Preparation of Fe–As alloys by mechanical alloying and vacuum hot‐pressed sintering: microstructure evolution, mechanical properties, and mechanisms
Bibliographic record
Abstract
Abstract Arsenic materials have attracted great attention due to their unique properties. However, research concerning iron–arsenic (Fe–As) alloys is very scarce due to the volatility of As at low temperature and the high melting point of Fe. Herein, a new Fe–As alloy was obtained by mechanical alloying (MA) followed by vacuum hot‐pressed sintering (VHPS). Moreover, a systematic study was carried out on the microstructural evolution, phase composition, leaching toxicity of As, and physical and mechanical properties of Fe–As alloys with varying weight fractions of As (20%, 25%, 30%, 35%, 45%, 55%, 65%, and 75%). The results showed that pre‐alloyed metallic powders (PAMPs) have a fine grain size and specific super‐saturated solid solution after MA, which could effectively improve the mechanical properties of Fe–As alloys by VHPS. A high density (> 7.350 g·cm −3 ), low toxicity, and excellent mechanical properties could be obtained for Fe–As alloys sintered via VHPS by adding an appropriate amount of As, which is more valuable than commercial Fe–As products. The Fe‐25% As alloy with low toxicity and a relatively high density (7.635 g·cm −3 ) provides an ultra‐high compressive strength (1989.19 MPa), while the Fe‐65% As alloy owns the maximum Vickers hardness (HV 0.5 899.41). After leaching by the toxicity characteristic leaching procedure (TCLP), these alloys could still maintain good mechanical performance, and the strengthening mechanisms of Fe–As alloys before and after leaching were clarified. Changes in the grain size, microstructure, and phase distribution induced significant differences in the compressive strength and hardness.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".