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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 271 records · Page 15

Smart Pixels: towards on-sensor inference of charged particle track parameters and uncertainties

The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to determine angular information of the charged particle passing through from pixel-cluster properties. This detector technology immediately improves the situation for offline tracking, but any major improvements in physics reach are unrealized since they are dominated by lowest-level hardware trigger acceptance. We will demonstrate track angle and hit position prediction, including errors, using a mixture density network within a single layer of silicon as well as the progress towards and status of implementing the neural network in hardware on both FPGAs and ASICs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Smartpixels: Towards on-sensor inference of charged particle track parameters and uncertainties

The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to determine angular information of the charged particle passing through from pixel-cluster properties. This detector technology immediately improves the situation for offline tracking, but any major improvements in physics reach are unrealized since they are dominated by lowest-level hardware trigger acceptance. We will demonstrate track angle and hit position prediction, including errors, using a mixture density network within a single layer of silicon as well as the progress towards and status of implementing the neural network in hardware on both FPGAs and ASICs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Toward full exploitation of coherent and incoherent information in Sentinel-1 TOPS data for retrieving surface displacement: Application to the 2016 Kumamoto (Japan) earthquake

Sentinel-1's continuous observation program over all major plate boundary regions makes it well suited for earthquake studies. However, decorrelation due to large displacement gradients and limited azimuth resolution of the Terrain Observation by Progressive Scan (TOPS) data challenge acquiring measurements in the near field of many earthquake ruptures and prevent measurements of displacements in the along-track direction. Here we propose to fully exploit the coherent and incoherent information of TOPS data by using standard interferometric synthetic aperture radar (InSAR), split-bandwidth interferometry in range and azimuth, swath/burst-overlap interferometry, and amplitude cross correlation to map displacements in both the line-of-sight and the along-track directions. Application to the 2016 Kumamoto earthquake sequence reveals the coseismic displacements from the far field to the near field. By adding near-field constraints, the derived slip model reveals more shallow slip than obtained when only using far-field data from InSAR, highlighting the importance of exploiting all coherent and incoherent information in TOPS data.

58 GEOSCIENCES↗

Formation and surface melting of nanoparticle superlattices in a solution

The wisdom in the saying of “There are no two snowflakes alike” lies in the importance of history or kinetic pathways in the phase transitions of solids. Likewise, “artificial solids,” namely superlattices consisting of functional nanoparticles, have lattice size, surface morphology, crystallinity, symmetry, and structural reconfiguration (for example, transition into a disordered state) highly dependent on the kinetic pathways as the nanoparticles interact with each other in solution [1]. Great progresses have been made in understanding the formation pathways of superlattices using liquid-phase transmission electron microscopy (TEM) [2-4]. For example, by tracking single nanoparticle’s trajectories, especially aided by U-net neural network-based machine learning, previous studies mapped the fundamental nanoparticle interactions at nanometer resolution [5]. Nonclassical, two-step nucleation pathway has also been elucidated in the system of nanoprisms, by optimizing protocols such as loading nanoparticle suspensions over the supersaturation threshold and minimizing particle‒substrate interaction [2]. Surface morphologies or exposed facets of superlattices have been shown to follow the principles of Wulff construction rule, where the facet-dependent surface energy can be measured based on the capillary wave theory [4]. However, the reverse process of crystallization of superlattices, the conversion from crystalline to disordered state, has been much less explored. On one hand, the melting of nanoparticle superlattices can provide a preferred pathway to induce structural reorganization or shuffling of building blocks for them to transform into different types of crystal structures. On the other hand, understanding nanoscale superlattice melting and comparing such behaviors with the prevailing surface melting theories developed for atomic/molecular solids can provide a potent way to engineer phase transitions of supra- and hierarchical structures constructed from nanoscale entities (e.g., DNA-coated nanoparticles, proteins), for their applications in reprogrammable and switchable materials with multifunctional properties [6, 7]. The experimental challenges to observe melting of superlattices are twofold. Practically it is difficult to load the initial superlattice form, in an intact manner, into the highly confined liquid-phase TEM chamber for in-situ observation. Here, the triggering of melting also needs meticulous manipulation of nanoparticle concentration, interparticle interaction, and solution environment.

Kim, Ahyoung↗

Update on Ce+BAF Injector Baseline Simulations

Progress in the development of the positron injector concept for the Ce+BAF is presented. The results of start-to-end positron beam tracking simulations for two injector operating modes (low current high polarized beam and high current low polarized beam) are discussed. The efficiency of the positron capture system based on a normal conducting focusing solenoid downstream of the conversion target is compared with the efficiency of a superconducting solenoid.

Ushakov [Thomas Jefferson National Accelerator Fac↗

Shake-Down Spectroscopy as State- and Site-Specific Probe of Ultrafast Chemical Dynamics

Tracking the multifarious ultrafast electronic and structural changes occurring in a molecule during a photochemical transformation is a challenging endeavor that benefits from recent experimental and computational progress in time-resolved techniques. Measurements of valence electronic states, which provide a global picture of the bonding structure of the molecule, and core electronic states, which provide insight into the local environment, traditionally require different approaches and are often studied separately. Here, we demonstrate that X-ray pulses from a seeded free-electron laser (FEL) enable the measurement of high-resolution, time-resolved X-ray photoelectron spectra (XPS) that capture weak satellite states resulting from shake-down processes in a valence-excited molecule. This approach effectively combines the advantages of both valence- and core-state investigations. We applied this method to investigate photoexcited CS2 molecules, where the role of internal conversion (IC) and intersystem crossing (ISC) in determining the predissociation dynamics is controversial. We present XPS spectra from photoexcited CS2, obtained at the FERMI FEL. High-resolution measurements, compared to the corresponding spectra obtained from accurate multireference quantum chemical calculations, reveal that shake-down satellite channels are highly sensitive to both valence electronic and geometric changes. Previous studies of the predissociation dynamics have led to uncertain assignments of the branching between singlet and triplet excited states. We derive a propensity rule that demonstrates the spin-selectivity of the shake-downs. This selectivity allows us to unequivocally assign contributions from the bright and dark singlet excited states, with populations tracked along the predissociation dynamic pathway.

Thompson, Henry J. [Univ. of Southampton (United K↗

Extended live-tracking and quantitative characterization of wound healing and cell migration with SiR-Hoechst

Highlights: • SiR-Hoechst is a nuclear dye that enables cell tracking without affecting migration. • Single cell analysis provides multiple migration metrics during wound healing. • Cell density-based report of wound healing is less susceptible to subjective bias. • Cell directionality is an important contributor of early wound recovery. Cell migration is essential to many life processes, including immune response, tissue repair, and cancer progression. A reliable quantitative characterization of the cell migration can therefore aid in the high throughput screening of drug efficacy in wound healing and cancer treatments. In this work, we report what we believe is the first use of SiR-Hoechst for extended live tracking and automated analysis of cell migration and wound healing. We showed through rigorous statistical comparisons that this far-red label does not affect migratory behavior. We observed excellent automated tracking of random cell migration, in which the motility parameters (speed, displacement, path length, directionality ratio, persistence time, and direction autocorrelation) obtained closely match those obtained from manual tracking. We also present an analysis framework to characterize the healing of a scratch wound from the perspective of single cells. The use of SiR-Hoechst is advantageous for the crowded environments in wound healing assays because as long as cell nuclei do not overlap, continuous tracking can be maintained even if there is cell-cell contact. In this paper, we report wound recovery based on the number of cells migrating into the wound over time, normalized by the initial cell count prior to the infliction of the wound. This normalized cell count approach is impervious to operator bias during the arbitration of wound edges and is also robust against variability that arises due to differences in the cell density of different samples. Additional wound healing characteristics were also defined based on the evolution of cell speed and directionality during healing. Not unexpected, the wound healing cells exhibited much higher tendency to maintain the same migratory direction in comparison to the randomly migrating cells. The use of SiR-Hoechst thus greatly simplified the automation of single cell and whole population analysis with high spatial and temporal resolution over extended periods of time.

60 APPLIED LIFE SCIENCES↗

Tracking the origins and drivers of subclonal metastatic expansion in prostate cancer

Tumour heterogeneity in primary prostate cancer is a well-established phenomenon. However, how the subclonal diversity of tumours changes during metastasis and progression to lethality is poorly understood. Here we reveal the precise direction of metastatic spread across four lethal prostate cancer patients using whole-genome and ultra-deep targeted sequencing of longitudinally collected primary and metastatic tumours. We find one case of metastatic spread to the surgical bed causing local recurrence, and another case of cross-metastatic site seeding combining with dynamic remoulding of subclonal mixtures in response to therapy. By ultra-deep sequencing end-stage blood, we detect both metastatic and primary tumour clones, even years after removal of the prostate. As a result, analysis of mutations associated with metastasis reveals an enrichment of TP53 mutations, and additional sequencing of metastases from 19 patients demonstrates that acquisition of TP53 mutations is linked with the expansion of subclones with metastatic potential which we can detect in the blood.

59 BASIC BIOLOGICAL SCIENCES↗

In Situ and Operando Observation of Zinc Moss Growth and Dissolution in Alkaline Electrolyte for Zinc–Air Batteries

As a promising battery technology, zinc–air batteries still face significant challenges, including the formation of a mossy structure on the zinc metal anode in alkaline electrolyte. Because a similar phenomenon also plagues lithium and sodium metal batteries, elucidating its mechanism has important implications for progress in energy storage. Herein, operando X-ray nanotomography was employed to visualize zinc moss growth and dissolution at the individual colony level. By tracking its microstructure evolution, zinc moss was found to display irreversible plating/stripping behavior. While zinc moss exhibits self-limiting growth and zinc deposition occurs mainly in its outer region, zinc dissolution is more uniformly distributed inside the moss colony upon stripping, leading to the formation of “dead” zinc and capacity loss. A direct correlation is established between the moss amount and zinc plating/stripping efficiency. Finally, results from this study offer new insights into mitigating the unstable zinc plating morphology and improving the cycle life of aqueous zinc–air batteries.

36 MATERIALS SCIENCE↗

Seasonally Dependent Future Changes in the U.S. Midwest Hydroclimate and Extremes

This study investigates the responses of the hydroclimate and extremes in the U.S. Midwest to global warming, based on ensemble projections of phase 6 of the Coupled Model Intercomparison Project and the multimodel initial-condition large-ensemble simulations. The precipitation response features a seasonally dependent change with increased precipitation in April–May but reduced precipitation in July–August. In this work, the late-spring wetting is attributed to the enhanced low-level moisture-transporting southerlies, which are induced by regional sea level pressure anomalies linked to the poleward shift of the North American westerly jet (NAWJ). The late-summer drying is attributed to the weakened storm track, which is also linked to the poleward NAWJ shift. The seasonally dependent future changes of the Midwest precipitation are analogous to its climatological seasonal progression, which increases over late spring as the NAWJ approaches the Midwest and decreases over late summer as the NAWJ migrates away. In response to the mean precipitation changes, extremely wet late springs (April–May precipitation above the 99th percentile of the historical period) and extremely dry late summers (below the 1st percentile) will occur much more frequently, implying increased late-spring floods and late-summer droughts. Future warming in the Midwest is amplified in late summer due to the reduced precipitation. With amplified background warming and increased occurrence, future late-summer droughts will be more devastating. Our results highlight that, under a time-invariant poleward jet shift, opposite precipitation changes arise before and after the peak rainy month, leading to substantial increases in the subseasonal extremes. The severity of such climate impacts is obscured in projections of the rainy-season mean.

54 ENVIRONMENTAL SCIENCES↗

Infrastructure-Based Cooperative Perception at a Traffic Intersection: Overview and Challenges: Preprint

Recent advancement in autonomous driving vehicles and V2X communication has attracted increasing attention towards Intelligent Transportation Systems to build a safe and reliable traffic intersection. However, most of the systems are still at the initial stages and require significant progress to become a reality. This paper presents an overview of NREL Infrastructure Perception and Control (IPC) framework which is an open-source track-data fusion engine which takes input from infrastructure-based perception sensors and cooperatively shared messages from Connected Autonomous Vehicles (CAVs) and Connected Vehicle (CVs) and the challenges associated with deploying such cooperative perception framework at a four-way traffic intersection in the city of Colorado Springs, CO, USA. The sensor data is collected by deploying two radars and two LiDAR sensors on the IPC mobile lab and two radars on diagonally opposite traffic poles at the proposed intersection. The sensor output results imply the need for rapid sensor calibration to bring the collective perception to a common coordinate frame, the importance of time synchronization between the sensors in order to capture accurate spatial and temporal alignment of the objects, and the need for a health monitoring system with fail safe closed-loop detection model for real-time deployment.

camera↗

Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations

Recent advances in scanning transmission electron and scanning probe microscopies have opened unprecedented opportunities in probing the materials structural parameters and various functional properties in real space with an angstrom-level precision. This progress has been accompanied by exponential increase in the size and quality of datasets produced by microscopic and spectroscopic experimental techniques. These developments necessitate adequate methods for extracting relevant physical and chemical information from the large datasets, for which a priori information on the structures of various atomic configurations and lattice defects is limited or absent. Here we demonstrate an application of deep neural networks to extracting information from atomically resolved images including location of the atomic species and type of defects. We develop a “weakly-supervised” approach that uses information on the coordinates of all atomic species in the image, extracted via a deep neural network, to identify a rich variety of defects that are not part of an initial training set. We further apply our approach to interpret complex atomic and defect transformation, including switching between different coordination of silicon dopants in graphene as a function of time, formation of peculiar silicon dimer with mixed 3-fold and 4-fold coordination, and the motion of molecular “rotor”. In conclusion, this deep learning based approach resembles logic of a human operator, but can be scaled leading to significant shift in the way of extracting and analyzing information from raw experimental data.

36 MATERIALS SCIENCE↗

Spectral Methods in Time-dependent Data Analysis

We aim to create a new model for time-dependent data analysis, named dynamical learning, that integrates data-driven manifold learning techniques with operator-theoretic methods from dynamical systems theory. This approach has the potential to deliver more efficient methods for analyzing time-dependent data, such as video streams, by naturally separating out the temporal and spatial features of the data. We aim to apply the newly developed methods to video surveillance data related to Sandia mission applications, and particularly focus on the problems of image segmentation and object tracking. This project ended early due to the departure of the PI from Sandia about 18 months into the project. Therefore, this document reports on partial progress towards the initial goals of the project. In addition, this document reports on part of the work conducted during the project; see the Appendix for a summary of all the work conducted during the 18 months.

97 MATHEMATICS AND COMPUTING↗

Photovoltaic System Pricing Trends: Historical, Recent, and Near-Term Projections 2015 Edition

This is the fourth edition in an annual briefing prepared jointly by LBNL and NREL intended to provide a high-level overview of historical, recent, and projected near-term PV system pricing trends in the United States. The briefing draws on several ongoing research activities at the two labs, including LBNL's annual Tracking the Sun report series, NREL's bottom-up PV cost modeling, and NREL's synthesis of PV market data and projections. The briefing examines progress in PV price reductions to help DOE and other PV stakeholders manage the transition to a market-driven PV industry, and integrates different perspectives and methodologies for characterizing PV system pricing, in order to provide a broader perspective on underlying trends within the industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Direct numerical simulation of reactor two-phase flows enabled by high-performance computing

Nuclear reactor two-phase flows remain a great engineering challenge, where the high-resolution two-phase flow database which can inform practical model development is still sparse due to the extreme reactor operation conditions and measurement difficulties. Owing to the rapid growth of computing power, the direct numerical simulation (DNS) is enjoying a renewed interest in investigating the related flow problems. A combination between DNS and an interface tracking method can provide a unique opportunity to study two-phase flows based on first principles calculations. More importantly, state-of-the-art high-performance computing (HPC) facilities are helping unlock this great potential. This paper reviews the recent research progress of two-phase flow DNS related to reactor applications. The progress in large-scale bubbly flow DNS has been focused not only on the sheer size of those simulations in terms of resolved Reynolds number, but also on the associated advanced modeling and analysis techniques. Specifically, the current areas of active research include modeling of sub-cooled boiling, bubble coalescence, as well as the advanced post-processing toolkit for bubbly flow simulations in reactor geometries. A novel bubble tracking method has been developed to track the evolution of bubbles in two-phase bubbly flow. Also, spectral analysis of DNS database in different geometries has been performed to investigate the modulation of the energy spectrum slope due to bubble-induced turbulence. In addition, the single-and two-phase analysis results are presented for turbulent flows within the pressurized water reactor (PWR) core geometries. The related simulations are possible to carry out only with the world leading HPC platforms. Furthermore, these simulations are allowing more complex turbulence model development and validation for use in 3D multiphase computational fluid dynamics (M-CFD) codes.

97 MATHEMATICS AND COMPUTING↗

Monsoon Extremes: Impacts, Metrics, and Synoptic-Scale Drivers

This project was led by UC Berkeley with a subcontract to UC Davis and collaborative funding at the Lawrence Berkeley National Lab (LBNL). It produced new understanding of transient atmospheric disturbances in monsoon regions, the precipitation extremes they produce, and the sensitivity of precipitation and monsoon winds to fine-scale orography (i.e., the narrow mountain ranges that are difficult to represent in conventional Earth system models). Fundamental research undertaken as part of this project led to discovery of new mechanisms that control the generation of extreme weather events and that govern the spatial patterns of intense precipitation in monsoon climates—including the North American monsoon. These research accomplishments are summarized below and documented in a series of 23 publications, 20 of which were led by project personnel (the others were collaborative work led by staff of other projects). One of the publications produced by this project was in Nature, where it was selected for the main cover image, and another was in PNAS. The project also produced two datasets and a tracking algorithm, both of which are publicly available and listed below. The project trained three Ph.D. students and four postdoctoral scientists, the vast majority of whom have progressed to more advanced positions in their scientific careers. Although the university funding for this project ended in 2022, the LBNL component of the project proceeded for almost one year longer; this report is being provided after completion of all components of the project.

54 ENVIRONMENTAL SCIENCES↗

HOMOLOGOUS SOLAR EVENTS ON 2011 JANUARY 27: BUILD-UP AND PROPAGATION IN A COMPLEX CORONAL ENVIRONMENT

In spite of the wealth of imaging observations at the extreme-ultraviolet (EUV), X-ray, and radio wavelengths, there are still relatively few cases where all of the imagery is available to study the full development of a coronal mass ejection (CME) event and its associated shock. The aim of this study is to contribute to the understanding of the role of the coronal environment in the development of CMEs and the formation of shocks, and their propagation. We have analyzed the interactions of a couple of homologous CME events with ambient coronal structures. Both events were launched in a direction far from the local vertical, and exhibited a radical change in their direction of propagation during their progression from the low corona into higher altitudes. Observations at EUV wavelengths from the Atmospheric Imaging Assembly instrument on board the Solar Dynamic Observatory were used to track the events in the low corona. The development of the events at higher altitudes was followed by the white-light coronagraphs on board the Solar and Heliospheric Observatory . Radio emissions produced during the development of the events were well recorded by the Nançay solar instruments. Thanks to their detection of accelerated electrons, the radio observations are an important complement to the EUV imaging. They allowed us to characterize the development of the associated shocks, and helped to unveil the physical processes behind the complex interactions between the CMEs and ambient medium (e.g., compression, reconnection).

79 ASTRONOMY AND ASTROPHYSICS↗

Metering Plan: Intelligent Operational Strategies Through Enhanced Metering Systems

The Sustainability Program at Pacific Northwest National Laboratory (PNNL) has adopted a “triple-bottom-line” approach of environmental stewardship, social responsibility, and economic prosperity to its operations. Metering at PNNL works in support of all three, specifically to measure and inform building energy use and greenhouse gas emissions and minimize water use. The foundation for metering at PNNL is a core goal set, which consists of four objectives: providing accurate data without interruption, analyzing data while it is still new, providing actionable recommendations to operations management, and ensuring PNNL’s compliance with contract metering requirements. These core objectives guide the decisions that we make during annual planning and as we operate throughout the year. This 2016 edition of the Metering Plan conveys the metering practices for and vision of the Sustainability Program. Changes in this plan from the 2015 edition include updated tables and an enhanced discussion on energy tracking systems used at PNNL. This plan also discusses updated benchmarking strategies using PNNL’s graphics and analytics tool, BuildingOS by Lucid Design Group. This plan presents our progress toward the metering goals shared by all federal agencies and highlights our successful completion of metering requirements. Currently, PNNL is fully compliant with the applicable legislative and Executive Order metering requirements. PNNL’s approach to the installation of new meters will be discussed. Perhaps most importantly, this plan details the analysis techniques utilized at PNNL that rely on the endless streams of data newly available as a result of increased meter deployment over the last several years. Previous Metering Plans have documented specific meter connection schemes as PNNL focused on deploying meters in a first step toward managing energy and water use. This plan serves not only to highlight PNNL’s successful completion of agency metering goals, but also can be used as a guideline for meter installation and data analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗