Tuning the microstructure and mechanical properties of magnetron sputtered Cu-Cr thin films: The optimal Cr addition
Source abstract
Abstract
Abstract Grain boundary (GB) engineering via alloying opens a pathway to design the interfaces in alloys for tuning their mechanical properties, thus it is quite critical to determine the optimum addition of alloying element. Here, we prepared immiscible Cu-Cr alloyed thin films by non-equilibrium magnetron sputtering deposition to study Cr alloying effects on the microstructure and mechanical properties of Cu thin films. It is found that Cr doping can notably refine the grains and promote the formation of fully nanotwinned columnar grains at low Cr volume concentrations (≤∼3.7 at.%) associated with the average GB Cr concentrations ≤ ∼15 at.%, beyond which the formation of nanotwins is significantly suppressed. The role of Cr atoms/clusters played in the twinning process is rationalized in terms of dislocation rebound-promotion mechanism. Importantly, a maximum hardness is discovered at the optimum Cr addition of ∼2.0 at.%. The Cr concentration-dependent hardness of Cu-Cr alloyed films was quantified by a combined strengthening model. The achievement of the maximum hardness was related to the greatest GB solute segregation-induced strength contribution. It is further uncovered that the Cu-Cr system exhibits strain rate sensitivity (SRS, m) monotonically reduced with increasing the Cr concentration, ranging from a positive m of 0.0314 (for pure Cu) to a negative m of −0.0245, which is attributed to a competition between the dislocation-boundary interactions (increasing m) and the dislocation-solute atoms interactions (decreasing m). These findings provide valuable insights into tuning the composition of alloyed thin films to achieve optimized mechanical performance.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Microstructure and mechanical properties · Aluminum Alloys Composites Properties · Metal and Thin Film Mechanics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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