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Lienert, Thomas J.

Publications and source records attributed to Lienert, Thomas J..

6 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Controlling microstructure and B2 ordering kinetics in Fe–Al system through additive manufacturing

Multi-material fabrication between steel and aluminum is challenging because of the formation of several intermetallic phases. Embrittling B2 ordered intermetallics form in the steel rich side and are stable till about 60% of Al dilution in steel. In this work by using multi-length scale characterization coupled with integrated computational process and thermokinetic modeling, we show that the ordered B2 intermetallics in the steel rich side of the Fe–Al system forms via a nucleation and growth mechanism. The extent of B2 ordered intermetallics can be controlled by modifying the directed energy deposition-additive manufacturing (DED-AM) process parameters. Our findings lay the foundation for enabling fabrication of crack-free functionally graded compositions between the two alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Additive manufacturing of ferritic/martensitic steel with improved high temperature strength

Techniques for using additive manufacturing (AM) to fabricate creep resistant ferritic/martensitic steel with improved high temperature strength are described. AM processing may be performed on Grade 91 steel powder. Beam powers from about 221 W to about 270 W may be used. Traverse rates from about 675 mm/s to about 825 mm/s may be used. Heat inputs ranging from about 55.7 J/mm3 to about 83.2 J/mm 3 may be produced. Creep resistant ferritic/martensitic steel, produced according to the present disclosure, has improved strain yield strength and ductility as compared to wrought steel.

Lienert, Thomas J.↗
DOE OSTI2022

Tempering kinetics during multilayer laser additive manufacturing of a ferritic steel

Grade 91 steel forms martensite during additive manufacturing and the extent of tempering of martensite significantly affects the mechanical properties of parts. Currently, there is a lack of quantitative understanding of the tempering kinetics for Grade 91 steel, and as a result, the effects of repeated thermal cycles on properties for different processing conditions cannot be determined. Here we evaluate the tempering kinetics by determining the constant terms in the Johnson Mehl Avrami kinetic equation from the tempering data available in the literature and the thermal cycles computed using a rigorously-tested heat and fluid flow model of multi-layer additive manufacturing. The raw tempering data are cleaned using a neural network to enhance accuracy. The lower layers experience repeating cycles of heating and cooling when the upper layers are added. As a result, the hardness is reduced owing to the tempering of martensite. In contrast, martensite formed in the upper layers is not tempered to the same extent and the hardness remains high. Therefore, the hardness of the part increases with the distance from the substrate. Variations in the heat input at different laser powers and scanning speeds significantly affect the extent of tempering. Finally, since the method used here can provide a quantitative understanding of the tempering of martensite and the spatial variation in hardness, it can be used to tailor the microstructure and hardness of heat treatable printed metallic parts.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High-Throughput Nanoindentation Mapping of Additively Manufactured T91 Steel

Here, this work aims to adapt nanoindentation mapping combined with a k-means algorithm as a high-throughput technique to study the nano-scale spatial changes in mechanical properties for a heterogeneous material. This technique can also classify the individual data points based on their properties. Hundreds to thousands of indents were performed on additively manufactured T91 at room temperature, 300°C, 400°C, and 500°C across a square area with a side length of 120 μm to 400 μm. From this data, the hardness and reduced modulus at each point could be calculated and mapped. Using k-means clustering, we were able to arrange the data into three or four clusters corresponding roughly to the ferritic and martensitic phases as well as one or two intermediate clusters sampling both the phases. The hardness of these two phases appears to be quite stable as a function of temperature. Nanoindentation mapping and the k-means algorithm can therefore be used to rapidly assess the feasibility of heterogeneous materials under extreme conditions, such as nuclear reactor steels.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Solid-State Welding of the Nanostructured Ferritic Alloy 14YWT Using a Capacitive Discharge Resistance Welding Technique

Joining nanostructured ferritic alloys (NFAs) has proved challenging, as the nano-oxides that provide superior strength, creep resistance, and radiation tolerance at high temperatures tend to agglomerate, redistribute, and coarsen during conventional fusion welding. In this study, capacitive discharge resistance welding (CDRW)—a solid-state variant of resistance welding—was used to join end caps and thin-walled cladding tubes of the NFA 14YWT. The resulting solid-state joints were found to be hermetically sealed and were characterized across the weld region using electron microscopy (macroscopic, microscopic, and nanometer scales) and nanoindentation. Microstructural evolution near the weld line was limited to narrow (~50–200 μm) thermo-mechanically affected zones (TMAZs) and to a reduction in pre-existing component textures. Dispersoid populations (i.e., nano-oxides and larger oxide particles) appeared unchanged by all but the highest energy and power CDRW condition, with this extreme producing only minor nano-oxide coarsening (~2 nm → ~5 nm Ø). Despite a minimal microstructural change, the TMAZs were found to be ~10% softer than the surrounding base material. These findings are considered in terms of past solid-state welding (SSW) efforts—cladding applications and NFA-like materials in particular—and in terms of strengthening mechanisms in NFAs and the potential impacts of localized temperature–strain conditions during SSW.

36 MATERIALS SCIENCE↗