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Ablation (ablatio – removal) is the removal or destruction of something from an object by vaporization, chipping, erosive processes, or by other means. Examples of ablative materials are described below, including spacecraft material for ascent and atmospheric reentry, ice and snow in glaciology, biological tissues in medicine and passive fire protection materials. In artificial intelligence (AI), especially machine learning, ablation is the removal of a component of an AI system. The term is by analogy with biology: removal of components of an organism. Biological ablation is the removal of a biological structure or functionality. Genetic ablation is another term for gene silencing, in which gene expression is abolished through the alteration or deletion of genetic sequence information. In cell ablation, individual cells in a population or culture are destroyed or removed. Both can be used as experimental tools, as in loss-of-function experiments. Electro-ablation, is a process that removes material from a metallic workpiece to reduce surface roughness. Electro-ablation breaks through highly resistive oxide surfaces, such as those found on Titanium and other exotic metals and alloys without melting the underlying non-oxidised metal or alloy. This allows very quick surface finishing The process is capable of providing surface finishing for a wide range of exotic and widely used metals and alloys, including: titanium, stainless steel, niobium, chromium–cobalt, Inconel, aluminium, and a range of widely available steels and alloys. Electro-ablation is very effective at achieving high levels of surface finishing in holes, valleys and hidden or internal surfaces on metallic workpieces (parts). The process is particularly applicable to components produced by additive manufacturing process, such as 3D-printed metals. These components tend to be produced with roughness levels well above 5–20 micron. Electro-ablation can be used to quickly reduce the surface roughness to less than 0.
Dario Floreano, Yegor Piskarev, Jun Shintake, Yi Sun, Matteo Righi
Mohamed Farhat, Davide Bernardo Preso, Ryan Holman