(Corrosion Division Morris Cohen Graduate Student Award) Local Hydrogen Detection Techniques for Atmospheric Uptake in Ultra-High Strength Steels
Bibliographic record
Abstract
Hydrogen embrittlement (HE) is a concern specifically in ultra-high strength steels (UHSS) prevalent in key structural and vehicle components. In full immersion environments, hydrogen production and uptake in high strength materials has been well documented, such as in the case of cathodic protection. However, for atmospheric exposures, there is a large lack of information regarding hydrogen production and uptake. Under atmospheric conditions, acidic pits can form in UHSS due to the breakdown of the passive film, metal dissolution, hydrolysis, and acidification which are prone to local H production and uptake. An understanding of the effects of marine aerosols, industrial pollutants, and other environmental factors, such as UV and relative humidity, on hydrogen production and uptake in UHSS is necessary to develop new alloys with improved corrosion resistance as well as to anticipate and manage the effects of environment severity on embrittlement susceptibility of currently employed UHSS. However, at present, the majority of available techniques for the measurement of hydrogen dissolved in metals and effective hydrogen diffusivity (DH,eff) lack spatial resolution at the micrometer scale. This is not only of significance for atmospheric exposures, with localized H uptake occurring at pits and/or within droplets, but is also of great importance since the hydrogen-metal interactions and processes occurring at the micrometer to nanometer length scales govern hydrogen embrittlement (HE). This presentation discusses and demonstrates select novel local hydrogen probes; the Scanning Kelvin Probe (SKP) and the Scanning Electrochemical Microscope (SECM). The detection of the spatial distribution of diffusible H concentrations was demonstrated on pre-exposed metallic surfaces with the SKP and SECM. SKP and SECM scans of H uptake in samples from controlled atmospheric pre-exposures are also presented. The application of these techniques is shown to provide local and spatial information on H concentrations produced through atmospheric corrosion. An understanding of the H severity at this local scale can provide significant information on severity of atmospheric exposure environments in terms of H production, uptake, and transport. Furthermore these techniques are adaptable to even higher resolution measurements with the application of the SKP atomic force microscope (SKPFM) or SECM-AFM. Acknowledgement: Research was sponsored by the US Air Force Academy under agreement number FA7000-13-2-0020 and ONR under PROJ0007990. The authors would like to acknowledge the Army Research Laboratories, as well as Monash University, in particular Dr. Sebastian Thomas and Prof. Nick Birbilis. The research was partially supported by a 2014 Australia Endeavour Award Research Fellowship with support from Dr. Kishore Venkatesan and Dr. Ivan Cole at CSIRO.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.209 | 0.113 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".