Review of applications of Defect Photoluminescence Imaging (DPLI) during IC processing

Jastrzȩbski, L.; Duru, Romain; Le-Cunff, Delphine; Cannac, Maxime; Joblot, S.; Mica, I.; Polignano, M. L.; Galbiati, A.; Monge, Paolo; Roffarello,; Nadudvari, Gyorgy; Kiss, Zoltán; Lajtos, Imre; Pongrácz, Anita; Molnár, Gábor; Nagy, M.; Dudás, László; Basa, P.; Greenwood, B.; Gambino, Jeff

doi:10.23919/iwjt.2019.8802893

Cited by 5 publications

(1 citation statement)

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“…In this respect, room-temperature micro-photoluminescence imaging (RT micro-PL) is an emerging and nondestructive, noncontact technique that can reveal crystal defects in silicon based on the radiative recombination of charge carriers mediated by defect bands. [8][9][10] This technique allows the identification of buried defects in silicon with a lateral resolution of 1 μm and can be applied in the production line with an acquisition time of few seconds per field of view. Moreover, the defect recognition can be automatized with a classification based on their morphology in the micro-PL images.…”

Section: Introductionmentioning

confidence: 99%

Micro‐Photoluminescence Imaging at Room Temperature of Crystallographic Defects Generated by Deep Trench Structures

Frascaroli

Colombo

Fumagalli

et al. 2022

Physica Status Solidi (a)

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Deep trenches (DT) in silicon are a source of mechanical stress that can eventually lead to the formation of crystal defects. Herein this work, it is shown that room‐temperature micro‐photoluminescence imaging can be applied for a nondestructive in‐line monitoring of buried defects generated by DT. With the training of a convolutional neural network for automatic image segmentation, image analysis is automatized, allowing the inspection of large areas. The analysis of DT structures with various spacing and multiplicity reveals that the DT mutual distance is the main factor governing defects generation. Finally, a step‐by‐step analysis allows to detect the step responsible for defect generation and a further defect density increase along the process flow.

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Section: Introductionmentioning

confidence: 99%