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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Driving Force Dependent Photoinduced Charge Transfer Dynamics in Polymer-Wrapped Semiconducting Single-Walled Carbon Nanotubes

Here, we investigate the thermodynamic driving-force dependences of photoinduced charge separation (CS) and subsequent charge transfer dynamics in single-walled carbon nanotube (SWNT)–perylenediimide (PDI) donor–acceptor (D–A) superstructures. Pump–probe spectroscopy reveals that [SWNT (•+)n ]-(PDI –• ) n CS states form on an ∼100 fs time scale following photoexcitation; these dynamics are invariant across an ∼400 mV driving force range, indicating that SWNT hole polaron formation time scales are determined by nanotube lattice and solvent relaxation. These CS states feature SWNT hole polarons adjacent to (geminate) and nearby (nongeminate) PDI radical anions. Analysis of the free energy dependence for charge recombination (CR) of [SWNT •+ ] geminate -(PDI –• ) CS states highlights an ∼2 meV value for D–A electronic coupling (HAB) and ∼0.93 eV for the total reorganization energy (λ T ). A corresponding driving force dependence of the CR dynamics for [SWNT •+ ] nongeminate -(PDI –• ) CS states indicates a diminished H AB value (∼0.6 meV) and a larger λ T (∼1.1 eV), consistent with larger transfer distances. SWNT excitons that persist following photoinduced CS drive photooxidation of PDI –• components of [SWNT (•+)n ]-(PDI –• ) n CS states ( 1 SWNT* + PDI •– → PDI + SWNT •– ); this reaction manifests a significantly reduced λ T value (∼0.67 eV) as the initially prepared SWNT reduced state bears the character of a conduction band injected electron ([SWNT •– ] CB ). This reaction thus gives rise to relaxed, nongeminate SWNT electron and hole polarons on the same nanotube; these polarons react on a 10 2 ps time scale independent of the electronic structure of these SWNT-PDI superstructures.

anions↗
DOE OSTI2025

Precise Linker Length and Dynamic Bond Exchange Control Penetrant Diffusion in Dense Vitrimers

Polymer networks with dynamic covalent bonds have been investigated for their self-healing ability, recyclability, and potential as more sustainable materials. Recent results have indicated that in some cases, bond exchange can enhance the transport of penetrants in dense networks, pointing to their potential for separations of membranes. Here, imine dynamic bonds in ethylene oxide (EO) networks with precise linker lengths were synthesized to investigate the transport of N,N′-bis(2,5-di-tert-butylphenyl)-3,4,9,10-perylenedicarboximide (BTBP), a large, anisotropic dye molecule. Networks with mesh sizes smaller than, comparable to, and greater than the size of the penetrant axes were investigated to probe the effects of bond exchange and network confinement on transport. Mesh sizes, which ranged from 0.5 to 1.62 nm, were determined from shear rheology, glass transitions by calorimetry, and probe diffusion coefficients by fluorescence recovery after photobleaching. Permanent networks with identical EO chain lengths were prepared as control samples, and up to a 3 orders of magnitude increase in diffusion coefficient is observed in the dynamic systems for short linkers containing 13 backbone atoms. The longest linkers with 71 backbone atoms show no difference between the permanent and dynamic networks. Linkers shorter than 11 backbone atoms, corresponding to a mesh size smaller than the penetrant small axis, diffusion is no longer observable on the experimental time scale, indicating a sharp cutoff attributed to the precise linkers and narrow mesh size distribution. The dynamic imine exchange time scales were compared to the diffusive hopping times of penetrants and indicate that exchange can occur during a diffusive displacement. Furthermore, these findings provide insights into the factors affecting penetrant transport in dense polymers and inspire the development of next-generation selective polymer membranes.

Diffusion↗
DOE OSTI2024

Space-time generalization of mutual information

The mutual information characterizes correlations between spatially separated regions of a system. Yet, in experiments we often measure dynamical correlations, which involve probing operators that are also separated in time. Here, we introduce a space-time generalization of mutual information which, by construction, satisfies several natural properties of the mutual information and at the same time characterizes correlations across subsystems that are separated in time. In particular, this quantity, that we call the space-time mutual information, bounds all dynamical correlations. We construct this quantity based on the idea of the quantum hypothesis testing. As a by-product, our definition provides a transparent interpretation in terms of an experimentally accessible setup. We draw connections with other notions in quantum information theory, such as quantum channel discrimination. Finally, we study the behavior of the space-time mutual information in several settings and contrast its long-time behavior in many-body localizing and thermalizing systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Associative polymers with controlled sticker placement: How reversible bond distribution and density govern polymer dynamics

Associative polymers with precisely arranged stickers offer opportunities to program material properties with molecular precision. Yet, it remains unclear how the placement and fraction of stickers dictate structure, dynamics, and macroscopic properties. By developing a model unentangled polymer system with hydrogen-bonding stickers, we show that randomly distributed stickers neither form clusters nor change flow properties, whereas stickers placed at chain ends drive nanocluster formation even at low concentrations. Adding more end stickers produces a rubbery plateau spanning eight decades in frequency with two distinct relaxation timescales, in contrast to the single plateau predicted by the classic sticky Rouse model. These results demonstrate that sticker distribution dictates whether associative polymers undergo nanocluster formation or microphase separation, while substantial alterations in dynamics and viscoelasticity require both sticker aggregation and thermomechanical stability of associated domains. Our findings resolve a longstanding debate on associative polymer dynamics and provide molecular design rules for programmable soft materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Optimization of Membrane-based Carbon Capture using Dimensional Analysis, CFD and Process System Engineering

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibil-ity and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability.To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity requires a multi-stage membrane process, where the optimal network configuration of the membrane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules. Numerical results indicate that the optimal design includes three membrane stages, and the capture cost is 45.4 $/t-CO2.

Pedrozo, Hector A.↗
DOE OSTI2024

Membrane-based Carbon Capture Process Optimization using CFD Modeling

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity re-quires a multi-stage membrane process, where the optimal network configuration of the mem-brane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules.

Pedrozo, Hector A.↗
DOE OSTI2026

Custom-trained Machine-learning Interatomic Potentials: ZnCl2 Aqueous Solution

This dataset was generated using an iterative active-learning strategy implemented in the ArcaNN software package (https://github.com/arcann-chem/arcann_training) to train machine-learning interatomic potentials for aqueous ZnCl2 solutions. Each active-learning cycle consisted of three stages: training, exploration, and labeling. The initial training set combined configurations generated in this work from enhanced-sampling ab initio molecular dynamics simulations with configurations from a previously reported neural-network-potential study of aqueous ZnCl2. The enhanced-sampling ab initio molecular dynamics simulations involved Zn–Cl separation and the chloride coordination number around Zn²? as collective variables. These configurations served as the seed dataset. Subsequent active-learning cycles expanded the training set by identifying and labeling configurations that were poorly represented by the current models, thereby improving coverage of ion-association states and changes in local coordination and charge-state environments relevant to the solution free-energy landscape. For all selected configurations, single-point calculations of the total energies and atomic forces were performed within density functional theory using the CP2K Quickstep module. Reference calculations employed the revPBE-D3 and r2SCAN exchange-correlation functionals. Motivated by recent work on aqueous Zn²?, the main revPBE calculations omitted D3 dispersion contributions involving Zn²?, while retaining the D3 correction for water and chloride. For comparison, fully dispersion-corrected revPBE-D3 reference calculations were also performed, with D3 applied to all species, including Zn²?. Valence electrons were treated explicitly, while core electrons were represented using norm-conserving Goedecker–Teter–Hutter pseudopotentials. The wave functions were expanded using the mixed Gaussian-and-plane-wave scheme with TZV2P-MOLOPT basis sets for all elements and a 600 Ry auxiliary plane-wave cutoff for the electron density. Self-consistent-field convergence was accelerated using the orbital-transformation and Direct Inversion in the Iterative Subspace algorithms, with a convergence threshold of 10?6. All single-point calculations were performed in periodic orthorhombic cells. The CELL_REF keyword in CP2K was used to define a fixed reference cell with a box length of 25 Å. This treatment ensured a consistent reference for configurations extracted from NpT trajectories with fluctuating cell dimensions. The resulting DFT energies and atomic forces constitute the ground-truth labels used to train the MLIPs. The resulting MLIP was trained for aqueous ZnCl2 solutions spanning concentrations from 0 to 30 molal and a broad pH range, from strongly acidic to strongly basic conditions. Representative examples of configurations included in the MLIP training dataset are provided below. These include 1) Representative configurations from the dataset labeled at the revPBE-D3 level, with D3 dispersion interactions involving Zn2+ excluded (revPBE-wo-D3). 2) Representative configurations from the dataset labeled at the fully dispersion-corrected revPBE-D3 level, with D3 interactions applied to all species, including Zn2+ (revPBE-D3). 3) Representative configurations from the dataset labeled at the r2SCAN level of theory (r2SCAN).

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗
DOE OSTI2024

Membrane-based carbon capture process optimization using CFD modeling

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High fidelity simulations have been shown to be effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity requires a multi-stage membrane process, where the optimal network configuration of the membrane modules must be studied in a systematic way. In order to address the design problem at process scale, we formulate a superstructure for the membrane-based carbon capture, including up to three separation stages. In the formulation of the optimization problem, we include reduced models, based on rigorous CFD simulations of the membrane modules. Numerical results indicate that the optimal design includes three membrane stages, and the capture cost is 45.4 $/t-CO2.

Pedrozo, Hector A.↗
DOE OSTI2026

Polyolefin blends with co-continuous architectures enabled by dynamic covalent crosslinking

Blending polymers produces brittle materials due to macrophase separation and poor interfacial adhesion, which is exemplified by mixtures of polyolefins. This presents a formidable challenge for the mechanical recycling of mixed plastic waste. Here, we demonstrate that dynamic covalent crosslinking of immiscible polyolefin blends creates macrophase separated co-continuous architectures, yet they display excellent mechanical properties, which challenges the conventional wisdom regarding morphology-property relationships in polymer blend compatibilization. We find that the position and orientation of dynamic crosslinks and their influence on crystallinity are key to understanding the structure-morphology-property relationships. In particular, high-resolution microscopy imaging reveals alignment of crystallite planes with strong orientational preference, particularly at polymer-polymer interfaces, which contribute to material performance. We further demonstrate that changes in crosslinker density and valency allow the properties of binary and ternary polyolefin blends to be tuned in a modular fashion.

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

REBOUND: Reverse Engineering Bidirectional Outflow Under Non-Equilibrium Diffusion

Rare-earth elements (REEs) are essential for electronics, renewable energy, and defense technologies. However, the current supply of REEs relies on mining concentrated in a few countries and energy-intensive separations. DOE’s Basic Energy Sciences (BES) program has launched a grand challenge which aims to ensure a sustainable supply of critical REEs by developing innovative and environmentally friendly separation methods. As an alternative to costly and harmful traditional methods, the Non-Equilibrium Transport Driven Separations (NETS) initiative has created a microfluidic Y-channel co-flow method that applies external fields to exploit magneto- and electrohydrodynamic effects for separating dilute REE ions from complex feedstocks. Computational fluid dynamics (CFD) studies have identified a few operating conditions with promising ion selectivity and separation efficiency. However, challenges remain regarding Y-channel versatility across feedstocks and accurate incorporation of physical phenomena into CFD models. In this work, we develop a multi-fidelity modelling approach which integrates experimental results with CFD simulation to build a surrogate model for the dependence of separation efficiency to variation of design parameters. The surrogate model enables a reinforcement learning (RL) method to adaptively launch CFD and experimental runs, improving model fidelity around optimal Y-channel parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Background-field Method and QCD Factorization

One method for deriving a factorization for QCD processes is to use successive integration over fields in the functional integral. In this approach, we separate the fields into two categories: dynamical fields with momenta above a relevant cutoff, and background fields with momenta below the cutoff. The dynamical fields are then integrated out in the background of the low-momentum background fields. This strategy works well at tree level, allowing us to quickly derive QCD factorization formulas at leading order. However, to extend the approach to higher loops, it is necessary to rigorously define the functional integral over dynamical fields in an arbitrary background field. This framework was carefully developed for the calculation of the effective action in a background field at the two-loop level in the classic paper by Abbott «The Background Field Method Beyond One Loop», Nucl. Phys. B 185 , 189 (1981). Building on this work, I specify the renormalized background-field Lagrangian and define the notion of the quantum average of an operator in a background field, consistent with the “separation of scales” scheme mentioned earlier. As examples, I discuss the evolution of the twist-2 gluon light-ray operator and the one-loop gluon propagator in a background field near the light cone.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

SODAs: sparse optimization for the discovery of differential and algebraic equations

Differential-algebraic equations (DAEs) integrate ordinary differential equations (ODEs) with algebraic constraints, providing a fundamental framework for developing models of dynamical systems characterized by time-scale separation, conservation laws and physical constraints. While sparse optimization has revolutionized model development by allowing data-driven discovery of parsimonious models from a library of possible equations, existing approaches for dynamical systems assume DAEs can be reduced to ODEs by eliminating variables before model discovery. This assumption limits the applicability of such methods for DAE systems with unknown constraints and time scales. We introduce sparse optimization for differential-algebraic systems (SODAs), a data-driven method for the identification of DAEs in their explicit form. By discovering the algebraic and dynamic components sequentially without prior identification of the algebraic variables, this approach leads to a sequence of convex optimization problems. It has the advantage of discovering interpretable models that preserve the structure of the underlying physical system. To this end, SODAs improves since SODAs is singular numerical stability when handling high correlations between library terms, caused by near-perfect algebraic relationships, by iteratively refining the conditioning of the candidate library. We demonstrate the performance of our method on biological, mechanical and electrical systems, showcasing its robustness to noise in both simulated time series and real-time experimental data.

DAE↗
DOE OSTI2025

Backbone Dynamics of Bottlebrush Polymers Studied by Neutron Scattering

Bottlebrush polymers have a versatile architecture that is highly customizable due to the combination of a linear backbone and side chains. As a result of the chemical tethering of the side chains, both parts cannot be easily be separated. Huge effort is seen regarding the dynamical behavior of the side chains or the entire bottlebrush polymer, whereas few studies are available considering the backbone. Here, isotopic labeling in combination with quasi-elastic neutron scattering was used to compare the dynamical behavior of the bottlebrush’s backbone with the side chain dynamics. Keeping the side chains deuterated, (h-PNB)- g -(d-PPO), leads to the scattering signal dominated by backbone dynamics, while the fully protonated sample, (h-PNB)- g -(h-PPO), gives side chain dynamics. Both results reveal slower dynamics associated with the backbone with less heterogeneity, as seen for the side chains. Additionally, a plasticizer effect for the backbone dynamics is confirmed by extracting the glass transition temperature and comparing it with pure linear PNB.

neutron scattering↗
DOE OSTI2024

Impact of Asymmetric Microstructure on Ion Transport in Ti 3 C 2 T x Membranes

Consolidation or densification of low-dimensional MXene materials into membranes can result in the formation of asymmetric membrane structures. Nanostructural (short-range) and microstructural (long-range) heterogeneity can influence mass transport and separation mechanisms. Short-range structural dynamics include the presence of water confined between the 2D layers, while long-range structural properties include the formation of defects, micropores, and mesopores. Herein, it is demonstrated that structural heterogeneity in Ti 3 C 2 T x membranes fabricated via vacuum-assisted filtration significantly affects ion transport. Higher ion permeabilities are achieved when the dense “bottom” side of the membrane, rather than the porous “top” side, faces the feed solution. Characterization of the membrane reveals distinct differences in flake alignment, surface roughness, and porosity across the membrane. In conclusion, the directional dependence on permeability suggests that one region of the membrane experiences stronger internal concentration polarization, potentially suppressing permeability through the porous side of the membrane.

MXene↗
DOE OSTI2025

The Influence of Structural Dynamics in Two-Dimensional Hybrid Organic–Inorganic Perovskites on Their Photoluminescence Efficiency — Neutron Scattering Analysis

Two-dimensional hybrid organic–inorganic perovskites (HOIPs) have emerged as promising materials for light-emitting diode applications. In this study, by using time-of-flight neutron spectroscopy we identified and quantitatively separated the lattice vibrational and molecular rotational dynamics of two perovskites, butylammonium lead iodide (BA)2PbI4 and phenethyl-ammonium lead iodide (PEA) 2 PbI 4 . By examining the corresponding temperature dependence, we found that the lattice vibrations, as evidenced by neutron spectra, are consistent with the lattice dynamics obtained from Raman scattering. We revealed that the rotational dynamics of organic molecules in these materials tend to suppress their photoluminescence quantum yield (PLQY) while the vibrational dynamics did not show predominant correlations with the same. Additionally, we observed photoluminescence emission peak splitting for both systems, which becomes prominent above certain critical temperatures where the suppression of PLQY begins. This study suggests that the rotational motions of polarized molecules may lead to a reduction in exciton binding energy or the breaking of degeneracy in exciton binding energy levels, enhancing non-radiative recombination rates, and consequently reducing photoluminescence yield. These findings offer a deeper understanding of fundamental interactions in 2D HOIPs and could guide the design of more efficient light-emitting materials for advanced technological applications.

Rajeev, Haritha Sindhu [Univ. of Virginia, Charlot↗
DOE OSTI2025

Skyrmion-skyrmionium phase separation and laning transitions via spin-orbit torque currents

Many driven binary systems can exhibit laning transitions when the two species have different mobilities, such as colloidal particles with opposite charges in electric fields. Another example is pedestrian or active-matter systems, where particles moving in opposite directions form a phase-separated state that enhances the overall mobility. In this work, we use atomistic simulations to demonstrate that mixtures of skyrmions and skyrmioniums also exhibit pattern formation and laning transitions. Skyrmions move more slowly and at a finite skyrmion Hall angle compared to skyrmioniums, which move faster and without a skyrmion Hall effect. At low drives, the system forms a partially jammed phase where the skyrmioniums are dragged by the surrounding skyrmions, resulting in a finite angle of motion for the skyrmioniums. At higher drives, the system transitions into a laned state, but unlike colloidal systems, the lanes in the skyrmion-skyrmionium mixture are tilted relative to the driving direction due to the intrinsic skyrmion Hall angle. In the laned state, the skyrmionium angle of motion is reversed when it aligns with the tilted lane structure. At even higher drives, the skyrmioniums collapse into skyrmions. Below a critical skyrmion density, both textures can move independently with few collisions, but above this density, the laning state disappears entirely, and the system transitions to a skyrmion-only state. We map out the velocity and Hall responses of the different textures and identify three distinct phases: partially jammed, laned, and skyrmion-only moving crystal states. In conclusion, we compare our results to recent observations of tilted laning phases in pedestrian flows, where chiral symmetry breaking in the particle interactions leads to similar behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Initial energy-momentum to final flow: A general framework for heavy-ion collisions

The evolution of a relativistic heavy-ion collision is typically understood as a process that transmutes the initial geometry of the system into the final momentum distribution of observed hadrons, which can be described via a cumulant expansion of the initial distribution of energy density and is represented at leading order as the well-known eccentricity scaling of anisotropic flow. We extend this framework to include the contribution from initial momentum-space properties, as encoded in other components of the energy-momentum tensor. Furthermore, we confirm the validity of the framework in state-of-the-art hydrodynamic simulations of large and small systems. With this framework, it is possible to separate the effects of early time dynamics from those of final-state evolution, even in the case when the distribution of energy does not fully determine subsequent evolution, as for example, in small systems. Specifically, we answer the question of when and how azimuthal correlations from the initial state survive to the final state. In very small systems such as 𝑝−𝑝, for example, initial momentum degrees of freedom dominate over energy. Thus, even if the system forms a quark-gluon plasma that is well described by hydrodynamics, the usual hydrodynamic picture of the transmutation of initial geometry to final momentum anisotropy is broken. Nevertheless, we show that the hydrodynamic response to the full energy-momentum tensor can be well understood in a similar manner as larger systems. Additionally, this framework elucidates the generic features of the system's evolution that are responsible for the impressive success of hydrodynamic simulations, but which may still hold even in cases where hydrodynamics is not applicable.

Relativistic heavy-ion collisions↗