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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The chemical composition of globular clusters in the Local Group

We present detailed chemical abundance measurements for 45 globular clusters (GCs) associated with galaxies in (and, in one case, beyond) the Local Group. The measurements are based on new high-resolution integrated-light spectra of GCs in the galaxies NGC 185, NGC 205, M 31, M 33, and NGC 2403, combined with reanalysis of previously published observations of GCs in the Fornax dSph, WLM, NGC 147, NGC 6822, and the Milky Way. The GCs cover the range -2.8 < [Fe/H] < -0.1 and we determined abundances for Fe, Na, Mg, Si, Ca, Sc, Ti, Cr, Mn, Ni, Cu, Zn, Zr, Ba, and Eu. Corrections for non local thermodynamic equilibrium effects are included for Na, Mg, Ca, Ti, Mn, Fe, Ni, and Ba, building on a recently developed procedure. For several of the galaxies, our measurements provide the first quantitative constraints on the detailed composition of their metal-poor stellar populations. Overall, the GCs in different galaxies exhibit remarkably uniform abundance patterns of the α, iron-peak, and neutron-capture elements, with a dispersion of less than 0.1 dex in [α/Fe] for the full sample. There is a hint that GCs in dwarf galaxies are slightly less α-enhanced (by ~0.04 dex on average) than those in larger galaxies. One GC in M 33 (HM33-B) resembles the most metal-rich GCs in the Fornax dSph (Fornax 4) and NGC 6822 (SC7) by having α-element abundances closer to scaled-solar values, possibly hinting at an accretion origin. A principal components analysis shows that the α-element abundances strongly correlate with those of Na, Sc, Ni, and Zn. Several GCs with [Fe/H] < -1.5 are deficient in Mg compared to other α-elements. We find no GCs with strongly enhanced r-process abundances as reported for metal-poor stars in some ultra-faint dwarfs and the Magellanic Clouds. The similarity of the abundance patterns for metal-poor GCs in different environments points to similar early enrichment histories and only allow for minor variations in the initial mass function.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Enzalutamide response in a panel of prostate cancer cell lines reveals a role for glucocorticoid receptor in enzalutamide resistant disease

Representative in vitro model systems that accurately model response to therapy and allow the identification of new targets are important for improving our treatment of prostate cancer. Here we describe molecular characterization and drug testing in a panel of 20 prostate cancer cell lines. The cell lines cluster into distinct subsets based on RNA expression, which is largely driven by functional Androgen Receptor (AR) expression. KLK3 , the AR-responsive gene that encodes prostate specific antigen, shows the greatest variability in expression across the cell line panel. Other common prostate cancer associated genes such as TMPRSS2 and ERG show similar expression patterns. Copy number analysis demonstrates that many of the most commonly gained (including regions containing TERC and MYC ) and lost regions (including regions containing TP53 and PTEN) that were identified in patient samples by the TCGA are mirrored in the prostate cancer cell lines. Assessment of response to the anti-androgen enzalutamide shows a distinct separation of responders and non-responders, predominantly related to status of wild-type AR. Surprisingly, several AR-null lines responded to enzalutamide. These AR-null, enzalutamide-responsive cells were characterized by high levels of expression of glucocorticoid receptor (GR) encoded by NR3C1 . Treatment of these cells with the anti-GR agent mifepristone showed that they were more sensitive to this drug than enzalutamide, as were several of the enzalutamide non-responsive lines. This is consistent with several recent reports that suggest that GR expression is an alternative signaling mechanism that can bypass AR blockade. This study reinforces the utility of large cell line panels for the study of cancer and identifies several cell lines that represent ideal models to study AR-null cells that have upregulated GR to sustain growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Statistical analysis of spatial distribution of pores in metal additive manufacturing

We report mechanical properties of additively manufactured parts are sensitive to the presence of pores form during the manufacturing process. The impact of pores on the mechanical performance has been investigated extensively with respect to different parameters, such as pore volume fraction, shape, and size. However, statistical investigations focusing on the relationships between the spatial distribution of pores and process parameters; and consequently, the performance of the manufactured parts are scattered and limited. Also, these sparse investigations usually suffer from an ambiguous definition of terminologies. For instance, the required criteria to consider a point pattern as complete spatial randomness (CSR) are generally not clarified. Moreover, no numerical formalism is yet developed to show how much the observed spatial results are statistically significant. To address these shortcomings, the statistical definition of CSR in a point pattern and the procedure to quantitatively determine the deviation of a pattern from CSR were discussed. The explained statistical approach was used to investigate the effect of scanning speed parameter on the spatial distribution of gas pores in laser powder bed fusion manufactured stainless steel parts. Furthermore, and to highlight the impact of the spatial distribution of pores on mechanical properties, fatigue performances of parts with clustered and randomly distributed pores were simulated by finite element analysis. It is shown that by reducing the scanning speed, the spatial distribution of gas pores deviated more from CSR, and correspondingly fatigue performance deteriorated.

36 MATERIALS SCIENCE↗
NASA NTRS2008

Mapping the Sedna-Lavinia Region of Venus

Geologic mapping of Venus at 1:5 M scale has shown in great detail the flow complexes of volcanoes, coronae, and shield fields, and the varying structural patterns that differentiate tesserae from corona rims and isolated patches of densely lineated terrain. In most cases, however, the lower-elevation plains between the higher-standing landforms are discriminated only on the basis of potentially secondary features such as late-stage lava flooding or tectonic overprinting. This result, in which volcanoes and tesserae appear as "islands in the sea," places weak constraints on the relative age of large upland regions and the nature of the basement terrain. In this work, we focus on the spatial distribution and topography of densely lineated and tessera units over a large region of Venus, and their relationship to apparently later corona and shield flow complexes. The goal is to identify likely connections between patches of deformed terrain that suggest earlier features of regional extent, and to compare the topography of linked patches with other such clusters as a guide to whether they form larger tracts beneath the plains. Mapping Approach. We are mapping the region from 57S to 57N, 300E-60E. Since the 1:5 M quadrangles emphasize detail of tessera structure and corona/edifice flows, we simply adopt the outlines of these features as they relate to the outcrops of either "densely lineated terrain" or tessera (Fig. 1). The densely lineated material is mapped in many quadrangles based on pervasive structural deformation, typically with a single major axis (in contrast to the overlapping orthogonal patterns on tesserae). This unit definition is often extended to include material of corona rims. We do not at present differentiate between plains units, since earlier efforts show that their most defining attributes may be secondary to the original emplacement (e.g., lobate or sheet-like flooding by thin flow units, tectonic patterns related to regional and localized stress regimes) [1].

Campbell, Bruce A.↗
DOE OSTI2023

An investigation of non-canonical mixing in red giant stars using APOGEE 12 C/ 13 C ratios observed in open cluster stars

Standard stellar evolution theory poorly predicts the surface abundances of chemical species in low-mass, red giant branch (RGB) stars. Observations show an enhancement of p–p chain and CNO cycle products in red giant envelopes, which suggests the existence of non-canonical mixing that brings interior burning products to the surface of these stars. The 12 C/ 13 C ratio is a highly sensitive abundance metric used to probe this mixing. We investigate extra RGB mixing by examining: (1) how 12 C/ 13 C is altered along the RGB, and (2) how 12 C/ 13 C changes for stars of varying age and mass. Our sample consists of 43 red giants, spread over 15 open clusters from the Sloan Digital Sky Survey’s APOGEE DR17, that have reliable 12 C/ 13 C ratios derived from their APOGEE spectra. We vetted these 12 C/ 13 C ratios and compared them as a function of evolution and age/mass to the standard mixing model of stellar evolution, and to a model that includes prescriptions for RGB thermohaline mixing and stellar rotation. We find that the observations deviate from standard mixing models, implying the need for extra mixing. Additionally, some of the abundance patterns depart from the thermohaline model, and it is unclear whether these differences are due to incomplete observations, issues inherent to the model, our assumption of the cause of extra mixing, or any combination of these factors. Nevertheless, the surface abundances across our age/mass range clearly deviate from the standard model, agreeing with the notion of a universal mechanism for RGB extra mixing in low-mass stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Household energy resilience in extreme weather events: An investigation of energy service importance, HVAC usage behaviors, and willingness to pay

Household energy resilience, particularly maintaining essential energy services within an acceptable and affordable level, is critical during extreme weather events (e.g., winter storms, heat waves) with power shortages or outages. However, the research on the importance and acceptable compromise levels of energy services, HVAC usage behavior changes, and willingness to pay (WTP) for energy services during disasters is limited. Therefore, this study investigates the importance and compromise of household energy services, HVAC usage behaviors, and WTP, as three key dimensions of household energy resilience, in both normal days and disaster scenarios through surveys (n=485). First, 12 common residential end-uses are grouped into high, mid, and low-priority services using hierarchical clustering, in which high-priority services (perceived as important and un-compromisable) include food cooking and storage (refrigerator and freezer) and thermal comfort (space heating and cooling), mid-priority services involve water heating and lighting, while low-priority services are mostly related to entertainment and housework (e.g., TV, laundry). Also, HVAC use patterns demonstrate that occupants become more energy conservative during disasters, e.g., reducing durations of running HVAC and adjusting temperature setpoints to save energy. In terms of energy cost, approximately 60% of respondents are willing to pay more to maintain energy services during disasters, although only 13% are prepared to pay over double the normal energy prices. The regression models further reveal that household energy resilience varies across different sociodemographic groups (e.g., age, income, family size) and is impacted by disaster experience and beliefs in clean energy and climate. In conclusion, these research findings provide important perspectives to understand household energy resilience and inform measures for disaster adaptation of households in extreme weather events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low‐Frequency Changes in ENSO Variance

Abstract El Niño Southern Oscillation (ENSO) diversity is characterized based on the longitudinal location of maximum sea surface temperature anomalies (SSTA) and amplitude in the tropical Pacific, as Central Pacific events are typically weaker than Eastern Pacific events. SSTA pattern and intensity undergo low‐frequency modulations, affecting ENSO prediction skill and remote impacts, and resulting in low‐frequency changes in ENSO variance. Yet, how different ENSO types contribute to these decadal variance changes remains unclear. Here, we decompose the low‐frequency changes of ENSO variance into contributions from ENSO diversity categories. We propose a fuzzy clustering of monthly SSTA to allow for non‐binary event category memberships, where each event can belong to different clusters. Our approach identifies two La Niña and three El Niño categories and shows that the major shift of ENSO variance in the mid‐1970s was associated with an increasing likelihood of strong La Niña and extreme El Niño events.

Geology↗
DOE OSTI2021

Modeling temporal and hormonal regulation of plant transcriptional response to wounding

Plants respond to wounding stress by changing gene expression patterns and inducing the production of hormones including jasmonic acid. This wounding transcriptional response activates specialized metabolism pathways such as the glucosinolate pathways in Arabidopsis thaliana. While the regulatory factors and sequences controlling a subset of wound-response genes are known, it remains unclear how wound response is regulated globally. Here, we how these responses are regulated by incorporating putative cis-regulatory elements, known transcription factor binding sites, in vitro DNA affinity purification sequencing, and DNase I hypersensitive sites to predict genes with different wound-response patterns using machine learning. We observed that regulatory sites and regions of open chromatin differed between genes upregulated at early and late wounding time-points as well as between genes induced by jasmonic acid and those not induced. Expanding on what we currently know, we identified cis-elements that improved model predictions of expression clusters over known binding sites. Using a combination of genome editing, in vitro DNA-binding assays, and transient expression assays using native and mutated cis-regulatory elements, we experimentally validated four of the predicted elements, three of which were not previously known to function in wound-response regulation. Our study provides a global model predictive of wound response and identifies new regulatory sequences important for wounding without requiring prior knowledge of the transcriptional regulators.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Adversarial Ensemble Modeling of Multi-modal Mechanical Properties for Iron-Based Alloys

Mechanical properties of alloys are controlled by their microstructure; and microstructure evolution is controlled by internal and external stressors. Chemical complexity during the alloy processing may result in heterogeneity and observation of multimodal performance patterns. Thus, to ensure the desired performance of stressed components it is important to understand the origin and mechanisms of such behavior. Adversarial ensemble modeling was introduced here to explain multimodal mechanical properties of the iron-based alloys. The modeling results showed that the areas of a single mechanism predominance were contiguous across the alloy compositions clustered by similarity, with sharp and persistent boundaries separating the single-mechanism domains. The marginal compositions resulted in increased competition between the adversarial models but only led to the multimodal behavior when the competing models diverged. Transparency of the clustering method allowed explicit interpretation of the chemistries leading to such competition. The adversarial ensemble was interpreted through transition from ductile to brittle microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2025

47 Tuc in Rubin Data Preview 1. Exploring Early LSST Data and Science Potential

We present analyses of the early data from Rubin Observatory’s Data Preview 1 (DP1) for the field of the globular cluster 47 Tuc. The DP1 data set for 47 Tuc includes four nights of observations from the Rubin Commissioning Camera (LSSTComCam), covering multiple bands (ugriy). We address challenges of crowding in the inner region of the cluster and toward the SMC in DP1, and demonstrate improved star–galaxy separation by fitting fifth-degree polynomials to the stellar loci in color–color diagrams and applying multidimensional sigma clipping. We compile a catalog of 3576 probable 47 Tuc member stars selected via a combination of isochrone, Gaia proper-motion, and color–color space matched filtering. We explore the sources of photometric scatter in the 47 Tuc color–color sequence, evaluating contributions from various potential sources, including differential extinction within the cluster. Finally, of the 72 well-characterized variables in the field, we recover three known variable stars, including two RR Lyrae and one eclipsing binary, in the coadd-based object catalog, and identify 62 in the difference image-based object catalog. Although the DP1 lightcurves have sparse temporal sampling, they appear to follow the patterns of densely sampled literature lightcurves well. Despite some data limitations for crowded-field stellar analysis, DP1 demonstrates the promising scientific potential for future LSST data releases.

Choi, Yumi [NSF National Optical-Infrared Astronom↗
DOE OSTI2026

Assessing the Application of a Genomic Network Analysis in Population Ecology: Inferring Patterns of Dispersal and Geographic Structure in the Emerging Pathogen, Coccidioides

A challenge in population ecology studies is identifying how to best group individuals into populations, especially when individual origin is unknown. Machine learning has improved upon traditional methods of identifying population structure and is more efficient at handling large, complex datasets. We demonstrate the applicability of a machine learning method to identify hierarchical population structure in an emerging pathogen, Coccidioides spp., the causative agent of Valley fever. We compared the network clusters to structure identified by traditional tools as a validation of the network performance. We used publicly available whole-genome data for 48 C. immitis and 102 C. posadasii, resulting in 168,211 genome-wide SNPs among the two species. The network analysis grouped samples into populations comparable to the literature for these species but also identified fine-scale geographic structure and travel-associated cases not reported thus far. Exploring different resolutions in the network made it easy to identify unique genotypes specific to California and possibly Nevada, as well as Phoenix- and Tucson-acquired infections in non-endemic areas, regardless of reported travel history. The present study provides a promising example of how a ML-based network analysis can improve our ability to understand pathogen ecology, group cases into populations and infer travel-associated infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Interpreting the spatial distribution of soil properties with a physically-based distributed hydrological model

Digital soil maps are commonly data-driven as the development of physically-based models for soil mapping is difficult due to the complexity of soils. However, physically-based hydrologic models have been successful in simulating water dynamics. Since water movement is a major driver of pedogenesis, the physical rules that govern water movement might help explain and predict the spatial variation of soil properties. Here, we demonstrate the novel use of a physically-based, distributed hydrologic model to inform the spatial distribution of soil properties. The Distributed Hydrology Soil Vegetation Model (DHSVM) was utilized to simulate soil moisture content (SM) and water table depth (WTD) in two hillslope catchments under pasture and forest management wherein hydrologic model outputs were then compared with soil properties measured in situ. SM sensors and wells were installed in both catchments to validate simulations of soil water movement via Nash-Sutcliffe Efficiency (E). In-situ observations were made at 87 sites within both catchments to study the connection between simulated water movement (SM and WTD) and observed soil properties, namely the depth and thickness of the argillic (Bt), fragic (Btx), and C horizons, and the depth of redoximorphic features. The simulated time series of SM and WTD were also clustered per season using Dynamic Time Warping (DTW), which identified similarity among time series at varying timescales. Model validation suggested that simulations of surficial SM (0–20 cm) were reasonable (E = 0.45), however, simulated subsurface SM (45–60 cm) and WTD were not sufficiently accurate. The thickness of Btx horizons were spatially grouped into different populations by SM clusters from every season except spring. For the other properties, only SM dynamics of specific seasons grouped into significantly different populations, suggesting that the explanatory power of simulated water movement varies seasonally and was greater during winter. Here, we show clusters of simulated SM separated soil properties into statistically different populations, showing that hydrologic models could inform areas that followed different water dynamics related to pedogenic trajectories and related biogeochemical processes not necessarily simulated by the model. As such, physically-based modeling of water dynamics can, therefore, inform and advance digital soil mapping by linking water movement patterns stemming from hydrologic model outputs to spatial patterns of soil properties and pedogenesis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Intermittent Criticality Multi‐Scale Processes Leading to Large Slip Events on Rough Laboratory Faults

Abstract We discuss data of three laboratory stick‐slip experiments on Westerly Granite samples performed at elevated confining pressure and constant displacement rate on rough fracture surfaces. The experiments produced complex slip patterns including fast and slow ruptures with large and small fault slips, as well as failure events on the fault surface producing acoustic emission bursts without externally‐detectable stress drop. Preparatory processes leading to large slips were tracked with an ensemble of ten seismo‐mechanical and statistical parameters characterizing local and global damage and stress evolution, localization and clustering processes, as well as event interactions. We decompose complex spatio‐temporal trends in the lab‐quake characteristics and identify persistent effects of evolving fault roughness and damage at different length scales, and local stress evolution approaching large events. The observed trends highlight labquake localization processes on different spatial and temporal scales. The preparatory process of large slip events includes smaller events marked by confined bursts of acoustic emission activity that collectively prepare the fault surface for a system‐wide failure by conditioning the large‐scale stress field. Our results are consistent overall with an evolving process of intermittent criticality leading to large failure events, and may contribute to improved forecasting of large natural earthquakes.

Geochemistry & Geophysics↗
DOE OSTI2024

Studying CPU and memory utilization of applications on Fujitsu A64FX and Nvidia Grace Superchip

ARM-based manycore CPU architectures are well-positioned to provide the rising memory throughput requirements of modern data intensive scientific applications in High Performance Computing (HPC). The Fujitsu A64FX CPU platform is based on the ARM v8.2A architecture, and is the processor of the flagship Japanese supercomputer - "Fugaku", which was previously ranked as the #1 supercomputer in the world according to the Top500 list. The Nvidia Grace superchip features 144 Neoverse V2 cores based on the ARMv9 architecture with 4x128b SVE2, providing exceptional computational power. The chip supports up to 480GB of memory, making it ideal for AI, machine learning, and scientific computing workloads. In this paper, we conduct a thorough performance exploration of a variety of parallel bandwidth-sensitive benchmarks and applications compiled with the native Fujitsu compiler on a Fugaku A64FX compute node and ARM (LLVM) Compiler on an NVIDIA Grace superchip compute node, engaging all the computational cores per cluster using OpenMP multithreading (assuming the cores can drive the available bandwidth). Our ultimate goals are to study the resource utilization of scientific applications and benchmarks on A64FX and Grace superchip, considering graph application scenarios ( GAP Benchmark suite) and eleven appli- cation proxies from the Rodinia heterogeneous benchmark suite (considering domains such as Data Mining, Bioinformatics, Fluid Dynamics, Pattern Recognition, etc.). Through exhaustive performance monitoring, we quantify the resource utilization of diverse OpenMP-based HPC applications on both the Fujitsu A64FX and the Nvidia Grace Superchip platforms.

benchmarking, Performance Analysis, High performan↗
NASA NTRS1973

A study to explore the use of orbital remote sensing to determine native arid plant distribution

The author has identified the following significant results. Ground truth spectral signature data for various types of scenes, including ground with and without annuals, and various shrubs, were collected. When these signature data are plotted with infrared (MSS band 6 or 7) reflectivity on one axis and red (MSS band 5) reflectivity on the other axis, clusters of data from the various types of scenes are distinct. This method of expressing spectral signature data appears to be more useful for distinguishing types of scenes than a simple infrared to red reflectivity ration. Large areas of varnished desert pavement are visible and mappable on ERTS-1 and high altitude aircraft imagery. A large scale vegetation pattern was found to be correlated with the presence of the desert pavement. The large scale correlation was used in mapping the vegetation of the area. It was found that a distinctive soil type was associated with the presence of the varnished desert pavement. The high salinity and exchangeable sodium percentage of this soil type provide a basis for the explanation of both the large scale and small scale vegetation pattern.

Mcginnies, W. G.↗
NASA NTRS2000

Spatial expression of Hox cluster genes in the ontogeny of a sea urchin

The Hox cluster of the sea urchin Strongylocentrous purpuratus contains ten genes in a 500 kb span of the genome. Only two of these genes are expressed during embryogenesis, while all of eight genes tested are expressed during development of the adult body plan in the larval stage. We report the spatial expression during larval development of the five 'posterior' genes of the cluster: SpHox7, SpHox8, SpHox9/10, SpHox11/13a and SpHox11/13b. The five genes exhibit a dynamic, largely mesodermal program of expression. Only SpHox7 displays extensive expression within the pentameral rudiment itself. A spatially sequential and colinear arrangement of expression domains is found in the somatocoels, the paired posterior mesodermal structures that will become the adult perivisceral coeloms. No such sequential expression pattern is observed in endodermal, epidermal or neural tissues of either the larva or the presumptive juvenile sea urchin. The spatial expression patterns of the Hox genes illuminate the evolutionary process by which the pentameral echinoderm body plan emerged from a bilateral ancestor.

Non-NASA Center↗
NASA NTRS1974

An analysis of fracture trace patterns in areas of flat-lying sedimentary rocks for the detection of buried geologic structure

Two study areas in a cratonic platform underlain by flat-lying sedimentary rocks were analyzed to determine if a quantitative relationship exists between fracture trace patterns and their frequency distributions and subsurface structural closures which might contain petroleum. Fracture trace lengths and frequency (number of fracture traces per unit area) were analyzed by trend surface analysis and length frequency distributions also were compared to a standard Gaussian distribution. Composite rose diagrams of fracture traces were analyzed using a multivariate analysis method which grouped or clustered the rose diagrams and their respective areas on the basis of the behavior of the rays of the rose diagram. Analysis indicates that the lengths of fracture traces are log-normally distributed according to the mapping technique used. Fracture trace frequency appeared higher on the flanks of active structures and lower around passive reef structures. Fracture trace log-mean lengths were shorter over several types of structures, perhaps due to increased fracturing and subsequent erosion. Analysis of rose diagrams using a multivariate technique indicated lithology as the primary control for the lower grouping levels. Groupings at higher levels indicated that areas overlying active structures may be isolated from their neighbors by this technique while passive structures showed no differences which could be isolated.

Podwysocki, M. H.↗
NASA NTRSDate not supplied

Monte Carlo Study of the Formation of Chromosome Aberrations by Direct Ion Traversal vs. Delta-Electrons

Space radiation constitutes a major risk for the safety of space travel. Galactic Cosmic Rays (GCRs) are made of high energy protons (87%), high energy helium ions (12%) and high-charge and energy (HZE) ions [1]. At a cellular scale, HZE ions display a characteristic pattern of energy deposition, known as the ion track, that correlates with the ion linear energy transfer (LET). These energy deposition events (ionizations/excitations) create DNA breaks that, if misrepaired, lead to the formation of chromosome aberrations (CAs). Compared to low-LET terrestrial radiations (X-rays and γ-rays), high LET ions are known to create complex, clustered DNA breaks that are particularly efficient at forming CAs. Indeed, ion tracks are usually described as a dense ionization core, where clustered breaks are formed, and a penumbra, made of low-LET δ-electrons that have sufficient energy to travel across many cells and induce breaks that are more homogeneously distributed. In this work, we investigated the formation of CAs, and separated them into two contributions (direct ion traversal of the nucleus vs.δ-electrons), to elucidate to which extent δ-electrons contribute to CA formation.

Floriane Poignant↗