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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 OSTI2022

Controlling process instability for defect lean metal additive manufacturing

The process instabilities intrinsic to the localized laser-powder bed interaction cause the formation of various defects in laser powder bed fusion (LPBF) additive manufacturing process. Particularly, the stochastic formation of large spatters leads to unpredictable defects in the as-printed parts. Here we report the elimination of large spatters through controlling laser-powder bed interaction instabilities by using nanoparticles. The elimination of large spatters results in 3D printing of defect lean sample with good consistency and enhanced properties. We reveal that two mechanisms work synergistically to eliminate all types of large spatters: (1) nanoparticle-enabled control of molten pool fluctuation eliminates the liquid breakup induced large spatters; (2) nanoparticle-enabled control of the liquid droplet coalescence eliminates liquid droplet colliding induced large spatters. The nanoparticle-enabled simultaneous stabilization of molten pool fluctuation and prevention of liquid droplet coalescence discovered here provide a potential way to achieve defect lean metal additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2017

SME Acceptability Determination For DWPF Process Control (U)

The statistical system described in this document is called the Product Composition Control System (PCCS). K. G. Brown and R. L. Postles were the originators and developers of this system as well as the authors of the first three versions of this technical basis document for PCCS. PCCS has guided acceptability decisions for the processing at the Defense Waste Processing Facility (DWPF) at the Savannah River Site (SRS) since the start of radioactive operations in 1996. The author of this revision to the document gratefully acknowledges the firm technical foundation that Brown and Postles established to support the ongoing successful operation at the DWPF. Their integration of the glass propertycomposition models, developed under the direction of C. M. Jantzen, into a coherent and robust control system, has served the DWPF well over the last 20+ years, even as new challenges, such as the introduction into the DWPF flowsheet of auxiliary streams from the Actinide Removal Process (ARP) and other processes, were met. The purpose of this revision is to provide a technical basis for modifications to PCCS required to support the introduction of waste streams from the Salt Waste Processing Facility (SWPF) into the DWPF flowsheet. An expanded glass composition region is anticipated by the introduction of waste streams from SWPF, and property-composition studies of that glass region have been conducted. Jantzen, once again, directed the development of glass property-composition models applicable for this expanded composition region. The author gratefully acknowledges the technical contributions of C.M. Jantzen leading to the development of these glass property-composition models. The integration of these models into the PCCS constraints necessary to administer future acceptability decisions for the processing at DWPF is provided by this sixth revision of this document.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Lamination of >21% Efficient Perovskite Solar Cells with Independent Process Control of Transport Layers and Interfaces

Transport layer and interface optimization is critical for improving the performance and stability of perovskite solar cells (PSCs) but is restricted by the conventional fabrication approach of sequential layer deposition. While the bottom transport layer is processed with minimum constraints, the narrow thermal and chemical stability window of the halide perovskite (HP) layer severely restricts the choice of top transport layer and its processing conditions. To overcome these limitations, we demonstrate lamination of HPs—where two transport layer-perovskite half-stacks are independently processed and diffusion-bonded at the HP-HP interface—as an alternative fabrication strategy that enables self-encapsulated solar cells. Power conversion efficiencies (PCE) of >21% are realized using cells that incorporate a novel transport layer combination along with dual-interface passivation via self-assembled monolayers, both of which are uniquely enabled by the lamination approach. This is the highest reported PCE for any laminated PSC encapsulated between glass substrates. We further show that this approach expands the processing window beyond traditional fabrication processes and is adaptable for different transport layer compositions. The laminated PSCs retained >75% of their initial PCE after 1000 h of 1-sun illumination at 40 °C in air using an all-inorganic transport layer configuration without additional encapsulation. Furthermore, a laminated 1 cm 2 device maintained a V oc of 1.16 V. Finally, the scalable lamination strategy in this study enables the implementation of new transport layers and interfacial engineering approaches for improving performance and stability.

14 SOLAR ENERGY↗
DOE OSTI2025

Employing MACS/ViBRANT as a Surrogate MARVEL Reactor for Startup Reactivity Tuning and Supervisory Control Processes

Advanced nuclear reactors are a key part of the future of nuclear energy both in the United States and globally. They offer unique benefits for various energy-demanding applications, including use in remote locations, compact size, modular manufacturing, remote monitoring, low and/or variable power rating operation, and reliance on novel technologies to enhance operational safety. To achieve economic feasibility, advanced reactors must significantly reduce their workforces in comparison with the current fleet. Achieving this reduction will occur through reducing staff workloads using technology to achieve autonomous or semi-autonomous operations, demonstrated by comprehensive testing and validation activities. These operations will require both software and hardware platforms during the design and testing phases. While simulations are useful during the design phase, their performance can significantly deviate during actual deployment on hardware. This report presents the outcomes of a collaborative technical initiative between the U.S. Department of Energy (DOE) Microreactor Program (MRP) and Advanced Sensors and Instrumentation (ASI) Program. The collaboration utilized the Microreactor Automated Control System (MACS) hardware platform to bridge the gap between theoretical reactor design and actual startup and control operations. Two key use cases were investigated: facilitating the startup testing period and demonstrating supervisory control. The first use case details the key Microreactor Applications Research Validation and Evaluation (MARVEL) reactor startup physics testing activities conducted using the MACS platform. These activities included drum worth measurements, shutdown margin assessment, temperature feedback analysis, and scram time evaluation, as well as unique testing that would apply to the MARVEL reactor to demonstrate the testing methodologies in a low-risk environment. The MACS platform, serving as a surrogate representation of the MARVEL reactor, proved instrumental in performing these tests. The exercise revealed aspects that led to optimized processes, refined hardware design, and enhanced base software capabilities. By maturing methods and technologies in this manner, the initiative promises to reduce wasted time in the actual on-site reactor deployment effort, thereby saving significant time and resources. The second use case focuses on the development and implementation of supervisory control methods aimed at managing core tilt, which can result from asymmetrical operations or manufacturing imperfections in fuel rods or reactivity control devices. A key objective was to assess and compare the use of artificial intelligence (AI) for supervisory control. The effort aimed to define the role of supervisory control to enhance performance without risking control instability. This effort explored three distinct approaches: rules-based (RB) methods, optimization techniques, and reinforcement learning (RL) algorithms. Each approach was evaluated for its ease of implementation, its usability, and its effectiveness in responding to asymmetries in neutron flux. Comparative analysis of these approaches provided valuable insights into their applicability and effectiveness, offering a robust framework for advanced reactor operations. Together, these two use cases highlight the potential of hardware test beds to help streamline the design, operation, and control of advanced nuclear reactors. This collaborative effort underscores the importance of continued innovation and experimentation in achieving the next generation of safe, reliable, and economically viable nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Surface Processes Control the Fate of Reactive Oxidants Generated by Electrochemical Activation of Hydrogen Peroxide on Stainless-Steel Electrodes

Low-cost stainless-steel electrodes can activate hydrogen peroxide (H 2 O 2 ) by converting it into a hydroxyl radical ( • OH) and other reactive oxidants. At an applied potential of +0.020 V, the stainless-steel electrode produced • OH with a yield that was over an order of magnitude higher than that reported for other systems that employ iron oxides as catalysts under circumneutral pH conditions. Decreasing the applied potential at pH 8 and 9 enhanced the rate of H 2 O 2 loss by shifting the process to a reaction mechanism that resulted in the formation of an Fe(IV) species. Significant metal leaching was only observed under acidic pH conditions (i.e., at pH <6), with the release of dissolved Fe and Cr occurring as the thickness of the passivation layer decreased. Despite the relatively high yield of • OH production under circumneutral pH conditions, most of the oxidants were scavenged by the electrode surface when contaminant concentrations comparable to those expected in drinking water sources were tested. The stainless-steel electrode efficiently removed trace organic contaminants from an authentic surface water sample without contaminating the water with Fe and Cr. With further development, stainless-steel electrodes could provide a cost-effective alternative to other H 2 O 2 activation processes, such as those by ultraviolet light.

42 ENGINEERING↗
DOE OSTI2017

Spatial variation in microbial processes controlling carbon mineralization within soils and sediments

Soils have a defining role in global carbon cycling, having one of the largest dynamic stocks of C on earth—3300 Pg of C are stored in soils, which is three-times the amount stored in the atmosphere and more than the terrestrial land plants. An important control on soil organic matter (SOM) quantities is the mineralization rate. It is well recognized that the rate and extent of SOM mineralization is affected by climatic factors and mineral-organic matter associations. What remained elusive is to what extent constraints on microbial metabolism induced by the respiratory pathway, and specifically the electron acceptor in respiration, control overall rates of carbon mineralization in soils. Therefore, physical factors limiting oxygen diffusion such as soil texture and aggregate size (soil structure) may therefore be central controls on C mineralization rates. The goal of our research was therefore to determine if variations in microbial metabolic rates induced by anaerobic microsites in soils are a major control on SOM mineralization rates and thus storage. We performed a combination of laboratory experiments and field investigations will be performed to fulfill our research objectives. We used laboratory studies to examine fundamental factors of respiratory constraints (i.e., electron acceptor) on organic matter mineralization rates. We ground our laboratory studies with both manipulation of field samples and in-field measurements. Selection of the field sites is guided by variation in soil texture and structure while having (other environmental/soil factors constant. Our laboratory studies defined redox gradients and variations in microbial metabolism operating at the aggregate-scale (cm-scale) within soils using a novel constructed diffusion reactor. We further examined micro-scale variation in terminal electron accepting processes and resulting C mineralization rates within re-packed soils. A major outcome of our research is the ability to quantitatively place the importance of aggregate-based heterogeneity in microbial redox processes and the resulting lack of oxygen on the rate of carbon mineralization. Collectively, our research shows that anaerobic microsites are prevalent in soils and are important regulators of soil carbon persistence, shifting microbial metabolism to less efficient anaerobic respiration and selectively protecting otherwise bioavailable, reduced organic compounds such as lipids and waxes from decomposition. Further, shifting from anaerobic to aerobic conditions leads to a 10-fold increase in volume-specific mineralization rate, illustrating the sensitivity of anaerobically protected carbon to disturbance. Vulnerability of anaerobically protected carbon to future climate or land use change thus constitutes a yet unrecognized soil carbon-climate feedback that should be incorporated into terrestrial ecosystem models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Coupled Biotic-Abiotic Processes Control Biogeochemical Cycling of Dissolved Organic Matter in the Columbia River Hyporheic Zone

A critical component of assessing the impacts of climate change on watershed ecosystems involves understanding the role that dissolved organic matter (DOM) plays in driving whole ecosystem metabolism. The hyporheic zone—a biogeochemical control point where ground water and river water mix—is characterized by high DOM turnover and microbial activity and is responsible for a large fraction of lotic respiration. Yet, the dynamic nature of this ecotone provides a challenging but important environment to parse out different DOM influences on watershed function and net carbon and nutrient fluxes. We used high-resolution Fourier-transform ion cyclotron resonance mass spectrometry to provide a detailed molecular characterization of DOM and its transformation pathways in the Columbia river watershed. Samples were collected from ground water (adjacent unconfined aquifer underlying the Hanford 300 Area), Columbia river water, and its hyporheic zone. The hyporheic zone was sampled at five locations to capture spatial heterogeneity within the hyporheic zone. Our results revealed that abiotic transformation pathways (e.g., carboxylation), potentially driven by abiotic factors such as sunlight, in both the ground water and river water are likely influencing DOM availability to the hyporheic zone, which could then be coupled with biotic processes for enhanced microbial activity. The ground water profile revealed high rates of N and S transformations via abiotic reactions. The river profile showed enhanced abiotic photodegradation of lignin-like molecules that subsequently entered the hyporheic zone as low molecular weight, more degraded compounds. While the compounds in river water were in part bio-unavailable, some were further shown to increase rates of microbial respiration. Together, river water and ground water enhance microbial activity within the hyporheic zone, regardless of river stage, as shown by elevated putative amino-acid transformations and the abundance of amino-sugar and protein-like compounds. This enhanced microbial activity is further dependent on the composition of ground water and river water inputs. Our results further suggest that abiotic controls on DOM should be incorporated into predictive modeling for understanding watershed dynamics, especially as climate variability and land use could affect light exposure and changes to ground water essential elements, both shown to impact the Columbia river hyporheic zone.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Marine boundary layer aerosol in the eastern North Atlantic: seasonal variations and key controlling processes

The response of marine low cloud systems to changes in aerosol concentrationrepresents one of the largest uncertainties in climate simulations. Majorcontributions to this uncertainty are derived from poor understanding of aerosolunder natural conditions and the perturbation by anthropogenic emissions. Theeastern North Atlantic (ENA) is a region of persistent but diverse marineboundary layer (MBL) clouds, whose albedo and precipitation are highlysusceptible to perturbations in aerosol properties. In this study, we examineMBL aerosol properties, trace gas mixing ratios, and meteorologicalparameters measured at the Atmospheric Radiation Measurement Climate ResearchFacility's ENA site on Graciosa Island, Azores, Portugal, during a 3-yearperiod from 2015 to 2017. Measurements impacted by local pollution onGraciosa Island and during occasional intense biomass burning and dust eventsare excluded from this study. Submicron aerosol size distribution typicallyconsists of three modes: Aitken (At, diameter <~100 nm),accumulation (Ac, D p within ~100 to ~300 nm), andlarger accumulation (LA, D p &gt; ~ 300 nm) modes, with averagenumber concentrations (denoted as N At , N Ac , and N LA below) of 330, 114, and 14 cm -3 , respectively. N At , N Ac , and N LA show contrasting seasonalvariations, suggesting different sources and removal processes. N LA is dominated by sea spray aerosol (SSA) and is higher in winter andlower in summer. This is due to the seasonal variations of SSA production,in-cloud coalescence scavenging, and dilution by entrained free troposphere(FT) air. In comparison, SSA typically contributes a relatively minorfraction to N At (10 %) and N Ac (21 %) on an annual basis. Inaddition to SSA, sources of Ac-mode particles include entrainment of FTaerosols and condensation growth of Aitken-mode particles inside the MBL, whilein-cloud coalescence scavenging is the major sink of N Ac . The observedseasonal variation of N Ac , being higher in summer and lower in winter,generally agrees with the steady-state concentration estimated from majorsources and sinks. N At is mainly controlled by entrainment of FTaerosol, coagulation loss, and growth of Aitken-mode particles into theAc-mode size range. Our calculation suggests that besides the directcontribution from entrained FT Ac-mode particles, growth of entrained FTAitken-mode particles in the MBL also represent a substantial source ofcloud condensation nuclei (CCN), with the highest contribution potentiallyreaching 60 % during summer. The growth of Aitken-mode particles to CCN sizeis an expected result of the condensation of sulfuric acid, a product fromdimethyl sulfide oxidation, suggesting that ocean ecosystems may have asubstantial influence on MBL CCN populations in the ENA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Additive manufacturing of a metastable high entropy alloy: Metastability engineered microstructural control via process variable driven elemental segregation

Compositional paradigm shift in high entropy alloys (HEAs) provided new opportunities for microstructural engineering, whereas process control during laser powder bed fusion (LPBF) additive manufacturing (AM) enable fine microstructure tailoring. Metastability engineering in transformation induced plasticity (TRIP) HEAs by addition of minor alloying elements is an attractive strategy for fine microstructural tuning. This study explored in detail the microstructural evolution during LPBF AM of a metastable Fe 40 Mn 20 Co 20 Cr 15 Si 5 (at.%) dual phase HEA (CS-HEA). LPBF processing window for CS-HEA was established based on quantitative analysis and experiments. Based on melt pool overlap lack of fusion pores were observed at lower energy densities (J) of $\textit{J}$ ≤ 31.25 J/mm 3 and key-hole formation by melt pool destabilization in case of $\textit{J}$ ≥ 75 J/mm 3 . The microstructure of CS-HEA consists of metastable FCC-γ and HCP-ε phases; LPBF process parameters governed the final phase fraction in the alloy which has been correlated to metastability alteration of the high temperature γ phase. Final microstructural engineering was devised by LPBF process control which enabled cooling rate manipulation to guide Mn and Si segregation at the cell boundaries, thereby controlling the matrix metastability and final phase fraction. Additionally, high resolution transmission electron microscopy (TEM) revealed disparity in stacking fault morphology in CS-HEA with LPBF process variable alterations associated with local variations in chemical composition and stacking fault energy. Further, the phase evolution with process parameters also affected the nanomechanical behavior of the alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Multifaceted processes controlling the distribution of hazardous compounds in the spontaneous combustion of coal and the effect of these compounds on human health

Highlights: • Electron bean reveals the interactions among nanoparticles and hazardous compounds. • Samples were obtained from the most big Brazilian coal power plant. • Overall, exposure to hazardous compounds in coal fire pose health risks. Pollution generated by hazardous elements and persistent organic compounds that affect coal fire is a major environmental concern because of its toxic nature, persistence, and potential risk to human health. The coal mining activities are growing in the state of Santa Catarina in Brazil, thus the collateral impacts on the health and economy are yet to be analyzed. In addition, the environment is also enduring the collateral damage as the waste materials directly influence the coal by-products applied in civil constructions. This study was aimed to establish the relationships between the composition, morphology, and structural characteristics of ultrafine particles emitted by coal mine fires. In Brazil, the self-combustions produced by Al–Ca–Fe–Mg–Si coal spheres are rich in chalcophile elements (As, Cd, Cu, Hg, Pb, Sb, Se, Sn, and Zn), lithophile elements (Ce, Hf, In, La, Th, and U), and siderophile elements (Co, Cr, Mo, Fe, Ni, and V). The relationship between nanomineralogy and the production of hazardous elements as analyzed by advanced methods for the geochemical analysis of different materials were also delineated. The information obtained by the mineral substance analysis may provide a better idea for the understanding of coal-fire development and assessing the response of particular coal in different combustion processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Developing a peptide concatemer (PepCon) as a process control for LC-MS based proteomics

Quantitative concatenated peptide (QconCAT) technology is currently used for the absolute quantification of proteins of interest in a biological sample. It relies on artificially created proteins that are concatenations of different, isotopically labeled peptides. Because these isotopically labeled peptides are at a 1:1 ratio and correspond to naturally occurring peptides in the biological sample, each peptide can be used as a standard for the absolute quantitation of all proteins of interest at once. Although the QconCAT technology has utility for quantitation of known peptides in a mixture, it is not helpful for scientists who need a proteomics standard (1) that can be spiked into a protein mixture at an extremely low level, (2) that can be co-purified during sample fractionation, and (3) that is optimized for ESI used in mass spectrometry. Thus, there exists a need for an ideal standard protein that is large enough to behave as a protein but consists of multiple, concatenated copies of the same peptide, which, upon digestion, amplifies (e.g., >10-fold) into a detectable peptide species. Here, this technical report describes the development of “PepCon”, a peptide concatemer that fulfills this unmet need.

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

Processes controlling helium bubble dynamics at varying temperatures in simulated radioactive materials

Alpha-radiation damage is known to degrade materials exposed to harsh radiation environments via swelling and embrittlement by nano-scale helium bubbles. How these bubbles grow under varying temperature is essential to understanding and predicting material failure and optimization. Using in situ X-ray scattering, we probed ≈1012 bubbles before, during and after annealing at different temperatures in He-implanted aluminum to reveal a critical growth activation temperature that depends strongly on the helium implantation conditions. An analysis of the data aided by our molecular dynamics simulations identifies multiple temperature-dependent bubble growth mechanisms above and below the critical growth activation temperature. Moreover, the irreversible bubble growth that occurs after annealing for ≈4 h was evaluated using dislocation dynamics and found to negligibly affect the yield strength but may affect subsequent bubble growth at temperature. These in situ results provide valuable insight into bubble growth never observed before and reveal, for the first time, bubble shrinkage after cooling.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multi-Model and Multi-Scale Global Sensitivity Analysis for Identifying Controlling Processes of Complex Systems

An environmental model consists of multiple process level sub-models, and each sub-model represents a process that is key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this project develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods with variance-based global sensitivity analysis to address uncertainty in process models and parameters. The new method yields three process sensitivity indices. The first one is called first-order process sensitivity index, and it is derived as a single summary measure of relative process importance. Evaluating the index is computationally expensive, because it relies in a Monte Carlo scheme that requires thousands and even millions of model executions. To reduce computational cost, this project develops a computationally efficient, quasi Monte Carlo method, and this method is presented in Chapter 2 of this report with and a numerical example for demonstration. The numerical example shows that the results of the quasi Monte Carlo method are substantially close to those of the full Monte Carlo method, but the computational cost of the quasi Monte Carlo method is only 0.7% of that of the full Monte Carlo method. The second index is called total-effect process sensitivity index, and it measures interactions between different processes. Therefore, this sensitivity index includes the first-order process sensitivity index, and can be used to identify influential processes. On the other hand, the total-effect process sensitivity index can also be used to screen non-influential processes. This is demonstrated by two numerical examples using the Sobol-G* functions and groundwater flow models that consider recharge process, geological process, and snowmelt process. The numerical examples shows that the total-effect process sensitivity index is more informative than the first-order process sensitivity. The derivation of the process sensitivity index and the numerical examples are discussed in Chapter 3. Chapter 4 presents two computationally efficient methods for screening non-influential processes to exclude them from further investigation. The two methods are the multi-model difference-based sensitivity (MMDS) analysis method, which can be implemented using the Latin Hypercube Sampling. The second one is the implementation of MMDS method using a binning method. The numerical example for the Sobol-G* function indicates the two methods are capable of identifying non-influential models, and the numerical examples for the groundwater flow and reactive transport show that the two methods are effective for groundwater problems. However, it should be noted that the two methods are numerical approximations, and they can only be used for screening non-influential processes, not for ranking importance of system processes. All the sensitivity analysis methods are implemented by developing python codes, and the codes are in a software called SAMMPY: a python package for process sensitivity analysis under multiple models. The SAMMPY design and structure are discussed in Chapter 5, and the package is released to the public for free download.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Geophysical Retrievals in an Artificial Intelligence (AI) Framework for Illuminating Processes Controlling Water Cycle

Focal Area(s): This white paper responds to Focal Area #3: Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: This white paper addresses the water-cycle and data-model integration grand challenge. It leverages data from the Atmospheric Radiation Measurement (ARM) Climate Research Facility, and Next-Generation Ecosystem Experiment (NGEE), and Science Focus Area (SFA). The white paper focuses on controlling cloud, precipitation, and radiative properties as observed and simulated by the Earth System Models (ESM). The described framework can be readily applied to any other ensemble of instruments, including satellites and other ground-based networks.

54 ENVIRONMENTAL SCIENCES↗