Project description
Nanoelectronics
Directed self-assembly (DSA) of block copolymers is one of the most promising techniques to enable the continued miniaturization of ICs and to boost the performance in More Moore. It combines top-down photolithography for creation of guiding patterns with engineered new materials and processes to facilitate cost effective bottom-up techniques for pattern density multiplication and defect rectification. An industry scale application of DSA still faces two challenges: i) The host substrate heavily impacts DSA. The resulting pattern formation must be well understood and modeled in order to optimize its efficiency and avoid defects. ii) The specific properties of DSA must be considered early in the design process.CoLiSA.MMP will develop new material and process models and a computational lithography framework for DSA. Existing and new, specially designed atomistic and coarse-grained models will be combined with experimental data to develop and calibrate efficient predictive reduced models, seamlessly integrated in lithographic process simulation. The new modeling capabilities will be used to establish new design flows which include the lithographic generation of guiding patterns and the resulting patterns after DSA. Inversion of the problem will predict lithographically manufacturable guiding patterns and process conditions for given target structures. The extended capabilities of computational lithography will be also used to improve materials and processes which are still under development, to study the root causes of DSA specific defects and to propose strategies to avoid or reduce them.CoLiSA.MMP combines European expertise in soft matter physics, block copolymer chemistry, lithographic process and computational lithography. This will help to bridge the gap between the multifaceted research activities on DSA and the integration of DSA in future processes and design flows for More Moore IC manufacturing and for new functionality in More than Moore.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
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Topic(s)
Call for proposal
FP7-ICT-2013-11
See other projects for this call
Funding Scheme
CP - Collaborative project (generic)Coordinator
80686 Munchen
Germany