Features of arc surfacing of intermetallic alloys of the Fe–Al system on the surface of low-carbon steels
Bibliographic record
Abstract
The durability of industrial components is largely determined by the materials they are made of. Often, the materials used must be resistant to wear, corrosion, and high temperatures. Advanced materials, such as high-strength alloy steels, are expensive and have limited weldability, which complicates the restoration of worn components. Fe–Al alloys having high corrosion resistance, wear resistance, and heat resistance at a lower cost are considered as an alternative. The objective of this study is to increase the wear resistance and heat resistance of low-carbon steel components by studying the processes of arc surfacing of iron aluminides and their properties. The study methodology included single-arc and double-arc surfacing using aluminium and steel electrode wires, analysis of the chemical composition of the deposited coatings, their hardness, wear resistance, and heat resistance. The results showed that single-arc surfacing forms alloys based on FeAl3 and α-Al phases with Fe2Al5 and FeAl3 inclusions, while double-arc surfacing produces alloys more saturated with iron with an α-Fe matrix phase and a Fe3AlCx carbide phase. The resulting alloys demonstrate a hardness of up to 58 HRC, a relative wear resistance of up to 2.5 units, and a weight loss of no more than 5 % with an aluminium content of up to 20 %, which indicates their potential for use under high loading conditions. The results confirm the feasibility of using iron aluminides as an inexpensive alternative to expensive coatings, which expands the possibilities for increasing the wear resistance and heat resistance of components in industry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".