A Combined Theoretical and Experimental Study of the Polymer Matrix-Mediated Stress Transfer in a Cellulose Nanocomposite

Dispersion of Cellulose Nanofibers in Methacrylate-Based Nanocomposites

Poly(methylmethacrylate-co-methacrylic acid) (PMMA-co-MAA) polymers were prepared via cobalt-mediated free radical copolymerization and were characterized after synthesis. The synthesis led to a 98.5% conversion and a final ratio between the two units, MMA/MAA, was equal to 63:37 mol%. PMMA-co-MAA was then used as a matrix for cellulose-based nanocomposites to tailor filler compatibility, thanks to the presence of carboxylic groups capable of generating strong H-bonds with the cellulose surface. Cellulose nanofibers (CNFs) were dispersed using a solution with a mixture of two solvents to tailor compatibility of both the components. For this purpose, CNFs were successfully re-dispersed in methanol using the solvent exchange method and tetrahydrofuran/methanol mixtures at different ratios were used for the preparation of the films. Fully transparent films of PMMA-co-MAA + CNF were prepared up to 15 wt% of CNF with a good dispersion in the matrix. This dispersion state leads to the reinforcement of the polymethacrylate matrix, increasing its tensile strength whilst preserving optical transparency.

Leveraging peptide-cellulose interactions to tailor the hierarchy and mechanics of peptide-polymer hybrids

Inspired by spider silk's hierarchical diversity, we leveraged peptide motifs with the capability to tune structural arrangement for controlling the mechanical properties of a conventional polymer framework. The addition of nanofiller with hydrogen bonding sites was used as another pathway towards hierarchical tuning via matrix-filler interactions. Specifically, peptide-polyurea hybrids (PPUs) were combined with cellulose nanocrystals (CNCs) to develop mechanically-tunable nanocomposites via tailored matrix-filler interactions (or peptide-cellulose interactions). In this material platform, we explored the effect of these matrix-filler interactions on the secondary structure, hierarchical ordering, and mechanical properties of the peptide hybrid nanocomposites. Interactions between the peptide matrix and CNCs occur in all of the PPU/CNC nanocomposites, preventing α-helical ordering, but promoting inter-molecular hydrogen bonded β-sheet formation. Depending on peptide and CNC content, the Young's modulus varies from 10 to 150 MPa. Unlike conventional cellulose-reinforced polymer nanocomposites, the mechanical properties of these composite materials are dictated by a balance of CNC reinforcement, peptidic ordering, and microphase-separated morphology. This research highlights that leveraging peptide-cellulose interactions is a strategy to create materials with targeted mechanical properties for a specific application using a limited selection of building blocks.

Automatic Multiscale Method of Building up a Cross-linked Polymer Reaction System: Bridging SMILES to the Multiscale Molecular Dynamics Simulation

An automatic method is introduced to generate the initial configuration and input file from SMILES for multiscale molecular dynamics (MD) simulation of cross-linked polymer reaction systems. Inputs are a modified version of SMILES of all the components and conditions of coarse-grained (CG) and all-atom (AA) simulations. The overall process comprises the following steps: (1) Modified SMILES inputs of all the components are converted to 3-dimensional coordinates of molecular structures. (2) Molecular structures are mapped to the coarse-grained scale, followed by a CG reaction simulation. (3) CG beads are backmapped to the atomic scale after the CG reaction. (4) An AA productive run is finally performed to analyze volume shrinkage, glass transition, and atomic detail of network structure. The method is applied to two common epoxy resin reactions, that is, the cross-linking process of DGEVA (diglycidyl ether of vanillyl alcohol) and DHAVA (dihydroxyaminopropane of vanillyl alcohol) and that of DGEBA (diglycidyl ether of bisphenol A) and DETA (diethylenetriamine). These components form network structures after the CG cross-linking reaction and are then backmapped to calculate properties in the atomic scale. The result demonstrates that the method can accurately predict volume shrinkage, glass transition, and all-atom structure of cross-linked polymers. The method bridges from SMILES to MD simulation trajectories in an automatic way, which shortens the time of building up cross-linked polymer reaction model and suitable for high-throughput computations.

Machine-Learning-Assisted Design of Highly Tough Thermosetting Polymers

Despite advances in machine learning for accurately predicting material properties, forecasting the performance of thermosetting polymers remains a challenge due to the sparsity of historical experimental data and their complicated crosslinked structures. We proposed a machine-learning-assisted materials genome approach (MGA) for rapidly designing novel epoxy thermosets with excellent mechanical properties (high tensile moduli, high tensile strength, and high toughness) through high-throughput screening in a vast chemical space. Machine-learning models were established by combining attention- and gate-augmented graph convolutional networks, multilayer perceptrons, classical gel theory, and transfer learning from small molecules to polymers. Proof-of-concept experiments were carried out, and the structures designed by the MGA were verified. Gene substructures affecting the modulus, strength, and toughness were also extracted, revealing the mechanisms of polymers with high mechanical properties. The developed strategy can be employed to design other thermosetting polymers efficiently.

Tailoring Interfacial Adhesion between PBAT Matrix and PTFE-Modified Microcrystalline Cellulose Additive for Advanced Composites

Cellulose materials have the potential to serve as sustainable reinforcement in polymer composites, but they suffer from challenges in improving interfacial compatibility with polymers through surface modification. Here, we propose adjusting the interfacial compatibility between microcrystalline cellulose (MCC) and poly (butylene adipate-co-terephthalate) (PBAT) through the strategy based on surface energy regulation. Mechanical ball milling with polytetrafluoroethylene (PTFE) powder was used to simultaneously pulverize, and surface modify MCC to produce MCC sheets with different surface energy. The modified MCC was used to reinforce PBAT composites by simple melt blending. The surface morphology, surface energy of MCC, and the amount of friction transferred PTFE during ball milling were characterized. The mechanical performance, composite morphology, crystallization behavior and dynamic thermomechanical analysis of the composites were investigated. The interfacial adhesion strength of composites closely relates to the surface energy of modified MCC. When the surface energy of MCC is closer to that of the PBAT matrix, it exhibits the better interfacial adhesion strength, resulting in the increased mechanical properties, crystallization temperature, storage modulus, and loss modulus. This work provides effective strategy for how to design fillers to obtain high-performance composites.

A Review of Cellulose Coarse-Grained Models and Their Applications

Cellulose is the most common biopolymer and widely used in our daily life. Due to its unique properties and biodegradability, it has been attracting increased attention in the recent years and various new applications of cellulose and its derivatives are constantly being found. The development of new materials with improved properties, however, is not always an easy task, and theoretical models and computer simulations can often help in this process. In this review, we give an overview of different coarse-grained models of cellulose and their applications to various systems. Various coarse-grained models with different mapping schemes are presented, which can efficiently simulate systems from the single cellulose fibril/crystal to the assembly of many fibrils/crystals. We also discuss relevant applications of these models with a focus on the mechanical properties, self-assembly, chiral nematic phases, conversion between cellulose allomorphs, composite materials and interactions with other molecules.