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At least 73 records · Page 4

Correlations of norbornenyl crosslinked polyimide resin structures with resin thermo-oxidative stability, resin glass transition temperature and composite initial mechanical properties

PMR (polymerization of monomeric reactants) methodology was used to prepare 70 different polyimide oligomeric resins and 30 different unidirectional graphite fiber/polyimide composites. Monomeric composition as well as chain length between sites of crosslinks were varied to examine their effects on resin thermo-oxidative stability and glass transition temperature (Tg) of the cured/postcured resins. A linear correlation of decreasing 316 C resin weight loss/surface area versus (1) decreasing aliphatic content, or (2) increasing benzylic/aliphatic content stoichiometry ratio over a wide range of resin compositions was observed. An almost linear correlation of Tg versus molecular distance between the crosslinks was also observed. An attempt was made to correlate Tg with initial composite mechanical properties (flexural strength and interlaminar shear strength). However, the scatter in mechanical strength data prevented obtaining a clear correlation. Instead, only a range of composite mechanical properties was obtained at 25, 288, and 316 C. Perhaps more importantly, what did become apparent during the correlation study was (1) the PMR methodology could be used to prepare composites from resins containing a wide variety of monomer modifications, (2) that these composites almost invariably provided satisfactory initial mechanical properties as long as the resins formulated exhibited satisfactory processing flow, and (3) that PMR resins exhibited predictable rates of 316 C weight loss/surface area based on their benzylic/aliphatic stoichiometery ratio.

Alston, William B.↗

Predictions of the glass transition temperature and viscosity of organic aerosols from volatility distributions

Abstract. Volatility and viscosity are important properties of organic aerosols (OA), affecting aerosol processes such as formation, evolution, and partitioning of OA. Volatility distributions of ambient OA particles have often been measured, while viscosity measurements are scarce. We have previously developed a method to estimate the glass transition temperature (Tg) of an organic compound containing carbon, hydrogen, and oxygen. Based on analysis of over 2400 organic compounds including oxygenated organic compounds, as well as nitrogen- and sulfur-containing organic compounds, we extend this method to include nitrogen- and sulfur-containing compounds based on elemental composition. In addition, parameterizations are developed to predict Tg as a function of volatility and the atomic oxygen-to-carbon ratio based on a negative correlation between Tg and volatility. This prediction method of Tg is applied to ambient observations of volatility distributions at 11 field sites. The predicted Tg values of OA under dry conditions vary mainly from 290 to 339 K and the predicted viscosities are consistent with the results of ambient particle-phase-state measurements in the southeastern US and the Amazonian rain forest. Reducing the uncertainties in measured volatility distributions would improve predictions of viscosity, especially at low relative humidity. We also predict the Tg of OA components identified via positive matrix factorization of aerosol mass spectrometer (AMS) data. The predicted viscosity of oxidized OA is consistent with previously reported viscosity of secondary organic aerosols (SOA) derived from α-pinene, toluene, isoprene epoxydiol (IEPOX), and diesel fuel. Comparison of the predicted viscosity based on the observed volatility distributions with the viscosity simulated by a chemical transport model implies that missing low volatility compounds in a global model can lead to underestimation of OA viscosity at some sites. The relation between volatility and viscosity can be applied in the molecular corridor or volatility basis set approaches to improve OA simulations in chemical transport models by consideration of effects of particle viscosity in OA formation and evolution.

54 ENVIRONMENTAL SCIENCES↗

Leveraging the Polymer Glass Transition to Access Thermally Switchable Shear Jamming Suspensions

Suspensions of polymeric nano-and microparticles are fascinating stress-responsive material systems that, depending on their composition, can display a diverse range of flow properties under shear, such as drastic thinning, thickening, and even jamming (reversible solidification driven by shear). However, investigations to date have almost exclusively focused on nonresponsive particles, which do not allow in situ tuning of the flow properties. Polymeric materials possess rich phase transitions that can be directly tuned by their chemical structures, which has enabled researchers to engineer versatile adaptive materials that can respond to targeted external stimuli. Reported herein are suspensions of (readily prepared) micrometer-sized polymeric particles with accessible glass transition temperatures (T g ) designed to thermally control their non-Newtonian rheology. The underlying mechanical stiffness and interparticle friction between particles change dramatically near T g . Capitalizing on these properties, it is shown that, in contrast to conventional systems, a dramatic and nonmonotonic change in shear thickening occurs as the suspensions transition through the particles' T g . This straightforward strategy enables the in situ turning on (or off) of the system's ability to shear jam by varying the temperature relative to T g and lays the groundwork for other types of stimuli-responsive jamming systems through polymer chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Explainability and extrapolation of machine learning models for predicting the glass transition temperature of polymers

Abstract Machine learning (ML) offers promising tools to develop surrogate models for polymers' structure–property relations. Surrogate models can be built upon existing polymer data and are useful for rapidly predicting the properties of unknown polymers. The accuracy of such ML models appears to depend on the feature space representation of polymers, the range of training data, and learning algorithms. Here, we establish connections between these factors for predicting the glass transition temperature (T g ) of polymers. Our analysis suggests linear models with fewer fitting parameters are as accurate as nonlinear models with many hidden and unexplainable parameters. Also, the performance of a monomer topology‐based ML model is found to be qualitatively identical to that of a physicochemical descriptor‐based ML model. We find that the ML models's performance in the extrapolative region is enhanced as the property range of the training data increases. Moreover, we establish newT g – polymer chemistry correlations via ML. Our work illustrates how ML can advance the fundamental understanding of polymer structure–property correlations and its efficacy for extrapolation problems.

Polymer Science↗

Effect of thermal history on mechanical properties of polyetheretherketone below the glass transition temperature

The effect of thermal history on the tensile properties of polyetheretherketone neat resin films was investigated at different test temperatures (125, 25, and -100) using four samples: fast-quenched amorphous (Q); quenched, then crystallized at 180 C (C180); slowly cooled (for about 16 h) from the melt (SC); and air-cooled (2-3 h) from the melt (AC). It was found that thermal history significantly affects the tensile properties of the material below the glass transition. Fast quenched amorphous films were most tough, could be drawn to greatest strain before rupture, and undergo densification during necking; at the test temperature of -100 C, these films had the best ultimate mechanical properties. At higher temperatures, the semicrystalline films AC and C180 had properties that compared favorably with the Q films. The SC films exhibited poor mechanical properties at all test temperatures.

Cebe, Peggy↗

Molecular dynamics simulations for glass transition temperature predictions of polyhydroxyalkanoate biopolymers

Polyhydroxyalkanoates (PHAs) represent an emerging class of biosynthetic and biodegradable polyesters that exhibit considerable potential to replace petroleum-based plastics towards a sustainable future. Despite the promise, general structure–property mappings within this class of polymers remain largely unexplored. An efficient exploration of this vast chemical space calls for the development and validation of predictive methods for accurate estimation of a diverse range of properties for PHA-based polymers. Towards this aim, we present and validate in this work the results of our molecular dynamics (MD) simulation based approach aimed at predicting glass transition temperatures (T g ) of PHA-based polymers. Since generally available and widely used polymer forcefields exhibit a relatively poor performance for T g predictions, we have developed a new forcefield by modifying the polymer consistent force field (PCFF) via refining a selected set of torsion potentials of the polymer backbone using accurate density functional theory (DFT) computations. After carefully assessing the dependence of critical simulation parameters, such as, polymer chain length, number of polymer chains, supercell size, and thermal quenching rate used in the simulation, the applicability and transferability of the modified PCFF (mPCFF) is demonstrated by directly comparing the computed T g predictions of various polymers with different chemistries, polymer side chain lengths and functional groups forming the polymer side chains against the respective experimentally measured values. Furthermore, the transport properties such as self-diffusion coefficient and viscosity are computationally determined and their well-known correlation with the target properties is demonstrated. Lastly, we have employed the developed approach to predict T g values for a number of yet-to-be-synthesized PHA-based polymers with a diverse set of functional groups in the polymer side chains. The results are further rationalized by correlating the predicted T g values with the inter-chain H-bond formation tendencies of the different side chain functional groups. This work represents an important first step towards computationally guided design of PHA-based functional polymers and opens up new directions for a systematic investigation of composition- and configuration-dependent structure–property relationships in more complex binary and ternary copolymer systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting the influence of particle size on the glass transition temperature and viscosity of secondary organic material

Abstract Atmospheric aerosols can assume liquid, amorphous semi-solid or glassy, and crystalline phase states. Particle phase state plays a critical role in understanding and predicting aerosol impacts on human health, visibility, cloud formation, and climate. Melting point depression increases with decreasing particle diameter and is predicted by the Gibbs–Thompson relationship. This work reviews existing data on the melting point depression to constrain a simple parameterization of the process. The parameter $$\xi $$ ξ describes the degree to which particle size lowers the melting point and is found to vary between 300 and 1800 K nm for a wide range of particle compositions. The parameterization is used together with existing frameworks for modeling the temperature and RH dependence of viscosity to predict the influence of particle size on the glass transition temperature and viscosity of secondary organic aerosol formed from the oxidation of $$\alpha $$ α -pinene. Literature data are broadly consistent with the predictions. The model predicts a sharp decrease in viscosity for particles less than 100 nm in diameter. It is computationally efficient and suitable for inclusion in models to evaluate the potential influence of the phase change on atmospheric processes. New experimental data of the size-dependence of particle viscosity for atmospheric aerosol mimics are needed to thoroughly validate the predictions.

36 MATERIALS SCIENCE↗

Composition and Configuration Dependence of Glass-Transition Temperature in Binary Copolymers and Blends of Polyhydroxyalkanoate Biopolymers

Polyhydroxyalkanoates (PHAs), a promising class of biomaterials, have gained considerable attention to replace petroleum-based plastics owing to their excellent biocompatibility and biodegradability. Homopolymers of PHA suffer from poor tunability in thermal and mechanical properties. Going from homopolymers to copolymers, the design space can be substantially enhanced by combining two or more monomers in different compositions (i.e., relative ratios of the different monomers) and configurations (i.e., relative positions of the different monomers in the polymer backbone) leading to a substantially large chemical space where application-specific optimization for the targeted functionality can be performed. However, this composition and configuration dependence of properties in the vast PHA copolymer chemical space remains largely unexplored. In this contribution, further building on our past work with PHA homopolymers, we systematically explore these chemical trends for glass-transition temperature (Tg) in PHA copolymers and blends. Overall, our molecular dynamics simulations, utilizing a previously validated force field for PHAs, suggest that these trends are largely governed not only by the homopolymer Tg values but also configuration-dependent interchain interactions in the copolymer system. In particular, our results indicate that the configuration-dependent variation in the target property at a fixed composition can be significant in the presence of hydrogen-bond-forming monomers. These qualitative observations are further rationalized by quantitatively analyzing various closely related atomic level descriptors of copolymers and blends such as monomer mobility, number of hydrogen bonds, and pair correlation functions. The findings presented in this work help to develop a deeper atomistic-level understanding of thermomechanical behavior of PHA-based copolymers and can potentially guide the rational design of biopolymers as environmental-friendly functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Low-Cost, High Glass-Transition Temperature, Thermosetting Polyimide Developed

PMR-15 polyimide, developed in the mid-1970's at the NASA Lewis Research Center, is recognized as a state-of-the-art high-temperature resin for composite applications in the temperature range of 500 to 550 F (260 to 288 C). PMR-15 offers easy processing and good property retention at a reasonable cost. For these reasons, it is widely used in both military and commercial aircraft engine components. Traditionally, polyimide composites have been designed for long-term use at 500 to 600 F over thousands of hours. However, new applications in reusable launch vehicles (RLV's) require lightweight materials that can perform for short times (tens of hours) at temperatures between 800 and 1000 F (425 and 538 C). Current efforts at Lewis are focused on raising the use temperature of polyimide composites by increasing the glass-transition temperature of the matrix resins. Achieving this dramatic increase in the upper use temperature without sacrificing polymer and composite processability is a major technical challenge.

Chuang, Kathy C.↗

Two-dimensional glass transition–like behavior of Janus particle–laden interface

Abstract Understanding the interactive behavior of Janus particles (JPs) is a growing field of research. The enhancement in binding energy, in comparison to homogenous particles, and the dual characteristic of JPs open up new possibilities for novel applications. In many such applications, interfacial materials become subjected to flows that produce dilational and shear stresses. Therefore, it is important to understand the impact that the Janus character brings to interfaces. In this work, we study the microstructure of two-dimensional (2D) JP monolayers formed at the air–water interface and examine the shear viscoelasticity with an interface rheometer that was adapted for in situ surface pressure control via a Langmuir trough. We extend concepts from bulk rheology to data obtained from interfacial rheology as a tool to understand and predict the monolayer’s viscoelastic behavior. Finally, by calculating the time relaxation spectrum from the measured 2D dynamic moduli, we conclude that a phenomenon similar to glass transition is taking place by analogy.

42 ENGINEERING↗

Non-Isochronal Behavior of Charge Transport at Liquid–Liquid and Liquid–Glass Transition in Aprotic Ionic Liquids

A reversible, first-order transition separating two liquid phases of a single-component material is a fascinating yet poorly understood phenomenon. Here, we investigate the liquid–liquid transition (LLT) ability of two tetraalkylphosphonium ionic liquids (ILs), [P 666,14 ]Cl and [P 666,14 ][1,2,4-triazolide], using differential scanning calorimetry and dielectric spectroscopy. The latter technique also allowed us to study the LLT at elevated pressure. We found that cooling below 205 K transforms [P 666,14 ]Cl and [P 666,14 ][Trz] from one liquid state (liquid 1) to another (the self-assembled liquid 2), while the latter facilitates the charge transport decoupled from structural dynamics. In contrast to temperature, pressure was found to play an essential role in the self-organization of a liquid 2 phase, resulting in different time scales of charge transport for rapidly and slowly compressed samples. Furthermore, τ σ (P LL ) was found to be much shorter than τ σ (T LL , P=atm), which constitutes the first example of non-isochronal behavior of charge transport at LLT. In turn, dielectric studies through the liquid–glass transition revealed the non-monotonic behavior of τ σ at elevated pressure for [P 666,14 ]Cl, while for [P 666,14 ][Trz] τ σ (P g ) was almost constant. These results highlight the diversity of liquid–liquid transition features within the class of phosphonium ionic liquids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Direct observation of a dynamical glass transition in a nanomagnetic artificial Hopfield network

Spin glasses, generally defined as disordered systems with randomized competing interactions, are a widely investigated complex system. Theoretical models describing spin glasses are broadly used in other complex systems, such as those describing brain function, error-correcting codes5 or stock-market dynamics. This wide interest in spin glasses provides strong motivation to generate an artificial spin glass within the framework of artificial spin ice systems. Here we present the experimental realization of an artificial spin glass consisting of dipolar coupled single-domain Ising-type nanomagnets arranged onto an interaction network that replicates the aspects of a Hopfield neural network. Using cryogenic X-ray photoemission electron microscopy (XPEEM), we performed temperature-dependent imaging of thermally driven moment fluctuations within these networks and observed characteristic features of a two-dimensional Ising spin glass. Specifically, the temperature dependence of the spin glass correlation function follows a power-law trend predicted from theoretical models on two-dimensional spin glasses. As a result, we observe clear signatures of the hard-to-observe rugged spin glass free energy in the form of sub-aging, out-of-equilibrium autocorrelations and a transition from stable to unstable dynamics.

36 MATERIALS SCIENCE↗