Bayesian-optimization-assisted discovery of stereoselective aluminum complexes for ring-opening polymerization of racemic lactide

Ring Opening Polymerization of Six- and Eight-Membered Racemic Cyclic Esters for Biodegradable Materials

The low percentage of recyclability of the polymeric materials obtained by olefin transition metal (TM) polymerization catalysis has increased the interest in their substitution with more eco-friendly materials with reliable physical and mechanical properties. Among the variety of known biodegradable polymers, linear aliphatic polyesters produced by ring-opening polymerization (ROP) of cyclic esters occupy a prominent position. The polymer properties are highly dependent on the macromolecule microstructure, and the control of stereoselectivity is necessary for providing materials with precise and finely tuned properties. In this review, we aim to outline the main synthetic routes, the physical properties and also the applications of three commercially available biodegradable materials: Polylactic acid (PLA), Poly(Lactic-co-Glycolic Acid) (PLGA), and Poly(3-hydroxybutyrate) (P3HB), all of three easily accessible via ROP. In this framework, understanding the origin of enantioselectivity and the factors that determine it is then crucial for the development of materials with suitable thermal and mechanical properties.

%VBur index and steric maps: from predictive catalysis to machine learning

Steric indices are parameters used in chemistry to describe the spatial arrangement of atoms or groups of atoms in molecules. They are important in determining the reactivity, stability, and physical properties of chemical compounds. One commonly used steric index is the steric hindrance, which refers to the obstruction or hindrance of movement in a molecule caused by bulky substituents or functional groups. Steric hindrance can affect the reactivity of a molecule by altering the accessibility of its reactive sites and influencing the geometry of its transition states. Notably, the Tolman cone angle and %VBur are prominent among these indices. Actually, steric effects can also be described using the concept of steric bulk, which refers to the space occupied by a molecule or functional group. Steric bulk can affect the solubility, melting point, boiling point, and viscosity of a substance. Even though electronic indices are more widely used, they have certain drawbacks that might shift preferences towards others. They present a higher computational cost, and often, the weight of electronics in correlation with chemical properties, e.g. binding energies, falls short in comparison to %VBur. However, it is worth noting that this may be because the steric index inherently captures part of the electronic content. Overall, steric indices play an important role in understanding the behaviour of chemical compounds and can be used to predict their reactivity, stability, and physical properties. Predictive chemistry is an approach to chemical research that uses computational methods to anticipate the properties and behaviour of these compounds and reactions, facilitating the design of new compounds and reactivities. Within this domain, predictive catalysis specifically targets the prediction of the performance and behaviour of catalysts. Ultimately, the goal is to identify new catalysts with optimal properties, leading to chemical processes that are both more efficient and sustainable. In this framework, %VBur can be a key metric for deepening our understanding of catalysis, emphasizing predictive catalysis and sustainability. Those latter concepts are needed to direct our efforts toward identifying the optimal catalyst for any reaction, minimizing waste, and reducing experimental efforts while maximizing the efficacy of the computational methods.

Mechanism of Alternating Poly(lactic-co-glycolic acid) Formation by Polymerization of (S)- and (R)-3-Methyl Glycolide Using an Enantiopure Aluminum Complex

The mechanism(s) of alternating PLGA synthesis by ring-opening polymerization of (S)- and (R)-3-methyl glycolide promoted by enantiopure aluminum complexes have been rationalized by density functional theory (DFT) calculations. The high regioselectivity of the (S)-MeG polymerization is obtained by repetitive ring opening at the glycolyl site by the (R)-catalyst whereas a lower regioselectivity is predicted by the ROP of (R)-MeG. The behavior of the two monomers is rationalized by unveiling the active site fluxionality of the enantiopure catalyst, identifying the rate-limiting steps that encode a preference at the glycolyl site versus the lactyl site, and revealing selection of the opposite monomer enantioface. The microstructure of the PLGA copolymers is predicted by considering the influence of the configuration of the last inserted unit. The identification of the preferred mechanistic paths may allow for a targeted catalyst design to enhance control of the polymer microstructures.

Navigating the Expansive Landscapes of Soft Materials: A User Guide for High-Throughput Workflows

Synthetic polymers are highly customizable with tailored structures and functionality, yet this versatility generates challenges in the design of advanced materials due to the size and complexity of the design space. Thus, exploration and optimization of polymer properties using combinatorial libraries has become increasingly common, which requires careful selection of synthetic strategies, characterization techniques, and rapid processing workflows to obtain fundamental principles from these large data sets. Herein, we provide guidelines for strategic design of macromolecule libraries and workflows to efficiently navigate these high-dimensional design spaces. We describe synthetic methods for multiple library sizes and structures as well as characterization methods to rapidly generate data sets, including tools that can be adapted from biological workflows. We further highlight relevant insights from statistics and machine learning to aid in data featurization, representation, and analysis. This Perspective acts as a "user guide" for researchers interested in leveraging high-throughput screening toward the design of multifunctional polymers and predictive modeling of structure-property relationships in soft materials.

Recent advances in enantioselective ring-opening polymerization and copolymerization

Precisely controlling macromolecular stereochemistry and sequences is a powerful strategy for manipulating polymer properties. Controlled synthetic routes to prepare degradable polyester, polycarbonate, and polyether are of recent interest due to the need for sustainable materials as alternatives to petrochemical-based polyolefins. Enantioselective ring-opening polymerization and ring-opening copolymerization of racemic monomers offer access to stereoregular polymers, specifically enantiopure polymers that form stereocomplexes with improved physicochemical and mechanical properties. Here, we highlight the state-of-the-art of this polymerization chemistry that can produce microstructure-defined polymers. In particular, the structures and performances of various homogeneous enantioselective catalysts are presented. Trends and future challenges of such chemistry are discussed.