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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Urbanization and edge effects interact to drive mutualism breakdown and the rise of unstable pathogenic communities in forest soil

Temperate forests are threatened by urbanization and fragmentation, with over 20% (118,300 km 2 ) of U.S. forest land projected to be subsumed by urban land development. We leveraged a unique, well-characterized urban-to-rural and forest edge-to-interior gradient to identify the combined impact of these two land use changes—urbanization and forest edge creation—on the soil microbial community in native remnant forests. We found evidence of mutualism breakdown between trees and their fungal root mutualists [ectomycorrhizal (ECM) fungi] with urbanization, where ECM fungi colonized fewer tree roots and had less connectivity in soil microbiome networks in urban forests compared to rural forests. However, urbanization did not reduce the relative abundance of ECM fungi in forest soils; instead, forest edges alone led to strong reductions in ECM fungal abundance. At forest edges, ECM fungi were replaced by plant and animal pathogens, as well as copiotrophic, xenobiotic-degrading, and nitrogen-cycling bacteria, including nitrifiers and denitrifiers. Urbanization and forest edges interacted to generate new “suites” of microbes, with urban interior forests harboring highly homogenized microbiomes, while edge forest microbiomes were more heterogeneous and less stable, showing increased vulnerability to low soil moisture. When scaled to the regional level, we found that forest soils are projected to harbor high abundances of fungal pathogens and denitrifying bacteria, even in rural areas, due to the widespread existence of forest edges. Our results highlight the potential for soil microbiome dysfunction—including increased greenhouse gas production—in temperate forest regions that are subsumed by urban expansion, both now and in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Linking Associations of Rare Low-Abundance Species to Their Environments by Association Networks

Studies of microbial communities by targeted sequencing of rRNA genes lead to recovering numerous rare low-abundance taxa with unknown biological roles. We propose to study associations of such rare organisms with their environments by a computational framework based on transformation of the data into qualitative variables. Namely, we analyze the sparse table of putative species or OTUs (operational taxonomic units) and samples generated in such studies, also known as an OTU table, by collecting statistics on co-occurrences of the species and on shared species richness across samples. Based on the statistics we built two association networks, of the rare putative species and of the samples respectively, using a known computational technique, Association networks (Anets) developed for analysis of qualitative data. Clusters of samples and clusters of OTUs are then integrated and combined with metadata of the study to produce a map of associated putative species in their environments. We tested and validated the framework on two types of microbiomes, of human body sites and that of the Populus tree root systems. We show that in both studies the associations of OTUs can separate samples according to environmental or physiological characteristics of the studied systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Prioritizing the selection of CMIP6 model ensemble members for downscaling projections of CONUS temperature and precipitation

Given the mismatch between the large volume of data archived for the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and limited personnel and computational resources for downscaling, only a small fraction of the CMIP6 archive can be downscaled. In this work, we develop an approach to robustly sample projected hydroclimate states in CMIP6 for downscaling to test whether the selection of a single initial condition (IC) ensemble member from each CMIP6 model is sufficient to span the range of modeled hydroclimate over the conterminous United States (CONUS) and CONUS sub-regions. We calculate the pattern-centered root mean square difference of IC ensemble member anomalies relative to each model’s historical climatology for shared socioeconomic pathway (SSP) projections over 30-year time periods and compare the ratio of inter-model to intra-model variability for this metric. Regardless of SSP, inter-model variability is generally much greater than intra-model variability at the scales of the CONUS as a whole, as well as for most CONUS sub-regions. However, for some variables and scenarios, inter- and intra-model variability are similar at sub-CONUS scales, indicating that selecting a single IC ensemble member per model may be sufficient to sample the range of projected hydroclimate states in the 21st Century across CONUS, but for specific regions and variables, more careful selection of ensemble members may be necessary. Regionally resolved Taylor diagrams identify where more IC ensemble member downscaling efforts should be focused if resources are available to do so. Our results suggest that, with parsimonious sampling, the requisite computational expense of downscaling temperature and precipitation fields over the CONUS for subsequent CMIP activities may increase only marginally despite the great increase in data volumes with each successive CMIP phase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Measuring Fundamental Improvements in Sustainable Urban Mobility: The Mobility-Energy Productivity Metric

Recent technological advancements in mobility are creating many options for connecting citizens with employment, goods, and services, particularly in urban areas where modes such as bike and car shares, electric scooters, ridesourcing, and ridesharing are proliferating at a rapid pace. Analysis and tools for overall transportation planning are dominated by urban regional travel demand models whose roots in highway operations poorly reflect the system dynamics in denser areas where parking costs, convenience, and availability - not to mention sustainability concerns and quality of life - are driving people to an ever-greater spectrum of mobility services. In this paper, we present a new paradigm for evaluating mobility options within an urban area. First developed for the U.S. Department of Energy's Energy Efficient Mobility System research program, this metric is termed the mobility-energy productivity (MEP) metric. At its heart, the MEP metric measures accessibility and appropriately weights it with travel time, cost, and energy of modes that provide access to opportunities in any given location. The proposed metric is versatile in that it can be computed from readily available data sources or derived from outputs of regional travel demand models. End times associated with parking, curb access, cost, and reliability and frequency of service need to be carefully considered to obtain an appropriate and accurate perspective when computing the metric. Ultimately, the MEP metric can be used to reflect the impacts of new mobility technologies (transportation network companies, electric scooters), business models (car shares and bike shares), and land-use practices (such as transit-oriented development) on sustainable urban mobility. This paper lays out the need, requirements, and framework for this new metric, and offers it, in collaboration with the American Society for Civil Engineers (ASCE), as a foundational metric for smart city assessment.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2018

Community Organizations: Changing the Culture in Which Research Software Is Developed and Sustained

Software is the key crosscutting technology that enables advances in mathematics, computer science, and domain-specific science and engineering to achieve robust simulations and analysis for science, engineering, and other research fields. However, software itself has not traditionally received focused attention from research communities; rather, software has evolved organically and inconsistently, with its development largely as by-products of other initiatives. Moreover, challenges in scientific software are expanding due to disruptive changes in computer hardware, increasing scale and complexity of data, and demands for more complex simulations involving multiphysics, multiscale modeling and outer-loop analysis. In recent years, community members have established a range of grass-roots organizations and projects to address these growing technical and social challenges in software productivity, quality, reproducibility, and sustainability. This article provides an overview of such groups and discusses opportunities to leverage their synergistic activities while nurturing work toward emerging software ecosystems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The Influence of Shear on Deep Convection Initiation. Part I: Theory

Abstract This article introduces a novel hypothesis for the role of vertical wind shear (“shear”) in deep convection initiation (DCI). In this hypothesis, initial moist updrafts that exceed a width and shear threshold will “root” within a progressively deeper steering current with time, increase their low-level cloud-relative flow and inflow, widen, and subsequently reduce their susceptibility to entrainment-driven dilution, evolving toward a quasi-steady self-sustaining state. In contrast, initial updrafts that do not exceed the aforementioned thresholds experience suppressed growth by shear-induced downward pressure gradient accelerations, will not root in a deep-enough steering current to increase their inflow, will narrow with time, and will succumb to entrainment-driven dilution. In the latter case, an externally driven lifting mechanism is required to sustain deep convection, and deep convection will not persist in the absence of such lifting mechanism. A theoretical model is developed from the equations of motion to further explore this hypothesis. The model indicates that shear generally suppresses DCI, raising the initial subcloud updraft width that is necessary for it to occur. However, there is a pronounced bifurcation in updraft growth in the model after the onset of convection. Sufficiently wide initial updrafts grow and eventually achieve a steady state. In contrast, insufficiently wide initial updrafts shrink with time and eventually decay completely without external support. A sharp initial updraft radius threshold discriminates between these two outcomes. Thus, consistent with our hypothesis and observations, shear inhibits DCI in some situations, but facilitates it in others.

42 ENGINEERING↗
DOE OSTI2018

Reducing Arsenic Concentration in Panax notoginseng via Contaminant Immobilization in Soil Using Fe–Ce Oxide

Panax notoginseng (Burk.) F.H. Chen, a precious Chinese medicine, is currently confronted with arsenic (As) contamination in China due to soil pollution. Our previous research demonstrated that Fe(0) and zeolite had certain inhibitory effect on As accumulation in P. notoginseng. To further increase the As immobilization efficiency and to reduce As accumulation in the plant, a synthetic iron material (Fe-Ce oxide, FC) with high As adsorption capacity was tested for As remediation. P. notoginseng was planted in As-contaminated soil when the FC amendment was applied to the soil. The As leaching behavior of the treated soil and As accumulation in P. notoginseng were evaluated. Results showed that FC more effectively immobilized As than Fe(0) and zeolite in soils with high As concentrations. When the FC dosage was 0.5 wt.%, As concentration of P. notoginseng root (the main medicinal part) decreased by 55.8%, and its biomass increased by 54.6%. FC could reduce the non-specifically adsorbed As fraction (F1) and specifically adsorbed As fraction (F2) by 21.8%-30.6% and 4.6%-16.6%, respectively, thus reducing the TCLP (Toxicity Characteristic Leaching Procedure) concentration by 40.6%-67.0%. The finding of iron plaque coating on root and its function as a barrier for As uptake for P. notoginseng was reported for the first time. The occurrence of iron plaque led to As concentration reduction in the phellem and xylem/phloem by 65.6%-79.7% and 43.2%-70.2%, respectively, thus raising the proportion of As(III) to 75%. This study is of significance in developing As contamination control in P. notoginseng planting areas.

Lin, Longyong↗
DOE OSTI2020

Analytic Modeling of a Deep Shielding Problem

Previous generations of scientists would make tremendous efforts to simplify non-tractable problems and generate simpler models that preserved the fundamental physics. This process involved applying assumptions and simplifications to reduce the complexity of the problem until it reached a solvable form. Each assumption and simplification was chosen and applied with the intent to preserve the essential physics of the problem, since, if the core physics of the problem were eliminated, the simplified model served no purpose. Moreover, if done correctly, solutions to the reduced model would serve as useful approximations to the original problem. In a sense, solving the simple models laid the ground-work for and provided insight into the more complex problem. Today, however, the affordability of high performance computing has essentially replaced the process for analyzing complex problems. Rather than "building up" a problem by understanding smaller, simpler models, a user generally relies on powerful computational tools to directly arrive at solutions to complex problems. As computational resources grow, users continue trying to simulate new, more complex, or more detailed problems, resulting in continual stress on both the code and computational resources. When these resources are limited, the user will have to make concessions by simplifying the problem while trying to preserve important details. In the context of MCNP, simplifications typically come as reductions in geometry, or by using variance reduction techniques. Both approaches can influence the physics of the problem, leading to potentially inaccurate or non-physical results. Errors can also be introduced as a result of faulty input into a computational tool: something as simple as transposing numbers in a tally input can result in incorrect answers. In this paradigm, reduced complexity computational and analytical models still have an important purpose. The explicit form of an analytic solution is arguably the best way to understand the qualitative properties of simple models. In contrast to "building up" a complex problem through understanding simpler problems, results from detailed computational scenarios can be better explained by "building down" the complex model through simple models rooted in the fundamental or essential phenomenology. Simplified analytic and computational models can be used to 1) increase a user's confidence in the computational solution of a complex model, 2) confirm there are no user input errors, and 3) ensure essential assumptions of the simulation tool are preserved. This process of using analytic models to develop a more valuable analysis of simulation results is named the results analysis methodology. The utility of the results assessment methodology and a complimentary sensitivity analysis is exemplified through the analysis of the neutron flux in a dry used fuel storage cask. This application was chosen due to current scientific interest in used nuclear fuel storage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Analytic Modeling of a Deep Shielding Problem

Previous generations of scientists would make tremendous efforts to simplify non-tractable problems and generate simpler models that preserved the fundamental physics. This process involved applying assumptions and simplifications to reduce the complexity of the problem until it reached a solvable form. Each assumption and simplification was chosen and applied with the intent to preserve the essential physics of the problem, since, if the core physics of the problem were eliminated, the simplified model served no purpose. Moreover, if done correctly, solutions to the reduced model would serve as useful approximations to the original problem. In a sense, solving the simple models laid the ground-work for and provided insight into the more complex problem. Today, however, the affordability of high performance computing has essentially replaced the process for analyzing complex problems. Rather than "building up" a problem by understanding smaller, simpler models, a user generally relies on powerful computational tools to directly arrive at solutions to complex problems. As computational resources grow, users continue trying to simulate new, more complex, or more detailed problems, resulting in continual stress on both the code and computational resources. When these resources are limited, the user will have to make concessions by simplifying the problem while trying to preserve important details. In the context of the Monte Carlo N-Particle radiation transport simulation tool, simplifications typically come as reductions in geometry, or by using variance reduction techniques. Both approaches can influence the physics of the problem, leading to potentially inaccurate or non-physical results. Errors can also be introduced as a result of faulty input into a computational tool: something as simple as transposing numbers in a tally input can result in incorrect answers. In this paradigm, reduced complexity computational and analytical models still have an important purpose. The explicit form of an analytic solution is arguably the best way to understand the qualitative properties of simple models. In contrast to "building up" a complex problem through understanding simpler problems, results from detailed computational scenarios can be better explained by "building down" the complex model through simple models rooted in the fundamental or essential phenomenology. Simplified analytic and computational models can be used to 1) increase a user's confidence in the computational solution of a complex model, 2) confirm there are no user input errors, and 3) ensure essential assumptions of the simulation tool are preserved. This process of using analytic models to develop a more valuable analysis of simulation results is named the results assessment methodology. The utility of the results assessment methodology and a complimentary sensitivity analysis is exemplified through the analysis of the neutron flux in a dry used fuel storage cask. This application was chosen due to current scientific interest in used nuclear fuel storage.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

NGEE Arctic Plant Traits: Nodule Biomass, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, 2017

Nodule biomass was measured within fifteen plots at the Kougarok hillslope site in June and July of 2017. The sampled plots were distributed across two ecotypes that contain the deciduous shrub Alnus viridis subsp. fruticosa (alder). Alder forms a symbiosis with nitrogen-fixing Frankia bacteria living within root nodules. Nodule biomass per unit area was determined with extensive soil core collection under the alder canopy. Alder height and basal area were also recorded. This dataset contains one csv file and one pdf file.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Silicon Photomultiplier for Medical Imaging -Analysis of SiPM characteristics-

This paper proposes an automatic procedure, based on ROOT data Analysis Framework, for the analysis of Silicon Photomultipliers (SiPM) characteristics. In particular, it can be used to analyze experimental waveforms, from oscilloscope, containing SiPM pulses acquired at different temperatures and bias voltages. Important SiPMs characteristics such as: charge distribution, gain, breakdown voltage, pulse shape (rise time and recovery time) and overvoltage can been calculated. Developed procedure can be easily used to analyze any type of SiPM detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Measuring Fundamental Improvements in Sustainable Urban Mobility: The Mobility-Energy Productivity Metric: Preprint

Recent technological advancements in mobility are creating many options for connecting citizens with employment, goods, and services, particularly in urban areas where modes such as bike and car shares, electric scooters, ridesourcing, and ridesharing are proliferating at a rapid pace. Analysis and tools for overall transportation planning are dominated by urban regional travel demand models whose roots in highway operations poorly reflect the system dynamics in denser areas where parking costs, convenience, and availability - not to mention sustainability concerns and quality of life - are driving people to an ever-greater spectrum of mobility services. In this paper, we present a new paradigm for evaluating mobility options within an urban area. First developed for the U.S. Department of Energy's Energy Efficient Mobility System research program, this metric is termed the Mobility-Energy Productivity (MEP) metric. At its heart, the MEP metric measures accessibility and appropriately weights it with travel time, cost, and energy of modes that provide access to opportunities in any given location. The proposed metric is versatile in that it can be computed from readily available data sources or derived from outputs of regional travel demand models. End times associated with parking, curb access, cost, and reliability and frequency of service need to be carefully considered to obtain an appropriate and accurate perspective when computing the metric. Ultimately, the MEP metric can be used to reflect the impacts of new mobility technologies (transportation network companies, electric scooters), business models (car shares and bike shares), and land-use practices (such as transit-oriented development) on sustainable urban mobility. This paper lays out the need, requirements, and framework for this new metric, and offers it, in collaboration with the American Society for Civil Engineers (ASCE), as a foundational metric for Smart City assessment.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

AAPM Truth‐based CT (TrueCT) reconstruction grand challenge

Background: This Special Report summarizes the 2022, AAPM grand challenge on Truth-based CT image reconstruction. Purpose: To provide an objective framework for evaluating CT reconstruction methods using virtual imaging resources consisting of a library of simulated CT projection images of a population of human models with various diseases. Methods: Two hundred unique anthropomorphic, computational models were created with varied diseases consisting of 67 emphysema, 67 lung lesions, and 66 liver lesions. The organs were modeled based on clinical CT images of real patients. The emphysematous regions were modeled using segmentations from patient CT cases in the COPDGene Phase I dataset. For the lung and liver lesion cases, 1–6 malignant lesions were created and inserted into the human models, with lesion diameters ranging from 5.6 to 21.9 mm for lung lesions and 3.9 to 14.9 mm for liver lesions. The contrast defined between the liver lesions and liver parenchyma was 82 ± 12 HU, ranging from 50 to 110 HU. Similarly, the contrast between the lung lesions and the lung parenchyma was defined as 781 ± 11 HU, ranging from 725 to 805 HU. For the emphysematous regions, the defined HU values were −950 ± 17 HU ranging from −918 to −979 HU. The developed human models were imaged with a validated CT simulator. The resulting CT sinograms were shared with the participants. The participants reconstructed CT images from the sinograms and sent back their reconstructed images. Further, the reconstructed images were then scored by comparing the results against the corresponding ground truth values. The scores included both task-generic (root mean square error [RMSE] and structural similarity matrix [SSIM]), and task-specific (detectability index [d’] and lesion volume accuracy) metrics. For the cases with multiple lesions, the measured metric was averaged across all the lesions. To combine the metrics with each other, each metric was normalized to a range of 0 to 1 per disease type, with “0” and “1” being the worst and best measured values across all cases of the disease type for all received reconstructions. Results: The True-CT challenge attracted 52 participants, out of which 5 successfully completed the challenge and submitted the requested 200 reconstructions. Across all participants and disease types, SSIM absolute values ranged from 0.22 to 0.90, RMSE from 77.6 to 490.5 HU, d’ from 0.1 to 64.6, and volume accuracy ranged from 1.2 to 753.1 mm3. The overall scores demonstrated that participant “A” had the best performance in all categories, except for the metrics of d’ for lung lesions and RMSE for liver lesions. Participant “A” had an average normalized score of 0.41 ± 0.22, 0.48 ± 0.32, and 0.42 ± 0.33 for the emphysema, lung lesion, and liver lesion cases, respectively. Conclusions: The True-CT challenge successfully enabled objective assessment of CT reconstructions with the unique advantage of access to a diverse population of diseased human models with known ground truth. This study highlights the significant potential of virtual imaging trials in objective assessment of medical imaging technologies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Dynamics-Based Peptide–MHC Binding Optimization by a Convolutional Variational Autoencoder: A Use-Case Model for CASTELO

An unsolved challenge in the development of antigen-specific immunotherapies is determining the optimal antigens to target. Comprehension of antigen–major histocompatibility complex (MHC) binding is paramount toward achieving this goal. Here, we apply CASTELO, a combined machine learning-molecular dynamics (ML-MD) approach, to identify per-residue antigen binding contributions and then design novel antigens of increased MHC-II binding affinity for a type 1 diabetes-implicated system. We build upon a small-molecule lead optimization algorithm by training a convolutional variational autoencoder (CVAE) on MD trajectories of 48 different systems across four antigens and four HLA serotypes. We develop several new machine learning metrics including a structure-based anchor residue classification model as well as cluster comparison scores. ML-MD predictions agree well with experimental binding results and free energy perturbation-predicted binding affinities. Moreover, ML-MD metrics are independent of traditional MD stability metrics such as contact area and root-mean-square fluctuations (RMSF), which do not reflect binding affinity data. Finally, our work supports the role of structure-based deep learning techniques in antigen-specific immunotherapy design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Kinetics and dynamics of the C( 3 P) + H 2 O reaction on a full-dimensional accurate triplet state potential energy surface

A full dimensional accurate potential energy surface (PES) for the C( 3 P) and H 2 O reaction is developed based on ~34 000 data points calculated at the level of the explicitly correlated unrestricted coupled cluster method with single, double, and perturbative triple excitations with the augmented correlation-consistent polarized triple zeta basis set (CCSD(T)-F12a/AVTZ). The PES is invariant with respect to the permutation of the two hydrogen atoms and the total root mean square error (RMSE) of the fit is only 0.31 kcal mol -1 . The PES features two barriers in the entrance channel and several potential minima, as well as multiple product channels. The rate coefficients of this reaction calculated using a transition-state theory and quasi-classical trajectory (QCT) method are small near room temperature, consistent with experiments. The reaction dynamics is also investigated with QCT on the new PES, which found that the reactivity is constrained by the entrance barriers and the final product branching is not statistical.

Li, Jun↗
DOE OSTI2019

A Zoom-in Analysis of I/O Logs to Detect Root Causes of I/O Performance Bottlenecks

Scientific applications frequently spend a large fraction of their execution time in reading and writing data on parallel file systems. Identifying these I/O performance bottlenecks and attributing root causes are critical steps toward devising optimization strategies. Several existing studies analyze I/O logs of a set of benchmarks or applications that were run with controlled behaviors. However, there is still a lack of general approach that systematically identifies I/O performance bottlenecks for applications running "in the wild" on production systems. In this study, we have developed an analysis approach of "zooming in" from platform-wide to application-wide to job-level I/O logs for identifying I/O bottlenecks in arbitrary scientific applications. We analyze the logs collected on a Cray XC40 system in production over a two-month period. This study results in several insights for application developers to use in optimizing I/O behavior.

Wang, Teng↗
DOE OSTI2017

Large-amplitude nuclear motion formulated in terms of dissipation of quantum fluctuations

The potential-barrier penetrability and quasi-stationary thermal-decay rate of a metastable state are formulated in terms of microscopic quantum diffusion. Apart from linear coupling in momentum between the collective and internal subsystems, the formalism embraces the more general case of linear couplings in both the momentum and the coordinates. The developed formalism is then used for describing the process of projectile-nucleus capture by a target nucleus at incident energies near and below the Coulomb barrier. The capture partial probability, which determines the cross section for formation of a dinuclear system, is derived in analytical form. The total and partial capture cross sections, mean and root-mean-square angular momenta of the formed dinuclear system, astrophysical -factors, logarithmic derivatives, and barrier distributions are derived for various reactions. Also investigated are the effects of nuclear static deformation and neutron transfer between the interacting nuclei on the capture cross section and its isotopic dependence, and the entrance-channel effects on the capture process. The results of calculations for reactions involving both spherical and deformed nuclei are in good agreement with available experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗