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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Taking Measure of the Milky Way

We intend to use SIM to make definitive measurements of fundamental structural and dynamical parameters of the Milky Way. The important niche in dynamical parameter space afforded by SIM can be exploited to resolve, with unprecedented precision, a number of classical problems of Galactic astronomy. In addition, we have developed new tests of the Galactic mass distribution specifically designed for data with the special properties of SIM products. Our proposed suite of experiments will utilize the SIM Astrometric Grid as well as complementary observations of star clusters and other strategically-selected, distant "test particles" for a definitive characterization of the major components (bulge, disk, halo, satellite system) of the Milky Way. Specifically, our goals will be: 1) The determination of two fundamental parameters that play a central role in virtually every problem in Galactic astronomy, namely (a) the solar distance to the center of the Milky Way, R(sub 0); (b) the solar angular velocity around the Galactic: center, omega(sub 0). 2) The measurement of fundamental dynamical properties of the Milky Way, among them (a) the pattern speed of the central bar (b) the rotation field and velocity-dispersion tensor in the disk (c) the kinematics (mean rotational velocity and velocity dispersion tensor) of the halo as a function of position 3. The definition of the mass distribution of the Galaxy, which is dominated by the presence of dark matter. We intend to measure (a) the relative contribution of the disk and halo to the gravitational potential (b) the local volume and surface mass density of the disk (c) the shape, mass and extent of the dark halo of the Milky Way out to 250 kpc.

Majewski, Steven R.↗
DOE OSTI2026

Photodissociation and Infrared Spectroscopy of U + (CO 2 ) n , UO + (CO 2 ) n , and UO 2+ (CO 2 ) n Cation-Molecular Complexes

Laser vaporization of uranium in a pulsed supersonic expansion of carbon dioxide is used to produce complexes of the form U + (CO 2 ) n , UO + (CO 2 ) n , and UO 2+ (CO 2 ) n . These ions are selected in a reflectron time-offlight mass spectrometer and studied with visible laser photodissociation and tunable infrared laser photodissociation spectroscopy in the region of the CO 2 antisymmetric stretch. The dissociation patterns and spectroscopy of these ions indicate that CO 2 ligands are intact molecules. Although reaction products that form oxide-carbonyl or oxalate species are predicted to be stable, there is no direct evidence in the frequency range studied for the formation of these species. There is no clear indication for the coordination numbers for singly charged uranium and its oxide complexes with CO 2 . However, there is strong support in the vibrational patterns for an eight-coordinate complex of the doubly charged UO 2+ species, i.e., UO 2+ (CO 2 ) 8 .

Cluster chemistry↗
DOE OSTI2015

Clustering effects in fusion evaporation reactions with light even-even N = Z nuclei. The {sup 24}Mg and {sup 28}Si cases

In the recent years, cluster structures have been evidenced in many ground and excited states of light nuclei [1, 2]. Within the currently ongoing experimental campaign by the NUCL-EX collaboration we have measured the {sup 12}C+{sup 12}C and {sup 14}N+{sup 10}B reactions at 95 MeV and 80 MeV respectively, and compared experimental data corresponding to complete fusion of target and projectile into an excited {sup 24}Mg nucleus to the results of a pure statistical model[3, 4]. We found clear deviations from the statstical model in the decay pattern: emission channels involving multiple α particles are more probable than expected from a purely statistical behavior. To continue the investigation on light systems, we have recentely measured the {sup 16}O+{sup 12}C reaction at three different beam energies, namely E{sub beam} = 90, 110 and 130 MeV.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Inclusive jet and hadron suppression in a multistage approach

We present a new study of jet interactions in the quark-gluon plasma created in high-energy heavy-ion collisions, using a multistage event generator within the jetscape framework. We focus on medium-induced modifications in the rate of inclusive jets and high transverse momentum (high-p T ) hadrons. Scattering-induced jet energy loss is calculated in two stages: a high virtuality stage based on the matter model, in which scattering of highly virtual partons modifies the vacuum radiation pattern, and a second stage at lower jet virtuality based on the LBT model, in which leading partons gain and lose virtuality by scattering and radiation. Coherence effects that reduce the medium-induced emission rate in the matter phase are also included. The TRENTO model is used for initial conditions, and the (2 + 1)dimensional VISHNU model is used for viscous hydrodynamic evolution. Jet interactions with the medium are modeled via 2-to-2 scattering with Debye screened potentials, in which the recoiling partons are tracked, hadronized, and included in the jet clustering. Holes left in the medium are also tracked and subtracted to conserve transverse momentum. Calculations of the nuclear modification factor (R AA ) for inclusive jets and high-p T hadrons are compared to experimental measurements at the BNL Relativistic Heavy Ion Collider (RHIC) and the CERN Large Hadron Collider (LHC). Within this framework, we find that with one extra parameter which codifies the transition between stages of jet modification—along with the typical parameters such as the coupling in the medium, the start and stop criteria, etc.—we can describe these data at all energies for central and semicentral collisions without a rescaling of the jet transport coefficient q.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Identifying and Exploiting Diurnal Motifs in Wind Generation Time Series Data

Wind energy is scheduled on the power grid using 0–6 h ahead forecasts generated from computer simulations or historical data. When the forecasts are inaccurate, control room operators use their expertise, as well as the actual generation from previous days, to estimate the amount of energy to schedule. However, this is a challenge, and it would be useful for the operators to have additional information they can exploit to make better informed decisions. In this paper, we use techniques from time series analysis to determine if there are motifs, or frequently occurring diurnal patterns in wind generation data. Here we compare two different representations of the data and four different ways of identifying the number of motifs. Using data from wind farms in Tehachapi Pass and mid-Columbia Basin, we describe our findings and discuss how these motifs can be used to guide scheduling decisions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Silver clusters encapsulated in C{sub 60}: A density functional study

We explore the possibility of formation of endohedral complexes of Ag{sub n} atoms (n=1-9) inside C{sub 60} molecule using density functional theory and molecular dynamics. The obtained results reveal that Ag{sub n} (n=8) atoms can form stable complexes with the C{sub 60} molecule. Encapsulation of large number of Ag{sub n} atoms (n>8) make C{sub 60} cage instable, showing distortion of cage. Binding energy/atom increases with the number of Ag atoms up to n=4, after that it increases. Ionization potential decreases till n=4 and then increases, electron affinity increases till n=4 and then shows oscillatory nature as a function of Ag atoms inside the cage. Homo –Lumo gap shows no systematic pattern. Our results agreed well with the data available.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Development of molecular cluster models to probe pyrite surface reactivity

Abstract The recent discovery that anaerobic methanogens can reductively dissolve pyrite and utilize dissolution products as a source of iron and sulfur to meet their biosynthetic demands for these elements prompted the development of atomic‐scale nanoparticle models, as maquettes of reactive surface sites, for describing the fundamental redox steps that take place at the mineral surface during reduction. The given report describes our computational approach for modeling n (FeS 2 ) nanoparticles originated from mineral bulk structure. These maquettes contain a comprehensive set of coordinatively unsaturated Fe (II) sites that are connected via a range of persulfide (S 2 2− ) ligation. In addition to the specific maquettes with n = 8, 18, and 32 FeS 2 units, we established guidelines for obtaining low‐energy structures by considering the pattern of ionic, covalent, and magnetic interactions among the metal and ligand sites. The developed models serve as computational nano‐reactors that can be used to describe the reductive dissolution mechanism of pyrite to better understand the reactive sites on the mineral, where microbial extracellular electron‐transfer reactions can occur.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Displacement Analysis of Geothermal Field Based on PSInSAR And SOM Clustering Algorithms A Case Study of Brady Field, Nevada—USA

The availability of free and high temporal resolution satellite data and advanced SAR techniques allows us to analyze ground displacement cost-effectively. Our aim was to properly define subsidence and uplift areas to delineate a geothermal field and perform time-series analysis to identify temporal trends. A Persistent Scatterer Interferometry (PSI) algorithm was used to estimate vertical displacement in the Brady geothermal field located in Nevada by analyzing 70 Sentinel-1A Synthetic-Aperture Radar (SAR) images, between January 2017 and December 2019. To classify zones affected by displacement, an unsupervised Self-Organizing Map (SOM) algorithm was applied to classify points based on their behavior in time, and those clusters were used to determine subsidence, uplift, and stable regions automatically. Finally, time-series analysis was applied to the clustered data to understand the inflection dates. The maximum subsidence is –19 mm/yr with an average value of –6 mm/yr within the geothermal field. The maximum uplift is 14 mm/yr with an average value of 4 mm/yr within the geothermal field. The uplift occurred on the NE of the field, where the injection wells are located. On the other hand, subsidence is concentrated on the SW of the field where the production wells are located. The coupling of the PSInSAR and the SOM algorithms was shown to be effective in analyzing the direction and pattern of the displacements observed in the field.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Ion effects in hydrogen-induced blistering of Mo/Si multilayers

The role that energetic (>800 eV) hydrogen ions play in inducing and modifying the formation of blisters in nanoscale Mo/Si multilayer samples is investigated. Such samples are confirmed to be susceptible to blistering by two separate mechanisms. The first is attributed to the segregation of H atoms to voids and vacancies associated with the outermost Mo layer, driving blister formation in the form of H{sub 2} filled bubbles. This process can occur in the absence of ions. A second blister distribution emerges when energetic ions are present in the irradiating flux. This is attributed to an ion-induced vacancy clustering mechanism that produces void blisters. The defects and strained states associated with the Mo-on-Si interfaces provide the preferred nucleation points for blistering in both cases. The effects of ions are ascribed to promotion of hydrogen uptake and mobility, in particular through the Si layers; to the generation of additional mobile species in the Si and Mo layers; and to the creation of new blister nucleation points. In addition to directly stimulating blistering via vacancy clustering, ions modify the development of H{sub 2}-filled blisters. This is most evident in the formation of multi-component structures due to overlapping delaminations at different layer interfaces. This affect is attributed to the introduction of active transport of hydrogen from the H{sub 2} filled blisters across the outermost Mo-on-Si interface to the underlying layers. Ion-induced variations in hydrogen uptake and distribution and in the rates of blister nucleation and growth produce lateral differences in blister size and areal number density that create a macroscopic concentric pattern across the surface.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tetranucleotide frequencies differentiate genomic boundaries and metabolic strategies across environmental microbiomes

Microbiomes are constrained by physicochemical conditions, nutrient regimes, and community interactions across diverse environments, yet genomic signatures of this adaptation remain unclear. Metagenome sequencing is a powerful technique to analyze genomic content in the context of natural environments, establishing concepts of microbial ecological trends. Here, we developed a data discovery tool-a tetranucleotide-informed metagenome stability diagram-that is publicly available in the integrated microbial genomes and microbiomes (IMG/M) platform for metagenome ecosystem analyses. We analyzed the tetranucleotide frequencies from quality-filtered and unassembled sequence data of over 12,000 metagenomes to assess ecosystem-specific microbial community composition and function. We found that tetranucleotide frequencies can differentiate communities across various natural environments and that specific functional and metabolic trends can be observed in this structuring. Our tool places metagenomes sampled from diverse environments into clusters and along gradients of tetranucleotide frequency similarity, suggesting microbiome community compositions specific to gradient conditions. Within the resulting metagenome clusters, we identify protein-coding gene identifiers that are most differentiated between ecosystem classifications. We plan for annual updates to the metagenome stability diagram in IMG/M with new data, allowing for refinement of the ecosystem classifications delineated here. This framework has the potential to inform future studies on microbiome engineering, bioremediation, and the prediction of microbial community responses to environmental change. IMPORTANCE: Microbes adapt to diverse environments influenced by factors like temperature, acidity, and nutrient availability. We developed a new tool to analyze and visualize the genetic makeup of over 12,000 microbial communities, revealing patterns linked to specific functions and metabolic processes. This tool groups similar microbial communities and identifies characteristic genes within environments. By continually updating this tool, we aim to advance our understanding of microbial ecology, enabling applications like microbial engineering, bioremediation, and predicting responses to environmental change.

Kellom, Matthew↗
NASA NTRS2003

Low Thermal Conductivity Thermal Barrier Coatings Developed

Thermal barrier coatings (TBCs) are used extensively in modern gas turbine engines to thermally insulate air-cooled metallic components from the hot gases in the engine. These coatings typically consist of a zirconia-yttria ceramic that has been applied by either plasma spraying or physical vapor deposition. Future engines will rely even more heavily on TBCs and will require materials that have even higher temperature capability with improved insulation (i.e., lower thermal conductivity even after many hours at high temperature). This report discusses new TBCs that have been developed with these future requirements in mind. The Ultra-Efficient Engine Technology Program at the NASA Glenn Research Center is funding this effort, which has been conducted primarily at Glenn with contractor support (GE and Howmet) for physical vapor deposition. As stated, the new TBC not only had to be more insulating but the insulation had to persist even after many hours of exposure-that is, the new TBC had to have both lower conductivity and improved sintering resistance. A new type of test rig was developed for this task. This new test approach used a laser to deliver a known high heat flux in an essentially uniform pattern to the surface of the coating, thereby establishing a realistic thermal gradient across its thickness. This gradient was determined from surface and backside pyrometry; and since the heat flux and coating thickness are known, this permitted continuous monitoring of thermal conductivity. Thus, this laser rig allowed very efficient screening of candidate low-conductivity, sinter-resistant TBCs. The coating-design approach selected for these new low-conductivity TBCs was to identify oxide dopants that had the potential to promote the formation of relatively large and stable groupings of defects known as defect clusters. This approach was used because it was felt that such clusters would reduce conductivity while enhancing stability. The approach proved to be successful: low-conductivity TBCs having improved sintering resistance were developed.

Zhu, Dongming↗
DOE OSTI2023

A Siamese CNN + KNN-Based Classification Framework for Non-intrusive Load Monitoring

Through the development of smart grids, programs such as demand side response, have been presented as auxiliary services to the real-time operation of distributed networks. In order to provide consumers information on their energy consumption, so that a modulation in consumption is possible, non-intrusive load monitoring has been introduced as an solution to this pattern recognition problem. Non-intrusive load monitoring enables the modeling of electrical loads connected to the low-voltage system, considering only a single measurement point. Presented state-of-the-art solutions though, consider availability of data as well as representation of all possible classes of the environment. This is of course a most conservative hypothesis, since in real-life applications availability of such data is much difficult, as well as the dynamic behavior of models is implicitly evolving in time. Here, a framework that uses neural Siamese networks with k-nearest neighbor clustering is presented toward non-intrusive load monitoring. Online learning feature is implemented, which relaxes the hypothesis of data requirements as well addresses the evolving nature of load profile. k-nearest clustering allows nonlinear characteristic space modelling. Test results using synthetics and real-life data show that the solution, besides obtaining a good generalizability in the classification, also obtained results with an accuracy of 95.77%.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Cosmogenic surface exposure ( 10 Be) dating of raised beaches in Marguerite bay, Antarctic Peninsula: Implications for relative sea-level history

Understanding the dynamics of ice mass loss in polar regions is crucial for deciphering climate change and Glacio Isostatic Adjustment patterns. This study focuses on Marguerite Bay, located in the south-central Antarctic Peninsula. We dated raised beaches to investigate relative sea-level changes using the cosmogenic surface exposure ( 10 Be) method. Previous studies have provided valuable insights into the region's glacial history, but limitations in dating techniques and age estimates necessitate further investigation. By analysing raised shingle beaches in Gaul Cove of Horseshoe Island and the southern coast of Calmette Bay, this research aims to contribute relative sea-level change history for these areas. In Horseshoe Island's Gaul Cove, raised beaches clustered on prominent steps reveal a 15 m relative sea-level change over the last 3.31 ka. Differently, Calmette Bay exhibits a 36 m relative sea-level fall over the last 7.29 ka. Finally, these findings indicate significant and differential glacial-isostatic adjustments in both regions during the middle and late Holocene. Additionally, our data reveal accelerated sea-level fall periods corresponding to Holocene deglaciation and glacial advance events, indicating the shorelines' relative sea-level change sensitivity to climate change.

58 GEOSCIENCES↗
DOE OSTI2023

Clonality, local population structure, and gametophyte sex ratios in cryptic species of the Sphagnum magellanicum complex

Sphagnum (peatmoss) comprises a moss (Bryophyta) clade with approximately 300-500 species. The genus has unparalleled ecological importance because Sphagnum-dominated peatlands store almost a third of the terrestrial carbon pool and peatmosses engineer the formation and microtopography of peatlands. Genomic resources for Sphagnum are being actively expanded, but many aspects of their biology are still poorly known. Among these are the degree to which Sphagnum species reproduce asexually, and the relative frequencies of male and female gametophytes in these haploid-dominant plants. Here, we assess clonality and gametophyte sex ratios and test hypotheses about the local-scale distribution of clones and sexes in four North American species of the S. magellanicum complex. These four species are difficult to distinguish morphologically and are very closely related. We also assess microbial communities associated with Sphagnum host plant clones and sexes at two sites. 405 samples of the four species, representing 57 populations, were subjected to RADseq. Analyses of population structure and clonality based on the molecular data utilized both phylogenetic and phenetic approaches. Multi-locus genotypes (genets) were identified using the RADseq data. Sexes of sampled ramets were determined using a molecular approach that utilized coverage of loci on the sex chromosomes after the method was validated using a sample of plants that expressed sex phenotypically. Sex ratios were estimated for each species, and populations within species. Differences in fitness between genets was estimated as the numbers of ramets each genet comprised. Degree of clonality (numbers of genets/numbers of ramets [samples]) within species, among sites, and between gametophyte sexes were estimated. Sex ratios were estimated for each species, and populations within species. Sphagnum-associated microbial communities were assessed at two sites in relation to Sphagnum clonality and sex. All four species appear to engage in a mixture of sexual and asexual (clonal) reproduction. A single ramet represents most genets but 2-8 ramets were detected for some genets. Only one genet is represented by ramets in multiple populations; all other genets are restricted to a single population. Within populations ramets of individual genets are spatially clustered, suggesting limited dispersal even within peatlands. Sex ratios are male-biased in S. diabolicum but female-biased in the other three species, although significantly so only in S. divinum. Neither species nor males/females differ in levels of clonal propagation. At St. Regis Lake (NY) and Franklin Bog (VT), microbial community composition is strongly differentiated between the sites, but differences between species, genets, and sexes were not detected. Within S. divinum, however, female gametophytes harbored 2-3 times the number oi of microbial taxa as males. These four Sphagnum species all exhibit a similar reproductive patterns that result from a mixture of sexual and asexual reproduction. The spatial patterns of clonally replicated ramets of genets suggest that these species fall between the so-called phalanx patterns where genets abut one another but do not extensively mix, because of limited ramet fragmentation, and the guerrilla patterns where extensive genet fragmentation and dispersal results in greater mixing of different genets. Although sex ratios in bryophytes are most often female-biased, both male and female biases occur in this complex of closely related species. The association of far greater microbial diversity for female gametophytes in S. divinum, which has a female-biased sex ratio, suggests additional research to determine if levels of microbial diversity are consistently correlated with differing patterns of sex ratio biases.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2014

Amorphous and Crystalline H20 Ice at Rhea's Inktomi Crater

We present the analysis of Cassini spectral data from spectral mapping of Saturnian icy moons Dione and Rhea, to investigate possible effects of impact crater formation on the relative abundances of crystalline and amorphous water ice in the moons' ice crusts. Both moons display morphologically young ray craters as well as older craters. Possible changes in ice properties due to crater formation are conjectured to be more visible in younger craters, and as such Rhea's well imaged ray crater Inktomi is analysed, as are older craters for comparison. We used data from Cassini's Visual and Infrared Mapping Spectrometer (VIMS). For each pixel in the VIMS maps, spectral data were extracted in the near-infrared range (1.75 micrometers less than lambda less than 2.45 micrometers). Analysis was begun by fitting a single Gaussian to the peak in absorption at 2.0 micrometers, which was then subtracted from the data, leaving residuals with a minimum on either side of the original 2.0-micrometers band. The spectra of the individual spatial pixels were then clustered by the differences between these minima, which are sensitive to changes in both ice grain size and crystallinity. This yielded preliminary maps which approximated the physical characteristics of the landscape and were used to identify candidates for further analysis. Spectra were then clustered by the properties of the 1.5-micrometers band, to divide the map into regions based on inferred grain size. For each region, the predicted differences in minima from the Gaussian residuals, over a range of crystallinities, were calculated based on the found grain sizes. This model was used to find the crystallinity of each pixel via grain size and characteristics of the residual function. Preliminary results show a greater degree of crystallization of young crater interiors, particularly in Rhea's ray crater Inktomi, where ice showed crystalline ice abundances between 33 percent and 61 percent. These patterns in ice crystallization are possibly attributable to increased heat generated during crater formation.

Saturn Satellites↗
DOE OSTI2024

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗
DOE OSTI2025

Optimization of edge bead removal (EBR) process to enhance defect reduction in optical lithography

Defect reduction remains a critical objective in the integrated circuit manufacturing process, particularly within the highly re-entrant lithography modules where minimizing defects is crucial. Defects at the wafer edge can contaminate lithography modules and downstream processing equipment, leading to redistribution onto the wafer surface and adversely affecting overall device yield. A persistent challenge in the resist coating process is the formation of resist edge beads, driven by the strong Van der Waals attraction of excess photoresist (PR) to itself and the underlying substrate. The edge bead removal (EBR) process is a standard cleaning step designed to eliminate these edge beads and prevent potential contamination. Here, in this study, we identify the sources of EBR induced defects and additional EBR process encroachment toward edge patterning during the EBR cleaning process. This study provides a comprehensive study aimed at optimizing the EBR cleaning process to effectively eliminate EBR-induced defects, thereby enhancing overall device yield. Specifically, we identify three primary defects induced by the EBR cleaning process: rainbow-type, finger-shaped, and teardrop-type defects. Our experimental study reveals that in addition to EBR rinse time, PR cast time is crucial parameters contributing to the formation of these defects. By properly optimizing the PR cast time and EBR rinse time, we were able to remove nearly 100 % of dense clusters of defects that were easily visible even at low magnification optical microscopy throughout the wafer edge. We observed that shorter PR casting times shows edge defects caused by inefficient EBR process because of insufficient time for PR to fully settle causing superfluous PR to continue flowing toward wafer edge during EBR clearing step, leading to partial removal of PR at the wafer edge and the formation of rainbow defects. Proper optimization of both PR casting time and EBR chemistries dispense time is essential to resolve these defects, ensuring efficient EBR cleaning process and improved overall device yield.

42 ENGINEERING↗
DOE OSTI2016

WE-DE-202-00: Connecting Radiation Physics with Computational Biology

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)

60 APPLIED LIFE SCIENCES↗