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Kesler, Michael S.

Publications and source records attributed to Kesler, Michael S..

11 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Corrosion Behavior of a Reactive Bond Between Stainless Steel and a Cast AlCeMg Alloy

Corrosion is a longstanding issue for metal components, especially those used in heat exchanger applications. Al–Ce–Mg alloys may provide a potential solution to this problem due to their good mechanical properties and potential reaction bonding with other metals. The reaction bonding involves a “reactive” bond that occurs upon casting of Al–Ce–Mg alloy over stainless steel (SS). Here this study examined the corrosion response of Al–2Ce–6Mg (atomic percent)/(SS) reactive bond interfaces after samples were completely submerged in nitric, sulfuric, formic, and mixed acids for 267 h. Scanning electron microscopy revealed that in the as-cut condition, reactive bond formations were seen frequently throughout the length of the casting and maintained a secure bond between the alloy and the SS tubes. Furthermore, the nitric, sulfuric, and the mixed acids did not have a deleterious effect on the reactive bond structure. However, formic acid did produce changes in both the microstructural appearance and the elemental profile across the bond due to the formation of corrosion reaction products on the acid-exposed surface.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Magnetic nanoparticle‐induced sorbent regeneration for direct air capture

Direct air capture (DAC) is a promising technology for decarbonization through the removal of CO 2 from the atmosphere. In many DAC processes, the regeneration energy used to restore the capture capacity of sorbents accounts for a significant fraction of the energy required by the whole process. Here we report an effective and scalable sorbent regeneration method for liquid DAC solvents based on magnetic nanoparticles (MNPs) heating with AC magnetic fields. MNPs can be directly heated to provide uniform and rapid volumetric heating, as we demonstrate by promoting the release of captured CO 2 from an aqueous solution of potassium sarcosinate. Our results showed that 90% of the solvent can be regenerated within 7.5 min of heating through proposed technique. The MNPs and solvent are found to be stable during the regeneration process and the MNPs showed long-term stability in the CO 2 -saturated solvent. Cyclic experiments showed that the nanoparticles can be reused for multiple cycles without performance deterioration. The process is operated in a noncontact mode through electromagnetic waves, making it an adoptable approach for existing carbon capture systems. The MNPs heating provides an effective regeneration strategy for liquid solvents used in carbon capture processes, in particular for DAC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The evolution of grain boundary energy in textured and untextured Ca–doped alumina during grain growth

The role of anisotropic grain boundary energy in grain growth is investigated using textured microstructures that contain a high proportion of special grain boundaries. Textured and untextured Ca–doped alumina was prepared by slip casting inside and outside a high magnetic field, respectively. At 1600°C, the textured microstructure exhibits faster growth than the untextured microstructure and its population of low–angle boundaries increases. Atomic force microscopy (AFM) is employed to measure the geometry of thermal grooves to assess the relative grain boundary energy of these systems before and after growth. In the textured microstructure, the grain boundary energy distribution narrows and shifts to a lower average energy. Conversely, the energy distribution broadens for the untextured microstructure as it grows and exhibits abnormal grain growth. Further analysis of the boundary networks neighboring abnormal grains reveals an energy incentive that facilitates their growth. These results suggest that coarsening is not the only dominant grain growth mechanism and that the system can lower its energy effectively by replacing high energy boundaries with those of low energy. The faster growth of lower energy boundaries suggests that isotropic simulations do not adequately account for anisotropic grain growth mechanisms or anisotropic mobility.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rare Earth Element—Aluminum Alloys

An alloy includes aluminum, a rare earth element, and an alloying element selected from the following: Si, Cu, Mg, Fe, Ti, Zn, Zr, Mn, Ni, Sr, B, Ca, and a combination thereof. The aluminum (Al), the rare earth element (RE), and the alloying element are characterized by forming at least one form of an intermetallic compound. An amount of the rare earth element in the alloy is in a range of about 1 wt. % to about 12 wt. %, and an amount of the alloying element in the alloy is greater than an amount of the alloying element present in the intermetallic compound.

Moore, Emily E.↗
DOE OSTI2023

Aluminum-fiber composites containing intermetallic phase at the matrix-fiber interface

A solid aluminum-fiber composite comprising: (i) an aluminum-containing matrix comprising elemental aluminum; (ii) coated or uncoated fibers embedded within said aluminum-containing matrix, wherein said fibers have a different composition than said aluminum-containing matrix and impart additional strength to said aluminum-containing matrix as compared to said aluminum-containing matrix in the absence of said fibers embedded therein; and (iii) an intermetallic layer present as an interface between each of said fibers and the aluminum-containing matrix, wherein said intermetallic layer has a composition different from said aluminum-containing matrix and said fibers, and said intermetallic layer contains at least one element that is also present in the aluminum-containing matrix and at least one element present in the fibers, whether from the coated or interior portion of the fibers. Methods of producing the above-described composite are also described.

Rios, Orlando↗
DOE OSTI2023

Aluminum-cerium-manganese alloy embodiments for metal additive manufacturing

Disclosed herein are embodiments of an Al—Ce—Mn alloy for use in additive manufacturing. The disclosed alloy embodiments provide fabricated objects, such as bulk components, comprising a heterogeneous microstructure and having good mechanical properties even when exposed to conditions used during the additive manufacturing process. Methods for making and using alloy embodiments also are disclosed herein.

Allard, Lawrence F.↗
DOE OSTI2023

Investigating the failure behavior of cast Al-11Ce-0.4Mg alloys using in-situ scanning electron microscopy tensile testing

Within the last decade, research on Al-Ce-Mg alloys has reported promising results for use in cast part applications. In this paper, the failure behavior of cast Al-11Ce-0.4Mg (wt%) was investigated experimentally with focus on the effect the matrix and intermetallic phases have on the fracture propagation behavior at failure. For the first time, in-situ SEM tensile testing was used to study the failure behavior of cast Al-Ce alloys, reporting results for uniaxial, DIC, and single edge notch tensile tests. The results of the in-situ SEM tensile testing were compared with the materials characterization experiments, which included serial sectioning, EBSD, EDS, and fractography. Analysis of EBSD and EDS mapping of cast Al-11Ce-0.4Mg showed that the cast microstructure was a hypereutectic two phase Al-Ce alloy with grains encompassing large complex colonies of laminar eutectic Al 11 Ce 3 intermetallic. The uniaxial tensile results reported the effect casting defects have on the strength and ductility of the alloy, and DIC in-situ testing showed that the eutectic colonies plastically deform less than the matrix phase. In-situ SEM single edge notch tensile testing displayed how the strength of an individual phase affected the crack propagation direction in the alloy. The results of both the materials characterization and in-situ tensile testing experiments on the failure of this alloy revealed further directions for future alloy development that can improve both the strength and fracture toughness of Al-Ce-Mg alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Reactive matrix infiltration of powder preforms

A reactive matrix infiltration process is described herein, which includes contacting a surface of a preform comprising reinforcement material particles with a molten infiltrant comprising a matrix material, the matrix material comprising an Al—Ce alloy, whereby the infiltrant at least partially fills spaces between the reinforcement material particles by capillary action and reacts with the reinforcement material particles to form a composite material form, the composite material comprising the matrix material, at least one intermetallic phase, and, optionally, reinforcement material particles. A composite material form also is described, which includes a plurality of reinforcement material particles comprising a metal alloy or a ceramic, a matrix material at least partially filling spaces between the reinforcement material particles; and at least one intermetallic phase surrounding at least some of the reinforcement material particles. The reinforcement material particles and intermetallic phase together may form a gradient core-shell structure.

Rios, Orlando↗
DOE OSTI2023

Automated, high-accuracy classification of textured microstructures using a convolutional neural network

Crystallographic texture is an important descriptor of material properties but requires time-intensive electron backscatter diffraction (EBSD) for identifying grain orientations. While some metrics such as grain size or grain aspect ratio can distinguish textured microstructures from untextured microstructures after significant grain growth, such morphological differences are not always visually observable. This paper explores the use of deep learning to classify experimentally measured textured microstructures without knowledge of crystallographic orientation. A deep convolutional neural network is used to extract high-order morphological features from binary images to distinguish textured microstructures from untextured microstructures. The convolutional neural network results are compared with a statistical Kolmogorov–Smirnov tests with traditional morphological metrics for describing microstructures. Results show that the convolutional neural network achieves a significantly improved classification accuracy, particularly at early stages of grain growth, highlighting the capability of deep learning to identify the subtle morphological patterns resulting from texture. The results demonstrate the potential of a convolutional neural network as a tool for reliable and automated microstructure classification with minimal preprocessing.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Structural direct-write additive manufacturing of molten metals

An alloy for structural direct-writing additive manufacturing comprising a base element selected from the group consisting of aluminum (Al), nickel (Ni) and a combination thereof, and a rare earth element selected from the group consisting of cerium (Ce), lanthanide (La) and a combination thereof, and a eutectic intermetallic present in said alloy in an amount ranging from about 0.5 wt. % to 7.5 wt. %. The invention is also directed to a method of structural direct-write additive manufacturing using the above-described alloy, as well as 3D objects produced by the method. The invention is also directed to methods of producing the above-described alloy.

Rios, Orlando↗