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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The ATLAS Fast TracKer system

The ATLAS Fast TracKer (FTK) was designed to provide full tracking for the ATLAS high-level trigger by using pattern recognition based on Associative Memory (AM) chips and fitting in high-speed field programmable gate arrays. The tracks found by the FTK are based on inputs from all modules of the pixel and silicon microstrip trackers. The as-built FTK system and components are described, as is the online software used to control them while running in the ATLAS data acquisition system. Also described is the simulation of the FTK hardware and the optimization of the AM pattern banks. An optimization for long-lived particles with large impact parameter values is included. A test of the FTK system with the data playback facility that allowed the FTK to be commissioned during the shutdown between Run 2 and Run 3 of the LHC is reported. The resulting tracks from part of the FTK system covering a limited $\eta$-$\phi$ region of the detector are compared with the output from the FTK simulation. It is shown that FTK performance is in good agreement with the simulation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

The role of substrate on stabilizing new phases of two-dimensional tin

In this work, we investigate the role of substrates in determining the morphologies and electronic structures of two-dimensional (2D) Sn. Here, we use Ir(111) and 2D hexagonal boron nitride (h-BN) predeposited on Ir(111) as substrates. The latter contains Moiré patterns with varying binding strength between h-BN and metal. Using scanning tunneling microscopy and first-principles calculations, we reveal the distinct morphologies of 2D Sn on different substrates. Of particular interest, we discover a new √7 × √7 Sn phase, originating from the local charge transfer with metal beneath the “decoupling” h-BN monolayer at the strongly interacting Moiré region. To the best of our knowledge, this work demonstrates, for the first time via combined experimental and theoretical approach, that new 2D Sn phases can be achieved using Moiré patterns on h-BN/metal. This finding should be instrumental in the development of 2D-based topological materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Influence of the Turing instability on the motion of domain boundaries

Turing's theory of pattern formation has provided crucial insights into the behavior of various biological, geographical, and chemical systems over the last few decades. Existing studies have focused on moving-boundary Turing systems for which the motion of the boundary is prescribed by an external agent. In this paper, we present an extension of this theory to a class of systems in which the front motion is governed by the physical processes that occur within the domain. Biological systems exhibiting apically dominant growth and corrosion of metals and alloys highlight some of the noteworthy examples of such systems. In this study, we characterize the nature of interaction between the moving front and the Turing-instability for both an activator-inhibitor and an activator-substrate model. Behavioral regimes of periodic, as well as nonperiodic (nonconstant), growth rates are obtained. Furthermore, the trends in the first show striking similarities with the cyclic-boundary-kinetics observed in experimental systems. In general, a stationary, periodic structure is also left behind the moving front. If the periodicity of the boundary kinetics agrees with the allowed range of the stable-periodic solutions, the pattern formed tends to persist. Lastly, it evolves to a nearby energy-minimum either by peak-splitting, peak-decay, or by settling down to a spatially homogeneous state.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Iterative Learning Control for Video-rate Atomic Force Microscopy

We present a control scheme for video-rate atomic force microscopy with rosette pattern. The controller structure involves a feedback internal-model-based controller and a feedforward iterative learning controller. The iterative learning controller is designed to improve tracking performance of the feedback-controlled scanner by rejecting the repetitive disturbances arising from the system nonlinearities. We investigate the performance of two inversion techniques for constructing the learning filter. We conduct tracking experiments using a two-degree-of-freedom microelectromechanical system (MEMS) nanopositioner at frame rates ranging from 5 to 20 frames per second. Furthermore, the results reveal that the algorithm converges rapidly and the iterative learning controller significantly reduces both the transient and steady-state tracking errors. We acquire and report a series of high-resolution time-lapsed video-rate AFM images with the rosette pattern.

42 ENGINEERING↗
DOE OSTI2022

Inferring plant–plant interactions using remote sensing

Rapid technological advancements and increasing data availability have improved the capacity to monitor and evaluate Earth's ecology via remote sensing. However, remote sensing is notoriously ‘blind’ to fine-scale ecological processes such as interactions among plants, which encompass a central topic in ecology. Here, we discuss how remote sensing technologies can help infer plant–plant interactions and their roles in shaping plant-based systems at individual, community and landscape levels. At each of these levels, we outline the key attributes of ecosystems that emerge as a product of plant–plant interactions and could possibly be detected by remote sensing data. We review the theoretical bases, approaches and prospects of how inference of plant–plant interactions can be assessed remotely. At the individual level, we illustrate how close-range remote sensing tools can help to infer plant–plant interactions, especially in experimental settings. At the community level, we use forests to illustrate how remotely sensed community structure can be used to infer dominant interactions as a fundamental force in shaping plant communities. At the landscape level, we highlight how remotely sensed attributes of vegetation states and spatial vegetation patterns can be used to assess the role of local plant–plant interactions in shaping landscape ecological systems. Synthesis . Remote sensing extends the domain of plant ecology to broader and finer spatial scales, assisting to scale ecological patterns and search for generic rules. Robust remote sensing approaches are likely to extend our understanding of how plant–plant interactions shape ecological processes across scales—from individuals to landscapes. Combining these approaches with theories, models, experiments, data-driven approaches and data analysis algorithms will firmly embed remote sensing techniques into ecological context and open new pathways to better understand biotic interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The global decline in the sensitivity of vegetation productivity to precipitation from 2001 to 2018

The sensitivity of vegetation productivity to precipitation (S ppt ) is a key metric for understanding the variations in vegetation productivity under changing precipitation and predicting future changes in ecosystem functions. However, a comprehensive assessment of S ppt over all the global land is lacking. Here, we investigated spatial patterns and temporal changes of S ppt across the global land from 2001 to 2018 with multiple streams of satellite observations. We found consistent spatial patterns of S ppt with different satellite products: S ppt was highest in dry regions while low in humid regions. Grassland and shrubland showed the highest S ppt , and evergreen needle-leaf forest and wetland showed the lowest. Temporally, S ppt showed a generally declining trend over the past two decades (p < .05), yet with clear spatial heterogeneities. The decline in S ppt was especially noticeable in North America and Europe, likely due to the increase in precipitation. In central Russia and Australia, however, S ppt showed an increasing trend. Biome-wise, most ecosystem types exhibited significant decrease in S ppt , while grassland, evergreen broadleaf forest, and mixed forest showed slight increases or non-significant changes in S ppt . Our finding of the overall decline in S ppt implies a potential stabilization mechanism for ecosystem productivity under climate change. However, the revealed S ppt increase for some regions and ecosystem types, in particular global grasslands, suggests that grasslands might be increasingly vulnerable to climatic variability with continuing global climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

I/O in Machine Learning Applications on HPC Systems: A 360-degree Survey

Growing interest in Artificial Intelligence (AI) has resulted in a surge in demand for faster methods of Machine Learning (ML) model training and inference. This demand for speed has prompted the use of high performance computing (HPC) systems that excel in managing distributed workloads. Because data is the main fuel for AI applications, the performance of the storage and I/O subsystem of HPC systems is critical. In the past, HPC applications accessed large portions of data written by simulations or experiments or ingested data for visualizations or analysis tasks. ML workloads perform small reads spread across a large number of random files. This shift of I/O access patterns poses several challenges to modern parallel storage systems. In this paper, we survey I/O in ML applications on HPC systems, and target literature within a 6-year time window from 2019 to 2024. We define the scope of the survey, provide an overview of the common phases of ML, review available profilers and benchmarks, examine the I/O patterns encountered during offline data preparation, training, and inference, and explore I/O optimizations utilized in modern ML frameworks and proposed in recent literature. Lastly, we seek to expose research gaps that could spawn further R&D.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Multiscale Interactions between Local Short- and Long-Term Spatio-Temporal Mechanisms and Their Impact on California Wildfire Dynamics

California has experienced a surge in wildfires, prompting research into contributing factors, including weather and climate conditions. This study investigates the complex, multiscale interactions between large-scale climate patterns, such as the Boreal Summer Intraseasonal Oscillation (BSISO), El Niño Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO) and their influence on moisture and temperature fluctuations, and wildfire dynamics in California. The combined impacts of PDO and BSISO on intraseasonal fire weather changes; the interplay between fire weather index (FWI), relative humidity, vapor pressure deficit (VPD), and temperature in assessing wildfire risks; and geographical variations in the relationship between the FWI and climatic factors within California are examined. The study employs a multi-pronged approach, analyzing wildfire frequency and burned areas alongside climate patterns and atmospheric conditions. The findings reveal significant variability in wildfire activity across different climate conditions, with heightened risks during specific BSISO phases, La-Niña, and cool PDO. The influence of BSISO varies depending on its interaction with PDO. Temperature, relative humidity, and VPD show strong predictive significance for wildfire risks, with significant relationships between FWI and temperature in elevated regions (correlation, r > 0.7, p ≤ 0.05) and FWI and relative humidity along the Sierra Nevada Mountains (r ≤ -0.7, p ≤ 0.05).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Changes in Hydropower Resource Operations Following Participation in the CAISO Energy Imbalance Market - A Case Study

Portland General Electric (PGE), an investor-owned electric utility serving nearly 900,000 customers in 51 Oregon cities, joined Western Energy Imbalance Market (EIM) – a California Independent System Operator (CAISO) platform for sharing cleaner and more efficient generation resources among multiple states in the Western U.S. While participation in EIM brings a new set of economic opportunities for PGE by capturing flexibility needs in the market, it also changes operational patterns (e.g., more frequent start/stop, off-nominal power output, and ramping) of PGE’s conventional generation fleet, including hydropower units. With 492 MW of hydropower capacity, which constitutes 15\% of PGE’s generation mix, it is important for PGE (as any other EIM-participant utility) to understand how participation in EIM impacts its hydropower assets, and how a techno-economically sustainable operation of those assets could be accomplished. In this paper, a case study is performed with PGE's hydropower generation facilities to assess and quantify EIM-participation driven changes in hydropower operational patterns.

hydropower, operational patterns, energy imbalance↗
DOE OSTI2024

Cancer Incidence Trends in Successive Social Generations in the US

Importance: The incidence of some cancers in the US is increasing in younger age groups, but underlying trends in cancer patterns by birth year remain unclear. Objective: To estimate cancer incidence trends in successive social generations. Design, Setting, and Participants: In this cohort study, incident invasive cancers were ascertained from the Surveillance, Epidemiology, and End Results (SEER) program’s 13-registry database (November 2020 submission, accessed August 14, 2023). Invasive cancers diagnosed at ages 35 to 84 years during 1992 to 2018 within 152 strata were defined by cancer site, sex, and race and ethnicity. Exposure: Invasive cancer. Main Outcome and Measures: Stratum-specific semiparametric age-period-cohort (SAGE) models were fitted and incidence per 100 000 person-years at the reference age of 60 years was calculated for single-year birth cohorts from 1908 through 1983 (fitted cohort patterns [FCPs]). The FCPs and FCP incidence rate ratios (IRRs) were compared by site for Generation X (born between 1965 and 1980) and Baby Boomers (born between 1946 and 1964). Results: A total of 3.8 million individuals with invasive cancer (51.0% male; 8.6% Asian or Pacific Islander, 9.5% Hispanic, 10.4% non-Hispanic Black, and 71.5% non-Hispanic White) were included in the analysis. In Generation X vs Baby Boomers, FCP IRRs among women increased significantly for thyroid (2.76; 95% CI, 2.41-3.15), kidney (1.99; 95% CI, 1.70-2.32), rectal (1.84; 95% CI, 1.52-2.22), corpus uterine (1.75; 95% CI, 1.40-2.18), colon (1.56; 95% CI, 1.27-1.92), and pancreatic (1.39; 95% CI, 1.07-1.80) cancers; non-Hodgkins lymphoma (1.40; 95% CI, 1.08-1.82); and leukemia (1.27; 95% CI, 1.03-1.58). Among men, IRRs increased for thyroid (2.16; 95% CI, 1.87-2.50), kidney (2.14; 95% CI, 1.86-2.46), rectal (1.80; 95% CI, 1.52-2.12), colon (1.60; 95% CI, 1.32-1.94), and prostate (1.25; 95% CI, 1.03-1.52) cancers and leukemia (1.34; 95% CI, 1.08-1.66). Lung (IRR, 0.60; 95% CI, 0.50-0.72) and cervical (IRR, 0.71; 95% CI, 0.57-0.89) cancer incidence decreased among women, and lung (IRR, 0.51; 95% CI, 0.43-0.60), liver (IRR, 0.76; 95% CI, 0.63-0.91), and gallbladder (IRR, 0.85; 95% CI, 0.72-1.00) cancer and non-Hodgkins lymphoma (IRR, 0.75; 95% CI, 0.61-0.93) incidence decreased among men. For all cancers combined, FCPs were higher in Generation X than for Baby Boomers because gaining cancers numerically overtook falling cancers in all groups except Asian or Pacific Islander men. Conclusions and Relevance: In this model-based cohort analysis of incident invasive cancer in the general population, decreases in lung and cervical cancers in Generation X may be offset by gains at other sites. Generation X may be experiencing larger per-capita increases in the incidence of leading cancers than any prior generation born in 1908 through 1964. On current trajectories, cancer incidence could remain high for decades.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Pulmonary ACE2 expression in neonatal and adult rats

Children show a distinct presentation of COVID‐19, characterized by a lower incidence and mild phenotype, but the reason for this is still unknown. The angiotensin‐converting enzyme 2 (ACE2) functions as the primary cell entry receptor for Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and is thought to cause distinct clinical features between children and old people. The primary purpose of this study was to determine whether differences exist in the level of expression and distribution of ACE2 between neonatal and adult rat lungs. The lung tissues from rats of various ages were used to investigate the expression patterns of ACE2. Western blot, immunohistochemistry, and immunofluorescence were used to quantify or identify the localization of ACE2 in rat lungs. ACE2 was homogenously expressed in fewer alveolar type II (AT2) cells in the neonatal lung, with no polarization to the alveolar space and additional expression in pulmonary endothelium when compared to adult rat lungs. These findings suggest that the patterns of ACE2 distribution and cellular localization in rat lungs change with age.

Zhao, Depeng↗
DOE OSTI2022

A Reactive Inkjet Printing Process for Fabricating Biodegradable Conductive Zinc Structures

A novel reactive inkjet printing (RIJ) process for fabricating environmentally benign, conductive zinc structures on biodegradable substrates is reported. A precursor consisting of oxidized zinc microparticles is formulated into a viscous ink for high‐resolution, high‐repeatability screen printing. A single RIJ process is performed to selectively dispense an acid‐based oxide etching agent onto the screen‐printed zinc ink to significantly improve its electrical conductivity, up to 4 × 10 4 S m −1 . The RIJ process enables precise control of the amount of deposited etching agent, allowing control of conductivity and avoiding damage caused by excessive acid exposure. The RIJ process deposits the etching agent selectively on the screen‐printed, water‐soluble zinc patterns, thus preserving the print fidelity by avoiding ink smearing that can occur when using a blanket treatment such as submersion. A printed biodegradable antenna with a minimum feature size of 500 μm for use with a batteryless radio frequency identification (RFID) chip is fabricated as demonstration. Due to the higher ink conductivity and improved pattern fidelity, the antenna fabricated by the RIJ process shows a ≈2.2× increase in reading distance compared with a similar antenna that is screen printed and activated using a drop‐casting process.

Sui, Yongkun↗
DOE OSTI2024

The Toughness of Interlocking Metasurfaces

Interlocking metasurfaces (ILMs) are arrays of autogenous latching unit cells patterned across a surface. These create structural joints similar to bioinspired suture joints but patterned over a 2D surface rather than a 1D seam. This enables ILMs to be an alternative to conventional joining technologies such as bolts, welds, and adhesives. However, compared to conventional joining methods, relatively little is known of the engineering considerations for designing structural ILMs. Herein, the interfacial toughness of an archetypal ILM is examined for the first time. Under the conditions studied here, the ILM is substantially tougher than the material from which it is made, in this case, exhibiting up to a 50% increase in interfacial crack initiation energy over the solid base material, a photocured 3D‐printed polymer. Through experimental tests using in‐situ digital image correlation along with complementary computational analyses, the mechanism of toughening in the ILM structure and the origins of toughness anisotropy are revealed. The increase in toughness is associated with cross‐cell interactions, that is, load‐sharing across unit cells, which give rise to a finite process zone length with different effective material properties. In this way, ILM toughening is analogous to crack blunting in ductile materials or fiber bridging in composites; yet here, the ILM is composed of a single‐phase base material and so the architected toughening is geometric in nature and hence amenable to future topological optimization.

fracture↗
DOE OSTI2021

Orientational Ordering within Semiconducting Polymer Fibrils

Abstract Due to a general paucity of suitable characterization methods, the internal orientational ordering of polymer fibrils has rarely been measured despite its importance particularly for semi‐conducting polymers. An emerging tool with sensitivity to bond orientation is polarized resonant soft X‐ray scattering (P‐RSoXS). Here, P‐RSoXS reveals the molecular arrangement within fibrils (if type I or type II fibrils), the extent of orientation in the fibril crystal, and an explicit crystal‐amorphous interphase. Neat films as well as binary blends with a fullerene derivative are characterized for three different polymers, that are prototypical materials widely used in organic electronics applications. Anisotropic P‐RSoXS patterns reveal two different fibril types. Analysis of the q ‐dependence of the anisotropy from simulated and experimental scattering patterns reveal that neat polymer fibrillar systems likely comprise more than two phases, with the third phase in addition to crystal and amorphous likely being an interphase with distinct density and orientation. Intriguingly, the fibril type correlates to the H‐ or J‐aggregation signature in ultraviolet‐visible (UV–vis) spectroscopy, revealing insight into the fibril formation. Together, the results will open the door to develop more sophisticated structure‐function relationships between chemical design, fibril type, formation pathways and kinetics, interfacial ordering, and eventually device functions.

Mukherjee, Subhrangsu↗
DOE OSTI2022

Deep-Learning-Enabled Crack Detection and Analysis in Commercial Lithium-Ion Battery Cathodes

We report in Li-ion batteries, the mechanical degradation initiated by micro cracks is one of the bottlenecks for enhancing the performance. Quantifying the crack formation and evolution in complex composite electrodes can provide important insights into electrochemical behaviors under prolonged and/or aggressive cycling. However, observation and interpretation of the complicated crack patterns in battery electrodes through imaging experiments are often time-consuming, labor intensive, and subjective. Herein, a deep learning-based approach is developed to extract the crack patterns from nanoscale hard X-ray holo-tomography data of a commercial 18650-type battery cathode. Efficient and effective quantification of the damage heterogeneity with automation and statistical significance is demonstrated. The crack characteristics are further associated with the active particles’ packing densities and a potentially viable architectural design is discussed for suppressing the structural degradation in an industry-relevant battery configuration.

25 ENERGY STORAGE↗
DOE OSTI2024

Charge‐Programmable Photopolymers for 3D Electronics via Additive Manufacturing

Charge‐programmed 3D printing enables the fabrication of 3D electronics with lightweight and high precision via selective patterning of metals. This selective metal deposition is catalyzed by Pd nanoparticles that are specifically immobilized onto the charged surface and promises to fabricate a myriad of complex electronic devices with self‐sensing, actuation, and structural elements assembled in a designed 3D layout. However, the achievable property space and the material‐performance correlation of the charge‐programmed printing remain unexplored. Herein, a series of photo‐curable resins are designed for unveiling how the charge and crosslink densities synergistically impact the nanocatalyst‐guided selective deposition in catalytic efficiency and properties of the 3D printed charge‐programmed architectures, leading to high‐quality 3D patterning of solid and liquid metals. The findings offer a wide tunability of the structural properties of the printed electronics, ranging from stiff to extreme flexibility. Capitalizing on these results, the printing and successful application of an ultralight‐weight and deployable 3D multi‐layer antenna system operating at an ultrahigh‐frequency of 19 GHz are demonstrated.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Scalable Nanoimprint Manufacturing of Functional Multilayer Metasurface Devices

Optical metasurfaces, consisting of subwavelength-scale meta-atom arrays, hold great promise of overcoming the fundamental limitations of conventional optics. Due to their structural complexity, metasurfaces usually require high-resolution yet slow and expensive fabrication processes. Here, using a metasurface polarimetric imaging device as an example, the photonic structures and the Nanoimprint lithography (NIL) processes are designed, creating two separate NIL molds over a patterning area of > 20 mm2 with designed Moiré alignment markers by electron-beam writing, and further subsequently integrate silicon and aluminum metasurface structures on a chip. Uniquely, the silicon and aluminum metasurfaces are fabricated by using the nanolithography and 3D pattern-transfer capabilities of NIL, respectively, achieving nanometer-scale linewidth uniformity, sub-200 nm translational overlay accuracy, and <0.017 rotational alignment error while significantly reducing fabrication complexity and surface roughness. Here, the micro-sized multilayer metasurfaces have high circular polarization extinction ratios as large as ≈20 and ≈80 in blue and red wavelengths. Further, the metasurface chip-integrated CMOS imager demonstrates high accuracy in broad-band, full Stokes parameter analysis in the visible wavelength ranges and single-shot polarimetric imaging. This novel, NIL-based, multilayered nanomanufacturing approach is applicable to the scalable production of large-area functional structures for ultra-compact optic, electronic, and quantum devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nanoscale Editing of Multi and Single Layer Tungsten Disulfide via Gas‐Assisted Focused Electron Beam Induced Etching for Device Prototyping

Focused electron beam induced etching (FEBIE) with XeF 2 (xenon difluoride) precursor is conducted on multi-layer exfoliated WS 2 (tungsten disulfide) and monolayer WS 2 grown by chemical vapor deposition (CVD). The films are characterized by atomic force microscopy (AFM) and Raman and photoluminescence (PL) spectroscopy post-etching. The etch rates/efficiencies are reported as a function of electron beam energy, current, dwell time, and XeF 2 pressure. Bulk film Raman spectra are unchanged post-FEBIE, indicating minimal subsurface damage. Monolayer WS 2 shows a decrease in Raman and PL intensity post-FEBIE, with a dose-to-clear of ≈2 nC µm −2 . The study reveals regimes affected by the various mass transport contributions such as refresh time and the ratio of electrons/XeF 2 . Spontaneous etching was discovered during FEBIE of large patterned areas due to the long frame/refresh times. Density functional theory and ab initio molecular dynamics simulations compares desorption of SF x and WF x molecules from pristine WS 2 basal planes and pore edges, revealing the spontaneous etching is consistent with etching of partially etched monolayers during each frame. Single-line etching width of 21 nm, and patterning flakes into 100 nm wide channels are demonstrated. In conclusion, this work demonstrates the possibility of editing WS 2 flakes into electronic devices of arbitrary dimensions for semiconductor applications.

2D materials↗