Monte-Carlo Simulations of Soft Matter Using SIMONA: A Review of Recent Applications

Molecular simulations such as Molecular Dynamics (MD) and Monte Carlo (MC) have gained increasing importance in the explanation of various physicochemical and biochemical phenomena in soft matter and help elucidate processes that often cannot be understood by experimental techniques alone. While there is a large number of computational studies and developments in MD, MC simulations are less widely used, but they offer a powerful alternative approach to explore the potential energy surface of complex systems in a way that is not feasible for atomistic MD, which still remains fundamentally constrained by the femtosecond timestep, limiting investigations of many essential processes. This paper provides a review of the current developments of a MC based code, SIMONA, which is an efficient and versatile tool to perform large-scale conformational sampling of different kinds of (macro)molecules. We provide an overview of the approach, and an application to soft-matter problems, such as protocols for protein and polymer folding, physical vapor deposition of functional organic molecules and complex oligomer modeling. SIMONA offers solutions to different levels of programming expertise (basic, expert and developer level) through the usage of a designed Graphical Interface pre-processor, a convenient coding environment using XML and the development of new algorithms using Python/C++. We believe that the development of versatile codes which can be used in different fields, along with related protocols and data analysis, paves the way for wider use of MC methods

SimStack: An Intuitive Workflow Framework

Establishing a fundamental understanding of the nature of materials via computational simulation approaches requires knowledge from different areas, including physics, materials science, chemistry, mechanical engineering, mathematics, and computer science. Accurate modeling of the characteristics of a particular system usually involves multiple scales and therefore requires the combination of methods from various fields into custom-tailored simulation workflows. The typical approach to developing patch-work solutions on a case-to-case basis requires extensive expertise in scripting, command-line execution, and knowledge of all methods and tools involved for data preparation, data transfer between modules, module execution, and analysis. Therefore multiscale simulations involving state-of-the-art methods suffer from limited scalability, reproducibility, and flexibility. In this work, we present the workflow framework SimStack that enables rapid prototyping of simulation workflows involving modules from various sources. In this platform, multiscale- and multimodule workflows for execution on remote computational resources are crafted via drag and drop, minimizing the required expertise and effort for workflow setup. By hiding the complexity of high-performance computations on remote resources and maximizing reproducibility, SimStack enables users from academia and industry to combine cutting-edge models into custom-tailored, scalable simulation solutions

Enantiomeric Separation of Semiconducting Single-Walled Carbon Nanotubes by Acid Cleavable Chiral Polyfluorene

Helical wrapping by conjugated polymer has been demonstrated as a powerful tool for the sorting of single-walled carbon nanotubes (SWCNTs) according to their electronic type, chiral index, and even handedness. However, a method of one-step extraction of left-handed (M) and right-handed (P) semiconducting SWCNTs (s-SWCNTs) with subsequent cleavage of the polymer has not yet been published. In this work, we designed and synthesized one pair of acid cleavable polyfluorenes with defined chirality for handedness separation of s-SWCNTs from as-produced nanotubes. Each monomer contains a chiral center on the fluorene backbone in the 9-position, and the amino and carbonyl groups in the 2- and 7-positions maintain the head-to-tail regioselective polymerization resulting in polyimines with strictly all-(R) or all-(S) configuration. The obtained chiral polymers exhibit a strong recognition ability toward left- or right-handed s-SWCNTs from commercially available CoMoCAT SWCNTs with a sorting process requiring only bath sonication and centrifugation. Interestingly, the remaining polymer on each single nanotube, which helps to prevent aggregation, does not interfere with the circular dichroism signals from the nanotube at all. Therefore, we observed all four interband transition peaks (E11, E22, E33, E44) in the circular dichroism (CD) spectra of the still wrapped optically enriched left-handed and right-handed (6,5) SWCNTs in toluene. Binding energies obtained from molecular dynamics simulations were consistent with our experimental results and showed a significant preference for one specific handedness from each chiral polymer. Moreover, the imine bonds along the polymer chains enable the release of the nanotubes upon acid treatment. After s-SWNT separation, the polymer can be decomposed into monomers and be cleanly removed under mild acidic conditions, yielding dispersant-free handedness sorted s-SWNTs. The monomers can be almost quantitatively recovered to resynthesize the chiral polymer. This approach enables high selective isolation of polymer-free s-SWNT enantiomers for their further applications in carbon nanotube (CNT) devices