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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Effect of penetrant–polymer interactions and shape on the motion of molecular penetrants in dense polymer networks

The diffusion of dilute molecular penetrants within polymers plays a crucial role in the advancement of material engineering for applications such as coatings and membrane separations. The potential of highly cross-linked polymer networks in these applications stems from their capacity to adjust the size and shape selectivity through subtle changes in network structures. In this paper, we use molecular dynamics simulation to understand the role of penetrant shape (aspect ratios) and its interaction with polymer networks on its diffusivity. We characterize both local penetrant hopping and the long-time diffusive motion for penetrants and consider different aspect ratios and penetrant–network interaction strengths at a variety of cross-link densities and temperatures. The shape affects the coupling of penetrant motion to the cross-link density- and temperature-dependent structural relaxation of networks and also affects the way a penetrant experiences the confinement from the network meshes. The attractive interaction between the penetrant and network primarily affects the former since only the system of dilute limit is of present interest. These results offer fundamental insights into the intricate interplay between penetrant characteristics and polymer network properties and also suggest future directions for manipulating polymer design to enhance the separation efficiency.

Chemistry↗
DOE OSTI2020

On the Network Topology of Cross-Linked Acrylate Photopolymers: A Molecular Dynamics Case Study

A reactive molecular dynamics approach is used to simulate cross-linking of acrylate polymer networks. By employing the same force field and reactive scheme and studying three representative multifunctional acrylate monomers, we isolate the importance of the nonreactive moieties within these model monomers. Analyses of reactive trajectories benchmark the estimated gel points, cyclomatic character, and spatially resolved cross-linking tendencies of the acrylates as a function of conversion. The insights into the similarities and differences of the polymerization and resulting networks presented here suggest molecular mechanics as a useful tool in the rational design of photopolymerization resins.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Photo-Induced Charge Transfer of Fullerene and Non-Fullerene Conjugated Polymer Blends via Ab Initio Excited-State Dynamics

Organic conjugated polymers (CPs) are promising candidates for organic photovoltaic (OPV) devices due to their unique tunable mechanical and optoelectronic performance. Over the last decade, optoelectronic properties of narrow band gap CPs as a blend with acceptor units are largely optimized, which leads to noticeable progress in OPV technology. However, their power conversion efficiency is still lower than their organic counterparts (i.e., silicon), limiting their practical usage. In this study, we employ ab initio molecular dynamics to explore photo-induced charge transfer (CT) of the diketopyrrolopyrrole-based polymer as a blend with non-fullerene (i.e., ITIC) and fullerene (i.e., PCBM) acceptor units. The results of charge carrier dynamics induced by selected photoexcitation show that hole density redistribution in space is much faster than electron relaxation. We track the relaxation rates of charge carriers over time, where the derivative of the difference between the rate of electron and hole implies the current density at zero voltage. Furthermore, this can be utilized to characterize the CT performance of CPs blended with different acceptor units. Relaxation rate results indicate that CP blend with ITIC promises a better PV performance, illustrating that the current computational approach opens the door to determine bulk heterojunctions’ electronic performance for OPV devices and narrowing down the list of potential donor–acceptor candidates.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Data-Centric Development of Lignin Structure–Solubility Relationships in Deep Eutectic Solvents Using Molecular Simulations

Lignin is a natural source of aromatic chemicals with significant potential as an abundant, renewable feedstock for value-added products. Deep eutectic solvents (DES)–solvents composed of a hydrogen bond donor (HBD) and acceptor (HBA) in varying ratios–have emerged as a highly tunable class of solvents for lignin solubilization. However, the variety of possible DES compositions and limited molecular-scale understanding of lignin solubility makes solvent selection a challenge without laborious trial-and-error experimentation. To address these challenges, we use classical molecular dynamics (MD) simulations to study the interactions of lignin model compounds with various DES–water systems. Quantitative parameters (descriptors) were calculated by postprocessing the MD results and used to train a regression model that predicts experimentally determined solubilities of lignin model compounds. This approach revealed that the most important descriptors of solubility are the system temperature, solute hydrophilicity, and metrics quantifying hydrogen bonding. Maximizing the interactions between solute–HBD (hydrophobic group), water–HBD (hydrophilic group), and water–HBA molecules led to the highest model compound solubility. Our results support a hydrotropic mechanism in which extensive DES–water hydrogen bonding and favorable HBD interactions with the solute promote high solubility. We applied the regression model derived using model compounds to predict the solubility of representative lignin oligomers. The model predicted lignin oligomers’ solubilities in good agreement with experiments, indicating that the simulations of model compounds can be extended to predict the solubility of larger lignin compounds across a range of solvent compositions and temperatures. Furthermore, these findings provide new molecular-scale insight into lignin solubilization mechanisms and a new method for computationally screening potential solvent systems for lignin valorization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Self-assembly of a triply periodic continuous mesophase with Fddd symmetry in simple one-component liquids

Triply periodic continuous morphologies (networks) arising as a result of the microphase separation in block copolymer melts have so far never been observed self-assembled in systems of particles with spherically symmetric interaction. Here, we report a molecular dynamics simulation where two simple one-component liquids form upon cooling an equilibrium network with the Fddd space group symmetry. This complexity reduction in the liquid network formation in terms of the particle geometry and the number of components evidences the generic nature of this class of phase transition suggesting opportunities for producing these structures in a variety of new systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Discovery of Innovative Polymers for Next-Generation Gas-Separation Membranes using Interpretable Machine Learning

Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research on membrane technologies, design of new membrane materials remains a largely Edisonian process. To address this shortcoming, we demonstrate a generalizable, accurate machine-learning (ML) implementation for the discovery of innovative polymers with ideal separation performance. Specifically, multitask ML models are trained on available experimental data to link polymer chemistry to gas permeabilities of He, H2, O2, N2, CO2, and CH4. Here, we interpret the ML models and extract chemical heuristics for membrane design, through Shapley Additive exPlanations (SHAP) analysis. We then screen over nine million hypothetical polymers through our models and identify thousands of candidates that lie well above current performance upper bounds. Notably, we discover hundreds of never-before-seen ultrapermeable polymer membranes with O2 and CO2 permeability greater than 104 and 105 Barrer, respectively. These hypothetical polymers are capable of overcoming undesirable trade-off relationship between permeability and selectivity, thus significantly expanding the currently limited library of polymer membranes for highly efficient gas separations. High-fidelity molecular dynamics simulations confirm the ML-predicted gas permeabilities of the promising candidates, which suggests that many can be translated to reality.

Yang, Jason↗
DOE OSTI2025

In-Silico Design of Next Generation Cellulose-Derived Packaging Materials (CRADA Final Report)

Developing sustainable solutions for single-use packaging is an important objective to combat the environmental crisis of plastics pollution. Most embodiments of cellulose-based packaging materials, including CellophaneTM, are completely biodegradable in both terrestrial and marine environments. However, petroleum-derived alternatives offer some performance advantages for metrics such as moisture barriers and mechanical properties. This project leverages molecular dynamics simulation to investigate how molecular modifications to cellulose-based polymer assemblies impact their material properties. An important performance criterion for the modified materials was to retain biodegradability; thus, modifications by naturally occurring, biodegradable additives were the focus of this study. Specifically, we developed models with xylan and lignin of varying monomeric compositions into the cellulose matrix. The mechanical properties were investigated by performing stress-strain simulations, and the water barrier and hydrophobicity were investigated by simulating the water contact angle. Our findings indicate that the incorporation of xylan into the cellulose matrix tends to increase the mechanical properties with an optimal loading of ~27 wt%. We also predict that orienting the nanoscale directionality of the xylan chains such that they are perpendicular to the cellulose fibrils will dramatically increase mechanical strength. In contrast, the incorporation of lignin tends to weaken the composite at all loadings investigated. Simulations of water contact angle predicted that coating polymers on the surface of the cellulose assembly creates a more hydrophobic surface than incorporating them throughout the matrix. Of the coatings investigated, lignin resulted in the most hydrophobic surface, followed by pectin and keratin, which both imparted modest increases in hydrophobicity. Future experimental work done by Futamura will focus on designing material prototypes to capitalize on the predictions of performance enhancement obtained from molecular modeling. While substantial progress was made by the simulations performed in this project, there still exists a vast parameter space that we were unable to investigate, including branching, functional group decoration, and degree of polymerization of polymer additives. However, the methods developed in this initial investigation will facilitate more rapid evaluation of the impact of molecular characteristics on the performance of biopolymer composite materials and thereby accelerate future materials discovery efforts in this area.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Interfacial Response and Structural Adaptation of Structured Polyelectrolyte Thin Films

Ionizable block copolymers with distinctive block characteristics display the diversity crucial for the design of macromolecules for targeted applications. In contrast to van der Waals copolymers, their interfaces, which are critical to their function, consist of nanodomains, each of a different nature and thus unique interfacial behavior. Here, the interfacial response of a symmetric block copolymer with a sulfonated polystyrene polyelectrolyte center, tethered to polyethylene-r-propylene and terminated by poly(t-butyl styrene) is probed as polymer films are exposed to three polar solvents, water, propanol, and tetrahydrofuran (THF), using molecular dynamics simulations. Each of the solvents captures a distinctive interaction with the individual blocks. We find that at the film boundary, the interfacial response is initially dominated by that of the hydrophobic blocks to all solvents. At later times, the solvent distribution among the blocks, where water molecules associate predominantly with the sulfonated groups and propanol and THF reside at multiple different sites, determines the chemical composition and the polymer conformation at the interface. Altogether, these simulations provide the first direct molecular insight into the interfacial response of ionizable copolymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Developing the Science Basis for Understanding Polymer Encapsulant Degradation Mechanisms: DuraMAT 2.0 Final Project Report

Polymeric encapsulants are essential materials in photovoltaic modules, protecting sensitive electronics from the environment while providing mechanical integrity to the multilayered assembly. However, these polymeric materials are susceptible to degradation processes driven by the ingress of environmental species, ultraviolet radiation, thermal stresses, and mechanical loading. In this study, we employ a combined atomistic simulation and accelerated aging experimental approach to study the molecular-scale mechanisms of encapsulant degradation. Classical molecular dynamics simulations quantify the diffusion of environmental and degradation species through the polymer matrix, producing composition-specific diffusion coefficients. Reactive simulations characterize activation energy barriers and reaction rate constants for key chemical pathways. In parallel, thermal-desorption analyses coupled with mass spectrometry monitor the emergence and concentration profiles of degradation products under controlled stressor conditions. By integrating simulation and experiment, we establish quantitative correlations between polymer composition, species diffusivity, and chemical reactivity. We anticipate that these relations and quantitative values could serve as high-fidelity inputs to reaction-diffusion models, enabling physics-informed lifetime predictions and guiding the design of more durable encapsulant materials for solar energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Perpendicular crossing chains enable high mobility in a noncrystalline conjugated polymer

The nature of interchain π-system contacts, and their relationship to hole transport, are elucidated for the high-mobility, noncrystalline conjugated polymer C16-IDTBT by the application of scanning tunneling microscopy, molecular dynamics, and quantum chemical calculations. The microstructure is shown to favor an unusual packing motif in which paired chains cross-over one another at near-perpendicular angles. By linking to mesoscale microstructural features, revealed by coarse-grained molecular dynamics and previous studies, and performing simulations of charge transport, it is demonstrated that the high mobility of C16-IDTBT can be explained by the promotion of a highly interconnected transport network, stemming from the adoption of perpendicular contacts at the nanoscale, in combination with fast intrachain transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Thermodynamics and Structure of Poly[n]catenane Melts.

Motivated by recent achievements in the synthesis of interlocking polymers, the structural features of poly[n]catenanes, polymers composed entirely of interlocking rings (or macrocycles), are studied by extensive molecular dynamics simulations in the melt state. The degree of polymerization (number of links) is varied from n = 1 25 and the number of beads per macrocycle is varied from m = 15-50; the results are compared to linear chains of degrees of polymerization N = 15-175. The mechanical bonds in the system cause significant topological contributions to the pressure and potential energy density not seen in other polymer systems. The polymers themselves possess many unusual structural features at short and intermediate length scales, which can be attributed to density inhomogeneities along the polymer contour. Furthermore, the conformations of the individual macrocycles within poly[n]catenanes are quite different from those of ordinary ring polymers and depend on the topology of the macrocycle, that is, whether it is threaded by one ring (chain end) or two (chain center). At larger length scales, the poly[n]catenanes are conformationally similar to ideal linear chains, but unlike traditional (covalent) polymers, they are highly globular at low degrees of polymerization and are extremely flexible relative to their size, which inhibits interchain entanglement. Implications for poly[n]catenane material properties and synthesis are discussed.

Rauscher, Phillip M.↗
DOE OSTI2023

Solution Structure and Scaling Laws of Cylindrical and Tapered Bottlebrush Polymers

Bottlebrush polymers are a unique class of macromolecular architectures with a plethora of potential industrial and pharmaceutical applications that critically depend on the bottlebrush shape and dimensions. Here, a systematic series of 12 cylindrical and 12 cone-shaped (tapered) bottlebrush polymers with poly(tert-butyl acrylate) (PtBA) or polystyrene (PS) side chains were synthesized using the sequential addition of macromonomers ring-opening metathesis polymerization (SAM-ROMP) grafting-through method. Small-angle neutron scattering (SANS) studies on dilute solutions of the two types of bottlebrush polymers provided noninvasive characterization of their structural dimensions and chain conformations. Simulated SANS traces, generated using coarse-grained molecular dynamics simulations, reproduced the distinctive features observed in the experimental SANS signals and provided necessary validation for data modeling. The combined analysis of experimental and simulated SANS signals yielded key structural and conformational parameters, including the bottlebrush radius, length, and Kuhn length as well as the excluded volume parameter and the correlation length of the polymer side chains. Importantly, the obtained structural parameters followed well-defined scaling laws as a function of the backbone and side chain degrees of polymerization, as predicted by mean field theories. In conclusion, these findings provide clear experimental and computational evidence of the interdependence of structural and conformational properties in an important class of polymer architectures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Coordinated Multiscale Modeling and Synthesis of Novel Nanostructured Composite Membranes for Solar Fuels Generation (Final Report)

Generation of carbon-based liquid fuels from reduction of CO 2 using solar energy requires the development of improved membranes that provide good ionic conductivity and mechanical properties while minimizing the crossover of gases and reduction products. Using closely coordinated multiscale modeling, synthesis and characterization studies we propose to investigate and develop novel nanostructured composite membranes with applications to conversion of carbon dioxide to storable chemical fuels. The envisioned proton exchange membranes (PEMs) will be based on a support of self- assembling polymer-modified nanoparticles with controllable porosity and tortuosity. The use of a nanoparticle support will provide control of transport and mechanical properties of the membranes. Tuning the copolymer modification of nanoparticles (polymer architectures, brush grafting density) will allow to optimize the ion (proton) transport via the Grotthuss mechanism through narrow hydrated channels while minimizing crossover of gases and reaction products due to the high density of the grafted brush and use of a non-ionic conducting glassy polymers to fill spaces between polymer-grafted nanoparticles. In Phase I synthesis of the copolymers and their attachment to the nanoparticle support will be guided by multiscale simulations that include atomistic molecular dynamics and continuum-level transport simulations. The former will include reactive and non-reactive atomistic simulations that will provide key insight into nanoscale polymer morphology and ion/molecular transport mechanisms need to optimize the copolymer structure. The latter will provide insight into the role of nanoparticle self-assembly on the global transport of ionic and molecular species. The proton conduction and CO 2 /methanol permeability of the membranes will be experimentally characterized as well as simulated and will be correlated with morphology and polymer structure. Prototypes of optimal membranes will be fabricated and characterized at the end of the project. Successful development of improved nanostructured composite PEMs and demonstration of the simulation-guided materials-by-design paradigm will result in our ability to design and synthesize membranes for a wide variety of solar fuels generation and related electrochemical applications.

14 SOLAR ENERGY↗
DOE OSTI2021

Crystalline Supramolecular Polymers: Dynamics, Chirality, and Function

Inspired by biological systems, supramolecular polymers have emerged over the past three decades as an important way to form functional structures with potential to tune the internal order and dynamics and to create materials with the potential for responsiveness, reconfigurability, and recyclability. We focus here on several recent examples of ordered supramolecular polymers with a significant extent of internal order that results in crystalline molecular packing, or with dynamics that allow them to undergo structural reconfiguration. These examples highlight the spectrum of molecular mobility that the noncovalently bound constituents can experience. Furthermore, these materials have found interesting functions in their interaction with chiral biological systems and in their ability to form materials with interesting optoelectronic and photocatalytic behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Accelerated Sequence Design of Star Block Copolymers: An Unbiased Exploration Strategy via Fusion of Molecular Dynamics Simulations and Machine Learning

Star block copolymers (s-BCPs) have potential applications as novel surfactants or amphiphiles for emulsification, compatibilization, chemical transformations, and separations. s-BCPs have chain architectures where three or more linear diblock copolymer arms comprised of two chemically distinct linear polymers, e.g., solvophobic and solvophilic chains, are covalently joined at one point. The chemical composition of each of the subunit polymer chains comprising the arms, their molecular weights, and the number of arms can be varied to tailor the surface and interfacial activity of these architecturally unique molecules. Further, this makes identification of the optimal s-BCP design nontrivial as the total number of plausible s-BCP architectures is experimentally or computationally intractable. In this work, we use molecular dynamics (MD) simulations coupled with a reinforcement learning-based Monte Carlo tree search (MCTS) to identify s-BCP designs that minimize the interfacial tension between polar and nonpolar solvents. We first validate the MCTS approach for the design of small- and medium-sized s-BCPs and then use it to efficiently identify sequences of copolymer blocks for large-sized s-BCPs. The structural origins of interfacial tension in these systems are also identified by using the configurations obtained from MD simulations. Chemical insights into the arrangement of copolymer blocks that promote lower interfacial tension were mined using machine learning (ML) techniques. Overall, this work provides an efficient approach to solve design problems via fusion of simulations and ML and provides important groundwork for future experimental investigation of s-BCPs for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Toward the Prediction and Control of Glass Transition Temperature for Donor–Acceptor Polymers

Semiconducting donor–acceptor (D–A) polymers have attracted considerable attention toward the application of organic electronic and optoelectronic devices. However, a rational design rule for making semiconducting polymers with desired thermal and mechanical properties is currently lacking, which greatly limits the development of new polymers for advanced applications. Here, polydiketopyrrolopyrrole (PDPP)-based D–A polymers with varied alkyl side-chain lengths and backbone moieties are systematically designed, followed by investigating their thermal and thin film mechanical responses. The experimental results show a reduction in both elastic modulus and glass transition temperature (Tg) with increasing side-chain length, which is further verified through coarse-grained molecular dynamics simulations. Informed from experimental results, a mass-per-flexible bond model is developed to capture such observation through a linear correlation between Tg and polymer chain flexibility. Using this model, a wide range of backbone Tg over 80 °C and elastic modulus over 400 MPa can be predicted for PDPP-based polymers. This study highlights the important role of side-chain structure in influencing the thermomechanical performance of conjugated polymers, and provides an effective strategy to design and predict Tg and elastic modulus of future new D–A polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Charge state-dependent ion condensation near conjugated polymer backbones

Despite the technological appeal of polymeric organic mixed ionic/electronic conductors (OMIECs) for diverse applications, a deep understanding of the fundamentals of mixed charge transport in these materials, especially regarding the complex interplay between polymer, ion and solvent structure in determining transport, is lacking. Herein, extensive molecular dynamics (MD) simulations of a model OMIEC representing various electrochemically gated states are reported that reveal charge state-dependent counterion condensation. X-ray diffraction simulations based on the MD data predict a measurable change in the scattering intensity at the counterion absorption edge, indicative of counterion repositioning with charging. We leverage an operando resonant X-ray scattering technique to experimentally corroborate the simulated scattering and report excellent agreement between predicted and experimental data, confirming that counterions preferentially reside in the lamellar mid-plane of crystallites at low doping, and near the polymer backbone at higher doping. Driving forces for ion type-dependent spatial repositioning and implications thereof are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Scaling Field-Theoretic Simulation for Multicomponent Mixtures with Neural Operators

Multicomponent polymer mixtures are ubiquitous in biological self-organization but are notoriously difficult to study computationally. Plagued by both slow single molecule relaxation times and slow equilibration within dense mixtures, molecular dynamics simulations are typically infeasible at the spatial scales required to study the stability of mesophase structure. Polymer field theories offer an attractive alternative, but analytical calculations are only tractable for mean-field theories and nearby perturbations, constraints that become especially problematic for fluctuation-induced effects such as coacervation. Here, we show that a recently developed technique for obtaining numerical solutions to partial differential equations based on operator learning, neural operators, lends itself to a highly scalable training strategy by parallelizing per-species operator maps. We illustrate the efficacy of our approach on six-component mixtures with randomly selected compositions and that it significantly outperforms the state-of-the-art pseudospectral integrators for field-theoretic simulations, especially as polymer lengths become long.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗