Resolution capability of resist patterns and throughput using alkaline treatment under ultrasonic irradiation

Author(s):  
Hideto Onishi ◽  
Miyake Mikio ◽  
Hajime SHIRAI

Abstract Alkaline treatment of the photoresist under ultrasonic irradiation has been investigated to improve the resolution capability of resist patterns with higher throughput. The selectively dissolved phenol resin for the combination of the alkaline treatment with ultrasonic irradiation was increased by 2.3 times compared to the solely alkaline treatment. The sensitizing effect of naphthoquinone diazide (sensitizer) based on phenol was increased to 0.46 against dip treatment of 0.31. As a result, resist sensitivity was increased to 26% and the resolution capability was drastically improved. Consequently, the 0.5 μm line and space resist patterns were resolved completely with fine profile by using the photoresist with a 0.7 μm resolution limit together with g-line exposure machine with a 0.6 μm resolution limit. As a consequence, a high throughput of 25 wafers/min was achieved, which was more than 25 times higher than that of electron beam (EB) lithography.

Nano Letters ◽  
2005 ◽  
Vol 5 (7) ◽  
pp. 1303-1307 ◽  
Author(s):  
Willem F. van Dorp ◽  
Bob van Someren ◽  
Cornelis W. Hagen ◽  
Pieter Kruit ◽  
Peter A. Crozier

2019 ◽  
Vol 218 (8) ◽  
pp. 2797-2811 ◽  
Author(s):  
Yury S. Bykov ◽  
Nir Cohen ◽  
Natalia Gabrielli ◽  
Hetty Manenschijn ◽  
Sonja Welsch ◽  
...  

Genetic screens using high-throughput fluorescent microscopes have generated large datasets, contributing many cell biological insights. Such approaches cannot tackle questions requiring knowledge of ultrastructure below the resolution limit of fluorescent microscopy. Electron microscopy (EM) reveals detailed cellular ultrastructure but requires time-consuming sample preparation, limiting throughput. Here we describe a robust method for screening by high-throughput EM. Our approach uses combinations of fluorophores as barcodes to uniquely mark each cell type in mixed populations and correlative light and EM (CLEM) to read the barcode of each cell before it is imaged by EM. Coupled with an easy-to-use software workflow for correlation, segmentation, and computer image analysis, our method, called “MultiCLEM,” allows us to extract and analyze multiple cell populations from each EM sample preparation. We demonstrate several uses for MultiCLEM with 15 different yeast variants. The methodology is not restricted to yeast, can be scaled to higher throughput, and can be used in multiple ways to enable EM to become a powerful screening technique.


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