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The tensile properties of additively manufactured (AM) metals and alloys are among the most important variables that impact the potential applications of these materials. Here we examine and report on the tensile properties of AM 316L stainless steels fabricated by the laser powder-bed-fusion (L-PBF) technique, via twelve sets of optimized laser processing parameters that produce materials with density >98.8 ± 0.10%. A heterogeneous microstructure is observed in all L-PBF samples, including microscopic features such as dislocations, cellular walls, elemental segregations, local misorientations, impurities, precipitates, and a large fraction of low-angle grain boundaries (2-10°, ∼40–60%). The derived average grain size defined by high-angle grain boundaries (>10°) is ∼30–50 μm. Tensile testing reveals a yield strength ranging from 552 to 635 MPa and a tensile-elongation-to-failure (TEF) of 0.09–0.42 for directly-printed samples, whereas these values are 592–690 MPa and 0.29–0.50 for samples machined from the as-built rectangular thin plates. In all samples, we observe a variation of tensile yield strength within ∼15% but not the TEF, suggesting marginal microstructural changes despite a wide range of laser processing parameters. The large scatter of TEF in directly-printed samples originates from the sensitivity of thin gauge geometry (∼2 mm2 cross-section area) to the built-in flaws. We measured a substantially higher strain rate sensitivity (m∼0.02–0.03) of L-PBF 316L compared to the coarse-grained counterparts (∼0.006), together with a small activation volume of ∼20–30b3 (where b is the Burgers vector of 316L). These deformation kinetics parameters suggest that the tensile plasticity of L-PBF 316L is controlled by a much finer microstructural length scale than the measured grain size, consistent with the high strength and juxtaposed nano- to macro-structures seen in these materials. Strategies to optimize the tensile properties of AM materials are discussed.

The build-up of residual stresses in a part during laser powder bed fusion provides a significant limitation to the adoption of this process. These residuals stresses may cause a part to fail during a build or fall outside the specified tolerances after fabrication. In the present work a thermomechanical model is used to simulate the build process and calculate the residual stress state for Ti–6Al–4V specimens built with continuous and island scan strategies. A layer agglomeration, or lumping, approach is used to speed up the computations. A material model is developed to naturally capture the strain-rate dependence and annealing behavior of Ti–6Al–4V at elevated temperatures. Results from the thermomechanical simulations showed good agreement with synchrotron X-ray diffraction measurements used to determine the residual elastic strains in these parts. However, the experimental measurements showed higher residual strains for the specimen built with an island scan strategy; a trend not fully captured by the simulations. Parameter studies were performed to fully understand the advantages and limitations of the current simulation methodology. Reasons for both the computational and experimental findings are discussed.

The production of metallic parts via laser-powder bed fusion (L-PBF) additive manufacturing is rapidly growing. To use components produced via L-PBF in safety-critical applications, a high degree of confidence is required in their quality. This qualification can be supported by means of a validated thermomechanical model capable of predicting the final residual stress state and subsequent performance. In this work, we use high-energy X-ray diffraction to determine a three-dimensional residual strain and stress state in a Ti-6Al-4V L-PBF component. The experimental results are used to provide validation of simulations, showing strong quantitative agreement.

The evaluation of simple thermal model of selective laser melting (SLM) process shows that the temperature distribution in the sample is characterized by two dimensionless parameters: normalized enthalpy and the ratio of dwell time to the thermal diffusion time. We demonstrated that the melt depth data taken for different machines for different materials collapsed in one curve, making possible to rescale the optimal processing parameters between the different materials and machines. The melt pool depth, width and the length are the universal function of these two parameters. Within the operational range of parameters for SLM these functions can be interpolated by the simple algebraic expressions given the possibility to reduce the calculation of the melt pool characteristic to spreadsheet model.

Additive manufacturing (AM) is a rapidly growing, multibillion dollar industry. AM is increasingly being used to manufacture functional parts, including components of safety critical systems in aerospace, automotive, and other industries. This makes AM an attractive attack target. AM Security is a fairly new field of research that addresses this novel threat. This paper serves dual purposes: For researchers just entering AM security, we provide an in-depth introduction to this highly multi-disciplinary research field. And, for active researchers in the field, this paper provides a comprehensive, structured survey of the state of the art as well as our proposal for attack taxonomies.

Additive Manufacturing is a promising way of processing tungsten, with opportunities to create more complex parts than are possible using other powder metallurgical routes. This may lead to extended applications such as collimators, in fusion reactors, or in other structurally loaded, high temperature environments. The poor thermal shock resistance and ductile-to-brittle transition that occurs in tungsten above room temperature are challenges that hinder production of fully dense and crack free parts. This research employs high speed in-situ monitoring of Selective Laser Melting of single tracks to visualize crack initiation and propagation. The circumstances that lead to cracking are correlated with microstructural morphology and processing conditions.

Additive Manufacturing (AM) is a direct digital manufacturing technology increasingly used to manufacture functional parts for military and civilian applications. As AM becomes more integral to national security and economic prosperity, it also becomes an attractive cyber-physical attack target. In this paper, we focus on attacks aiming to sabotage metal parts produced using Powder Bed Fusion (PBF), a metal AM process used to manufacture near net shaped parts for safety critical systems. Specifically, we focus on the Powder Delivery System (PDS), an integral PBF subsystem. In our examination, we adopt the attacker’s perspective, identify possible manipulations which can be used individually or in combination to degrade part mechanical properties. We experimentally evaluate the impact of a selected manipulation on part fatigue life. Destructive testing on two different types of stainless steel specimens, 17–4PH and 316 L, confirmed effectiveness of this attack and revealed material-dependent impacts while non-destructive testing illustrated the difficulty in attack detection. Based on our analysis and experimental evaluation, we conclude that the investigated attacks have the potential to be effective against complex geometry parts such as those used in military and civilian systems while remaining undetected.

During the laser-powder bed fusion ( L -PBF) process, high laser intensities, short interaction times and highly localized heat input drive large thermal gradients that result in a state of high residual stresses. Generally, the residual stresses that develop during the L -PBF process can compromise the performance of the component. Up to now, the literature has indicated that the magnitude of the residual stresses can be affected by various process parameters. In this study, all process parameters such as laser power and speed are held fixed and the focus is solely on the effect of the laser scan strategy on the three-dimensional residual stress state of L -PBF metallic components. Four Ti-6Al-4V bridge shaped components were built using island and continuous scanning patterns parallel and offset 45° from the sample axes. High-energy X-ray diffraction was used to determine the residual stress field in each of the components. Two of them were re-measured after being partially removed from the build plate. The assumptions implicit in diffraction measurements of stress are reviewed and discussed in depth because the unique microstructure associated with L-PBF Ti-6Al-4V renders the validity of those assumptions uncertain. Specifically, additional data was collected and analyzed to evaluate the relationship between grain scale and macroscopic scale stresses. The observed residual stresses were large, ½ to ¾ of the yield strength, particularly the build direction stresses near the lateral edges of the bridges. In this work, the higher stresses were observed in the bridges built via the island scan strategies, chiefly near the edges of the parts.

Laser Powder-Bed Fusion (L-PBF) metal-based additive manufacturing (AM) is complex and not fully understood. Successful processing for one material, might not necessarily apply to a different material. This paper describes a workflow process that aims at creating a material data sheet standard that describes regimes where the process can be expected to be robust. The procedure consists of building a Gaussian process-based surrogate model of the L-PBF process that predicts melt pool depth in single-track experiments given a laser power, scan speed, and laser beam size combination. The predictions are then mapped onto a power versus scan speed diagram delimiting the conduction from the keyhole melting controlled regimes. This statistical framework is shown to be robust even for cases where experimental training data might be suboptimal in quality, if appropriate physics-based filters are applied. Additionally, it is demonstrated that a high-fidelity simulation model of L-PBF can equally be successfully used for building a surrogate model, which is beneficial since simulations are getting more efficient and are more practical to study the response of different materials, than to re-tool an AM machine for new material powder.

• This article focuses on reviewing modeling and simulation effort in metal additive manufacturing taking places at U.S. Department of Energy national laboratories.

The microstructures of rapidly solidified U-6wt%Nb powder particles synthesized by centrifugal atomization were characterized using scanning electron microscopy and transmission electron microscopy. Observed variations in microstructure are related to particle sizes. All of the powder particles exhibited a two-zone microstructure. The formation of this two-zone microstructure is described by a transition from solidification controlled by internal heat flow and high solidification rate during recalescence (micro-segregation-free or partitionless growth) to solidification controlled by external heat flow with slower solidification rates (dendritic growth with solute redistribution). The extent of partitionless solidification increased with decreasing particle size due to larger undercoolings in smaller particles prior to solidification. The metastable phases that formed are related to variations in Nb concentration across the particles. The microstructures of the powders were heavily twinned.

Circumventing spatter Laser powder bed fusion is an additive manufacturing technique that laser-melts powder layer by layer to build a three-dimensional (3D) part. Khairallah et al. used experiments and a multiphysics model to determine the origin of the melt spatter and defect formation that degrade the properties of built parts (see the Perspective by Polonsky and Pollock). Informed modulation of laser power is important to avoid disturbing the powder bed and creating laser shadowing. This reduces pore formations and leads to more uniform properties of 3D-printed parts. Science , this issue p. 660 ; see also p. 583

Computational models for simulating physical phenomena during laser-based powder bed fusion additive manufacturing (L-PBF AM) processes are essential for enhancing our understanding of these phenomena, enable process optimization, and accelerate qualification and certification of AM materials and parts. It is a well-known fact that such models typically involve multiple sources of uncertainty that originate from different sources such as model parameters uncertainty, or model/code inadequacy, among many others. Uncertainty quantification (UQ) is a broad field that focuses on characterizing such uncertainties in order to maximize the benefit of these models. Although UQ has been a center theme in computational models associated with diverse fields such as computational fluid dynamics and macro-economics, it has not yet been fully exploited with computational models for advanced manufacturing. The current study presents one among the first efforts to conduct uncertainty propagation (UP) analysis in the context of L-PBF AM. More specifically, we present a generalized polynomial chaos expansions (gPCE) framework to assess the distributions of melt pool dimensions due to uncertainty in input model parameters. We develop the methodology and then employ it to validate model predictions, both through benchmarking them against Monte Carlo (MC) methods and against experimental data acquired from an experimental testbed.

Additive manufacturing (AM) enables the fabrication of complex designs that are difficult to create by other means. Metal parts manufactured by laser powder bed fusion (LPBF) can incorporate intricate design features and demonstrate desirable mechanical properties. However, printing a part that is qualified for its intended application often involves reprinting and discarding many parts to eliminate defects, improve dimensional accuracy, and increase repeatability. The process of iteratively converging on the appropriate build parameters increases the time and cost of creating functional LPBF manufactured parts. This paper describes a fast, scalable method for part-scale process optimization of arbitrary geometries. The computational approach uses feature extraction to identify scan vectors in need of parameter adaptation and applies results from simulation-based feed forward control models. This method provides a framework to quickly optimize complex parts through the targeted application of models with a range of fidelity and by automating the transfer of optimization strategies to new part designs. The computational approach and algorithmic framework are described, a software package is implemented, the method is applied to parts with complex features, and parts are printed on a customized open architecture LPBF machine.

The metal laser powder bed fusion additive manufacturing process uses high power lasers to build parts layer upon layer by melting fine metal powders. Qualification of parts produced using this technology is broadly recognised as a significant challenge. Physics based process models have been identified as being foundational to qualification of additively manufactured metal parts. In the present article, a multiscale modelling strategy is described that will serve as the foundation upon which process control and part qualification can be built. This includes a model at the scale of the powder that simulates single track/single multilayer builds and provides powder bed and melt pool thermal data. A second model computationally builds a complete part and predicts manufactured properties (residual stress, dimensional accuracy) in three dimensions. Modelling is tied to experiment through data mining.

Laser powder-bed fusion additive manufacturing of metals employs high-power focused laser beams. Typically, the depth of the molten pool is controlled by conduction of heat in the underlying solid material. But, under certain conditions, the mechanism of melting can change from conduction to so-called “keyhole-mode” laser melting. In this mode, the depth of the molten pool is controlled by evaporation of the metal. Keyhole-mode laser melting results in melt pool depths that can be much deeper than observed in conduction mode. In addition, the collapse of the vapor cavity that is formed by the evaporation of the metal can result in a trail of voids in the wake of the laser beam. In this paper, the experimental observation of keyhole-mode laser melting in a laser powder-bed fusion additive manufacturing setting for 316L stainless steel is presented. The conditions required to transition from conduction controlled melting to keyhole-mode melting are identified.

Additive Manufacturing, a.k.a. 3D Printing, is increasingly used to manufacture functional parts, including components of safety critical systems. Therefore, assuring part quality has become of paramount importance. In-situ infrared (IR) imaging systems are a promising solution to increase final build quality and minimize time-consuming and costly post processing and characterization. However, it also raises novel security concerns. We argue that, if compromised, the same in-situ quality control can be abused to sabotage manufactured parts. As a basis for our discussion, we first detail how IR thermography is used in open-loop and, experimentally, in closed-loop quality control for powder bed fusion (PBF) systems. We then identify malicious manipulations that an adversary can perform. We discuss the consequences of the manipulations on the manufactured part's quality. For selected attacks, we also provide experimental proof of the identified manipulations and their consequences.

Additive manufacturing involves a new class of cyber-physical systems that manufacture 3D objects incrementally by depositing and fusing together thin layers of source material. In 2015, the global additive manufacturing industry had $5.165 billion in revenue, with 32.5% of all manufactured objects used as functional parts. Because of their reliance on computerization, additive manufacturing devices (or 3D printers) are susceptible to a broad range of attacks. The rapid adoption of additive manufacturing in aerospace, automotive and other industries makes it an attractive attack target and a critical asset to be protected.

Additive manufacturing (AM) technology provides unique opportunities for producing net-shape geometries at the macroscale through microscale processing. This level of control presents inherent trade-offs necessitating the establishment of quality controls aimed at minimizing undesirable properties, such as porosity and residual stresses. Here, we perform a parametric study into the effects of laser scanning pattern, power, speed, and build direction in powder bed fusion AM on residual stress. In an effort to better understand the factors influencing macroscale residual stresses, a destructive surface residual stress measurement technique (digital image correlation in conjunction with build plate removal and sectioning) has been coupled with a nondestructive volumetric evaluation method (i.e., neutron diffraction). Good agreement between the two measurement techniques is observed. Furthermore, a reduction in residual stress is obtained by decreasing scan island size, increasing island to wall rotation to 45 deg, and increasing applied energy per unit length (laser power/speed). Neutron diffraction measurements reveal that, while in-plane residual stresses are affected by scan island rotation, axial residual stresses are unchanged. We attribute this in-plane behavior to misalignment between the greatest thermal stresses (scan direction) and largest part dimension.

The microstructures of U–6 wt%Nb powder particles were investigated to assess their use as a distributed fuel phase in dispersion-type nuclear fuels. The powder was produced by centrifugal atomization, leading to rapid solidification of the molten alloy particles. The microstructure of the solidified particles consisted of a dendritic structure comprising metastable α-phase-related dendrites and interdendritic metastable γ 0 phase formation. The relationship between the observed microstructure and processing conditions are discussed.

A multi-atom gas bubble-nucleation mechanism has been proposed as part of a predictive fission-gas release model for metallic nuclear fuels. Validation of this mechanism requires experimental measurement of fission-gas bubble-size distributions at well-controlled gas concentrations and temperatures. There are advantages to carrying out such a study using ion implantation as the source of gas atoms compared with neutron irradiations. In spite of previous successes using ion implantation to study fission-gas behavior in oxide fuels, there is significant uncertainty about the efficacy of using ion beams for metallic fuel studies. To address the question of the applicability of ion beams in experiments designed to study fission-gas behavior in metallic fuels, we developed and applied an exact model for the redistribution of implanted ions under annealing conditions. The conclusion is that, given the assumptions, the results from implantations at 1 MeV or less may be overwhelmed by the surface effects at all relevant temperatures. Implanting at 10 or 80 MeV can significantly diminish the influence of the surfaces and the steep concentration gradients. At 80 MeV, the location of the peak concentration profile remains stable with annealing time. Thus, it appears that ion implantation can be an appropriate tool to study the size distribution of Xe bubbles in metallic fuels. Of the conditions investigated, the best for the study are to implant at 80 MeV and carry out anneals at 773 K, 873 K, and 973 K for times less than 10,000 s.

We have applied a model for lattice and grain boundary diffusion in polycrystalline materials to assess the potential for the use of fission gas release experiments to measure the lattice and grain boundary diffusion coefficients in metallic nuclear fuel materials. Our assessment is that, assuming that grain boundary diffusion in metallic fuels is similar to that in other metals, it is reasonable to expect that lattice diffusion coefficients can be determined from short time gas release experiments and the product of the grain boundary diffusion coefficient, the segregation factor, and the boundary width can be extracted from gas release experiments at longer times. Under the same assumption, activation energies can be deduced from the temperature dependence of the measured diffusivities.

Effective integration of nonproliferation management into the design process is key to the broad deployment of advanced nuclear energy systems, and is an explicit goal of the Laser Inertial Fusion Energy (LIFE) project at Lawrence Livermore National Laboratory. The nuclear explosives utility of a nuclear material to a state (proliferator) or sub-state (terrorist) is a critical factor to be assessed and is one aspect of material attractiveness. In this work, we approached nuclear explosives utility through the calculation of a “figure of merit” (FOM) that has recently been developed to capture the relative viability and difficulty of constructing nuclear explosives starting from various nuclear material forms and compositions. We discuss the integration of the figure of merit into an assessment of a nuclear material theft scenario and its use in the assessment. This paper demonstrates that material attractiveness is a multidimensional concept that embodies more than the FOM. It also seeks to propose that other attributes may be able to be quantified through analogous FOMs (e.g., transformation) and that, with quantification, aggregation may be possible using concepts from the risk community.

The microstructure and properties of a material depend on dynamic processes such as defect motion, nucleation and growth, and phase transitions. Transmission electron microscopy (TEM) can spatially resolve these nanoscale phenomena but lacks the time resolution for direct observation. We used a photoemitted electron pulse to probe dynamic events with “snapshot” diffraction and imaging at 15-nanosecond resolution inside of a dynamic TEM. With the use of this capability, the moving reaction front of reactive nanolaminates is observed in situ. Time-resolved images and diffraction show a transient cellular morphology in a dynamically mixing, self-propagating reaction front, revealing brief phase separation during cooling, and thus provide insights into the mechanisms driving the self-propagating high-temperature synthesis.

Using the unique capabilities and high time resolution of dynamic transmission electron microscopy (DTEM), the fast kinetics of α → β-phase transformation in nanocrystalline Ti films were investigated using single-shot electron diffraction and bright-field TEM images. From quantitative analysis of the diffraction patterns, the transformation rates were determined for temperatures between transition start (1155 K) and melt temperature (1943 K). The experimental data were summarized in a time–temperature-transformation (TTT) curve with nanosecond time resolution. Theoretical TTT curves were calculated using analytical models for isothermal martensite and available thermodynamic data. Above 1300 K, there is excellent agreement between the experiment and the discrete–obstacle interaction model, suggesting that the nucleation rate and thermally assisted motion of the martensite interface are controlled by interface–solute atom interactions. However, theory predicts much slower transformation rates near the transition temperature than experiment. Experimental data fits using the Pati–Cohen model suggests that an increase in autocatalytic nucleation may partially account for the fast transformation rates at lower temperatures.

Although recent years have seen significant advances in the spatial resolution possible in the transmission electron microscope (TEM), the temporal resolution of most microscopes is limited to video rate at best. This lack of temporal resolution means that our understanding of dynamic processes in materials is extremely limited. High temporal resolution in the TEM can be achieved, however, by replacing the normal thermionic or field emission source with a photoemission source. In this case the temporal resolution is limited only by the ability to create a short pulse of photoexcited electrons in the source, and this can be as short as a few femtoseconds. The operation of the photo-emission source and the control of the subsequent pulse of electrons (containing as many as 5 x 10(7) electrons) create significant challenges for a standard microscope column that is designed to operate with a single electron in the column at any one time. In this paper, the generation and control of electron pulses in the TEM to obtain a temporal resolution10(-6)s will be described and the effect of the pulse duration and current density on the spatial resolution of the instrument will be examined. The potential of these levels of temporal and spatial resolution for the study of dynamic materials processes will also be discussed.

The transient events of the α–β martensitic transformation in nanocrystalline Ti films were explored via single-shot electron diffraction patterns with 1.5 ns temporal resolution. The diffraction patterns were acquired with a newly constructed dynamic transmission electron microscope (DTEM), which combines nanosecond pulsed laser systems and pump-probe techniques with a conventional TEM. With the DTEM, the transient events of fundamental material processes can be captured in the form of electron diffraction patterns or images with nanosecond temporal resolution. The transient phenomena of the martensitic transformations in nanocrystalline Ti is ideally suited for study in the DTEM, with their rapid nucleation, characteristic interface velocities ∼1 km/s, and significant irreversible microstructural changes. Free-standing 40-nm-thick Ti films were laser-heated at a rate of ∼1010 K/s to a temperature above the 1155 K transition point, then probed at various time intervals with a 1.5-ns-long, intense electron pulse. Diffraction patterns show an almost complete transition to the β phase within 500 ns. Post-mortem analysis (after the sample is allowed to cool) shows a reversion to the α phase coupled with substantial grain growth, lath formation, and texture modification. The cooled material also shows a complete lack of apparent dislocations, suggesting the possible importance of a “massive” short-range diffusion transformation mechanism.

Improved properties are realized in certain materials by modification of the grain boundary character distribution (GBCD) through thermomechanical processing. Here, we evaluate the influence of different processing paths on the resulting GBCD and demonstrate that the primary effect is to reduce or break the connectivity of the network of random grain boundaries.

Grain boundary character distributions and triple junction distributions have been determined for 70 experimental microstructures, comprising aluminum-, copper-, austenitic iron- and nickel-based alloys in a wide variety of processed states. In these FCC metals, the fraction of coincidence site lattice (CSL) boundaries ranges from about 12% (as for a random Mackenzie distribution) to values as high as 75%. Despite wide variations in composition, processing, and grain size, we find that the grain boundary character distribution and triple junction distributions of these materials have striking similarities, and can be described by just a few parameters. This universality arises due to the highly non-random laws that govern the assembly of the grain boundary network, and due to the kinematic limitation that CSL boundaries arise primarily through twinning.

The practical classification of grain boundaries as coincidence site lattice (CSL) boundaries requires the use of an acceptance criterion, of which the classical Brandon criterion is the most commonly used. In this work, we consider the role of the acceptance criterion on the grain boundary character distribution, triple junction distribution, and the boundary clustering behavior in nine experimental microstructures. The Brandon criterion is directly compared with the Palumbo–Aust criterion, which is more restrictive in the allowable deviations from exact CSL misorientation. Although the latter criterion causes changes in the CSL fraction, the triple junction distributions, and the cluster characteristics of the experimental microstructures, these changes are all mutually commensurate. The essential features of boundary connectivity are therefore not fundamentally affected by the choice of a CSL acceptance criterion.

The goal of grain boundary engineering is to increase the fraction of so-called special grain boundaries, while decreasing the contiguity of the remaining random boundaries which are susceptible to intergranular degradation such as cracking, cavitation, corrosion and rapid self-diffusion. In the present work, we describe a technique for the quantitative experimental study of grain boundary network topology, with an emphasis on the connectivity of special and random grain boundaries. Interconnected grain boundary networks, or “clusters”, of either entirely random or entirely special boundaries are extracted from electron backscatter diffraction data on a Ni-base alloy, and characterized according to their total normalized length (their “mass”), as well as their characteristic linear dimensions. The process of grain boundary engineering, involving cycles of straining and annealing, is found to substantially reduce the mass and size of random boundary clusters. Furthermore, quantitative assessment of the boundary network topology shows that the special grain boundary fraction is a poor predictor of network topology, but that the higher-order correlation derived from triple junction distributions can successfully describe the length scales of random boundary clusters.

Grain boundary engineering comprises processes by which the relative fractions of so-called special and random grain boundaries in microstructures are manipulated with the objective of improving materials properties such as corrosion, creep resistance, and weldability. One such process also referred to as sequential thermomechanical processing (TMP), consists of moderate strains followed by annealing at relatively high temperatures for short periods of time. These thermomechanical treatments on fcc metals and alloys with low to medium stacking fault energies result in microstructures with high fractions of Σ3n and other special boundaries, as defined by the coincidence site lattice (CSL) model. More importantly, the interconnected networks of random boundaries are significantly modified as a consequence of the processing. The modifications in the grain boundary network have been correlated with post-mortem electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM) observations of the deformed and annealed states of the material. The evolution of the microstructure to a high fraction of Σ3n boundaries is correlated with the decomposition or dissociation of immobile boundaries during annealing. This is evidenced by TEM observations of the decomposition of relatively immobile boundaries into two components, one with very low energy and thus immobile, and the other a highly mobile boundary that migrates into neighboring areas of higher strain levels. The formation of low-energy grain boundaries through this mechanism and its effect on boundary network topology is discussed within the context of grain boundary engineering and linked to known microstructural evolution mechanisms.

The identical ∑ = 5, (310)-[001] symmetric tilt grain boundary (STGB) was fabricated in three different bcc metals (Nb, Mo and Ta) by ultrahigh-vacuum diffusion bonding and the atomic structure was observed by high-resolution transmission electron microscopy. We report the results of quantitative measures of the rigid-body shift of the ∑ = 5, (310)-[001] STGB for all three metals. The atomic structures of these boundaries were also predicted by atomistic simulations using potentials developed within the framework of the model generalized pseudopotential theory for these same three metals. These potentials are an example of a new class of interatomic potentials that incorporate angularly dependent d-state interactions. These models of interatomic interactions should have applicability to simulations of the central transition bcc metals owing to the directional nature of the d bonding. To test these new models, methods were developed for quantitative measurement of the grain-boundary structure from...