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At least 163 records · Page 9

Thermal diffusion, exhaust gas recirculation and blending effects on lean premixed hydrogen flames

Thermodiffusively-unstable lean premixed hydrogen flames are investigated using two-dimensional direct numerical simulation employing finite-rate chemical kinetics. Three databases are generated focussing on the inclusion of the Soret effect, the recirculation of exhaust gas, and blending with methane. A simple rescaling of a classic thermal diffusion model is presented and shown to mimic multicomponent diffusion with very low computational cost and little-to-no loss in accuracy. It is also shown that a previously developed model for mean local flame speeds in lean premixed hydrogen flames can still be used provided Soret effects are taken into account in one-dimensional calculations. The addition of exhaust gas to the unburned mixture is found to enhance thermodiffusive instability; the primary mechanism for this was shown to be the highly-efficient third-body nature of water, with the reduction of adiabatic flame temperature a second-order effect. Again, the existing mean local flame speed model proved sufficient. Finally, blending with methane was found to reduce the thermodiffusive response of the flame, more so than the existing model suggests, despite adjustment of the fuel Lewis number; an adapted model is presented to account for this.

08 HYDROGEN

Investigation of Sub‐Bandgap Emission and Unexpected n‐Type Behavior in Undoped Polycrystalline CdSe x Te 1‐x

Abstract Se alloying has enabled significantly higher carrier lifetimes and photocurrents in CdTe solar cells, but these benefits can be highly dependent on CdSe x Te 1‐x processing. This work evaluates the optoelectronic, chemical, and electronic properties of thick (3 µm) undoped CdSe x Te 1‐x of uniform composition and varied processing conditions (CdSe x Te 1‐x evaporation rate, CdCl 2 anneal, Se content) chosen to reflect various standard device processing conditions. Sub‐bandgap defect emission is observed, which increased as Se content increased and with “GrV‐optimized CdCl 2 ” (i.e., CdCl 2 anneal conditions used for group‐V‐doped devices). Low carrier lifetime is found for GrV‐optimized CdCl 2 , slow CdSe x Te 1‐x deposition, and low‐Se films. Interestingly, all films (including CdTe control) exhibited n‐type behavior, where electron density increased with Se up to an estimated ≈10 17 cm −3 . This behavior appears to originate during the CdCl 2 anneal, possibly from Se diffusion leading to anion vacancy (e.g., V Se , V Te ) and Cl Te generation.

14 SOLAR ENERGY

Li 21 Ge 8 P 3 S 34 : New Lithium Superionic Conductor with Unprecedented Structural Type

Abstract Lithium superionic conductors are pivotal for enabling all‐solid‐state batteries, which aim to replace liquid electrolytes and enhance safety. Herein, we report the discovery of an unprecedented lithium superionic conductor, Li 21 Ge 8 P 3 S 34 , featuring a novel structural type and a new composition in the Li–Ge–P–S system. This material exhibits high lithium ionic conductivity of approximately 1.0 mS cm −1 at 303 K with a low activation energy of 0.20(1) eV. It's unique crystal structure was elucidated using three‐dimensional electron diffraction (3D ED) and further refined through combined powder X‐ray and neutron diffraction analyses. The structure consists of alternating two‐dimensional slabs: one of corner‐sharing GeS 4 tetrahedra and the other of isolated PS 4 tetrahedra, enabling efficient lithium‐ion transport through a tetrahedrally interconnected network of 1D, 2D, and 3D diffusion pathways. This distinctive structural motif provides a novel design strategy for next‐generation solid electrolytes, broadening the structural landscape of lithium superionic conductors. With further advancements in compositional tuning and interfacial engineering, Li 21 Ge 8 P 3 S 34 could contribute to the development of high‐performance all‐solid‐state batteries.

Chemistry

Perspective on “Active Brownian particles moving in a random Lorentz gas”

Self-propelled active matter can exhibit vastly different behavior than systems with purely Brownian motion. In Eur. Phys. J. E 40, 23 (2017), Zeitz, Wolf, and Stark compared an active matter particle with a Brownian particle moving in a random obstacle array. They showed that near the obstacle percolation density, both Brownian and active particles exhibit the same subdiffusive behavior, but the active particle reaches a steady state more rapidly. They also found that for high activity, the active particle has a lower effective diffusion than the Brownian particle due to the increased self-trapping effect generated by the activity. This result opens new directions for the study of active matter in disordered media, including bacteria in porous media, active colloids on quenched disorder, and active particles in crowded environments.

36 MATERIALS SCIENCE

Generative unfolding with distribution mapping

Machine learning enables unbinned, highly-differential cross section measurements. A recent idea uses generative models to morph a starting simulation into the unfolded data. We show how to extend two morphing techniques, Schrödinger Bridges and Direct Diffusion, in order to ensure that the models learn the correct conditional probabilities. This brings distribution mapping (DM) to a similar level of accuracy as the state-of-the-art conditional generative unfolding methods. Numerical results are presented with a standard benchmark dataset of single jet substructure as well as for a new dataset describing a 22-dimensional phase space of Z+2 -jets.

Butter, Anja

Generative learning for slow manifolds and bifurcation diagrams

In dynamical systems characterized by separation of time scales, the approximation of so called “slow manifolds”, on which the long term dynamics lie, is a useful step for model reduction. Initializing on such slow manifolds is a useful step in modeling, since it circumvents fast transients, and is crucial in multiscale algorithms (like the equation-free approach) alternating between fine scale (fast) and coarser scale (slow) simulations. In a similar spirit, when one studies the infinite time dynamics of systems depending on parameters, the system attractors (e.g., its steady states) lie on bifurcation diagrams (curves for one-parameter continuation, and more generally, on manifolds in state parameter space. Sampling these manifolds gives us representative attractors (here, steady states of ODEs or PDEs) at different parameter values. Algorithms for the systematic construction of these manifolds (slow manifolds, bifurcation diagrams) are required parts of the “traditional” numerical nonlinear dynamics toolkit. In more recent years, as the field of Machine Learning develops, conditional score-based generative models (cSGMs) have been demonstrated to exhibit remarkable capabilities in generating plausible data from target distributions that are conditioned on some given label. It is tempting to exploit such generative models to produce samples of data distributions (points on a slow manifold, steady states on a bifurcation surface) conditioned on (consistent with) some quantity of interest (QoI, observable). In this work, we present a framework for using cSGMs to quickly (a) initialize on a low-dimensional (reduced-order) slow manifold of a multi-time-scale system consistent with desired value(s) of a QoI (a “label”) on the manifold, and (b) approximate steady states in a bifurcation diagram consistent with a (new, out-of-sample) parameter value. This conditional sampling can help uncover the geometry of the reduced slow-manifold and/or approximately “fill in” missing segments of steady states in a bifurcation diagram. Finally, the quantity of interest, which determines how the sampling is conditioned, is either known a priori or identified using manifold learning-based dimensionality reduction techniques applied to the training data.

Dynamical systems

Understanding the Conductivity and Transference Trade-Off in Polymer Electrolytes Using a Robeson-Inspired Upper Bound

The development of high-performance electrolytes is crucial for advancing next-generation lithium and sodium battery technologies. Since the cation is the working ion in both technologies, electrolytes exhibiting the rapid cation transport are essential for making progress. Pathways to optimize electrolytes are unclear due to the inherent trade-off between conductivity and cation transference. While this trade-off is sometimes recognized, there are no well-accepted methodologies for quantifying it. Inspired by the Robeson upper bound for the permeability–selectivity trade-off in gas separation membranes, we propose an approach for quantifying the trade-off in electrolytes using Newman’s concentrated solution theory. We suggest calling this the Newman upper bound. By analyzing published data from 30 polymer electrolytes containing univalent lithium and sodium salts, the Newman upper bound is expressed as κ = 2.0­(1/ρ+ – 1) where κ (mS/cm) is conductivity and ρ+ is the current fraction measured in a symmetric cell as first described by Bruce et al. [J. Electroanal. Chem. Interfacial Electrochem. 1987, 225 (1), 1–17]. This formulation of the upper bound introduces a critical guiding metric for designing next-generation polymer electrolytes; it highlights factors underlying the trade-off, including the salt diffusion coefficient (D), cation transference number relative to solvent velocity ( t + 0 ), and thermodynamic factor (1 + (d lnγ+–)/(d lnm)), where γ+– is the mean molar activity coefficient and m is the molality. These parameters have been measured for very few electrolytes. We posit that establishing the molecular properties that govern these parameters will lead to improved electrolytes that greatly exceed the current upper bound.

He, Zirong

Development and validation of non-axisymmetric heat flux simulations with 3D fields using the HEAT code

A new comprehensive module to simulate heat fluxes from three-dimensional (3D) magnetic fields has been implemented in the HEAT code. Especially compact tokamaks like SPARC require tools to predict and manage large heat fluxes. Existing release versions of HEAT can only simulate axisymmetric heat flux on 3D plasma facing components. The new module uses an M3D-C1 perturbed equilibrium and the MAFOT code to trace field lines of the perturbed 3D magnetic field. Heat flux is then assigned to the resulting footprints via a 3D layer model. The model distinguishes between the scrape-off layer, the magnetic lobes and the private flux region, and employs only 0D parameters like the layer width, diffusive spread and the last closed flux surface position in the perturbed edge to generate a heat flux profile. The magnitude is normalized to the total input power. Resulting heat flux simulations are compared and validated against infrared measurements in the DIII-D tokamak with applied 3D fields; good agreement is found for several cases. The new module can now be applied to the SPARC tokamak; a preliminary result for applied rotating 3D fields is shown.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Lithium‐Containing Hybrid SEI Layer Enabling High Mass Loading and Anode‐Less Sodium Metal Batteries

The continuous rupturing and rebuilding of unstable solid electrolyte interphase (SEI) layer during cycling would block Na + diffusion and induce Na dendrite formation, ultimately limiting the practical application of high-energy-density sodium metal batteries. Herein, a hybrid SEI layer containing Li-species is dexterously constructed on the surface of sodium metal anode. Li-containing inorganic components (Li 3 N, LiF, and Li 2 CO 3 ) are introduced to stabilize the Na/electrolyte interface and enhance the mechanical and diffusion kinetic properties of the SEI layer, which can reduce the side reactions and gas generation, regulate Na + flux during cycling and promote rapid Na + migration for uniform dendrite-free Na deposition. As a result, the constructed Na symmetric cells achieve low overpotential and long cycle life of 5900, 1800, and 500 h at current densities of 3, 10, and 30 mA cm −2 , respectively. Furthermore, the full cells paired with the Na₃V₂(PO₄)₃ cathode demonstrate high specific capacity and excellent cycle stability, even at an ultra-high cathode loading of 39.3 mg cm −2 and a low N/P ratio (negative/positive electrode capacity ratio of 1.21).

Diffusion kinetic

Probing the Impact of Vacancy Diffusion on Void Dynamics at the Lithium Metal–Solid Electrolyte Interface

Lithium (Li) metal-based solid-state batteries (SSBs) are considered promising candidates for next-generation energy storage due to their superior energy density and enhanced safety compared to conventional Li-ion systems. However, their practical application is limited by challenges such as void formation at the Li-solid electrolyte (SE) interface, which disrupts ion transport and accelerates interfacial degradation. This work investigates how the coupled effects of electro-dissolution kinetics and surface diffusion at the Li metal surface govern the evolution of interfacial morphology during stripping. This work examines the influence of three distinct surface diffusion modes, which are terrace diffusion, step diffusion, and interlayer diffusion, on maintaining interfacial stability. In addition, how the dominant surface diffusion mechanism can overcome the contact loss due to high reaction kinetics is explored. Furthermore, the roughness of the Li metal anode surface is quantified, and the influence of different diffusion mechanisms on the evolution of the dynamic solid–solid interface is examined. The critical role of temperature in enhancing Li surface diffusivity and expanding the regime of stable contact is highlighted. By identifying distinct regimes of interface stability, this study analyzes how non-uniform electrochemical dynamics dictate void morphology evolution and interfacial contact. These insights offer guiding principles for engineering robust Li–SE interfaces in SSBs.

lithium metal anode

D$e^+e^-$ffusion: Capturing the Beam-Beam Physics of $e^+e^-$ Collisions with Diffusion Models

Beam-induced backgrounds at high-luminosity $e^+e^-$ colliders, such as the FCC-ee, are dominated by incoherent pair creation (IPC), and require computationally expensive simulations with dedicated Monte Carlo (MC) event generators. Reliable detector and machine-detector interface studies necessitate event samples that are several orders of magnitude larger than what is practically attainable with existing MC. To alleviate this bottleneck, we present D$e^+e^-$ffusion, a denoising diffusion probabilistic model that operates as a permutation-equivariant, set-valued surrogate for fast IPC simulation. Trained on a small GuineaPig++ sample, D$e^+e^-$ffusion faithfully reproduces the marginal and joint kinematic, angular, and positional distributions of all three IPC production processes. In addition, we assess the fidelity at the detector level by propagating both Geant4 and D$e^+e^-$ffusion events through a Geant4 simulation of the CLD vertex detector and by training a transformer-based two-sample classifier; the classifier achieves an area under the ROC curve of $0.553 \pm 0.016$. The trained model generates events nearly four orders of magnitude faster than Geant4, paving the way for a fast-simulation surrogate for FCC-ee design studies.

Chahine, Antonio [Imperial Coll., London]

Lithium‐Containing Hybrid SEI Layer Enabling High Mass Loading and Anode‐Less Sodium Metal Batteries

Abstract The continuous rupturing and rebuilding of unstable solid electrolyte interphase (SEI) layer during cycling would block Na + diffusion and induce Na dendrite formation, ultimately limiting the practical application of high‐energy‐density sodium metal batteries. Herein, a hybrid SEI layer containing Li‐species is dexterously constructed on the surface of sodium metal anode. Li‐containing inorganic components (Li 3 N, LiF, and Li 2 CO 3 ) are introduced to stabilize the Na/electrolyte interface and enhance the mechanical and diffusion kinetic properties of the SEI layer, which can reduce the side reactions and gas generation, regulate Na + flux during cycling and promote rapid Na + migration for uniform dendrite‐free Na deposition. As a result, the constructed Na symmetric cells achieve low overpotential and long cycle life of 5900, 1800, and 500 h at current densities of 3, 10, and 30 mA cm −2 , respectively. Furthermore, the full cells paired with the Na₃V₂(PO₄)₃ cathode demonstrate high specific capacity and excellent cycle stability, even at an ultra‐high cathode loading of 39.3 mg cm −2 and a low N/P ratio (negative/positive electrode capacity ratio of 1.21).

Xia, Li [State Key Laboratory of Physical Chemistr

Binder-Free Graphite Anodes for Next-Generation High-Performance Lithium-Ion Batteries

High-energy density anodes are crucial for next-generation lithium-ion batteries (LIBs) particularly for electric vehicle (EV) applications. Sluggish lithium-diffusion kinetics coupled with conventional anode fabrication processes containing polymeric binders hinder fast-charging capabilities and high-energy density of graphite. Herein, we introduce a binder-free graphite anode fabrication strategy using the electrospinning technique that contains ~2.41% carbon nanotubes (CNTs). Our strategy relies on the formation of an interconnecting conductive CNT network coupled with an ultrathin N-doped carbon coating on graphite particles from sacrificial binders. This combination enhances both structural integrity and electrical conductivity and, in turn, improves fast-charging capabilities and high energy density of LIBs. The binder-free graphite anode achieves ~335.0 mAh g–1 capacity at C/3 rate over 400 cycles with capacity retention of >95% and average Coulombic efficiencies >99.95%. These promising results suggest that the binder-free anode fabrication with a multifunctional design approach could elevate the energy-density limits of the graphite anodes, solving high-energy density requirements of EVs, and potentially provides a path forward for the development of economically feasible energy storage systems for various applications.

Ozcan, Muca [ORNL] (ORCID:0000000320020474)

Crystal Growth of Quaternary Rare Earth Selenosilicates by Using the Flux-Assisted Boron Chalcogen Mixture Method: Investigation of Their Magnetic and Optical Properties

A series of rare earth magnesium selenosilicates, RE3Mg 0.5 SiSe 7 (RE = Ce, Pr, Nd, Sm, Gd, Tb, Dy) were obtained as single crystal using the flux assisted boron chalcogen mixture (BCM) method. The structures of the crystals were determined by single-crystal X-ray diffraction. The RE3Mg 0.5 SiSe 7 series crystallizes in the hexagonal crystal system in the space group P6 3 . Polycrystalline powders were synthesized to perform physical property measurements. Magnetic measurements over the 2–300 K temperature range reveal that Ce 3 Mg 0.5 SiSe 7 and Gd 3 Mg 0.5 SiSe 7 exhibit paramagnetic behavior with negative Weiss constants (θ W = −14.50, θ W = −6.13 K, respectively). The optical properties of RE 3 Mg 0.5 SiSe 7 (RE = Ce, Pr, Nd, Sm, Gd) were measured by ultraviolet–visible (UV–vis) diffuse reflectance. Density functional theory (DFT) electronic structure calculations were performed. Furthermore, a second harmonic generation measurement was performed on a polycrystalline powder of Ce 3 Mg 0.5 SiSe 7 and was found to be SHG active with an efficiency of 0.11 times the standard potassium dihydrogen phosphate (KDP).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

A comprehensive review of diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) techniques in protonic ceramic cells (PCCs): Current status and future perspective

Protonic ceramic cells (PCCs) have emerged as a promising technology for power generation, energy storage, and value-added chemical synthesis, offering benefits such as fuel flexibility, low emissions, and efficient operation at intermediate temperatures (300–600 ​°C). Recently, significant breakthroughs in materials and manufacturing methods have markedly enhanced the performance of PCCs. However, establishing a fundamental understanding of their electrocatalytic reactions has gained less attention. As a fast and cost-effective method for physicochemical fingerprinting, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) has proven to be a surface-sensitive analytical tool for structural and functional studies. This review critically examines the most up-to-date applications of DRIFTS for characterizing key components of PCCs, including oxygen electrodes, protonic electrolytes, and hydrogen electrodes for different applications, with a focus on revealing hydration properties and catalytic reactions, and guiding rational material design. The challenges for advancing DRIFTS, including quantitative capabilities and operando applications for PCC investigations, are highlighted and strategies to tackle these challenges are discussed. Ultimately, this review underscores the critical role of DRIFTS in accelerating the development of high-performance and durable PCCs for next-generation energy solutions, offering methodologies and insights broadly applicable to a wide range of electrochemical energy conversion and storage technologies.

Diffuse Reflectance Infrared Fourier Transform Spe

Chemo‐Mechanical Coupling in Hydrogels: Dynamics in the Diffusion‐Limited Regime

Hydrogels are characterized by substantial volume changes in response to external stimuli, making them promising candidates for developing smart materials with enhanced adaptability and responsiveness. By integrating chemical reactions, hydrogels acquire dynamic and tunable responsiveness to external stimuli through chemo‐mechanical coupling, expanding their potential in emerging applications. However, capturing their transient behavior remains challenging due to the complex interplay of chemical reactions, solvent transport, and polymer network deformation. Classical theories capture equilibrium swelling but fail to describe time‐dependent phenomena. To address this, a time‐dependent continuum model is developed that explicitly couples these processes. Volume phase transition in hydrogels with homogeneous chemical reactions is investigated, then the effects of reaction kinetics on these transitions are analyzed. The coupling of these mechanisms is further explored through a study of transient mechanical instabilities. To illustrate the impact of distinct reaction and diffusion timescales, a photo‐active gripper is studied for robotic applications. Finally, a photo‐active microswimmer that exhibits non‐reciprocal motion is proposed to highlight the solvent diffusion for locomotion at the micro‐ and nano‐ scales. The work establishes that transient dynamics of chemo‐mechanical hydrogels generate functions not accessible by steady state models and provides a predictive platform for designing adaptive materials in emerging applications.

chemo-mechanical coupling

From Electronic Structure to Ion Transport: Photoelectron Spectroscopy and Molecular Dynamics Simulations Reveal the Role of Anions in Lithium Battery Electrolytes

Electrolyte anions are pivotal for lithium battery performance, yet their fundamental electronic structural properties are not well understood. In this work, we employ a combination of negative-ion photoelectron spectroscopy (NIPES), ab initio calculations, and molecular dynamics (MD) simulations to investigate the electronic structures of three representative electrolyte anions. This multiscale approach enables us to elucidate how their intrinsic electronic properties govern anion–solvent interactions in gas-phase clusters, as well as lithium-ion (Li + ) solvation structures and ion transport behavior in the condensed phase. NIPES reveals that difluoro(oxalato)borate (DFOB – ), bis(fluorosulfonyl)imide (FSI – ), and bis(oxalato)borate (BOB – ) all exhibit high electron binding energies, with vertical/adiabatic detachment energies increasing from DFOB – (6.09/5.70 eV) to FSI – (6.80/6.10 eV) to BOB – (6.82/6.40 eV), correlating with enhanced oxidation stability. Ab initio calculations reveal that DFOB – /FSI – –solvent complexes bind Li + ∼ 10 kcal/mol stronger than BOB – series, aligning with the strength of a Li + –anion model. DFOB – exhibits pronounced charge localization on both oxygen and fluorine atoms, enabling their involvement in Li + coordination. In contrast, fluorine atoms in FSI – are largely electron-depleted and remain excluded from direct Li + binding. MD simulations further demonstrate that LiDFOB and LiFSI systems exhibit Li + diffusion coefficients three and five times higher than those of LiBOB across four common solvents. Notably, LiFSI salt in acetonitrile (AN) exhibits the fastest Li + diffusion among 12 electrolyte systems, highlighting the synergistic effect of FSI – and AN in promoting ion mobility. In conclusion, these findings provide a molecular-level understanding of the critical roles of anion and its microsolvation in optimizing Li + diffusion dynamics, once again emphasizing the positioning of FSI – and DFOB – as prime candidates for next-generation electrolytes.

25 ENERGY STORAGE

Versatile TRISO fuel particle modeling in Bison

Tri-structural isotropic (TRISO) fuel particles are a key component in several previous and current reactors as well as in a variety of novel nuclear reactor designs. Interest in TRISO fuel is on the rise, necessitating considerable computer modeling of TRISO fuel behavior in order to support related design and licensing activities. The Bison nuclear fuel performance code, which offers a full set of capabilities for modeling TRISO fuels, makes it easier to explore the various important aspects of TRISO fuel behavior. One key advantage of Bison is its ability to create meshes in 1D, 2D, and 3D. Users can customize these meshes for specific geometries, mesh densities, and use cases. This enables a wide variety of analyses, including thermal, structural, mass diffusion, homogenization, and statistical failure analyses. Furthermore, the meshing capability simplifies analysts’ workflows. The inherent mesh generation capability eliminates the need for separate mesh-generating software and mesh file management. Also, the fact that the meshes are customizable makes it straightforward to automate an investigation over a range of geometric parameters or mesh densities. Here, the present paper highlights the ease with which Bison may be used to create meshes for both simple and relatively complex TRISO fuel particles, and it explores the types of analyses enabled by these meshes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS