Concentration effects on the self-assembly of tyrosine molecules
文献情報
Hajar Nili Ahmadabadi, Amir Ali Masoudi, Sahin Uyaver
Molecular self-assembly is a ubiquitous phenomenon in which individual atoms or molecules set up an ordered structure. It is of high interest for understanding the biology and a variety of diseases at the molecular level. In this work, we studied the self-assembly of tyrosine molecules via extensive molecular dynamics simulations. The formation of structures by self-assembly was systematically studied at various concentrations, from very low to very high. The temperature was kept constant, at which, in our former studies, we have already observed well-formed self-assembled structures. Depending on the concentration, the system displays a wide range of different structures, ranging from freely scattered monomers to very well formed four-fold structures. Different regimes of concentration dependence are observed. The results are proved by calculating the moments of inertia of the structures and the number of hydrogen bonds formed. Free energy landscapes calculated for the number of hydrogen bonds versus the number of contacts within a criterion provide insights into the structures observed.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.












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