Subtleties Behind Hydrogen Embrittlement of Cadmium-Plated 4340 Steel Revealed by Thermal Desorption Spectroscopy and Sustained-Load Tests

Abstract Steels are the most used structural material in the world, and hydrogen content and localization within the microstructure play an important role in its properties, namely inducing some level of embrittlement. The characterization of the steels susceptibility to hydrogen embrittlement (HE) is a complex task requiring always a broad and multidisciplinary approach. The target of the present work is to introduce the artificial neural network (ANN) computing system to predict the hydrogen-induced mechanical properties degradation using the hydrogen thermal desorption spectroscopy (TDS) data of the studied steel. Hydrogen sensitivity parameter (HSP) calculated from the reduction of elongation to fracture caused by hydrogen was linked to the corresponding hydrogen thermal desorption spectra measured for austenitic, ferritic, and ferritic-martensitic steel grades. Correlation between the TDS input data and HSP output data was studied using two ANN models. A correlation of 98% was obtained between the experimentally measured HSP values and HSP values predicted using the developed densely connected layers ANN model. The performance of the developed ANN models is good even for never-before-seen steels. The ANN-coupled system based on the TDS is a powerful tool in steels characterization especially in the analysis of the steels susceptibility to HE.

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On the Methodology of Thermal Desorption Spectroscopy to Evaluate Hydrogen Embrittlement

Materials Science Forum ◽

10.4028/www.scientific.net/msf.706-709.2354 ◽

2012 ◽

Vol 706-709 ◽

pp. 2354-2359 ◽

Cited By ~ 5

Author(s):

Diana Pérez Escobar ◽

Kim Verbeken ◽

Lode Duprez ◽

Marc Verhaege

Keyword(s):

Hydrogen Embrittlement ◽

Thermal Desorption ◽

Surface Preparation ◽

Thermal Desorption Spectroscopy ◽

Sample Surface ◽

Hydrogen Desorption ◽

Sample Geometry ◽

Metal Interactions ◽

Charging Time ◽

The Impact

Thermal desorption spectroscopy (TDS) is a very important tool in hydrogen embrittlement (HE) related research and has been applied on many different materials over the last decades in order to improve knowledge on the HE phenomenon. TDS provides the opportunity to distinguish between different types of hydrogen traps based on the analysis of a spectrum with different peak temperatures each corresponding to hydrogen desorption from a specific trap. These peak temperatures, and consequently the different traps in a material, arise from the various microstructural characteristics of the material. However, TDS results are also influenced by many other parameters, such as the sample surface preparation, the electrolytes used for hydrogen charging, sample geometry, charging time, current density, charging temperature. Even though the use of thermal desorption to evaluate hydrogen-metal interactions has increased over the past years, a careful evaluation of the effect of these other parameters was not yet performed. In this work, the impact of some of the above mentioned parameters was studied. It was demonstrated that the sample geometry, the surface roughness, and the initial total pressure of the TDS chamber influenced significantly the obtained TDS spectrum.

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Evaluation of Steels Susceptibility to Hydrogen Embrittlement: A Thermal Desorption Spectroscopy-Based Approach Coupled with Artificial Neural Network

Materials ◽

10.3390/ma13235500 ◽

2020 ◽

Vol 13 (23) ◽

pp. 5500

Author(s):

Evgenii Malitckii ◽

Eric Fangnon ◽

Pedro Vilaça

Keyword(s):

Neural Network ◽

Mechanical Properties ◽

Artificial Neural Network ◽

Hydrogen Embrittlement ◽

Thermal Desorption ◽

Network Architecture ◽

Data Augmentation ◽

Thermal Desorption Spectroscopy ◽

Quantitative Prediction ◽

Artificial Neural

A novel approach has been developed for quantitative evaluation of the susceptibility of steels and alloys to hydrogen embrittlement. The approach uses a combination of hydrogen thermal desorption spectroscopy (TDS) analysis with recent advances in machine learning technology to develop a regression artificial neural network (ANN) model predicting hydrogen-induced degradation of mechanical properties of steels. We describe the thermal desorption data processing, artificial neural network architecture development, and the learning process beneficial for the accuracy of the developed artificial neural network model. A data augmentation procedure was proposed to increase the diversity of the input data and improve the generalization of the model. The study of the relationship between thermal desorption spectroscopy data and the mechanical properties of steel evidences a strong correlation of their corresponding parameters. A prototype software application based on the developed model is introduced and is openly available. The developed prototype based on TDS analysis coupled with ANN is shown to be a valuable engineering tool for steel characterization and quantitative prediction of the degradation of steel properties caused by hydrogen.

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Investigation of the Pressure Dependent Hydrogen Solubility in a Martensitic Stainless Steel Using a Thermal Agile Tubular Autoclave and Thermal Desorption Spectroscopy

Metals ◽

10.3390/met11020231 ◽

2021 ◽

Vol 11 (2) ◽

pp. 231

Author(s):

Patrick Fayek ◽

Sebastian Esser ◽

Vanessa Quiroz ◽

Chong Dae Kim

Keyword(s):

Stainless Steel ◽

Thermal Desorption ◽

Hydrogen Diffusion ◽

Martensitic Stainless Steel ◽

Thermal Desorption Spectroscopy ◽

Hydrogen Uptake ◽

Hydrogen Solubility ◽

Automotive Components ◽

Set Up ◽

Service Application

Hydrogen is nowadays in focus as an energy carrier that is locally emission free. Especially in combination with fuel-cells, hydrogen offers the possibility of a CO2 neutral mobility, provided that the hydrogen is produced with renewable energy. Structural parts of automotive components are often made of steel, but unfortunately they may show degradation of the mechanical properties when in contact with hydrogen. Under certain service conditions, hydrogen uptake into the applied material can occur. To ensure a safe operation of automotive components, it is therefore necessary to investigate the time, temperature and pressure dependent hydrogen uptake of certain steels, e.g., to deduct suitable testing concepts that also consider a long term service application. To investigate the material dependent hydrogen uptake, a tubular autoclave was set-up. The underlying paper describes the set-up of this autoclave that can be pressurised up to 20 MPa at room temperature and can be heated up to a temperature of 250 °C, due to an externally applied heating sleeve. The second focus of the paper is the investigation of the pressure dependent hydrogen solubility of the martensitic stainless steel 1.4418. The autoclave offers a very fast insertion and exertion of samples and therefore has significant advantages compared to commonly larger autoclaves. Results of hydrogen charging experiments are presented, that were conducted on the Nickel-martensitic stainless steel 1.4418. Cylindrical samples 3 mm in diameter and 10 mm in length were hydrogen charged within the autoclave and subsequently measured using thermal desorption spectroscopy (TDS). The results show how hydrogen sorption curves can be effectively collected to investigate its dependence on time, temperature and hydrogen pressure, thus enabling, e.g., the deduction of hydrogen diffusion coefficients and hydrogen pre-charging concepts for material testing.

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The Role of Cr in H Desorption Kinetics in Rapidly Solidified Al

Materials Science Forum ◽

10.4028/www.scientific.net/msf.783-786.264 ◽

2014 ◽

Vol 783-786 ◽

pp. 264-269 ◽

Cited By ~ 3

Author(s):

Iya I. Tashlykova-Bushkevich ◽

Keitaro Horikawa ◽

Goroh Itoh

Keyword(s):

High Temperature ◽

Thermal Desorption ◽

High Purity ◽

Thermal Desorption Spectroscopy ◽

Secondary Phase ◽

Hydrogen Desorption ◽

Oxide Surface ◽

Desorption Kinetics ◽

Hydrogen Trapping ◽

Rapidly Solidified

Hydrogen desorption kinetics for rapidly solidified high purity Al and Al-Cr alloy foils containing 1.0, 1.5 and 3.0 at % Cr were investigated by means of thermal desorption analysis (TDA) at a heating rate of 3.3°C/min. For the first time, it was found that oxide inclusions of Al2O3 are dominant high-temperature hydrogen traps compared with pores and secondary phase precipitates resulted in rapid solidification of Al and its alloys. The correspondent high-temperature evolution rate peak was identified to be positioned at 600°C for high purity Al and shifted to 630°C for Al-Cr alloys. Amount of hydrogen trapped by dislocations increases in the alloys depending on Cr content. Microstructural hydrogen trapping behaviour in low-and intermediate temperature regions observed here was in coincidence with previous data obtained for RS materials using thermal desorption spectroscopy (TDS). The present results on hydrogen thermal desorption evolution indicate that the effect of oxide surface layers becomes remarkable in TDA measurements and show advantages in combinations of both desorption analysis methods to investigate hydrogen desorption kinetics in materials.

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