Mechanical properties of gradient copolymers of styrene and n -butyl acrylate

In-situ photo-crosslinkable elastomer based on polyalphaolefin/halloysite nanohybrid

In this research, new injectable and in situ photocurable elastomeric nanohybrids have been fabricated from polyalphaolefin (PAO) resins and halloysite nanofiller. In this regard, the co-oligomerization of long α-olefin monomers (C6, C8 and C10) with alkenol counterparts was carried out via a simple cationic route to provide OH-functionalized PAOs. The newly formed PAO type copolymer resins as well as halloysite nanoclay were then equipped with photocurable CC bonds containing an acrylate moiety. After the characterization of the final chemical substances and also of the intermediate structures, experimentally and computationally by means of Density Functional Theory (DFT) calculations, the neat treated PAO and PAO/halloysite nanohybrids were subjected to a curing process by visible light irradiation (λ ∼ 475 nm, blue light). The crosslinking efficiency of the neat resins and the formed nanohybrid was evaluated using shrinkage strain-time curves and equilibrium swelling method. The suggested nanohybrid is not only biocompatible (96 % in the MTT assay), and hydrophilic (with a water contact angle of 61°), but also exhibits an easy, fast and robust curing process with great potential for coating and sealing technologies for medical devices.

Effect of Macromolecular Structure on Phase Separation Regime in 3D Printed Materials

In this study, the fabrication of 3D-printed polymer materials with controlled phase separation using polymerization induced microphase separation (PIMS) via photoinduced 3D printing is demonstrated. While many parameters affecting the nanostructuration in PIMS processes are extensively investigated, the influence of the chain transfer agent (CTA) end group, i.e., Z-group, of macromolecular chain transfer agent (macroCTA) remains unclear as previous research has exclusively employed trithiocarbonate as the CTA end group. Herein, the effect of macroCTAs containing four different Z-groups on the formation of nanostructure of 3D printed materials is explored. The results show that the different Z-groups lead to distinct network formation and phase separation behaviors between the resins, influencing both the 3D printing process and the resulting material properties. Specifically, less reactive macroCTAs toward acrylic radical addition, such as O-alkyl xanthate and N-alkyl-N-aryl dithiocarbamate, result in translucent and brittle materials with macrophase separation morphology. In contrast, more reactive macroCTAs such as S-alkyl trithiocarbonate and 4-chloro-3,5-dimethylpyrazo dithiocarbamate produce transparent and rigid materials with nano-scale morphology. Findings of this study provide a novel approach to manipulate the nanostructure and properties of 3D printed PIMS materials, which can have important implications for materials science and engineering.

Machine Learning-Assisted Identification of Copolymer Microstructures Based on Microscopic Images

The microstructure of polymer materials is an important bridge between their molecular structure and macroproperties, which is of great significance to be effectively identified. With the increasing refinement of polymer material design, the microstructure of different polymer materials gradually converges, which is difficult to distinguish. In this study, the machine learning method is applied to recognize the microstructure. A highly accurate and interpretable model based on small experimental data sets has been completed by the methods of transfer learning and feature visualization, making the result of the model that can be explained from the perspective of physical chemistry. This work provides an idea for identifying microstructure and will help further promote intelligent polymer research and development.

Machine learning strategies for the structure-property relationship of copolymers

Establishing the structure-property relationship is extremely valuable for the molecular design of copolymers. However, machine learning (ML) models can incorporate both chemical composition and sequence distribution of monomers, and have the generalization ability to process various copolymer types (e.g., alternating, random, block, and gradient copolymers) with a unified approach are missing. To address this challenge, we formulate four different ML models for investigation, including a feedforward neural network (FFNN) model, a convolutional neural network (CNN) model, a recurrent neural network (RNN) model, and a combined FFNN/RNN (Fusion) model. We use various copolymer types to systematically validate the performance and generalizability of different models. We find that the RNN architecture that processes the monomer sequence information both forward and backward is a more suitable ML model for copolymers with better generalizability. As a supplement to polymer informatics, our proposed approach provides an efficient way for the evaluation of copolymers.

Nano- to macro-scale control of 3D printed materials via polymerization induced microphase separation

Although 3D printing allows the macroscopic structure of objects to be easily controlled, controlling the nanostructure of 3D printed materials has rarely been reported. Herein, we report an efficient and versatile process for fabricating 3D printed materials with controlled nanoscale structural features. This approach uses resins containing macromolecular chain transfer agents (macroCTAs) which microphase separate during the photoinduced 3D printing process to form nanostructured materials. By varying the chain length of the macroCTA, we demonstrate a high level of control over the microphase separation behavior, resulting in materials with controllable nanoscale sizes and morphologies. Importantly, the bulk mechanical properties of 3D printed objects are correlated with their morphologies; transitioning from discrete globular to interpenetrating domains results in a marked improvement in mechanical performance, which is ascribed to the increased interfacial interaction between soft and hard domains. Overall, the findings of this work enable the simplified production of materials with tightly controllable nanostructures for broad potential applications.

Controlling phase separated domains in UV-curable formulations with OH-functionalized prepolymers

Modification of photocurable radical systems with high molecular weight prepolymers enables access to a wide array of polymer structures and properties.

Nanostructure Control in 3D Printed Materials

Currently, there are no straightforward methods to 3D print materials with nanoscale control over morphological and functional properties. Here, a novel approach for the fabrication of materials with controlled nanoscale morphologies using a rapid and commercially available Digital Light Processing 3D printing technique is demonstrated. This process exploits reversible deactivation radical polymerization to control the in-situ-polymerization-induced microphase separation of 3D printing resins, which provides materials with complex architectures controllable from the macro- to nanoscale, resulting in the preparation of materials with enhanced mechanical properties. This method does not require specialized equipment or process conditions and thus represents an important development in the production of advanced materials via additive manufacturing.

A Methodology Towards Mechanical Properties Optimization of Three-Component Polymers by the Gradual Variation of Feed Composition in Semi-Continuous Emulsion-Free Radical Polymerization

In this work, a new methodology for the synthesis of three-component polymers (TCPs) was developed using a seeded, semi-continuous free-radical emulsion polymerization towards the optimization of the moduli–ultimate deformation performance and energy dissipation capacity for a styrene (S), n-butyl acrylate (BA), and 4-vinylbenzyl chloride (VBC) system. The three components were sequentially fed in pairs, varying feed composition along the conversion using S as the common monomer. To prepare a reference material, an industrial method was utilized with those monomers, using an equivalent global composition in a two-stage batch process (TS). Nanophase formation in the particles was observed by transmission electron microscopy (TEM), while the separation of the phases in the solid samples was observed by atomic force microscopy (AFM). The changes in glass transition temperature were determined by differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA). The latter was primarily used to compare mechanodynamic properties as a function of temperature for the two synthesis methods used. Thus, the higher toughness of the forced composition three-component polymeric materials was evaluated by means of their energy dissipation capacity, toughness, and stress–strain measurements at several temperatures.

Tailoring Copolymer Properties by Gradual Changes in the Distribution of the Chains Composition Using Semicontinuous Emulsion Polymerization

To design the properties of a copolymer using free radical polymerization, a semicontinuous process can be applied to vary the instantaneous copolymer composition along the conversion searching for a specific composition spectrum of copolymer chains, which can be termed as weight composition distribution (WCD) of copolymer chains. Here, the styrene-n-butyl acrylate (S/BA) system was polymerized by means of a semicontinuous emulsion process, varying the composition of the comonomer feed to obtain forced composition copolymers (FCCs). Five different feeding profiles were used, searching for a scheme to obtain chains rich in S (looking for considerable modulus), and chains rich in BA (looking for large deformation) as a technique to achieve synergy in copolymer properties; the mechanostatic and dynamic characterization discloses the correspondence between WCD and the bulk properties. ¹H-nuclear magnetic resonance (¹H-NMR) analysis enabled the determination of the cumulative copolymer composition characterization, required to estimate the WCD. The static test (stress-strain) and dynamic mechanical analysis (DMA) were performed following normed procedures. This is the first report that shows very diverse mechanostatic performances of copolymers obtained using the same chemical system and global comonomer composition, forming a comprehensive failure envelope, even though the tests were carried out at the same temperature and cross head speed. The principles for synergic performance can be applied to controlled radical copolymerization, designing the composition variation in individual molecules along the conversion.

Copolymerization of l-lactide/trimethylene carbonate by organocatalysis: controlled synthesis of comb-like graft copolymers with side chains with different topologies

Synthesis of comb-like graft copolymers of lcP(LLA-co-TMC) from an organocatalyst/PB–OH system: including lcP(TMC-b-LLA), lcP(LLA-grad-TMC) and lcP(LLA-ran-TMC).