In Situ Tracking of Composition and Morphology of a Diblock Copolymer Film with GISAXS during Exchange of Solvent Vapors at Elevated Temperatures

Abstract

Solvothermal vapor annealing at elevated temperature is applied to a thin film from a cylinder-forming polystyrene-block-poly(dimethyl siloxane) (PS-b-PDMS) diblock copolymer. At this, the film is swollen in the vapor of n-heptane (highly selective for PDMS). This vapor is stepwise replaced by the vapor of toluene (weakly selective for PS). The morphologies are investigated using in situ, real-time grazing-incidence small-angle X-ray scattering (GISAXS). The initial cylindrical morphology is transformed into, among others, the lamellar one. This novel type of experiments allows probing a trajectory in the state diagram of the PS-b-PDMS/n-heptane/toluene mixture. To corroborate the morphologies, they are generated by molecular simulations, and the 2D GISAXS maps are calculated using the distorted-wave Born approximation. To relate the morphologies to the solvent distribution in the two types of nanodomains, the latter is estimated from the intensities of the Bragg reflections in the 2D GISAXS maps along with the swelling ratio of the film. Comparison with the results from a similar experiment carried out at room temperature results in the same sequence of morphologies; however, at elevated temperature, more well-ordered structures are obtained. This new approach proves to be efficient to achieve a block copolymer thin film having a desired morphology and orientation.

BornAgain: software for simulating and fitting grazing-incidence small-angle scattering

“…They involve films of water (Gutfreund et al, 2016), alkane (Fontaine et al, 2018), lipid (Nylander et al, 2017), organic semiconductor (Zykov et al, 2017) and inorganic semiconductor (Highland et al, 2017;Singh et al, 2017); microgels (Kyrey et al, 2018) and microemulsions ; templated (Li-Destri et al, 2016) and self-assembled polymer structures (Berezkin et al, 2018;Glavic et al, 2018;Xie et al, 2018); nanocolumns growing from vapor deposition (Haddad et al, 2016); Au nanoparticles during CO oxidation (Odarchenko et al, 2018); C 60 monolayer islands (Kowarik, 2017); magnetic nanoparticles (Ukleev et al, 2016(Ukleev et al, , 2017 and magnetic films (Merkel et al, 2015;Glavic et al, 2018); lithographic gratings (Pflü ger et al, 2019); and sputtered multilayers . They involve films of water (Gutfreund et al, 2016), alkane (Fontaine et al, 2018), lipid (Nylander et al, 2017), organic semiconductor (Zykov et al, 2017) and inorganic semiconductor (Highland et al, 2017;Singh et al, 2017); microgels (Kyrey et al, 2018) and microemulsions ; templated (Li-Destri et al, 2016) and self-assembled polymer structures (Berezkin et al, 2018;Glavic et al, 2018;Xie et al, 2018); nanocolumns growing from vapor deposition (Haddad et al, 2016); Au nanoparticles during CO oxidation (Odarchenko et al, 2018); C 60 monolayer islands (Kowarik, 2017); magnetic nanoparticles (Ukleev et al, 2016(Ukleev et al, , 2017 and magnetic films (Merkel et al, 2015;…”

High-Precision Solvent Vapor Annealing for Block Copolymer Thin Films

“…Recent results reveal that optimized ordering of hexagonally-packed cylinders can potentially occur in seconds and extend through the film using SVA, but this approach can be somewhat unreliable [ 38 ], where near 100% success of forming the desired morphology has yet to be achieved. Advances in computer simulation as well as in situ X-ray and neutron scattering continue to both further understand this process and improve upon it [ 39 , 40 , 41 ]. While such an understanding of the self-assembly behavior is critical to the advancement of this field, utilizing a statistical approach to quantifying SVA with large sample sets, with a goal of overcoming reliability barriers, requires the ability to identify, measure and develop controls for all of the pertinent variables with reliable precision.…”

“…This includes chamber pressure, solvent exposure time, solvent concentration in the film, solvent evaporation rate, solvent purity or combinations, ambient temperature, sample and solvent temperature, humidity [ 42 ], and film thickness to name a few. These are addressed in the present manuscript, with a primary focus on the role of controlling chamber pressure and solvent evaporation rates at fast time scales of ~10 ms. We note that this chamber does not actively control sample [ 41 ] or solvent temperature [ 43 , 44 , 45 ], or include multiple solvents [ 46 ], which have been shown important to controlling annealing kinetics. So, these results work to keep these parameters as consistent as possible.…”

Self-assembly of block copolymers under non-isothermal annealing conditions as revealed by grazing-incidence small-angle X-ray scattering

“…Remarkably, due to the recent progress in synchrotron instrumentation for GISAXS, sub-millisecond time-resolution measurements can be performed, thus enabling an accurate study of the kinetics of the BCP self-assembly process. However, most of the reported in situ and real-time studies using synchrotron radiation were performed on solventannealed samples (Papadakis et al, 2008;Di et al, 2010;Gu et al, 2014;Zhang et al, 2014;Sinturel et al, 2014;Berezkin et al, 2018;Lee et al, 2019). In general, the characterization of thermally annealed samples is mainly performed on already self-assembled ex situ samples by taking snapshots during the process of interest (Ferrarese Lupi et al, 2017), while only a few studies have been performed during the thermal annealing (Yager et al, 2009;Sepe et al, 2011;Maret et al, 2014;Samant et al, 2016).…”