values < 0.05) affected the PSD, cohesion, compressibility (CPS), conditioned bulk density (CBD) and permeability of the granules. The KEs and SEs significantly (p -value < 0.05) affected the dissolution, which was attributed to their effects on CPS and CBD of the granules. The distance between kneading zones had no significant effect on granules and tablet characteristics. Finally, these results may be used to further study the interaction of the identified critical screw design parameters with other processing parameters for continuous manufacturing of this ER matrix-based tablet formulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Unraveling the Effects of Melt–Mantle Interactions on the Gold Fertility of Magmas

The oxidation state of the Earth’s mantle and its partial melting products exert a key control on the behavior and distribution of sulfur and chalcophile and siderophile elements between the mantle and crust, underpinning models of ore deposit formation. Whether the oxidized nature of magmas is inherited from the asthenospheric mantle source or acquired during ascent and differentiation is vigorously debated, limiting our understanding of the mechanisms of extraction of sulfur and metals from the mantle. Here, we focused on the redox-sensitive behavior of sulfur in apatite crystallized from quenched alkaline basaltic melts preserved within a peridotite xenolith from the El Deseado Massif auriferous province in southern Patagonia. We took advantage of this unique setting to elucidate the redox evolution of melts during their ascent through the subcontinental lithospheric mantle (SCLM) and grasp the inner workings of the Earth’s mantle during gold metallogenesis. Our data reveal that an initially reduced silicate melt (ΔFMQ -2.2 to -1.2) was oxidized to ΔFMQ between 0 and 1.2 during percolation and interaction with the surrounding peridotite wall-rock (ΔFMQ 0 to +0.8). This process triggered changes in sulfur speciation and solubility in the silicate melt, boosting the potential of the melt to scavenge ore metals such as gold. We suggest that large redox gradients resulting from the interaction between ascending melts and the surrounding mantle can potentially modify the oxidation state of primitive melts and enhance their metallogenic fertility. Among other factors including an enriched metal source and favorable geodynamic conditions, redox gradients in the mantle may exert a first-order control on the global-scale localization of crustal provinces endowed with gold deposits.

58 GEOSCIENCES↗
DOE OSTI2025

Coarse-grained molecular dynamics simulation of solvent-dependent cellulose nanofiber interactions

Associations between cellulose are important both in biofuel production and in the use of cellulose for biomaterials. Cellulose nanofibers (CNFs) are sustainable, strong, light-weight alternatives to traditional materials in manufacturing, but are challenging to obtain due to irreversible aggregation in solution during preparative fibrillation. Therefore, it is imperative to understand the underlying factors driving aggregation with a view to designing solvents that can effectively compete with interfiber interactions, hence reducing aggregation. Molecular dynamics (MD) simulation at atomic detail can provide useful information on local interactions. However, the length and timescales accessible are too short to fully capture association processes. Here, we provide a method for accessing the longer length and timescales required using coarse-grained (CG) MD simulations with a MARTINI force field to calculate the interaction behavior of CNFs in three selected solvents: NaOH-urea-water, acetone, and neat water. The CG results are consistent with our prior all-atom MD and with previous experimental results. While acetone is found not to be an effective solvent, urea and ionic moieties in NaOH-urea-water not only solvate the fibrils but also improve the confinement of water molecules around them as shown by the solvent residence times and mean-square displacements. Overall, the presence of urea and ions reduces the likelihood of aggregation in multi-CNF systems relative to neat water irrespective of whether the hydrophobic or hydrophilic CNF surfaces are interacting. In conclusion, the CG method shows clear promise for selecting potential high-performance solvents for experimental prioritization in bioenergy and biomaterials research in a relatively fast manner as well as for understanding the aggregation and rheological behavior of CNF-solvent systems.

aggregation↗
DOE OSTI2024

System Modeling of Frost/Defrost Cycles in Heat Pumps

Accurately modeling frost/defrost cycles is crucial for guiding heat exchanger design, appropriately sizing the compressor, and quantifying seasonal energy consumption for heating. While previous modelling studies of frosting cycle have predominantly focused on the component level of fin-and-tube coils, there has been limited development of models for system defrosting cycles. This study enhances the existing knowledge by improving a detailed, segment-to-segment heat exchanger model to simulate frost/defrost cycles for both fin-and-tube coils and microchannel heat exchangers. Furthermore, it integrates this component-level model into a steady-state/quasi-steady-state system modeling framework to simulate complete frost/defrost processes, i.e. the ORNL Heat Pump Design Model (HPDM). This comprehensive approach will unveil differences in coil types, and their interactions with the outdoor fan. It will also predict energy consumption patterns and time intervals associated with these processes.

Shen, Bo↗
DOE OSTI2023

Science Plan for the Deployment of the Third ARM Mobile Facility to the Southeastern United States at the Bankhead National Forest, Alabama (AMF3 BNF)

In 2018, the U.S. Department of Energy (DOE) held a workshop for the Atmospheric Radiation Measurement (ARM) (Mather and Voyles 2013) user facility to discuss critical climate challenges and locations where key ARM Mobile Facility (AMF) observational assets could impact Earth system modeling (ESM). As an outcome, the southeast United States (SE U.S.) was identified as a high-priority region to target climate-process studies that promote a deeper understanding of the climate system and bolster ARM interactions with the community to drive ESM advancement. The DOE ARM user facility is a globally recognized leader in deploying and operating strategically located observation sites around the world for studying the properties of aerosols and clouds and their interaction with radiation, precipitation, and the Earth’s surface. In partnering with the DOE Atmospheric System Research (ASR) program, ARM solicited a multi-agency Site Science Team approach to provide input and close interaction with ARM management towards a successful SE U.S. deployment of the ARM third Mobile Facility (AMF3) (Miller et al. 2016). These efforts included identifying key locations, science drivers and instruments, and measurement strategies to address the wider climate-process needs and ESM improvement. Community input served a vital role in establishing, refining, and informing the relevant drivers and decisions regarding this AMF3 deployment. The team has identified Northern Alabama (N. AL) as regionally representative to unlock the key opportunities that will improve our understanding and model representation of aerosol, cloud, and land surface processes and their couplings in the SE U.S. A defining aspect of the AMF3 deployment is its commitment to long-term (anticipated five-year) observations to mitigate potential seasonal-to-annual variability that often limits appropriate attribution of phenomena to local or larger-scale processes. The proposed location may leverage nearby surface networks and multi-agency and partner assets to enrich this multi-year deployment. One motivation is to understand the role of spatiotemporal variability (thermodynamic, land-surface) across aspects of the climate system, with our AMF3 team anticipating future demands on characterizing the relationships between local-to-regional cloud development and surface processes across a diverse patchwork of natural, managed, and urban landscapes as found throughout the N. AL regions. The main site targets an intact, representative, forested region – the Bankhead National Forest (BNF) – underscoring further team commitment to regionally important land atmosphere two-way interactive studies “from the canopy to the clouds”, with enhanced tower instrumentation augmenting traditional ARM capabilities adjacent to this site. Multiple supplemental sites will also be distributed across this region, prioritizing added needs for biodiversity. Anticipated high-priority cloud science themes will target N. AL as a regional SE U.S. hotbed for high-impact weather, convective cloud onset, and shallow to-deep cloud transitioning. Anticipated aerosol drivers will focus on chemical processes that control the evolution of organic aerosol, the seasonality and spatial distribution of water vapor and particle-phase water, and its role on aerosol optical properties. Anticipated land atmosphere drivers consider the two-way feedbacks between surface influence on aerosols, clouds, and precipitation properties and the associated radiative impacts on plant physiology and canopy-scale fluxes. Emphasis will include the study of the impact of surface processes on aerosols via precursor emission, and on clouds via moisture flux and thermal development.

Doppler lidar, aerosols, convection↗
DOE OSTI2025

Optimizing the impacts of solid additives on the operational stability and processing reliability of organic solar cells

Previous reports have revealed that by leveraging solid additives, organic solar cells (OSCs) can surpass the device’s performance beyond the intrinsic limitations of host photoactive molecules, a remarkable advancement. However, the impacts of more complex interactions introduced by solid additives are not yet well understood. Herein, optimizing the fabrication process based on the traditional efficiency-guided approach fails to represent the ideal and most practical devices. In particular, achieving superior operational stability while minimizing the device performance scattering was found to require processing solvent evaporation to be synchronized with the volatility of the chosen solid additive. However, this may be challenging since most organic photoactive materials display excellent efficiencies only with selected solvents. Accordingly, this work also demonstrates the potential of dual and complementary solvents selection, consisting of low boiling point (primary) and high boiling point (secondary). This strategy allows for the suppression of any potential trade-offs in efficiency. Meanwhile, the operational stability and precision of device performance are substantially enhanced. Additionally, solid additives have demonstrated that the singlet exciton dissociation rate does not limit the free charge generation yield. Finally, these findings are expected to reformulate OSC device fabrication strategies towards more practical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Adsorption Hysteresis Under Control: Tuning Host–Guest Interactions via a Genetic Algorithm

Mesoporous adsorbent materials offer a large volumetric capacity; however, cyclic adsorption/desorption processes in these systems often suffer from hysteresis and may require a significant pressure swing to access this capacity. To mitigate hysteresis, a proposed strategy is to include nucleation sites on the walls of the mesoporous material to facilitate droplet and bubble formation, lowering the free energy barriers to the respective phase transitions. It is unclear, however, what combination of adsorbate− adsorbent interactions and spatial patterning would be beneficial for a given application, considering that improvements to some sorption properties may come at the expense of other attributes. To understand these interconnected observables, we examine two model systems, planar-slit and cylindrical pores with tunable interaction sites, using GPU-accelerated transition matrix Monte Carlo simulations. The simulations provide a free energy map of the pressure−adsorption space in a matter of minutes, which we use to track adsorption isotherm characteristics as a function of adsorbent properties. We then leverage the rapid acquisition of simulation data to construct a genetic algorithm to iteratively modify interaction sites of the slit-pore wall to minimize the hysteresis of this system without sacrificing uptake. We find that the adsorption branch of the isotherm is easily modulated via the average host−guest interaction strength, but desorption is only adjustable if there is a suitable bubble nucleation site. Within the context of a slit-pore system, we identify relative interaction strengths and patch sizes required to gain control over both branches of the hysteresis loop.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Science Plan for the Deployment of the Third ARM Mobile Facility to the Southeastern United States at the Bankhead National Forest, Alabama (AMF3 BNF)

In 2018, the U.S. Department of Energy (DOE) held a workshop for the Atmospheric Radiation Measurement (ARM) (Mather and Voyles 2013) user facility to discuss critical climate challenges and locations where key ARM Mobile Facility (AMF) observational assets could impact Earth system modeling (ESM). As an outcome, the southeast United States (SE U.S.) was identified as a high-priority region to target climate-process studies that promote a deeper understanding of the climate system and bolster ARM interactions with the community to drive ESM advancement. The DOE ARM user facility is a globally recognized leader in deploying and operating strategically located observation sites around the world for studying the properties of aerosols and clouds and their interaction with radiation, precipitation, and the Earth’s surface. In partnering with the DOE Atmospheric System Research (ASR) program, ARM solicited a multi-agency Site Science Team approach to provide input and close interaction with ARM management towards a successful SE U.S. deployment of the ARM third Mobile Facility (AMF3) (Miller et al. 2016). These efforts included identifying key locations, science drivers and instruments, and measurement strategies to address the wider climate-process needs and ESM improvement. Community input served a vital role in establishing, refining, and informing the relevant drivers and decisions regarding this AMF3 deployment. The team has identified Northern Alabama (N. AL) as regionally representative to unlock the key opportunities that will improve our understanding and model representation of aerosol, cloud, and land-surface processes and their couplings in the SE U.S. A defining aspect of the AMF3 deployment is its commitment to long-term (anticipated five-year) observations to mitigate potential seasonal-to-annual variability that often limits appropriate attribution of phenomena to local or larger-scale processes. The proposed location may leverage nearby surface networks and multi-agency and partner assets to enrich this multi-year deployment. One motivation is to understand the role of spatiotemporal variability (thermodynamic, land-surface) across aspects of the climate system, with our AMF3 team anticipating future demands on characterizing the relationships between local-to-regional cloud development and surface processes across a diverse patchwork of natural, managed, and urban landscapes as found throughout the N. AL regions. The main site targets an intact, representative, forested region – the Bankhead National Forest (BNF) – underscoring further team commitment to regionally important land-atmosphere two-way interactive studies “from the canopy to the clouds”, with enhanced tower instrumentation augmenting traditional ARM capabilities adjacent to this site. Multiple supplemental sites will also be distributed across this region, prioritizing added needs for biodiversity. Anticipated high-priority cloud science themes will target N. AL as a regional SE U.S. hotbed for high-impact weather, convective cloud onset, and shallow-to-deep cloud transitioning. Anticipated aerosol drivers will focus on chemical processes that control the evolution of organic aerosol, the seasonality and spatial distribution of water vapor and particle-phase water, and its role on aerosol optical properties. Anticipated land-atmosphere drivers consider the two-way feedbacks between surface influence on aerosols, clouds, and precipitation properties and the associated radiative impacts on plant physiology and canopy-scale fluxes. Emphasis will include the study of the impact of surface processes on aerosols via precursor emission, and on clouds via moisture flux and thermal development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Supercritical water desalination and oxidation (SCWDO): Effectiveness on complex solutions, technoeconomic, and CO 2 impact for produced water treatment

The modern energy-economy is increasingly causing the production of highly saline brines, including from produced water. Supercritical water desalination can concentrate and extract minerals from these brines, but the effects of mixed salt interactions, organic degradation with additives, and the technology's economics are not well understood at supercritical condition. The present study evaluated and experimentally studied an integrated supercritical water desalination and oxidation (SCWDO) process for treating real-produced water samples from oil/natural gas field. The complex interactions between the various anions and cations in produced water were extensively evaluated. Most of the divalent and trivalent ions were extracted below 250 °C while the majority of the monovalent salt were removed between 380 to 410 °C. The treated real produced water was of drinking water quality, with <500 mg/l of total dissolved solid (TDS) and with 100% organics removal. Furthermore, the heat liberated during the organic oxidation could be utilized internally and for electricity generation for enhanced the energy efficiency and lower cost of produced water treatment. With system optimization, the proposed SCWDO process can essentially be made a net zero energy process. A novel process flow diagram for the commercial scale self-powered hybrid SCWDO technology was proposed as a cost-effective produced water treatment to mitigate the environmental crises. Techno-economic analysis showed that produced water treatment cost with SCWDO can be reduced to 2–3 $/m 3 and can be up to 60 % cheaper to traditional deep well reinjection. Additionally, the proposed SCWDO process could achieve net negative CO 2 emission.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Knowledge Graph for End-to-End Traceability of an Integrated Human-Earth System Model

Integrated human-Earth system models inform energy-water-land system dynamics and policies, yet their results are difficult to trace through input-data, model structure, scenario configurations, and solved outputs. Because this information is siloed across disconnected artifacts, process-based IAMs have historically lacked a unified, queryable representation. Such lack of traceability prevents researchers from systematically isolating the multi-sector drivers of complex outcomes (such as tracing water-scarcity results back to distant energy-system dynamics) or conducting holistic uncertainty attribution across hundreds of interacting parameters. To address this concern, our work documents the software engineering process of a knowledge graph that unifies these four layers for the Global Change Analysis Model (GCAM-USA_Reference scenario, GCAM v9.1). The graph was built as a relational property graph in DuckDB from the run’s own artifacts: the input-preparation dependency map (gcamdata chunk map), the model’s XML input files, the run configuration, and the results database (BaseX), successfully mapping the model’s declared structure. The resulting graph comprises 204,321 nodes and 1,687,814 edges across 16 node types and 15 edge types, with approximately 16.3 million time-series values stored separately to maintain structural efficiency. To ensure representation fidelity, every edge carries an epistemic-status annotation recording the warrant for the relationship (structural, provenance, dependency, or model-derived), and a machine-readable provenance ledger classifying the origin of every schema element. Evaluation against a fixed five-benchmark suite with locked baselines reports zero structural orphans, zero dangling edge endpoints, and 100% of output-producing technologies traceable to raw input files. Two interactive interfaces present the graph, including a serverless browser application built on DuckDB-Wasm. By establishing the first end-to-end provenance framework for an IAM, this work enables researchers and scientists to systematically audit complex policy scenarios, debug model structures, and trace policy-relevant outputs to their data origins in real time.

Artifical Intelligence↗
DOE OSTI2024

Medium-induced photon bremsstrahlung in neutrino-nucleus, antineutrino-nucleus, and electron-nucleus scattering from multiple QED interactions

Interactions of charged leptons with nuclei and the naive tree-level kinematics of these processes are affected by radiation of photons induced by the QED nuclear medium. We evaluate cross section modifications at leading orders of the number of correlated interactions inside the nucleus, known as the opacity expansion. We derive results for soft and collinear types of the bremsstrahlung at the first three orders in opacity and generalize them to higher orders. We present the leading in opacity energy spectra of soft and collinear photons and radiative energy loss inside the nucleus for experiments with lepton kinematics in the GeV energy range. At leading power of the Glauber soft-collinear effective field theory, the soft radiation is further resummed to all orders both in opacity and in the electromagnetic coupling constant. We find that the soft and collinear medium-induced radiation is vacuumlike, and additional corrections are power suppressed. Despite the negligible modification to the induced photon spectra, the nuclear medium-induced radiation sizably affects the broadening of charged leptons in the direction orthogonal to their propagation. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Selection Algorithm for electron neutrino charged current interactions in SBND

The Short Baseline Neutrino (SBN) program at Fermilab is a joint proposal by three experimental collaborations primarily for the investigation of the cause behind the low-energy electron-like event excess observed by the MiniBoone experiment. This dissertation focuses on the near detector of the project, named the Short Baseline Near Detector (SBND), a Liquid Argon Time Projection Chamber apparatus which will conduct searches for sterile neutrinos in the mass range of 1 ${eV}^2/{c}^4$, as well as provide cross-section measurements for neutrino interactions in argon and perform other beyond the standard model studies.\\ \indent As is the case for all detectors in the program, the SBND will use the Booster Neutrino Beam as its source, which will provide it with both muon and electron neutrinos. Given that the ability to discern between the neutrino flavors will be crucial to the fulfillment of the detector's physics goals, the objective of this work is to provide the collaboration with a tool capable of doing so. As such, we here present the development process for an inclusive selection algorithm for the identification of electron neutrino charged current (CC) events regardless of their interaction channel. This is done through a combination of traditional techniques, such as the implementation of cuts on the reconstructed interaction properties, with the use of the Convolutional Visual Network, a machine learning algorithm capable of classifying particle interactions through the analysis of the topology of their final states. With this approach, we have developed a selection process that is capable of identifying $\nu_e$ CC interactions across a wide range of topologies with 34.4\% efficiency, as well as a purity of 91.2\%, making it especially promising for use in cross section studies.

Freire, Hector Moya [ABC Federal U.] (ORCID:000900↗
DOE OSTI2025

Machine learning for single-ended event reconstruction in PROSPECT experiment

The Precision Reactor Oscillation and Spectrum Experiment, PROSPECT, was a segmented antineutrino detector that successfully operated at the High Flux Isotope Reactor in Oak Ridge, TN, during its 2018 run. Despite challenges with photomultiplier tube base failures affecting some segments, innovative machine learning approaches were employed to perform position and energy reconstruction, and particle classification. This work highlights the effectiveness of convolutional neural networks and graph convolutional networks in enhancing data analysis. By leveraging these techniques, a 3.3% increase in effective statistics was achieved compared to traditional methods, showcasing their potential to improve analysis performance. Furthermore, these machine learning methodologies offer promising applications for other segmented particle detectors, underscoring their versatility and impact.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Topological Defect Mediated Helical Phase Reorientation by Uniaxial Stress

Strain engineering enables precise, energy-efficient control of nanoscale magnetism. However, unlike well-studied strain-dislocation interactions in mechanical deformation, the spatial evolution of strain-induced spin rearrangement remains poorly understood. Using Lorentz transmission electron microscopy, we manipulate and observe helical domain reorientation under quantitatively applied uniaxial tensile stress. Our findings reveal striking similarity to plastic deformation in metals, where the critical stress for propagation vector ( Q ) reorientation depends on its angle with the stress direction. Magnetic defects mediate reorientation via “break-and-reconnect” or “dislocation gliding–annihilation” processes. Simulations confirm that strain-induced anisotropic Dzyaloshinskii-Moriya interaction may play a key role. These insights advance strain-driven magnetism and offer a promising route for energy-efficient magnetic nanophase control in next-generation information technology. Published by the American Physical Society 2025

36 MATERIALS SCIENCE↗
DOE OSTI2020

A web-based decision support system for collaborative mitigation of multiple water-related hazards using serious gaming

The paper presents a web-based application developed as a medium for executing a serious game to enhance multi-jurisdictional collaborative planning and decision making for mitigation of multiple hazards related to water (i.e., floods, soil erosions, water quality). The gaming application is integrated into the Iowa Watershed Decision Support System (IoWaDSS) designed to serve as a comprehensive multi-sectoral data repository along with the simulation results of process modeling to educate and inform communities on the status of their watersheds during extreme conditions. The interactive serious gaming application was devised to encourage public engagement, facilitate communication and positive relationship between watershed communities, and make the decision process more attractive and transparent for the stakeholders. The web environment offers easily-accessible, user-friendly interfaces that match the skills and knowledge level of a non-technical user. Developed with adaptive design and flexible architecture, the gaming application is generalizable and extendable to support hazard mitigation in other watersheds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Observational study of relationships between entrainment rate, homogeneity of mixing, and cloud droplet relative dispersion

The entrainment–mixing process is key to the cloud’s dynamical and microphysical processes. However, to the best of our knowledge, no study has quantitatively linked entrainment rate and homogeneity of mixing. Additionally, their combined effects on cloud droplet relative dispersion and physical mechanisms are even more unclear. This study analyzed the aircraft measurements of cumulus clouds collected in the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems field campaign to identify these relationships. The relationship between the entrainment rate and homogeneous mixing degree was found to be moderately positive, and the underlying mechanisms related to mixing and evaporation time scales and environmental relative humidity were explored. The relationship between relative dispersion and entrainment rate changes from positive to negative with increasing entrainment rate, depending on the dominance of evaporation of large or small droplets. The relative dispersion first increases and then decreases with increasing homogeneous mixing degree, validating the results of previous model simulations. Further, the results shed new light on understanding the interactions between cloud microphysics and cloud dynamics through turbulent entrainment and mixing processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Guiding the choice of informatics software and tools for lipidomics research applications

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Enabling Numerical Modeling of Extreme-Intensity Laser Produced Dense Plasma

We have developed physics models of extreme intensity laser-matter interaction, x-ray and γ-ray emissions, and x-ray absorption (e.g. photoionization and Auger atomic processes). The atomic processes are solved self-consistently with radiation transport, which is coupled to our collisional particle-in-cell code, PICLS. Together with a significantly improved photoionization model our capability of simulation has been extended to account for detailed atomic and radiation physics during intense optical laser-matter interaction and also the XFEL-matter interaction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗