RESUMEN
As a machine-recognizable representation of polymer connectivity, BigSMILES line notation extends SMILES from deterministic to stochastic structures. The same framework that allows BigSMILES to accommodate stochastic covalent connectivity can be extended to non-covalent bonds, enhancing its value for polymers, supramolecular materials, and colloidal chemistry. Non-covalent bonds are captured through the inclusion of annotations to pseudo atoms serving as complementary binding pairs, minimal key/value pairs to elaborate other relevant attributes, and indexes to specify the pairing among potential donors and acceptors or bond delocalization. Incorporating these annotations into BigSMILES line notation enables the representation of four common classes of non-covalent bonds in polymer science: electrostatic interactions, hydrogen bonding, metal-ligand complexation, and π-π stacking. The principal advantage of non-covalent BigSMILES is the ability to accommodate a broad variety of non-covalent chemistry with a simple user-orientated, semi-flexible annotation formalism. This goal is achieved by encoding a universal but non-exhaustive representation of non-covalent or stochastic bonding patterns through syntax for (de)protonated and delocalized state of bonding as well as nested bonds for correlated bonding and multi-component mixture. By allowing user-defined descriptors in the annotation expression, further applications in data-driven research can be envisioned to represent chemical structures in many other fields, including polymer nanocomposite and surface chemistry.
RESUMEN
Successful transformation of carbon dioxide (CO2) into value-added products is of great interest, as it contributes in part to the circular carbon economy. Understanding chemical interactions that stabilize crucial reaction intermediates of CO2 is important, and in this contribution, we employ atom centered density matrix propagation (ADMP) molecular dynamics simulations to investigate interactions between CO2 - anion radicals with surrounding solvent molecules and electrolyte cations in both aqueous and nonaqueous environments. We show how different cations and solvents affect the stability of the CO2 - anion radical by examining its angle and distance to a coordinating cation in molecular dynamics simulations. We identify that the strength of CO2 - interactions can be tailored through choosing an appropriate cation and solvent combination. We anticipate that this fundamental understanding of cation/solvent interactions can facilitate the optimization of a chemical pathway that results from selective stabilization of a crucial reaction intermediate.
RESUMEN
The properties of foams, an important class of cellular solids, are most sensitive to the volume fraction and openness of its elementary compartments; size, shape, orientation, and the interconnectedness of the cells are other important design attributes. Control of these morphological traits would allow the tailored fabrication of useful materials. While approaches like ice templating have produced foams with elongated cells, there is a need for rapid, versatile, and energy-efficient methods that also control the local order and macroscopic alignment of cellular elements. Here, a fast and convenient method is described to obtain anisotropic structural foams using frontal polymerization. Foams are fabricated by curing mixtures of dicyclopentadiene and a blowing agent via frontal ring-opening metathesis polymerization (FROMP). The materials are characterized using microcomputed tomography (micro-CT) and an image analysis protocol to quantify the morphological characteristics. The cellular structure, porosity, and hardness of the foams change with blowing agent, concentration, and resin viscosity. Moreover, a full factorial combination of variables is used to correlate each parameter with the structure of the obtained foams. The results demonstrate the controlled production of foams with specific morphologies using the simple and efficient method of frontal polymerization.
RESUMEN
The rational design of 3D structures (MOFs, COFs, etc.) is presently limited by our understanding of how the molecular constituents assemble. The common approach of using reversible interactions (covalent or noncovalent) becomes challenging, especially when the target is made from multivalent building blocks and/or under conditions of slow exchange, as kinetic traps and nonequilibrium product distributions are possible. Modeling the time course of the assembly process is difficult because the reaction networks include many possible pathways and intermediates. Here we show that rule-based kinetic simulations efficiently model dynamic reactions involving multivalent building blocks. We studied "strand escape from an [n]-rung ladder" as an example of a dynamic process characterized by a complex reaction network. The strand escape problem is important in that it predicts the time a dynamic system needs to backtrack from errors involving [n]-misconnections. We quantify the time needed for error correction as a function of the dissociation rate coefficient, strand valency, and seed species. We discuss the simulation results in relation to a simple probabilistic framework that captures the power law dependence on the strand's valency, and the inverse relationship to the rung-opening rate coefficient. The model also tests the synthetic utility of a one-rung (i.e., hairpin) seed species, which, at intermediate times, bifurcates to a long-lived, fully formed [n]-rung ladder and a pair of separated strands. Rule-based models thus give guidance to the planning of a dynamic covalent synthesis by predicting time to maximum yield of persistent intermediates for a particular set of rate coefficients and valency.
