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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A co-registered in-situ and ex-situ dataset from wire arc additive manufacturing process

Recent progress in sensing techniques and data analytics tools have significantly accelerated the development of Wire Arc Additive Manufacturing (WAAM) systems. This data-centric approach emphasizes leveraging sensor data available throughout the production process to optimize performance. Integration of extensive data analysis provides opportunities for improving precision, reducing waste, and enhancing the quality of produced parts. This method relies on AI/ML models and optimization techniques, which are developed using the data collected from various sources, including in-situ sensors, ex-situ imaging, and manufacturing process parameters. The quality and diversity of this data, along with the alignment between different data streams (achieved through spatiotemporal registration) are critical for the successful development of AI/ML and optimization models. In this work, we present a spatiotemporally registered dataset generated during the WAAM process of deposition of a rectangular block. The dataset includes a comprehensive description of the deposition process, process parameters, welding characteristics and acoustic data collected in-situ, and X-Ray Computed Tomography data of the build.

42 ENGINEERING↗
DOE OSTI2022

Evaluation of subsurface transport processes of delayed gas signatures applicable to underground nuclear explosions

Radioactive gas signatures from underground nuclear explosions (UNEs) result from gas-migration processes occurring in the subsurface. The processes considered in this study either drive or retard upward migration of gases from the detonation cavity. The relative importance of these processes is evaluated by simulating subsurface transport in a dual-permeability medium for the multi-tracer Noble Gas Migration Experiment (NGME) originally intended to study some aspects of transport from a UNE. For this experiment, relevant driving processes include weak two-phase convection driven by the geothermal gradient, over pressuring of the detonation cavity, and barometric pumping while gas sorption, dissolution, radioactive decay, and usually diffusion represent retarding processes. From deterministic simulations we found that over-pressuring of the post-detonation chimney coupled with barometric pumping produced a synergistic effect amplifying the tracer-gas reaching the surface. Bounding simulations indicated that the sorption and dissolution of gases, tending to retard transport, were much smaller than anticipated by earlier laboratory studies. The NGME observations themselves show that differences in gas diffusivity have a larger effect on influencing upward transport than do the combined effects of tracer-gas sorption and dissolution, which is consistent with a Sobol’ sensitivity analysis. Both deterministic simulations and those considering parametric uncertainties of transport-related properties predict that the excess in concentration of SF 6 compared to 127 Xe as might be captured in small volumetric samples should be much smaller than the order-of-magnitude contrast found in the large-volume gas samples taken at the site. While extraction of large-volume subsurface gas samples is shown to be capable of distorting in situ gas compositions, the highly variable injection rate of SF 6 into the detonation cavity relative to that of 127 Xe at the start of the field experiment is the most likely explanation for the large difference in observed concentrations.

58 GEOSCIENCES↗
DOE OSTI2016

Techno-economic analysis of a conceptual biofuel production process from bioethylene produced by photosynthetic recombinant cyanobacteria

Ethylene is a petrochemical produced in large volumes worldwide. It serves as a building block for a wide variety of plastics, textiles, and chemicals, and can be converted into liquid transportation fuels. There is great interest in the development of technologies that produce ethylene from renewable resources, such as biologically derived CO 2 and biomass. One of the metabolic pathways used by microbes to produce ethylene is via an ethylene-forming enzyme (EFE). By expressing a bacterial EFE gene in a cyanobacterium, ethylene has been produced through photosynthetic carbon fixation. Here, we present a conceptual design and techno-economic analysis of a process of biofuel production based on the upgradation of ethylene generated by the recombinant cyanobacterium. This analysis focuses on potential near-term to long-term cost projections for the integrated process of renewable fuels derived from ethylene. The cost projections are important in showing the potential of this technology and determining research thrusts needed to reach target goals. The base case for this analysis is a midterm projection using tubular photobioreactors for cyanobacterial growth and ethylene production, cryogenic distillation for ethylene separation and purification, a two-step Ziegler oligomerization process with subsequent hydrotreatment and upgradation for fuel production, and a wastewater treatment process that utilizes anaerobic digestion of cyanobacterial biomass. The minimum fuel selling price (MFSP) for the midterm projection is 15.07 per gallon gasoline equivalent (GGE). Near-term and long-term projections are 28.66 per GGE and 5.36 per GGE, respectively. Single- and multi-point sensitivity analyses are conducted to determine the relative effect that chosen variables could have on the overall costs. This analysis identifies several key variables for improving the overall process economics and outlines strategies to guide future research directions. Finally, the productivity of ethylene has the largest effect on cost and is calculated based on a number of variables that are incorporated into this cost model (i.e., quantum requirement, photon transmission efficiency, and the percent of energy going to either ethylene or cyanobacterial biomass production).

09 BIOMASS FUELS↗
DOE OSTI2019

Lignin valorization process control under feedstock uncertainty through a dynamic stochastic programming approach

The randomness introduced by reactants is an issue when processing renewable bioresources. In this paper, we apply tools from dynamic stochastic programming theory to the biochemical process. Instead of introducing extra preprocessing units, we consider the inherent randomness of the process and optimize in expectation the performance of the system. In a general setting, this is a multistage stochastic optimization problem and we investigate its approximate solution via two approaches, namely stochastic dual dynamic programming (SDDP) and the finite state, finite action Markov decision process (MDP) framework. These two methods are implemented to a case study of lignin valorization that is crucial to a cost-effective biorefinery process using biomass as the feedstock.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A green closed-loop process for selective recycling of lithium from spent lithium-ion batteries

As the economy started to recover from the COVID pandemic, the price of Li 2 CO 3 skyrocketed to its highest. This situation has aggravated concerns about the supply chain for lithium-ion batteries (LIBs). Recycling spent LIBs is a potential solution to alleviate the bottleneck of the supply chain and prevent environmental pollution, and has attracted lots of attention. However, lithium recycling is generally disregarded because of the complex recycling process and its low recycling efficiency. Here, in this work we developed a sustainable lithium recovery process, which can selectively leach and recover lithium with formic acid before recycling valuable metals. With the reported method, lithium can be 99.8% recovered from layered oxide cathode materials with 99.994% purity. In addition, this lithium recovery process is affordable, compared to the typical hydrometallurgical process, by saving 11.15% per kilogram of spent LIBs. Therefore, this research provided a new solution to eliminating the effects of lithium ions on valuable metal separation and the co-precipitation reaction and precluding the influence of other metal ions on lithium recovery. Finally, this simplified lithium recovery process provides new opportunities for sustainable recycling of LIBs and economical restoration of the lithium supply chain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Development of a continuous synthesis process for carbamazepine using validated in-line Raman spectroscopy and kinetic modelling for disturbance simulation

Mitigation of failure modes in the continuous synthesis (CS) of a drug substance (DS) has the potential to widen the adoption of continuous manufacturing (CM) technologies by the pharmaceutical industry. Here, this work demonstrates the development of a robust continuous process for the synthesis of carbamazepine (CBZ), an essential medicine as per the World Health Organization (WHO), facilitated by kinetic modelling and monitored by in-line Raman spectroscopy. Accurate kinetic modelling and the use of validated process analytical technology (PAT) models for quantitative measurement were found to play an important role in developing CS of drug substances. Kinetic data for the formation of CBZ from iminostilbene (ISB) were collected by batch reaction sampling and high-performance liquid chromatography (HPLC) analysis. A non-linear solver and iterative method was applied to determine two sets of Arrhenius parameters simultaneously for the reaction system by minimizing the standard error of the model fit. The start-up and dynamic equilibrium stages for the CS of CBZ using a continuous stirred tank reactor (CSTR) were modelled based on the batch kinetic data and employed to optimize conversion and simulate process disturbances. An in-line Raman spectroscopy method was successfully developed, validated, and integrated to determine the concentrations of CBZ and ISB within the operating range for the CS. The CS kinetic model was evaluated experimentally from startup to dynamic equilibrium over 10 residence times with monitoring by HPLC and in-line Raman spectroscopy. The developed kinetic model in tandem with in-line Raman spectroscopy successfully predicted disturbances due to changes in process variables and can serve as a useful tool in the future design of advanced process control strategies for the continuous synthesis of CBZ.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Impact of T - and ρ -dependent decay rates and new (n, γ ) cross-sections on the s process in low-mass asymptotic giant branch stars

Aims. We study the impact of nuclear input related to weak-decay rates and neutron-capture reactions on predictions for the slow neutron-capture process (s process) in asymptotic giant branch (AGB) stars. We provide the first database of surface abundances and stellar yields of the isotopes heavier than iron from the Monash models. Methods. We ran nucleosynthesis calculations with the Monash post-processing code for seven stellar structure evolution models of low-mass AGB stars with three different sets of nuclear inputs. The reference set has constant decay rates and represents the set used in the previous Monash publications. The second set contains the temperature and density dependence of β decays and electron captures based on the default rates of nuclear NETwork GENerator (NETGEN). In the third set, we further update 92 neutron-capture rates based on re-evaluated experimental cross sections from the ASTrophysical Rate and rAw data Library. We compare and discuss the predictions of the sets relative to each other in terms of isotopic surface abundances and total stellar yields. We also compare the results to isotopic ratios measured in presolar stardust silicon carbide (SiC) grains from AGB stars. Results. The new sets of models result in a ∼66% solar s-process contribution to the p-nucleus 152 Gd, confirming that this isotope is predominantly made by the s process. The nuclear input updates result in predictions for the 80 Kr/ 82 Kr ratio in the He intershell and surface 64 Ni/ 58 Ni, 94 Mo/ 96 Mo, and 137 Ba/ 136 Ba ratios that are more consistent with the corresponding ratios measured in stardust; however, the new predicted 138 Ba/ 136 Ba ratios are higher than the typical values of the SiC grains. The W isotopic anomalies are in agreement with data from the analyses of other meteoritic inclusions. We confirm that the production of 176 Lu and 205 Pb is affected by too large uncertainties in their decay rates from NETGEN.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The R-Process Alliance: Hunting for gold in the near-UV spectrum of 2MASS J05383296–5904280

Over the past few years, the R-Process Alliance (RPA) has successfully carried out a search for stars that are highly enhanced in elements produced via the rapid neutron-capture (r-) process. In particular, the RPA has identified a number of relatively bright, highly r-process-enhanced (r-II) stars, suitable for observations with the Hubble Space Telescope (HST), facilitating abundance derivation of elements such as gold (Au) and cadmium (Cd). This paper presents the detailed abundances derived for the metal-poor ([Fe/H] = −2.55) highly r-process-enhanced ([Eu/Fe] = +1.29) r-II star 2MASS J05383296–5904280. One-dimensional local thermodynamic equilibrium (LTE) elemental abundances were derived via equivalent width and spectral synthesis using high-resolution high signal-to-noise near-UV HST/STIS and optical Magellan/MIKE spectra. Abundances were determined for 43 elements, including 26 neutron-capture elements. In particular, abundances of the rarely studied elements Nb, Mo, Cd, Lu, Os, Pt, and Au are derived from the HST spectrum. These results, combined with RPA near-UV observations of two additional r-II stars, increase the number of Cd abundances derived for r-process-enriched stars from seven to ten and Au abundances from four to seven. A large star-to-star scatter is detected for both of these elements, highlighting the need for more detections enabling further investigations, specifically into possible non-LTE effects.

chemically peculiar stars↗
DOE OSTI2012

Experimental challenge to nuclear physics problems in the {nu}p-process

Astrophysical stellar reactions at extremely high temperatures involve a variety of problems both in nuclear reactions and nuclear structures. Specifically, the problems in the {nu}pprocess were discussed in this talk based on our recent experimental results with low-energy RI beams and a simulation study. The {nu}p-process is one of the key processes for investigating the mechanism of type II supernovae, and the process could be possibly responsible for 'the excess production' of p-nuclei around mass 90-100. Alpha cluster resonances have been discovered experimentally to play a crucial role for the stellar ({alpha}, p) reactions just above the alpha threshold. Neutron induced reactions in the proton-rich nuclear regions in the {nu}p-process are also suggested to play an important role, which involve nuclear structures of high level density at high excitation energies, probably giant resonances. The discussion also covered the p-nuclei production through the {nu}p-process at around mass 100.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Stretching the limits of forming processes by robust optimization: A demonstrator

Robust design of forming processes using numerical simulations is gaining attention throughout the industry. In this work, it is demonstrated how robust optimization can assist in further stretching the limits of metal forming processes. A deterministic and a robust optimization study are performed, considering a stretch-drawing process of a hemispherical cup product. For the robust optimization study, both the effect of material and process scatter are taken into account. For quantifying the material scatter, samples of 41 coils of a drawing quality forming steel have been collected. The stochastic material behavior is obtained by a hybrid approach, combining mechanical testing and texture analysis, and efficiently implemented in a metamodel based optimization strategy. The deterministic and robust optimization results are subsequently presented and compared, demonstrating an increased process robustness and decreased number of product rejects by application of the robust optimization approach.

36 MATERIALS SCIENCE↗
DOE OSTI2014

The transition probability and the probability for the left-most particle's position of the q-totally asymmetric zero range process

We treat the N-particle zero range process whose jumping rates satisfy a certain condition. This condition is required to use the Bethe ansatz and the resulting model is the q-boson model by Sasamoto and Wadati [“Exact results for one-dimensional totally asymmetric diffusion models,” J. Phys. A 31, 6057–6071 (1998)] or the q-totally asymmetric zero range process (TAZRP) by Borodin and Corwin [“Macdonald processes,” Probab. Theory Relat. Fields (to be published)]. We find the explicit formula of the transition probability of the q-TAZRP via the Bethe ansatz. By using the transition probability we find the probability distribution of the left-most particle's position at time t. To find the probability for the left-most particle's position we find a new identity corresponding to identity for the asymmetric simple exclusion process by Tracy and Widom [“Integral formulas for the asymmetric simple exclusion process,” Commun. Math. Phys. 279, 815–844 (2008)]. For the initial state that all particles occupy a single site, the probability distribution of the left-most particle's position at time t is represented by the contour integral of a determinant.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Porosity of additive manufacturing parts for process monitoring

Some metal additive manufacturing processes can produce parts with internal porosity, either intentionally (with careful selection of the process parameters) or unintentionally (if the process is not well-controlled.) Material porosity is undesirable for aerospace parts - since porosity could lead to premature failure - and desirable for some biomedical implants, since surface-breaking pores allow for better integration with biological tissue. Changes in a part's porosity during an additive manufacturing build may also be an indication of an undesired change in the process. We are developing an ultrasonic sensor for detecting changes in porosity in metal parts during fabrication on a metal powder bed fusion system, for use as a process monitor. This paper will describe our work to develop an ultrasonic-based sensor for monitoring part porosity during an additive build, including background theory, the development and detailed characterization of reference additive porosity samples, and a potential design for in-situ implementation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Optimization of oxidation processes to improve crystalline silicon solar cell emitters

Control of the oxidation process is one key issue in producing high-quality emitters for crystalline silicon solar cells. In this paper, the oxidation parameters of pre-oxidation time, oxygen concentration during pre-oxidation and pre-deposition and drive-in time were optimized by using orthogonal experiments. By analyzing experimental measurements of short-circuit current, open circuit voltage, series resistance and solar cell efficiency in solar cells with different sheet resistances which were produced by using different diffusion processes, we inferred that an emitter with a sheet resistance of approximately 70 Ω/□ performed best under the existing standard solar cell process. Further investigations were conducted on emitters with sheet resistances of approximately 70 Ω/□ that were obtained from different preparation processes. The results indicate that emitters with surface phosphorus concentrations between 4.96 × 10{sup 20} cm{sup −3} and 7.78 × 10{sup 20} cm{sup −3} and with junction depths between 0.46 μm and 0.55 μm possessed the best quality. With no extra processing, the final preparation of the crystalline silicon solar cell efficiency can reach 18.41%, which is an increase of 0.4%{sub abs} compared to conventional emitters with 50 Ω/□ sheet resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Modeling delay in genetic networks: From delay birth-death processes to delay stochastic differential equations

Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here, we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove a quantitative bound on the error between the pathwise realizations of these two processes. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemical Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the oscillatory behavior in negative feedback circuits, cross-correlations between nodes in a network, and spatial and temporal information in two commonly studied motifs of metastability in biochemical systems. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Analysis of electron capture process in charge pumping sequence using time domain measurements

A method for analyzing the electron capture process in the charge pumping (CP) sequence is proposed and demonstrated. The method monitors the electron current in the CP sequence in time domain. This time-domain measurements enable us to directly access the process of the electron capture to the interface defects, which are obscured in the conventional CP method. Using the time-domain measurements, the rise time dependence of the capture process is systematically investigated. We formulate the capture process based on the rate equation and derive an analytic form of the current due to the electron capture to the defects. Based on the formula, the experimental data are analyzed and the capture cross section is obtained. In addition, the time-domain data unveil that the electron capture process completes before the electron channel opens, or below the threshold voltage in a low frequency range of the pulse.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Quantum cascade laser based monitoring of CF{sub 2} radical concentration as a diagnostic tool of dielectric etching plasma processes

Dielectric etching plasma processes for modern interlevel dielectrics become more and more complex by the introduction of new ultra low-k dielectrics. One challenge is the minimization of sidewall damage, while etching ultra low-k porous SiCOH by fluorocarbon plasmas. The optimization of this process requires a deeper understanding of the concentration of the CF{sub 2} radical, which acts as precursor in the polymerization of the etch sample surfaces. In an industrial dielectric etching plasma reactor, the CF{sub 2} radical was measured in situ using a continuous wave quantum cascade laser (cw-QCL) around 1106.2 cm{sup −1}. We measured Doppler-resolved ro-vibrational absorption lines and determined absolute densities using transitions in the ν{sub 3} fundamental band of CF{sub 2} with the aid of an improved simulation of the line strengths. We found that the CF{sub 2} radical concentration during the etching plasma process directly correlates to the layer structure of the etched wafer. Hence, this correlation can serve as a diagnostic tool of dielectric etching plasma processes. Applying QCL based absorption spectroscopy opens up the way for advanced process monitoring and etching controlling in semiconductor manufacturing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A study of internal structure in components made by additive manufacturing process using 3 D X-ray tomography

Additive manufacturing methods are gaining increasing popularity for rapidly and efficiently manufacturing parts and components in the industrial context, as well as for domestic applications. However, except when used for prototyping or rapid visualization of components, industries are concerned with the load carrying capacity and strength achievable by additive manufactured parts. In this paper, the wire-arc additive manufacturing (AM) process based on gas tungsten arc welding (GTAW) has been examined for the internal structure and constitution of components generated by the process. High-resolution 3D X-ray tomography is used to gain cut-views through wedge-shaped parts created using this GTAW additive manufacturing process with titanium alloy materials. In this work, two different control conditions for the GTAW process are considered. The studies reveal clusters of porosities, located in periodic spatial intervals along the sample cross-section. Such internal defects can have a detrimental effect on the strength of the resulting AM components, as shown in destructive testing studies. Closer examination of this phenomenon shows that defect clusters are preferentially located at GTAW traversal path intervals. These results highlight the strong need for enhanced control of process parameters in ensuring components with minimal defects and higher strength.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Thermographic process monitoring in powderbed based additive manufacturing

Selective Laser Melting is utilized to build metallic parts directly from CAD-Data by solidification of thin powder layers through application of a fast scanning laser beam. In this study layerwise monitoring of the temperature distribution is used to gather information about the process stability and the resulting part quality. The heat distribution varies with different kinds of parameters including scan vector length, laser power, layer thickness and inter-part distance in the job layout which in turn influence the resulting part quality. By integration of an off-axis mounted uncooled thermal detector the solidification as well as the layer deposition are monitored and evaluated. Errors in the generation of new powder layers usually result in a locally varying layer thickness that may cause poor part quality. For effect quantification, the locally applied layer thickness is determined by evaluating the heat-up of the newly deposited powder. During the solidification process space and time-resolved data is used to characterize the zone of elevated temperatures and to derive locally varying heat dissipation properties. Potential quality indicators are evaluated and correlated to the resulting part quality: Thermal diffusivity is derived from a simplified heat dissipation model and evaluated for every pixel and cool-down phase of a layer. This allows the quantification of expected material homogeneity properties. Maximum temperature and time above certain temperatures are measured in order to detect hot spots or delamination issues that may cause a process breakdown. Furthermore, a method for quantification of sputter activity is presented. Since high sputter activity indicates unstable melt dynamics this can be used to identify parameter drifts, improper atmospheric conditions or material binding errors. The resulting surface structure after solidification complicates temperature determination on the one hand but enables the detection of potential surface defects on the other hand. These issues and proper key figures for thermographic monitoring of the Selective Laser Melting process are discussed in the paper. Even though microbolometric temperature measurement is limited to repetition rates in the Hz-regime and sub megapixel resolution, current results show the feasibility of process surveillance by thermography for a limited section of the building platform in a commercial system.

42 ENGINEERING↗