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Autonomous phototaxis of hydrogel swimmers

The design of synthetic soft matter capable of emulating the complex behaviors of living organisms, such as sensing and adapting to their environment, remains an important challenge in developing biomimetic materials. Functionalized hydrogels are ideal candidates for such materials since they are highly responsive to their environment and can be operated in water. In this work, we investigate a hybrid bonding hydrogel composed of peptide amphiphile supramolecular nanofibers covalently attached to a photoresponsive network, in which high-aspect-ratio ferromagnetic nanowires are aligned along the length of the sample, designed to swim under oscillating magnetic fields. This hybrid hydrogel swimmer can autonomously swim toward a light source by utilizing photoinduced interactions between supramolecular and covalent networks reminiscent of phototactic swimming in living systems. Using a combination of experimental techniques and a continuum model incorporating photochemistry, magnetoelasticity, and hydrodynamics, we explain the swimming mechanism and predict phototactic behavior. Our work highlights the potential role of hybrid bonding polymers, which leverage the interplay between supramolecular assemblies and covalent networks. We demonstrate how these polymers can be tailored to react dynamically to their environment, paving the way for developing intelligent and autonomous robotic systems.

Science & Technology - Other Topics

A parametric study of slow dynamic nonlinear elasticity with comparisons to models

Several phenomenological models that aspire to quantitative description of anomalous nonlinear mesoscopic elasticity are reviewed and compared with laboratory measurements. This class of nonlinearity, best known perhaps for slow dynamics and aging, is seen widely in imperfectly consolidated granular solids but is not well understood. Typical slow dynamic tests show that a modest conditioning oscillatory "pump" strain depresses material stiffness, which then recovers like the logarithm of time after conditioning ceases. Several phenomenological models based on physical arguments have been proposed that predict the material stiffness response to arbitrary pump strain histories during conditioning and recovery. Approximate closed form and numerical solutions to the models are presented that predict the quantitative influence of three key pump parameters: the pump's strain amplitude, the pump's strain rate, and the pump’s duration. Laboratory measurements on Berea sandstone, concrete and a confined single aluminum bead find that slow dynamic responses are linear in pump strain and independent of pump frequency. Measurements also show that, after pump-off, stiffness recovers over times far longer than the pump duration. These observations and others are compared to model predictions. One of the considered models, based on a picture of fast brittle damage and slow healing, successfully matches all these behaviors.

36 MATERIALS SCIENCE

Eliminating chemo-mechanical degradation of lithium solid-state battery cathodes during >4.5 V cycling using amorphous Nb2O5 coatings

Abstract Lithium solid-state batteries offer improved safety and energy density. However, the limited stability of solid electrolytes (SEs), as well as irreversible structural and chemical changes in the cathode active material, can result in inferior electrochemical performance, particularly during high-voltage cycling (>4.3 V vs Li/Li + ). Therefore, new materials and strategies are needed to stabilize the cathode/SE interface and preserve the cathode material structure during high-voltage cycling. Here, we introduce a thin (~5 nm) conformal coating of amorphous Nb 2 O 5 on single-crystal LiNi 0.5 Mn 0.3 Co 0.2 O 2 cathode particles using rotary-bed atomic layer deposition (ALD). Full cells with Li 4 Ti 5 O 12 anodes and Nb 2 O 5 -coated cathodes demonstrate a higher initial Coulombic efficiency of 91.6% ± 0.5% compared to 82.2% ± 0.3% for the uncoated samples, along with improved rate capability (10x higher accessible capacity at 2C rate) and remarkable capacity retention during extended cycling (99.4% after 500 cycles at 4.7 V vs Li/Li + ). These improvements are associated with reduced cell polarization and interfacial impedance for the coated samples. Post-cycling electron microscopy analysis reveals that the Nb 2 O 5 coating remains intact and prevents the formation of spinel and rock-salt phases, which eliminates intra-particle cracking of the single-crystal cathode material. These findings demonstrate a potential pathway towards stable and high-performance solid-state batteries during high-voltage operation.

Science & Technology - Other Topics

Energy 101 - Wind [Slides]

The Energy 101: Wind presentation, developed for the Energy Technology Innovation Partnership Project (ETIPP), provides an overview of wind energy. It covers fundamental concepts, technologies, considerations, case studies, and additional resources.

17 WIND ENERGY

Assembly bias and local Primordial non-Gaussianity from DESI DR1 quasars

The analysis of the large-scale clustering of quasars (QSO) observed by the Dark Energy Spectroscopic Instrument (DESI) represents a promising avenue for constraining local Primordial non-Gaussianity (PNG), parameterized by f NL . The signal to be constrained is the scale-dependent bias induced in the 2-point clustering of the considered tracer sample. The resulting constraints on f NL , however, are fully degenerate with the local PNG bias parameter b ϕ , dependent on the assembly bias parameter p. Using IllustrisTNG hydrodynamical simulations, we select a QSO sample reflecting the selection criteria and properties of DESI QSOs, and provide a robust prior for p, and thus for b ϕ , building on the findings of Fondi et al. 2024. We find a distribution with mean p̅ ≃ 1.4 with weak redshift dependence, stable to selection noise and consistent with the expected recent merger history typical of quasar-hosting halos. By comparing with the CAMELS simulations we demonstrate that this prior is robust to astrophysical assumptions and cosmic variance. Finally, applying this prior to the DESI DR1 dataset, we derive updated constraints on local PNG, obtaining f NL = -3.3±9.2.

cosmological parameters from LSS

Internet of Things Data Characterization Process: Pattern of Life Behavioral Data Study

The HoneyBee™ TARDIS LDRD team completed a data scoping study that identified the initial processes and procedures to baseline the normal and expected behaviors during operability and interoperability of Internet of Things (IoT) device networks. This research is the initial step in developing a process (or methodology) to inform a much broader information framework incorporating machine learning to determine device pattern-of-life which enables the detection of abnormal IoT behaviors on an individual device, as well as in the context of a larger network.

97 MATHEMATICS AND COMPUTING

In Situ UV–vis Quantification of Chlorobasicity in Binary Molten Chlorides

Optical basicity measurements provide a basis for determining the relative chlorobasicity of a given molten salt composition. This study uses Bi3+ as a spectroscopic probe to investigate optical basicity across three binary molten chloride systems (LiCl-KCl, MgCl2–KCl, and ZnCl2–KCl) through in situ UV–vis spectroscopy measurements of the 1S0→3P1 transition. LiCl-KCl systems exhibit the highest optical basicity with minimal compositional dependence, while both divalent systems show stronger, yet nonlinear, dependence that is reminiscent of acid–base titration curves. The influence of cation electronegativity and polarizing power (Li+ < Mg2+ < Zn2+) directly reflects the basicity curves, with ZnCl2–KCl displaying the steepest gradients and lowest basicity values. Nonlinear dependencies in divalent systems indicate formation of chloride-bridged network structures with coordination states dictated by the amount of KCl in a salt composition, which was further investigated and validated by molecular dynamics simulations of polymeric structures formed in ZnCl2 and MgCl2-based salts using machine learning force fields. The temperature dependence of chlorobasicity in terms of optical basicity was investigated, and a loose, positive correlation between the two was revealed. These findings establish Bi3+ as a sensitive probe for understanding electronic environments in molten chloride systems and provide insights for predicting the chemical behavior of molten salts for use in high-temperature environments.

Buttice, Kailee [Department of Nuclear Engineering

Terahertz conductivity of two-dimensional materials: a review

Two-dimensional (2D) van der Waals materials are shaping the landscape of next-generation devices, offering significant technological value thanks to their unique, tunable, and layer-dependent electronic and optoelectronic properties. Time-domain spectroscopic techniques at terahertz (THz) frequencies offer noninvasive, contact-free methods for characterizing the dynamics of carriers in 2D materials. They also pave the path toward the applications of 2D materials in detection, imaging, manufacturing, and communication within the increasingly important THz frequency range. In this paper, we overview the synthesis of 2D materials and the prominent THz spectroscopy techniques: THz time-domain spectroscopy, optical-pump THz-probe technique, and optical pump–probe THz spectroscopy. Through a confluence of experimental findings, numerical simulation, and theoretical analysis, we present the current understanding of the rich ultrafast physics of technologically significant 2D materials: graphene, transition metal dichalcogenides, MXenes, perovskites, topological 2D materials, and 2D heterostructures. Finally, we offer a perspective on the role of THz characterization in guiding future research and in the quest for ideal 2D materials for new applications.

2D materials

Unique Conductivity Behavior in Water-In-Salt Electrolytes Driven by Ion Clusters

Understanding and predicting ion transport in aqueous electrolytes are crucial for advanced energy storage and biophysics, and many emergent technologies yet remain elusive. Herein, we introduce a unified framework to quantitatively describe and predict electrolyte conductivity that shifts from conventional molar concentration-based metrics to a volume fraction-based approach. Through analyzing a variety of electrolyte solutions via this perspective, we observe a universal conductivity peak at a 37% volume fraction. Small-angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations reveal that nanometer-scale ion clusters drive this general behavior. Moreover, key geometric features of the ion transport pathwayssuch as pore size, tortuosity, and connectivityfollow a consistent dependence with respect to the volume fraction, reinforcing the argument for the universal conductivity trend. This paradigm shift opens new avenues for designing high-performance electrolytes and provides transformative insights for advancing studies in many fields, wherein molecular aggregates dictate transport properties.

Nguyen, Huong T. D.

Manganese‐Based Spinel Cathodes: A Promising Frontier for Solid‐State Lithium‐Ion Batteries

Recently, all-solid-state lithium-ion batteries (ASSLIBs), which exhibit improved safety and enhanced energy density compared to conventional commercialized lithium-ion batteries (LIBs), thereby have garnered extensive research interest. Among the promising cathode candidates, Mn-based spinel cathodes LiMn 2 O 4 (LMO) and LiNi 0.5 Mn 1.5 O 4 (LNMO), with the unique characteristics of low cost, structural stability, and 3D Li-ion diffusion channels, have demonstrated excellent performance in LIBs and presented great potential in ASSLIBs applications. However, several challenges, including structural degradations, poor interfacial contact, large interfacial resistance, and Mn-dissolution/diffusion during the electrochemical cycling, hinder their practical applications and commercialization in the ASSLIBs. Particularly, the high-voltage LNMO cathodes suffer from the challenge of electrochemical incompatibility with most of the solid-state electrolytes (SSEs). Herein, the spinel structure, the electrochemical behavior, and the structural degradation of the LMO/LNMO are explored. The characteristics and recent progress of the mitigating strategies to the challenges of various SSEs, including polymer-, oxide-, composite-, sulfide-, halide-, and LiPON-based SSEs, are introduced when paired with LMO/LNMO. Finally, the directions for future research to advance Mn-based spinel cathodes and fulfill the requirements of the next-generation ASSLIBs are also discussed.

Dou, Yu [Concordia University, Montreal, QC (Canad

Activity-induced migration of viscous droplets on a solid substrate

Active matter exploits motion to induce changes in shape and conformation via external input. Here, in this paper, we establish theoretically that viscous liquid droplets containing magnetic nanoparticles with frozen-in magnetic moments, sitting on a solid substrate and surrounded by an ambient gas phase, can deform and migrate under the influence of a magnetic torque. The effect arises because the collective rotation of the magnetic nanoparticles at the liquid–gas interface tilts the droplet away from a symmetric configuration, breaks the reflection symmetry with respect to the centre axis, and leads to a left–right asymmetry of the contact angles. A sufficiently strong magnetic torque leads the contact angles to overcome hysteresis effects leading the droplet to migrate. We develop a general framework to explain how symmetry-breaking affects droplet migration. Thus previous results of droplet spreading and migration can be recovered as special cases. Such droplets can be employed as agents in active surfaces and can move against gravity, chemical and thermal gradients, providing a mechanism that could be utilized by both industry and medicine.

Aggarwal, A. [Northwestern Univ., Evanston, IL (Un

3D Printing ofThermally Responsive Shape Memory LiquidCrystalline Epoxy Networks

Abstract A two-component liquid crystalline epoxy network (LCEN) with shape memory behavior was developed and evaluated as a candidate material for 3D printing. The cure kinetics of the uncured material and the shape memory properties of the cured LCEN were investigated by using parallel plate rheology and dynamic mechanical analysis, respectively. A commercially available fumed silica additive was introduced to the neat, uncured material to improve the rheological properties for 3D printing. The addition of fumed silica was found to increase the yield stress, shear-thinning behavior, and toughness of the uncured epoxy ink. Polarized light microscopy, differential scanning calorimetry, and wide-angle X-ray scattering measurements between the neat and additive-modified LCEN suggested a reduction in liquid crystalline alignment in the modified LCEN, owing to interactions between crystalline domains and fumed silica, which in turn influenced the mechanical behavior. Overall, the additive was found to be successful in preserving the shape memory properties of LCEN while improving its printability.

Chemistry

Techno-Economic Evaluation of a 600MW Pumped Storage Hydropower Plant using the Pumped Storage Hydropower Valuation Tool

This paper presents a techno-economic evaluation of the proposed 600 MW, 8-hour Craig – Hayden pumped storage hydropower project using the U.S. Department of Energy’s Pumped Storage Hydropower Valuation Tool. The analysis integrates plant technical characteristics, regional grid conditions, and market-based operating assumptions to quantify stacked value streams from energy arbitrage, capacity, ancillary services, transmission congestion relief, and reliability. Both price taker and price influencer frameworks are applied to examine the impact of market participation and system interactions on lifecycle economic performance using Benefit - Cost Analysis and Multi - Criteria Decision Analysis. The results show that the price taker approach provides higher revenue estimates based on exogenous price signals, while the price influencer approach captures production cost savings, renewable curtailment reduction, and market price formation, yielding more conservative but system-representative outcomes. The study demonstrates the strategic value of long-duration PSH for enhancing operational flexibility, resource adequacy, and grid reliability in a high-renewable Western Interconnection.

Bhattacharyya, Arjun [ORNL] (ORCID:000900060976046

Effect of Biomass Water Dynamics in Cosmic-Ray Neutron Sensor Observations: A Long-Term Analysis of Maize–Soybean Rotation in Nebraska

Precise soil water content (SWC) measurement is crucial for effective water resource management. This study utilizes the Cosmic-Ray Neutron Sensor (CRNS) for area-averaged SWC measurements, emphasizing the need to consider all hydrogen sources, including time-variable plant biomass and water content. Near Mead, Nebraska, three field sites (CSP1, CSP2, and CSP3) growing a maize–soybean rotation were monitored for 5 (CSP1 and CSP2) and 13 (CSP3) years. Data collection included destructive biomass water equivalent (BWE) biweekly sampling, epithermal neutron counts, atmospheric meteorological variables, and point-scale SWC from a sparse time domain reflectometry (TDR) network (four locations and five depths). In 2023, dense gravimetric SWC surveys were collected eight (CSP1 and CSP2) and nine (CSP3) times over the growing season (April to October). The N0 parameter exhibited a linear relationship with BWE, suggesting that a straightforward vegetation correction factor may be suitable (fb). Results from the 2023 gravimetric surveys and long-term TDR data indicated a neutron count rate reduction of about 1% for every 1 kg m−2 (or mm of water) increase in BWE. This reduction factor aligns with existing shorter-term row crop studies but nearly doubles the value previously reported for forests. This long-term study contributes insights into the vegetation correction factor for CRNS, helping resolve a long-standing issue within the CRNS community.

Chemistry

Humins-Derived Hard Carbon as a Low-Cost Material for Sodium-Ion Battery Anodes

The growing demand for sodium-ion batteries (SIBs) in grid storage underscores the need for electrode materials that balance performance and cost, including sustainable and robust carbon sources. The equitable and abundant distribution of materials for SIBs, along with their superior low-temperature performance, safety, and fast-charging capability, further distinguishes them from lithium-ion batteries (LIBs). Hard carbon (HC) is the state-of-the-art anode for SIBs, but current commercial HC production is localized mostly to one region of the world, raising concerns about supply chain vulnerability, critical material dependency, and environmental aspects. Here, the first demonstration of humins, an abundant biorefinery byproduct, as a precursor for HC anodes for sodium-ion storage is reported. Humins were carbonized at 1100 degrees C-1300 degrees C, and the resulting materials were subjected to comprehensive materials and electrochemical characterization. Among the temperatures studied, humins-derived hard carbon synthesized at 1200 degrees C delivers an initial reversible capacity 270mA h g-1 , with stable cycling performance up to 500 cycles and excellent rate capability, representing the optimal performance. This study establishes humins as a promising and low-cost carbon source that provides a route to mitigate supply chain risks and valorizes an underutilized biorefinery waste stream for high-performance SIB anodes.

25 ENERGY STORAGE

Small Co-doping induced magnetic and electrical transitions in single crystal CaF⁢e 0.95 ⁢C⁢o 0.05 ⁢O 3

CaFe⁢O 3 and CaF⁢e 0.95 ⁢C⁢o 0.05 ⁢O 3 single crystals were grown by combing floating-zone method with high oxygen pressure treatment. Both crystals show charge disproportionation of Fe (F⁡e 4+ → F⁡e 3+ + F⁡e 5+ ) accompanied by a metal-to-insulator transition as well as a crystal structural transformation from Pbnm to 𝑃⁢2 1 /𝑛. However, the slight introduction of Co significantly suppresses the critical temperature of charge disproportionation from 290 K in CaFe⁢O 3 to 260 K in CaF⁢e 0.95 ⁢C⁢o 0.05 ⁢O 3 . Different from the single antiferromagnetic phase transition as observed in the polycrystalline CaFe⁢O 3 , two sequential antiferromagnetic transitions are found to occur in these two single crystals with the Néel temperatures around 119 and 112 K for CaFe⁢O 3 crystal and 109 and 98 K for CaF⁢e 0.95 ⁢C⁢o 0.05 ⁢O 3 crystal, respectively. Neutron diffraction illustrates the formation of a spiral antiferromagnetic structure. Moreover, as the temperature further decreases to 65 K, a third magnetic transition accompanied by a second electrical transition is observed in the slightly Co-doped CaF⁢e 0.95 ⁢C⁢o 0.05 ⁢O 3 crystal. In conclusion, first-principles calculations suggest that the introduction of a moderate amount of Co and the peculiar spiral spin texture play an important role in the presence of such new magnetic and electrical transitions.

Xia, Hailiang [Chinese Academy of Sciences (CAS),

Quantifying System Strength From Grid-Forming Resources Using Frequency Scan Approach: Preprint

Current industry practices for quantifying the system strength contribution from grid-forming (GFM) resources to ensure stability of power systems dominated by inverter-based resources (IBRs) are primarily based on iterative electromagnetic transient (EMT) time-domain simulation studies. While feasible, these approaches are resource-intensive, lack scalability and intuition, and might not evaluate the system strength contribution over the entire frequency range of interest. This paper introduces a novel, frequency-domain approach to quantify system strength support provided by a GFM resource using frequency scans. The proposed method uses transfer functions from the grid voltage magnitude (V) and phase (?), respectively, to the reactive (Q) and active power (P) output of a GFM resource for quantifying its contribution to system strength. These transfer functions provide a direct measure of the ability of a GFM resource to behave as a stiff voltage source behind a reactance over a specified frequency range, enabling robust quantification of its system strength contribution. The key innovation of this work is the development of a frequency domain system strength metric called the dynamic short-circuit ratio (dSCR) that is suitable for IBR-dominated power systems and is directly related with the familiar short circuit ratio (SCR) metric. The new metric, dSCR, enables the assessment of system strength contributions from both synchronous machines and converter-based GFM resources using a unified benchmark, which is not possible with the traditional SCR metric. The paper also demonstrates how impedance scans could identify if an unstable condition observed during weak grid conditions is a result of the lack active or reactive power support or both. By leveraging the proposed frequency-domain dSCR metric for quantifying system strength contribution from GFM IBRs, the paper demonstrates targeted mitigation strategies for weak grid instabilities without resorting to repeated, time-consuming time-domain simulations. The result is a scalable and efficient approach to remediate stability challenges in power systems with high shares of IBRs and accelerating the integration of GFM technologies for system strength support in power systems.

24 POWER TRANSMISSION AND DISTRIBUTION

Nonlocal Effect of Percolated Particle Networks on Viscoelasticity of Polymer–Filler Nanocomposites: A Mesoscale Simulation Study

With nanoparticles (NPs) as fillers, polymer nanocomposites (PNCs) usually exhibit enhanced mechanical properties. However, a direct connection between the microscopic structural relaxation and macroscopic mechanical properties of PNCs remains to be established. To investigate the micro-to-macro connection, we develop a mesoscale model, in which the NPbridging polymer chains are represented by a dynamic bonded interaction between NPs, and the bulk polymer matrix is implicitly modeled by overdamped Langevin dynamics. Extensive equilibrium simulations are performed to quantify the microscopic dynamics of model PNCs. Systematic analyses of modified Rouse dynamics, dynamic structure factor, and relaxation modulus uncover that the microscopic relaxation dynamics of PNCs are significantly decelerated across different length scales because of nonlocal effects of percolated particle networks a phenomenon that has not been adequately captured in prior simulation studies. We find that NPvolume- fraction and NP-bonding-energy barrier are the two critical variables that affect bulk viscoelasticity the most. The proposed mesoscale model is versatile and provides a powerful framework for studying structure−property relations of different PNCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH