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Optoelectronic devices, such as photovoltaic devices, comprising a low band gap, solution processable diketopyrrolopyrrole or dithioketopyrrolopyrrole chromophore core or cores are disclosed. Also disclosed are methods of fabricating such optoelectronic devices.
This study present a test case in which the Bayesian Optimization method is applied to a simulation-based reactor core design optimization problem. The test case aims to showcase the potential of an automated design optimization algorithm for reactor designs by streamlining the reactor core design workflow, given the high computational cost of simulations. The contributions of this work are threefold. First, the existing HTGR model is converted into a simulation-based design optimization test case by developing a pipeline that enables modification of key design parameters and evaluates design performance based on simulation outputs. Second, Bayesian Optimization is implemented and adapted to demonstrate the feasibility of automatic design optimization for nuclear reactor core. Proposed approach leverages Gaussian Process models to characterize the relationship between design variables and performance metrics, while incorporating novel acquisition functions that balance exploration of the design space with exploitation of promising configurations. This implementation lays the foundation for the future developments of reactor design optimization algorithms.
In 2010, the National Aeronautics and Space Agency (NASA) of the U.S.A. and the Japanese Exploration Agency (JAXA) of Japan in cooperation with other U.S. and international partners will launch the Global Precipitation Measurement (GPM) mission. The mission center-piece is a core U.S. provided satellite holding a scanning microwave imager provided by the U.S. A. and a dual-frequency precipitation radar provided by Japan. The core satellite is in a 65 deg inclination (the current Tropical Rainfall Measuring Mission -TRMM is in a 35 deg inclination). Joining the core satellite are a constellation of approximately 8 satellites containing scanning radiometers. The purpose of the constellation is to increase the global sampling capability of the mission. One constellation satellite will be provided by NASA. Some of the constellation radiometers will provided by other U.S. agencies with existing (e.g. SSMI/S) or planned (NPOESS) radiometer assets. International groups have also expressed interest in contributing to the GPM mission including providing radiometer data for the GPM constellation. The use of a heterogeneous group of scanning radiometers each with its own unique purpose, characteristics and calibration offers a significant challenge for combining brightness temperatures or rain retrievals to create meaningful combined global radiometer products. However, the availability of active dual precipitation radar on the GPM core in combination with a well-calibrated radiometer on the same platform offers the possibility of inter-calibrating the constellation radiometers using the core satellite as a calibrator. This paper describes a joint NASA/GSFC and Colorado State University prototype effort at inter-calibrating existing radiometers using such a core calibrator approach. In the prototype, existing radiometers (i.e. SSM/I and AMSR-E) are intercalibrated, as required, using the TRMM Precipitation Radar (PR) and TRMM Microwave Imager (TMI) as the calibration core. This prototype includes four basic steps: provide the data in a normalized-common logical radiometer format, convert all data to a granule that stops and starts at the southernmost latitude rather than at the equator, perform basic processing and finally inter-calibrate the radiometers with the TRMM core as appropriate. Basic processing includes quality control, cross-track bias correction as well as the core action of converting T(sub a), to T(sub b). The purpose of the inter-calibration step is to provide consistent brightness temperatures for the various SSMA sensors, TMI and AMSR-E. The C appended to the level of the product indicates common brightness temperature (T(sub c)). The paper provides a summary of each of these actions. The details of the processing as well as data format and tools can be obtained by connecting to the website at mrain.atmos.colostate.eduLEVEL1C .
We investigate the ultrafast interfacial charge transfer dynamics in mixed-dimensional PbS/CdS quantum dot (QD)–monolayer MoS 2 heterostructures exhibiting a type-II band alignment. These 0D–2D heterostructures were assembled using oleic acid-capped PbS/CdS QDs with systematically varied core sizes deposited onto molecular beam epitaxy-grown monolayer MoS 2 . Steady-state and time-resolved optical spectroscopies revealed pronounced bidirectional charge transfer between the 0D and 2D components, involving both electron and hole exchange across the interface. The quenching of the monolayer MoS 2 A-exciton bleach and the modifications of its decay dynamics provide direct evidence for efficient hole transfer from photoexcited MoS 2 into the PbS QD core. Concurrently, attenuation of the QD ground-state bleach and the emergence of ultrafast decay components confirmed electron transfer from photoexcited QDs to monolayer MoS 2 . Both hole and electron transfer processes are dependent on the QD core size, with smaller cores enabling faster transfer rates and higher efficiencies due to enhanced band offsets and interfacial coupling. The complementary insights gained from transient absorption and time-resolved photoluminescence measurements clarify the mechanisms governing interfacial carrier exchange and highlight the importance of both hole and electron transfer as key components in the functioning of such 0D–2D heterostructures. This study underscores the potential of 0D–2D semiconductor heterostructures for advanced optoelectronic and light-energy conversion applications.
We perform monthly monitoring of the quasar 1633+382 (4C+38.41) within a sample of gamma-ray blazars with the VLBA at 43 GHz along with optical photometric and polarimetric observations. We construct the gamma-ray light curve of 1633+382 using data obtained by the Fermi LAT. We find that a high gamma-ray state of the quasar starting in 2009 September is simultaneous with an increase of the flux in the mm-wave VLBI core. We resolve a superluminal feature on the VLBA images that appears to be responsible for the mm-wave flux increase. We find a strong correlation between optical and gamma-ray light curves with a delay of gamma-ray variations of 5+/-3 days, as well as a strong correlation between optical flux and degree of polarization during the high gamma-ray state. Comparison between the optical polarization position angle and that in the VLBI core supports the idea that in the quasar 1633+382 a high gamma-ray state is connected with processes originating near the mm-VLBI core.
Novel perspectives of controlling molecular systems have recently arisen from the possibility of generating attosecond pulses in the ultraviolet regime and tailoring electron dynamics in its natural time scale. The cornerstone mechanism is the so-called charge migration, he production of a coherent charge transfer with subfemtosecond oscillations across a molecule. Typically, charge migration is induced by the ionization of valence molecular orbitals. However, recent technological developments allow the generation of attosecond pulses in the x-ray regime. Here, in this case, the absorption of photons creates core-hole states. In light elements, core-hole states mainly decay by Auger processes that, driven by electron correlations, involve valence orbitals. We theoretically demonstrate in a fluoroacetylene molecule a double-hole charge migration triggered by attosecond core-electron photoionization, followed by Auger electron relaxations. This opens a new route for inducing with x rays charge transfer processes in the subfemtosecond time scale.
Highlights: • Investigated the benefits of exfoliation mechanism of WS{sub 2} nanosheets. • C@e-WS{sub 2} was successfully synthesized via two step exfoliation -hydrothermal process. • C@e-WS{sub 2} core-shell confirmed by HRTEM. • C@e-WS{sub 2} core-shell photocatalyst exhibited excellent photocatalytic activity. • Photodegradation mechanism of C@e-WS{sub 2} photocatalyst is elucidated and discussed. - Abstract: Exfoliated Tungsten disulfide (e-WS{sub 2}) nanosheets were obtained from bulk Tungsten disulfide (WS{sub 2}) in a liquid-phase ultrasonic exfoliation method using a DMF solvent. Core-shell mannered carbon coating was developed by hydrothermal process on exfoliated Tungsten disulfide (e-WS{sub 2}) to enhance the efficient charge separation, specific surface area with mesoporosity and stability for chemical processes and mechanical strains. The carbon coated e-WS{sub 2} nanosheets (C@e-WS{sub 2}) was performed by series of characterization techniques and explored to the photocatalytic degradation of malachite green (MG) dye by comparing with bulk WS{sub 2} and e-WS{sub 2}. Among all the photocatalysts highest performance was observed for the C@e-WS{sub 2}. C@e-WS{sub 2} catalyst displays more than 11 fold enhancements in the photocomposition rate of MG over bulk WS{sub 2} and nearly 8 fold improvements over e-WS{sub 2} for 90 min irradiation. In addition, for complete degradation of MG dye over the bulk WS{sub 2}, e-WS{sub 2}, and C@e-WS{sub 2} catalysts were observed at 150, 130, and 90 min under simulated solar light irradiation. The results obtained using core-shell mannered C@e-WS{sub 2} are stepping stone for developing cost-effective and noble metal-free catalysts for photodegradation.
An element of the NASA/FAA wind shear program is the integration of ground-based microburst information on the flight deck, to support airborne wind shear alerting and microburst avoidance. NASA conducted a wind shear flight test program in the summer of 1991 during which airborne processing of Terminal Doppler Weather Radar (TDWR) data was used to derive microburst alerts. High level microburst products were extracted from TDWR, transmitted to a NASA Boeing 737 in flight via data link, and processed to estimate the wind shear hazard level (F-factor) that would be experienced by the aircraft in the core of each microburst. The microburst location and F-factor were used to derive a situation display and alerts. The situation display was successfully used to maneuver the aircraft for microburst penetrations, during which in situ 'truth' measurements were made. A total of 19 penetrations were made of TDWR-reported microburst locations, resulting in 18 airborne microburst alerts from the TDWR data and two microburst alerts from the airborne in situ measurements. The primary factors affecting alerting performance were spatial offset of the flight path from the region of strongest shear, differences in TDWR measurement altitude and airplane penetration altitude, and variations in microburst outflow profiles. Predicted and measured F-factors agreed well in penetrations near microburst cores. Although improvements in airborne and ground processing of the TDWR measurement would be required to support an airborne executive-level alerting protocol, the feasibility of airborne utilization of TDWR data link data has been demonstrated.
Purpose: This project seeks to demonstrate a new high-throughput (rapid) alloy design technique applied to creating new high entropy alloys (HEAs) for extreme environments. High entropy alloys shift the design paradigm from being focused on a single principal element (e.g. nickel-based alloys) to target alloys that include high atomic fractions (X >10%) of multiple elements. These HEA materials can exhibit sluggish diffusion and enhanced corrosion resistance, ideal for potential applications in advanced ultra supercritical (A-USC) steam cycles for power generation. Scope: The addition of multiple elements in high atomic fractions creates an enormous design space that cannot easily be investigated by traditional material design strategies such as designed of experiments (DOE). This project utilizes a Bayesian machine learning algorithm that has been modified to work with calculation of phase diagrams (CALPHAD) software. This Bayesian algorithm reduces manual inputs and increase the likelihood of achieving an optimal solution. Compositional inputs to this algorithm will be assessed using existing material property models for high temperature strength and corrosion resistance. The target for alloy performance will be a 15% (~100 ⁰C) increase in allowable service temperature beyond heat-resistant stainless steels while maintaining or improving alloy cost and corrosion resistance. Haynes 230 was selected as a baseline, which is 57 wt% Ni with 22 wt% Cr 14 wt% W, and 2 wt% Mo as solid solution strengtheners. In addition to rapid design via Bayesian machine learning, the alloys were rapidly fabricated using a multi-wire arc additive manufacturing (mWAAM) technique which allows for precise control of alloy composition and assessing of alloy design “windows” to study composition effects. Build speeds for wire-arc additive processes are among the highest for additive technologies enabling rapid and reliable sample fabrication when compared to conventional methods such as arc button melting. The mWAAM samples will be rapidly characterized via instrumented indentation for room temperature modulus and strength and for elevated temperature strength via hot hardness tests. After being screened with hardness testing, potential alloys will be further evaluated with conventional microscopy techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to assess agreement with modeling results. The most promising compositions will also be evaluated by printing full sized tensile specimens for mechanical behavior tests at elevated temperatures. Results: Bayesian machine learning of a single performance function was initially used to optimize five performance metrics: 1) single phase stability, 2) yield strength, 3) creep resistance (low diffusion coefficient), 4) freezing range (weldability), and 5) material cost. The single performance function was suboptimal as assumptions had to be made about the results while formulating the optimization. A goal-oriented Bayesian optimization strategy (Hanaoka, 2021) was implemented with CALPHAD for use with the five metrics above. This multi-objective Bayesian optimization (MOBO) enabled the design of NiCrCoFe alloys with V and W additions. A base composition of NiCoCr was selected as Ni provides a stable FCC matrix, Cr aids corrosion/oxidation resistance, and Co is a solid-solutions strengthener that also improves creep by increasing the activation energy. Fe helps reduce diffusion coefficients and cost. Finally, V and W were selected for their reasonable solubility and high atomic misfit to aid in solid solution strengthening. Cracking of the mWAAM specimens was an early issue, and the Easton solidification cracking model (Easton et al., 2014a) was selected for addition to the MOBO function. High performing alloys fabricated by mWAAM included Ni 28 Cr 25 Co 26 Fe 15 V 8 and Ni 62 Cr 18 Co 1 Fe 3 W 15 . It was observed that even after adapting the mWAAM process for W, the W did not fully dissolve. To fully evaluate the Ni 62 Cr 18 Co 1 Fe 3 W 15 composition, a cored wire (80-20 NiCr sheath/powder core) was manufactured and printed via WAAM, and HIP’ing was utilized to homogenize and densify the printed alloy. The V and W alloys produced met metrics 1 (solid solution), 4 (solidification cracking), and 5 (cost). However, an unmodeled mechanism of thermal stress cracking was identified in the WAAM produced materials, perhaps exacerbated by the lack of grain boundary strengthening elements (B, C). Conclusions & Recommendations: A high-throughput (rapid) alloy design technique was applied to designing and manufacturing new high entropy alloys (HEAs) for extreme environments utilizing MOBO and mWAAM. The developed process was rapid and effective in addressing the mechanisms included in the model. The lack of grain boundary strengthening element additions (e.g., B, C) was a simplification that likely produced thermal stress cracking that turned into a large part of the investigation. Additions on the order of 0.005 wt% B and 0.05 wt% C likely would have minimized thermal stress grain boundary cracking. Overall, the high throughput design strategy is promising for rapid design of metrics-driven alloys for advanced ultra supercritical (A-USC) steam cycles for power generation. The MOBO and mWAAM process could be commercialized to accelerate metrics-driven alloy design. In addition, the cored-wire process utilized for scale-up is a promising high-volume process for WAAM alloy development and scale-up.
A long-lived central engine embedded in expanding supernova ejecta can alter the dynamics and observational signatures of the event, producing an unusually luminous, energetic, and/or rapidly evolving transient. We use 2D hydrodynamics simulations to study the effect of a central energy source, varying the amount, rate, and isotropy of the energy deposition. We post-process the results with a time-dependent Monte Carlo radiation transport code to extract observational signatures. The engine excavates a bubble at the centre of the ejecta, which becomes Rayleigh–Taylor unstable. Sufficiently powerful engines are able to break through the edge of the bubble and accelerate, shred, and compositionally mix the entire ejecta. The breakout of the engine-driven wind occurs at distinct rupture points, and the outflowing high-velocity gas may eventually give rise to radio emission. The dynamical impact of the engine leads to faster rising optical light curves, with photon escape facilitated by the faster expansion of the ejecta and the opening of low-density channels. For models with strong engines, the spectra are initially hot and featureless, but later evolve to resemble those of broad-line Ic supernovae. Under certain conditions, line emission from ionized, low-velocity material near the centre of the ejecta may be able to escape and produce narrow emission similar to that seen in interacting supernovae. We discuss how variability in the engine energy reservoir and injection rate could give rise to a heterogeneous set of events spanning multiple observational classes, including the fast blue optical transients, broad-line Ic supernovae, and superluminous supernovae.
This study was initiated to identify operations problems and cost drivers for current propulsion systems and to identify technology and design approaches to increase the operational efficiency and reduce operations costs for future propulsion systems. To provide readily usable data for the Advance Launch System (ALS) program, the results of the Operationally Efficient Propulsion System Study (OEPSS) were organized into a series of OEPSS Data Books as follows: Volume 1, Generic Ground Operations Data; Volume 2, Ground Operations Problems; Volume 3, Operations Technology; Volume 4, OEPSS Design Concepts; and Volume 5, OEPSS Final Review Briefing, which summarizes the activities and results of the study. This volume presents ground processing data for a generic LOX/LH2 booster and core propulsion system based on current STS experience. The data presented includes: top logic diagram, process flow, activities bar-chart, loaded timelines, manpower requirements in terms of duration, headcount and skill mix per operations and maintenance instruction (OMI), and critical path tasks and durations.
The Bioprocessing Separations Consortium solves separations challenges that are unique to bioprocessing. To do this, the Consortium uses two methods: applying existing technologies to new challenges and developing new technologies that may address these unique challenges better than today’s commercial technologies. In its research and development, the Consortium leverages its three core capabilities: materials development and evaluation, process development, and analysis and computation. In its first three years, from 2016 to 2019, the Consortium addressed four critical challenges in biochemical and thermochemical processing. First, the Consortium targeted the fractionation of lignin to enable valorization of this portion of biomass that offers diverse, complex, and valuable building blocks and products. Second, Consortium researchers developed technologies to enable process intensification, which can reduce equipment needs, energy consumption, and waste generation, thereby cutting bioprocessing capital costs and rendering processes more efficient. Third, the Consortium sought to recover carbon from dilute aqueous streams that are common to bioprocessing; recovering dilute carbon can improve process efficiency and economics. Finally, Consortium researchers designed and developed new materials and catalysts to reduce targeted foulants and poisons in bioprocessing streams that can limit the lifetime of downstream catalysts or fermenting microorganisms. Table 1 lists the technologies that were examined and places them in the context of the Consortium’s capabilities, types of bioprocesses, and critical challenges in bioprocessing separations. Overall, across these projects, we have developed separations technologies for 10 bioprocesses, addressed 9 target compounds in bioprocessing, developed 10 materials, and evaluated 4 processes for cost and sustainability.
The Bioprocessing Separations Consortium solves separations challenges that are unique to bioprocessing. To do this, the Consortium uses two methods: applying existing technologies to new challenges and developing new technologies that may address these unique challenges better than today’s commercial technologies. In its research and development, the Consortium leverages its three core capabilities: materials development and evaluation, process development, and analysis and computation. In its first three years, from 2016 to 2019, the Consortium addressed four critical challenges in biochemical and thermochemical processing. First, the Consortium targeted the fractionation of lignin to enable valorization of this portion of biomass that offers diverse, complex, and valuable building blocks and products. Second, Consortium researchers developed technologies to enable process intensification, which can reduce equipment needs, energy consumption, and waste generation, thereby cutting bioprocessing capital costs and rendering processes more efficient. Third, the Consortium sought to recover carbon from dilute aqueous streams that are common to bioprocessing; recovering dilute carbon can improve process efficiency and economics. Finally, Consortium researchers designed and developed new materials and catalysts to reduce targeted foulants and poisons in bioprocessing streams that can limit the lifetime of downstream catalysts or fermenting microorganisms. Table 1 lists the technologies that were examined and places them in the context of the Consortium’s capabilities, types of bioprocesses, and critical challenges in bioprocessing separations. Overall, across these projects, we have developed separations technologies for 10 bioprocesses, addressed 9 target compounds in bioprocessing, developed 10 materials, and evaluated 4 processes for cost and sustainability.
The Bioprocessing Separations Consortium solves separations challenges that are unique to bioprocessing. To do this, the Consortium uses two methods: applying existing technologies to new challenges and developing new technologies that may address these unique challenges better than today’s commercial technologies. In its research and development, the Consortium leverages its three core capabilities: materials development and evaluation, process development, and analysis and computation. In its first three years, from 2016 to 2019, the Consortium addressed four critical challenges in biochemical and thermochemical processing. First, the Consortium targeted the fractionation of lignin to enable valorization of this portion of biomass that offers diverse, complex, and valuable building blocks and products. Second, Consortium researchers developed technologies to enable process intensification, which can reduce equipment needs, energy consumption, and waste generation, thereby cutting bioprocessing capital costs and rendering processes more efficient. Third, the Consortium sought to recover carbon from dilute aqueous streams that are common to bioprocessing; recovering dilute carbon can improve process efficiency and economics. Finally, Consortium researchers designed and developed new materials and catalysts to reduce targeted foulants and poisons in bioprocessing streams that can limit the lifetime of downstream catalysts or fermenting microorganisms. Table 1 lists the technologies that were examined and places them in the context of the Consortium’s capabilities, types of bioprocesses, and critical challenges in bioprocessing separations. Overall, across these projects, we have developed separations technologies for 10 bioprocesses, addressed 9 target compounds in bioprocessing, developed 10 materials, and evaluated 4 processes for cost and sustainability.
The Transformational Challenge Reactor (TCR) program plans to build most of the TCR core components through additive manufacturing (AM) processes. These processes include laser powder bed fusion (LPBF) for the metallic (316L) components and the newly developed combined process of binderjet printing and chemical vapor infiltration (CVI) for the SiC fuel matrix. Mechanical testing and characterization tasks have been carried out since the beginning of the TCR program to (1) build a property database for the AM materials that will be used in TCR core and (2) to assess the materials’ performance in TCR-relevant conditions. This document reports the outcome of the testing and characterization efforts for the fiscal year with a focus on the mechanical performance data of AM 316L stainless steel (SS). Baseline tensile testing over a wide temperature range of room temperature–600 °C was completed for the AM 316L alloy in as-built, stress-relieved, and solution-annealed conditions. The as-built 316L showed the highest strength, and the alloy after the post-build treatments showed reduced strengths in the low-strain range. However, the strength differences among the AM materials became insignificant in the later part of deformation. Furthermore, regardless of post-build processing, the AM 316L SS showed higher strength and comparable ductility when compared with wrought 316L SS. Thermal creep testing and microstructural evolution during creep deformation were also performed under selected conditions. It was found that the AM 316L steel showed the best creep resistance in the stress-relieved condition. In-situ tensile tests were performed using scanning electron microscopy and 1-ID beamline at the Advanced Photon Source to elucidate the deformation and fracture behavior of AM 316L and the evolution of crystalline stress, dislocations, and pore distribution. Using these in-situ testing data, an in-depth analysis of the roles of microstructural features in deformation and fracture processes is presented herein. The final section of the document introduces ongoing and future activities for materials testing and characterization, including irradiation effect studies and ball punch testing on AM 316L and AM IN718 alloys.
Abstract We describe an ocean hydrostatic dynamical core implemented in Oceananigans optimized for Graphical Processing Unit (GPU) architectures. On 64 A100 GPUs, equivalent to 16 computational nodes in current state‐of‐the‐art supercomputers, our dynamical core can simulate a decade of near‐global ocean dynamics per wall‐clock day at an 8‐km horizontal resolution; a resolution adequate to resolve the ocean's mesoscale eddy field. Such efficiency, achieved with relatively modest hardware resources, suggests that climate simulations on GPUs can incorporate fully eddy‐resolving ocean models. This removes a major source of systematic bias in current IPCC coupled model projections, the parameterization of ocean eddies, and represents a major advance in climate modeling. We discuss the computational strategies, focusing on GPU‐specific optimization and numerical implementation details that enable such high performance.
Friction consolidation (FC) is a solid phase processing approach where discrete material forms such as powders, chips, nuggets, etc. are densified via shear deformation. The precursors are placed in a billet container and brought in contact with a rotating tool that applying the desirable amount of normal force. Under the combined action of the rotation and normal pressure, the discrete precursor is consolidated through porosity reduction and shear deformation. FC is increasingly being studied as an attractive approach to manufacturing fully dense parts from powder forms owing to its ability to mix, alloy and consolidate difficult-to-process precursors in minimal number of process steps. Material consolidation and deformation in shear consolidation processes have been studied extensively previously for different material combinations previously. However, despite the extensive research in this area, understanding of the mechanistic processes in pore consolidation, deformation-induced mixing and material solubility during FC is still evolving. Material development using solid phase processing approaches such as FC is often performed based on research experience/education, which can be biased. Conventional analysis and simulation tools in this area tend to be successful only when material thermodynamic pathways and microstructural evolution sequences resulting from processing are clearly defined or known. They are not as effective for emerging advanced manufacturing technologies where material evolution pathways are not well established. The ability to predict optimal process parameters based on material chemistry and bulk properties is essential to accelerate materials design and processing, as are an understanding of the relevant structure-processing-property relationships. These structure-processing-property-performance relationships are at the core of materials science research. Microstructure characterization provides the link to these four core areas, often through visualizing material microstructure using imaging techniques. However, linking microstructure image data (i.e., micrographs) to variables of interest (e.g., processing parameters, material chemistry) in a reproducible, generalizable, and quantitative manner is a significant challenge. Typically, quantitatively linking image data to processing history relies on significant domain knowledge and manual or subject matter expert (SME)-heuristic based image analysis. Such an approach to image analysis has the potential to be biased, inefficient, and difficult to replicate.
The origin of the Z greater than 28, ultraheavy (UH) cosmic rays in supernova explosions of massive stars, at least about 10 solar masses, is considered. For Z greater than 70, the UH data are dominated by an r-process source distribution, but for the elements just beyond iron, Z from 29 to 36, the data cannot be explained by any single process of nucleosynthesis. This problem is solved naturally in a massive-star model by secondary neutron-capture reactions occurring during core helium burning (a limited s-process) and during explosive carbon burning. Interstellar-propagation calculations have been performed with these episodes of synthesis as source distributions, and the results offer an explanation for the current UH cosmic-ray data. Further, the heavy-element synthesis during explosive carbon burning is re-examined by using more realistic initial conditions given by the post-helium-burning configuration of the star. These results are compared with earlier work and the UH cosmic-ray data. Some effects of preferential acceleration, based upon ionization potential, are considered, and experimental tests for this model are discussed.