Kinetics and evolution of solid-state metal dealloying in thin films with multimodal analysis

Zhao, Chonghang; Yu, Lin-Chieh; Kisslinger, Kim; Clark, Charles; Chung, Cheng-Chu; Li, Ruipeng; Fukuto, Masafumi; Lu, Ming; Bai, Jianming; Liu, Xiaoyang; Zhong, Hui; Liu, Mingzhao; Ghose, Sanjit; Chen‐Wiegart, Yu‐chen Karen

doi:10.1016/j.actamat.2022.118433

Cited by 6 publications

(3 citation statements)

References 73 publications

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“…The dealloying process to create nanoarchitectured materials, including nanoporous materials and nanocomposites, has gained significant attention due to their various benefits, such as mechanical strength, lightweight, high surface‐area‐to‐volume ratio, thermal, and electrical conductivities. These materials thus have found applications in nanotechnology for energy conversion, [ 1–6 ] mechanical engineering, [ 7–9 ] medicine, [ 10–12 ] and sensors, [ 13–18 ] Among different types of the dealloying processes in solid, [ 19–23 ] liquid, [ 7,24,25 ] and gas [ 26,27 ] media, the solid‐state metal dealloying (SSMD) process, previously termed solid‐state interfacial dealloying (SSID), [ 21–23 ] has emerged as a promising method for fabricating nanoarchitectured composites. In SSMD, a solid‐state metallic solvent, referred to as the dealloying agent (element C), is used to induce a phase separation in a parent alloy (alloy AB) into A and B‐C components.…”

Section: Introductionmentioning

confidence: 99%

Oxidation Driven Thin‐Film Solid‐State Metal Dealloying Forming Bicontinuous Nanostructures

Chung,

Clark,

Zhao

et al. 2023

Adv Materials Inter

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Solid‐state metal dealloying (SSMD) is a promising method for fabricating nanoscale metallic composites and nanoporous metals across a range of materials. Thin‐film SSMD is particularly attractive due to its ability to create fine features via solid‐state interfacial reactions within a thin‐film geometry, which can be integrated into devices for various applications. This work examines a new dealloying couple, namely the Nb–Al alloy with the dealloying agent Sc, as previously predicted in the machine‐learning (ML) models. Prior ML predictions aimed to guide the design of nanoarchitectured materials through dealloying, relying on intuition‐driven discovery within a large parameter space. However, this work reveals that at the nanoscale, the involvement of oxygen in thin film processing may instead drive the dealloying process, resulting in the formation of bicontinuous nanostructures similar to those formed by metal‐agent dealloying. The phase evolution, as well as chemical and morphological changes, are closely analyzed using a combination of X‐ray absorption spectroscopy, diffraction, and scanning transmission electron microscopy to understand the mechanisms behind nanostructure formation. The findings suggest a potential pathway for utilizing oxygen to drive the formation of bicontinuous metal–metal oxide nanocomposites, paving the way for further development of functional nanoporous materials in diverse fields.

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Section: Introductionmentioning

confidence: 99%

Oxidation Driven Thin‐Film Solid‐State Metal Dealloying Forming Bicontinuous Nanostructures

Chung,

Clark,

Zhao

et al. 2023

Adv Materials Inter

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“…More specifically, the technique of chemical/electrochemical dealloying can be efficiently applied only for fabrication of nanoporous noble metals, while the approach of liquid metal dealloying inherently requires a proper liquid metal to act as the etchant, as well as high temperature experimental conditions. Furthermore, as indicated by Kosmidou et al [30] and Zhao et al [31], neither technique is ideal for preparing nanoporous refractory metals, as any oxidation that occurs during the dealloying process is undesired.…”

Section: Introductionmentioning

confidence: 99%

Synthesizing Nanoporous Stainless Steel Films via Vacuum Thermal Dealloying

Liu

Zhang

Kosmidou

et al. 2023

Metals

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Vacuum thermal dealloying is a recently developed technique and was newly introduced to produce nanoporous metals, due to its intriguing advantages, i.e., preventing oxidation and producing no chemical waste, etc. Here, we report on the fabrication of nanoporous stainless steel films by vacuum thermal dealloying of sputtered stainless steel–magnesium precursor films. It was found that crack-free nanoporous stainless steel films can be successfully attained under a broad temperature range of 450–600 °C, with a dealloying time of 0.5–2 h. The resulting structure and ligaments were temperature- and time-dependent, and moreover, the condition of “600 °C + 2 h” generated the most homogeneous structure. Moreover, small amounts of residual Mg were found at pore sites in the resultant structures, suggesting that the dealloying was not fully complete.

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“…Recently, liquid metal dealloying (LMD), where liquid metal is used as the dealloying agent (metal C), was reintroduced to fabricate less noble nanoporous materials 5 , including stainless steel 6,7 , silicon 8,9 , magnesium 10 , graphite 11 , αtitanium 5,12 , β-titanium 13 , and TiVNbMoTa high entropy alloys 14 . Solid-state metal dealloying (SSMD), or solid-state interfacial dealloying (SSID), has been introduced to fabricate nanoporous Fe, Fe-Cr, and α-Ti with a finer ligament, which can be used to overcome the limitation of high fabrication temperatures and handle liquid metal difficulties in LMD [15][16][17][18] . However, the fundamental mechanisms leading to metal-agent dealloying remain unclear, thereby creating challenges in defining a strategy for materials design using metal-agent dealloying.…”

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confidence: 99%

Machine-learning for designing nanoarchitectured materials by dealloying

et al. 2022

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Machine learning-augmented materials design is an emerging method for rapidly developing new materials. It is especially useful for designing new nanoarchitectured materials, whose design parameter space is often large and complex. Metal-agent dealloying, a materials design method for fabricating nanoporous or nanocomposite from a wide range of elements, has attracted significant interest. Here, a machine learning approach is introduced to explore metal-agent dealloying, leading to the prediction of 132 plausible ternary dealloying systems. A machine learning-augmented framework is tested, including predicting dealloying systems and characterizing combinatorial thin films via automated and autonomous machine learning-driven synchrotron techniques. This work demonstrates the potential to utilize machine learning-augmented methods for creating nanoarchitectured thin films.

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Kinetics and evolution of solid-state metal dealloying in thin films with multimodal analysis

Cited by 6 publications

References 73 publications

Oxidation Driven Thin‐Film Solid‐State Metal Dealloying Forming Bicontinuous Nanostructures

Oxidation Driven Thin‐Film Solid‐State Metal Dealloying Forming Bicontinuous Nanostructures

Synthesizing Nanoporous Stainless Steel Films via Vacuum Thermal Dealloying

Machine-learning for designing nanoarchitectured materials by dealloying

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