Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Feature Space”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47

Design and construction of the CMS Outer Tracker for the Phase-2 Upgrade

The High Luminosity LHC (HL-LHC) is expected to deliver an integrated luminosity of $3000-4000\;$fb$^{-1}$ after 10 years of operation with peak instantaneous luminosity reaching about $5-7.5\times10^{34}$cm$^{-2}$s$^{-1}$. During Long Shutdown 3, several components of the CMS detector will undergo major changes, called Phase-2 upgrades, to be able to operate in the challenging environment of the HL-LHC. The current CMS silicon strip tracker has to be replaced with a new detector. The Phase-2 Outer Tracker (OT) will have high radiation tolerance, higher granularity and the capability to handle higher data rates. Another key feature of the OT will be to provide tracking information to the Level-1 trigger, allowing trigger rates to be kept at a sustainable level without sacrificing physics potential. For this, the OT will be made out of modules which have two closely spaced sensors read out by front-end ASICs, which can correlate hits in the two sensors creating short track segments, called stubs. The stubs will be used for tracking in the L1 track finder. In this contribution, the design of the CMS Phase-2 OT, the technological choices and first results with prototype devices are reported.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Geochemistry of Mars with Laser-Induced Breakdown Spectroscopy (LIBS): ChemCam, SuperCam, and MarSCoDe

Laser-induced breakdown spectroscopy (LIBS) has been used to explore the chemistry of three regions of Mars on respective missions by NASA and CNSA, with CNES contributions. All three LIBS instruments use ~100 mm diameter telescopes projecting pulsed infrared laser beams of 10–14 mJ to enable LIBS at 2–10 m distances, eliminating the need to position the rover and instrument directly onto targets. Over 1.3 million LIBS spectra have been used to provide routine compositions for eight major elements and several minor and trace elements on >3000 targets on Mars. Onboard calibration targets common to all three instruments allow careful intercomparison of results. Operating over thirteen years, ChemCam on Curiosity has explored lacustrine sediments and diagenetic features in Gale crater, which was a long-lasting (>1 My) lake during Mars’ Hesperian period. SuperCam on Perseverance is exploring the ultramafic igneous floor, fluvial–deltaic features, and the rim of Jezero crater. MarSCoDe on the Zhurong rover investigated for one year the local blocks, soils, and transverse aeolian ridges of Utopia Planitia. The pioneering work of these three stand-off LIBS instruments paves the way for future space exploration with LIBS, where advantages of light-element (H, C, N, O) quantification can be used on icy regions.

47 OTHER INSTRUMENTATION↗

Background-Aware 3-D Point Cloud Segmentation With Dynamic Point Feature Aggregation

With the proliferation of LiDAR sensors and 3-D vision cameras, 3-D point cloud analysis has attracted significant attention in recent years. In this article, we propose a novel 3-D point cloud learning network, referred to as dynamic point feature aggregation network (DPFA-Net), by selectively performing the neighborhood feature aggregation (FA) with dynamic pooling and an attention mechanism. DPFA-Net has two variants for semantic segmentation and classification of 3-D point clouds. As the core module of the DPFA-Net, we propose an FA layer, in which features of the dynamic neighborhood of each point are aggregated via a self-attention mechanism. In contrast to other segmentation models, which aggregate features from fixed neighborhoods, our approach can aggregate features from different neighbors in different layers providing a more selective and broader view to the query points and focusing more on the relevant features in a local neighborhood. In addition, to further improve the performance of semantic segmentation, we exploit the background–foreground (BF) information and present two novel approaches, namely, two-stage BF-Net and BF regularization. Experimental results show that the proposed DPFA-Net achieves the state-of-the-art overall accuracy score of 89.22% for semantic segmentation on the Stanford large-scale 3-D Indoor Spaces (S3DIS) dataset and provides consistently satisfactory performance across different tasks of semantic segmentation, part segmentation, and 3-D object classification. Furthermore, our model achieves 93.1% accuracy on the ModelNet40 dataset and provides a mean shape intersection-over-union (IoU) value of 85.5% for part segmentation on the ShapeNet-Part dataset. It is a also computationally more efficient compared to other methods.

3-D↗

Uncovering novel liquid organic hydrogen carriers: a systematic exploration of chemical compound space using cheminformatics and quantum chemical methods

We present a comprehensive, in silico-based discovery approach to identifying novel liquid organic hydrogen carrier (LOHC) candidates using cheminformatics methods and quantum chemical calculations. We screened over 160 billion molecules from ZINC15 and GDB-17 chemical databases for structural similarity to known LOHCs and employed a data-driven selection criterion connecting molecular features with dehydrogenation enthalpy. This scoring criterion effectively predicts dehydrogenation enthalpies from SMILES strings, streamlining the LOHC screening process. After rigorous screening and down-selection, we compiled a database of 3000 dehydrogenation reactions for the most promising LOHC candidates, setting the stage for future selection based on kinetics and catalysis. This work demonstrates the significant impact of integrating quantum chemistry and cheminformatics in materials discovery, accelerating the selection process while reducing experimental efforts and time. By proposing new molecules as prospective LOHC candidates, our study provides a valuable resource for researchers and engineers in the development of advanced LOHC systems and showcases a successful approach for high-throughput discovery, contributing to more efficient and sustainable energy storage solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High- χ diblock copolymers containing poly(vinylpyridine- N -oxide) segments

Block copolymers exhibiting an enhanced segregation strength due to an underlying high Flory–Huggins interaction parameter (high χ) have attracted considerable attention because of their potential of forming microphase-separated domains with very small feature sizes (<10 nm) useful for next-generation lithography. Here, we report the synthesis, characterization, and self-assembly of poly(styrene)- block -poly(2-vinylpyridine N -oxide) (PS- b -P2VPNO) and poly(styrene)- block -poly(4-vinylpyridine N -oxide) (PS- b -P4VPNO) block copolymers. These PS- b -PVPNOs were obtained from the oxidation of their precursors, poly(styrene)- block -poly(2-vinylpyridine) (PS- b -P2VP) and poly(styrene)- block -poly(4-vinylpyridine) (PS- b -P4VP), respectively. The PS- b -PVPNOs exhibit an enhanced segregation as revealed by ordered cylindrical and lamellar structures in the sub-10 nm scale from copolymers with relatively low molecular weight. The morphologies and periodicities of the ordered structures were determined by small-angle X-ray scattering, while atomic-force microscopy was used to image the self-assembly in thin films. Estimates of the changes in disorder–order transition temperature and domain spacing are derived from a theory based on the effects of dipolar interactions. All the experimentally observed morphological changes resulting from the oxidation of P2VP and P4VP precursors can be qualitatively explained in terms of an increased dipole moment of vinylpyridine N -oxide segments. Therefore, our results demonstrate that PVPNO based block copolymers are versatile candidates toward nanopatterned structures with small feature sizes critical for the future microelectronics industry and beyond.

36 MATERIALS SCIENCE↗

The Hubble Space Telescope's Near-UV and Optical Transmission Spectrum of Earth as an Exoplanet

We observed the 2019 January total lunar eclipse with the Hubble Space Telescope’s STIS spectrograph to obtain the first near-UV (1700–3200 Å) observation of Earth as a transiting exoplanet. The observatories and instruments that will be able to perform transmission spectroscopy of exo-Earths are beginning to be planned, and characterizing the transmission spectrum of Earth is vital to ensuring that key spectral features (e.g., ozone, or O{sub 3}) are appropriately captured in mission concept studies. O{sub 3} is photochemically produced from O{sub 2}, a product of the dominant metabolism on Earth today, and it will be sought in future observations as critical evidence for life on exoplanets. Ground-based observations of lunar eclipses have provided the Earth’s transmission spectrum at optical and near-IR wavelengths, but the strongest O{sub 3} signatures are in the near-UV. We describe the observations and methods used to extract a transmission spectrum from Hubble lunar eclipse spectra, and identify spectral features of O{sub 3} and Rayleigh scattering in the 3000–5500 Å region in Earth’s transmission spectrum by comparing to Earth models that include refraction effects in the terrestrial atmosphere during a lunar eclipse. Our near-UV spectra are featureless, a consequence of missing the narrow time span during the eclipse when near-UV sunlight is not completely attenuated through Earth’s atmosphere due to extremely strong O{sub 3} absorption and when sunlight is transmitted to the lunar surface at altitudes where it passes through the O{sub 3} layer rather than above it.

79 ASTRONOMY AND ASTROPHYSICS↗

Mesoscale Convective Systems in a Superparameterized E3SM Simulation at High Resolution

Accurately representing mesoscale convective systems (MCSs) is crucial to simulating the energy and water cycles in global climate models. Using a novel MCS identification and tracking algorithm applied to observations and model simulations, we evaluate how well the Energy Exascale Earth System Model simulates MCSs over the central US. Simulations performed by E3SM at 25 km grid spacing with (SP-E3SM) and without (E3SM) superparameterization are compared and evaluated against observations using multiple metrics highlighting important MCS characteristics. Compared to E3SM, SP-E3SM better simulates MCS number and MCS precipitation amount, diurnal cycle, propagation, and the probability distribution of precipitation rate in both spring and summer. The improvement from SP is partly contributed by improvement in simulating the large-scale environments, featuring enhanced atmospheric low-level moisture and larger moisture transport to the central US relative to E3SM. However, SP-E3SM still underestimates MCS precipitation amount, particularly in summer. This underestimation is closely related to the negative bias in MCS precipitation intensity, although the drier environments simulated during summer also contributes to underestimation of MCS frequency. Without SP, the larger bias in MCS precipitation amount is closely related to the negative bias in MCS frequency, while the substantial dry bias in the large-scale environments also contributes to underestimation of MCS intensity. Our results suggest that SP improves MCS simulation by improving modeling of the large-scale environments and convection initiation, which are both major limiting factors in E3SM even at 25 km grid spacing where deep convection is represented by a cumulus parameterization.

54 ENVIRONMENTAL SCIENCES↗

Three different directions in which the European Union could replace Russian natural gas

Russia's invasion of Ukraine fuelled an energy crisis, which considerably impacted Europe given its heavy reliance on Russian natural gas imports. This study uses an ensemble of four global integrated assessment models, which are further soft-linked to two sectoral models, and explores the synergies and trade-offs among three approaches to living without Russian gas in Europe: (a) replacing with other gas imports, (b) boosting domestic energy production, and (c) reducing demand and accelerating energy efficiency. We find that substituting Russian gas from other trade partners would miss an opportunity to accelerate decarbonisation in end-use sectors while risking further fossil-fuel lock-ins, despite featuring the lowest gas price spikes and potentially reducing heating costs for end-users in the near term. Boosting domestic, primarily renewable, energy production on the other hand would instead require considerable investments, potentially burdening consumers. Energy demand reductions, however, could offer considerable space for further emissions cuts at the lowest power-sector investment costs; nonetheless, an energy efficiency-driven strategy would also risk relocation of energy-intensive industries, an aspect of increasing relevance to EU policymakers.

03 NATURAL GAS↗

Navigating the Expansive Landscapes of Soft Materials: A User Guide for High-Throughput Workflows

Synthetic polymers are highly customizable with tailored structures and functionality, yet this versatility generates challenges in the design of advanced materials due to the size and complexity of the design space. Thus, exploration and optimization of polymer properties using combinatorial libraries has become increasingly common, which requires careful selection of synthetic strategies, characterization techniques, and rapid processing workflows to obtain fundamental principles from these large data sets. Herein, we provide guidelines for strategic design of macromolecule libraries and workflows to efficiently navigate these high-dimensional design spaces. We describe synthetic methods for multiple library sizes and structures as well as characterization methods to rapidly generate data sets, including tools that can be adapted from biological workflows. We further highlight relevant insights from statistics and machine learning to aid in data featurization, representation, and analysis. This Perspective acts as a “user guide” for researchers interested in leveraging high-throughput screening toward the design of multifunctional polymers and predictive modeling of structure–property relationships in soft materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reconstruction of Electron and Ion Distribution Functions in a Magnetotail Reconnection Diffusion Region

In the diffusion region of magnetotail reconnection, particle distributions are highly structured, exhibiting triangular shapes and multiple striations that deviate dramatically from the Maxwellian distribution. Fully kinetic simulations have been demonstrated to be capable of producing the essential structures of the observed distribution functions, yet are computationally not feasible for 3D global simulations. The fluid models used for large-scale simulations, on the other hand, do not have the kinetic physics necessary for describing reconnection accurately. Our study aims to bridge fully kinetic and fluid simulations by quantifying the information required to capture the non-Maxwellian features in the distributions underlying the closures used in the fluid code. Here, we compare the results of fully kinetic simulations with observed electron velocity distributions in a magnetotail reconnection diffusion region and use the maximum entropy model to reconstruct electron and ion distributions using various numbers of moments obtained from the simulation. Our results indicate that using only local moments, the maximum entropy model can reproduce many of the features of the distributions: (1) the electron outflow distribution with a tilted triangular structure is reproduced with 21 or more moments in agreement with Ng et al. and (2) counterstreaming distributions can be captured with the 35-moment model when the separation in velocity space between the populations is large.

58 GEOSCIENCES↗

Mapping Glacier Basal Sliding Applying Machine Learning

During the RESOLVE project (“High-resolution imaging in subsurface geophysics: development of a multi-instrument platform for interdisciplinary research”), continuous surface displacement and seismic array observations were obtained on Glacier d’Argentière in the French Alps for 35 days in May 2018. The data set is used to perform a detailed study of targeted processes within the highly dynamic cryospheric environment. In particular, the physical processes controlling glacial basal motion are poorly understood and remain challenging to observe directly. Especially in the Alpine region for temperate based glaciers where the ice rapidly responds to changing climatic conditions and thus, processes are strongly intermittent in time and heterogeneous in space. Spatially dense seismic and Global Positioning System (GPS) measurements are analyzed applying machine learning to gain insight into the processes controlling glacial motions of Glacier d’Argentière. Using multiple bandpass-filtered copies of the continuous seismic waveforms, we compute energy-based features, develop a matched field beamforming catalog and include meteorological observations. Features describing the data are analyzed with a gradient boosting decision tree model to directly estimate the GPS displacements from the seismic noise. We posit that features of the seismic noise provide direct access to the dominant parameters that drive displacement on the highly variable and unsteady surface of the glacier. The machine learning model infers daily fluctuations and longer term trends. The results show on-ice displacement rates are strongly modulated by activity at the base of the glacier. The techniques presented provide a new approach to study glacial basal sliding and discover its full complexity.

58 GEOSCIENCES↗

Stellar splashback: the edge of the intracluster light

We examine the outskirts of galaxy clusters in the C-EAGLE simulations to quantify the ‘edges’ of the stellar and dark matter distribution. The radius of the steepest slope in the dark matter, commonly used as a proxy for the splashback radius, is located at $\sim \, r_{200 \rm m}$; the strength and location of this feature depends on the recent mass accretion rate, in good agreement with previous work. Interestingly, the stellar distribution (or intracluster light, ICL) also has a well-defined edge, which is directly related to the splashback radius of the halo. Thus, detecting the edge of the ICL can provide an independent measure of the physical boundary of the halo, and the recent mass accretion rate. We show that these caustics can also be seen in the projected density profiles, but care must be taken to account for the influence of substructures and other non-diffuse material, which can bias and/or weaken the signal of the steepest slope. This is particularly important for the stellar material, which has a higher fraction bound in subhaloes than the dark matter. Finally, we show that the ‘stellar splashback’ feature is located beyond current observational constraints on the ICL, but these large projected distances (>> 1 Mpc) and low surface brightnesses (μ>>32 mag arcsec -2 ) can be reached with upcoming observational facilities such as the Vera C. Rubin Observatory, the Nancy Grace Roman Space Telescope, and Euclid.

79 ASTRONOMY AND ASTROPHYSICS↗

Effective one-band models for the one-dimensional cuprate Ba 2-x Sr x CuO 3+δ

In this work, we consider a multiband Hubbard model H m for Cu and O orbitals in Ba 2-x Sr x CuO 3+δ similar to the three-band model for two-dimensional cuprates. The hopping parameters are obtained from maximally localized Wannier functions derived from ab initio calculations. Using the cell perturbation method, we derive both a generalized t–J model H tJ and a one-band Hubbard model H H to describe the low-energy physics of the system. H tJ has the advantage of having a smaller relevant Hilbert space, facilitating numerical calculations, while additional terms should be included in H H to accurately describe the multiband physics of H m . Using H tJ and the density matrix renormalization group method, we calculate the wave-vector-resolved photoemission and discuss the relevant features in comparison with recent experiments. In agreement with previous calculations, we find that the addition of an attractive nearest-neighbor interaction of the order of the nearest-neighbor hopping shifts the weight from the 3k F to the holon-folding branch. Kinetic effects also contribute to this process.

1-dimensional systems↗

Semi-Dirac Fermions in a Topological Metal

Topological semimetals with massless Dirac and Weyl fermions represent the forefront of quantum materials research. In two dimensions, a peculiar class of fermions that are massless in one direction and massive in the perpendicular direction was predicted 16 years ago. These highly exotic quasiparticles—the semi-Dirac fermions—ignited intense theoretical and experimental interest but remain undetected. Using magneto-optical spectroscopy, we demonstrate the defining feature of semi-Dirac fermions— B 2 / 3 scaling of Landau levels—in a prototypical nodal-line metal ZrSiS. In topological metals, including ZrSiS, nodal lines extend the band degeneracies from isolated points to lines, loops, or even chains in the momentum space. With calculations and theoretical modeling, we pinpoint the observed semi-Dirac spectrum to the crossing points of nodal lines in ZrSiS. Crossing nodal lines exhibit a continuum absorption spectrum but with singularities that scale as B 2 / 3 at the crossing. Our work sheds light on the hidden quasiparticles emerging from the intricate topology of crossing nodal lines and highlights the potential to explore quantum geometry with linear optical responses. Published by the American Physical Society 2024

Shao, Yinming (ORCID:0000000228910028)↗

Thermally Responsive Hydrogels for Passive Temperature Regulation under Direct Sunlight

By spontaneously emitting midinfrared radiation to outer space through the atmospheric window and reflecting sunlight, daytime radiative coolers achieve notable passive cooling performance. However, existing daytime radiative cooling systems generally lack the ability to adaptively switch between heating and cooling states based on ambient conditions. Herein a passive thermal regulation system that features a temperature‐dependent switchable solar reflectance from 0.05 (low temperature) to 0.8 (high temperature) is presented. This, along with a ≈0.95 midinfrared emittance, it enables automatic switching between radiative cooling and solar heating. Switchablity is enabled using a poly( N ‐isopropylacrylamide) (PNIPAM) hydrogel which exhibits high solar scattering above its tunable lower critical solution temperature (LCST) and transparency below its LCST. The lower part of the hydrogel is loaded with graphite to absorb solar energy in the heating state. In testing under sunny and partly cloudy outside conditions, this system maintains a temperature close to the set LCST.

Xie, Dajie↗

Multifunctional Charge and Hydrogen‐Bond Effects of Second‐Sphere Imidazolium Pendants Promote Capture and Electrochemical Reduction of CO 2 in Water Catalyzed by Iron Porphyrins**

Abstract Microenvironments tailored by multifunctional secondary coordination sphere groups can enhance catalytic performance at primary metal active sites in natural systems. Here, we capture this biological concept in synthetic systems by developing a family of iron porphyrins decorated with imidazolium (im) pendants for the electrochemical CO 2 reduction reaction (CO 2 RR), which promotes multiple synergistic effects to enhance CO 2 RR and enables the disentangling of second‐sphere contributions that stem from each type of interaction. Fe‐ ortho ‐im(H) , which poises imidazolium units featuring both positive charge and hydrogen‐bond capabilities proximal to the active iron center, increases CO 2 binding affinity by 25‐fold and CO 2 RR activity by 2000‐fold relative to the parent Fe tetraphenylporphyrin ( Fe‐TPP ). Comparison with monofunctional analogs reveals that through‐space charge effects have a greater impact on catalytic CO 2 RR performance compared to hydrogen bonding in this context.

Narouz, Mina R.↗

Machine learning-based discovery of molecular descriptors that control polymer gas permeation

While machine learning has found increasing use in predicting the properties of polymeric materials with only a knowledge of chain architecture, determining the molecular factors underpinning properties (“interpretable AI”) has remained less well explored. We show that encoding chain chemistry in commonly employed formats, e.g., binary-valued fingerprints, leads to uniqueness issues during the hashing process to save storage space. This is because the hashing algorithm can map several chemical moieties into the same bit. These issues carry over into the ML algorithms, especially for “inverse” design and interpretable AI, and cannot be avoided by changing the length of the fingerprint. Using MACCS key featurizations of monomer repeats resolves some of these issues, and we show that a few substructures consistently appear in top features for maximizing permeability across several gases and ML models. These are carbon–carbon double bonds (as in polyacetylenes) especially when they are associated with methyl groups (found in branching architectures). Here these results, derived from the limited data set of ~ 500 polymers with experimental gas permeation data, are in agreement with physical insight and thus provide a robust foundation which could further enable study of these material classes through detailed experiments and simulations.

36 MATERIALS SCIENCE↗

Stable and unstable supersonic stagnation of an axisymmetric rotating magnetized plasma

The Naval Research Laboratory ‘Mag Noh problem’, described in this paper, is a self-similar magnetized implosion flow, which contains a fast magnetohydrodynamic (MHD) outward propagating shock of constant velocity. We generalize the classic Noh ( OSTI Tech. Rep. 577058, 1983) problem to include azimuthal and axial magnetic fields as well as rotation. Our family of ideal MHD solutions is five parametric, each solution having its own self-similarity index, gas gamma, magnetization, the ratio of axial to the azimuthal field and rotation. While the classic Noh problem must have a supersonic implosion velocity to create a shock, our solutions have an interesting three-parametric special case with zero initial velocity in which magnetic tension, instead of implosion flow, creates the shock at $t=0+$ . Our self-similar solutions are indeed realized when we solve the initial value MHD problem with the finite volume MHD code Athena. We numerically investigated the stability of these solutions and found both stable and unstable regions in parameter space. Stable solutions can be used to test the accuracy of numerical codes. Unstable solutions have also been widely used to test how codes reproduce linear growth, transition to turbulence and the practically important effects of mixing. Now we offer a family of unstable solutions featuring all three elements relevant to magnetically driven implosions: convergent flow, magnetic field and a shock wave.

Mechanics↗