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At least 127 records · Page 7

A comprehensive review on liquid electrolyte design for low-temperature lithium/sodium metal batteries

Lithium/sodium metal batteries (LMBs/SMBs) possess immense potential for various applications due to their high energy density. Nevertheless, LMBs/SMBs are highly susceptible to the detrimental effects of an unstable solid electrolyte interphase (SEI) and dendrites during practical applications, particularly pronounced in low-temperature environments. Furthermore, sluggish ion transportation further compromises the cycling stability of LMBs/SMBs at low temperatures. To achieve stable operation of LMBs/SMBs at low temperatures, researchers have made numerous efforts including electrolyte optimization aimed at creating stable SEIs and suppressing the metal dendrites under low temperature conditions. Despite the significant advancements made recently in the liquid electrolyte design, there remains considerable hurdle in electrolyte engineering for practical low-temperature, high energy density LMBs/SMBs, calling for a profound comprehension of the intricate interplay between the electrochemical reaction kinetics and electrolyte compositions. Here, this review provides a thorough overview of various strategies in optimizing liquid electrolytes covering weakly solvating electrolytes, concentration-designed electrolytes, and solvation structure-designed electrolytes, to address the challenges faced by LMBs/SMBs at low temperatures, including slow reaction kinetics and the difficulties in Li + /Na + solvation/desolvation. Furthermore, this review discusses future prospects for the advancement of this field, intending to provide valuable insights and support for subsequent research undertakings.

25 ENERGY STORAGE↗

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↗

Self-Assembled BaTiO 3 –Au x Ag 1– x Low-Loss Hybrid Plasmonic Metamaterials with an Ordered “Nano-Domino-like” Microstructure

Metallic plasmonic hybrid nanostructures have attracted enormous research interest due to the combined physical properties coming from different material components and the broad range of applications in nanophotonic and electronic devices. However, the high loss and narrow range of property tunability of the metallic hybrid materials have limited their practical applications. In this study, a metallic alloy-based self-assembled plasmonic hybrid nanostructure, i.e., a BaTiO 3 –Au x Ag 1– x (BTO) vertically aligned nanocomposite, has been integrated by a templated growth method for low-loss plasmonic systems. Comprehensive microstructural characterizations including high-resolution scanning transmission electron microscopy (HRSTEM), energy-dispersive X-ray spectroscopy (EDS), and three-dimensional (3D) electron tomography demonstrate the formation of an ordered “nano-domino-like” morphology with Au 0.4 Ag 0.6 nanopillars as cylindrical cores and BTO as square shells. By comparing with the BTO–Au hybrid thin film, the BTO–Au 0.4 Ag 0.6 alloyed film exhibits much broader plasmon resonance, hyperbolic dispersion, low-loss, and thermally robust features in the UV–vis–NIR wavelength region. This study provides a feasible platform for a complex alloyed plasmonic hybrid material design with low-loss and highly tunable optical properties toward all-optical integrated devices.

36 MATERIALS SCIENCE↗

External-Field-Induced Phase Transformation and Associated Properties in a Ni 50 Mn 34 Fe 3 In 13 Metamagnetic Shape Memory Wire

Metamagnetic shape memory alloys exhibit a series of intriguing multifunctional properties and have great potential for applications in magnetic actuation, sensing and magnetic refrigeration. However, the poor mechanical properties of these alloys with hardly any tensile deformability seriously limit their practical application. In the present work, we developed a Ni-Fe-Mn-In microwire that exhibits both a giant, tensile superelasticity and a magnetic-field-induced first-order phase transformation. The recoverable strain of superelasticity is more than 20% in the temperature range of 233–283 K, which is the highest recoverable strain reported heretofore in Ni-Mn-based shape memory alloys (SMAs). Moreover, the present microwire exhibits a large shape memory effect with a recoverable strain of up to 13.9% under the constant tensile stress of 225 MPa. As a result of the magnetic-field-induced first-order phase transformation, a large reversible magnetocaloric effect with an isothermal entropy change ΔS m of 15.1 J kg –1 K –1 for a field change from 0.2 T to 5 T was achieved in this microwire. The realization of both magnetic-field and tensile-stress-induced transformations confers on this microwire great potential for application in miniature multi-functional devices and provides an opportunity for multi-functional property optimization under coupled multiple fields.

36 MATERIALS SCIENCE↗

Synthesis of cerium precursors with alkoxide ligands for degradation to cerium oxide nanoparticles

Lanthanide oxide and sulfide nanoparticles present intriguing theoretical questions regarding their electronic structures, alongside numerous potential applications in material science and catalysis. Although these materials can be formed through hydrolysis, their synthesis via thermolysis is crucial for nanoscale materials and practical applications. This research aims to enhance our understanding of the decomposition mechanisms by focusing on cerium compounds, which are analogous to those studied previously. Currently, our knowledge of the decomposition mechanisms of cerium alkoxide precursors is limited. The objective of this project is to develop a mechanistic understanding of the formation of cerium oxide nanoparticles from cerium alkoxide precursors, employing a variety of techniques. These techniques include collision-induced dissociation in an ion-trap mass spectrometer, nuclear magnetic resonance (NMR) spectroscopy, thermogravimetric analysis coupled with differential scanning calorimetry (TGA-DSC), and gas chromatography-mass spectrometry (GC-MS) to investigate the decomposition mechanisms of the synthesized precursors.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

VoroClust

SAND2025-11465O VoroClust, also known as Voronoi Clustering, is a fast, density-based unsupervised clustering algorithm applicable to high-resolution and high-dimensional data. It operates as quickly as distance-based clustering methods while effectively capturing complex regional geometries, matching the performance of current density-based methods. VoroClust employs a data-centered sphere cover to reduce computational demands while preserving data topology. It propagates clusters outward from local density peaks. Although supervised machine learning is powerful for applications like image classification and segmentation, it requires comprehensive, consistent datasets, which many applications lack. Unsupervised clustering algorithms analyze the structure of each dataset rather than relying on similarities with other examples, making them well-suited for practical applications with insufficient or inappropriate data for supervised learning. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Ebeida, Mohamed [Sandia National Lab. (SNL-CA), Li↗

Putting multipoint kinetics to the test: preliminary analysis of the MUSE-4 experiment with APOLLO3

Modeling neutron kinetics is a challenging task and over the years, several approaches have been developed offering different tradeoffs between precision and cost. Probably the most popular one is point kinetics (PK), which, despite being very cheap, provides good results for many applications. One of the limitations of PK is that it is not able to model effects that happen before the prompt jump time scale. In practice, applications, where those time scales are interesting, are rare and those for which experimental data are available are even rarer. One of those cases is the MUSE-4 experiment for which the focus is on the very fast behavior and where we have no thermal feedback. As we have shown in a recent paper, a simple extension of PK, known as multipoint kinetics (MPK), can overcome this limitation. In this paper, which is intended as a preliminary study, we show how a simple MPK model can qualitatively reproduce the fast behavior that we cannot model with PK. Moreover, we will show how to exploit its low cost and compact form to model also slow effects as the precursors built up, behaviours that are not affordable to model with more expensive techniques, such as kinetic Monte Carlo simulations. For the periodic pulse transients with no feedbacks we will also provide an analytical solution in closed form. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Corrosion resistant hot melt adhesive to bind metals

Hot melt adhesives (HMAs) play an important role in many industries, and their demand is expected to grow. HMAs don't require any solvents, and their application results in the formation of strong bonds with the substrate upon cooling within seconds. These properties differentiate them from liquid glues and make them preferable for practical application. Currently, commercial HMAs are used in bonding lightweight materials such as paper, polymers, and cartons, and have limited usage in areas necessitating the bonding of heavier objects like metals. Here, in this study, we report a design and testing of versatile platform comprising an ion-coordinating polymer and ionic fillers for performance optimization and understanding of structure–property relationships, enabling the rational design of HMAs with improved adhesion to metal surfaces. All-atom Molecular dynamics (MD) simulations and various characterization methods are used to elucidate the adhesion mechanism in model composite system containing polyethylene oxide mixed with chemically diverse salt particles. The maximum adhesion strength is found in composites with Al(OH) 3 and FeCl 3 fillers. Interestingly, the presence of Al(OH) 3 also provides a multifunctional anticorrosion property as measured electrochemically using the Tafel method. The discovered path to formulations with improved adhesion to metal surfaces constitutes an important step toward advancing HMAs for use in the structural and semi-structural metal work domain.

Adhesive and cohesive forces↗

Calculating elements of matrix functions using divided differences

In this work, we introduce a method for calculating individual elements of matrix functions. Our technique makes use of a novel series expansion for the action of matrix functions on basis vectors that is memory efficient even for very large matrices. We showcase our approach by calculating the matrix elements of the exponential of a transverse-field Ising model and evaluating quantum transition amplitudes for large many-body Hamiltonians of sizes up to 2 64 x 2 64 on a single workstation. We also discuss the application of the method to matrix inverses. We relate and compare our method to the state-of-the-art and demonstrate its advantages. We also discuss practical applications of our method.

97 MATHEMATICS AND COMPUTING↗

Role of Fast Dynamics in Conductivity of Polymerized Ionic Liquids

Polymerized ionic liquids (PolyILs) are promising candidates for a broad range of technologies. However, the relatively low conductivity of PolyILs at room temperature has strongly limited their applications. In this work, we provide new insights into the roles of various microscopic parameters controlling ion transport in these polymers, which are crucial for their rational design and practical applications. Using broadband dielectric spectroscopy and neutron and light scattering techniques, we found a clear connection between the activation energy for conductivity, fast dynamics, and high-frequency shear modulus in PolyILs at their glass transition temperature (T g ). In particular, our analysis reveals a correlation between conductivity and the amplitude of fast picosecond fluctuations at T g , suggesting the possible involvement of fast dynamics in lowering the energy barrier for ion conductivity. We also demonstrate that both the activation energy for ion transport and the amplitude of the fast fluctuations depend on the high-frequency shear moduli of PolyILs, thus identifying a practically important parameter for tuning conductivity. Finally, the parameters recognized in this work and their connection to the ionic conductivity of PolyILs set the stage for a deeper understanding of the mechanism of ion transport in PolyILs in the glassy state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface Modification of Nickel-Rich Cathode Materials by Ionically Conductive Materials at Room Temperature

Nickel-rich cathode materials (LiNi x Mn y Co 1-x-y O 2 , NMC) are promising to push the limits of lithium-ion batteries to higher energy density. This approach is favored in practical applications including electric vehicles and aviation transportation. However, the instability of the NMC at charged state results in safety concerns and poor cycling stability. Surface coating is a practical and effective strategy to address this. Cubic Li7La3Zr2O12 (LLZO) is an ideal coating material regarding the low electron transfer rate and high Li+ conductivity. Thus, a LLZO coating layer can suppress the parasitic reactions in the electrode/electrolyte interface without deteriorating the lithium migration. However, high-temperature calcination seems to inevitably create the chemical couplings between NMC and LLZO, leading to the interdiffusion and degradation of NMC and LLZO crystal structures. This work presents a simple mechanochemical method to effectively coat LLZO on the NMC particle surface. Furthermore, the coated cathode demonstrates superior electrochemical performance compared with the pristine NMC cathode.

25 ENERGY STORAGE↗

Spectral emittance measurements of micro/nanostructures in energy conversion: a review

Micro/nanostructures play a key role in tuning the radiative properties of materials and have been applied to the high-temperature energy conversion systems for improved performance. Among the various radiative properties, spectral emittance is of integral importance for the design and analysis of materials that function as radiative absorbers or emitters. This article presents an overview of the spectral emittance measurement techniques using both the direct and indirect methods. Several micro/nanostructures are also introduced, and a special emphasis is placed on the emissometers developed for characterizing engineered micro/nanostructures in high-temperature applications (e.g., solar energy conversion and thermophotovoltaic devices). Both experimental facilities and measured results for different materials are summarized. Future prospects in developing instrumentation and micro/nanostructured surfaces for practical applications are also outlined. This study provides a comprehensive source of information for the application of micro/nanostructures in high-temperature energy conversion engineering.

14 SOLAR ENERGY↗

4D structural changes and pore network model of biomass during pyrolysis

Biochar is an engineered carbon-rich substance used for soil improvement, environmental management, and other diverse applications. To date, the understanding of how biomass affects biochar microstructure has been limited due to the complexity of analysis involved in tracing the changes in the physical structure of biomass as it undergoes thermochemical conversion. In this study, we used synchrotron x-ray micro-tomography to visualize changes in the internal structure of biochar from diverse feedstock (miscanthus straw pellets, wheat straw pellets, oilseed rape straw pellets, and rice husk) during pyrolysis by collecting a sequence of 3D scans at 50 °C intervals during progressive heating from 50 °C to 800 °C. The results show a strong dependence of biochar porosity on feedstock as well as pyrolysis temperature, with observed porosity in the range of 7.41–60.56%. Our results show that the porosity, total surface area, pore volume, and equivalent diameter of the largest pore increases with increasing pyrolysis temperature up to about 550 °C. The most dramatic development of pore structure occurred in the temperature range of 350–450 °C. This understanding is pivotal for optimizing biochar’s properties for specific applications in soil improvement, environmental management, and beyond. By elucidating the nuanced variations in biochar’s physical characteristics across different production temperatures and feedstocks, this research advances the practical application of biochar, offering significant benefits in agricultural, environmental, and engineering contexts.

54 ENVIRONMENTAL SCIENCES↗

Effects of fluorinated solvents on electrolyte solvation structures and electrode/electrolyte interphases for lithium metal batteries

Electrolyte is very critical to the performance of the high-voltage lithium (Li) metal battery (LMB), which is one of the most attractive candidates for the next generation high-density energy storage systems. Electrolyte formulation and structure determine the physical properties of the electrolytes and their interfacial chemistries on the electrode surfaces. Localized high-concentration electrolytes (LHCEs) outperform state-of-the-art carbonate electrolytes in many aspects in LMBs due to their unique solvation structure. Types of fluorinated co-solvents used in LHCEs are investigated here in searching for the most suitable diluent for high concentration electrolytes (HCEs). Non-solvating solvents (including fluorinated ethers, fluorinated borate and fluorinated orthoformate) added in HCEs enable the formation of LHCEs with high-concentration solvation structures. However, low solvating fluorinated carbonate will coordinate with Li+ ions and form a second solvation shell or a pseudo-LHCE which diminishes the benefits of LHCE. In addition, it is evident that the diluent has significant influence on the electrode/electrolyte interphases (EEIs) beyond retaining the high-concentration solvation structures. Diluent molecules surrounding the high-concentration clusters could accelerate or decelerate the anion decomposition through co-participation of diluent decomposition in the EEI formation. The varied interphase features lead to significantly different battery-performance. This study points out the importance of diluents and their synergetic effects with the conductive salt and the solvating solvent in designing LHCEs. These systematic comparisons and fundamental insights into LHCEs using different types of fluorinated solvents can guide further development of advanced electrolytes for high-voltage LMBs.

Cao, Xia↗

Doping Bottleneck in Hematite: Multipole Clustering by Small Polarons

We report highly effective doping in transition metal oxides is critical to fundamentally overcome low carrier conductivity due to small polaron formation and reach their ideal efficiency for energy conversion applications. However, the optimal doping concentration in polaronic oxides such as hematite has been extremely low, for example, less than a percent, which hinders the benefits of doping for practical applications. In this work, we investigate the underlying mechanism of low optimal doping concentration with group IV (Ti, Zr, and Hf) and XIV (Si, Ge, Sn, and Pb) dopants from first-principles calculations. We find that novel dopant-polaron clustering occurs even at very low dopant concentrations and resembles electric multipoles. These multipoles can be very stable at room temperature and are difficult to fully ionize compared to separate dopants, and thus they are detrimental to carrier concentration improvement. This allows us to uncover mysteries of the doping bottleneck in hematite and provide guidance for optimizing doping and carrier conductivity in polaronic oxides toward highly efficient energy conversion applications.

36 MATERIALS SCIENCE↗

Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning

Here this article proposes a model-based deep reinforcement learning (DRL) method to design emergency control strategies for short-term voltage stability problems in power systems. Recent advances show promising results for model-free DRL-based methods in power systems control problems. But in power systems applications, these model-free methods have certain issues related to training time (clock time) and sample efficiency; both are critical for making state-of-the-art DRL algorithms practically applicable. DRL-agent learns an optimal policy via a trial-and-error method while interacting with the real-world environment. It is also desirable to minimize the direct interaction of the DRL agent with the real-world power grid due to its safety-critical nature. Additionally, the state-of-the-art DRL-based policies are mostly trained using a physics-based grid simulator where dynamic simulation is computationally intensive, lowering the training efficiency. We propose a novel model-based DRL framework where a deep neural network (DNN)-based dynamic surrogate model (SM), instead of a real-world power grid or physics-based simulation, is utilized within the policy learning framework, making the process faster and more sample efficient. However, having stable training in model-based DRL is challenging because of the complex system dynamics of large-scale power systems. We addressed these issues by incorporating imitation learning to have a warm start in policy learning, reward-shaping, and multi-step loss in surrogate model training. Finally, we achieved 97.5% reduction in samples and 87.7% reduction in training time for an application to the IEEE 300-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Understanding and design of interstitial oxygen conductors

Highly efficient oxygen-active materials that react with, absorb, and transport oxygen is essential for fuel cells, electrolyzers and related applications. While vacancy-mediated oxygen-ion conductors have long been the focus of research, they are limited by high migration barriers at intermediate temperatures (400–600 °C), which hinder their practical applications. In contrast, interstitial oxygen conductors exhibit significantly lower migration barriers enabling higher ionic conductivity at lower temperatures. This review systematically examines both well-established and recently identified families of interstitial oxygen-ion conductors, focusing on how their unique structural motifs such as corner-sharing polyhedral frameworks, isolated polyhedral, and cage-like architectures, facilitate low migration barriers through interstitial and/or interstitialcy diffusion mechanisms. A central discussion of this review focuses on the evolution of design strategies, from targeted donor doping, element screening, to physical-intuition descriptor material screening and machine learning approach, which leverage computational tools to explore vast chemical spaces in search for new interstitial conductors. The success of these strategies demonstrates that a significant, largely unexplored space remains for discovering high-performing interstitial oxygen conductors. Crucial features enabling high-performance interstitial oxygen diffusion include the availability of electrons for oxygen reduction and sufficient structural flexibility with accessible volume for interstitial accommodation and migration. This review concludes with a forward-looking perspective, proposing a knowledge-driven methodology that integrates current understanding with data-centric approaches to identify promising interstitial oxygen conductors outside traditional search paradigms. These approaches are expected to significantly accelerate the development of high-performance interstitial oxygen conductors for a variety of oxygen-active applications, ultimately paving the way for more efficient and sustainable energy technologies.

Interstitial oxygen conductors↗

Three-dimensional Zn-based alloys for dendrite-free aqueous Zn battery in dual-cation electrolytes

Aqueous zinc-ion batteries, in terms of integration with high safety, environmental benignity, and low cost, have attracted much attention for powering electronic devices and storage systems. However, the interface instability issues at the Zn anode caused by detrimental side reactions such as dendrite growth, hydrogen evolution, and metal corrosion at the solid (anode)/liquid (electrolyte) interface impede their practical applications in the fields requiring long-term performance persistence. Despite the rapid progress in suppressing the side reactions at the materials interface, the mechanism of ion storage and dendrite formation in practical aqueous zinc-ion batteries with dual-cation aqueous electrolytes is still unclear. Herein, we design an interface material consisting of forest-like three-dimensional zinc-copper alloy with engineered surfaces to explore the Zn plating/stripping mode in dual-cation electrolytes. The three-dimensional nanostructured surface of zinc-copper alloy is demonstrated to be in favor of effectively regulating the reaction kinetics of Zn plating/stripping processes. The developed interface materials suppress the dendrite growth on the anode surface towards high-performance persistent aqueous zinc-ion batteries in the aqueous electrolytes containing single and dual cations. This work remarkably enhances the fundamental understanding of dual-cation intercalation chemistry in aqueous electrochemical systems and provides a guide for exploring high-performance aqueous zinc-ion batteries and beyond.

25 ENERGY STORAGE↗