Thermodynamic and kinetic analyses of high temperature oxidation of 316L stainless steel
Bibliographic record
Abstract
This study investigates the thermodynamic behavior and non-isothermal oxidation kinetics of 316L stainless steel in the temperature range of 1100 K - 1373 K, with relevance to the heat-affected zone during welding in oil and gas pipeline applications. Thermogravimetric analysis was performed at heating rates of 5, 10, 15, 20, and 25 K/min study the high-temperature oxidation kinetics of AISI 316L stainless steel welds. Kinetic analysis was conducted using Kennedy-Clark and Coats-Redfern methods as well as Friedman, Starink, Kissinger-Akahira-Sunose, and Flynn-Wall-Ozawa model-free isoconversional methods. Activation energies determined using isoconversional models ranged from 224.79 to 233.81 kJ/mol. The second-order (F2) and third-order (F3) reaction models provided the best fit to the experimental data, as confirmed by Criado master plot analysis. Thermodynamic properties (ΔH ≠ . , ΔS ≠ . , ΔG ≠ ) were also calculated for isocoversional models. FactSage thermochemical simulations revealed the formation of a dual-layer protective oxide scale primarily composed of spinel and corundum phases. These oxide layers enhance oxidation resistance at high temperatures. The findings contribute to a mechanistic and kinetic understanding of high-temperature oxidation in 316L stainless steel, supporting its reliable application in demanding oil and gas environments. • Kinetic analysis of 316LSS oxidation using isoconversional and model-fitting methods. • Identification of solid-state reaction mechanisms through Criado master plot analysis. • Thermochemical validation of oxidation products using FactSage simulations • Integrating multiple kinetic approaches to enhance the accuracy of E a determination.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".