Optimal Design of High-Strength Ti‒Al‒V‒Zr Alloys through a Combinatorial Approach

Wu, Di; Tian, Yueyan; Zhang, Ligang; Wang, Zhengyu; Sheng, Jinwen; Wang, Wanlin; Zhou, Kechao; Liu, Libin

doi:10.3390/ma11091603

Cited by 6 publications

(3 citation statements)

References 43 publications

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“…The differences in the surface roughness values between different materials might be explained by differences in stiffness and hardness of the materials [ 25 , 26 , 27 ]. Ti and CoCr showed the highest surface roughness values and also deeper scratches on the surface after the curette and ultrasonic scaling.…”

Section: Discussionmentioning

confidence: 99%

Surface Roughness and Streptococcus mutans Adhesion on Metallic and Ceramic Fixed Prosthodontic Materials after Scaling

et al. 2021

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The aim of this study was to evaluate the surface roughness of fixed prosthodontic materials after polishing or roughening with a stainless steel curette or ultrasonic scaler and to examine the effect of these on Streptococcus mutans adhesion and biofilm accumulation. Thirty specimens (10 × 10 × 3 mm3) of zirconia (Zr), pressed lithium disilicate (LDS-Press), milled lithium disilicate glazed (LDS-Glaze), titanium grade V (Ti) and cobalt-chromium (CoCr) were divided into three groups (n = 10) according to surface treatment: polished (C), roughened with stainless steel curette (SC), roughened with ultrasonic scaler (US). Surface roughness values (Sa, Sq) were measured with a spinning disc confocal microscope, and contact angles and surface free energy (SFE) were measured with a contact angle meter. The specimens were covered with sterilized human saliva and immersed into Streptococcus mutans suspensions for bacterial adhesion. The biofilm was allowed to form for 24 h. Sa values were in the range of 0.008−0.139 µm depending on the material and surface treatment. Curette and ultrasonic scaling increased the surface roughness in LDS-Glaze (p < 0.05), Ti (p < 0.01) and CoCr (p < 0.001), however, surface roughness did not affect bacterial adhesion. Zr C and US had a higher bacterial adhesion percentage compared to LDS-Glaze C and US (p = 0.03). There were no differences between study materials in terms of biofilm accumulation.

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Section: Discussionmentioning

confidence: 99%

Surface Roughness and Streptococcus mutans Adhesion on Metallic and Ceramic Fixed Prosthodontic Materials after Scaling

et al. 2021

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“…Finally, CALPHAD methods are both computationally efficient and have sufficiently large databases to produce accurate predictions for many HEA compositions [147,148] . In fact, CALPHAD methods are able to screen more compositions than any of the other computational methods (up to 10 6 compositions) in a reasonable time span [135] .…”

Section: Comparison Of Computational Methodsmentioning

confidence: 99%

A review on high-throughput development of high-entropy alloys by combinatorial methods

Mooraj¹,

Chen²

2023

J Mater Inf

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High-entropy alloys (HEAs) are an emerging class of alloys with multi-principal elements that greatly expands the compositional space for advanced alloy design. Besides chemistry, processing history can also affect the phase and microstructure formation in HEAs. The number of possible alloy compositions and processing paths gives rise to enormous material design space, which makes it challenging to explore by traditional trial-and-error approaches. This review highlights the progress in combinatorial high-throughput studies towards rapid prediction, manufacturing, and characterization of promising HEA compositions. This review begins with an introduction to HEAs and their unique properties. Then, this review describes high-throughput computational methods such as machine learning that can predict desired alloy compositions from hundreds or even thousands of candidates. The next section of this review presents advances in combinatorial synthesis of material libraries by additive manufacturing for efficient development of high-performance HEAs at bulk scale. The final section of this review discusses the high-throughput characterization techniques that are used to accelerate the material property measurements for systematic understanding of the composition-processing-structure-property relationships in combinatorial HEA libraries.

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“…Database mining was first introduced in materials science to predict stable compositions, or estimate material properties from composition. Database mining has been successfully implemented to predict stable crystal structures [209][210][211] and predict material properties as a function of composition [212][213][214][215][216]. Some specially designed search algorithms have also been designed for improved speed in automated searches [217].…”

Section: A151 Alloy Design and Feedstock Selectionmentioning

confidence: 99%

In Situ High Energy X-ray Diffraction Characterization of Phase Transformations and Mechanical Behaviors in Rapidly Solidified Titanium and Stainless Steel Alloys [Thesis]

Johnson

2021

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Advanced manufacturing techniques like additive manufacturing (AM) have poised themselves to revolutionize metal manufacturing. A wide range of AM techniques are capable of manufacturing metal components with unique, complex geometries and hastening the scientific-engineering-development cycle. Metal AM relies on a layer-by-layer rapid manufacturing process to build components from the substrate up. Rapid solidification is a large departure from traditional metal manufacturing due to its complex physics. Characterization of rapid solidification is difficult, stemming from the small volumes used in AM and the fast dynamics of the process. High energy X-ray diffraction (HEXRD) is a solution to the characterization problems of rapidly solidified alloys and AM. HEXRD can probe small volumes at fast rates and provides a wide range of thermomechanical and kinetic information.This thesis presents the application of HEXRD to rapidly solidified titanium and stainless steel alloys through a series of case studies. In the first two studies, HEXRD is applied to rapidly solidified titanium and stainless steel welds. The materials are characterized for their temperature history, phase changes, kinetics, and microstructural evolution. In the next case study, HEXRD is applied to characterize phase changes in elastocaloric NiTi shape memory alloys (SMAs) under thermomechanical load. HEXRD, in conjunction with other tools, is used to explain the superior performance of the additively manufactured SMAs. In the final two case studies, HEXRD is used to measure the mechanical response of AM parts with complex geometries; namely, the octet truss lattice. Diffraction reveals a wide range of materials information about the AM microstructure including unexpected phases, texture, and mechanical response to loading. The mechanical results from HEXRD and then compared with theoretical predictions about the performance of octet truss lattices. Summarily, HEXRD is a diverse tool that is poised to address the complex characterization problems of many aspects of the additive manufacturing process.

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Optimal Design of High-Strength Ti‒Al‒V‒Zr Alloys through a Combinatorial Approach

Cited by 6 publications

References 43 publications

Surface Roughness and Streptococcus mutans Adhesion on Metallic and Ceramic Fixed Prosthodontic Materials after Scaling

Surface Roughness and Streptococcus mutans Adhesion on Metallic and Ceramic Fixed Prosthodontic Materials after Scaling

A review on high-throughput development of high-entropy alloys by combinatorial methods

In Situ High Energy X-ray Diffraction Characterization of Phase Transformations and Mechanical Behaviors in Rapidly Solidified Titanium and Stainless Steel Alloys [Thesis]

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