Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Grain boundary structure optimization”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Laser Powder Directed Energy Deposition of Steels for Nuclear Applications

This comprehensive investigation examines the structure–property relationships in two nuclear alloy systems—Alloy 709 (A709) austenitic stainless steel and Grade 92 (G-92) ferritic/martensitic (F/M) steel—manufactured via directed energy deposition (DED) for sodium-cooled fast reactor applications. This study establishes the fundamental mechanisms for controlling microstructures for optimizing the mechanical performance of additively manufactured nuclear materials through systematic heat treatment optimization and multiscale characterization. As-deposited A709 steel develops a complex multiscale strengthening architecture consisting of a fine cellular solidification structure with diameter of 2-3 µm within10–50 µm grains, elevated dislocation densities from rapid thermal cycling, and grain boundary precipitates that activate concurrent Hall–Petch, dislocation, and precipitation hardening mechanisms to achieve exceptional properties [yield strength (YS): 603 MPa, ultimate tensile strength (UTS): 844 MPa, Vickers hardness: 220 HV] that achieve a 44% superior strength compared to that of the wrought material. Heat treatments produce different results. Solution annealing (SA) dissolves the cellular structure and reduces the hardness to 190 HV. Precipitation treatment (PT) keeps the cellular structure but adds carbides, allowing the hardness to reach 205 HV. The best approach combines both treatments (SA+PT) and creates uniform precipitate distributions with M 23 C 6 carbides at the grain boundaries and MX carbonitrides in the matrix, achieving a hardness of 195 HV. However, directional differences persist, with a 12%–15% strength variation between orientations due to the inherited layered microstructural architecture that survives aggressive heat treatment. While tensile testing at 550°C demonstrates 40%–50% thermal softening with dynamic strain aging, DED A709 steel still maintains a 71% higher YS than that of the wrought material. Ion irradiation studies (100–400 dpa) of DED A709 steel reveal progressive radiation damage with increasing void density and radiation-induced segregation causing nickel enrichment and chromium depletion, which will ultimately compromise mechanical properties. As-deposited G-92 exhibits exceptional strength (UTS: 1650–1700 MPa, 430 HV) through a complex microstructure containing both ferrite and martensite phases, a high geometrically necessary dislocation (GND) density (17.04×10 14 /m 2 ), and fine carbides. Heat treatments create distinct changes. Normalizing produces fresh martensite with the highest hardness (460 HV) and an increased GND density (20.23×10 14 /m 2 ). Tempering develops dual precipitation systems and reduces the hardness to 290 HV. The optimal approach uses sequential normalizing plus tempering, achieving balanced properties with the lowest hardness (250 HV) and a reduced GND density (11.01×10 14 /m 2 ). A processing-dependent anisotropy is observed: horizontal specimens achieve superior ductile behavior, while vertical specimens exhibit brittle failure. A tempering heat treatment successfully mitigates this anisotropic behavior by transforming the hard martensitic as-deposited structure into tempered martensite enabling both horizontal and vertical specimens to exhibit similar stress–strain characteristics with visible necking behavior. Remarkably, testing at 550°C reveals a reversal in the anisotropy, where as-deposited specimens achieve near isotropy with superior thermal stability (a 15%–20% strength reduction), while tempered specimens develop an orientation dependence with a 25%–30% strength reduction. Both alloy systems demonstrate that DED processing creates specimens with a superior strength through refined microstructural features, though with distinct strengthening mechanisms—austenitic through cellular structures and precipitates versus F/M through phase transformations and precipitates. Heat treatment optimization requires alloy-specific approaches, with A709 benefiting from controlled precipitation while G-92 requires careful phase transformation control. The results show that DED manufacturing can produce nuclear materials with exceptional performance, but directional effects and temperature-dependent behavior must be carefully considered for reactor component design and qualification.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Materials genome innovation for computational software (magics) center

Functional layered material (LM) architectures will dominate nanomaterials science in this century. We have developed theory, modeling, simulation, and software and data tools that enhance understanding and AI guide synthesis, enable characterization of complex structures, and improve capabilities in the predictive design and growth of LMs. Research at the Center has focused on: Computational synthesis and characterization: AI guided synthesis and experimental synthesis of stacked LMs with tailored properties via optimized chemical vapor deposition (CVD) growth and liquid-phase exfoliation; study defects, edges, grain boundaries, wrinkling of atomic layers and their effects on chemical, mechanical, electrical, and optical properties. Far-from-equilibrium processes: Joint experimental and simulation based probe of electronic processes with NAQMD and ultrafast X-ray free-electron laser (XFEL) and ultrafast electron diffraction (UED) facilities at Stanford. Experimentally validate NAQMD by ultrafast electron diffraction and X-ray spectroscopy studies of structural and excited state dynamics, shape fluctuations, and phonon dynamics. Scalable software: Simulation engines for desktop-to-exascale platforms using low-overhead, linear-scaling QMD algorithms; divide-conquer-recombine NAQMD with electronic excitations; extended-Lagrangian reactive molecular dynamics (RMD), machine learning (ML) based neural-network quantum molecular dynamics (NNQMD), and super-state accelerated molecular dynamics (AMD) and kinetic Monte Carlo codes; thermal and electrical transport software; and design 3D architectures of LMs with desired functionality using scalable software. Distribution of software and data, and training: Software and simulation-experimental data generated within the Center are distributed to the materials science community via Berkeley Materials Project (MP) framework. We have also organized three workshops for software distribution and training at USC (Nov. 2017, Mar. 2018) and Gaithersburg, MD (Nov. 2018) to train researchers, with the last one in focused on underrepresented groups, in collaboration with Howard University which is one of the largest HBCUs. The Center supported a total of 46 personnel and 6 undergraduate students. These include 14 faculty, 11 postdoctoral research associates, 20 graduate research assistants, and mentored 6 undergraduate students. This resulted in the publications of 63 research papers that include 46 publications on Reactive and Quantum Dynamics Simulations, 13 publications on Machine Learning for Quantum Materials, and 4 publications on Quantum Computing.

2D Materials↗
DOE OSTI2017

Accurate force field for molybdenum by machine learning large materials data

In this work, we present a highly accurate spectral neighbor analysis potential (SNAP) model for molybdenum (Mo) developed through the rigorous application of machine learning techniques on large materials data sets. Despite Mo's importance as a structural metal, existing force fields for Mo based on the embedded atom and modified embedded atom methods still do not provide satisfactory accuracy on many properties. We will show that by fitting to the energies, forces and stress tensors of a large density functional theory (DFT)-computed dataset on a diverse set of Mo structures, a Mo SNAP model can be developed that achieves close to DFT accuracy in the prediction of a broad range of properties, including energies, forces, stresses, elastic constants, melting point, phonon spectra, surface energies, grain boundary energies, etc. We will outline a systematic model development process, which includes a rigorous approach to structural selection based on principal component analysis, as well as a differential evolution algorithm for optimizing the hyperparameters in the model fitting so that both the model error and the property prediction error can be simultaneously lowered. We expect that this newly developed Mo SNAP model will find broad applications in large-scale, long-time scale simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Influence of graphene thickness and grain boundaries on MoS 2 wrinkle nanostructures

Controlling wrinkle nanostructures of two-dimensional materials is critical for optimizing the material properties and device performance. Herein, we demonstrated the in situ synthesis of large-area MoS 2 wrinkles on graphene by chemical-vapor-deposition-assisted sulfurization, and investigated the influence of graphene thickness and grain structures on the feature dimensions of MoS 2 wrinkle nanostructures. The height, width, and overall surface roughness of the MoS 2 wrinkles diminish as the number of graphene layers increases, which was further verified by determining the binding energy of graphene layers by density functional theory calculations. Furthermore, the feature dimensions of MoS 2 wrinkle nanostructures were also influenced by graphene domain boundaries because of the difference in graphene nucleation density. This may be attributed to the influence of the mechanical properties of graphene substrates on the overall feature dimensions of MoS 2 wrinkles, which are directly correlated with the interfacial adhesion energy. We believe that our findings may contribute toward the controllable synthesis of MoS 2 wrinkle nanostructures and other two-dimensional materials used for high-performance devices.

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

AI‐Driven Defect Engineering for Advanced Thermoelectric Materials

Thermoelectric materials offer a promising pathway to directly convert waste heat to electricity. However, achieving high performance remains challenging due to intrinsic trade-offs between electrical conductivity, the Seebeck coefficient, and thermal conductivity, which are further complicated by the presence of defects. This review explores how artificial intelligence (AI) and machine learning (ML) are transforming thermoelectric materials design. Advanced ML approaches including deep neural networks, graph-based models, and transformer architectures, integrated with high-throughput simulations and growing databases, effectively capture structure-property relationships in a complex multiscale defect space and overcome the “curse of dimensionality”. This review discusses AI-enhanced defect engineering strategies such as composition optimization, entropy and dislocation engineering, and grain boundary design, along with emerging inverse design techniques for generating materials with targeted properties. Finally, it outlines future opportunities in novel physics mechanisms and sustainability, highlighting the critical role of AI in accelerating the discovery of thermoelectric materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Strength stability at high temperatures for additively manufactured alumina forming austenitic alloy

Several fast-spectrum nuclear reactors designed to generate high power (~450 MWe) rely on forced convection of media such as supercritical CO 2 , sodium, or liquid lead to cool the nuclear core, operating at temperatures up to 600 °C. Cost-effective, high-strength Fe-based alumina forming austenitic (AFA) alloys are a promising candidate for the fabrication of critical nuclear components. This study investigated laser powder bed fusion (LPBF) processing of an AFA alloy composition optimized for improved creep resistance. Electron microscopy revealed an elongated grain structure along the build direction with a fine sub-grain cellular structure decorated with (Cr,Fe,Nb) 23 C 6 carbide precipitates at the intercellular boundaries. Finally, at temperatures of 20–900 °C, the LPBF alloy's superior tensile properties compared to its arc-melted counterpart and other advanced steels (e.g., SS316) were attributed to the distribution of nano-sized carbide precipitates, whereas the high ductility was attributed to the LPBF alloy's elongated grain structure.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Density functional theory study of the influence of segregation of S or Fe impurities on electromigration in nano-grained copper interconnects

The reliability of the circuits in the modern microelectronic devices remains, during last decades, one of the key topics in research and gains an attention for improving the promising candidates for conductors. Improvement of materials for such applications can be obtained by both electronic and compositional optimization. Ab initio calculations using full potential linearized augmented plane wave method in density functional theory are applied to explain the reduction in electromigration effect in the vicinity of grain boundaries (GB) in nano-structured Cu due to the segregation of some additives to the GB. Several possible mechanisms are considered. It is demonstrated that S atoms segregated to GB of nano-structured Cu lead to the growth of effective mass of the electrons. This decreases the mobility of electrons in external electric field, and, correspondingly, the momentum that they may transfer to atoms in collisions. Fe atoms segregated to GB of Cu create new empty states at the top of the valance band. These non-occupied states may stimulate the current of holes when external electric field is applied to the system, creating the “hole wind” in the direction opposite to the current of electrons. Such “hole wind” will compensate the forces generated by the electron current and therefore will reduce the total momentum transfer between charge carriers and atoms. The calculated electron density maps show that S and Fe segregating to Cu GB increases the strength of covalent bonds reducing the diffusion of Cu atoms in the vicinity of GB.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Nature of the Active Sites for CO Reduction on Copper Nanoparticles; Suggestions for Optimizing Performance

Recent experiments show that the grain boundaries (GBs) of copper nanoparticles (NPs) lead to an outstanding performance in reducing CO 2 and CO to alcohol products. We report here multiscale simulations that simulate experimental synthesis conditions to predict the structure of a 10 nm Cu NP (158 555 atoms). To identify active sites, we first predict the CO binding at a large number of sites and select four exhibiting CO binding stronger than the (211) step surface. Then, we predict the formation energy of the *OCCOH intermediate as a descriptor for C–C coupling, identifying two active sites, both of which have an under-coordinated surface square site adjacent to a subsurface stacking fault. As a result, we then propose a periodic Cu surface (4 by 4 supercell) with a similar site that substantially decreases the formation energy of *OCCOH, by 0.14 eV.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Thermoelectric Properties of Co 1-x Rh x Si 0.98 B 0.02 Alloys

In our previous study, modest boron segregation at CoSi grain boundaries could drastically reduce the electrical resistivity while maintaining a large Seebeck coefficient. We attribute this behavior to a healing effect of B on microcracks without affecting the electronic structures. CoSi 0.98 B 0.02 is the optimized sample possessing the highest power factor of 60 μW K -2 cm -1 at room temperature. To reduce the thermal conductivity while maintaining the high power factor, isoelectronic substitution, i.e., Rh on Co site, is adopted. Co 1-x Rh x Si 0.98 B 0.02 alloys with x = 0.00, 0.05, 0.10, and 0.20 were prepared by an arc melting and annealing procedure. The lattice thermal conductivity decreases monotonically with increasing x, which is ascribed to enhanced phonon scattering by point defects. The lowest lattice thermal conductivity obtained for the x = 0.20 sample is less than 50% of that for CoSi at room temperature. However, all the samples still exhibit very low resistivity and large Seebeck coefficient and thus the power factor is not decreased much. The best sample is x = 0.10, showing a room-temperature power factor of 58 μW K - 2 cm -1 . The room-temperature ZT is raised by a factor of 2.3 compared with CoSi due to the power factor enhancement and simultaneous thermal conductivity reduction.

36 MATERIALS SCIENCE↗
DOE OSTI2016

In situ investigation of the formation and metastability of formamidinium lead tri-iodide perovskite solar cells

Organic–inorganic perovskites have emerged as an important class of next generation solar cells due to their remarkably low cost, band gap, and sub-900 nm absorption onset. Here, we show a series of in situ observations inside electron microscopes and X-ray diffractometers under device-relevant synthesis conditions focused on revealing the crystallization process of the formamidinium lead-triiodide perovskite at the optimum temperature of 175 °C. Direct in situ observations of the structure and chemistry over relevant spatial, temporal, and temperature scales enabled identification of key perovskite formation and degradation mechanisms related to grain evolution and interface chemistry. The lead composition was observed to fluctuate at grain boundaries, indicating a mobile lead-containing species, a process found to be partially reversible at a key temperature of 175 °C. Using low energy electron microscopy and valence electron energy loss spectroscopy, lead is found to be bonded in the grain interior with iodine in a tetrahedral configuration. At the grain boundaries, the binding energy associated with lead is consequently shifted by nearly 2 eV and a doublet peak is resolved due presumably to a greater degree of hybridization and the potential for several different bonding configurations. At the grain boundaries there is adsorption of hydrogen and OH¯ ions as a result of residual water vapor trapped as a non-crystalline material during formation. Lastly, insights into the relevant formation and decomposition reactions of formamidinium lead iodide at low to high temperatures, observed metastabilities, and relationship with the photovoltaic performance were obtained and used to optimize device processing resulting in conversion efficiencies of up to 17.09% within the stability period of the devices.

14 SOLAR ENERGY↗
DOE OSTI2015

Real-Space Distributions of Electrical Potential in Planar and Porous Peroveskite Solar Cells: Carrier Separation and Transport

We study the carrier transport and separation in planar and porous PS devices, which is one of the most fundamental operation mechanisms of solar cells, by profiling the electrical potential across the devices. We found that the PV devices work by p-n junction at the TiO2/PS interface for the both device structures. Combining the potential profiling results with the solar cell performance parameters taken on the optimized and thickened devices, we found that mobility is the main factor limiting the device performance. Improving the mobility both within grains and across grain boundaries (or enlarging the grain size) are expected to significantly improve the device efficiency.

14 SOLAR ENERGY↗
DOE OSTI2025

Quasiaperiodic grain boundary phases of Σ⁢5 tilt grain boundaries in refractory metals

We report ground-state structures and phase transitions in Σ⁢5⁢[001] tilt grain boundaries (GBs) in body-centered-cubic (bcc) refractory metals Nb, Ta, Mo, and W. Σ⁢5 tilt GBs have been extensively investigated over the past several decades, with their ground-state structure—composed of kite-shaped structural units—previously thought to be well understood. By performing a rigorous GB structure search that optimizes the number of atoms in the boundary core, we predict different quasiaperiodic “split kite” phases analogous to those previously found in GBs in face-centered-cubic metals. Furthermore, our results suggest that complex aperiodic phases of GBs appear to be a general phenomenon, as validated through density functional theory calculations. Moreover, the atoms in the split kite phase demonstrate distinct collective diffusion dynamics. Phase-contrast image simulations of split kites show better agreement with experimental observations, offering an alternative explanation for previous microscopy results and motivating future atomically resolved imaging of the GB structure.

Body-centered cubic↗
DOE OSTI2017

Grain engineering: How nanoscale inhomogeneities can control charge collection in solar cells

Statistical and correlative analysis are increasingly important in the design and study of new materials, from semiconductors to metals. Non-destructive measurement techniques, with high spatial resolution, capable of correlating composition and/or structure with device properties, are few and far between. For the case of polycrystalline and inhomogeneous materials, the added challenge is that nanoscale resolution is in general not compatible with the large sampling areas necessary to have a statistical representation of the specimen under study. For the study of grain cores and grain boundaries in polycrystalline solar absorbers this is of particular importance since their dissimilar behavior and variability throughout the samples makes it difficult to draw conclusions and ultimately optimize the material. In this study, we present a nanoscale in-operando approach based on the multimodal utilization of synchrotron nano x-ray fluorescence and x-ray beam induced current collected for grain core and grain boundary areas and correlated pixel-by-pixel in fully operational Cu(In(1-x)Gax)Se2Cu(In(1-x)Gax)Se2 solar cells. We observe that low gallium cells have grain boundaries that over perform compared to the grain cores and high gallium cells have boundaries that under perform. These results demonstrate how nanoscale correlative X-ray microscopy can guide research pathways towards grain engineering low cost, high efficiency solar cells.

14 SOLAR ENERGY↗
DOE OSTI2022

Optimizing thermal stability and mechanical behavior in segregation-engineered nanocrystalline Al–Ni–Ce alloys: A combinatorial study

The deliberate use of solute enrichment at grain boundaries, otherwise known as segregation engineering, is a promising approach to tailor the properties of interface-dominated materials such as nanocrystalline alloys. Here, the ensuing chemical and structural evolution at grain boundaries can give rise to thermal stability and excellent mechanical properties, but the interplay between enrichment, phase decomposition, grain growth, and mechanical behavior exists in a vast composition and processing space. In this study, a combinatorial synthesis and rapid characterization approach was applied to segregation-engineered nanocrystalline Al–Ni–Ce alloys to assess the evolution of microstructure and resulting mechanical behavior as functions of alloying content and annealing conditions. In addition to the identification of alloys and processing conditions that give rise to exceptional thermal stability, strength retention, and homogeneous plastic flow, we construct combined thermal stability and deformation mechanism maps that demarcate several important regimes of behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Controlling colloidal crystals via morphing energy landscapes and reinforcement learning

We report a feedback control method to remove grain boundaries and produce circular shaped colloidal crystals using morphing energy landscapes and reinforcement learning–based policies. We demonstrate this approach in optical microscopy and computer simulation experiments for colloidal particles in ac electric fields. First, we discover how tunable energy landscape shapes and orientations enhance grain boundary motion and crystal morphology relaxation. Next, reinforcement learning is used to develop an optimized control policy to actuate morphing energy landscapes to produce defect-free crystals orders of magnitude faster than natural relaxation times. Morphing energy landscapes mechanistically enable rapid crystal repair via anisotropic stresses to control defect and shape relaxation without melting. This method is scalable for up to at least N = 10 3 particles with mean process times scaling as N 0.5 . Further scalability is possible by controlling parallel local energy landscapes (e.g., periodic landscapes) to generate large-scale global defect-free hierarchical structures.

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

Microstructure and coercivity in alnico 9

Magnetic property enhancement of alnico, a rare-earth free permanent magnet, is highly dependent on both the initial microstructure and the evolution of the spinodal decomposition (SD) inside each grain during the heat treatment process. The size, shape and distribution of the magnetic FeCo-rich (α 1 ) phase embedded in continuous non-magnetic AlNi-rich (α 2 ) phase as well as a minor Cu-enriched phase residing in between are shown to be crucial in controlling coercivity. Phase and magnetic domain morphology in a commercial alnico 9 alloy was studied using a combination of structural characterization techniques, including scanning electron microscopy, electron backscatter diffraction, aberration-corrected scanning transmission electron microscopy and Lorentz microscopy. Our results showed that casting created structural nonuniformity and defects, such as porosity, TiS 2 precipitates and grain misorientation, are heterogeneously distributed, with the center section having the best crystallographic orientation and minimal defects. The optimal spinodal is a “mosaic structure”, composed of rod-shape α1 phase with {110} or {100} planar faceting and diameter of ~30–45nm. There is also a Cu-enriched phase residing at the corners of two < 110 > facets of the α1 phase. Furthermore, it was observed that grain boundary phase reverse magnetization direction at lower external magnetic field compared to the SD region inside the grain. Improving grain orientation uniformity, reducing detrimental grain boundary phase volume fraction, and the branching of the α 1 rods, as well as their diameter, are promising routes to improve energy product of alnico.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Understanding the Unique Reactivity of Cu for Electrochemical CO 2 Reduction with a 3-Site Model

Cu-based catalysts for the electrochemical reduction of CO 2 and CO exhibit a perplexingly unique reactivity toward multicarbon based products compared to other studied electrocatalysts. Here, in this study, we use insights gained from a recent phenomenological 3-site microkinetic model and grand-canonical density functional theory calculations to clarify the importance of an underemphasized aspect critical to Cu’s unique reactivity: a population of so-called “reservoir” sites. Using model Cu surface motifs, we discuss how these types can be represented by undercoordinated structural defects like step edges and grain boundaries which form a network of highly anisotropic migration channels. These pathways are found to be amenable for feeding *CO over time to reactive sites like Cu adatoms more active toward C–C coupling. These results highlight an often overlooked aspect of catalyst optimization: reservoir site engineering, which exploits surface mobility and presents an equally important avenue for electrocatalyst engineering oversimply maximizing active site densities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗