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DOE OSTI2024

Atomistic simulations to reveal HIP-bonding mechanisms of Al6061/Al6061

Molecular dynamics simulations were employed to understand the diffusion bonding process during hot isostatic pressing (HIP) of Al6061/Al6061 alloy. Simulations of the HIP process reveal atomistic phenomena that are difficult or unlikely to be observed experimentally and provide useful insights into the mechanism of diffusion and bonding. Here, the results reveal that at the start of the HIP process, a massive incursion of oxygen atoms occurs from the pre-existing γ-Al 2 O 3 to the 6061 region across the interphase interface. These oxygen atoms interact with the enriched Mg atom layer present at the existing γ-Al 2 O 3 and 6061 matrix to form a secondary complex Mg 2 Al 2 O 5 phase. Diffusion calculations also show that transport of atoms due to the applied pressure is 4–5 orders of magnitude higher than would occur in the absence of HIP conditions. The Mg 2 Al 2 O 5 phase also provides efficient pathways for the rapid transport of Mg atoms. Because of the higher diffusion coefficients observed for Mg within the phase, Mg atoms can move more swiftly compared to their diffusion within other phases such as γ-Al 2 O 3 . This accelerated mobility facilitates the rapid movement of Mg atoms across the interface, leading to changes in the local composition and the potential growth of the Mg 2 Al 2 O 5 phase.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Direct observation of strain-enhanced hydrogen segregation and failure at high-angle grain boundaries in nickel

Understanding the mechanisms underlying hydrogen embrittlement remains difficult, even in single-element metals. Both microstructure and stress state influence hydrogen distribution in metals and alloys, which impacts deformation and failure. Here, in this work, we use in-situ Kelvin probe force microscopy (KPFM) to monitor the hydrogen distribution in pure nickel over time at 1.1 % and 3.5 % strain. The sample strained to 3.5 % results in preferential hydrogen segregation to high-angle grain boundaries whereas the sample strained to 1.1 % does not exhibit preferential hydrogen segregation. Optical digital image correlation (DIC) shows that hydrogen charging results in both localized and reduced strains during tensile testing of a notched sample. Later stages of deformation and failure (e.g. microcracking) are studied by using in-situ transmission X-ray microscopy (TXM). TXM reveals nanoscale structural changes to a propagating crack in a hydrogen environment. Localized void growth and secondary cracking occur at grain boundaries near the primary crack front. Correlative electron backscattering diffraction (EBSD) is used to relate the cracking at grain boundaries to the hydrogen segregation observed in KPFM. These findings are unified in a proposed hydrogen embrittlement mechanism that describes the interaction of hydrogen with grain boundaries, and the role of grain boundaries in hydrogen embrittlement.

Grain boundary fracture↗

DOE OSTI2025

Effect of stress on Laves phase precipitation in creep ruptured Grade 92 ferritic martensitic steel characterized by a novel accessible method

At high temperature conditions relevant to fossil and nuclear energy plants, Laves phase (Fe 2 X, X=Mo, W) precipitation is observed in common ferritic martensitic (FM) structural steels, with various reported effects on creep behavior. Despite being valuable metrics to correlate with mechanical properties and other precipitate phases, the volume fraction and number density of Laves phase precipitates has been difficult to quantify accurately using common techniques such as transmission electron microscopy (TEM) due to the relatively large size (∼0.25 μm) and low number density (∼10 11 cm −3 ) of Laves precipitates. Here, to address this characterization challenge, we developed and demonstrated a high-throughput and widely accessible method to quantify the volume fraction and number density of the Laves phase based on scanning electron microscope (SEM) images with a backscattered electron signal and the information depth (ID) of backscattered electrons. We applied this new technique in creep ruptured Grade 92 FM steel to study the effect of Laves phase on creep properties and determine the influence of stress on Laves phase precipitation. The quantitative accuracy of the SEM-based volume fraction and number density values was verified using synchrotron high energy X-ray diffraction and serial sectioning tomography. Stress did not significantly affect the Laves phase size or volume fraction during creep testing at 550 – 650°C and stress levels of 90 – 260 MPa (vs. unstressed conditions). Conversely, a moderate but statistically significant stress-enhanced increase in Laves phase number density, corresponding to an increase in nucleation rate, occurred during creep exposure above 110 MPa.

Creep↗

DOE OSTI2026

In-Situ Visualization of a Growing Brittle Crack in Aluminum Oxynitride Using Synchrotron X-Rays and the Double-Cleavage Drilled Compression Geometry

Brittle fracture is difficult to study in situ due to the speed of a growing crack and the often-catastrophic nature of failure in brittle materials. As a result, the influence of microstructural considerations, such as orientation, grain boundary locations, and strain field, on the crack path remains poorly understood. Presented in this study is a method addressing this knowledge gap, which utilizes the double-cleavage drilled compression geometry to achieve quasi-stable fracture in aluminum oxynitride (AlON). Synchrotron X-ray micro-computed tomography is used to characterize the crack shape and length, while high-energy diffraction microscopy provides information on the strains, orientations, and shapes of grains in the microstructure surrounding the crack tip. During testing, the crack grew in discrete and irregular jumps while the fracture toughness falls within reported ranges. The crack in AlON is found to have no greater tendency to crack intergranularly as compared to transgranularly, and grains which are cracked transgranularly do not display a trend in orientation or stress when compared to those around which the crack followed a grain boundary. The high resolution of the crack path and microstructural data provides a path forward for modeling and understanding 3D brittle fracture.

Gorske, Sara F.↗

DOE OSTI2021

Sensor impact evaluation and verification for fault detection and diagnostics in building energy systems: A review

Sensors are the key information source for fault detection and diagnostics (FDD) in buildings. However, sensors are often not properly designed, installed, calibrated, located, and maintained, which negatively impacts FDD performance. Several sensor-related FDD topics have been widely studied, covering a wide range of fault types and applications. However, it is difficult to get a clear picture of the technical development of sensor-related topics in FDD. A systematic review of sensor topics is needed to summarize the existing research in a logical way, draw conclusions on the current development, and predict the future development of sensors in building FDD. To address this gap, we conducted a comprehensive literature review of more than 100 FDD-sensor-related papers. In this article, we subdivide the FDD tasks into building-level, system-level, and component-level FDD, and review sensor-related topics in each category. Our major conclusions are: (a) current data-driven FDD research focuses more on FDD algorithms than sensors, (b) sensor “hardware” research topics are less studied than sensor “software” topics, (c) very few papers focus on sensor engineering as an integral aspect of FDD development, and (d) some important sensor topics, such as sensor cost-effectiveness and sensor schema/layout/location, are not well studied. Finally, we discuss the need for a systematic framework of FDD sensors and models to integrate sensor design/selection, sensor data analysis/mining, feature selection, physics-based or data-driven algorithm development, sensor fault detection, sensor calibration, and sensor maintenance. Finally, expert interviews are conducted to validate the above findings and conclusions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Optimal Gas-Electric Energy System Decarbonization Planning

As energy utilities implement climate change mitigation policies, system planners require strategies for achieving affordable emissions reductions. Coordinated planning of electric power and natural gas systems will allow synergistic investments to address cross-sector operational constraints, competing uses for net-zero emissions fuels, and shifts in energy demands across energy carriers. In this study, we develop a novel optimization program that finds the cost-minimizing mix of infrastructure expansion or reduction across gas and electric systems to satisfy sector-specific emissions constraints. Alongside energy supply resources, our framework allows for central-planning of end-use equipment stocks to allow switching between gas and electric appliances upon failure or premature replacement. The proposed model is used to simulate case study scenarios for a benchmark 24-pipe gas network coupled to a 24-node power system test network. We find that electrification of greater than 80% of core gas demands is a component of the least-cost solution for modeled energy systems. Despite this substitution, the gas system is maintained to service difficult-to-electrify customers and to deliver net-zero emissions gas to electricity generators in times of peak electricity demand. Restricting electrification of gas appliances increases reliance on power- to-gas technologies and increases annual costs by 15% in 2040. Neglecting constraints on pipeline blending of hydrogen can produce a misleading result that relies on hydrogen blend fractions of greater than 50%. In all cases, we find the average costs of delivered gas increase nearly 5-fold across the decarbonization transition, highlighting the importance of future work investigating cost-allocation strategies for ensuring an equitable energy transition.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Decarbonizing all-electric communities via carbon-responsive control of behind-the-meter resources

The progression of electrification in the building and transportation sectors brings new opportunities for energy decarbonization. With higher dependence on the grid power supply, the variation of the grid carbon emission intensity can be utilized to reduce the carbon emissions from the two sectors. Existing coordinated control methods for buildings with distributed energy resources (DERs) either consider electricity price or renewable energy generation as the input signal, or adopt optimization in the decision-making, which is difficult to implement in the real-world environment. This paper aims to propose and validate an easy-to-deploy rule-based carbon responsive control framework that facilitates coordination between all-electric buildings and electric vehicles (EVs). The signals of the grid carbon emission intensity and the local photovoltaics (PV) generation are used for shifting the controllable loads. Extensive simulations were conducted using a model of an all-electric mixed-use community in a cold climate to validate the control performance with metrics such as emissions, energy consumption, peak demand, and EV end-of-day state-of-charge (SOC). Our study identifies that 4.5% to 27.1% of annual emission reduction can be achieved with limited impact on energy costs, peak demand, and thermal comfort. Additionally, up to 32.7% of EV emission reduction can be obtained if the EV owners reduce the target SOC by less than 21.2%.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

A non-melting additive approach to structural repair of aluminum aircraft fastener holes

The damage to fastener holes in aerospace aluminum structures presents significant challenges for aircraft durability, and conventional bushing methods for repairing oversized holes often fall short due to the lack of metallurgical bonding and limited edge distance availability. This study investigates additive friction stir deposition, a non-melting additive process, as a viable alternative for the structural repair of aerospace fastener holes. The repair process, demonstrated on AA7050 (Al-Zn-Mg-Cu-Zr) hole structures, involves filling oversized holes with new material and machining to restore the original hole size. The repaired hole coupons are defect-free and exhibit good fatigue performance under fully reversed tension-compression loading (R = -1). At a nominal stress amplitude of 123.5 MPa, the average number of cycles to failure is 12,666 for unrepaired baseline coupons and 17,372 for effectively repaired coupons. Restoring complex geometries without compromising fatigue performance has been difficult in aerospace applications; this study marks the first demonstration of additive repair that consistently outperforms the unrepaired baseline coupons. Notably, the result is achieved through a low-energy, cost-effective solution without the need for post-repair heat treatment. Except for a few outliers, the post-repair fatigue performance generally remains inferior to that of undamaged, pristine coupons, likely due to precipitate evolution in AA7050 caused by the thermomechanical processing nature of additive friction stir deposition. This evolution weakens the repair region and the adjacent base material, leading to faster crack initiation and growth compared to the properly aged base material, AA7050-T7451.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Process optimization of complex geometries using feed forward control for laser powder bed fusion additive manufacturing

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 work describes a fast, scalable method for part-scale process optimization of arbitrary geometries. Additionally, 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.

3D printing↗

DOE OSTI2020

Correlation of SWIR imaging with LPBF 304L stainless steel part properties

In the Laser Powder Bed Fusion (LPBF) process, the local thermal history can vary significantly over a part as the heat transfer characteristics and the laser scan path are geometry dependent. The variations introduce the potential for defects that lead to part failure, some of which are difficult to identify non-destructively with common ex-situ evaluation techniques. These defects include significant microstructural and mechanical property differences in the part interiors. In this paper, thermal features are extracted from in-situ Short-Wave Infrared (SWIR) imaging measurements to compile voxel based part representations and understand how the complexities in the thermal history affect part performance. The deviations in thermal features due to different laser processing parameters and complex scan pathing are explored. Empirical correlations are developed to map thermal features with the engineering properties (bulk yield strength, area percentage porosity, and local state) of 304L stainless steel parts manufactured by LPBF. Processing modes (insufficient melting and keyholing) are determined by mapping part property measurements with multiple thermal features. Generating the relationships between thermographic measurements and resulting SLM part properties lays the foundation for in-situ part qualification.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Characterizing material transitions in large-scale Additive Manufacturing

Integrating Multiple Materials (MM) into large-scale Additive Manufacturing (AM) is a key for various industrial applications wishing to incorporate site-specific properties into geometrically complex designs that are difficult to manufacture with traditional techniques. Printing with multiple materials is typically accomplished by using layers as natural material boundaries, but having the capability to switch between materials within a single layer without pausing would further expand MM possibilities. This study used Cincinnati Incorporated’s Big Area Additive Manufacturing (BAAM) system to explore material transitions with a novel dual-hopper that enables in-situ material blending of a pelletized feedstock. Constructing MM and functionally graded material (FGM) structures requires depositing a specific material composition at a specific geometric location to achieve a desired performance. Furthermore, accurately implementing this with the BAAM’s blended extrusion system requires a thorough understanding of the transition between distinct material compositions. This study characterizes a step-change transition between neat acrylonitrile butadiene styrene (ABS) and carbon fiber-reinforced ABS. Three distinct techniques were compared for analyzing the fiber content, and the transition zone between materials was characterized as a function of transition direction. The transition process was consistent to within 0.7 wt% carbon fiber variation between different layers and prints. The transition between materials was found to be directionally dependent, with ABS to CF/ABS having a transition length of 3.5 m compared to 3.2 m for CF/ABS to ABS. Furthermore, the transition from Material A to Material B was found to be repeatable with a possible variance in transition length of 0.3 m.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Fused filament fabrication of novel phase-change material functional composites

Additively manufactured polymer heat exchangers are of recent interest in the thermal sciences due to their lightweight and intricate heat-transfer-enhancing geometrical features. The goal of the present research is to directly encapsulate phase-change material (PCM) into polymer filament for the purpose of 3D printing polymer heat exchangers capable of latent heat thermal energy storage and management. PCMs have the ability to absorb large amounts of latent heat while undergoing a solid-to-liquid phase change at a nearly constant temperature. Encapsulation or containment of PCMs is necessary to prevent leaking since the material continuously cycles between a liquid and a solid state. An organic-based PCM and high-density polyethylene (HDPE) were combined and extruded into a functional composite filament. For the first time, with the aid of a heated enclosure and HDPE build plates, it was demonstrated that these functional composite materials can be printed using fused filament fabrication (FFF). Printing HDPE is known to be difficult; however, based on what was observed in the current study, the PCM and HDPE composite was easier to print than pure HDPE. Thermal properties, such as latent heat of fusion, phase-change temperature, and thermal conductivity, of the composite filament and 3D printed samples were investigated and compared with compression-molded bulk material. Finally, the microstructures of the composite filament and 3D printed samples were visualized, and the basic structures of the HDPE and PCM within both the filament and 3D printed parts were clearly delineated.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Nanoparticle-enhanced absorptivity of copper during laser powder bed fusion

We report laser powder bed fusion (LPBF) of pure copper for thermal and electrical applications is hampered by its low near-infrared absorptivity and high thermal diffusivity. These material properties make it very difficult to localize the thermal energy needed to produce high density 3D printed parts. Modification of metal powders via nanoparticle additives is a promising approach to increasing absorptivity, but the effect of nanoparticles on absorptivity and melting behavior during LPBF is not well understood. In this study, we developed an in situ calorimetry system to measure effective absorptivity during LPBF on copper substrates. We decorated copper substrates using three nanoparticle systems (CuS, TiB 2 , multilayer graphene flakes) and demonstrated an enhanced absorptivity of the decorated substrates relative to pure copper. Graphene nanoflakes resulted in the highest improved absorption relative to pure copper from 0.09 to 0.48, due to their stability at high laser scanning powers. A thermomechanical model with convective heat transfer provided confidence in the measurements by reproducing the experimental melt pool traces. Full 3D cylindrical prints demonstrated an improvement in relative density of the copper-graphene powder prints (in the range of 0.930–0.992), relative to that of as-purchased copper powder prints (in the range of 0.854–0.972). This work provides a fundamental study of nanoparticle-enabled LPBF of highly reflective metals and demonstrates a viable route for expanding the library of reliably printable metals.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Review of Computer-Aided Manufacturing (CAM) strategies for hybrid directed energy deposition

Hybrid additive manufacturing intertwines both additive and subtractive manufacturing layer by layer to digitally fabricate parts with complex geometries, improved surface finish and tight dimensional accuracies, the sum of which is difficult to obtain with any single process. Computer-Aided Manufacturing (CAM) software is required to orchestrate the machine toolpathing for both the deposition as well as the machining processes and is crucial for the successful fabrication of high quality structures. Additionally, CAM requires substantial operator input to account for challenging aspects of each fabricated structure. For example, deciding at which layer of deposition will the machining process continue to maintain access to complex cavities for finishing - internal features that would otherwise be unfinishable due to reach limitations or obstructions. Moreover, of the many commercially-available hybrid systems, each has a unique kinematic environment which can benefit from specific optimization of toolpath planning and substantial research has directly correlated toolpathing with the microstructure evolution, mechanical properties, porosity and residual stress state of the final fabricated part. This review explores the available strategies for CAM in the context of hybrid direct energy deposition, discusses the advantages and disadvantages of each and considers future CAM trends for this transformational digital manufacturing technology.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Nanoparticle-enabled increase of energy efficiency during laser metal additive manufacturing

The low energy efficiency of the laser metal additive manufacturing (AM) process is a potential sustainability concern for large-scale industrial production. Explicit investigation of the energy efficiency for laser melting requires the direct characterization of melt pool dimension and vapor depression, which is very difficult due to the opaque nature of the molten metal. Here we report the direct observation and quantification of effects of the TiC nanoparticles on the vapor depression and melt pool formation during laser powder bed fusion (LPBF) of Al6061 by in-situ high-speed high-energy x-ray imaging. Based on the quantification results, we calculated the laser melting energy efficiency (defined here as the ratio of the energy needed to melt the material to the energy delivered by the laser beam) with and without TiC nanoparticles during LPBF of Al6061. Here the results show that adding TiC nanoparticles into Al6061 leads to a significant increase of laser melting energy efficiency (114% increase on average, 521% increase under 312 W laser power, 0.4 m/s scan speed). Systematic property measurement, simulation, and x-ray imaging studies enable us, for the first time, to identify that three mechanisms work together to enhance the laser melting energy efficiency: (1) adding TiC nanoparticles increases the absorptivity; (2) adding TiC nanoparticles decreases the thermal conductivity, and (3) adding TiC nanoparticles enables the initiation of vapor depression and multiple reflection at lower laser power (i.e., lowers the laser power threshold for keyholing). The method and mechanisms of using TiC nanoparticles to increase the laser melting energy efficiency during LPBF of Al6061 we reported here may guide the development of feedstock materials for more energy efficient laser metal AM.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Denoising diffusion probabilistic models for generative alloy design

Inverse material design is an extremely challenging optimization task made difficult by, in part, the highly nonlinear relationship linking performance with composition. Quantitative approaches have improved significantly owing to advances in high throughput experimentation and computational thermodynamics. However, existing physics-based tools are mostly forward models; input a chemistry and obtain a prediction. More recently the materials community has leveraged advances in the machine learning community to establish novel inverse design frameworks. Very recently denoising diffusion probabilistic models have been shown to be extremely powerful generators producing synthetic data of various modalities e.g. images, text, audio, tables, etc.. In this work a novel framework for alloy design and optimization is proposed leveraging these class of models. Five key generative tasks are demonstrated (1) unconditional generation (2) composition conditioned generation (3) property conditioned generation (4) multi-feedstock conditioned generation and (5) generative optimization. These methods were tested on three case studies: high entropy alloy design, superalloy binder jet additive manufacturing, and in-situ dual-feedstock wire-arc additive manufacturing. Results indicate that the established models are extremely flexible, expressive, and robust. The architecture’s flexibility and training procedure empower the model to learn complex intra-compositional and composition-property relationships. Furthermore, the probabilistic nature of these models makes them well suited for addressing solution non-uniqueness and tackling uncertainty quantification tasks. While the fidelity and quantity of the underlying training data is paramount, we envision that future alloy design frameworks will make extensive use of these kinds of machine learning models as “search” tools bolstering the utility of experimental and computational approaches.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Methodology to determine printability criteria of highly concentrated pastes through rheological characterization

Material extrusion is an additive manufacturing technique that enables the creation of reproducible and complex hardware by depositing a viscous, shear-thinning ink onto a substrate in a custom-pattern via extrusion through a syringe. Here, the ability of an ink to be extruded onto a substrate in many layers, and maintain the desired shape is what defines the printability. Printability is often investigated by formulating, printing, and postmortem analysis of final parts in an iterative manner. Investigations of printability through rheological characterization have often been concerned with inks that straddle the line between printable and too thin, leaving out an entire class of inks that are highly-filled pastes, where extrudability is the limiting factor. Highly-filled pastes continue to pose issues for researchers as the effect of filler morphology, size, loading, and packing fraction on the ink rheology and corresponding printability is not understood. While traditional rheological characterizations may be useful for some inks, we show that protocols utilizing steady-shear, or large-amplitude oscillatory shear are difficult and unreliable for highly-filled pastes. Through transient rheology paired with real-time images we show that each traditional protocol produces inhomogeneous deformations that violate the assumptions that underly common rheological definitions. Instead, we demonstrate metrics measured with small-amplitude oscillatory shear that are correlated to the printability of various ink formulations ranging in loading. The rheological measures that accurately predict the printability of the inks are the axial stress measured at small amplitudes, and the critical stress amplitude above which rheological characterizations become impossible. In addition, we estimate the maximum packing fraction for each filler, based on the exponent common to hard sphere models, and show that the printability of each ink can be predicted by the ratio of the packing fraction to the theoretical maximum. We show how small-amplitude oscillatory shear allows users to develop printability criteria for any ink to enhance the workflow in the development of new inks, increase the performance of material extrusion printing, and improve the stability of printed parts, with less wasted time and materials.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Enforcing global constraints for the dispersion closure problem: τ 2 -SIMPLE algorithm

Permeability and effective dispersion tensors are critical parameters to characterize flow and transport in porous media at the continuum scale. Homogenization theory defines a framework in which such effective properties are first computed from solving a closure problem in a repeating unit cell of the periodic microstructure and then used in a macroscopic formulation for efficient computation. The closure problem is formulated as a local boundary value problem subjected to global constraints, which guarantee the uniqueness of the solution and can be difficult to satisfy for complex geometries and at high flow conditions. These constraints also ensure that pore-scale pressure, velocity, and concentration fields can be accurately reconstructed from the closure variable. Building on a previous work, here we present a framework that allows to satisfy global constraints associated to both the permeability and the dispersion closure problems by introducing two artificial time scales. The algorithm, called τ 2 -SIMPLE, computes both permeability and effective dispersion given an arbitrarily complex geometry and flow condition. Furthermore, this algorithm is demonstrated to be accurate for both 2D and 3D geometries across varying flow conditions, and thus it can be used to quickly characterize effective properties from porous media images in many applications.

97 MATHEMATICS AND COMPUTING↗