Auger Spectroscopy and the Chemistry of Defects

The physics of Auger spectroscopy have previously been discussed, but a quick summary is as follows: a sample is bombarded with a high energy electron beam, which causes the sample to emit (among multiple other particles) Auger electrons. These Auger electrons have unique characteristic energy levels depending on the type of atom they originated from; by analyzing these energy levels, the elemental makeup of a given sample can be determined. Unlike techniques like x-ray fluorescence (XRF) which can penetrate into the bulk of a sample, Auger spectroscopy is purely a surface analysis technique – making it perfect for analyzing contaminants on a failing device.

Though its high degree of spatial resolution and sensitivity make Auger spectroscopy a perfect tool for analyzing contaminants, it can be used easily for many other purposes as well. When performing a construction analysis on a new product, for example, it may be very useful to determine whether all the constituent components of the device – the layers on an integrated circuit, the various solders and metal traces on a printed circuit board, et cetera – meet the necessary material specifications. Indeed, on many modern integrated circuits, Auger spectroscopy is one of the only electronic failure analysis tools that is precise enough to characterize the elemental makeup of the infinitesimal features that make up the transistors that give the device its brainpower.

Auger spectroscopy’s adaptability makes it applicable to many different situations: not only can it easily pick up the carbon, oxygen, and phosphorus left behind by the accidental spill of a certain name-brand soft drink that ended the life of a TV remote, it is also perfect for characterizing the construction of integrated circuits and printed circuit boards. This versatility makes it a valuable addition to the failure analyst’s toolbox; since one never knows what the next failing sample to come in will be, it is always necessary to have tools that can be used in a wide variety of ways to uncover the root cause of failure.

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