Revealing the Formation, Growth, Prevalence and Impact of Metal Whiskers
A special issue of Metals (ISSN 2075-4701). This special issue belongs to the section "Structural Integrity of Metals".
Deadline for manuscript submissions: closed (30 August 2023) | Viewed by 316
Special Issue Editors
Interests: finite element method; laser-material interaction; data-driven materials science; artificial neural network; Pb-free solder alloys; intermetallic compounds; multi-principal element alloys; dynamics at materials interface; multiphysics simulation; heat transfer; transport phenomena at mesoscale; in situ imaging techniques
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In this era of big data and Industry 4.0, huge significance is attached to the integrity and reliability of devices and components used in scientific and technological applications. Metallic materials are utilized in industrial applications at a large scale. Metal whiskers are hair-like protrusions that spontaneously grow from the surface of certain metals (e.g., Sn, Zn, Cd, Ge or Pb). The growth of whiskers can cause short-circuit problems and other reliability issues in the context of devices with electrical connections.
Though metal whiskering is a commonly observed phenomenon in industrial applications, the exact mechanisms responsible for the formation and growth of these single crystals are not fully understood hitherto. Some evidence has been observed regarding the role of mechanical stress and stress gradients as the triggering factor for the growth of these structures. However, much more study is needed at multi-length and -time scales to completely unravel the mechanisms driving the formation, growth, and prevalence of metal whiskers.
Therefore, it is necessary to amalgamate the aspects of experiments, modeling, and data science for state-of-the-art multi-scale characterization and description of metal whiskers. The quantitative data of whiskers’ origin and impact can be essentially utilized for the retrospective design of techniques to reduce the probability of their incidence. This Special Issue is aimed at recent advances in mechanistic and experimental investigation of metallic whiskers, including exploratory study using machine learning models.
Dr. Anil Kunwar
Dr. Johan Hektor
Guest Editors
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Keywords
- whiskers
- crystal plasticity
- finite element analysis
- machine learning
- phase field method
- imaging
- strain gradients
- diffraction
- microscopy
- molecular dynamics
