Optical wafer defect inspection at the 10nm technology node and beyond

Defect inspection scientists from Huazhong University of Science and Technology, Harbin Institute of Technology, and the Chinese University of Hong Kong do a comprehensive review of exciting new insights and trends based on previous excellent reviews in the field. of defect inspection methods. The review focuses on three specific areas: (1) defect detectability assessment, (2) various optical inspection systems, and (3) post-processing algorithms.

Posting in the newspaper International Magazine of Extreme Manufacturing, the Nanoscale and Optical Metrology Research Center (NOMRC) led by Prof. Shiyuan Liu and Prof. Jinlong Zhu of Huazhong University of Science and Technology and their collaborators from Harbin Institute of Technology and Hong Kong Chinese University Kong wrote the first systematic review to present the research background, discuss the latest developments, and the trend of optical wafer defect inspection. This review has revealed that state-of-the-art techniques such as nanophotonics, optical vortices, computational imaging, quantitative phase imaging, and deep learning can have a profound impact on sub-10nm defect inspection. The work may pave new avenues for the field of semiconductor wafer defect inspection.

Professor Jinlong Zhu and Professor Shiyuan Liu state that “the shrinking features and space on patterned wafers would put great pressure on the capabilities of all current metrology and inspection solutions to balance sensitivity, specificity, speed of the process and the rate of capture”.

Far-field optical wafer inspection remains one of the workhorses for factory defect inspection. In a conventional defect inspection tool, defects are captured by comparing circuit pattern images of adjacent dies. The first author of the review paper, Professor Jinlong Zhu, says that “the key to defect inspection is not resolution, but rather signal-to-noise ratio (SNR) and contrast. The improvement of SNR and contrast depends relying heavily on sophisticated instrumentation, advanced modeling architectures, and post-processing algorithms, all of which led us to conduct a comprehensive review of wafer defect detection methods from the following three aspects: (1) evaluation of detectability of defects, (2) the various optical inspection systems, and (3) the post-processing algorithms.”

“It is of great importance to carry out defect detectability assessment for a specific type of inspection tools for advanced nodes,” explained co-senior author Dr. Jiamin Liu. “In fact, defect detectability evaluation generally involves the formulation of quantitative rules for the SNR of defect scattering signals, the development of simulation tools for defect scattering signal modeling, and the analysis of the SNR. We found that the SNR of defects depends significantly on material and defect topology.”

Conventional approaches in optical defect inspection, such as amplitude-based along with their post-processing algorithms, have been thoroughly discussed. New inspection mechanisms, including those based on phase, orbital angular momentum, terahertz wave, and hyperbolic Bloch modes, have been highlighted to remind readers of their potential to open up new directions in the field. In addition, X-ray picography, the only optical method that can directly image defects less than 20 nm from the surface and bottom surface of the entire wafer, has also been reviewed and explored in detail in the article. X-ray ptography has the potential to penetrate the field by providing revolutionary 3D resolution and sensitivity once disadvantages including synchrotron X-ray light source, large amount of data and low speed are overcome to be conquered in the future. the future.

“Whether it is the simplest image difference operator or complex image synthetic algorithm or even deep learning algorithms, these post-processing algorithms play a critical role in optical defect inspection in terms of improving SNR and image contrast. Therefore, we provide a detailed discussion of the post-processing algorithms involved in wafer defect inspection with a specific focus on the advantages and disadvantages of deep learning algorithms,” added co-author Dr. Tianlai Xu.

Professor Jinlong Zhu says that “we believe that the inspection of optical defects in patterned wafers will remain a challenging but interesting topic that needs to be addressed urgently. We believe that this review article, which is written on the basis of previous reviews and some exploratory research in cutting-edge management, it is important both for new entrants to the field and for those seeking to use it in interdisciplinary work.”

Provided by International Journal of Extreme Manufacturing