Search NASA⌕ Search

Engineering topics

Olszta, Matthew

Publications and source records attributed to Olszta, Matthew.

9 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Tribological behavior of hybrid Aluminum-TiB 2 metal matrix composites for brake rotor applications

Here, this research investigates the feasibility of hybrid aluminum metal matrix composites (MMC) incorporating TiB 2 particles for brake rotor applications. The composites were produced by incorporating both in-situ, submicron-sized TiB 2 particles and regular micron-sized TiB 2 powders via stir and squeeze casting techniques into A206 aluminum alloy matrix. Systematic adjustments in the fractions of in-situ and ex-situ TiB 2 particles were conducted to evaluate their impact on wear behavior and mechanisms. Combination of both particle types allowed composites with up to 10 vol% of reinforcements. Composites with higher proportions of ex-situ particles demonstrated increased wear resistance compared to those solely composed of in-situ particles, control specimens without TiB 2 , and conventional cast iron counterparts. The lowest wear rate for the hybrid composites sliding against phenolic brake pads was 1.1 × 10 -5 mm 3 /Nm, signifying a 3-fold reduction relative to cast iron sliding against the same pads. Wear analysis elucidated distinctive mechanisms within the hybrid composites, characterized by mild fragmented abrasive wear, adhesive wear, and plastic deformation, accompanied by the formation of an intermixed tribo-oxide layer.

42 ENGINEERING↗
DOE OSTI2024

Mechanistic understanding of speciated oxide growth in high entropy alloys

Abstract Complex multi-element alloys are gaining prominence for structural applications, supplementing steels, and superalloys. Understanding the impact of each element on alloy surfaces due to oxidation is vital in maintaining material integrity. This study investigates oxidation mechanisms in these alloys using a model five-element equiatomic CoCrFeNiMn alloy, in a controlled oxygen environment. The oxidation-induced surface changes correlate with each element’s interactive tendencies with the environment, guided by thermodynamics. Initial oxidation stages follow atomic size and redox potential, with the latter becoming dominant over time, causing composition inversion. The study employs in-situ atom probe tomography, transmission electron microscopy, and X-ray absorption near-edge structure techniques to elucidate the oxidation process and surface oxide structure evolution. Our findings deconvolute the mechanism for compositional and structural changes in the oxide film and will pave the way for a predictive design of complex alloys with improved resistance to oxidation under extreme conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Directly monitoring the shift in corrosion mechanisms of a model FeCrNi alloy driven by electric potential

Abstract Stainless steels are used in a myriad of engineering applications, including construction, automobiles, and nuclear reactors. Developing accurate, predictive mechanistic models for corrosion and electrochemical corrosion kinetics of stainless steels has been a topic of research studies over many decades. Herein, we quantified the aqueous corrosion kinetics of a model austenitic Fe–18Cr–14Ni (wt%) alloy in the presence and absence of applied potential using systematic in situ electrochemical atomic force microscopy (EC-AFM) and transmission electron microscopy (TEM). Without an applied bias, vertical dissolution of corrosion pits is controlled by the surface kinetics/diffusion hybrid mechanism, whereas lateral dissolution is diffusion controlled. When an electric bias is applied, the increase in corrosion rate is dominated by the nucleation of new pits. These insights gained by the in situ EC-AFM will allow applications of this method for a quantitative understanding of corrosion of a wider class of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Temperature-dependent formation of gradient structures with anomalous hardening in an Al–Si alloy

The temperature effect on forming gradient structure in an Al-Si alloy during surface severe deformation is studied in this report. The intermediate temperature (473 K) produces the steepest gradient structure by an anomalous hardening on the top layer compared to lower (300 K) and higher temperature (673 K) counterparts. Our analysis shows profuse aluminum oxide particles in the top layer of the gradient structure under 473 K and thus lead to anomalous hardening by oxide-dispersion strengthening. Here, the counterintuitive enhancement of strengthening at the intermediate temperature is explained by the dynamic interplay between thermal-driven, mechanical-aided oxidation and the wear-induced loss of surface materials as a function of temperature, which yields a critical processing temperature to achieve the steepest gradient structure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Rapid assessment of interfacial stabilization mechanisms of metastable precipitates to accelerate high-temperature Al-alloy development

Precipitate strengthened high-temperature alloys are currently used in safety-critical applications. Understanding precipitate stability and solute segregation mechanisms at high temperatures is key to designing high-strength alloys. Rapid in-situ approaches, therefore, are pivotal in accelerating the alloy design process. Hereby using the test case of a promising high-temperature Al-Cu-Mn-Zr alloy, we demonstrate the value of in-situ atom probe tomography coupled with in-situ transmission electron microscopy to reveal atomic-scale mechanisms that lead to the emergence of non-equilibrium solute segregation. Mn and Zr segregation at strengthening precipitate(θ’)-matrix interface increases the kinetic barrier for phase transformation thus retaining high-temperature strength.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Shear strain gradient in Cu/Nb nanolaminates: Strain accommodation and chemical mixing

Disentangling the intragranular and interfacial plasticity contribution to the overall strain accommodation is crucial to understanding the microstructural evolution and mass transport upon deformation in materials with the nanoscale feature size. In this study, we devise a new approach to tackle the issue by introducing shear strain gradients into Cu/Nb nanolaminates of different layer thicknesses with the shear perpendicular to the laminate interfaces. The measurement of the strain gradient and the resultant lattice disorientation enables a quantitative understanding of the intragranular and interfacial plasticity contribution. We found that intragranular slip entirely governs the deformation in the 300 nm-layer laminate and, unexpectedly, contributes ~80% of the total plasticity in the 30 nm-layer laminate. The high intragranular plasticity in the thin laminate is attributed to the large width of confined slip planes and their remnant potential for storing dislocations. In addition, substantial forced chemical mixing is observed in the top region of the 30 nm-layer laminate where the effective layer thickness is reduced below 8 nm. The transition of deformation mechanism from confined layer slip to dislocation transmission is largely responsible for the initiation of substantial mixing. Our method and findings shed light on the deformation mechanism and deformation-induced mass transport behavior in nanostructured materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multimodal Analysis of Spatially Heterogeneous Microstructural Refinement and Softening Mechanisms in Three-Pass Friction Stir Processed Al4Si Alloy

Multiple thermally and thermomechanically induced microstructural refinement mechanisms can be activated in metallic alloys when subjected to solid phase processing methods such as friction stir processing (FSP). In this work, we provide detailed descriptions of the relationship between region-specific microstructural refinement mechanisms and the variation in microhardness, through a systematic and multimodal microstructural characterization of an FSP-processed 75% cold-rolled Al-4 at.% Si model binary alloy. Spatially resolved high-energy synchrotron X-ray diffraction, electron backscattered diffraction, and scanning transmission electron microscopy were used to understand the spatially heterogeneous microstructural evolution due to FSP. Results provide insights into how mechanisms such as static recovery, static recrystallization, dynamic recovery and recrystallization, geometric and continuous dynamic recrystallization, and particle-stimulated static or dynamic grain nucleation may occur heterogeneously in the microstructure as a function of the distance from the stir zone in processed alloys, directly influencing the degree of softening. The systematic analysis of microstructures and hardness in the FSP-processed model binary alloy given in this work highlights the rich microstructural domains that can be uniquely harnessed through solid phase processing of metallic alloys.

Al4Si, Friction Stir Processing, Geometric Dynamic↗
DOE OSTI2021

Rapid and flexible segmentation of electron microscopy data using few-shot machine learning

Abstract Automatic segmentation of key microstructural features in atomic-scale electron microscope images is critical to improved understanding of structure–property relationships in many important materials and chemical systems. However, the present paradigm involves time-intensive manual analysis that is inherently biased, error-prone, and unable to accommodate the large volumes of data produced by modern instrumentation. While more automated approaches have been proposed, many are not robust to a high variety of data, and do not generalize well to diverse microstructural features and material systems. Here, we present a flexible, semi-supervised few-shot machine learning approach for segmentation of scanning transmission electron microscopy images of three oxide material systems: (1) epitaxial heterostructures of SrTiO 3 /Ge, (2) La 0.8 Sr 0.2 FeO 3 thin films, and (3) MoO 3 nanoparticles. We demonstrate that the few-shot learning method is more robust against noise, more reconfigurable, and requires less data than conventional image analysis methods. This approach can enable rapid image classification and microstructural feature mapping needed for emerging high-throughput characterization and autonomous microscope platforms.

36 MATERIALS SCIENCE↗