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1. Phase transition in Polymer Derived Ceramics (PDCs) and its effect on mechanical response

   Ma, C. & (July 2021, Proceedings of the International Conference on Computational Methods)

   Polymer-derived ceramics (PDCs) which are fabricated through pyrolysis of preceramic polymers have attracted increasing attention due to their versatility in structure architecture design and property tailoring. Shaping at the polymer state using 3D printing allows the final ceramic products to exhibit arbitrary shapes and complex architectures that are otherwise impossible to achieve through traditional processing routes. The polymer-to-ceramic phase transition also provides additional space for mechanical property tailoring. A multiscale computational model is developed to explore the phase transition mechanisms and their correlations with processing parameters and mechanical response. Calculations in this work concern PMHS/DVB. Molecular dynamics simulations are carried out first to track the chemical reaction mechanisms and atomic structure evolution. The density of generated gas during pyrolysis is transferred to the finite element model (FEM) for coupled heat transfer and phase transition analysis. FEM calculations reveal the effect of pyrolysis temperature and heating rate on structure-level phase composition and elastic modulus. It is found that there is a threshold of pyrolysis temperature above which full ceramic phase is formed. Higher heating rate promotes ceramization and leads to higher elastic modulus. In addition, volume shrinkage is found to accelerate ceramic formation which slightly enhances material strength. 

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2. Enhancing organosilicon polymer-derived ceramic properties

   https://doi.org/10.1063/5.0085844  

   Loughney, Patricia A.; Mujib, Shakir B.; Pruyn, Timothy L.; Singh, Gurpreet; Lu, Kathy; Doan-Nguyen, Vicky (August 2022, Journal of Applied Physics)

   Polymer-derived ceramic (PDC) nanocomposites enable access to a large library of functional properties starting from molecular design and incorporating nanofillers. Tailoring preceramic polymer (PCP) chemistry and nanofiller size and morphology can lead to usage of the nanocomposites in complex shapes and coatings with enhanced thermal and mechanical properties. A rational design of targeted nanocomposites requires an understanding of fundamental structure–property–performance relations. Thus, we tailor our discussions of PCP design and nanofiller integration into single source precursors as well as pyrolytic processing for functionalizing PDCs. We also discuss the promises and limitations of advanced characterization techniques such as 4D transmission electron microscopy and pair distribution functions to enable in situ mapping structural evolution. The feedback loop of in situ monitoring sets the foundation for enabling accelerated materials discovery with artificial intelligence. This perspective assesses the recent progress of PDC nanocomposite research nanocomposites and presents scientific and engineering challenges for synthesis, fabrication, processing, and advanced characterization of PDC nanocomposites for enhanced magnetic, electrical, and energy conversion and storage properties. 

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3. Towards Porous Silicon Oxycarbide Materials: Effects of Solvents on Microstructural Features of Poly(methylhydrosiloxane)/Divynilbenzene Aerogels

   https://doi.org/10.3390/ma11122589  

   Aguirre-Medel, Susana; Jana, Prasanta; Kroll, Peter; Sorarù, Gian (December 2018, Materials)

   We investigate the impact of solvents on the microstructure of poly(methylhydrosiloxane)/divinylbenzene (PMHS/DVB) aerogels. The gels are obtained in highly diluted conditions via hydrosilylation reaction of PMHS bearing Si-H groups and cross-linking it with C=C groups of DVB. Polymer aerogels are obtained after solvent exchange with liquid CO2 and subsequent supercritical drying. Samples are characterized using microscopy and porosimetry. Common pore-formation concepts do not provide a solid rationale for the observed data. We postulate that solubility and swelling of the cross-linked polymer in various solvents are major factors governing pore formation of these PMHS/DVB polymer aerogels. 

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4. CONTROLLING ASSEMBLY OF POLYMER-GRAFTED NANOPARTICLES TO ENHANCE MECHANICAL PROPERTIES IN POLYMER NANOCOMPOSITE FILMS

   Zhang, Aria (May 2025, University of Pennsylvania)

   Polymer nanocomposite (PNC) films are of interest for many applications including electronics, energy storage, and advanced coatings. In phase-separating PNCs, the interplay between thermodynamic and kinetic factors governs the assembly of polymer-grafted nanoparticles (NPs), which directly influences material properties. Understanding how processing parameters affect the structure-property relationship of PNCs is important for designing advanced materials. This thesis provides insight by investigating a model PNC system of poly(methyl methacrylate)-grafted nanoparticles (PMMA-NPs) embedded in a poly(styrene-ran-acrylonitrile) (SAN) matrix. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) was developed to quantify the distribution of NPs within PMMA-NP/SAN films, enabling precise 3D reconstruction of PNC structures. Experimental parameters such as primary ion beam angle and charge compensation were optimized to enhance secondary ion signals and depth resolution. Upon annealing in the twophase region, PMMA-NP/SAN films exhibited phase separation and surface segregation, leading to morphological evolutions characterized by atomic force microscopy (AFM), ToF-SIMS, water contact angle measurements, and transmission electron microscopy. By systematically exploring the effects of film thickness on PNC structures, we found that film thickness-induced confinement reduces lateral phase separation and enhances NP dispersion at the surface. A dimensional crossover from three to two dimensions was observed around 240 nm, below which surface-directed spinodal decomposition is suppressed. As a result of phase separation and surface segregation, six distinct bulk morphologies were identified, allowing for the construction of a morphology map correlating film thickness and annealing time. Among these morphologies, percolated structures were found to improve mechanical properties such as hardness and reduced modulus, as measured using AFM nanoindentation. Notably, interconnected networks show the highest hardness and modulus at both low and high force loadings. Additionally, Marangoni-induced hexagonal honeycomb patterns were observed in spin-coated as-cast PMMA-NP/SAN films. By changing to a less volatile solvent, these defects were eliminated, demonstrating the importance of solvent selection in achieving uniform and high-quality thin films. These findings demonstrate the potential for precise control of surface-enriched and phase-separated microstructures in PNC films through tailoring processing conditions. This thesis advances the understanding of processing-structure-property relationships in PNCs, providing a foundation for designing highly functional materials with broad industrial applications. 

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5. Predicting Polymers’ Glass Transition Temperature by a Chemical Language Processing Model

   https://doi.org/10.3390/polym13111898  

   Chen, Guang; Tao, Lei; Li, Ying (June 2021, Polymers)

   We propose a chemical language processing model to predict polymers’ glass transition temperature (Tg) through a polymer language (SMILES, Simplified Molecular Input Line Entry System) embedding and recurrent neural network. This model only receives the SMILES strings of a polymer’s repeat units as inputs and considers the SMILES strings as sequential data at the character level. Using this method, there is no need to calculate any additional molecular descriptors or fingerprints of polymers, and thereby, being very computationally efficient. More importantly, it avoids the difficulties to generate molecular descriptors for repeat units containing polymerization point ‘*’. Results show that the trained model demonstrates reasonable prediction performance on unseen polymer’s Tg. Besides, this model is further applied for high-throughput screening on an unlabeled polymer database to identify high-temperature polymers that are desired for applications in extreme environments. Our work demonstrates that the SMILES strings of polymer repeat units can be used as an effective feature representation to develop a chemical language processing model for predictions of polymer Tg. The framework of this model is general and can be used to construct structure–property relationships for other polymer properties. 

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