High-Throughput Electrochemistry to Study Materials Degradation in Extreme Environments

被引:5
作者
Wang, Yafei [1 ,2 ]
Goh, Bonita [1 ]
Moorehead, Michael [1 ]
Hattrick-Simpers, Jason [3 ]
Couet, Adrien [1 ]
机构
[1] Univ Wisconsin, Dept Engn Phys, Madison, WI 53715 USA
[2] Shanghai Jiao Tong Univ, Sch Nucl Sci & Engn, Shanghai 200240, Peoples R China
[3] Univ Toronto, Dept Mat Sci & Engn, Toronto, ON M5S 3E4, Canada
关键词
CORROSION; ALLOY; BULK; COMBINATORIAL;
D O I
10.1021/acs.analchem.2c03325
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Electrochemistry has been used for decades to study materials' degradation in situ in corrosive environments, whether it is in room-temperature chemically aggressive solutions containing halide ions or in high-temperature oxidizing media such as pressurized water, liquid metals, or molten salts. Thus, following the recent surge in high-throughput techniques in materials science, it seems quite natural that high-throughput electrochemistry is being considered to study materials' degradation in extreme environments, with the objective to reduce corrosion resistant alloy development time by orders of magnitude and identify complex degradation mechanisms. However, while there has been considerable interest in the development of high- throughput methods for accelerating the discovery of corrosion resistant materials in different environments, these extreme environments propose formidable and exciting challenges for high-throughput electrochemical instrumentation, characterization, and data analysis. It is the objective of this paper to highlight those challenges, to present relatively new efforts to tackle them, and to develop research perspectives on the future of this exciting field. This Perspective is articulated around four main interconnected topics, which must be conjointly considered to enable corrosion resistant alloy design using high-throughput electrochemical methods: (1) high-throughput processing methods to develop material libraries, (2) high-throughput electrochemical methods for corrosion testing and evaluation, (3) high-throughput machine-learning augmented electrochemical data analysis, and (4) high-throughput autonomous electrochemistry representing the future of accelerated electrochemistry research.
引用
收藏
页码:16528 / 16537
页数:10
相关论文
共 70 条
[1]   A High-Throughput Test Methodology for Atmospheric Corrosion Studies [J].
Azmat, N. S. ;
Ralston, K. D. ;
Muster, T. H. ;
Muddle, B. C. ;
Cole, I. S. .
ELECTROCHEMICAL AND SOLID STATE LETTERS, 2011, 14 (06) :C9-C11
[2]   Study of stainless steels corrosion in a strong acid mixture. Part 1: cyclic potentiodynamic polarization curves examined by means of an analytical method [J].
Bellezze, Tiziano ;
Giuliani, Giampaolo ;
Roventi, Gabriella .
CORROSION SCIENCE, 2018, 130 :113-125
[3]   Exploring the use of machine learning for interpreting electrochemical impedance spectroscopy data: evaluation of the training dataset size [J].
Bongiorno, V. ;
Gibbon, S. ;
Michailidou, E. ;
Curioni, M. .
CORROSION SCIENCE, 2022, 198
[4]   Distribution (function) of relaxation times, successor to complex nonlinear least squares analysis of electrochemical impedance spectroscopy? [J].
Boukamp, Bernard A. .
JOURNAL OF PHYSICS-ENERGY, 2020, 2 (04)
[5]   Analysis and Application of Distribution of Relaxation Times in Solid State Ionics [J].
Boukamp, Bernard A. ;
Rolle, Aurelie .
SOLID STATE IONICS, 2017, 302 :12-18
[6]  
Carter G.C., 1978, APPL PHASE DIAGRAMS
[7]   A deep crystal structure identification system for X-ray diffraction patterns [J].
Chakraborty, Abhik ;
Sharma, Raksha .
VISUAL COMPUTER, 2022, 38 (04) :1275-1282
[8]   The high throughput assessment of aluminium alloy corrosion using fluorometric methods. Part II - A combinatorial study of corrosion inhibitors and synergistic combinations [J].
Chambers, B. D. ;
Taylor, S. R. .
CORROSION SCIENCE, 2007, 49 (03) :1597-1609
[9]   Computer vision AC-STEM automated image analysis for 2D nanopore applications [J].
Chen, Joshua ;
Balan, Adrian ;
Das, Paul Masih ;
Thiruraman, Jothi Priyanka ;
Drndic, Marija .
ULTRAMICROSCOPY, 2021, 231
[10]   Integrated high-throughput research in extreme environments targeted toward nuclear structural materials discovery [J].
Couet, Adrien .
JOURNAL OF NUCLEAR MATERIALS, 2022, 559