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DOE OSTI2024

Understanding the High-Temperature Deformation Behaviors in Additively Manufactured Al6061+TiC Composites via In Situ Neutron Diffraction

Aluminum matrix composites (AMCs) are designed to enhance the performance of conventional aluminum alloys for engineering applications at both room and elevated temperatures. However, the dynamic phase-specific deformation behavior and load-sharing mechanisms of AMCs at elevated temperatures have not been extensively studied and remain unclear. Here, in situ neutron diffraction experiments are employed to reveal the phase-specific structure evolution of additively manufactured Al6061+TiC composites under compressive loading at 250 °C. It is found that the addition of a small amount of nano-size TiC significantly alters the deformation behavior and increases the strength at 250 °C in comparison to the as-printed Al6061. Unlike the two-stage behavior observed in Al6061, the Al6061+TiC composites exhibit three stages during compression triggered by changes in the interphase stress states. Further analysis of Bragg peak intensity and broadening reveals that the presence of TiC alters the dislocation activity during deformation at 250 °C by influencing dislocation slip planes and promoting dislocation accumulation. These findings provide direct experimental observations of the phase-specific dynamic process in AMCs under deformation at an elevated temperature. The revealed mechanisms provide insights for the future design and optimization of high-performance AMCs.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Observing Arctic Sea Ice

Our understanding of Arctic sea ice and its wide-ranging influence is deeply rooted in observation. Advancing technologies have profoundly improved our ability to observe Arctic sea ice, document its processes and properties, and describe atmosphere-ice-ocean interactions with unprecedented detail. Yet, our progress toward better understanding the Arctic sea ice system is mired by the stark disparities between observations that tend to be siloed by method, scientific discipline, and application. This article presents a review and philosophical design for observing sea ice and accelerating our understanding of the Arctic sea ice system. We give a brief history of Arctic sea ice observations and showcase the 2018 melt season within the context of five observational themes: spatial heterogeneity, temporal variability, cross-disciplinary science, scalability, and retrieval uncertainty. We synthesize buoy data, optical imagery, satellite retrievals, and airborne measurements to demonstrate how disparate data sets can be woven together to transcend observational-scale issues. The results show that there are limitations to interpreting any single data set alone. However, many of these limitations can be surmounted by combining observations that cross spatial and temporal scales. We conclude the article with pathways toward coordinating across observational platforms in order to: (1) optimize the scientific, operational, and community return on observational investments, and (2) facilitate a richer understanding of Arctic sea ice and its role in the climate system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Investigation of Rare Earth Elements Mobility Using Molecular Dynamics

Rare Earth Elements (REE) are critical many applications such as electronics, permanent magnets, agricultural etc. Effective separation of REEs is a challenge due to their similarities in chemical and physical properties. Current separation processes are costly and environmentally detrimental. Therefore, research on REEs mobility in water-based solvents is necessary to design effective separation processes. In this research, the key kinetic and thermodynamic parameters, including diffusion coefficient and hydration shell are determined under the influence of external electric field. The diffusion coefficient of metal ions increases due to electric field in pure water.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Investigation of Rare Earth Elements Mobility Using Molecular Dynamics

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Effect of process route on powder three-dimensional-printing of metal powders

The purpose of this study is to investigate the effect of two unique processing routes (solvent jetting (SJ) and binder jetting (BJ)), on the green density of printed stainless steel 316L (SS316L) and Nickel (Ni) powders. In the SJ processing route, a solvent is jetted unto the powder/binder mixture to selectively activate the binder, layer by layer. In the BJ processing route, a solution of the binder mixture is jetted onto the powder bed to selectively bind powder particles. The effects of printing parameters such as layer height, roller speed, shaker speed and nozzle temperature on the green density of printed components are investigated and compared for both processing routes. Results show that layer height and nozzle temperature affect the relative density of the printed compact for both processing routes. Slightly higher relative densities were achieved via the SJ route, with the overall highest relative density being 42.7% at 100 µ m layer height and 70% nozzle temperature for the SS316L components and 43.7% at 150 µ m layer height and 90% nozzle temperature for the Ni components, respectively. Results also show an increase in the final sintered relative density with an increase in green (printed) relative density of the solvent jetted SS316L components, with the highest relative density being 87.2%. The paper studies the influence of printing parameters on the green density of printed SS316L and Ni samples in an unprecedented effort to provide a comparative understanding of the process-property relationships in BJ and SJ of SS316L and Ni components to the additive manufacturing research community.

Engineering↗

DOE OSTI2024

The Computational Analysis of a Generic Hypersonic Store Separation

Many current hypersonic vehicles involve a main vehicle from which components separate during flight and presents simulation challenges such as shock-shock interactions, highly nonlinear interactions, and shock wave boundary layer interactions. These aerodynamic phenomena influence the attitude and trajectory of each object, which needs to be understood before large-scale experiments can be run. To gain a generic understanding of the process, high-fidelity Reynolds-averaged Navier-Stokes solutions are performed on a conical vehicle geometry passing through an oblique shock wave that is representative of different configurations and scenarios. Trajectory and applied forces are tracked and show the vehicle’s dynamics are predominantly the result of differential flow incidence angles causing a strong shock; this leads to a large pressure increase over a fraction of the vehicle, which influences pitch. The vehicle appears to follow conventional stability theory with detached eddy simulation and small disturbances in initial attitude shown to have minimal influence on the scenario.

Savery, Ryan↗

DOE OSTI2020

Direct Conversion of Biomass Carbohydrates to Platform Chemicals: 5-Hydroxymethylfurfural (HMF) and Furfural

5-hydroxymethylfurfural (HMF) and furfural are promising platform molecules which can be converted to fuel intermediates and hydrocarbon fuels. Herein, one-step, direct conversion of the carbohydrates in never treated biomass to HMF and furfural in a microwave reactor was investigated. The influence of reaction temperature, time, feedstock, addition of Lewis and Bronsted acids, solvent and solvent to aqueous ratio were studied to find the optimum process conditions to maximize the yields of furfurals. The reaction conditions of 200 degrees C for 5 min with 33 mM HCl and 8 mM AlCl 3 using a dioxane/water (4:1) miscible solvent system were found to be the most conducive for direct dehydration of the glucan and hemicelluloses present in untreated poplar wood to furfural and HMF in yields of 91 and 69%, respectively. Furfural could be easily produced in yields greater than 80%, and once formed, it was found to be stable under the various process conditions explored. In contrast, HMF yields varied with both reaction time and temperature, as it readily underwent rehydration to levulinic acid in yields approaching 25-30% at increased reaction severity. The additions of both Bronsted (HCl) and Lewis (AlCl 3 ) acids in catalytic amounts, i.e., 33 and 8 mM, respectively, were required to maximize the yield of furfurals. Reactions were also performed on other feedstocks (corn stover, switchgrass, loblolly pine, and pure cellulose) to investigate the effect of feedstock type on furfurals yields. Results showed that HMF and furfural yields were primarily dependent on hexosan and pentosan loading regardless of the type of feedstock. In addition, biomass physical features, such as crystallinity or the presence of other biomass constituents, such as lignin, had little influence on furfurals yields.

09 BIOMASS FUELS↗

DOE OSTI2024

Atomic Diffusivities of Yttrium, Titanium and Oxygen Calculated by Ab Initio Molecular Dynamics in Molten 316L Oxide-Dispersion-Strengthened Steel Fabricated via Additive Manufacturing

Oxide-dispersion-strengthened (ODS) steels have long been viewed as a prime solution for harsh environments. However, conventional manufacturing of ODS steels limits the final product geometry, is difficult to scale up to large components, and is expensive due to multiple highly involved, solid-state processing steps required. Additive manufacturing (AM) can directly incorporate dispersion elements (e.g., Y, Ti and O) during component fabrication, thus bypassing the need for an ODS steel supply chain, the scale-up challenges of powder processing routes, the buoyancy challenges associated with casting ODS steels, and the joining issues for net-shape component fabrication. In the AM process, the diffusion of the dispersion elements in the molten steel plays a key role in the precipitation of the oxide particles, thereby influencing the microstructure, thermal stability and high-temperature mechanical properties of the resulting ODS steels. In this work, the atomic diffusivities of Y, Ti, and O in molten 316L stainless steel (SS) as functions of temperature are determined by ab initio molecular dynamics simulations. The latest Vienna Ab initio Simulation Package (VASP) package that incorporates an on-the-fly machine learning force field for accelerated computation is used. At a constant temperature, the time-dependent coordinates of the target atoms in the molten 316L SS were analyzed in the form of mean square displacement in order to obtain diffusivity. The values of the diffusivity at multiple temperatures are then fitted to the Arrhenius form to determine the activation energy and the pre-exponential factor. Given the challenges in experimental measurement of atomic diffusivity at such high temperatures and correspondingly the lack of experimental data, this study provides important physical parameters for future modeling of the oxide precipitation kinetics during AM process.

Chemistry↗

DOE OSTI2020

Pervasive shifts in forest dynamics in a changing world

Forest dynamics arise from the interplay of environmental drivers and disturbances with the demographic processes of recruitment, growth, and mortality, subsequently driving biomass and species composition. However, forest disturbances and subsequent recovery are shifting with global changes in climate and land use, altering these dynamics. Changes in environmental drivers, land use, and disturbance regimes are forcing forests toward younger, shorter stands. Rising carbon dioxide, acclimation, adaptation, and migration can influence these impacts. Recent developments in Earth system models support increasingly realistic simulations of vegetation dynamics. In parallel, emerging remote sensing datasets promise qualitatively new and more abundant data on the underlying processes and consequences for vegetation structure. In combination, these advances hold promise for improving the scientific understanding of changes in vegetation demographics and disturbances.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗

DOE OSTI2024

Tracking copper nanofiller evolution in polysiloxane during processing into SiOC ceramic

Polymer-derived ceramics (PDCs) remain at the forefront of research for a variety of applications including ultra-high-temperature ceramics, energy storage and functional coatings. Despite their wide use, questions remain about the complex structural transition from polymer to ceramic and how local structure influences the final microstructure and resulting properties. This is further complicated when nanofillers are introduced to tailor structural and functional properties, as nanoparticle surfaces can interact with the matrix and influence the resulting structure. The inclusion of crystalline nanofiller produces a mixed crystalline–amorphous composite, which poses characterization challenges. With this study, we aim to address these challenges with a local-scale structural study that probes changes in a polysiloxane matrix with incorporated copper nanofiller. Composites were processed at three unique temperatures to capture mixing, pyrolysis and initial crystallization stages for the pre-ceramic polymer. We observed the evolution of the nanofiller with electron microscopy and applied synchrotron X-ray diffraction with differential pair distribution function (d-PDF) analysis to monitor changes in the matrix's local structure and interactions with the nanofiller. The application of the d-PDF to PDC materials is novel and informs future studies to understand interfacial interactions between nanofiller and matrix throughout PDC processing.

Chemistry↗

DOE OSTI2020

Temperature and processing effects on lithium ion conductivity of solution‐deposited lithium zirconium phosphate (LiZr 2 P 3 O 12 ) thin films

Abstract Lithium zirconium phosphate (LiZr 2 P 3 O 12 ) thin films have been prepared on platinized silicon substrates via a chemical solution deposition approach with processing temperatures between 700°C and 775°C. Films that were subject to a single high‐temperature anneal were found to crystallize at temperatures above 725°C. Crystallization was observed in films annealed after each deposited layer at 700°C and above. In both cases, grain size was found to increase with annealing temperature. Ion conductivity was found to increase with annealing temperature in singly annealed films. In per‐layer annealed films ion conductivity was found to initially increase then decrease with increasing annealing temperature. A maximum ion conductivity of 1.6 × 10 −6 S/cm was observed for the singly annealed 775°C condition, while a maximum ion conductivity of 5.8 × 10 −7 S/cm was observed for the 725°C per‐layer annealed condition. These results are consistent with an increasing influence of cross‐plane, internal interface resistance and vapor phase carrier loss in the per‐layer annealed samples. This work demonstrates that post‐deposition processing methods can strongly affect the ion conducting properties of LiZr 2 P 3 O 12 thin films.

Brummel, Ian A.↗

DOE OSTI2024

Development of Modified Perturbation Solutions to the One-Phase Stefan Problems With a Convective Boundary

The classical Stefan problem is used to track the moving solid-liquid interface during the freezing process. Perturbation theory has often been applied to find an approximate analytical solution due to the nonlinearity of the moving interface. However, the Stefan number (i.e., the sensible over latent heat) must be small and usually less than 0.01 to assume the perturbation expansion, which in turn limits the thermal engineering applications. In this study, a modified perturbation solution is developed by adding a correction term after the leading-order solution to be valid for a much wider range of Stefan numbers (i.e., 0.01 less than or equal to Ste less than or equal to 1). Specifically, a one-phase Stefan problem is first formulated subjected to a convective boundary in the Cartesian, cylindrical, and spherical coordinate systems for inward solidification. The leading-order solution is calculated based on the regular perturbation theory, while the correction term is obtained using the Monte-Carlo method and a multi-variant regression. Results show that the correction term has a linear relationship with the Stefan number and is not significantly influenced by the Biot number. The proposed modified perturbation solution can accurately and rapidly predict the nonlinear moving interface motion for the freezing process.

DIRECT ENERGY CONVERSION,MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Influence of Calendering on the Electrochemical Performance of LiNi 0.9 Mn 0.05 Al 0.05 O 2 Cathodes in Lithium-Ion Cells

Electrode calendering is a necessary process used in industry to improve the volumetric capacity of lithium-ion batteries. However, calendering high-nickel cathodes leads to electrode particle pulverization, raising concerns of a reduced cycle life due to parasitic side reactions. We present here an investigation of the impact of calendering on the morphology and electrochemical performance of the cobalt-free layered oxide cathode LiNi 0.9 Mn 0.05 Al 0.05 O 2 (NMA-90). We find that secondary particle pulverization and fusion simultaneously occur at sufficiently high pressures. The initial surface area of the cathode is shown to increase with the degree of calendering, despite the higher likelihood of secondary particle fusion. Long-term cycling of full coin cells assembled with the NMA-90 cathode and the graphite anode indicates that cells with higher degrees of cathode calendering exhibit lower capacity fade compared to uncalendered cathodes. Hybrid pulse-power tests demonstrate that the usable capacity range of cells with calendered cathodes far exceeds those with uncalendered cells after long-term cycling. The improved capacity retention and pulse-power performance are attributed to the enhanced mechanical properties of the electrode after calendering that prevents loss of the primary particle contact during long-term cycling. As a result, we find that calendering high-nickel NMA-90 to industrially relevant densities does not have a detrimental effect on capacity fade, marking an important step toward commercial adoption.

25 ENERGY STORAGE↗

DOE OSTI2022

Liquid-Phase Effects on Adsorption Processes in Heterogeneous Catalysis

Aqueous solvation free energies of adsorption have recently been measured for phenol adsorption on Pt(111). Endergonic solvent effects of ~1 eV suggest solvents dramatically influence a metal catalyst’s activity with significant implications for the catalyst design. However, measurements are indirect and involve adsorption isotherm models, which potentially reduces the reliability of the extracted energy values. Computational, implicit solvation models predict exergonic solvation effects for phenol adsorption, failing to agree with measurements even qualitatively. In this study, an explicit, hybrid quantum mechanical/molecular mechanical approach for computing solvation free energies of adsorption is developed, solvation free energies of phenol adsorption are computed, and experimental data for solvation free energies of phenol adsorption are reanalyzed using multiple adsorption isotherm models. Explicit solvation calculations predict an endergonic solvation free energy for phenol adsorption that agrees well with measurements to within the experimental and force field uncertainties. Computed adsorption free energies of solvation of carbon monoxide, ethylene glycol, benzene, and phenol over the (111) facet of Pt and Cu suggest that liquid water destabilizes all adsorbed species, with the largest impact on the largest adsorbates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Influence of side-chain isomerization on the isothermal crystallization kinetics of poly(3-alkylthiophenes)

Flexible alkyl side chain in conjugate polymers (CPs) improves the solubility and promotes solution processability, in addition, it affects interchain packing and charge mobilities. Despite the well-known charge mobility and morphology correlation for these semi-crystalline polymers, there is a lack of fundamental understanding of the impact of side chain on their crystallization kinetics. In the present work, isothermal crystallization of five poly(3-alkylthiophene-2,5-diyl) (P3ATs) with different side-chain structures were systematically investigated. To suppress the extremely fast crystallization and trap the sample into amorphous glass, an advanced fast scanning chip calorimetry technique, which is able to quench the sample with few to tens thousands of K/s, was applied. Results show that the crystallization of P3ATs was greatly inhibited after incorporation of branched side chains, as indicated by a dramatic up to six orders of magnitude decrease in the crystallization rate. The suppressed crystallization of P3ATs were correlated with an increased π–π stacking distance due to unfavorable side-chain steric interaction. This research provides a pathway to use side-chain engineering to control the crystallization behavior for CPs, thus to control device performance.

36 MATERIALS SCIENCE↗

DOE OSTI2020

The Evaluation of Chemical Decontamination for Contaminated Carbon Steel Scrap by Multiphase Treatment Process - 20249

There is a significant growth in the field of decommissioning of nuclear facilities due the fact that for a lot of them their end of life is nearing. In Taiwan, the government plans to steadily reduce the dependence on nuclear power and moves gradually towards a nuclear-free homeland. Therefore, the development of decommissioning technology becomes the significant issue for the next coming years. The decommissioning of a nuclear power plant is a long process and practical work including radiological surveys, decontamination, dismantling, and the subsequent waste management. Chemical decontamination is an important task in the decommissioning of nuclear power plants and is usually performed by circulating the chemical solution in selected systems or full systems in order to reduce dose levels. However, the decontamination of segmented metal parts is also considered to reduce the contamination to such levels that they may be disposed of at a lower classification or be unconditionally released, and it helps to achieve the goal of waste minimization and provide a more economical cost for disposal management. Chemical decontamination technology is used to remove the contaminated oxides deposited on the surface of metals by dissolving them with chemical mechanisms, such as chelation, acidic or alkaline dissolution, redox reaction and so on. Carbon steel is the major material used in systems and pipelines in the nuclear power plant, thus it is also commonly selected as the target to be decontaminated in the decommissioning process. In this study, the effectiveness of chemical decontamination is evaluated by using multiphase treatment process including the reduction and the oxidation steps. In the step of redox reaction, the oxidation state of the substance is very important. Especially metals of some oxidation states show solubility in water, which has a decisive influence on the chemical decontamination. The experiment of decontamination of metal scraps is carried out by the immersion method within a chemical solution. The relative operation parameters such as temperature, pH, and concentration of the chemical solution are recorded to demonstrate the effect of the decontamination process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

TOUGH-RFPA: Coupled thermal-hydraulic-mechanical Rock Failure Process Analysis with application to deep geothermal wells

This paper presents a coupled thermal-hydraulic-mechanical (THM) model for simulating failure processes in geological media. The coupling between stress/strain and heat transfer describing how thermal expansion affects stress is based on the theory of thermo-elasticity. Additionally, the coupling between stress/strain and fluid flow describing how pore-pressure affects stress is governed by Biot's consolidation theory. Stress/strain-dependent porosity/permeability/capillary-pressure defines the influence of stress on fluid flow and thermal fields. The THM model is implemented in the solver module that links the multiphase, multicomponent fluid flow simulator TOUGH2 with the geomechanical simulator RFPA (Rock Failure Process Analysis), which is based on the concept that heterogeneity leads to non-linearity and progressive failure behavior. Capability of TOUGH-RFPA simulator was verified by two benchmark problems related to hydraulic-mechanical and thermal-mechanical response in a hollow cylinder. Then the applicability of TOUGH-RFPA was demonstrated for modeling cooling-induced damage around a very deep geothermal well with mesoscopic heterogeneous properties, which showed complex damage evolution and fracturing during well cooling and fluid pressurization.

42 ENGINEERING↗