De-risking EPE encapsulants: Modeling polymer-polymer interfaces
Computational efforts of DuraMAT project investigating EPE encapsulants for solar modules.
Dedmon, Hannah Claire [Sandia National Laboratorie↗
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Extreme Nanoconfinement Dramatically Enhances Small Molecule Solubility in Nonpolar Polymers
Elucidating gas solubility in confined polymer systems addresses a fundamental gap in polymer physics and has important implications for gas barrier and separation technologies and polymer upcycling reactions. In this study, we examine the solubility of methanol and n-hexane in polystyrene and low-density polyethylene confined within the interstitial pores of disordered silica nanoparticle packings. Using capillary rise infiltration, these polymers are infiltrated into the nanoparticle packings. Gas solubility in these confined polymers is measured using a quartz crystal microbalance. Remarkably, confinement leads to a 10- to ∼100-fold increase in gas solubility. Systematic experiments reveal that pore size plays a dominant role in increasing solubility. In contrast, the molecular weight of the polymer and the surface wetting characteristics of the nanoparticles, achieved by hydrophobically modifying the nanoparticles, have minimal effects. By systematically varying penetrant polarity, polymer crystallinity, pore size, and nanopore surface chemistry, this study isolates geometric nanoconfinement as the dominant factor governing solubility enhancement in confined polymers. Atomistic simulations revealed that confinement and surface−polymer interactions both contribute to enhanced solubility, with polymer packing playing a significant role in modulating gas uptake. Here, these results suggest that the changes in the molecular arrangements of polymer segments underlie the observed trends. This study highlights the potential of confined polymers in engineering the separation performance of membranes and heterogeneously catalyzed polymer upcycling reactions.
alcohols↗
Influence of Rigidity–Hydration Coupling on Size-Dependent Diffusion in Hydrated Polymer Membranes
Selective ion transport in polymer membranes depends critically on how penetrant motion couples to polymer dynamics and hydration. Yet, the mechanistic interplay between polymer rigidity, water content, and penetrant size remains poorly understood, especially in the regime where the penetrant diameter, polymer Kuhn length, and correlation length are comparable. Here, we employ coarse-grained molecular dynamics simulations to systematically investigate penetrant diffusion in hydrated polymer networks across a broad range of water volume fractions, chain rigidities, and penetrant sizes. The results reveal a transition from a decoupled regime, where small penetrants diffuse nearly independently of polymer relaxation, to a coupled regime in which large penetrants require cooperative polymer motion for transport. Increasing polymer rigidity amplifies the sensitivity of diffusivity to hydration, particularly at low water content, leading to pronounced deviations from Stokes−Einstein scaling. Comparison with scaling theories and free-volume models shows that classical nanoparticle-based frameworks fail to capture this intermediate regime. To address this gap, we extend the Yasuda model to incorporate polymer rigidity through a single parameter that quantifies the dynamic contribution of chain stiffness to free-volume fluctuations. The resulting model collapses diffusivity data across all sizes, water contents, and rigidities, providing a unified description of penetrant transport in hydrated polymer matrices. Furthermore, these findings establish polymer rigidity as a key, tunable determinant of diffusion and offer a framework for interpreting size-dependent transport in ion-selective membranes.
diffusion↗
Machine learning inversion from small-angle scattering for charged polymers
We develop Monte Carlo simulations for uniformly charged polymers and a machine learning algorithm to interpret the intra-polymer structure factor of the charged polymer system, which can be obtained from small-angle scattering experiments. The polymer is modeled as a chain of fixed-length bonds, where the connected bonds are subject to bending energy, and there is also a screened Coulomb potential for charge interaction between all joints. The bending energy is determined by the intrinsic bending stiffness, and the charge interaction depends on the interaction strength and screening length. All three contribute to the stiffness of the polymer chain and lead to longer and larger polymer conformations. The screening length also introduces a second length scale for the polymer besides the bending persistence length. To obtain the inverse mapping from the structure factor to these polymer conformation and energy-related parameters, we generate a large data set of structure factors by running simulations for a wide range of polymer energy parameters. We use principal component analysis to investigate the intra-polymer structure factors and determine the feasibility of the inversion using the nearest neighbor distance. We employ Gaussian process regression to achieve the inverse mapping and extract the characteristic parameters of polymers from the structure factor with low relative error.
36 MATERIALS SCIENCE↗
Polymer grafted aramid nanofiber reinforces immiscible waste polypropylene/poly(ethylene terephthalate)
Polypropylene (PP) and poly(ethylene terephthalate) (PET) are plastics commonly used for packaging because of their excellent barrier and mechanical properties. The properties of these plastics are often diminished after mechanical recycling, inevitably causing down-cycling. Furthermore, this problem is exacerbated when different kinds of polymers mix. Aramid nanofibers have the potential to improve the mechanical properties of polymers due to their excellent mechanical properties but their poor dispersion in polymers is a challenge. Grafting polymers onto nanofibers can help address this challenge. In this work, different loading levels (1%, 2%, and 5%) of polymer grafted aramid nanofibers (ANFs) are blended with waste PP/PET (90/10), simulating a PP waste stream containing traces of PET contaminants. Scanning electronic microscopy, rheology, and differential scanning calorimetry results show the affinity of PP functionalized aramid nanofibers (PP_ANF) towards the PP matrix. At 1 wt% of the nanofiber, the size of the PET droplets in the PP matrix of the PP_ANF blend range from 0.2 to 2.0 μm while that of unmodified ANF and PET_ANF blends are in the range of 0.1–6.2 and 0.5–7.4 μm, respectively. In summary, polymer grafted ANFs have the tendency of improving properties of its like polymers due to similarity in the grafting polymer and the polymer matrix.
36 MATERIALS SCIENCE↗
Critical role of polymer-ceramic ion exchange for high conductivity composite electrolytes
Polymer-ceramic composites offer a path to enhance the transport and mechanical properties of solid electrolytes. However, an in-depth understanding of the extent and role of ion transport along and across polymer-ceramic interfaces in these systems is lacking. We have recently shown that Li-conducting Li 0.11 Na 0.24 K 0.02 La 0.43 TiO 2.82 (LMTO) nanorods can be prepared by a molten flux method, and the addition of 30–50 weight (wt.)% LMTO to a bis[(trifluoromethyl)sulfonyl]imide-vinyl ethylene carbonate-based single-ion conducting (SIC) polymer electrolyte leads to a two-fold enhancement in Li-ion conductivity, from 1.4 to 3.0 × 10 −5 S/cm at 30 °C. In the present study, we use NMR methods to identify the Li-ion transport pathways and determine the timescale of chemical exchange between the SIC polymer and LMTO ceramic components. Tracer exchange NMR indicates preferential transport through the polymer or polymer-interfacial regions, and exchange spectroscopy (EXSY) and a new isotope exchange method reveal negligible Li exchange between the SIC polymer and LMTO ceramic up to several days. Here, LMTO nanorods act as a passive filler. Our results further highlight that significant (e.g., 10- or 100-fold) conductivity enhancements in composite electrolytes can only be achieved 1) with ionically-conductive fillers, and 2) when both the ceramic and polymer components actively participate in long-range transport. For this, fast interfacial ion exchange is needed. In conclusion, this leads us to introduce a critical interfacial ion exchange time to evaluate whether a filler actively contributes to conduction in a composite electrolyte, and screen for promising polymer-ceramic pairings to accelerate the development of high conductivity solid electrolytes.
Battery, Solid electrolyte↗
Polymers from Levoglucosenone and Other Anhydrosugars (CRADA Final Report)
The goal of this work is to identify promising drop-in or novel polymers that can be produced from levoglucosenone (LGO), CyreneTM, or other anhydrous sugars. LGO is a potentially important feedstock for polymers produced from renewable sources and can be produced in high yields by the company Circa from the pyrolysis of cellulose and biomass. NLR has a long history with anhydrosugars, pyrolysis and biomass-based polymers and has recently developed machine learning (ML) tools for predicting polymer properties. The DOE has recently supported efforts to identify coproducts from pyrolysis of biomass and their use in the production of performance advantaged polymers. DOE is also supporting the development of ML and molecular modeling for predicting and understanding polymer properties. NLR will leverage this expertise and experience to map out the pathways to polymers from LGO, use ML to identify the properties of novel polymers and estimate the market application space. From this effort NLR will deliver a summary report that outlines the most promising pathways based on quantitative and qualitative metrics for producing polymers from LGO.
09 BIOMASS FUELS↗
Rewritable Surface‐Grafted Polymer Brushes with Dynamic Covalent Linkages
Abstract Surface grafting of polymer brushes drastically modifies surface properties, including wettability, compatibility, responsiveness, etc. A broad variety of functionalities can be introduced to the surface via different types of polymers. Bringing together properties of two or more types of polymer brushes to one surface opens up even more possibilities in brush‐modified materials. However, while it is generally feasible to introduce several chemical compositions along the brushes via copolymerization, it is challenging to vary the types of polymer brushes along a surface. Although previous studies have demonstrated binary brushes via orthogonal polymerization techniques or partial deactivation/regrafting, they commonly limit the number of polymer types to two. Here, we propose a strategy to introduce dynamic covalent diketoenamine linkages at the root of polymer brushes. The grafting density could be precisely tuned during surface functionalization. The surface‐anchored polymer brushes were cleaved by the addition of small molecule amines. New polymer brushes can be regrafted from the surface following refunctionalization of exposed sites. The maneuverability allows tuning of the types and densities of the polymer brushes, pointing the way to the preparation of a new generation of well‐defined brush‐modified materials with mixed grafts, with potential applications in the design of smart materials and surfaces.
Cui, Feichen↗
Machine learning-assisted profiling of a kinked ladder polymer structure using scattering
Ladder polymers consisting of fused rings in the backbone have very limited conformational freedom, which results in very different properties from traditional linear polymers. However, accurately determining their size and chain conformations from solution scattering remains a challenge. Their chain conformations of kinked ladder polymers are largely governed by the structures and relative orientations or configurations of the repeat units, unlike conventional polymer chains whose bending angles between repeat units follow a unimodal Gaussian distribution. Meanwhile, traditional scattering models for polymer chains do not account for these unique structural features. This work introduces a novel approach that integrates machine learning with Monte Carlo simulations to construct a model that can describe the geometry of a type of kinked CANAL ladder polymers. We first develop a Monte Carlo simulation model for sampling the configuration space of CANAL ladder polymers, where each repeat unit is modeled as a biaxial segment. Then, we establish a machine learning-assisted scattering analysis framework based on Gaussian Process Regression. Finally, we conduct small-angle neutron scattering experiments on a CANAL ladder polymer solution to apply our approach. Our method uncovers structural features of such ladder polymers that conventional methods fail to capture.
Ding, Lijie [Oak Ridge National Laboratory (ORNL),↗
Local Chain Dynamics in Sequence-Controlled Polymers as a Tunable Handle for Rare Earth Sequestration
Chain dynamics govern the intricate behaviors of proteins, underpinning functions such as catalysis, recognition, and stimulus response, and are an increasingly appreciated aspect of structure–function relationships. Analogously, manipulating chain dynamics and structure in abiotic polymers via sequence control is an exciting, yet underexplored, strategy for improving material functions. In this work, we report a systematic study relating the sequence of polymeric sequestrants to their structure and dynamics, as well as to their binding affinity and selectivity for model substrates, rare earth elements (REEs). A series of sequence-controlled polymers with metal chelating, solubilizing, and structure forming monomers was synthesized via multiblock polymerization, yielding compositionally identical polymers with spectroscopically resolved domains and distinct morphologies. Using a combination of small-angle X-ray scattering and 19 F NMR relaxometry measurements, we connected differences in polymer structure and dynamics to polymer sequence variables such as the patchiness (density) of the structure forming monomer and the location of the chelating monomer. Furthermore, we found that, relative to calcium, all polymers in the series collapse more and have slower dynamics when binding REEs (lanthanum and lutetium) , though the extent of these effects were sequence-dependent and localized to specific domains within the polymer. Notably, sequence-controlled polymers that exhibited the largest conformational and dynamic changes upon binding REEs also bound REEs with the greatest affinity and modest selectivity. Collectively, these results correlate monomer patterning with dynamics, morphology, and REE binding performance en route to the development of efficient and selective macromolecular chelators.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Fabrication of Piezoelectric Polymer and Metal–Organic Framework Composite Thin Films Using Solution Shearing
Polymer-metal–organic framework (polymer-MOF) composites have garnered significant interest as polymers can enhance the processability and industrial applicability of MOFs. Thin films of these composites are particularly attractive for applications in sensing, separations, and flexible electronics. Solution shearing, a meniscus-guided coating technique, has emerged as a scalable process for fabricating thin films of MOFs, and can produce large-area films within minutes. In this study, we utilized solution shearing to fabricate composite thin films of a MOF UiO-66 and a piezoelectric polymer poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)), investigating how polymer concentration during MOF synthesis and composite formation influences thin film properties, including crystallinity, surface coverage, and piezoelectric performance. Additionally, solid-state NMR spectroscopy was utilized to probe the interactions between P(VDF-TrFE) and UiO-66 in the composite. Evidence from solid-state NMR indicated polymer-MOF interactions, suggesting that the polymer strands are in close proximity to the UiO-66 pores, supporting a mixed surface coating and pore infiltration model. Furthermore, incorporating P(VDF-TrFE) enhanced the film’s areal coverage from 70% to 100%. While the thermal conductivity remained essentially unchanged, the composite film showed an improved piezoelectric effect. The composite with 91 wt % P(VDF-TrFE) exhibited the highest output voltage of 9.1 V and a sensitivity of 0.26 V/N under applied pressure. This work demonstrates the potential of solution shearing as a scalable technique for fabricating polymer-MOF composite thin films.
P(VDF-TrFE)↗
Evolved Gas Analysis–Mass Spectrometry Exposes Polymer Network Structures
Polymer network structures in epoxy thermosets play an important role in the final thermoset material properties. However, analytical characterization of these network structures is difficult due to their amorphous nature. In this work, the application of evolved gas analysis–mass spectrometry (EGA-MS) to characterize the polymer network structures of bisphenol A (BPA)-based thermosets is demonstrated. Analytical characterization of the polymer network structures is accomplished by monitoring the Product-Specific Kinetics (PSK) of BPA monomer formation during thermal degradation investigations. We relate observed differences in the activation energy (E a ) of BPA monomer formation to the local packing environment around the BPA monomer units within the polymer network. Variations in the local environment related to the polymer networks manifest qualitatively as broadening in the thermal profile of the BPA monomer evolution and quantitatively as changes in the activation energy (E a ). Three BPA thermoset formulations were investigated; two amine-cured thermoset with 4,4′-diaminodiphenylmethane (DDM) or poly(propylene glycol) bis(2-amino-propyl ether) (PPG400) and a homopolymerized thermoset via curing with Epikure 3253 catalyst (3253). Results revealed that the 3253 thermoset contained two distinct packing densities in the polymer network, while DDM and PPG400 thermosets had uniform distributions of packing densities. Results from the DDM thermoset revealed a gradually decreasing E a , while the apparent E a of PPG400 was consistent over the entire degradation. Furthermore, these differences in E a were concluded to stem from the flexibility of the corresponding polymer networks and the ability of the network components to rearrange and occupy formed voids. Due to the minimal sample required for analysis (100–200 μg), this EGA-MS technique has great potential for postproduction evaluation of composite parts to identify changes in the polymer networks from use and aging, which could signal compromised performance.
Degradation↗
Tunable Nanoscale Structure via Divalent Ion Identity in Charged-Neutral Polymer Blends
Charged-neutral polymer blends, wherein an ioncontaining polymer is blended with a neutral polymer, are potential candidates for battery electrolytes due to their improved ion transport properties and electrochemical stability. Though electrostatic interactions in charged polymer blends can theoretically stabilize ordered nanostructures analogous to those observed in neutral block copolymers, direct experimental evidence remains limited. Here, we investigate the effects of divalent cation identity on the nanoscale morphology of charged-neutral polymer blends composed of poly(ethylene oxide) (PEO) and Mg 2+ or Ca 2+ ioncontaining polymers, poly[3-(methylacryloxy)propylsulfonyl-1-(trifluoromethanesulfonylimide)] (P(Mg(MTFSI) 2 ) or P(Ca- (MTFSI) 2 ). By tuning the size of the divalent counterion, we are able to precisely tune the ion solvation between the free cation and PEO, which acts as a solvent in this system. Differential scanning calorimetry (DSC) and small-angle X-ray scattering (SAXS) measurements reveal that Mg 2+ and Ca 2+ ions induce distinct structural behavior. In both systems, the blends become more miscible as the concentration of ion-containing polymer is increased indicated by increased suppression of PEO crystallinity. At the highest concentrations of P(Mg(MTFSI) 2 ), the blends undergo microphase separation and generate nanostructures with shortranged ordering. In contrast, calcium ions, which are more readily solvated by PEO, produce more homogeneous blends characterized by a single glass-transition temperature and featureless SAXS data. The results demonstrate the novel experimental confirmation that charged-neutral polymer blends can undergo microphase separation and show that counterion identity can be exploited as a design parameter to control nanoscale morphology.
Ions↗
High-performance n-Type Polymers Based on Multiple Electron-withdrawing Groups Decorated ( E )-1,2-Di(thiophen-2-yl)ethene Building Blocks
The performance of n-type conjugated polymers lags far behind that of p-type polymers, which significantly restricts the development of organic electronics. The (E)-1,2-di(thiophen-2-yl)ethene (TVT) unit, owing to its unique advantages, has been widely applied in the design of p-type polymer semiconductors. Previous studies have demonstrated that introducing electron-withdrawing groups can lower the frontier orbital energy levels of polymers and enhance electron injection/transporting capabilities. Based on this, we proposed incorporating multiple electronwithdrawing groups, such as amide groups, fluorine atoms, and cyano groups, into the polymer backbones of TVT-based polymer to facilitate the electron transport. Here, we successfully designed and synthesized the polymers TVTDA-4FTVT and TVTDA-2F2CNTVT. Both polymers exhibited low frontier orbital energy levels. Due to its significantly higher crystallization tendency and favorable intermolecular packing structure, the organic field-effect transistor (OFET) device based on TVTDA-4FTVT demonstrated an electron mobility one order of magnitude higher than that of TVTDA-2F2CNTVT. TVTDA-4FTVT showed the highest electron mobility of 0.87 cm 2 ·V −1 ·s −1 , while TVTDA-2F2CNTVT exhibited the highest electron mobility of 0.049 cm 2 ·V −1 ·s −1 . Owing to its deeper lowest unoccupied molecular orbital (LUMO) level, the OFET devices based on TVTDA-2F2CNTVT showed good air stability after being placed in a natural environment for 15 d.
36 MATERIALS SCIENCE↗
Dynamic Strength and Equation of State of Epon 828 and Diethanolamine (DEA) Polymer Epoxy Under Shock Loading
Polymers are increasingly utilized in engineering applications that can experience high loading rates, necessitating increased understanding of their response under such conditions. The tamped Richtmyer-Meshkov Instability (RMI) method was used to characterize the equation of state and dynamic strength of the polymer Epon 828 cured with Diethanolamine (DEA). Plate impact experiments that drove a uniaxial shock compression wave across a sinusoidally corrugated metal-polymer interface were performed to generate shock stresses from 4-12 GPa and strain rates of approximately 1/s in the polymer. X-ray phase contrast imaging recorded the shock motion in the polymer and subsequent interface evolution. Analysis of this data yielded the polymer equation of state and, in conjunction with numerical modeling, the dynamic strength. The equation of state was validated against one-dimensional plate impact experiments from existing literature. The dynamic strength was compared to prior data for Epon 828 and related polymers at lower strain rates and found to exhibit significant strain rate and pressure-hardening effects. The strength of the Epon 828 polymer at 10 6 1/s was found to be approximately 1.5 GPa, suggesting that it is comparable to the strength of high strength metals at these dynamic conditions.
Equation of state↗
ToPolyAgent: AI agents for coarse-grained bead-spring topological polymer simulations
We introduce ToPolyAgent, a multi-agent AI framework for performing coarse-grained molecular dynamics (MD) simulations of topological polymers through natural language instructions. By integrating large language models (LLMs) with domain-specific computational tools, ToPolyAgent supports both interactive and autonomous simulation workflows across diverse polymer architectures, including linear, ring, brush, and star polymers, as well as dendrimers. The system consists of four LLM-powered agents: a Config Agent for generating initial polymer–solvent configurations, a Simulation Agent for executing LAMMPS-based MD simulations and conformational analyses, a Report Agent for compiling markdown reports, and a Workflow Agent for streamlined autonomous operations. Interactive mode incorporates user feedback loops for iterative refinements, while autonomous mode enables end-to-end task execution from detailed prompts. We demonstrate ToPolyAgent's versatility through case studies involving diverse polymer architectures under varying solvent conditions, thermostats, and simulation lengths. Furthermore, we highlight its potential as a research assistant by directing it to investigate the effect of interaction parameters on the linear polymer conformation, and the influence of grafting density on the persistence length of the brush polymer. By coupling natural language interfaces with rigorous simulation tools, ToPolyAgent lowers barriers to complex computational workflows and advances AI-driven materials discovery in polymer science. It lays the foundation for autonomous and extensible multi-agent scientific research ecosystems.
Ding, Lijie [Oak Ridge National Laboratory (ORNL),↗
Superionic conduction in solid polymer electrolytes – decoupling ion transport from segmental relaxation
Solvent-free, solid polymer electrolytes (SPEs) are promising candidates for next-generation, electrochemical energy storage systems due to their potential to enhance safety and performance, enable flexible device architectures, and streamline manufacturing processes. Conventional SPEs suffer from limited ionic conductivity due to the strong coupling between ion transport and (generally slow) polymer segmental relaxation. The realization of superionic conduction in SPEs, in which ions move faster than the structural relaxation of the polymers, requires a shift in design principles to promote this type of decoupled ion motion. In this perspective, we discuss how polymer architecture, ion–ion correlations, and ion–polymer interactions can unlock superionic behavior. We highlight several key design features, such as crystallinity, bulky side groups, high molecular weight, and percolating ionic aggregation, with a focus on creating low-barrier transport pathways in various polymer systems. We also demonstrate opportunities to combine polymer chemistry and data science through high-throughput and automated screening approaches to reveal how phase behavior, ion dynamics, and ionic interactions govern transport, thereby potentially enabling data-driven discovery of superionic polymer electrolyte materials.
Yang, Mengying [Univ. of Delaware, Newark, DE (Uni↗
Solubility-limited depolymerization kinetics in the glycolysis of carbonyl-containing polymers
Chemical recycling of condensation polymers is often rationalized on the basis of the intrinsic reactivity of ester and carbonate functional groups. However, under heterogeneous conditions relevant to plastic waste processing and environmental degradation, bulk depolymerization rates often diverge from trends predicted by homogeneous chemistry. Here, we investigate how polymer–solvent compatibility, catalyst strength, and phase behavior govern the heterogeneous glycolysis of carbonyl-containing polymers. Using poly(ethylene terephthalate) (PET), glycol-modified PET (PETG), and bisphenol-A polycarbonate (PC) as model systems, we examine depolymerization kinetics at 180 °C with ethylene glycol and bisphenol A as diols under both amphoteric organosalt (TBD : MSA) and strong base (TBD) catalysis. Despite substantial differences in crystallinity and glycol uptake, PET and PETG depolymerize at comparable rates under organosalt catalysis, while PC depolymerizes significantly more slowly under identical conditions. Time-resolved molecular weight analysis and thermal characterization demonstrate that these rate differences do not arise from crystallinity, swelling, or inherent carbonyl reactivity, but instead reflect solubility-limited kinetics that constrain the transition from heterogeneous to homogeneous reaction regimes. When polymer solubility is low, depolymerization remains heterogeneous and slow; when solubility is enhanced—either through increased polymer–diol compatibility or stronger base catalysis—rapid homogeneous depolymerization is observed, reversing apparent reactivity trends. These results establish solubility and phase behavior as primary determinants of depolymerization kinetics in heterogeneous polymer recycling systems. By demonstrating how catalyst selection and solvent compatibility can expose or overcome solubility limitations, this work provides mechanistic insight to design more energy-efficient and selective chemical recycling processes. More broadly, these findings suggest that polymers with limited solvent or water compatibility may resist chemical degradation in the environment, favoring fragmentation and persistence as micro- and nanoplastics. Understanding solubility-controlled depolymerization offers a pathway toward more sustainable polymer design and end-of-life chemical recovery.
Watson-Sanders, Shelby [Department of Chemistry, U↗