Our Products

NanoLER™

Are you interested in measuring LER/LWR accurately, concisely, completely, and quickly with just a few clicks? If yes, then NanoLER™ is the targeted solution you are looking for!

LER is a delicate issue since it is a nanoscale edge effect sensitive to SEM image acquisition and the pervasive noise. Noise affects drastically LER measurements and its control is a prerequisite for a reliable and accurate LER metrology. nanoLER provides unbiased measurements of LER using the standard PSD-based method enhanced to output unbiased results for correlation length and roughness exponent. Also nanoLER can be hybridized with SEMD software of Nanometrisis which is using a Machine Learning model (Convolutional Neural Network) to denoise SEM images

SEM images are usually noisy especially when they show lines with width and height deep on nanometer scale! And in these images and edge detection is not an easy task! Usually, noise smoothing filters or models (more or less physical) are used to make the edge detection possible. But both approaches are based on assumptions which is not sure that hold in the vast spectrum of materials and processes used in modern semiconductor manufacturing. nanoLER utilizes a supra-local algorithm using a gradual approach to edge regions enabling the edge detection even in very noisy images with low contrast. 

From the first papers of our team on LER metrology, we emphasized that LER is not only the simple number of rms. A more complete characterization is needed. We proposed and developed the three-parameter model based on rms, correlation length and roughness exponent (fractal dimension) along with the two related functions of Height-Height Correlation Function (HHCF) and Power Spectral Density (PSD). This characterization approach has been adopted more or less by almost all LER measurement software in use today. nanoLER based on this long experience outputs the full spectrum of parameters and functions characterizing full-scale and full-frequency unbiased characterization of LER and LWR. Also, it goes one step further and quantifies for the first time the correlations between the LER of nearby lines providing new metrics for pattern roughness. (more info below)

In the manufacturing of current and coming chips, a mixing of lithographies are applied. Each one of these has its own footprint in LER/LWR and pattern roughness characteristics. The three-parameter model along with HHCF and PSD are not enough to identify the differences. An extension is needed including the characterization of pattern scale effects such as the cross-talk (correlations) between edge roughness of nearby lines. nanoLER has been enriched with this extension and provides metrics for the quantification of these differences. The novel metric of cross-line correlation length is measured to identify differences between   line patterns with correlated (DSA) or uncorrelated lines (EUV)

The key idea of modular metrology is to provide easy, fast and targeted software solutions embedding in its structure the specific features of the analyzed pattern. The targeted and customized character of nanoLER makes the used GUI very simple enabling the measurement of LER from the analysis of hundreds of SEM images in just five clicks. The results are automatically stored in excel file to be used straightforwardly in the statistical process control of the R&D or production lines. 

NanoLER™ is an example of the modular metrology approach. It has been designed purposefully to provide you in simple graphical interface measurements of LER, LWR, LCDU along with their spectral analysis and pattern roughness metrics.

NanoCER™

NanoCER™ analyses images with holes (contacts, biases) in a regular pattern. It outputs metrics for the size and variation of hole dimensions (CD, CD uniformity) as well as for the proportion of the defects in the measured sample (no well-printed or no-printed at all holes).

However, NanoCER™ goes beyond these first-order metrics. It has been designed to provide accurate detection of hole edges and quantifies their shape and roughness through both frequency and correlation analysis. Therefore, if you are interested in contact edge roughness effects and metrology, NanoCER™ is your solution.

NanoCER™ is another example of the modular metrology approach: It has been designed purposefully to provide you in a simple graphical interface measurements of CD, CDU, nanoCER along with their spectral analysis and pattern roughness metrics.

NanoCER™ features:

  • Strong scientific background
  • Robust in a large spectrum of image acquisition settings
  • Full-scale/frequency defect characterization including edge roughness
  • Lithography Aware
  • Easiness to use

LS_AFM™

LS_AFM™ analyses images of Line/Space or pillar patterns analyzed to characterize defects

LS_AFM™ has been designed with respect to nanoLER, in order to analyze AFM data of line-space patterns. Much like nanoLER, it has been developed purposefully to provide in a simple graphical interface, measurement of LER, LWR, LCDU along with their spectral analysis and pattern roughness metrics.

At the same time and ought to the fact that it handles AFM data, thus the z-axis information is available, it is also capable to provide additional information, such as the top roughness of the lines or spaces, the residual layer thickness of the wafer, fill fraction of lines, depth, line width at different depths etc. Of course as with nanoLER, there is no complicated menu, no long roll down lists with numerous but useless choices, no dozens of measured parameters with no clear meaning and straightforward link to your pattern geometry and roughness.

Pill_AFM ™/SEM™


Pill_AFMTM is tailored for analyzing Atomic Force Microscopy (AFM) data of pillar structures, while Pill_SEM is designed for Scanning Electron Microscopy (SEM) images of pillar structures. Both tools offer robust analysis capabilities.

Key Features:

The tools are equipped to handle a variety of pillar patterns, ensuring versatility in application. They analyze key physical attributes of pillar structures, including size and shape. For the AFM version, additional details such as height and residual layer thickness are available, providing a comprehensive view of the pillar’s dimensions. Furthermore, the tools calculate statistical distributions for features like pillar size and periodicity (pitch), helping to identify trends or inconsistencies across the dataset.

Standout feature of both the AFM and SEM versions is their ability to match the detected pillars with a predefined design pattern from a CIF file. This functionality enables precise alignment between the design intent and the actual imaging results. The tools generate a graphical overlay of the detected pillar pattern on the design grid, offering a clear visualization of how well the fabricated structures correspond to the original specifications. This feature is invaluable for quality control and design validation.

These tools enhance precision in data analysis for pillar structures, bridging design files and imaging results seamlessly.

Nano_PAR™

Nano_PAR™ software specializes in the analysis of SEM images depicting nano- and/or micro-particles. This software achieves fast, complete and, reliable detection of particles and provides statistical characterization of particle size, shape, roughness, distribution and, dispersion

Nano_BTR™/ BER

Nano_BTR™ and Nano_BER™ software used for the characterization of blade sharpness, roughness, and 3D morphology. The difference between the two SWs is the viewing angle of the blade in the SEM images they are called to analyze. In this sense nanoBTR handles blade SEM images depicting the «ridge» of the blade, thus the spatial roughness of the blade’s ridge, whereas nanoBER specializes in analyzing SEM images of the profile of the blade, thus the roughness of the edge of the blade. Both SWs have applications in blades, surgical scalpels, and generally in all cutting tool industries.