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Proximity effect (electron beam lithography)

About: Proximity effect (electron beam lithography) is a research topic. Over the lifetime, 940 publications have been published within this topic receiving 8508 citations.


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Journal ArticleDOI
TL;DR: This paper presents the hierarchical digital signal processing (DSP) model utilized by PYRAMID (the authors' proximity effect correction scheme) to estimate exposures and employs a two part hierarchical estimation technique which is several orders of magnitude faster than a direct (spatial domain or FFT-based) convolution yet is able to predict the result of an exposure with a high degree of accuracy.
Abstract: One of the major limiting factors in electron beam (e-beam) lithography is the undesired development of circuit area caused by electron scattering (the proximity effect). Since the proximity effect imposes a severe limitation on the ultimate resolution attainable with electron beam lithography, it is important to examine ways in which the proximity effect can be reduced. In order to develop a fast and efficient proximity effect correction scheme it is necessary to have a fast and accurate technique for finding the exposure (energy) deposited at any given point in the circuit pattern. In this paper we present the hierarchical digital signal processing (DSP) model utilized by PYRAMID (our proximity effect correction scheme) to estimate these exposures. Our approach employs a two part hierarchical estimation technique which is several orders of magnitude faster than a direct (spatial domain or FFT-based) convolution yet is able to predict the result of an exposure with a high degree of accuracy. A detailed description of our method of exposure estimation is followed by a thorough analysts of its performance through simulation and experimental results.

46 citations

Proceedings ArticleDOI
14 Sep 2001
TL;DR: In this paper, the acid-quencher mutual diffusion/quenching model is implemented to the fast resist image simulator and accuracy better than 10nm was obtained over wide varieties of 0.13-node metal-level pattern features.
Abstract: To describe complex acid/quencher interaction and their mutual diffusion in imaging with chemically amplified resist films, our acid-quencher mutual diffusion/quenching model is implemented to the fast resist image simulator. Accuracy better than 10-nm was obtained over wide varieties of 0.13- node metal-level pattern features. The model also suggested that diffusion of quencher, as well as that of acid, significantly degrades proximity effects and MEF.

44 citations

Journal ArticleDOI
TL;DR: In this article, an empirically derived model for calculating feature sizes in resist is presented. But the model is based on convolution of the mask pattern with a set of kernels determined from measuring the printed test structures in resist.
Abstract: We present the characterization of optical proximity effects and their correction in deep‐UV lithography using an empirically derived model for calculating feature sizes in resist. The model is based on convolution of the mask pattern with a set of kernels determined from measuring the printed test structures in resist. The fit of the model to the measurement data is reviewed. The model is then used for proximity correction using commercially available proximity correction software. Corrections based on this model is effective in restoring resist linearity and in reducing line‐end shortening. It is also more effective in reducing optical proximity effects than corrections based only on aerial image calculations.

44 citations

Journal ArticleDOI
TL;DR: In this article, a novel nanocomposite resist system was developed for sub-100 nm resolution e-beam lithography by dispersing surface-treated silica nanoparticles in a commercial ZEP520® resist.

43 citations

Journal ArticleDOI
TL;DR: In this article, a negative tone fullerene-derivative molecular resist was fabricated using helium ion beam lithography (HIBL) and shown to have a sensitivity of 40µC/cm2 with a 30keV helium beam.

43 citations


Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202316
202234
20214
20206
20194
20186