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DOE OSTI2021

Collective Vibrational Strong Coupling Effects on Molecular Vibrational Relaxation and Energy Transfer: Numerical Insights via Cavity Molecular Dynamics Simulations**

Abstract For a small fraction of hot CO 2 molecules immersed in a liquid‐phase CO 2 thermal bath, classical cavity molecular dynamics simulations show that forming collective vibrational strong coupling (VSC) between the C=O asymmetric stretch of CO 2 molecules and a cavity mode accelerates hot‐molecule relaxation. This acceleration stems from the fact that polaritons can be transiently excited during the nonequilibrium process, which facilitates intermolecular vibrational energy transfer. The VSC effects on these rates 1) resonantly depend on the cavity mode detuning, 2) cooperatively depend on Rabi splitting, and 3) collectively scale with the number of hot molecules. For larger cavity volumes, the average VSC effect per molecule can remain meaningful for up to N ≈10 4 molecules forming VSC. Moreover, the transiently excited lower polariton prefers to relax by transferring its energy to the tail of the molecular energy distribution rather than distributing it equally to all thermal molecules. As far as the parameter dependence is concerned, the vibrational relaxation data presented here appear analogous to VSC catalysis in Fabry–Pérot microcavities.

Li, Tao E.↗

DOE OSTI2021

Collective Vibrational Strong Coupling Effects on Molecular Vibrational Relaxation and Energy Transfer: Numerical Insights via Cavity Molecular Dynamics Simulations**

Li, Tao E.↗

DOE OSTI2025

Quantifying dislocation-type defects in post irradiation examination via transfer learning

The quantitative analysis of dislocation-type defects in irradiated materials is critical to materials characterization in the nuclear energy industry. The conventional approach of an instrument scientist manually identifying any dislocation defects is both time-consuming and subjective, thereby potentially introducing inconsistencies in the quantification. This work approaches dislocation-type defect identification and segmentation using a standard open-source computer vision model, YOLO11, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of annotated micrographs for training. This model demonstrates the ability to segment both dislocation lines and loops concurrently in micrographs with high pixel noise levels and on two alloys not represented in the training set. Inference of dislocation defects using transmission electron microscopy on three different irradiated alloys relevant to the nuclear energy industry are examined in this work with widely varying pixel noise levels and with completely unrelated composition and dislocation formations for practical post irradiation examination analysis. Code and models are available at https://github.com/idaholab/PANDA.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Enhancing $\phi$-sensitivity of ignition delay times through dilution of fuel-air mixture

The high $\phi$-sensitivity (η) of ignition delay time (τ IDT ) is one of the desirable fuel properties for the high-load extension of advanced compression ignition engine. Recent studies revealed the effectiveness of a high dilution rate (x D ) for enhancing η at the engine-relevant conditions. This study aims to quantify the effect of dilution on the η of isooctane using a combined experiment-simulation approach. The ignition delay of the isooctane/air mixture was measured with an Advanced Fuel Ignition Delay Analyzer (AFIDA) over the temperature range of 623 - 923 K at 10 bar pressure with global $\phi$ = 0.3 - 0.6, with and without 28.6% of additional N 2 dilution. For precise evaluation of experimental η, the facility effect of the AFIDA experiment was characterized with three-dimensional computational fluid dynamics (3-D CFD) simulation. The temperature in the combustion chamber from 3-D CFD indicated a substantial temporal dependency, varying up to ~52 K by charge-cooling of fuel injection and heat transfer from the wall. We introduced the dimensionless number θ(t) for characterizing the temporal profile of chamber temperature. Consideration of the facility effect using θ(t) resulted in better agreement between the experimental ..eta.. and zero-dimensional (0-D) kinetics simulation. The refined η were then further utilized to quantify the effectiveness of dilution to η The extent of η enhancement with dilution strategy was maximized at the low-temperature chemistry regime, increasing η by 77% with a 28.6% dilution rate. Further analysis on the dilution effect was carried out using 0-D kinetics simulation, revealing the critical dimensionless numbers relevant to the effectiveness of dilution to η enhancement. Here, this study is the first experiment-simulation combined research to quantify the effect of dilution on η, facilitating the kinetics model refinement for better reproduction of $\phi$-sensitivity.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Nonlinear Alfvén instability simulation and EP transport for ITER reversed shear (steady-state) and monotonic q-profile regimes *

The nonlinear evolution and dynamics of energetic particle (EP) driven instabilities in both steady-state (reversed shear q-profile) and monotonic q-profile regimes of ITER are examined using the global gyro-Landau closure model FAR3d. Both neutral beam and alpha components are included, leading to synergistic effects between the two populations. In order to maintain computational feasibility, the present nonlinear simulation includes all toroidal mode numbers ranging from n = 0 to 15. It cannot be excluded that n’s above this range could introduce larger linear growth rates; however, as indicated from the results, the n = 0 to 15 range is sufficient to provide a strong linear drive and significant nonlinear transport effects. While the toroidal mode numbers n = 6,13 dominate the linear instability growth phase, nonlinear energy transfers in the saturated phase reverse this trend, leading to the dominance of lower n’s in the saturated phase of the simulation. Zonal flow structure generation and EP density flattening are further consequences of the nonlinear phase. The density profile flattening is caused by collectively driven EP radial transport fluxes, which have non-local characteristics. Instantaneous alpha particle transport fluxes are significant (Γ α ~ 2 x 10 20 m –2 s –1 ) for the reversed shear regime and lower (Γ α ~ 1.1 x 10 20 m –2 s –1 ) for the monotonic q-profile case.

AE↗

DOE OSTI2025

Solvent Dynamics in Gel Polymer Electrolytes for Lithium–Sulfur Batteries

Li−sulfur (Li−S) batteries are promising as the next-generation energy storage technology but face challenges due to sluggish sulfur redox reaction (SRR) kinetics and a sulfur shuttling effect. While many studies have explored polycaprolactone (PCL)-based gel polymer electrolytes (GPEs) to address these issues, the influence of solvent properties, including dielectric constant (ϵ) and donor and acceptor numbers (DN and AN), remain unexplored despite their critical impact on performance and full-scale implementation. This study systematically compares three distinct electrolytes, dimethoxyethane (DME), dimethyl sulfoxide (DMSO), and tetraethylene glycol dimethyl ether (TEGDME)-paired with PCL, to correlate the varied solvent properties and their effects on the physical properties of the GPE, in terms of Li + transport and solvation, and polysulfide’s confinement. Among them, the DME-based GPE, with an intermediate DN, exhibited the lowest crystallinity (2.31%), highest ionic conductivity (7.49 mS/cm), and high Li + transference number (0.77). As a result, it achieved a specific capacity of 795 mAh/g sulfur and an average Coulombic efficiency of 97.5% after 120 cycles at C/5, outperforming its competitors. Operando Raman and UV−vis spectroscopy confirmed that PCL effectively confines long-chain polysulfides within its network, mitigating the shuttle effect and facilitating reversible polysulfide conversion. These findings demonstrate that GPEs with moderate DN values and balanced ϵ significantly enhance stability, extend cycle life, and improve rate performance for Li−S batteries. This work provides valuable insights into the design of advanced electrolyte systems for practical energy storage applications.

25 ENERGY STORAGE↗

DOE OSTI2022

Effect of Tethering Anions in Block Copolymer Electrolytes via Molecular Dynamics Simulations

Ion-containing block copolymers (BCPs) are promising solid-state electrolytes as they can combine ion conduction and mechanical robustness via multiple microphases. However, salt-doped BCPs can have low ion conduction and transference number. One strategy to increase transference number is to tether anions to the polymer backbone (creating a single-ion conductor), though this may impact cation mobility. Leveraging coarse-grained molecular dynamics simulations, we compare the effects of ion concentration and polymer dielectric constant on BCPs with and without bonding anions to the chain (without changing any other chemical properties). We find that single-ion BCPs have higher cation conductivity than analogous salt-doped BCPs, especially at moderate ion concentrations. Furthermore, we also compare several structural features of these systems; notably, tethering anions causes the ions to spread more evenly throughout the conducting phase, which is related to improved cation conduction.

25 ENERGY STORAGE↗

DOE OSTI2023

Electrolytic Etching of Germanium Substrates with Hydrogen Peroxide

Anodic electrolytic etching of germanium has been performed in hydrogen peroxide etchants with controlled external conditions. In-situ current and ex-situ etch-depths were measured and tracked with respect to etchant composition and stir rates. Gas bubbles formed during the etching process were found to cause non-uniformity in etch-current and surface quality. The effects were minimized in specific composition spaces. Quantitative analysis revealed a linear correlation of the number of electrons transferred during germanium oxidation with the number of surface atoms removed. Experimental results of 2.77 electrons/atom deviate significantly from 4 electrons/atom previously reported for silicon. The conclusion is that etching mechanisms for germanium are sufficiently different from those for silicon which invalidates the direct transfer of processing techniques between the two materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

A reactive electrochemomechanical theory for growth and remodeling of polyelectrolyte hydrogels and application to dynamic polymerization of $\text{DNA}$ hydrogels

Here this study develops a framework for growth and remodeling of active polyelectrolyte hydrogels that accounts for effects of compositional changes on the mechanical response. By developing a reactive electrochemomechanical theory, thermodynamical constraints upon reactive and remodeling processes are elucidated within a general framework that allows any number of chemical reactions to evolve the response of the gel and transfer mass and charge between constituents. Fully coupled, nonlinear constitutive relations are adopted for molar fluxes, allowing exploration of effects including cross-diffusion, electrophoresis, and electro-osmosis. A robust finite element implementation is developed in the open source FEBio software (febio.org) by exploiting an equivalence between electrochemomechanics and mixture theory. The implementation is verified against analytical solutions for free swelling, and a proper reduction to a prior chemomechanical theory is demonstrated for neutral gels swollen only by a solvent with no solutes. The theory and implementation are then applied to model the tunable large swelling achieved through dynamic polymerization of DNA crosslinkers seen in our recently developed experimental hydrogel system (Cangialosi et al., 2017). A novel constitutive model for reaction-driven evolution of the locking stretch λ L in a non-Gaussian mechanical free energy was developed, where the increasing concentration of DNA crosslinkers makes further swelling energetically favorable. With a single free parameter, excellent agreement was found between measured and predicted equilibrium swelling ratios. This study demonstrated the ability to extend the electrochemomechanical framework to include chemical reactions and composition-aware constitutive models, and showed that development of reactive models allows simulation of complex dynamic polymerization phenomena not treated before. The theoretical frame here can be further expanded in scope to incorporate additional non-ideal and nonlinear phenomena.

42 ENGINEERING↗

DOE OSTI2024

Anomalous Hall effects in chiral superconductors

We report theoretical results for the electronic contribution to thermal and electrical transport for chiral superconductors belonging to even or odd-parity E 1 and E 2 representations of the tetragonal and hexagonal point groups. Chiral superconductors exhibit novel properties that depend on the topology of the order parameter and Fermi surface, and—as we highlight—the structure of the impurity potential. An anomalous thermal Hall effect is predicted and shown to be sensitive to the winding number, ν, of the chiral order parameter via Andreev scattering that transfers angular momentum from the chiral condensate to excitations that scatter off the random potential. For heat transport in a chiral superconductor with isotropic impurity scattering, i.e., point-like impurities, a transverse heat current is obtained for ν = ± 1, but vanishes for | ν | > 1. This is not a universal result. For finite-size impurities with radii of order or greater than the Fermi wavelength, R ≥ ℏ / p f, the thermal Hall conductivity is finite for chiral order with | ν | ≥ 2, and determined by a specific Fermi-surface average of the differential cross-section for electron-impurity scattering. Our results also provide quantitative formulae for analyzing and interpreting thermal transport measurements for superconductors predicted to exhibit broken time-reversal and mirror symmetries.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Constitutional under-potential plating (CUP) – New insights for predicting the morphological stability of deposited lithium anodes in lithium metal batteries

Lithium (Li) cycling in lithium metal batteries (LMBs) inevitably witnesses a non-planar Li/electrolyte interface (cellular/dendritic microstructure) affecting the performance, safety and reliability of LMBs. Herein, the “constitutional under-potential plating” (CUP) concept is presented for the first time to understand the evolution, formation and predict the morphological stability/instability of the Li/electrolyte interface. Here, the CUP condition, a measure of the driving force for interface perturbation, occurs when the true potential gradient at the interface is smaller than the equilibrium electrodeposition potential gradient at the Li/electrolyte interface resulting in the electrolyte ahead of the Li-electrolyte interface to be in an under-potential state. Detailed CUP criterion calculations conducted herein establishes the relationship of battery operating conditions (e.g. current density, potential gradient) with the electrolyte properties (e.g. Li-ion transference number and diffusion coefficient) predicting the morphological stability condition at the interface. In addition to the driving force for interface perturbation, the capillarity effect or the Gibbs Thomson effect, a measure of the resistance to perturbation of the perturbed interface is discussed for understanding the influence of interfacial energy/adhesion energy between the current collector and the deposited Li on the overall morphological stability of the Li/electrolyte interface, a critical criterion for the unwanted dendritic morphology.

25 ENERGY STORAGE↗

DOE OSTI2024

A One-dimensional Heat Transfer Model for a Cooled Airfoil in a Direct-fired Supercritical CO 2 Turbine

A one-dimensional (1-D) heat transfer model was developed to predict the performance of a cooled airfoil for a supercritical carbon dioxide (sCO 2 ) turbine. The model included the effects of film cooling effectiveness, thermal barrier coating thickness, and internal Nusselt number augmentation. Trends for overall cooling effectiveness versus heat load parameter were obtained for over twelve unique thermal management schemes. The study found that adding a thermal barrier coating was the most effective scheme for increasing the airfoil overall cooling effectiveness. Internal cooling technologies have diminishing returns as the heat transfer coefficient augmentation increases past a factor of five, however the sensitivity of overall cooling effectiveness to heat transfer augmentation scales by a factor of 1.3 when a thermal barrier coating is introduced. Film cooling is seen as a long-term research area which will be inevitably explored as direct sCO 2 systems develop a market presence. However, the model indicates that realizable film cooling effectiveness levels yield a smaller improvement in overall cooling effectiveness than a thermal barrier coating.

42 ENGINEERING↗

DOE OSTI2025

Rapid Adaptation of Chemical Named Entity Recognition Using Few-Shot Learning and LLM Distillation

Named entity recognition (NER) has been widely used in chemical text mining for the automatic identification and extraction of chemical entities. However, existing chemical NER systems primarily focus on scenarios with abundant training data, requiring significant human effort on annotations. This poses challenges for applications in the chemical field, such as catalysis, where many advancements have traditionally relied on trial-and-error investigations and incremental adjustment of variables. This hinders catalysis science and technology progress in addressing emerging energy and environmental crises. In this work, we propose a few-shot NER model that can quickly adapt to extract new types of chemical entities by using only a limited number of annotated examples. Our model employs a metric-learning approach to transfer entity similarity knowledge from high-resource chemical domains (with abundant annotations) to enable effective entity recognition in low-resource specialized domains (limited annotation). We validate the effectiveness of our model on a few-shot chemical NER benchmark built based on six existing chemical NER data sets. Experiments show that the proposed few-shot NER model can achieve reasonable performance with only 5 examples per entity type and shows consistent improvement as the number of examples increases. Furthermore, we demonstrate how the proposed model can be trained with large language model (LLM) annotated data, opening a new pathway for rapid adaptation of NER systems. Furthermore, our approach leverages the knowledge broadness of large language models for chemistry while distilling this knowledge into a lightweight model suitable for efficient and in-house use.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Mitigating Electronic Conduction in Ceria‐Based Electrolytes via External Structure Design

Doped ceria electrolytes are the state of the art low‐temperature solid oxide electrolytes because of their high ionic conductivity and good material compatibility. However, cerium tends to reduce once exposed to reducing environments, leading to an increase in electronic conduction and a decrease in efficiency. Here, the leakage current is mitigated in ceria‐based electrolytes by controlling the defect chemistry through an engineered cathode side microstructure. This functional layer effectively addresses the problematic electronic conduction issue in ceria‐based electrolytes without adding significant ohmic resistance and increases the ionic transference number to over 0.93 in a thin 20 µm ceria‐based electrolyte at 500 °C, compared to a of 0.8 for an unmodified one. Based on this design, solid oxide fuel cells (SOFCs) are further demonstrated with the remarkable peak power density of 550 mW at 500 °C and excellent stability for over 2000 h. This approach enables a potential breakthrough in the development of ceria‐based low‐temperature solid oxide electrolytes.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows

Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Additionally, guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved. The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Burning of particles undergoing stripping breakup

A simple model for condensed-phase particle burning has been presented. Particles are assumed to start burning in quiescent air. Particles are then accelerated, adding convective effects. Convective effect due to the relative motion between the particle and air on heat and mass transfer is included by introducing the Nusselt number. Stripping of liquid is included at higher particle velocity. Evaporation and burning from the stripped tail are also included.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Dynamical Ion Correlations in Polymer and Membrane Electrolytes: Recent Advances and Open Questions

Ion transport in polymer and membrane electrolytes is often described using uncorrelated models like the Nernst–Einstein (NE) approximation, which link conductivity, transference number, and salt diffusivity to individual ion mobilities. However, growing evidence shows that dynamical ion correlations─arising from ion pairing, polymer-mediated coupling, confinement, and electrostatic interactions─can substantially alter macroscopic transport properties. The Onsager transport formalism offers a rigorous framework to quantify these effects via cross-correlated ionic displacements. This Perspective highlights how such correlations manifest across dry and hydrated systems, including salt-doped polymers, block copolymers, hydrogels, and ion-exchange membranes. Here, we examine key physical origins, the influence of salt chemistry and polymer structure, and open questions in measuring and controlling correlated motion. Embracing correlation-aware design enables new pathways to optimize conductivity, transference number, and selectivity─shifting the focus from individual ion mobility to engineered collective dynamics for next-generation electrolytes in energy storage and separations.

Charge transport↗

DOE OSTI2024

Preliminary Assessment of Additively Manufactured Cooling Channel Performance for Helium-Cooled Blanket Concepts

Sufficient cooling of the blanket first wall remains a critical challenge for the design and deployment of fusion power plants. Helium has been targeted as a potential blanket coolant due to its inertness and low neutron interactivity, among other advantages. However, the low thermal mass of helium creates a need for heat transfer enhancements in coolant channels to provide adequate cooling to the blanket’s first wall. Toward this end, a series of ribbed flow channels of various rib cross sections and configurations has been produced via additive manufacturing (AM) to study the efficacy of AM for first wall heat transfer enhancement and the optimization of heat transfer geometries. Helium cooling performance is studied in AM test articles at 4 MPa operating pressure, Reynolds numbers up to 197 000, and outer surface heat fluxes up to 42 kW/m 2 in the recently commissioned helium flow loop experiment (HFLE). Preliminary results of this study are presented herein. Heat transfer performance of nominally smooth (i.e., featureless) AM channels is quantified via measured Nusselt numbers and friction factors and compared to off-the-shelf smooth pipe experiments. Results are compared to existing correlations and used to discuss the effects of the AM processes on thermal-hydraulic performance. It is seen that the inherent roughness of the AM channels leads to an increase in both heat transfer coefficient and pressure drop when compared to the conventional pipe. In conclusion, recommendations are made for future studies based on these findings and additional considerations for the deployment of AM blanket cooling components.

36 MATERIALS SCIENCE↗