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At least 55 records · Page 3

Effect of stoichiometry and hydration level on water domain size and transport in poly(aryl piperidinium) alkaline anion-exchange membranes

Alkaline water electrolysis holds promise in decarbonizing the global economy by enabling renewable hydrogen production with non-precious group metal catalysts. Anion exchange membranes are an important component of alkaline water electrolyzers and would ideally be durable while allowing for high hydroxide conductivity. The poly(aryl piperidinium) (PAP) class of polymers has attracted recent interest due to their good mechanical robustness and high ionic conductivity. Here, in this work, we perform atomistic molecular dynamics (MD) simulations of several PAP polymers at experimentally relevant hydration levels and polymer ion exchange capacities (IECs) to gain nanoscale insight into their properties and to help elucidate the trade-offs that result from tuning the IECs through the polymer stoichiometry. Our MD-predicted macroscopic polymer properties were found to be in good agreement with experimentally available polymer swelling ratios, water-occupied volumes, X-ray scattering, and ionic conductivities. The models show that for hydration levels greater than 8H 2 O per cation a single water cluster will form that percolates through the system. The growth in water cluster size results in large polymer swelling, the creation of larger channels with widths of 7 Å or larger, and nanophase separation between the hydrophilic domains and the polymer with characteristic length scales of approximately 20–30 Å. The experimentally observed lack of a strong X-ray scattering peak at low wavevectors can be explained by a cancellation between the polymer-polymer/water-water and polymer-water correlations and not a loss in nanophase separation. The overlap in coordination environments of the hydroxide oxygen and polymer nitrogen atoms implies that vehicular diffusion between cationic groups could play a role in hydroxide transport. The polymers' hydroxide and water diffusion constants increase by approximately an order of magnitude between hydration levels of 8 and 20H 2 O per cation. However, there are diminishing returns in hydroxide diffusion constant once the IEC exceeds 2.4 meq/g.

08 HYDROGEN

Investigating the impact of preparation routes on the properties of copper-decorated silicon particles as anode materials for lithium-ion batteries

In recent years, the calendar life of Si has been recognized as a significant issue that must be addressed prior to technology deployment: The carbon conductive additive is a potential source of parasitic side reactions. However, carbon remains essential due to the low electronic conductivity of Si. In this study, we investigate the use of Cu as a conductive additive and potential alternative to carbon. Some Cu-decorated silicon particles (Si Cu ) were prepared using physical vapor deposition (PVD) via sputtering and high-energy milling. Other Si Cu particles were prepared by using a solution method and examined briefly. The milling method caused Cu to appear as island-like features on the Si surface, whereas the PVD method initially produced similar island-like features that gradually developed into a continuous coating around the Si as sputtering time increased. Electrodes fabricated from Si Cu exhibited lower overall resistivity, demonstrating the beneficial effect of Cu in improving electronic percolation through the electrode. Electrochemical tests showed that the milled SiCu exhibited higher capacity retention, improved rate capability, and lower overpotential. Furthermore, Si Cu coupled with an NMC811 cathode exhibited lower leakage currents compared with the baseline silicon, indicating that incorporating Cu provided an additional advantage of minimizing parasitic currents in the cells.

25 ENERGY STORAGE

Evaluating Material Design Principles for Calcium-Ion Mobility in Intercalation Cathodes

Multivalent-ion batteries offer an alternative to Li-based technologies, with the potential for greater sustainability, improved safety, and higher energy density, primarily due to their rechargeable system featuring a passivating metal anode. Although a system based on the Ca 2+ /Ca couple is particularly attractive given the low electrochemical plating potential of Ca 2+ , the remaining challenge for a viable rechargeable Ca battery is to identify Ca cathodes with fast ion transport. In this work, a high-throughput computational pipeline is adapted to (1) discover novel Ca cathodes in a largely unexplored space of empty intercalation hosts and (2) develop material design rules for Ca-ion mobility. One candidate from the screening, W 2 O 3 (PO 4 ) 2 , is confirmed to have a low Nudged Elastic Band (NEB) barrier of 168 meV within a one-dimensional (1D) ion percolation topology. This candidate is subsequently synthesized and electrochemically tested, achieving reversible Ca cycling with a capacity of 25 mA h/g. To further accelerate the screening for promising Ca intercalation electrodes, machine learning (ML) Random Forest (RF) and Extreme Gradient Boosting (XGB) classification models are created with local environment descriptors based on a large, structurally and chemically diverse dataset of minimum energy pathways, spanning over 5,000 density functional theory (DFT) site energy calculations. Accuracies of 92% are achieved, material design metrics are quantified, ML force-fields are leveraged in an accelerated iteration of the screening, and a total of 27 novel Ca cathode materials are highlighted for further investigation.

25 ENERGY STORAGE

Structure–Activity Relationships in Ether-Functionalized Solid-State Metal–Organic Framework Electrolytes

The structure–property relationships of metal–organic framework (MOF)-based solid-state electrolytes are not well understood. Herein, a systematic investigation of 12 Zr(IV)-based UiO-66 MOFs with varying ether-chain functional groups was carried out to elucidate the critical microscopic interactions that facilitate improved solid-state electrolyte performance. Enhanced sampling molecular dynamics (MD) simulations were employed and revealed a three-tier ion hopping mechanism: linker–linker hopping, linker-counterion hopping, and counterion-counterion hopping. Detailed structural analysis of the MD trajectories revealed that the chemistry and morphology of the linker groups affect the relative stability and population distribution of the electrolyte components, such that crown-ether-based linker groups enhance the probability of extended, low-barrier ion percolation pathways. As a result, we were able to tune the ionic conductivities by rationally manipulating the counterion distributions, linker binding strengths, and the configurational entropy (multivariability of the linkers). The resulting performance of these MOF-based solid-state electrolytes was significantly enhanced, with a methoxy-functionalized framework (UiO-66-L1 100 ) achieving high ionic conductivities of 2.32 × 10 –4 S/cm and 2.07 × 10 –3 S/cm at 30 °C and 90 °C, respectively, an order of magnitude greater than other all-solid-state MOF electrolyte systems. The electrolyte stability was evaluated with LiIn|LPSCl|MOF:LiTFSI|LPSCl|LiIn symmetric cells, showing excellent Li plating/stripping processes for over 2 months.

36 MATERIALS SCIENCE

Formation of Disordered Cocontinuous Phases by Randomly Linked Star Copolymers

Cocontinuous polymeric nanostructures have garnered significant interest due to their ability to combine different properties of two separate polymer domains. Randomly linked copolymer networks have proven to be especially robust for formation of disordered cocontinuous phases across wide composition ranges (≈30 wt % or more). While theoretical treatments of microphase-separated networks have focused primarily on the role of random elastic forces imposed on the self-assembled nanostructures by virtue of the network architecture, experimental studies seeking to disentangle these contributions from other potential effects, such as dispersity in preferred interfacial curvatures, have been scarce. To provide insight into this matter, we here study the self-assembly of randomly linked star copolymers (RSCs), constructed by linking premade polymer arms of polystyrene (PS) and poly(d,l-lactide) (PLA) using 3, 4, and 6-functional connectors. This architecture yields similar distributions of preferred curvature as networks made using corresponding difunctional strands, but lacks the elastic forces imposed by a network architecture. Gravimetry and small-angle X-ray scattering, coupled with scanning electron microscopy, were performed to identify the percolation of PS/PLA RSCs. Remarkably, the 4-arm RSC system exhibited a disordered cocontinuous window of ≈25 wt %, indicating that dispersity in preferred curvature can in some cases be sufficient to robustly drive formation of this morphology. However, the other RSC architectures showed smaller cocontinuous ranges, which we interpret in terms of the influence of homopolymer stars in the 3-arm case and the narrower distribution of preferred interfacial curvatures in the 6-arm case. Finally, thin layers of interconnected porous PS were achieved by solution-processing, suggesting that RSCs have the potential to serve as a robust and easily processable cocontinuous polymeric nanomaterials in both bulk and membrane geometries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Tunneling Barrier-Integrated Gold Nanofilms for Negative Strain Gauging with Near-Zero Energy Consumption

Wireless strain sensors with minimal power needs are essential for long-term monitoring in energy-limited environments. We present a soft tunneling barrier-integrated gold thin film for negative strain sensing with near-zero energy consumption. The device features a strain-induced transition from an insulating to a metallic state, increasing conductivity by 9 orders of magnitude under a controlled strain. It consists of Au-PDMS-Au nanofilm layers, where the Au structures are near the percolation threshold and the PDMS layer acts as a tunneling barrier. Under strain, thinning due to the Poisson effect lowers the barrier’s potential height, enabling electron tunneling and forming an electrical path. Further, with a standby power consumption of ~10 –5 mW over 10 6 times lower than conventional sensors (~12.5 mW), this device is ideal for real-time, long-term stationary structural monitoring in multiple locations.

77 NANOSCIENCE AND NANOTECHNOLOGY

Harnessing the Second-Order Metal−Insulator Transition for Neuromorphic Computing

Vanadium oxides are widely studied phase change materials for brain-inspired computing architectures. Systems like VO 2 and V 2 O 3 exhibit first-order metal−insulator transitions (MITs) with hysteresis and percolative switching, increasing stochasticity and device variability. Here, we focus on the less explored Magnéli phase V 4 O 7 , which undergoes a continuous, non-hysteretic, second-order MIT. This surprisingly enables highly reproducible volatile resistive switching in spiking-neuron-type devices. We synthesize V 4 O 7 films, characterize their structural and transport properties, and demonstrate voltage and current-driven threshold switching with electrothermal feedback. In a Pearson–Anson oscillator, V 4 O 7 devices produce stable, tunable spiking across 20–200 kHz, with consistent operation among multiple devices. We introduce a numerical analog leaky-integrate-and-fire (aLIF) model that captures waveform shapes and their dependence on load resistance, temperature, and voltage. Furthermore, these findings suggest that second-order MIT materials like V 4 O 7 are promising for deterministic, scalable spiking neuron arrays for neuromorphic computing.

V4O7

Elucidating Lithium Transport Mechanisms in Disordered LiF from Machine-Learning Molecular Dynamics Simulations

Lithium fluoride (LiF) is a ubiquitous component of solid- and cathode–electrolyte interphases, yet its functional role remains unclear under the structural and chemical heterogeneity typical of cycling batteries. Here, we systematically quantify how structural disorder, off-stoichiometry, and strain govern Li-ion transport in LiF. Using a machine-learning potential to enable extensive molecular-dynamics sampling, we compare crystalline and amorphous LiF, Li 0.95 F, and LiF 0.95 , and evaluate the impact of small homogeneous deformations. Defect-free crystalline LiF is effectively ion-blocking at 300−500 K, whereas amorphization generates free-volume–assisted percolation pathways that facilitates Li-ion diffusion. At elevated temperatures, thermodynamically driven crystallization disrupts these pathways, leading to non-Arrhenius behavior. In crystalline phases, Li deficiency activates vacancy-mediated diffusion, while in amorphous LiF, transport is governed primarily by network connectivity. Strain is found to have only a marginal effect on Li mobility in both crystalline and amorphous structures.

Batteries

Stabilized Oxygen Vacancy Chemistry toward High-Performance Layered Oxide Cathodes for Sodium-Ion Batteries

Anionic redox has emerged as a transformative paradigm for high-energy layered transition-metal (TM) oxide cathodes, but it is usually accompanied by the formation of anionic redox-mediated oxygen vacancies (OVs) due to irreversible oxygen release. Additionally, external factor-induced OVs (defined as intrinsic OVs) also play a pivotal role in the physicochemical properties of layered TM oxides. However, an in-depth understanding of the interplay between intrinsic and anionic redox-mediated OVs and the corresponding regulation mechanism of the dynamic evolution of OVs is still missing. Herein, we disclose the strong interrelationship between these OVs and demonstrate that the presence of intrinsic OVs in the TMO2 layers could induce weak integrity of the TM-O frameworks and unlock additional diffusion paths to trigger the generation and migration of anionic redox-mediated OVs. Accordingly, an OV stabilization strategy is proposed by deliberately introducing high-valence Nb5+, which could serve as an important building block in anchoring the oxygen sublattice and preventing the formation of a percolating OV migration network, thereby suppressing the formation/diffusion of anionic redox-mediated OVs. Consequently, superb structural integrity and improved electrochemical performance with reversible anionic redox chemistry are achieved. This work advances our understanding of the role of OVs for developing high-performance energy storage systems utilizing anionic redox.

anionic redox

Coexistence of Synchronization and Stochasticity in Thermally Coupled Mott Oscillators

Synchronization is conventionally regarded as a mechanism for suppressing variability and enforcing order in coupled systems, from pendula and lasers to neurons and electronic oscillators. Here, we show that synchronization can also embed stochasticity at finer scales. We observe this phenomenon in thermally coupled VO 2 neuristors, where robust in-phase synchronization at the microsecond scale coexists with spike onset fluctuations at the nanosecond scale, with no fixed leader. The coexistence of order and disorder originates from stochastic domain-level physics of the insulator–metal and metal–insulator transitions, where local variations in transition temperature drive cycle-to-cycle randomness in nucleation, percolation, and relaxation. A stochastic domain model reproduces this effect by generating synchronized spike trains with random lead–lag jitter, and experimental interspike interval statistics confirm the persistence of fine-scale variability despite macroscopic phase locking. These findings establish that synchronization and stochasticity can coexist within the same physical platform, revealing hidden disorder within collective order. Furthermore, this insight reframes synchronization as not purely deterministic, but as a universal context where microscopic variability can persist, with implications for electronics, cryptography, and the fundamental physics of order–disorder coexistence.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Shear Response of Ionizable Polymer Melts at the Crossover from Ionomers to Polyelectrolytes

Nonlinear shear response of polymers is affected by inherent barriers for diffusive motion, including entanglements and topology. In ionizable polymers, ionic clusters further constrain the intrinsic dynamics of the polymers, significantly enhancing their viscosity. Here, using fully atomistic molecular dynamics simulations, the nonlinear shear response of ionizable polymers is presented, across the transition from the ionomer regime where distinctive clusters dominate the structure to the polyelectrolyte regime where clusters percolate, in polystyrene randomly sulfonated with fractions of SO 3 − groups of f = 0.20 and 0.35, in pristine and tetrahydrofuran (THF) swollen polyelectrolyte melts. For f = 0.20, the ionic clusters first fracture into smaller clusters followed by splitting into individual ionic groups and eventually reform. At higher f, the clusters morph in shape but do not break under high shear. At very high shear rates, all of the chains stretch and recoil rapidly. As the shear rate is reduced, some chains stretch and recoil, while others remain largely unaffected by the shear. Macroscopically, for all systems, the shear viscosity displays initially an elastic response, followed by nonlinear shear stress overshoot and, eventually, a steady state. The evolution of viscosity with time and shear reflects that of the ionizable domains.

cluster chemistry

Local Cation-Ordered Superlattice Stabilizing Ni-Rich Single-Crystalline Cathodes

Ni-rich single-crystalline cathodes are pivotal for advancing lithium-ion battery technology due to their high energy density and mechanical stability. However, Ni-rich single-crystalline particles face intrinsic structural heterogeneity due to excessively high sintering temperature required to shape micron-sized morphologies─typically over 150 °C above the polycrystalline optimum, leading to rapid electrochemical decay and unsatisfied rate performance that hinder their practical application. Here, in this work, we propose a lithium-deficient presintering strategy to synthesize cation-ordered single-crystalline LiNi 0.83 Co 0.12 Mn 0.05 O 2 (S-NCM83), effectively minimizing lattice chemical heterogeneity and defect formation. The resulting cation-ordered percolation network enhances the structural stability of the bulk, reduces the energy barrier for Li + migration, and stabilizes Li + diffusion pathways. Consequently, S-NCM83 demonstrates significantly improved cycling stability across various operating temperatures and achieves exceptional rate performance, delivering 206 mAh g –1 at 0.1 C and 170 mAh g –1 at 5 C, without requiring surface coatings or doping. This work introduces a universal strategy to address the long-standing structural instability issues in single-crystalline cathodes, paving the way for simplified and scalable approaches to long-life and high-energy lithium-ion batteries.

36 MATERIALS SCIENCE

Predicting Flow in Fracture Networks With Quantum Algorithms

Uncertainty quantification plays a crucial role in the modeling of subsurface flow. For instance, uncertainties in the properties of geologic fracture networks significantly impact flow, requiring numerous simulations to accurately estimate quantities of interest. However, each simulation is computationally expensive because it requires solving a large linear system to capture features that involve both small and large fractures. An example is in percolation, where the interaction of many small fractures (which cumulatively can have a large surface area) with the rock matrix must be modeled precisely. Quantum computing is an emerging tool with the potential to address this issue. Quantum algorithms offer a significant speedup in solving linear systems, achieving efficiencies that are challenging to match with classical approaches. These classical approaches include direct solvers, such as LU decomposition, and iterative methods, notably preconditioned conjugate gradient, commonly used in subsurface modeling to solve large sparse systems. However, applying quantum algorithms to geologic fracture flow requires careful attention to algorithmic and problem-specific constraints to fully realize this quantum advantage. In this work we describe a quantum algorithm for generalized Monte Carlo applications with a quadratic speedup over the classical approaches which can be combined with the quantum speedup, currently under investigation, for solving quantum linear systems for subsurface flow. We show that for quantum algorithms the computational cost of estimating a quantity of interest for a statistical ensemble of networks is roughly the same as that of a single realization, essentially implying that one can get uncertainty quantification for free.

58 GEOSCIENCES

Conformally coated scaffold design using water-tolerant Pr 1.8 Ba 0.2 NiO 4.1 for protonic ceramic electrochemical cells with 5,000-h electrolysis stability

Protonic ceramic electrochemical cells (PCECs) have potential as long-duration energy storage systems. However, their operational stability is limited under industrially relevant conditions due to the intrinsic chemical instability of doped barium cerate-based electrolytes and oxygen electrodes against H 2 O, as well as the poor electrode–electrolyte interfacial contact. Here, in this study, we present a conformally coated scaffold (CCS) design to comprehensively address these issues. A porous proton-conducting scaffold is constructed and conformally coated with Pr 1.8 Ba 0.2 NiO 4.1 electrocatalyst, which has high chemical stability against H 2 O, triple conductivity and hydration capability, and protects vulnerable electrolytes from H 2 O. The CCS structure consolidates the electrode–electrolyte interfacial bonding to enable fast proton transfer in the percolated network. This design enables PCECs to reach electrolysis stability for 5,000 h at −1.5 A cm−2 and 600 °C in 40% H 2 O. This work provides a general strategy to stabilize PCECs and offers guidance for designing resilient and stable solid-state energy storage systems.

Protonic ceramic electrochemical cell

Optical control of orbital magnetism in magic-angle twisted bilayer graphene

Flat bands in twisted graphene structures host various strongly correlated and topological phenomena. Optically probing and controlling them can reveal important information such as symmetry and dynamics, but this has been challenging due to the small energy gap compared with optical wavelengths. Here, in this study, we report on the near-infrared optical control of orbital magnetism and associated anomalous Hall effects in a magic-angle twisted bilayer graphene on a monolayer WSe 2 device. We demonstrate control over the hysteresis and amplitude of the anomalous Hall effect near integer moiré fillings using circularly polarized light. By modulating the light helicity, we observe periodic modulation of the transverse resistance in a wide range of fillings, indicating light-induced orbital magnetization through a large inverse Faraday effect. At the transition between metallic and anomalous Hall effect regimes, we also reveal large and random switching of the Hall resistivity, which we attribute to the light-tuned percolating cluster of magnetic domains. Our results demonstrate the potential of the optical manipulation of correlation and topology in moiré structures.

Persky, Eylon [Stanford Univ., CA (United States);

Superionic conduction in solid polymer electrolytes – decoupling ion transport from segmental relaxation

Solvent-free, solid polymer electrolytes (SPEs) are promising candidates for next-generation, electrochemical energy storage systems due to their potential to enhance safety and performance, enable flexible device architectures, and streamline manufacturing processes. Conventional SPEs suffer from limited ionic conductivity due to the strong coupling between ion transport and (generally slow) polymer segmental relaxation. The realization of superionic conduction in SPEs, in which ions move faster than the structural relaxation of the polymers, requires a shift in design principles to promote this type of decoupled ion motion. In this perspective, we discuss how polymer architecture, ion–ion correlations, and ion–polymer interactions can unlock superionic behavior. We highlight several key design features, such as crystallinity, bulky side groups, high molecular weight, and percolating ionic aggregation, with a focus on creating low-barrier transport pathways in various polymer systems. We also demonstrate opportunities to combine polymer chemistry and data science through high-throughput and automated screening approaches to reveal how phase behavior, ion dynamics, and ionic interactions govern transport, thereby potentially enabling data-driven discovery of superionic polymer electrolyte materials.

Yang, Mengying [Univ. of Delaware, Newark, DE (Uni

Charge regulation effects on colloidal mixture nanoparticles

Changes in pH within a system containing dissociable sites affect the protonation and deprotonation of these groups, thereby influencing their physical properties. In response, the system modifies their surface charge, affecting electrostatic interactions, aggregation, stability, and structural behavior. Although the pH can be tuned in experiments, it is difficult to model this phenomenon using simulations or theoretical approaches. Here, we perform hybrid Monte Carlo-molecular dynamics simulations to model charge regulation effects in an equimolar colloidal charged system. We compare charge regulation effects with those of a system in which the charges of colloidal nanoparticles are not dissociable. The comparison between the two cases modifies the phase diagram, and it changes the volume fraction where a percolation network of nanoparticles is found. Charge regulation is found to destroy network formation, as the charge in the nanoparticles is modified because of the cooperativity dependency of the degree of charge dissociation sites among the nanoparticles favoring cluster formation. Furthermore, our work suggests that the ionic and/or electronic conductivity in functionalized nanoparticles can be modified by changing pH values. It also guides the experimental design of oppositely charged nanoparticles as inks for 3D printing processes.

Classical statistical mechanics

Investigating the impact of higher-order phase transitions in binary neutron-star mergers

In this paper we investigate quark deconfinement in neutrons stars and their mergers, focusing on the effects of higher orders for the phase transition between hadronic and quark matter. The different descriptions we use to describe matter microscopically contain varying particle degrees of freedom, including nucleons, hyperons, Delta baryons, and light and strange quarks. We use tabulated equations of state from the CompOSE database in which the quark deconfinement phase transition is described as being first order, and then smooth it out by introducing a percolation, replacing the single first-order phase transition with two transitions of second or third order. We then perform binary neutron-star merger simulations using these new equations of state, focusing on groups of binaries with the same single-star mass, radius, and tidal deformability, but different equations of state. Here, we go on to discuss differences in their evolution, and the ramifications for interpreting future gravitational wave observations and the potential to learn about dense matter.

79 ASTRONOMY AND ASTROPHYSICS