The semiconductor industry continues to produce ever smaller devices that are ever more complex in shape and contain ever more types of materials. The ultimate sizes and functionality of these new devices will be affected by fundamental and engineering limits such as heat dissipation, carrier mobility and fault tolerance thresholds. At present, it is unclear which are the best measurement methods needed to evaluate the nanometre-scale features of such devices and how the fundamental limits will affect the required metrology. Here, we review state-of-the-art dimensional metrology methods for integrated circuits, considering the advantages, limitations and potential improvements of the various approaches. We describe how integrated circuit device design and industry requirements will affect lithography options and consequently metrology requirements. We also discuss potentially powerful emerging technologies and highlight measurement problems that at present have no obvious solution.

A scanning-helium-ion-beam microscope is now commercially available. This microscope can be used to perform lithography similar to, but of potentially higher resolution than, scanning electron-beam lithography. This article describes the control of this microscope for lithography via beam steering/blanking electronics and evaluates the high-resolution performance of scanning helium-ion-beam lithography. The authors found that sub-10 nm-half-pitch patterning is feasible. They also measured a point-spread function that indicates a reduction in the micrometer-range proximity effect typical in electron-beam lithography.

This paper reports an interlaboratory comparison that evaluated a protocol for measuring and analysing the particle size distribution of discrete, metallic, spheroidal nanoparticles using transmission electron microscopy (TEM). The study was focused on automated image capture and automated particle analysis. NIST RM8012 gold nanoparticles (30 nm nominal diameter) were measured for area-equivalent diameter distributions by eight laboratories. Statistical analysis was used to (1) assess the data quality without using size distribution reference models, (2) determine reference model parameters for different size distribution reference models and non-linear regression fitting methods and (3) assess the measurement uncertainty of a size distribution parameter by using its coefficient of variation. The interlaboratory area-equivalent diameter mean, 27.6 nm ± 2.4 nm (computed based on a normal distribution), was quite similar to the area-equivalent diameter, 27.6 nm, assigned to NIST RM8012. The lognormal reference model was the preferred choice for these particle size distributions as, for all laboratories, its parameters had lower relative standard errors (RSEs) than the other size distribution reference models tested (normal, Weibull and Rosin–Rammler–Bennett). The RSEs for the fitted standard deviations were two orders of magnitude higher than those for the fitted means, suggesting that most of the parameter estimate errors were associated with estimating the breadth of the distributions. The coefficients of variation for the interlaboratory statistics also confirmed the lognormal reference model as the preferred choice. From quasi-linear plots, the typical range for good fits between the model and cumulative number-based distributions was 1.9 fitted standard deviations less than the mean to 2.3 fitted standard deviations above the mean. Automated image capture, automated particle analysis and statistical evaluation of the data and fitting coefficients provide a framework for assessing nanoparticle size distributions using TEM for image acquisition.

The width and shape of 10nm to 12 nm wide lithographically patterned SiO2 lines were measured in the scanning electron microscope by fitting the measured intensity vs. position to a physics-based model in which the lines' widths and shapes are parameters. The approximately 32 nm pitch sample was patterned at Intel using a state-of-the-art pitch quartering process. Their narrow widths and asymmetrical shapes are representative of near-future generation transistor gates. These pose a challenge: the narrowness because electrons landing near one edge may scatter out of the other, so that the intensity profile at each edge becomes width-dependent, and the asymmetry because the shape requires more parameters to describe and measure. Modeling was performed by JMONSEL (Java Monte Carlo Simulation of Secondary Electrons), which produces a predicted yield vs. position for a given sample shape and composition. The simulator produces a library of predicted profiles for varying sample geometry. Shape parameter values are adjusted until interpolation of the library with those values best matches the measured image. Profiles thereby determined agreed with those determined by transmission electron microscopy and critical dimension small-angle x-ray scattering to better than 1 nm.

The development of metrology for nanoparticles is a significant challenge. Cellulose nanocrystals (CNCs) are one group of nanoparticles that have high potential economic value but present substantial challenges to the development of the measurement science. Even the largest trees owe their strength to this newly appreciated class of nanomaterials. Cellulose is the world's most abundant natural, renewable, biodegradable polymer. Cellulose occurs as whisker-like microfibrils that are biosynthesized and deposited in plant material in a continuous fashion. The nanocrystals are isolated by hydrolyzing away the amorphous segments leaving the acid resistant crystalline fragments. Therefore, the basic raw material for new nanomaterial products already abounds in nature and is available to be utilized in an array of future materials. However, commercialization requires the development of efficient manufacturing processes and nanometrology to monitor quality. This paper discusses some of the instrumentation, metrology and standards issues associated with the ramping up for production and use of CNCs.