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At least 523 records · Page 29

Nanoparticle Surface Passivation Strategies to Improve the Cycle and Calendar Lifetime of Silicon Anodes in Standard Carbonate Electrolytes

Silicon Lithium alloys (SiLix) as the anode active material in a Li-Ion battery configuration offer possible energy densities paralleled only by pure lithium metal. However, the extreme mechanical deformation of alloying and dealloying SiLix through charge/discharge cycles paired with the highly reactive interface of SiLix which generates an interfacial layer known as the solid-electrolyte-interphase are large barriers to industrial adoption of high-silicon-content negative electrodes. Moreover, these challenges are magnified when the thickness of the electrode is brought to relevant levels (>3 mg/cm2). Here, I describe our efforts to address these challenges by utilizing single-nanometer-scale silicon nanoparticles to reduce capacity fade related to mechanical failure. I also detail our efforts to modify the silicon surface through interfacial chemical engineering strategies to passivate the silicon surface. This development three different majority silicon electrodes (50-74 wt%) to achieve cycle capacity retention of greater than 73% through 1000 charge/discharge cycles against capacity-matched NMC-based cathodes and calendar lifetimes greater than one year. This research is a part of the multi-national lab Silicon Consortium Project.

anodes↗

Collection of fluorescence from an ion using trap-integrated photonics

Spontaneously emitted photons are entangled with the electronic and nuclear degrees of freedom of the emitting atom, so interference and measurement of these photons can entangle separate matter-based quantum systems as a resource for quantum information processing. Since confinement in a single-mode facilitates the photon interference needed for generating entanglement, the dipole emission patterns relevant in spontaneous emission present a mode-matching challenge. Current demonstrations rely on bulk photon-collection and manipulation optics that suffer from large component size and system-to-system variability—factors that impede scaling to the large numbers of entangled pairs needed for quantum information processing. To address these limitations, we demonstrate a collection method that enables passive phase stability, straightforward photonic manipulation, and intrinsic reproducibility. Specifically, we engineer a waveguide-integrated grating to couple photons emitted from a trapped ion into a single optical mode within a microfabricated ion-trap chip. Using the integrated collection optic, we characterize the collection efficiency, image the ion, and detect the ion’s quantum state. The integrated optic covers 2.18% of the solid angle and collects 1.97 ± 0.3% of the spontaneously emitted light incident on the grating for a total collection efficiency of 0.043% into a single-mode waveguide. This proof-of-principle demonstration lays the foundation for leveraging the inherent stability and reproducibility of integrated photonics to create, manipulate, and measure multipartite quantum states in arrays of quantum emitters.

Optical physics↗

Accelerating the discovery of battery electrode materials through data mining and deep learning models

The availability of crystalline materials databases allows for building accurate machine learning (ML) models that can accelerate the exploration of materials chemical space for energy storage applications. In this work, we screen all inorganic materials included in the Materials Project and AFLOW databases as potential metal-ion battery electrodes. We develop an efficient protocol to mine and screen raw data in current databases and provide a new database of electrode materials by considering pairs of charged and discharged electrodes. This effort leads to a new database with over 190,000 instances, in contrast to the original battery database which contains about 5000. The expanded battery data set is then used to build regression-based deep neural network models for predicting average voltages and percentage volume changes upon charging and discharging, which present improvements of at least 28% for target properties with respect to previous models, and are now able to predict anode electrodes (low voltage region) as well as electrodes that will not work in electrochemical cells (negative voltages), overcoming the challenges identified in previous ML models for battery electrodes. Additionally, a further screening of the expanded database itself allowed us to identify 35 novel electrode candidates with excellent battery performance metrics.

25 ENERGY STORAGE↗

Laser ablation of high-loading Li-ion battery electrodes improves accessible capacity and cycle life for Behind-the-Meter Storage

Adoption of Behind-the-Meter Storage (BTMS) requires design of batteries that enable high safety, long cycle life, and low cost at the system level. Pairing Li 4 Ti 5 O 12 (LTO) with LiMn 2 O 4 (LMO) achieves targets related to safety and cycle life, but these materials' low energy densities contribute to higher cost at the system scale. Increasing electrode loading is a simple approach to improve energy density, but comes with a trade-off in electrode utilization due to long, tortuous Li + diffusion pathways. Here, laser ablation is used to microstructure (pattern) high-loading electrodes to enhance electrode performance through improved Li + diffusion pathways. Four cell types, comprising combinations of standard or patterned anode and cathode, were prepared to evaluate the effects of laser ablation at each electrode. A rate test shows that patterning electrodes enhances active material utilization at ≳1C rates. Patterning the cathode yields the most benefit, as cells with a patterned cathode demonstrate a ~20% higher accessible capacity than those without at 1.4C. Additionally, 1C capacity retention of cells with patterned cathode (91% through 3000 cycles) is significantly improved over cells with only the anode patterned (64%) and non-patterned electrodes (50%). Characterization of post-mortem cells before and after refreshing their electrolyte suggests that 1C capacity retention is improved by mitigation of electrode "dry-out". We hypothesize that the microstructure acts as a reservoir of additional electrolyte, or a path for gas to escape, so that active material remains wetted throughout long-term cycling, and/or the microstructure may reduce localized, gas-forming overpotentials in the high-loading electrode.

25 ENERGY STORAGE↗

Voltage Mining for (De)lithiation-Stabilized Cathodes and a Machine Learning Model for Li-Ion Cathode Voltage

Advances in lithium-metal anodes have inspired interest in discovery of Li-free cathodes, most of which are natively found in their charged state. This is in contrast to today's commercial lithium-ion battery cathodes, which are more stable in their discharged state. In this study, we combine calculated cathode voltage information from both categories of cathode materials, covering 5577 and 2423 total unique structure pairs, respectively. The resulting voltage distributions with respect to the redox pairs and anion types for both classes of compounds emphasize design principles for high-voltage cathodes, which favor later Period 4 transition metals in their higher oxidation states and more electronegative anions like fluorine or polyanion groups. Generally, cathodes that are found in their charged, delithiated state are shown to exhibit voltages lower than those that are most stable in their lithiated state, in agreement with thermodynamic expectations. Deviations from this trend are found to originate from different anion distributions between redox pairs. In addition, a machine learning model for voltage prediction based on chemical formulas is trained and shows state-of-the-art performance when compared to two established composition-based ML models for material properties predictions, Roost and CrabNet.

25 ENERGY STORAGE↗

The TDHF code Sky3D version 1.2

The Sky3D code has been widely used to describe nuclear ground states, collective vibrational excitations, and heavy-ion collisions. The approach is based on Skyrme forces or related energy density functionals. The static and dynamic equations are solved on a three-dimensional grid, and pairing is been implemented in the BCS approximation. This updated version of the code aims to facilitate the calculation of nuclear strength functions in the regime of linear response theory, while retaining all existing functionality and use cases. The strength functions are benchmarked against available RPA codes, and the user has the freedom of choice when selecting the nature of external excitation (from monopole to hexadecapole and more). Some utility programs are also provided that calculate the strength function from the time-dependent output of the dynamic calculations of the Sky3D code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Novel Dosimetry Method for Small Animal Irradiators Using 3D-printed Mouse Phantoms and Alanine Dosimeters

Abstract Accurate dosimetry is a crucial component of small animal and preclinical irradiation studies. Various dosimetry options are available but fail to characterize complex geometries and variable energy spectra of modern x-ray irradiators accurately. These options also lack national/international standards of recognition. This paper presents a novel dosimetry system, Dosequate, which uses murine phantoms embedded with alanine dosimeters and paired with x-ray energy spectra corrections to deliver consistent and accurate dosimetry measurements. This study compares Dosequate measurements against a Precision X-RAD 320 internal ion chamber and the treatment planning system of an Xstrahl Small Animal Radiation Research Platform. Results demonstrate the accuracy and reproducibility of the Dosequate system, highlighting its potential for standardizing dosimetry in preclinical research throughout the industry. Results demonstrate the accuracy and reproducibility of the Dosequate system, highlighting its potential for standardizing dosimetry in preclinical research throughout the industry. The Dosequate dosimetry method provides a robust and standardized approach for measuring absorbed dose in small animal irradiators. Its accuracy, reproducibility, and ability to account for complex irradiation geometries make it a valuable tool for preclinical research. This system has the potential to significantly improve the intercomparability of studies across different facilities and enhance the reliability of results.

Environmental Sciences & Ecology↗

Neuromorphic ionic computing in droplet interface synapses

Ionic devices with memory capabilities can emulate neural functionality, enabling neuromorphic computing and biomedical applications. In this study, we report an ionic spiking synapse based on aqueous droplet interface bilayer assembly. Under stepwise triangular voltages, the device displays coupled memcapacitive-memristive behavior, showing noncrossing pinched hysteretic I-V loops. This hysteretic ion dynamics can be regulated by modifying bilayer components, reconstituting protein channels, or adjusting droplet assembly configuration. Droplet interface synapses (DIS) exhibit fundamental neuromorphic behaviors such as paired-pulse facilitation/depression, spike rate–dependent plasticity, Hebbian learning, and short-term associative learning under classical conditioning. We also used reservoir computing with DIS to implement two learning algorithms: a classification algorithm that recognizes handwritten digits and a reinforcement learning algorithm that learns to play a board game of tic-tac-toe.

Li, Zhongwu [Lawrence Livermore National Laborator↗

Synthetic Access to a Framework-Stabilized and Fully Sulfided Analogue of an Anderson Polyoxometalate that is Catalytically Competent for Reduction Reactions

Polyoxometalates (POMs) featuring 7, 12, 18, or more redox-accessible transition metal ions are ubiquitous as selective catalysts, especially for oxidation reactions. The corresponding synthetic and catalytic chemistry of stable, discrete, capping-ligand-free polythiometalates (PTMs), which could be especially attractive for reduction reactions, is much less well developed. Among the challenges are the propensity of PTMs to agglomerate and the tendency for agglomeration to block reactant access of catalyst active sites. Nevertheless, the pervasive presence of transition metal sulfur clusters metalloenzymes or cofactors that catalyze reduction reactions and the justifiable proliferation of studies of two-dimensional (2D) metal-chalcogenides as reduction catalysts point to the promise of well-defined and controllable PTMs as reduction catalysts. Here, we report the fabrication of agglomeration-immune, reactant-accessible, capping-ligand-free Co II Mo 6 IV S 24 n– clusters as periodic arrays in a water-stable, hierarchically porous Zr-metal–organic framework (MOF; NU1K) by first installing a disk-like Anderson polyoxometalate, Co III Mo 6 VI O 24 m– , in size-matched micropores where the siting is established via difference electron density (DED) X-ray diffraction (XRD) experiments. Flowing H 2 S, while heating, reduces molybdenum(VI) ions to Mo(IV) and quantitatively replaces oxygen anions with sulfur anions (S 2– , HS – , S 2 2– ). DED maps show that MOF-templated POM-to-PTM conversion leaves clusters individually isolated in open-channel-connected micropores. Importantly, the structure of the immobilized cluster as determined, in part, by X-ray photoelectron spectroscopy (XPS), X-ray absorption fine structure (XAFS) analysis, and pair distribution function (PDF) analysis of total X-ray scattering agrees well with the theoretically simulated structure. PTM@MOF displays both electrocatalytic and photocatalytic competency for hydrogen evolution. Nevertheless, the initially installed PTM appears to be a precatalyst, gaining competency only after the loss of ~3 to 6 sulfurs and exposure to hydride-forming metal ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermodynamic analysis of hydrogel swelling in aqueous sodium chloride solutions

Here, a comprehensive thermodynamic model is presented for swelling and salt partitioning of poly (n-isopropyl acrylamide) hydrogels in aqueous sodium chloride (NaCl) solutions at 298 K. Together with a Helmholtz energy expression for network elastic energy, a modified electrolyte Nonradom Two-Liquid activity coefficient model is used to represent both the long-range electrostatic interactions and the short-range van der Waals interactions present in the gel phase. The model parameters include one network parameter per hydrogel system plus two binary parameters per interaction pair in the polymer–solvent-salt systems. With semiquantitave agreement with experimental data for both hydrogel swelling and salt partitioning up to salt saturation, the analysis suggests the ion hydration between NaCl and water is the root cause for hydrogel deswelling in aqueous NaCl solution at high NaCl concentrations, i.e., NaCl weight fraction >0.03. On the other hand, the strong repulsive interaction between NaCl and hydrogel polymer is the dominant factor for salt partitioning.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Collision-energy dependence of deuteron cumulants and proton-deuteron correlations in Au+Au collisions at RHIC

We report the first measurements of cumulants, up to 4th order, of deuteron number distributions and proton-deuteron correlations in Au+Au collisions recorded by the STAR experiment in phase-I of Beam Energy Scan (BES) program at the Relativistic Heavy Ion Collider. Deuteron cumulants, their ratios, and proton-deuteron mixed cumulants are presented for different collision centralities covering a range of center-of-mass energy per nucleon pair $\sqrt{s_{NN}} = 7.7$ to 200 GeV. It is found that the cumulant ratios at lower collision energies favor a canonical ensemble over a grand canonical ensemble in thermal models. An anti-correlation between proton and deuteron multiplicity is observed across all collision energies and centralities, consistent with the expectation from global baryon number conservation. The UrQMD model coupled with a phase-space coalescence mechanism qualitatively reproduces the collision-energy dependence of cumulant ratios and proton-deuteron correlations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Assessing the Effect of Explicit Polarizability on Models of Carbon Dioxide Solvation in Ionic Liquids

Ionic liquids are an important possible carbon capture material because of their anomalously high sorption selectivity for carbon dioxide over other gases common in air. Many research groups have investigated the molecular origins of this property and provided important insights, including using 1D and 2D-IR spectroscopy. Molecular dynamics simulations have been indispensable to the interpretation of these experiments. In prior molecular dynamics simulation work, charge-scaled force fields have typically been used to provide a mean-field treatment of effects vital to ionic liquid systems such as charge transfer and polarization. Here, we compare models of carbon dioxide solvated in ionic liquids with explicit polarization to models of the same with implicit polarizability through charge-scaling. We calculate structural, dynamical, and spectroscopic properties, and make comparisons to the same items measured in experiment. In this study, we focus on two ionic liquids: 1-butyl-3- methylimidazolium (BMIM + ) paired with bis(trifluoromethane sulfonyl imide) (Tf 2 N − ) and 1-butyl-3-methylimidazolium (BMIM+) paired with hexafluorophosphate (PF 6 − ). We find that many structural, dynamical, and spectroscopic properties are changed when polarization is modeled explicitly. We also find that explicit polarizability softens local ion cages around the carbon dioxide and that the long-time diffusion of the carbon dioxide is gated by the reorganization of the ionic liquid molecules. Comparisons to experiment show modest improvement of many observables compared with experiment for the explicitly polarizable model over the charge-scaled model. Overall, our results show that charge-scaled force fields are likely sufficient to compute spectroscopic properties of carbon dioxide in ionic liquids and suggest some interpretive rules for understanding their structural and dynamical properties. Those using charge-scaled force fields should generally assume that the ion cages around solutes such as carbon dioxide are too stiff and cation-rich in their models and adjust their interpretations and predictions accordingly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Local structure and ion storage properties of vanadate cathode materials regulated by the pre-alkalization

Aqueous Zn-ion batteries using mild acidic electrolytes utilizing a Zn 2+ /H + dual-ion storage mechanism have shown great potential in achieving high energy density comparable to non-aqueous lithium-ion batteries. Here, this study reveals that hydrated alkali-ions regulate the formation of alkali-intercalated vanadate layered compounds. Among various vanadate materials, lithium-intercalated vanadate has the largest interlayer spacing and most disordered local structure, exhibiting the largest storage capacity of 308 mA h g –1 at 0.05 A g –1 for Zn 2+ /H + dual-ion storage and improved charge transfer and transport kinetics and cycling performance, evidenced by in situ X-ray diffraction and ex situ X-ray total scattering and pair distribution function analysis. Our study provides new insight into designing layered vanadate materials for high-capacity aqueous batteries.

25 ENERGY STORAGE↗

NiAl–MoO 2 S 2 Nanoparticles: Structural Evolution and Mechanistic Insights into High-Performance Selenium Oxyanion Removal across Diverse pH Conditions

Advancing sorbent materials for the selective removal of toxic oxyanions from water requires synthetic control, tunable chemistry, and an atomic-level understanding of structure–function relationships. Here, we report the synthesis and detailed characterization of NiAl–MoO 2 S 2 , a novel layered double hydroxide (LDH) nanomaterial designed for the efficient sequestration of selenium oxoanions (SeO 3 2– and SeO 4 2– ) from complex aqueous environments. The material is synthesized through a room-temperature ion-exchange process, wherein interlayer NO 3 – anions in NiAl–LDH are replaced with MoO 2 S 2 2– clusters, forming high-surface-area, flower-like nanoparticles. Comprehensive structural analysis using the synchrotron X-ray pair distribution function, X-ray absorption spectroscopy, and X-ray photoelectron spectroscopy reveals a distinct chemical transformation of intercalated [MoO 2 S 2 ] 2– into [Mo 2 O 2 S 6 ] 2– -like clusters, generating redox-active interlayers that drive selenium capture. This tailored interfacial chemistry underpins the material’s exceptional sorption performance, achieving distribution coefficients (K d ) ≥ 10 6 mL/g and maximum capacities of 343 mg/g for SeO 4 2– and 514 mg/g for SeO 3 2– , outperforming state-of-the-art inorganic sorbents. Importantly, NiAl–MoO 2 S 2 maintains high selectivity and capacity across acidic, neutral, and alkaline pH, efficiently removing selenium from ppm to sub-10 ppb trace levels, even in the presence of competing ions typical of natural and industrial waters. The selenium uptake proceeds via reductive precipitation coupled with the oxidation of molybdenum and sulfide within the LDH framework. This study highlights the power of strategic synthetic modification and interlayer functionalization in LDHs to unlock new structural motifs and redox chemistries, offering a scalable route to advanced materials for environmental remediation.

Adsorption↗

Patch-Based Convolutional Neural Networks for Multiple Microstructural Features Detection in FIB-SEM Micrographs of Irradiated Nuclear Fuel

Focused ion beam scanning electron microscopy (FIB-SEM) tomography has increasingly been utilized for acquiring three-dimensional (3D) microstructure features at the sub-micron scale in irradiated nuclear materials. This technique involves sequential ion beam slicing followed by electron beam imaging and compositional mapping using energy dispersive spectroscopy (EDS). Despite its growing use, several challenges persist. These include the time-intensive nature of data collection of EDS data, difficulties in distinguishing between various microstructures, and issues with image alignment. These challenges currently limit the broader application of FIB-SEM tomography in the field. To overcome these limitations, we propose using convolutional neural networks (CNNs) to automate microstructure identification in SEM images. Our study introduces a new framework for identifying microstructures in irradiated U-10Zr (wt. %) metallic fuel with limited annotated data. The framework includes the creation of a reliable annotated dataset with paired SEM and ground truth data from EDS maps, the applications of CNNs for microstructure identification, and the validation of model performance. Specifically, we employed the Segment Anything Model (SAM) to align SEM images with corresponding EDS maps and focused ion beam (FIB) tomography SEM data. We evaluate several models, including Patch-based U-Net, Attention U-Net, and Residual U-Net, finding that patch-based U-Net exhibits superior segmentation performance and consistency. This approach reduces reliance on EDS detectors and aids in accelerating nuclear material analysis process, highlighting the potential of advanced deep learning techniques to improve microstructural understanding in nuclear material. This is the first framework to integrate SAM and Patch-based CNN models for semantic segmentation of irradiated nuclear materials, with potential applicability to other tomography datasets.

36 - MATERIALS SCIENCE↗

Accurate Prediction of Voltage of Battery Electrode Materials Using Attention-Based Graph Neural Networks

Performing first-principles calculations to discover electrodes’ properties in the large chemical space is a challenging task. While machine learning (ML) has been applied to effectively accelerate those discoveries, most of the applied methods ignore the materials’ spatial information and only use predefined features: based only on chemical compositions. Here, we propose two attention-based graph convolutional neural network techniques to learn the average voltage of electrodes. Our proposed methods, which combine both atomic composition and atomic coordinates in 3D-space, improve the accuracy in voltage prediction significantly when compared to composition-based ML models. The first model directly learns the chemical reaction of electrodes and metal ions to predict their average voltage, whereas the second model combines electrodes’ ML predicted formation energy (E form ) to compute their average voltage. Our E form -based model demonstrates improved accuracy in transferability from our subset of learned Li ions to Na ions. Moreover, we predicted the theoretical voltage of 10 Na x MPO 4 F (M = Ti, Cr, Fe, Cu, Mn, Co, and Ni) fluorophosphate battery frameworks, which are unavailable in the Material Project database. It could be shown that we can expect average voltages higher than 3.1 V from those Na battery frameworks except from the NaTiPO 4 F and TiPO 4 F pair of electrodes, which offer an average voltage of 1.32 V.

25 ENERGY STORAGE↗

Utilizing metal cation reactions with carbonyl sulfide to remove isobaric interferences in tandem inductively coupled plasma mass spectrometry analyses

Carbonyl sulfide (OCS) was used as a reaction gas to investigate gas phase metal (M + ) ion-molecule reactions using the Agilent 8900 inductively coupled plasma tandem mass spectrometer (ICP-MS/MS) to yield insight on how this gas may be used to remove isobaric interferences in analytical measurements. The experimental work was paired with density functional theory (DFT) calculations of the reaction enthalpy to predict whether M + will react with OCS. A multi-element standard containing 46 elements ranging from 9 to 208 u was analyzed in the presence and absence of OCS. When a reaction was observed, the dominant product was the sulfide (MS + ). Oxide products were also observed for many M + but formation was less efficient with OCS than previously observed with other reaction gases. This is likely due to the weaker OC-S bond that makes MS + formation more favorable. Increasing the flow rate from 0.1 to 0.2 mL/min (corresponding to a change in reaction gas pressure from 0.35 to 0.53 Pa (2.6 to 4.0 mTorr)) generally resulted in greater MS + production, including the secondary product MS 2 + for a few cations. The early lanthanide series ions (La + , Ce + , Pr + and Nd + ) produced greater quantities of MO + at the higher pressure, although MS + products were still the dominant product. The DFT-predicted reaction enthalpies were consistent with the observed sulfide formation, with an accuracy >90%; however, model predictions were less accurate for the minor and higher order products (< 77% for MO + ). Finally, the work presented here continues a systematic study of ion-molecule reactions in ICP-MS/MS to understand and develop new and novel ways to analyze complex mixtures with minimal pre-analysis treatment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Cobalt– and Manganese–Free High–Nickel Layered Oxide Cathode for Long–Life, Safer Lithium–Ion Batteries

High-nickel LiNi 1–x–y Mn x Co y O 2 and LiNi 1–x–y Co x Al y O 2 cathodes are receiving growing attention due to the burgeoning demands on high-energy-density lithium-ion batteries. The presence of both cobalt and manganese in them, however, triggers multiple issues, including high cost, high toxicity, rapid surface deterioration, and severe transition-metal dissolution. Herein, a Co- and Mn-free ultrahigh-nickel LiNi 0.93 Al 0.05 Ti 0.01 Mg 0.01 O 2 (NATM) cathode that exhibits 82% capacity retention over 800 deep cycles in full cells, outperforming two representative high-Ni cathodes LiNi 0.94 Co 0.06 O 2 (NC, 52%) and LiNi 0.90 Mn 0.05 Co 0.05 O 2 (NMC, 60%) is presented. It is demonstrated that a titanium-enriched surface along with aluminum and magnesium as the stabilizing ions in NATM not only ameliorates unwanted side reactions with the electrolyte and structural disintegrity, but also mitigates transition-metal dissolution and active lithium loss on the graphite anode. As a result, the graphite anode paired with NATM displays an ultrathin (≈8 nm), monolayer anode-electrolyte interphase architecture after extensive cycling. Furthermore, NATM displays considerably enhanced thermal stability with an elevated exothermic temperature (213 °C for NATM vs 180 and 190 °C for NC and NMC, respectively) and remarkably reduced heat release. This work sheds light on rational compositional design to adopt ultrahigh-Ni cathodes in lithium-based batteries with low cost, long service life, and improved thermal stability.

25 ENERGY STORAGE↗