The computational description of directed self-assembly (DSA) of copolymer materials requires the prediction of large-scale structure formation of copolymer materials guided by chemical or topographical patterns. Continuum models provide the highest level of coarse-graining describing the system only by the local composition and allowing for a fast optimization of thermodynamic quantities.
Except at the order-disorder transition, defects in lamella-forming block copolymers have a free energy of several hundreds kBT where kBT denotes the thermal energy scale. Thus, they cannot be conceived as equilibrium fluctuations around a perfectly ordered state. Instead, defects, which are observed in experiments, are formed in the course of self-assembly. Their behavior is dictated by the kinetics of structure formation, in particular, the kinetic pathways of defect motion and annihilation.Computational modeling can contribute to optimize materials parameters such as film thickness, interaction between copolymer blocks and substrate, geometry of confinement, in order to avoid the formation of defects in the early stages of structure formation or facilitate defect annihilation. Computations also provide fundamental insights into the universal physical mechanisms of directing the self-assembly, addressing the equilibrium structure and thermodynamics as well as the kinetics of self-assembly.We present computer simulation of highly coarse-grained particle-based models and self-consistent field calculations that allow us to access the long time and large length scales associated with self-assembly. These calculations provide information about the free-energy landscape and mechanisms of defect annihilation in thin films. Additionally, opportunities for directing the kinetics of self-assembly by temporal changes of thermodynamic conditions are discussed.
The introduction of DSA for lithography is still obstructed by a number of technical issues including the lack of a comprehensive computational platform. This work presents a direct source/mask/DSA optimization (SMDSAO) method, which incorporates standard lithographic metrics and figures of merit such as the maximization of process windows. The procedure is demonstrated for a contact doubling example, assuming grapho-epitaxy-DSA. To retain a feasible runtime, a geometry-based Interface Hamiltonian DSA model is employed. The feasibility of this approach is demonstrated through several results and their comparison with more rigorous DSA models
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