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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.
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.
3. Tailoring compositionally graded interface of 316L stainless steel to Al12Si aluminum alloy bimetallic structures via Additive Manufacturing

   https://doi.org/doi.org/10.1021/acsami.0c21478  

   Zhang, Yanning ; Bandyopadhyay, Amit ( February 2021 , ACS applied materials interfaces)

   316L stainless steel (SS) to Al12Si aluminum alloy structures were processed, tailoring the compositionally graded interface on a SS 316 substrate using a directed energy deposition (DED)-based additive manufacturing (AM) process. Applying such a compositionally graded transition on bimetallic materials, especially joining two dissimilar metals, could avoid the mechanical property mismatch. This study's objective was to understand the processing parameters that influence the properties of AM processed SS 316L to Al12Si bimetallic structures. Two different approaches fabricated these bimetallic structures. The results showed no visible defects on the as-fabricated samples using 4 layers of Al-rich mixed composition as the transition section. The microstructural characterization showed a unique morphology in each section. Both cooling rate and compositional variations caused microstructural variation. FeAl, Fe2Al5, and FeAl3 intermetallic phases were formed at the compositionally graded transition section. After stress relief heat-treatment of SS 316L/Al12Si bimetallic samples, diffused intermetallic phases were seen at the compositionally graded transition. At the interface, as processed, bimetallic structures had a microhardness value of 834.2 ± 107.1 HV0.1, which is a result of the FeAl3 phase at the compositionally graded transition area. After heat-treatment, the microhardness value reduced to 578.7 ± 154.1 HV0.1 due to more Fe dominated FexAlymore »phase formation. The compression test results showed that the non-HT and HT SS 316L/Al12Si bimetallic structures had a similar maximum compressive strength of 299.4 ± 22.1 MPa and 270.1 ± 27.1 MPa, respectively.« less
4. 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.
5. PRECISE 3D STRUCTURING OF POLYMER NANOCOMPOSITES USING TRIAXIAL MAGNETIC FIELDS

   Atescan, Yagmur ; Yamamoto, Namiko. ( January 2019 , Composites)

   Polymer nanocomposites have been sought after for their light weight, high performance (strength-to-mass ratio, renewability, etc.), and multi-functionality (actuation, sensing, protection against lightning strikes, etc.). Nano-/micro-engineering has achieved such advanced properties by controlling crystallinity, phases, and interfaces/interphases; hierarchical structuring, often bio-inspired, has been also implemented. While driven by the advanced properties of nanofillers, properties of polymer nanocomposites are critically affected by their structuring and interfaces/interphases due to their small size (< ~50 nm) and large surface area per volume. Measures of their property improvement by nanofiller addition are often smaller than theoretically predicted. Currently, application of these novel engineered materials is limited because these materials cannot often be made in large sizes without compromising nano-scale organization, and because their multi-scale structure-property relationships are not well understood. In this work, we study precise and fast nanofiller structuring with non-contact and energy-efficient application of oscillating magnetic fields. Magnetic assembly is a promising, scalable method to deliver bulk amount of nanocomposites while maintaining organized nanofiller structure throughout the composite volume. In the past, we have demonstrated controlled alignment of nanofillers with tunable inter-assembly distances with application of oscillating one-dimentional magnetic fields (~100s of G), by taking advantage of both magnetic attraction and repulsion.more »The low oscillation frequency (< 1 Hz) was tuned to achieve maghemite nanofiller alignment patterns, in an epoxy matrix, with different amount of inter-nanofiller contacts with the same nanofiller volume fraction (see Figure 1a). This work was recently expanded to three-dimensional assembly using a triaxial Helmholtz coil system (see Figure 1b); the system can apply the triaxial magnetic fields of varying magnitude (max. ±300G, ±250G, ±180G (x-y-z)) and frequency (0 to 1 Hz, ~0.1 Hz resolution) with controlled phase delay to the sample size of 1.5” x 2.5” x 3.5”(x-y-z). Two model systems are currently studied: maghemite nanofillers in an elastomer for magnetoactuation, and nickel-coated CNTs in an thermoset for mehcniacl and transport property reinforcement. The assembled nanofiller structures are currently characterized by microCT; microCT scan data (see Figure 1b) are segmented through a machine learning algorithm, and will be modeled for their transport properties using a Monte Carlo method. These estimated properties will be compared with the experimentally characterized mechanical, transport, and actuation properties, providing the structure-interphase-property relationships. In future, we plan to integrate these nanocomposites to CFRPs for interlaminar property reinforcement, possibly with an out-of-autoclave composite processing.« less