Over the last few years, significant improvements in sources, columns, detectors, control software, and accessories have enabled a wealth of new focused ion beam applications. In addition, modeling has provided many insights into ion-sample interactions and the resultant effects on the sample. With the knowledge gained, the community has found new ion-beam induced chemistries and ion-beam sources, allowing extending nanostructure fabrication and material deposition to smaller dimensions and better control for direct write and patterning. Insignificant proximity effects in resist-based ion beam lithography, combined with the availability of sub-nm ion spot sizes, opens the way to sub-10 nm structures and dense patterns. Additionally, direct-write ion beam nanomachining can process multilevel structures with arbitrary depths in one single process step, with all the information included in a single standard design file, thus enabling fabrication applications not achievable with any other technique.

Focused ion beam microscopes are extremely versatile and powerful instruments for materials research. These microscopes, when coupled in a system with a scanning electron microscope, offer the opportunity for novel sample imaging, sectioning, specimen preparation, three-dimensional (3D) nano- to macroscale tomography, and high resolution rapid prototyping. The ability to characterize and create materials features in a site-specific manner at nanoscale resolution has provided key insights into many materials systems. The advent of novel instrumentation, such as new ion sources that encompass more and more of the periodic table, in situ test harnesses such as cryogenic sample holders for sensitive material analyses, novel detector configurations for 3D structural, chemical, and ion contrast characterization, and robust and versatile process automation capabilities, is an exciting development for many fields of materials research.

This article reviews silicene, a relatively new allotrope of silicon, which can also be viewed as the silicon version of graphene. Graphene is a two-dimensional material with unique electronic properties qualitatively different from those of standard semiconductors such as silicon. While many other two-dimensional materials are now being studied, our focus here is solely on silicene. We first discuss its synthesis and the challenges presented. Next, a survey of some of its physical properties is provided. Silicene shares many of the fascinating properties of graphene, such as the so-called Dirac electronic dispersion. The slightly different structure, however, leads to a few major differences compared to graphene, such as the ability to open a bandgap in the presence of an electric field or on a substrate, a key property for digital electronics applications. We conclude with a brief survey of some of the potential applications of silicene.

This article reviews recent developments and applications of two beam systems (focused ion beam [FIB] and scanning electron microscope [SEM]) for in situ characterization and manipulation of material at the micro- and nanoscale. In these applications, the sample may be manipulated, ion milled, mechanically or electrically excited, and its temperature varied from above room temperature to cryogenic levels. FIB-SEM instruments offer new opportunities for in situ characterization by enabling localized exposure of surface layers within the high vacuum microscope chamber environment (especially in conjunction with cryogenic cooling of the bulk sample), through experiments that require either highly accurate material removal or localized material addition through beam-induced gas deposition, and by using micro- and nano-manipulation technologies for probing or positioning. This article describes the current state of the art of this experimental methodology and provides case studies in the areas of cryogenic, electrical, and mechanical characterization.

This article summarizes recent technological improvements of focused ion beam tomography. New in-lens (in-column) detectors have a higher sensitivity for low energy electrons. In combination with energy filtering, this leads to better results for phase segmentation and quantitative analysis. The quality of the 3D reconstructions is also improved with a refined drift correction procedure. In addition, the new scanning strategies can increase the acquisition speed significantly. Furthermore, fast spectral and elemental mappings with silicon drift detectors open up new possibilities in chemical analysis. Examples of a porous superconductor and a solder with various precipitates are presented, which illustrate that combined analysis of two simultaneous detector signals (secondary and backscattered electrons) provides reliable segmentation results even for very complex 3D microstructures. In addition, high throughput elemental analysis is illustrated for a multi-phase Ni-Ti stainless steel. Overall, the improvements in resolution, contrast, stability, and throughput open new possibilities for 3D analysis of nanostructured materials.

Ion beams are now widely used to thin, shape, or cut materials on the submicrometer scale. This is possible because ions can sputter (i.e., physically remove) material from the target. Ions can also be used to image materials because the incident beam generates ion-induced secondary electrons (iSE). In both cases, the nature of the target material and the choice of the ion employed and its initial energy will determine not only how quickly the beam can thin a specimen, but also the resolution and contrast of the iSE image that is generated. Clearly, there is a need to be able to predict parameters, such as the nature, information content, and spatial resolution of the iSE image. These and other related questions have been investigated using Monte Carlo simulations. We show how the parameters defining quantities, such as depth of penetration and the energy deposited by the incident beam, or the signal yield and resolution of the iSE image, can be predicted using this approach and how these results make it possible to interpret data and optimize operating conditions.