Aaron P. Stebner

Abstract Shape memory alloy (SMA) processing parameters play a critical role in determining phase transformation behavior, strain recovery, and total work output. This study casts compositionally equivalent SMAs using multiple techniques to vary heating and cooling rates, characterizes the resulting microstructures by optical microscopy, and assesses thermomechanical performance through digital image correlation, induction pyrometry, and uniaxial press measurements. Initial results demonstrate that drop casting produces equiaxed microstructures and that the identified processing-transformation relationships are transferable to higher-temperature SMA systems.

To date, process parameter developments for blown powder laser beam directed energy deposition additive manufacturing (DED‐LB‐BP) of pure molybdenum (Mo) frequently resulted in inconsistent depositions, cracking, and build plate delamination. In new statistics‐guided work to identify better performing process parameter sets, multiple process parameter sets that achieve >99% dense pure Mo depositions are identified. Still, the density results using each set are stochastic. The origin of build‐to‐build density variance using the same parameter sets is identified to be intergranular cracking. This root cause is validated by contrasting depositions of pure Mo with depositions of Mo with hafnium carbide (HfC) additions to refine the grain structures and eliminate intergranular cracking (but not reduce porosity). Additionally, this work exhibits the capability of HfC additions to inoculate Mo microstructures during DED‐LB‐BP processing. Altogether, this work provides insight and future direction to the development of Mo‐based alloys for DED‐LB‐BP, better enabling the potential for Mo‐based alloys as high specific strength, lower cost, additively manufactured refractory structural materials.

The use of reactive additive manufacturing (RAM) techniques to produce metal matrix composite (MMC) materials provides two salient benefits. RAM-MMCs display desirable strength and mechanical performance, while the RAM process, enabled through additive manufacturing techniques such as laser powder bed fusion, produces high-quality metal parts quickly and with complex geometries. Characterization and optimization purely by physical experimentation over the entire RAM-MMC design space is cost prohibitive in terms of time and resources. Creating tailorable designs of RAM-MMCs that meet specific mechanical performance targets, thus, requires computational models that accurately capture the effects of reinforcement in RAM-MMC materials—in conjunction with the process-induced microstructure—on the hardening and damage evolution response of the material. We propose a new RAM-MMC-specific strengthening formulation, which we couple with triaxiality-based continuum damage mechanics (CDM) and implement using a large-strain elasto-viscoplastic fast Fourier transform (LS-EVPFFT) code. The new constitutive model accounts for three specific strengthening mechanisms observed in RAM-MMCs, viz., Orowan looping, grain refinement strengthening through the Hall-Petch relationship, and geometric mismatch strengthening. This framework enables simulation of deformation and failure in 3D polycrystalline RAM-MMCs, capturing the influence of varying reinforcement phase volume fractions on mechanical performance. The framework effectively captures the microstructure-to-property relationship of RAM-MMCs and opens the door to their computationally driven design.

The 3D printing industry is rapidly growing and increasingly adopted across various sectors, including manufacturing, healthcare, and defense. However, the operational setup often involves hazardous environments, necessitating remote monitoring through cameras and other sensors, which opens the door to cyber-based attacks. In this paper, we show that an adversary with access to video recordings of the 3D printing process can reverse-engineer the underlying 3D print instructions. Our model tracks the printer nozzle's movements during the printing process and maps the corresponding trajectory into G-code instructions. Further, it identifies the correct parameters, such as feed rate and extrusion rate, leading us to be able to successfully perform IP theft. To validate the success of IP theft, we design an equivalence checker that quantitatively compares two sets of 3D print instructions, evaluating their similarity in producing objects that are alike in shape, external appearance, and internal structure. Our equivalence checker, unlike other simple distance-based metrics such as normalized mean square error, is rotational as well as translational invariant. This is necessary to capture shifts in the base/start position of the reverse-engineered instructions relative to the actual 3D print instructions that can happen due to different camera positions. Our model achieves an average accuracy of 90.87% and generates 30.20% fewer instructions compared to the current state-of-the-art methods that produce instructions that either lead to faulty or incorrect (in terms of difference in shape and internal structure) 3D prints. Additionally, we use our model to reverse-engineer the 3D print instructions from a video recording and print a fully-functional counterfeit object.

Abstract Multiscale crystal plasticity modeling of metal forming offers potential for effective design processes that consider microstructural evolution during significant plastic deformation. However, conventional multiscale methods for forming are expensive due to complex loading conditions and high-cost microscale models, making them challenging to apply in practice. These methods can be significantly accelerated through use of low-cost machine learning surrogate models for the microscale response. While these techniques have been demonstrated for simple load cases, they have not yet been demonstrated for manufacturing applications with full-field texture results. In this work, we develop efficient multiscale simulation workflows for manufacturing through single-point incremental forming using recurrent neural networks for constitutive response and texture evolution of a crystal plasticity model. This approach achieves up to a 63.6x increase in speed compared to conventional techniques and is demonstrated for an aluminum alloy with two unique forming paths. These workflows yield consistent trends between forming force and thickness variation, texture results in agreement with ground truth models, and permit extraction of the full-field texture evolution over the entire formed part. This enables efficient multiscale trade studies and optimization of local microstructures in industrial forming applications.

Arc cast samples made for alloy development research using a conventional water-cooled copper hearth often exhibit columnar microstructures and some amount of unmelted material, the extent of which may vary from sample to sample or operator to operator. To increase consistency and in turn comparability across different samples and operators, a drop-casting fixture for a non-consumable electrode arc casting furnace was developed to provide repeatable solidification conditions. In comparing the use of the new fixture to a conventional hearth, pure molybdenum castings exhibited more equiaxed microstructures evidenced by circularity measurements of grain cross-sections improving from 0.51 ± 0.03 to 0.67 ± 0.004, and a set of Mo-MoRe alloys showing an average circularity of 0.75 ± 0.008, indicating that an additional benefit is more homogenous, isotropic samples. The equiaxed microstructure repeatability was verified across multiple molybdenum samples and multiple dilute MoRe alloys.

Abstract Molybdenum (Mo) is comparable in weight, has higher thermal conductivity, costs less, and can sustain higher mechanical loads at high temperatures than niobium, motivating the development of additive manufacturing (AM) of Mo structural components as complements and/or replacements to niobium-base refractory alloys for high-temperature applications. Toward enabling AM of Mo components an investigation of directed energy deposition AM using a laser beam energy source and blown powder feeding (DED-LB-BP) was performed. Mo powders mixed with La 2 O 3 ceramic particles were printed and showed grain refinement compared to pure Mo depositions. Pure Mo samples exhibited grains that grew several millimeters, significant porosity, and intergranular cracking. Additions of 0.7–3.5 wt.% La 2 O 3 particles result in printed densities greater than 99% corresponding with 100- to 300-µm-sized grains, limited porosity, and reduced cracking. Furthermore, previous work suggested that laser powers greater than 4500 W may be required for DED-LB-BP of Mo; in this work, materials were fabricated and improved using laser powers less than 2000 W.

Laser powder bed fusion (LPBF) additive manufacturing is widely used to fabricate geometrically complex metal components. In LPBF, a layer of metal powder is swept onto the build surface by a recoater blade and then melted with a laser; this process is repeated to build a part layer-by-layer. A common flaw in LPBF processes is overbuilding, where some region of a layer is built higher than the desired layer height. Collisions between the overbuild and the recoater blade on subsequent sweeps can lead to a persistent defect in the part or damage to the recoater blade. In this research, acoustic emission sensors mounted to the recoater blade subassembly of an EOS M290 machine are used to detect collisions with the recoater blade. This work presents the sensor configurations for and results of preliminary experiments conducted during powder sweeps only and during fabrication of small test coupons. [Work supported by NASA Space Technology Graduate Research Opportunities (Grant No. 80NSSC23K1213)]

Outstanding challenges must be addressed to mature additive manufacturing (AM) technologies for glass‐forming alloys (GFA) including increasing as‐built densities, limiting cracks and pores, controlling crystallinity within fusion and heat‐affected zones (HAZ), and increasing the size of process parameter windows that result in quality materials. The thermal cycles that are unique and specific to AM limit the applicability of research from casting literature under some circumstances. In this work, single‐track and multitrack laser glazing experiments performed on four unique suction cast glass‐forming compositions provide a means for screening the suitability and relative process window sizes for powder bed fusion–laser beam (PBF–LB) AM of four GFAs in the absence of available powders. The crystallinity of the fusion zone and the HAZ as well as the presence of cracks are observed as process parameters are varied for each alloy. Both conventionally good and conventionally bad glass formers show great potential for PBF–LB processability. Glass‐forming ability in and of itself is not a good predictor of PBF–LB printability.

The characteristics of soft magnets are major drivers of the performance of electrical machinery. To better enable the rapid optimization of these properties relative to material or manufacturing changes, high-throughput characterization techniques are desired. In this work, a methodology for measuring the magnetic properties of soft ferromagnetic samples is developed. The proposed methodology utilizes an inexpensive desktop instrument designed to be amenable to automation. The use of the newly designed hardware and requisite data analysis methodology is validated and shown to have acceptable accuracy and repeatability for screening purposes; saturation magnetization is typically accurate to 1% and repeatable to 0.2%, while coercivity is repeatable to 20–30 A/m. The measurement time per specimen is under 20 seconds, with an architecture that allows for significant further improvement. No post-processing of samples is required, nor precise geometries. These characteristics are compared to existing techniques and shown to represent a favorable tradeoff for many screening applications.

Cold spray additive manufacturing (CSAM) is an attractive solid‐state bonding technique due to its rapid manufacturing rate and the ability to avoid deleterious effects found in solidification‐based additive manufacturing. Unfortunately, CSAM of steel components has been difficult to date to the high strength of the steel particles which resists deformation and creates interparticle porosity. Herein, it is found adding softer Cu powder particles to steel (SS316) powder and utilizing a heat treatment can decrease the porosity of the as‐sprayed structure while increasing the mechanical properties. The mixture results in an increased sprayability of the structure, as the Cu particles preferentially fill the pores, increasing the density. The microstructural evolution of the SS316 and Cu particles at the particle interfaces and interiors is investigated and reveals that the materials undergo a heterogeneous deformation route which facilitates the densification of the CSAM structure. Through annealing these components, the tensile strength increases and the density increases further. Both materials undergo microstructural recovery along with selected interdiffusion of elements which improves the metallurgical bonding. It is demonstrated that the heterogeneous deposition and microstructural evolution between the dissimilar materials can improve the overall component properties.

Nickel‐rich NiTiHf alloys that are heat treated to strengthen the microstructures with a dense distribution of Ni 4 Ti 3 nanoprecipitates exhibit very high strengths and good quasi‐static indentation resistance and rolling contact fatigue performances. To determine whether these properties are maintained at high rates of loading, in situ and recovery flyer plate impact shock experiments are performed on a Ni 54 Ti 45 Hf 1 alloy at impact velocities ranging from approximately 150 m s −1 (2.5 GPa) to 700 m s −1 (12.40 GPa). Analysis of shocked samples indicated less cracking is observed to emanate from spall failures resulting from impact velocities greater than 250 m s −1 (4.23 GPa), concurrent with observations of intragranular microbands within the microstructures. Analyses show clear evidence that, like responses to quasi‐static loading, martensitic phase transformation occurs upon shock compression in all cases. However, dissimilarly, for the higher impact velocities it reverses upon stress release, leaving behind microbands that show no evidence for retained martensite and within which the Ni 4 Ti 3 nanoprecipitates dissolved. These results indicate that strain‐rate dependence of these SMAs under shock loading is not only governed by the expected physics of rate‐dependence of the martensitic transformations themselves but may also be enhanced by inelastic deformation mechanisms that result in precipitate dissolution.

The necessity for recyclable materials in wind energy applications has fueled research in glass fiber reinforced thermoplastic composites to replace their thermoset counterparts. Toward demonstrating that infusible acrylic resins can replace epoxy based composite systems in wind blade manufacturing, comprehensive static test protocols were performed, and the resulting data are presented. Specifically, unidirectional and biaxial (±45) continuous E-glass reinforced thermoplastic and epoxy laminates were prepared in four and eight ply laminates. Physical properties were characterized including density, fiber volume fraction, and glass transition temperatures, together with mechanical properties for tensile, compression, and shear responses. Comprehensive evaluation of these data supports infusible acrylic thermoplastic resin systems as viable alternative prospects to replace epoxies in E-glass reinforced wind blades as verified by comparable results for both composite systems.

This technique requires measurements

Traditionally, thermoset resins such as polyesters (PE) and epoxies are used as the polymer matrix for construction of wind turbine blades. However, concern about their end‐of‐life treatment garners interest to use thermoplastics for increased recyclability. However, the high viscosity of molten thermoplastics inhibits their use in manufacturing wind turbine blades with injection or compression molding. A recently developed, infusible, reactive thermoplastic resin overcomes this technological barrier. Toward verifying that this recyclable resin is suitable for use in wind turbine blades, a dataset of R = 0.1 and R = 10 fatigue data for glass fiber–reinforced acrylic composites is provided and equal fatigue life to industry standard epoxy and unsaturated PE resin systems is demonstrated. Specifically, R = 0.1 fatigue data for acrylic composites at room temperature and −30 °C for verification of low‐temperature performance are tabulated. To elucidate failure mechanisms, in situ mechanical testing with X‐ray computed tomography demonstrates that damage accumulation occurs by crack propagation along the fiber–matrix interface under cyclic loading. Infrared (IR) thermography predicts failure points in composites specimens with porosity defects introduced from nonideal manufacturing processes. Furthermore, these manufacturing defects are shown to compromise the fatigue life of the acrylic laminates by an order of magnitude.