An application study on the stochastic effect of EUV photons

Kim, Jong-Su; Jue, Hyekyoung; Ryu, Hyungju; Kim, Sang-Jin; Park, Joon Soo; Shin, Ki Soon; Welling, Ulrich; Klostermann, Ulrich; Stock, Hans-Jürgen; Demmerle, Wolfgang; Jeong, Eunsoo; Chang, Sang-Yil; Choi, Jung-Hoe

doi:10.1117/12.2553319

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As the shrinking of dimensions continues, local measurements become necessary, since stochastic behaviors of physical processes become more dominant in describing the shape of structures. 1 Moreover, the third dimension becomes increasingly important, as vertically dominated structures (e.g., FinFETs, gate-all-around, and 3D NAND) have grown into popular building blocks for semiconductor devices. In this work, we zoom in on the dimension of a fin, which is the transistor channel of a fin field-effect-transistor (FinFET), as a key description parameter for the height of the physical structures (see Fig.…”

Section: Introductionmentioning

confidence: 99%

“…The measurements are used to control the production process in order to optimize production yield. As the shrinking of dimensions continues, local measurements become necessary, since stochastic behaviors of physical processes become more dominant in describing the shape of structures 1 . Moreover, the third dimension becomes increasingly important, as vertically dominated structures (e.g., FinFETs, gate-all-around, and 3D NAND) have grown into popular building blocks for semiconductor devices.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Training procedure for scanning electron microscope 3D surface reconstruction using unsupervised domain adaptation with simulated data

Houben

Huisman

Pisarenco

et al. 2023

J. Micro/Nanopattern. Mats. Metro.

View full text Add to dashboard Cite

Accurate metrology techniques for semiconductor devices are indispensable for controlling the manufacturing process. For instance, the dimensions of a transistor's current channel (fin) are an important indicator of the device's performance regarding switching voltages and parasitic capacities. We expand upon traditional 2D analysis by utilizing computer vision techniques for full-surface reconstruction. We propose a data-driven approach that predicts the dimensions, height and width (CD) values, of fin-like structures. During operation, the method solely requires experimental images from a scanning electron microscope of the patterns concerned. We introduce an unsupervised domain adaptation step to overcome the domain gap between experimental and simulated data. Our model is further fine-tuned with a height measurement from a second scatterometry sensor and optimized through a tailored training scheme for optimal performance. The proposed method results in accurate depth predictions, namely 100% accurate interwafer classification with an root-mean-squared error of 0.67 nm. The R 2 of the intrawafer performance on height is between 0.59 and 0.70. Qualitative results also indicate that detailed surface features, such as corners, are accurately predicted. Our study shows that accurate z-metrology techniques can be viable for high-volume manufacturing.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%