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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 343 records · Page 19

Understanding the Influence of Chain Architecture on the Transport Quantities of Polymer Electrolytes with Covalently Bonded Anions

Here, we use a combination of experiments and coarse-grained molecular dynamics simulations to elucidate the structure–property relationships in polymer electrolytes obtained by the copolymerization of poly(vinyl ethylene carbonate─lithium styrene bis(trifluoromethanesulfonyl)imide) or p(VEC-LiSTFSI). Experiments show that the conductivity reduces with increasing anion (i.e., STFSI) fraction on the chain, and the cation transference number (t + ) is found to be dependent on the anion fraction. Furthermore, a significant fraction of unpolymerized VEC monomers are observed. Since it is inherently difficult to experimentally control the chain architecture and the amount of unpolymerized VEC in these systems, we perform coarse-grained molecular dynamics simulations on model polymer systems with different chain architectures to mimic the plausible experimental systems. Specifically, we look at the differences in transference numbers arising from (i) a random copolymer of VEC and STFSI monomers; (ii) a blend of VEC-STFSI copolymer with VEC monomers; and (iii) a ternary blend of the VEC homopolymer, STFSI homopolymers, and VEC monomers. The ternary blend model demonstrates the closest resemblance with the experimental transference numbers and diffusivities. The lithium diffusivity obtained from the coarse-grained models with VEC monomers (plasticizers) is about 1.5 times that of the model without VEC monomers, showing that the plasticizing effect of VEC monomers is modest. We rationalize the experimental observations based on aggregate and cluster analyses obtained from molecular simulations. This work reveals that polymer electrolyte chain architecture and plasticizers can critically influence the transport properties, and these parameters should be considered when designing single ion conducting polymeric electrolytes.

cluster distribution↗

Modeling phonons in nanomaterials

The vibrational properties of nanomaterials play fundamentally important roles in determining their stability and various functionalities, from rippling of otherwise flat two-dimensional (2D) monolayers to the extreme thermal transport behaviors observed in one-dimensional (1D) and 2D carbon-based systems. Here we discuss modeling efforts to understand how phonons in lower dimensional materials differ from those in bulk, and how these behaviors manifest in their unusual properties. In particular, this chapter gives a heavy focus to calculations of phonon dynamics, interactions, and lattice thermal transport in 1D chains and nanotubes, 2D monolayers, and van der Waals coupled bulk materials from first principles methods. This chapter will discuss important phonon calculation details related to nanomaterials with examples and discussions providing both historical and modern perspectives.

Lindsay, Lucas↗

Floquet product mode

Results are presented for the dynamics of edge modes in interacting Floquet Ising chains. It is shown that in addition to the quasistable 0 and π edge modes, a third long lived edge mode arising from the operator product of the 0 and π edge modes exists. Depending on the microscopic parameters, this Floquet product mode is shown to have a substantially longer lifetime than the individual 0 and π modes. This is triggered by a scattering process which converts a 0 mode into a π mode while scattering two bulk excitations. This process can lead to a rapid decay of both 0 and π mode without affecting the product mode.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Universal Kardar-Parisi-Zhang Dynamics in Integrable Quantum Systems

Although the Bethe ansatz solution of the spin-1/2 Heisenberg model dates back nearly a century, the anomalous nature of its high-temperature transport dynamics has only recently been uncovered. Indeed, numerical and experimental observations have demonstrated that spin transport in this paradigmatic model falls into the Kardar-Parisi-Zhang (KPZ) universality class. This has inspired the significantly stronger conjecture that KPZ dynamics, in fact, occur in all integrable spin chains with non-Abelian symmetry. Here, in this letter, we provide extensive numerical evidence affirming this conjecture. Moreover, we observe that KPZ transport is even more generic, arising in both supersymmetric and periodically driven models. Motivated by recent advances in the realization of SU(N)-symmetric spin models in alkaline-earth-based optical lattice experiments, we propose and analyze a protocol to directly investigate the KPZ scaling function in such systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Utilizing the deuterium-tritium fusion resonance to diagnose thermal runaway in igniting plasmas

For high-efficiency inertial confinement fusion implosions, it is predicted that a burning hot spot will successfully encompass all surrounding fuel and then transition into a thermal runaway where the internal energy increase from fusion occurs on a timescale faster than the expansion of the fuel is able to quench the fusion chain reaction after ignition occurs. Observation of this dynamic phase transition would indicate distinct burn properties and indicate an implosion's robustness. A technique for diagnosing the presence of thermal runaway from measurements of nuclear reaction history is presented. The technique is based on taking the logarithmic derivative of the nuclear reaction history, called the 𝛼 curve, and allowing a mathematical decoupling of the mass, volume, and thermal reactivity in the fusion reaction rate equation. During thermal runaway, where the thermal temperature dominates the burn dynamics, a maximum in the 𝛼 curve is found where there is a maximum in the first derivative of the thermal fusion reactivity, an effect to the deuterium-tritium (DT) fusion cross-section resonance. This provides a distinct signature related to the fundamental nature of the DT fusion nuclear resonance and signifies the transition into the fusion thermal instability. Impacts of charged particle transport on the effect are also assessed and the analytical formulas are compared and found to be in agreement with radiation hydrodynamic codes.

high-energy-density plasmas↗

Disruption Prediction and Avoidance in High Beta Long Pulse KSTAR Plasmas

This research is a concentrated and coordinated experimental and physics analysis program by a small U.S. team, focused on the topical area of “Long Pulse Control” as stated in the proposal solicitation. The overall goal of the research is to produce world-class analysis regarding forecasting and avoidance of disruptions in a long-pulse, superconducting tokamak at high stability parameters (e.g. normalized beta) with direct, quantifiable figures of merit (i.e. plasma disruption rate - “disruptivity”) and its reduction based on improved stability physics and control. The research targets the backbone of the problem – the basic, main issues – to produce this quantitative analysis by: (1) Creating and applying a new physics-based paradigm to understand how to eliminate disruptions: disruption event characterization, and event chain analysis – a direct manifestation of the approach suggested in the DOE Transients Report, (2) Ensuring that the components required to produce high-quality measurements and analysis needed for disruption event characterization for the tokamak in question (here, KSTAR) exist (e.g. pressure profile peaking, high-accuracy pitch angle data, compensated low frequency toroidal mode number n = 1 mode measurement) to create a primarily physics-based disruption forecasting capability, and (3) Addressing disruption avoidance for the first time in KSTAR by attacking primary disruption ‘event chains’, utilizing the most important associated plasma measurements (dynamic n = 1 field). The focus of this work will be avoidance of macroscopic instabilities, especially global modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Dynamic modeling and control of multibody mechanical systems which are structurally flexible

This paper concerns the dynamic modeling and control of multibody, open-chained, structurally flexible, mechanical systems where the bodies are connected by revolute joints. The equations of motion are formulated based on a matrix form of Lagrange's equations for inertial quasi-coordinates. Each body is treated as a substructure of the system. For the purposes of simulation and control, the equations of motion are separated into two sets of equations using a perturbation approach: one to describe large rigid-body motions of the articulated system and the other to describe small linear motions of the bodies about the large motions. A biologically natural control strategy is used for vibration suppression and tracking the prescribed motion.

Quinn, R. D.↗

Is a Malleable Active Site Loop the Key to High Substrate Promiscuity? Hybrid, Biocatalytic Route to Structurally Diverse Taxoid Side Chains with Remarkable Dual Stereocontrol

Abstract These studies reveal the first structure ofClostridium acetobutylicumalcohol dehydrogenase (CaADH), a protein exhibiting remarkable substrate promiscuity and stereochemical fidelity. The CaADH enzyme is utilized here for synthesizing 20 potential aryl isoserine side chains for the Taxotere family of tubulin‐binding chemotherapeutics. The approach involves dynamic reductive kinetic resolution (DYRKR) upon the corresponding α‐chloro‐β‐keto esters, showing high D‐synstereoselectivity, including those leading to the clinically relevant milataxel (Ar = 2‐furyl) and simotaxel (Ar = 2‐thienyl) side chains. Furthermore, various cross‐coupling chemistries performed on thep‐bromophenyl isoserine side chain significantly enhance the structural diversity of the taxoid side chain library obtained (16 additional taxoid side chains). The CaADH structure is notable: (i) the nicotinamide cofactor is bound in ananti‐conformation, with the amide carbonyl occupying the ketone binding pocket, and (ii) a flexible loop near the active site likely contributes to the remarkable substrate promiscuity observed in CaADH. We present our perspective on the dynamic nature of the CaADH active site through molecular dynamics simulation, proposing a halogen bonding model as a potential mechanism for the remarkable selectivity for an (S)‐configured C─Cl bond, in addition to the D‐facial selectivity, demonstrated across 20 diverse substrates by this remarkable short‐chain dehydrogenase enzyme.

Chemistry↗

Unified understanding of the impact of semiflexibility, concentration, and molecular weight on macromolecular-scale ring diffusion

Conformationally fluctuating, globally compact macromolecules such as polymeric rings, single-chain nanoparticles, microgels, and many-arm stars display complex dynamic behaviors due to their rich topological structure and intermolecular organization. Synthetic rings are hybrid objects with conformations that display both ideal random walk and compact globular features, which can serve as models of genomic DNA. To date, emphasis has been placed on the effect of ring molecular weight on their unusual behaviors. Here, we combine simulations and a microscopic force-level theory to build a unified understanding for how key aspects of ring dynamics depend on different tunable molecular properties including backbone rigidity, monomer concentration, degree of traditional entanglement, and molecular weight. Our large-scale molecular dynamics simulations of ring melts with very different backbone stiffnesses reveal unanticipated behaviors which agree well with our generalized theory. This includes a universal master curve for center-of-mass diffusion constants as a function of molecular weight scaled by a chemistry and thermodynamic state-dependent critical molecular weight that generalizes the concept of an entanglement cross-over for linear chains. The key physics is how backbone rigidity and monomer concentration induced changes of the entanglement length, interring packing, degree of interpenetration, and liquid compressibility slow down space-time dynamic-force correlations on macromolecular scales. A power law decay of the center-of-mass diffusion constant with inverse molecular weight squared is the first consequence, followed by an ultraslow activated hopping transport regime. Our results set the stage to address slow dynamics and kinetic arrest in different families of compact synthetic and biological polymeric systems.

Science & Technology - Other Topics↗

Advanced Transmission Technologies – GETs and HPCs Session 1: ATT Foundations and Dynamic Line Ratings (DLRs)

The INL TADA GETs Cohort Session 1, held on November 4, 2025, convened experts to address the integration of advanced transmission technologies, including Grid-Enhancing Technologies (GETs) and High Performance Conductors (HPCs), with a focus on digital assurance challenges. The session highlighted the growing importance of cybersecurity, supply chain transparency, reliability, and business risk management in deploying GETs, especially Dynamic Line Ratings (DLRs). Participants examined how expanded attack surfaces, limited vendor pools, and new regulatory requirements—such as FERC Orders 881, 2023, and 1920—are influencing utilities and technology providers. The workshop underscored the need for cyber-informed engineering, secure-by-design principles, and practical risk management strategies, while fostering collaboration and knowledge sharing among industry peers. Technical discussions covered the evolution from static to dynamic line ratings, complexities of cloud-based architectures, and NERC CIP compliance challenges. The session concluded with a collaborative risk exercise and a preview of future workshops on advanced power flow control and transmission topology optimization, reinforcing the cohort’s commitment to advancing digital assurance in the energy sector.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Learning Latent Representations to Bridge Coarse-Grained and Atomistic Resolutions in Polymer Simulations

We present a machine-learning-based framework for learning reduced-order representations of polymer chain conformations across coarse-grained (CG) and united-atom (UA) fidelities. By employing linear singular value decomposition and nonlinear autoencoders, we compress high-dimensional polymer configurations into latent spaces with minimal loss of structural accuracy. Crucially, we demonstrate a near-perfect linear mapping between CG and UA latent spaces, enabling an efficient super-resolution back-mapping procedure that reconstructs high-fidelity UA configurations from CG simulations. While minor structural inaccuracies occur, they are effectively corrected through a brief molecular dynamics relaxation, forming a practical hybrid machine learning−physics scheme. This approach establishes the key structural prerequisites for accelerated polymer dynamics simulations: a compact and accurate latent encoding of polymer chain conformations and a validated multi-fidelity mapping that permits reconstruction of UA structures from CG configurations. The extension of this framework to explicit time evolution within the latent space, enabling dynamics to be propagated at CG fidelity and decoded to UA resolution only when required, represents a natural and well-motivated direction for future work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phonons reveal coupled cholesterol-lipid dynamics in ternary membranes

Experimental studies of collective dynamics in lipid bilayers have been challenging due to the energy resolution required to observe these low-energy phonon-like modes. However, inelastic X-ray scattering (IXS) measurements — a technique for probing vibrations in soft and biological materials — are now possible with sub-meV resolution, permitting direct observation of low energy, phonon-like modes in lipid membranes. Here, in this study, IXS measurements with sub-meV energy resolution reveal a low-energy optic-like phonon mode at roughly 3 meV in the liquid-ordered (L o ) and liquid-disordered (L d ) phases of a ternary lipid mixture. This mode is only observed experimentally at momentum transfers greater than 5 nm -1 in the L o system. A similar gapped mode is also observed in all-atom molecular dynamics (MD) simulations of the same mixture, indicating that the simulations accurately represnt the fast, collective dynamics in the L o phase. It’s optical nature and the Q range of the gap together suggest that the observed mode is due to the coupled motion of cholesterol-lipid pairs, separated by several hydrocarbon chains within the membrane plane. Analysis of the simulations provide molecular insight into the origin of the mode in transient, nanoscale substructures of hexagonally packed hydrocarbon chains. This nanoscale hexagonal packing was previously reported based on molecular dynamics simulations and later by NMR measurements. Here, however, the integration of IXS and MD simulations identifies a new signature of the L o substructure in the collective lipid dynamics, thanks to the recent confluence of IXS sensitivity and MD simulation capabilities.

36 MATERIALS SCIENCE↗

Phenolic Polymer Interactions with Water and Ethylene Glycol Solvents

Interactions between pre-cured phenolic polymer chains and a solvent have a significant impact on the structure and properties of the final post-cured phenolic resin. Developing an understanding of the nature of these interactions is important and will aid in the selection of the proper solvent that will lead to the desired final product. Here, we investigate the role of the phenolic chain structure and the solvent type on the overall solvation performance of the system through ab initio techniques and molecular dynamics simulations. Two types of solvents are considered: ethylene glycol (EGL) and H2O. Three phenolic chain structures are considered, including two novolac-type chains with either an ortho-ortho (OON) or an ortho-para (OPN) backbone network and a resole-type (RES) chain with an ortho-ortho network. Each system is characterized through a structural analysis of the solvation shell and the hydrogen-bonding environment as well as through a quantification of the solvation free energy along with partitioned interaction energies between specific molecular species. The combination of simulations and the analyses indicate that EGL provides a higher solvation free energy than H2O due to more energetically favorable hydrophilic interactions as well as favorable hydrophobic interactions between CH element groups. In addition, the phenolic chain structure significantly affects the solvation performance, with OON having limited intermolecular hydrogen-bond formations, while OPN and RES interact more favorably with the solvent molecules. The results suggest that a resole-type phenolic chain with an ortho-para network should have the best solvation performance in EGL, H2O, and other similar solvents.

Haskins, Justin B.↗

Dynamics of the abrupt change in Pacific Plate motion around 50 million years ago

Changes in Pacific Plate motion combined near equally with hotspot drift to generate the prominent bend in the Hawaiian-Emperor seamount chain some 50 million years ago, according to kinematic plate reconstruction and global dynamic models. A drastic change in plate tectonics and mantle convection occurred around 50 Ma as exemplified by the prominent Hawaiian-Emperor Bend. Both an abrupt Pacific Plate motion change and a change in mantle plume dynamics have been proposed to account for the Hawaiian-Emperor Bend, but debates surround the relative contribution of the two mechanisms. Here we build kinematic plate reconstructions and high-resolution global dynamic models to quantify the amount of Pacific Plate motion change. We find Izanagi Plate subduction, followed by demise of the Izanagi-Pacific Ridge and Izu-Bonin-Mariana subduction initiation alone, is incapable of causing a sudden change in plate motion, challenging the conventional hypothesis on the mechanisms of Pacific Plate motion change. Instead, Palaeocene slab pull from Kronotsky intraoceanic subduction in the northern Pacific exerts a northward pull on the Pacific Plate, while its Eocene demise leads to a sudden 30-35 degrees change in plate motion, accounting for about half of the Hawaiian-Emperor Bend. We suggest the Pacific Plate motion change and hotspot drift due to plume dynamics could have contributed nearly equally to the formation of the Hawaiian-Emperor Bend. Such a scenario is consistent with available constraints from global plate circuits, palaeomagnetic data and geodynamic models.

Hu, Jiashun↗

Complexity of life via collective mind

e mind is introduced as a set of simple intelligent units (say, neurons, or interacting agents), which can communicate by exchange of information without explicit global control. Incomplete information is compensated by a sequence of random guesses symmetrically distributed around expectations with prescribed variances. Both the expectations and variances are the invariants characterizing the whole class of agents. These invariants are stored as parameters of the collective mind, while they contribute into dynamical formalism of the agents' evolution, and in particular, into the reflective chains of their nested abstract images of the selves and non-selves. The proposed model consists of the system of stochastic differential equations in the Langevin form representing the motor dynamics, and the corresponding Fokker-Planck equation representing the mental dynamics (Motor dynamics describes the motion in physical space, while mental dynamics simulates the evolution of initial errors in terms of the probability density). The main departure of this model from Newtonian and statistical physics is due to a feedback from the mental to the motor dynamics which makes the Fokker-Planck equation nonlinear. Interpretation of this model from mathematical and physical viewpoints, as well as possible interpretation from biological, psychological, and social viewpoints are discussed. The model is illustrated by the dynamics of a dialog.

collective intelligence↗

Epoxy-based vitrimeric semi-interpenetrating network/MXene nanocomposites for hydrogen gas barrier applications

Herein, we report MXene-filled epoxy-based vitrimeric nanocomposites featuring a semi-interpenetrating network (S-IPN) to develop a hydrogen gas (H 2 ) barrier coating with self-healing characteristics for compressed H 2 storage applications. The reversible epoxy network was formed by synthesizing linear epoxy chains with pendent bis-hydroxyl groups using amino diol, which were then crosslinked with 1,4-benzenediboronic acid to generate dynamic boronic ester linkages. To achieve the S-IPN-type molecular arrangement, the epoxy chains were in situ crosslinked in the presence of poly(ethylene-co-vinyl alcohol) (EVOH), giving rise to a self-healing network (EEP) with a healing efficiency of 87%. Into the S-IPN vitrimer (EEP), a 2D platelet-type nanofiller MXene was incorporated to introduce a tortuous path for H 2 gas diffusion along with improved mechanical properties. The nanocomposite coating was applied to nylon 6 liner material, which is conventionally used in all-composite H 2 storage vessels. Further, the application of a 2 wt% MXene/EEP nanocomposite coating showed a permeability coefficient of 0.062 cm 3 mm m -2 d -1 atm -1 exhibiting ~96% reduction in gas permeability compared to uncoated nylon 6. The same nanocomposite exhibited a healing efficiency of 79%. Increasing the MXene loading to 10 wt% further reduced the permeability coefficient to 0.002 cm 3 mm m -2 d -1 atm -1 ; however, the healing efficiency decreased due to restricted chain mobility. In essence, the current work highlights the potential of vitrimeric S-IPN nanocomposite coatings for H 2 gas-barrier applications, enhancing safety and performance.

42 ENGINEERING↗

Effects of Ionic Group Distribution on the Structure and Dynamics of Amorphous Polymer Melts

Ionizable groups tethered to a polymer backbone often associate to form ionic clusters, whose features are determined by the balance of the polymer backbone and electrostatics. These assemblies impact the dynamics of the macromolecules and their ability to transport ions. Here, using fully atomistic molecular dynamics (MD) simulations, we investigate the effects of the distribution of ionizable groups along the polymer backbone on cluster characteristics and the resulting impacts on the structure and dynamics of amorphous polymers. Particularly, we probe polystyrene sulfonates (PSS) with random, precise, and block configurations of the SO 3 – sulfonate groups along the backbone with Na + as the counterion. We find that the distribution of the ionic groups affects the shape and distribution of the clusters as well as the internal packing of the ionizable groups in the cluster and the number of unique chains that participate in each cluster, affecting the structure and the dynamics of the polymers. Furthermore, the signature of ionic clusters, observed in the static structure factor S(q) for all three distributions, is significantly more pronounced for the precise and blocky polymers compared to the random one. Remarkably, we find that the local mobility of the polymer segments is not only affected by the number and size of the clusters but also by the number of polymer chains associated with clusters.

36 MATERIALS SCIENCE↗

Using mechanistic models and machine learning to design single-color multiplexed nascent chain tracking experiments

mRNA translation is the ubiquitous cellular process of reading messenger-RNA strands into functional proteins. Over the past decade, large strides in microscopy techniques have allowed observation of mRNA translation at a single-molecule resolution for self-consistent time-series measurements in live cells. Dubbed Nascent chain tracking (NCT), these methods have explored many temporal dynamics in mRNA translation uncaptured by other experimental methods such as ribosomal profiling, smFISH, pSILAC, BONCAT, or FUNCAT-PLA. However, NCT is currently restricted to the observation of one or two mRNA species at a time due to limits in the number of resolvable fluorescent tags. In this work, we propose a hybrid computational pipeline, where detailed mechanistic simulations produce realistic NCT videos, and machine learning is used to assess potential experimental designs for their ability to resolve multiple mRNA species using a single fluorescent color for all species. Our simulation results show that with careful application this hybrid design strategy could in principle be used to extend the number of mRNA species that could be watched simultaneously within the same cell. We present a simulated example NCT experiment with seven different mRNA species within the same simulated cell and use our ML labeling to identify these spots with 90% accuracy using only two distinct fluorescent tags. We conclude that the proposed extension to the NCT color palette should allow experimentalists to access a plethora of new experimental design possibilities, especially for cell Signaling applications requiring simultaneous study of multiple mRNAs.

59 BASIC BIOLOGICAL SCIENCES↗