arXiv subjects

Peter Liaw

Publications and source records attributed to Peter Liaw.

3 recordsLinked to original sources

arXiv2024

Fatigue Behavior of High-Entropy Alloys

High-entropy alloys (HEAs) refer to alloys composed of five or more elements in equal or near-equal amounts or in an atomic concentration range of 5 to 35 atomic percent (at%). Different elemental ratios will affect the microstructures of HEAs and provide them with unique properties. Based on past research, HEAs have exhibited superior performance, relative to most conventional alloys, with respect to many properties, such as strength, toughness, corrosion resistance, magnetic behavior, etc. Among them, fatigue behavior has been a topic of focus, due to its importance in industrial applications. In this article, we summarized the research progress in the HEA-fatigue behavior in the past ten years, including experimental results and theoretical studies in subdivisions, such as high-cycle fatigue, low-cycle fatigue, fatigue-crack growth, fatigue mechanisms, etc. The influence of the processing and test methods on HEAs is described. The accuracy of several commonly used prediction models is also outlined. Finally, unresolved issues and suggestions on the direction of future research efforts are presented.

cond-mat.mtrl-sci↗

arXiv2023

Construction of Multi-Dimensional Functions for Optimization of Additive-Manufacturing Process Parameters

The authors present a generic framework for the parameter optimization of additive manufacturing (AM) processes, one tailored to a high-throughput experimental methodology (HTEM). Given the large number of parameters, which impact the quality of AM-metallic components, the authors advocate for partitioning the AM parameter set into stages (tiers), based on their relative importance, modeling one tier at a time until successful, and then systematically expanding the framework. The authors demonstrate how the construction of multi-dimensional functions, based on neural networks (NN), can be applied to successfully model relative densities and Rockwell hardness obtained from HTEM testing of the Inconel 718 superalloy fabricated, using a powder-bed approach. The authors analyze the input data set, assess its suitability for predictions, and show how to optimize the framework for the multi-dimensional functional construction, such as to obtain the highest degree of fit with the input data set. The authors also compare and contrast the NN-based multi-dimensional functional construction to multi-variate linear regression, to polynomial regression, and to Gaussian process regression (GPR), highlight similarity between the NN-based multi-dimensional functional construction and the GPR, and offer insights into the suitability of each of these methods for the data set and the application at hand. In terms of the coefficient of determination, $R^2$, a relatively simple, single-layer NN with 5 or 10 nodes outperforms multi-variate linear regression, 2nd-order polynomial regression, and GPR for the primary Inconel 718 HTEM data set studied. The novelty of the research work entails the versatile and scalable NN framework presented, suitable for use in conjunction with HTEM, for the AM parameter optimization of superalloys, and beyond.

cond-mat.mtrl-sci↗

arXiv2020

Edge Dislocations Can Control Yield Strength in Refractory Body-Centered-Cubic High Entropy Alloys

Energy efficiency is motivating the search for new high-temperature metals. Some new body-centered-cubic random multicomponent "high entropy alloys (HEAs)" based on refractory elements (Cr-Mo-Nb-Ta-V-W-Hf-Ti-Zr) possess exceptional strengths at high temperatures but the physical origins of this outstanding behavior are not known. Here we show, using integrated neutron-diffraction (ND), high-resolution transmission electron microscopy (HRTEM), and theory, that the high strength and strength retention of a NbTaVTi alloy and a new high-strength/low-density CrMoNbV alloy are attributable to edge dislocations. This is surprising because plastic-flow in BCC elemental metals and dilute alloys is universally accepted to be controlled by screw dislocations. We use the insight and theory to perform a computationally-guided search over $10^7$ BCC HEAs and identify over $10^6$ possible ultra-strong high-temperature alloy compositions for future exploration.

cond-mat.mtrl-sci↗