Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “alloy development”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

ORNL_AISD_NiPt

This dataset describes the nickel-platinum (NiPt) solid solution binary alloy, where the two constituent elements nickel (Ni) and platinum (Pt) are randomly placed on the face centered cubic (FCC) crystal structure, with the lattice constant of 3.840 angstroms. The dataset comprises data for three different sizes of the crystal structure: 256 atoms, 864 atoms, and 2,048 atoms, each of which contains 1900 configurations. For each size of the crystal structure, the data set was generated for concentrations ranging from 0at% of Pt to 100at% of Pt in the NiPt binary system, with increasing the concentration of Pt in the system every 5at%. For each one of the chemical compositions, 100 random configurations were generated, each with a different random seed. Each of the output files contains the mass, type, atomic coordinates, energy per atom, and forces in x, y, and z directions respectively. For each atomic configuration, the output was collected every 150 steps during the minimization stage and every 1000 steps during the replica exchange stage. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) [1], which is a molecular dynamics code, was used to generate data for NiPt alloy. The simulation used the interatomic potential for NiPt binary system MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [3] from the OpenKIM library (Open Knowledgebase of Interatomic Models) [2]. This potential was developed based on the second nearest-neighbor modified embedded-atom method (2NN MEAM). The simulation process begins with the generation of the random NiPt structure and follows with the short minimization and replica exchange simulation. The minimization procedure adjusts atomic coordinates and performs energy minimization, which typically leads to a local potential energy minimum. The method used for the minimization was the conjugate gradient algorithm. A short replica exchange (parallel tempering) simulation involves four replicas (ensembles) of a system and follows the minimization stage. Multiple snapshots of the configuration were collected during the minimization and replica exchange stages. NiPt alloy is interesting due to its magnetic and charge transfer properties [4]. The data is provided in three compressed zipped folders: atoms256.zip, atoms864.zip, atoms2048.zip Each zipped folder contains the data that describes crystals of size 256 atoms, 864 atoms, and 2,048 atoms respectively. Each one of the three zipped folders contains the data structured in the following way: -Ni_ground_state.cfg --> atomic configuration for the pure nickel -Pt_ground_state.cfg --> atomic configuration for the pure platinum -Pt#_filtered --> folders containing atomic configurations for #at% concentration of platinum. The folder contains 100 atomic configurations, each saved in a subfolder. Each subfolder named config* is associated with a specific atomic configuration. Each of these subfolders contains files with .cfg format, corresponding to outputs for each atomic configuration The total number of atomic configurations contained in atoms256.zip is 65,046. The total number of atomic configurations contained in atoms864.zip is 63,936. The total number of atomic configurations contained in atoms2048.zip is 61,997. The total number of atomic configurations spanned by the entire dataset is 190,979. References [1] https://www.lammps.org/ [2] https://openkim.org/ [3] https://openkim.org/id/MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [4] El-Gendy, Ahmed A. and Hampel, Silke and Büccchner, Bernd and Klingeler, Rüdiger, Tuneable magnetic properties of carbon-shielded NiPt-nanoalloys, RSC Adv., volume 6, issue 57, pages 52427-52433, 2016, The Royal Society of Chemistry, doi:10.1039/C6RA05910D

36 MATERIALS SCIENCE↗
DOE OSTI2023

ORNL_AISD_NiPt_108atoms

This dataset describes the nickel-platinum (NiPt) solid solution binary alloy, where the two constituent elements nickel (Ni) and platinum (Pt) are randomly placed on the face centered cubic (FCC) crystal structure, with the lattice constant of 3.840 angstroms. The dataset comprises data for crystal structures with 108 atoms with 1,900 configurations. The data set was generated for concentrations ranging from 0at% of Pt to 100at% of Pt in the NiPt binary system, with increasing the concentration of Pt in the system every 5at%. For each one of the chemical compositions, 100 random configurations were generated, each with a different random seed. Each of the output files contains the mass, type, atomic coordinates, energy per atom, and forces in x, y, and z directions respectively. For each atomic configuration, the output was collected every 150 steps during the minimization stage and every 1000 steps during the replica exchange stage. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) [1], which is a molecular dynamics code, was used to generate data for NiPt alloy. The simulation used the interatomic potential for NiPt binary system 'MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001' [3] from the OpenKIM library (Open Knowledgebase of Interatomic Models) [2]. This potential was developed based on the second nearest-neighbor modified embedded-atom method (2NN MEAM). The simulation process begins with the generation of the random NiPt structure and follows with the short minimization and replica exchange simulation. The minimization procedure adjusts atomic coordinates and performs energy minimization, which typically leads to a local potential energy minimum. The method used for the minimization was the conjugate gradient algorithm. A short replica exchange (parallel tempering) simulation involves four replicas (ensembles) of a system and follows the minimization stage. Multiple snapshots of the configuration were collected during the minimization and replica exchange stages. NiPt alloy is interesting due to its magnetic and charge transfer properties [4]. The data is provided in a compressed zipped folders atoms108.zip. The zipped folder contains the data structured in the following way: - Ni_ground_state.cfg --> atomic configuration for the pure nickel - Pt_ground_state.cfg --> atomic configuration for the pure platinum - Pt#_filtered --> folders containing atomic configurations for #at% concentration of platinum. The folder contains 100 atomic configurations, each saved in a subfolder - Each subfolder named config* is associated with a specific atomic configuration. Each of these subfolders contains files with .cfg format, corresponding to outputs for each atomic configuration The total number of atomic configurations contained in atoms108.zip is 66,132. This dataset is an extension to the dataset ORNL_AISD_NiPt [5] that has been previously released with crystal structures of 256 atoms, 864 atoms, and 2,048 atoms, with the same methodology for data collection. References [1] https://www.lammps.org/ [2] https://openkim.org/ [3] https://openkim.org/id/MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [4] El-Gendy, Ahmed A. and Hampel, Silke and Büchner, Bernd and Klingeler, Rüdiger, Tuneable magnetic properties of carbon-shielded NiPt-nanoalloys, RSC Adv., volume 6, issue 57, pages 52427-52433, 2016, The Royal Society of Chemistry, doi:10.1039/C6RA05910D [5] M. Karabin, M. Lupo Pasini, and M. Eisenbach. ORNL_AISD_NiPt. United States: N. p., 2023. Web. doi:10.13139/OLCF/1958172.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Ab Initio Modeling of fcc Fe-Co-Cr-Ni High Entropy Alloys with Full Composition Range

The Fe-Co-Cr-Ni quaternary system has been studied extensively in the past decade, not only because of the superior properties achieved like high tensile ductility and fracture toughness, but also it is the foundation for the development of FeCrCoNi-based HEAs. However, most of the investigations are mainly focusing on the equiatomic and semi-equiatomic compositions. The physical properties of non-equiatomic compositions are barely explored. In the current work, the ab initio approach is adopted to predict the lattice parameter, structure stabilities, elastic properties, and enthalpy of formations of fcc Fe-Cr-Co-Ni HEA single crystals with the special quasirandom structure (SQS) method. To expand the design of Fe-Co-Cr-Ni HEAs into a full composition range, the current simulations cover all the binaries, ternaries, and the whole quaternary system. The 2-D composition-property contour diagrams are created to show the physical properties in the ternary and quaternary systems. Furthermore, our investigation shows that the fcc alloys' lattice parameter increases with the addition of Fe and Cr and decreases with Ni and Co. In addition to the enthalpy of formation at o K, the shape distortion rate is proposed to be another essential parameter to evaluate crystal stability. The results show the addition of Cr would destabilize the fcc lattice and cause symmetry breaking. Finally, the result of Pugh’s ratio shows that most of the fcc alloys show ductile behavior (P > 1.75), especially for the alloys around Fe 3 Ni, FeCo, and Fe 2 NiCo (P > 2.5). The brittle behavior (P < 1.75) is located around Fe 3 Cr and Fe 2 CoCr. Meanwhile, Cr 2 NiCo and Cr 2 FeNiCo are considered promising compositions to be tried and verified experimentally because of the higher bulk modulus and moderate shear modulus.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Off-Gas Design and Testing from Advanced Chlorination Process

Chlorination of Zr alloy cladding with sulfur-chloride reagents is being considered as a means of separating the main metal from alloying elements, imbedded U, actinides, and fission and activation products to purify the Zr. This would allow the Zr to be disposed of as low-level nuclear waste or possibly be recycled. A multistage process was developed that involves several steps and waste streams. Recycling of sulfur-chloride reagents S 2 Cl 2 and SOCl 2 is planned to minimize the waste stream. The generation of off-gas and entrainment of volatiles is anticipated to be minimized. However, given the complex nature of spent nuclear fuel (SNF), some volatile components will be generated, including the solvents themselves; Cl 2 used for the regeneration of S 2 Cl 2 ; volatile fission product chlorides, such as Sb and 3 H; and chlorinated alloying components, such as Sn, Nb, Fe, and Mo. This report discusses the chemical phenomena that might give rise to volatile species and their planned capture. The volatility of the transition metals will depend on their oxidation state and the compounds that are formed, such as Zr tritide. Loading radionuclides in the process off-gas will depend on the inputs to the process. For instance, processing separated Zr to reduce waste will have a much lower loading of radionuclides than if alternative chlorination were used for decladding SNF. Much of the volatile process streams will be part of the solvent recycling, which may involve online scrubbing. Generally, a caustic scrubber should be included in the off-gas to remove acidic vapors (e.g., Cl 2 , SOCl 2 ). The decontamination procedures for removing these species could involve pretreatment (i.e., heating) options or reduction by contact with H 2 . This report discusses these options along with a framework for testing these alternatives in future experiments. Technologies for off-gas capture will leverage those developed in the Materials Recovery and Waste Forms program.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Learning grain boundary segregation energy spectra in polycrystals

The segregation of solute atoms at grain boundaries (GBs) can profoundly impact the structural properties of metallic alloys, and induce effects that range from strengthening to embrittlement. And, though known to be anisotropic, there is a limited understanding of the variation of solute segregation tendencies across the full, multidimensional GB space, which is critically important in polycrystals where much of that space is represented. Here we develop a machine learning framework that can accurately predict the segregation tendency—quantified by the segregation enthalpy spectrum—of solute atoms at GB sites in polycrystals, based solely on the undecorated (pre-segregation) local atomic environment of such sites. We proceed to use the learning framework to scan across the alloy space, and build an extensive database of segregation energy spectra for more than 250 metal-based binary alloys. The resulting machine learning models and segregation database are key to unlocking the full potential of GB segregation as an alloy design tool, and enable the design of microstructures that maximize the useful impacts of segregation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Designing shape-memory-like microstructures in intercalation materials

During the reversible insertion of ions, lattices in intercalation materials undergo structural transformations. These lattice transformations generate misfit strains and volume changes that, in turn, contribute to the structural decay of intercalation materials and limit their reversible cycling. In this paper, we draw on insights from shape-memory alloys, another class of phase transformation materials, that also undergo large lattice transformations but do so with negligible macroscopic volume changes and internal stresses. We develop a theoretical framework to predict structural transformations in intercalation compounds and identify crystallographic design rules necessary for forming shape-memory-like microstructures in intercalation materials. We use our approach to systematically screen open-source structural databases comprising $n$ > 5000 pairs of intercalation compounds. We identify candidate compounds, such as Li x Mn 2 O 4 (Spinel), Li x Ti 2 (PO 4 ) 3 (NASICON), that approximately satisfy the crystallographic design rules and can be precisely doped to form shape-memory-like microstructures. Throughout, we compare our analytical results with experimental measurements of intercalation compounds. We find a direct correlation between structural transformations, microstructures, and increased capacity retention in these materials. These results, more generally, show that crystallographic designing of intercalation materials could be a novel route to discovering compounds that do not decay with continuous usage.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Implementation and experimental validation of nonlocal damage in a large-strain elasto-viscoplastic FFT-based framework for predicting ductile fracture in 3D polycrystalline materials

Ductile materials, such as metal alloys, can undergo substantial deformation before failure. Additionally, these materials are usually of polycrystalline composition and exhibit strongly anisotropic behavior at small length scales. Previously developed fast Fourier transform (FFT)-based models can model ductile fracture of isotropic materials or the elastic–plastic behavior of anisotropic polycrystalline materials; however, there remains a need to couple both capabilities. This work extends a large-strain FFT-based crystal plasticity model to simulate ductile fracture of polycrystalline materials. In this work, a triaxiality-based continuum damage mechanics (CDM) formulation is incorporated into a large-strain elasto-viscoplastic FFT (LS-EVPFFT) framework. The CDM formulation is augmented with an integral-based nonlocal regularization approach that correctly handles gas-phase material necessary to model unconstrained surfaces. To validate the damage-enabled LS-EVPFFT framework, mesoscale copper tensile coupons were machined using microwire electrical discharge machining and experimentally characterized using electron backscatter diffraction. In-situ optical digital image correlation was performed during uniaxial testing to provide a side-by-side comparison of the experimental and computational strain fields and stress–strain responses. The damage-enabled LS-EVPFFT framework can simulate the complete macroscopic stress–strain response of ductile polycrystals to failure. The model reproduces necking behavior that qualitatively agrees with experimental observations. By leveraging the relatively low computational cost of the damage-enabled LS-EVPFFT framework, the framework presented here allows the ductile fracture response of 3D polycrystalline materials to be tractably predicted.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Novel textured surfaces for superior corrosion mitigation in molten carbonate salts for concentrating solar power

Corrosion of metals in contact with molten salts used for thermal energy storage and heat transport at high temperatures is a serious impediment to the development of next-generation concentrating solar thermal systems. Toward addressing this limitation, novel multiscale fractal-textured Ni coatings on a variety of substrate alloys are presented in this study for exceptional corrosion mitigation in molten carbonate salts at a high temperature. Strongly adherent, durable, single-layer, and double-layer multiscale fractal coatings were fabricated using the electrodeposition method. Corrosion performance of the coatings on SS310, SS316, SS347, and In800H was studied in molten carbonate salt (32% Li 2 CO 3 +33% Na 2 CO 3 +35% K 2 CO 3 ) at 750 °C. Single-layer coatings are stable up to 300 h immersion, whereas double-layer coatings are stable beyond 750 h. The corrosion rate of double-layer Ni coatings on ferrous alloys was reduced by as much as 60% from that of uncoated surfaces and was about 18% below that of higher cost, high Ni content Ha230. The study represents the first-ever report of corrosion characteristics of alloys in carbonate salts at 750 °C and the first demonstration of a means of dramatically reducing corrosion in carbonate salts at a high temperature. The article is significant in that it provides a viable approach for low-cost structural alloys to be corrosion-resistant to molten carbonate heat transfer fluids and storage media in high-temperature concentrating solar thermal applications. Furthermore, the corrosion-resistant coatings provide opportunities for the use of low-cost, ferritic alloys instead of the expensive nickel-based alloys in practice.

14 SOLAR ENERGY↗
DOE OSTI2023

One dimensional wormhole corrosion in metals

Corrosion is a ubiquitous failure mode of materials. Often, the progression of localized corrosion is accompanied by the evolution of porosity in materials previously reported to be either three-dimensional or two-dimensional. However, using new tools and analysis techniques, we have realized that a more localized form of corrosion, which we call 1D wormhole corrosion, has previously been miscategorized in some situations. Using electron tomography, we show multiple examples of this 1D and percolating morphology. To understand the origin of this mechanism in a Ni-Cr alloy corroded by molten salt, we combined energy-filtered four-dimensional scanning transmission electron microscopy and ab initio density functional theory calculations to develop a vacancy mapping method with nanometer-resolution, identifying a remarkably high vacancy concentration in the diffusion-induced grain boundary migration zone, up to 100 times the equilibrium value at the melting point. Deciphering the origins of 1D corrosion is an important step towards designing structural materials with enhanced corrosion resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Crystallographic variant mapping using precession electron diffraction data

In this work, we developed three methods to map crystallographic variants of samples at the nanoscale by analyzing precession electron diffraction data using a high-temperature shape memory alloy and a VO2 thin film on sapphire as the model systems. The three methods are (I) a user-selecting-reference pattern approach, (II) an algorithm-selecting-reference-pattern approach, and (III) a k-means approach. In the first two approaches, Euclidean distance, Cosine, and Structural Similarity (SSIM) algorithms were assessed for the diffraction pattern similarity quantification. We demonstrated that the Euclidean distance and SSIM methods outperform the Cosine algorithm. We further revealed that the random noise in the diffraction data can dramatically affect similarity quantification. Denoising processes could improve the crystallographic mapping quality. With the three methods mentioned above, we were able to map the crystallographic variants in different materials systems, thus enabling fast variant number quantification and clear variant distribution visualization. The advantages and disadvantages of each approach are also discussed. We expect these methods to benefit researchers who work on martensitic materials, in which the variant information is critical to understand their properties and functionalities.

Crystallographic variant mapping↗
DOE OSTI2021

Effect of alloying with Sc, Nb and Zr on reduction-diffusion synthesis of magnetically hard Sm(Fe,Co,Ti) 12 -based monocrystalline powders

Powders of Sm(Fe,Co) 11.2 Ti 0.8 alloys modified with Sc, Nb and Zr, as well as with additional Ti were prepared by reducing mechanically activated raw oxides with Ca metal in the furnace preheated to 990–1250 °C. Expansion of the crystal lattice upon introduction of Nb or additional Ti implies that atoms of these elements replace the smaller Fe atoms in the tetragonal ThMn 12 -type structure. On the other hand, contraction of the lattice upon introduction of Sc or Zr was smaller than what was expected for replacement of the Sm atoms, which suggests that the Sc and Zr atoms replace both the Sm and Fe atoms. Washing away the reduction byproducts expands the crystal lattice of the 1:12 particles and increases their coercivity. The lattice expansion associated with the washing is believed to be caused by interstitial H atoms; more research, however, is needed to establish the mechanism(s) of the washing effect on the coercivity. The earlier reported development of a high coercivity in zirconium-modified monocrystalline particles achieved by increasing the reduction annealing temperature to ≈1200 °C was similarly characteristic of the particles modified with Sc (the coercivity reaches 11.5 kOe) and Nb (8.1 kOe), but not for the particles prepared with additional Ti where the maximum coercivity of 8.3 kOe develops for a lower annealing temperature. Furthermore, it is concluded that Sc, Nb and Zr modify the high-temperature phase equilibria of the Sm(Fe,Co) 11.2 Ti 0.8 alloys allowing for an effective high-temperature processing, whereas the alloy coercivity increases with the synthesis temperature through a different, still unknown mechanism which may involve suppression of the defects specific to the 1:12 crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine-learning enabled thermodynamic model for the design of new rare-earth compounds

We employ a descriptor based machine-learning approach to assess the effect of chemical alloying on formation-enthalpy of rare-earth intermetallics. Application of machine-learning approaches in rare-earth intermetallic design have been sparse due to limited availability of reliable datasets. In this work, we developed an ‘in-house’ rare-earth database with more than 600 + compounds, each entry was populated with formation enthalpy and related atomic features using high-throughput density-functional theory (DFT). The SISSO (sure independence screening and sparsifying operator) based machine-learning method with meaningful atomic features was used for training and testing the formation enthalpies of rare earth compounds. The complex lattice function coupled with the machine-learning model was used to explore the effect of transition metal alloying on the energy stability of Ce based cubic Laves phases (MgCu 2 type). The SISSO predictions show good agreement with high-fidelity DFT calculations and X-ray powder diffraction measurements. Our study provides quantitative guidance for compositional considerations within a machine-learning model and discovering new metastable materials. The electronic-structure of Ce-Fe-Cu based compound was also analyzed to get an in-depth understanding of the electronic origin of phase stability. The interpretable analytical models in combination with density-functional theory and experiments provide a fast and reliable design guide for discovering technologically useful materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Efficiently predicting pressure-composition-temperature diagrams to discover low-stability metal hydrides

Quantitatively accurate computational predictions of metal hydride thermodynamics are challenging but critical for alloy performance optimization across a multitude of technological domains, including hydrogen storage, compression, purification, and getters. Recent machine learning approaches have demonstrated great success in this area, but can potentially suffer from several shortcomings since they rely on imbalanced experimental training data and can have poor out-of-distribution (ood) test performance. Here, in this study, we circumvent such pitfalls by developing a computationally efficient, first principles-based workflow for direct prediction of metal hydride phase equilibrium, i.e., the pressure-composition-temperature (PCT) diagram. We then demonstrate its utility on predicting low stability hydrides derived from compositionally complex C14 Laves phase AB2 alloys. Specifically, we computationally predict and then experimentally validate an AB 2 alloy series (z < 0.6 for Ti 2−z Zr z CrMnFeNi) with ideal hydriding thermodynamics for a two-stage metal hydride-based compressor for pressurizing boil off from liquefied hydrogen. Importantly, this study lays the groundwork for accurate and efficient discovery/optimization of ood, low-stability hydrides for which purely data-driven approaches lack sufficient accuracy.

08 HYDROGEN↗
DOE OSTI2026

Microstructural Engineering of Cu-Rich Nanoprecipitate formation in NiCoFeCrCu0.12 High-Entropy Alloy via Severe Plastic Deformation for Enhanced Irradiation Tolerance

This study demonstrates a defect-engineering approach for controlling Cu-rich precipitates in FeNiCrCoCu0.2 high-entropy alloys (Cu-HEAs), delivering a novel pathway for next-generation nuclear reactor materials with superior irradiation resistance. This work establishes that severe plastic deformation (SPD) processing via Shear Assisted Processing and Extrusion (ShAPE) and Friction Stir Layer Deposition (FSLD) creates dense dislocation networks and subgrain boundaries that fundamentally alter precipitation behavior under identical thermal treatments. Atom probe tomography (APT) indicates that SPD produces a metastable, atomically homogeneous solid solution that, upon moderate heat treatment (500°C/10 hour), develops remarkedly stronger Cu clustering than the as-cast counterpart. High-temperature exposure (800°C/100 h) produces near-pure Cu precipitates (~90 at% Cu) with significantly enhanced defect-sink efficacy in SPD-processed alloys: precipitate sizes of 50-60 nm and number densities of 2.7-3.8 × 10¹7 m?³, compared to 89 nm and 0.44 × 10¹7 m?³ in as-cast materials. Collectively, the findings establish defect-mediated precipitation control as a scalable, high-impact route to tailor sink density and distribution in HEAs, enabling microstructures optimized for irradiation tolerance and mechanical robustness in nuclear reactor environments.

Meher, Subhashish↗
DOE OSTI2021

Domain knowledge-informed, process-mapping AI graph for designing Fe-based alloys

<span style="font-family: Calibri, sans-serif; font-size: 12pt;">Continuous improvement in efficiency of a power plant relies on designing materials for use at increasingly higher temperature and/or pressure, for 100,000s hours of operation. Due to complexity, non-linearity and high-dimensionality of the problem, traditional Machine Learning (ML) approaches require unreasonably large datasets for the data-driven model development. Science-based material and process engineering complements hard data with, sometimes soft and intuitive, empirical domain knowledge. Artificial Intelligence (AI) was used in this study to incorporate such knowledge into computational graph architecture (process-mimicking artificial neuron design, causal layer and graph structures, ensemble modeling of latent states) and learning procedures (variable transformation, fuzzy physics pre-training and freezing of deep layers, virtual microstructure representation, and adversarial multi-objective optimization). The first alloys design pathways suggested by the AI tool (pyroMind) passed a preliminary engineering review on soundness and transparency.</span>

Romanov, Vyacheslav↗
DOE OSTI2021

The Elevated-Temperature Cyclic Properties of Alloy 316H Fabricated by Powder Metallurgy Hot Isostatic Pressing (Rev.1)

Powder metallurgy hot isostatic pressing (PM HIP), an advanced manufacturing technique, is viewed by the Department of Energy as a “transformational technology” for heavy section manufacturing of nuclear components. Although PM HIP is a mature technology, it has not been qualified in Section III, Division 5 for elevated-temperature nuclear construction. This work seeks to demonstrate a PM HIP qualification method for elevated-temperature nuclear construction that is based on allowable material characteristics. Specifically, the elevated-temperature cyclic properties of PM HIP 316H are investigated. The creep-fatigue properties of PM HIP 316H are significantly degraded compared to those of wrought. Current PM HIP practices are not able to fabricate elevated-temperature nuclear components with creep-fatigue properties that are equivalent to or better than traditional wrought components. A research and development program is proposed for qualifying PM HIP 316H for elevated-temperature nuclear construction.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Investigation of twin growth mechanisms in precipitate hardened AZ91

Here, in this work, an elasto-viscoplastic fast-Fourier-transform (EVP-FFT) model with a dislocation-density (DD) based hardening law is employed to study the growth of a {10$\bar{1}$2} tensile twin that is blocked by basal-precipitates in precipitate-hardened AZ91 magnesium alloy. It is frequently reported that twin growth is hindered in precipitate-hardened Mg alloys; however, thick twin domains are often observed experimentally in these material systems. Detailed numerical investigation of deformation twinning starting from an early propagation stage, before twin growth, reveals that the stress fields that result from two sequentially propagated twins co-impinging on a precipitate relaxes the twin back stress locally and promotes twin growth at the twin-precipitate junction. Based on these findings, a two-step growth mechanism is proposed for twins arrested by precipitates. In the first step, the interaction of a twin tip with a precipitate develops a stress concentration on the other side of the precipitate, prompting the formation of a second twin. Subsequently, the back stresses associated with the first twin are relaxed by the formation of the second twin, allowing the first twin to grow at the twin-precipitate junction and eventually engulf the precipitate. This mechanism suggests that twin growth can be achieved locally with minimal additional external forces, explaining how relatively large twin domains can develop even in the presence of arrays of precipitates.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Utilizing Site Disorder in the Development of New Energy-Relevant Semiconductors

We report controlling site disorder in ternary and multinary compounds enables tuning optical and electronic properties at fixed lattice constants and stoichiometries, moving beyond many of the challenges facing binary alloy systems. Here, we consider possible enhancements to energy-related applications through the integration of disorder-tunable materials in devices such as light-emitting diodes, photonics, photovoltaics, photocatalytic materials, batteries, and thermoelectrics. However, challenges remain in controlling and characterizing disorder. Focusing primarily on II–IV–V 2 materials, we identify three metrics for experimentally characterizing cation site disorder. Complementary to these experiments, we discuss simulation methods to understand disordered materials. Nonidealities, such as off-stoichiometry and oxygen incorporation, can occur while synthesizing metastable disordered materials. While nonidealities may seem undesirable, we describe how if harnessed they could provide another knob for tuning disorder and subsequently properties. To illustrate the effects of disorder on device-relevant properties, we provide case examples of disordered materials and their potential in device applications.

36 MATERIALS SCIENCE↗