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Structure of Shock Waves and Inelasticity in Shock-Compressed Cemented Tungsten Carbides

In this study, shock wave experiments are conducted on General Carbide cemented tungsten carbide with 3.7wt.% cobalt binder to determine its shock-induced compression behavior up to 100 GPa. The measured wave profiles indicate the cemented tungsten carbide to undergo elastic-plastic deformation during shock compression. A three-stage particle velocity profile is observed in the experiments -- an initial elastic-rise to the Hugoniot Elastic Limit (HEL), an elastic-plastic ramp indicating substantial post-yield hardening, and finally a rise to the peak shocked Hugoniot state. The results of the experiments are used to determine the HEL, the shock velocity (U s ) vs. particle velocity (u p ) Hugoniot relation, and the longitudinal stress (σ x ) vs. specific volume (V) curve for the samples. The HEL of the material was determined to lie between 4.41 GPa and 4.58 GPa. The U s - u p relation was determined to be U s = 4.97 + 1. 457u p for particle velocities greater than 0.75 km/s. The measured plastic shock velocities for particle velocities less than 0.7 km/s were found to be larger than those predicted using the linear U s - u p Hugoniot relationship, indicating the cemented WC samples to preserve substantial shear strength in the post-yield deformation region. No phase transformation was observed up to 100 GPa.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Alleviating prior dependencies for DESI DR1 clustering fits through reparameterization

Bayesian analyses of the full-shape clustering of Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) exhibit prior-volume projection effects, whereby weakly constrained nuisance parameters of the Effective Field Theory of Large Scale Structure (EFTofLSS) shift marginalized cosmological posteriors away from the posterior maximum. We reanalyze DESI DR1 power spectrum multipoles using two complementary mitigation strategies: (i) nonlinear orthogonalization to decorrelate nuisance and cosmological parameter priors, and (ii) a fully reparameterization-invariant Jeffreys prior over all EFTofLSS coefficients, evaluated on-the-fly via closed-form Jacobians. Including data from DESI, Big-Bang Nuclesynthesis and a constraint on $n_{\mathrm{s}}$, baseline priors lead to multi-$σ$ projection in the Hubble parameter $H_{0}$ and dark energy equation of state parameters $w_{0}$ and $w_{a}$; the Jeffreys prior successfully recenters these posteriors to enclose the maximum a posteriori estimate within the 68% credible regions, demonstrating clear mitigation of projection effects for these late-time expansion parameters. A hybrid Jeffreys+baseline-Gaussian configuration controls residual over-broad tails in the physical cold dark matter density $ω_{\mathrm{c}}$ while preserving the volume correction, and is our favoured approach. We compare the credible intervals derived using our methodology to those obtained using Halo Occupation Distribution (HOD)-informed priors and to confidence intervals derived using frequentist profile likelihood analyses, finding agreement in both central values and degeneracy directions in the $w_{0}$--$w_{a}$ plane. This demonstrates that, once projection effects are properly controlled, we can make robust inferences about the late-time cosmological expansion independent of the statistical framework adopted.

Bonici, M. [Waterloo U.; Perimeter Inst. Theor. Ph↗

Confidentiality-preserving machine learning algorithms for soft-failure detection in optical communication networks

Automated fault management is at the forefront of next-generation optical communication networks. The increase in complexity of modern networks has triggered the need for programmable and software-driven architectures to support the operation of agile and self-managed systems. In these scenarios, the European Telecommunications Standards Institute zero-touch network and service management approach is imperative. The need for machine learning algorithms to process the large volume of telemetry data brings safety concerns as distributed cloud-computing solutions become the preferred approach for deploying reliable communication network automation. This paper’s contribution is twofold. First, we propose a simple yet effective method to guarantee the confidentiality of the telemetry data based on feature scrambling. The method allows the operation of third-party computational services without direct access to the full content of the collected data. Additionally, the effectiveness of four unsupervised machine learning algorithms for soft-failure detection is evaluated when applied to the scrambled telemetry data. The methods are based on factor analysis, principal component analysis, nonlinear principal component analysis, and singular value decomposition. Most dimensionality reduction algorithms have the common property that they can maintain similar levels of fault classification performance while hiding the data structure from unauthorized access. Evaluations of the proposed algorithms demonstrate this capability.

97 MATHEMATICS AND COMPUTING↗

Towards ternary binders involving limestone additions — A review

The review summarises literature to examine the transition from portland limestone cement system to composite ternary binder systems involving limestone. Interest in limestone addition as an ideal component in multicomponent binder systems has surged as evident from the large volume of literature published in the recent past. A ternary blended system, with co-substitution of limestone, has the potential to complement the reaction of the supplementary cementitious materials (SCMs). The direct addition of limestone powder helps to attain higher substitution levels of portland cement clinker, improve early age properties, and supplement SCM's reactivity. However, the dilution of hydrates could hamper the long-term benefits. In this review, the interaction of fine limestone is classified and elaborated under two broad umbrellas: physical and chemical interactions. The physical interactions can manifest in three ways, namely, filler action, shearing action and improved packing, which alters reaction rate and extent at early ages. The chemical interactions also modify the reaction kinetics and phase assemblage due to nucleation of C-S-H on calcite surfaces, preservation of the ettringite phase and formation of carboaluminates. Two different forms of carboaluminate hydrates — hemicarboaluminate and mono-carboaluminate can be present in the hydrate matrix depending on the balance between carbonate ions and aluminates in the pore solution. Several factors such as replacement level, particle size, choice of SCM, its reactivity and reactive aluminates content, sulphate levels, curing temperature, and duration of curing can control the carboaluminate formation, reaction degree of SCMs and chemical interaction from limestone additions. A combination of physical and chemical effects makes fine limestone a potential material for co-substitution with aluminosilicate based SCMs, mainly fly ash, slag, and calcined clay. In this review, the factors affecting limestone-SCM composites are summarised based on a detailed literature survey. The effects of SCM-limestone cement composites on hydration kinetics, reaction chemistry, the reactivity of SCMs, the stability of hydrated phases, and contribution to the physical structure development and macroscopic properties by evaluating hydration and mechanical properties are discussed. The importance of AFm (Al{sub 2}O{sub 3}–Fe{sub 2}O{sub 3}-mono) phases in various deterioration mechanisms in concrete and their influence on performance characteristics in different exposure environment is critically appraised.

36 MATERIALS SCIENCE↗

Tetragonal BaCoO 3 : A Co 4+ Ferromagnetic Mott Insulator

We report the stabilization of the metastable body-centered tetragonal (BCT) phase of BaCoO 3 (BCT-BaCoO 3 ) under high-pressure (15 GPa) and hightemperature (1200 °C) conditions using a mixture precursor. This double perovskite adopts the EuTiO 3 -type structure (space group I4/mcm), as confirmed by powder Xray diffraction and high-resolution STEM. X-ray photoelectron spectroscopy indicates a predominant Co 4+ oxidation state without detectable oxygen vacancies. Magnetization and heat capacity measurements reveal ferromagnetic ordering at T C ∼ 107 K, attributable to the BCT-BaCoO 3 phase. Above this temperature, the mixed-phase sample exhibits Curie−Weiss paramagnetism, a low-spin to high-spin crossover upon cooling, and a possible intermediate-spin state at elevated temperatures. Resistivity data indicates insulating behavior with weak magnetoresistance. DFT and DFT + DMFT calculations suggest that the insulating state originates from an orbitally selective transition sensitive to the nominal valence of the Co-d shell. The metastable BCT-BaCoO 3 phase cannot be retained in pure form at ambient pressure but can be stabilized by embedding it in a disordered mixture, offering a potential route to discover and preserve other high-pressure phases under ambient conditions.

Magnetic properties↗

Nanocapsules of unprecedented internal volume seamed by calcium ions

The inception of an unprecedented class of voluminous Platonic solids displaying hierarchical geometry based on pyrogallol[4]arene moieties seamed by divalent calcium ion is described. Single-crystal X-ray structural determination has established the highly conserved geometry of two original Ca 2+ -seamed nanocapsules to be essentially cubic in shape with C-ethylpyrogallol[4]arene units located along the twelve edges of the cube which are then bridged by metallic polyatomic cations ([Ca 4 Cl] 7+ or [Ca(HCO 2 )Na 4 ] 5+ ) at the six cube faces. The accessible volume of the nanocapsules is ca. 3500 Å 3 and 2500 Å 3 and is completely isolated from the exterior of the capsules. These remarkable nanocapsule discoveries cast a spotlight on a marginalized area of synthetic materials chemistry and encourage future exploration of diversiform supramolecular assemblies, networks, and capsules built on calcium, with clear benefits deriving from the intrinsic biocompatibility of calcium. Finally, a proof-of-concept is demonstrated for fluorescent reporter encapsulation and sustained release from the calcium-seamed nanocapsules, suggesting their potential as delivery vehicles for drugs, nutrients, preservatives, or antioxidants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pathways for methane emissions and oxidation that influence the net carbon balance of a subtropical cypress swamp

We evaluated the major pathways for methane emissions from wetlands to the atmosphere at four wetland sites in the Big Cypress National Preserve in southwest Florida. Methane oxidation was estimated based on the d13C-CH4 of surface water, porewater, and bubbles to evaluate mechanisms that limit surface water emissions. Spatially-scaled methane fluxes were then compared to organic carbon burial rates. The pathway with the lowest methane flux rate was diffusion from surface waters (3.50 ± 0.22 mmol m-2 d-1). Microbial activity in the surface water environment and/or shallow oxic sediment layer oxidized 26 ± 3% of the methane delivered from anerobic sediments to the surface waters. The highest rates of diffusion were observed at the site with the lowest extent of oxidation. Ebullition flux rates were 2.2 times greater than diffusion and more variable (7.79 ± 1.37 mmol m-2 d-1). Methane fluxes from non-inundated soils were 1.6 times greater (18.4 ± 5.14 mmol m-2 d-1) than combined surface water fluxes. Methane flux rates from cypress knees (emergent cypress tree root structures) were 3.7 and 2.3 times higher (42.0 ± 6.33 mmol m-2 d-1) than from surface water and soils, respectively. Cypress knee flux rates were highest at the wetland site with the highest porewater methane partial pressure, suggesting that the emergent root structures allow methane produced in anaerobic sediment layers to bypass oxidation in aerobic surface waters or shallow sediments. Scaled across the four wetlands, emissions from surface water diffusion, ebullition, non-inundated soils, and knees contributed to 14 ± 2%, 25 ± 6%, 34 ± 10%, and 26 ± 5% of total methane emissions, respectively. When considering only the three wetlands with cypress knees present, knee emissions contributed to 39 ± 5% of the total scaled methane emissions. Finally, the molar ratio of CH4 emissions to OC burial ranged from 0.03 to 0.14 in the wetland centers indicating that all four wetland sites are net sources of atmospheric warming potential on 20-100 yr timescales, but net sinks over longer time scales (500 yr) with the exception of one wetland site that was a net source even over 500 yr time scales.

Ward, Nicholas D.↗

DEVELOPMENT OF STABLE ANODE AND CATHODE MATERIALS FOR RECHARGEABLE BATTERIES

Batteries have been employed in a variety of applications, such as portable electronics, electric vehicles (EVs), and stationary energy storage to preserve energy from other renewable sources (like wind or solar energy). The ultimate goal is to develop high energy density, long life span, better safety, and low cost of the batteries. However, current commercialized batteries (like lead-acid, zinc-alkaline, lithium-ion batteries (LIBs)) could not fulfill all the demands of diversified applications. LIBs predominate the market because of their high energy density. To achieve a higher capacity of the cell, high-nickel layered (Ni > 90%) cathode materials are promising candidates since they compose high specific capacity and discharge voltage. In chapter 1, an introduction to cell energy density and the development of high-nickel layered cathode materials along with associated obstacles of poor cycling stability and thermal stability have been discussed. Associated works like doping or surface coating have also been mentioned in this section. In chapter 2, Al doping in high-nickel layered cathode materials to enhance the structural and thermal stability was introduced. Uniform incorporation of Al doping is achieved by mechanical fusion and calcination processes. The Al doping not only decreased the Li/Ni mixing ratio but also enhance the thermal resistance to oxygen evolution because of strong Al-O bonding, which leads to elevated electrochemical and thermal stability. In chapter 3, TiN is implemented as a Ti dopant for high-nickel layered cathode materials to improve the electrochemical performance in the LIBs. The Ti not only diffused within the bulk structure but also formed segregation on the surface, which improved the structural stability and led to better cycling performance. Although LIBs deliver high energy density, safety concerns of flammable organic electrolytes have not been resolved yet. Therefore, the aqueous rechargeable zinc-ion batteries (ZIB) have been praised for their safe, low-cost, eco-friendly stationary energy storage, which is considered as a complementary system to LIBs. In chapter 4, the mechanism, advantages, and challenges of ZIBs would be given and the strategies for solving the zinc metal anode issues have been discussed in this section. In chapter 5, a polymer coating method was reported to facilitate Zn deposition/ stripping by coordination with Zn2+ and prevented direct contact with aqueous electrolyte to block corrosion side-reactions. With this coating, a boost in a lifetime (up to 400 hours) and lower polarization under extremely high current conditions (10 mA cm-2) have been achieved in repeated Zn deposition/ stripping cycling.

25 ENERGY STORAGE↗

Quantum properties of non-Dirichlet boundary conditions in gravity

The Euclidean path integral for gravity is enriched by the addition of boundaries, which provide useful probes of thermodynamic properties. Common boundary conditions include Dirichlet conditions on the boundary induced metric; microcanonical conditions, which refers to fixing some components of the Brown-York boundary stress tensor; and conformal conditions, in which the conformal structure of the induced metric and the trace of the extrinsic curvature are fixed. Boundaries also present interesting problems of consistency. The Dirichlet problem is known, under various (and generally different) conditions, to be inconsistent with perturbative quantization of graviton fluctuations, to exhibit thermodynamic instability, or to require infinite fine-tuning in the presence of matter fluctuations. We extend some of these results to other boundary conditions. We find that similarly to the Dirichlet problem, the graviton fluctuation operator is not elliptic with microcanonical boundaries, and the nonelliptic modes correspond to “boundary-moving diffeomorphisms.” However, we argue that microcanonical factorization of path integrals—essentially, the insertion of microcanonical constraints on two-sided surfaces in the bulk—is not affected by the same issues of ellipticity. We also show that for a variety of matter field boundary conditions, matter fluctuations renormalize the gravitational bulk and boundary terms differently, so that the classical microcanonical or conformal variational problems are not preserved unless an infinite fine-tuning is performed.

Draper, Patrick [Univ. of Illinois at Urbana-Champ↗

In-situ Characterizations of Microstructural Degradation of Perovskite Solar Cells

Rapid progress has been achieved in perovskite solar cells (PSCs), and their efficiencies have improved from 3.8 % to 24.2 % in less than a decade. With low-cost processing, PSCs have shown exciting photovoltaic (PV) properties, such as effective optical absorption, a long carrier lifetime, and unique defect tolerance. While recent studies demonstrated improved stability up to 100 days, PSC technology is still challenged to meet the stringent industry requirements for commercialization. Despite considerable efforts, the underlying physical mechanisms for the inferior stability of PSCs are not well understood. One reason for this divergence is that many established measurement techniques (e.g., quantum efficiency, photoluminescence) probe the properties on length scales far greater than that of electronic and/or structural inhomogeneity (i.e., < 1 μm near grain boundaries) and therefore characterize convoluted and/or averaged properties. Ion/electron beam-based techniques have been extensively used to access the microstructures of PSCs, enabling atomic/nanoscale structural, chemical, optical, and electrical characterizations. For example, focused ion beam (FIB) milling produces an atomically smooth surface that minimizes the artifacts attributed to the surface roughness. FIB techniques can also create a well-defined cross-section of PSCs without mechanical damage in a physical cleaving sample preparation. While powerful, there are some concerns about possible beam damage of inorganic-organic perovskites via chemical-bond breakage and local heating. This project aims to comprehensively understand how the microstructural/interfacial properties of PSCs (e.g., Methylammonium Lead Iodide [MAPbI 3 ]) are modified under the irradiating ion beams. Specifically, we investigate the sub-surface properties of PSCs before and after Ar-ion beam injections. Kelvin probe force microscopy (KPFM) measures the contact potential differences (CPDs). Photoluminescence (PL) microscopy in conjunction with Finite-Difference Time-Domain (FDTD) simulations infers the formation of a “dead layer” (< 15 nm) on the subsurface of MAPbI 3 during Ar+ milling processes while preserving the initial bulk properties. The x-ray photoemission spectroscopy (XPS) confirms this modified surface is a lead-rich and iodine-deficient surface. We initiate customizing in-situ measurement setup while measuring the local optical and electrical properties of PSC under thermal (cooling, heating) and light stressors. Our results provide in-depth knowledge of the ion-beam impact on metal-halide perovskites and how this modified sub-surface impacts their properties under accelerated stressors of light and heat. Intensive Monte Carlo simulations of an electron beam interacting with PSCs provide the beam energy distribution in PSCs, proposing possible measurement conditions of using e-beam with minimizing beam damage. Our in-situ measurement platform can accommodate the diverse architecture of PSC devices for studying deterioration mechanisms under mixed environmental stressors.

14 SOLAR ENERGY↗

The Dominant Effect of Electrolyte Concentration on Rechargeability of γ -MnO 2 Cathodes in Alkaline Batteries

Achieving high cycle life rechargeableγ-MnO 2 cathodes in alkaline batteries face many challenges. Chief among these is the inability of theγ-MnO 2 polymorph to retain its structural integrity when cycled to high utilization of its theoretical capacity ∼300 mAh g −1 . In this paper, we investigate the root cause of failure of MnO 2 cathodes under deep cycling in the one-electron discharge range and establish a strong link between capacity fade and the amount of birnessite formed. We uncover the underlying cause of failure by cycling industrial scaleγ-MnO 2 cathodes at various levels of theoretical capacity utilization (100%, 50%, and 30%) and in different KOH concentrations (37, 25, and 10 wt%). To determine materials evolution the cycled cathodes were dissected, characterized and analyzed using SEM, XRD, FIB/SEM, EIS, and XPS. Based on our findings, we propose that one major cause of failure of MnO 2 cathodes stems from the solubility of Mn +3 formed during discharge which effectively results in destruction of theγ-MnO 2 phase and amorphization of the cathode. The results show that the bulk of theγ-MnO 2 phase is preserved only in ∼10 wt% KOH, which indicates the attractive range of KOH concentration for cycling of rechargeableγ-MnO 2 cathodes.

Electrochemistry↗

Knowledge Oriented Graph Unified Transformer (KOGUT) v0.1

KOGUT — Knowledge Oriented Graph Unified Transformer KOGUT implements the Relational Graph Transformer (RelGT) architecture for knowledge graph link prediction in biological domains, with a primary focus on microbial growth media prediction. While the original RelGT (arXiv:2505.10960) targets relational tables, time series, and multi-table databases, KOGUT adapts this architecture for heterogeneous biological knowledge graphs, providing first-in-class AI predictive models for microbial cultivation. Key Adaptations Beyond Original RelGT: - Knowledge Graph Focus: Applied to biological KGs with semantic node types (taxa, chemicals, media, phenotypes, environments) versus generic relational database tables, trained on the KG-Microbe knowledge graph (1.3M entities, 2.9M edges, 24 relation types). - Multimodal Node Encoding: Integrates node labels, categories, descriptions, and synonyms from KG metadata through learned embedding layers—adapting relational column features to graph node attributes with textual semantics. - Extended K-Hop Subgraph Strategy: Optimized neighborhood sampling (3-hop default, configurable up to 200 nodes) tuned for sparse biological networks, building on the original local-global attention framework with biological relation preservation. - Biolink Predicate Preservation: Type-specific transformations for 24 biological edge semantics (occurs_in, consumes, produces, has_phenotype, subclass_of) beyond standard relational foreign keys, enabling multi-relation link prediction. - Inductive Learning Support: Enables zero-shot predictions for novel taxa through feature-based embeddings (temperature, oxygen requirements, gram stain, cell shape), extending the original transductive relational benchmark scope to uncultured microorganisms. CheapSOTA Performance Optimizations (This Distribution): - VQ-EMA Centroid Attention: Vector quantization with exponential moving average for improved global context modeling (+5-10% MRR improvement). - HDF5 Precomputed Data Loading: One-time preprocessing of k-hop subgraphs to eliminate redundant graph traversals (2-5× training speedup). - Distributed Data Parallel Training: Multi-GPU support for scaling to larger knowledge graphs (tested on 4× NVIDIA A100 GPUs at NERSC Perlmutter). - Mixed Precision Training: Automatic mixed precision (AMP) for memory efficiency and faster training. Advantages Over Standard Knowledge Graph Embedding Models: Combines RelGT's proven multi-element tokenization (features, type, hop, structure) with graph-native biological representations, enabling interpretable link prediction across heterogeneous entities that standard embedding models (TransE, RotatE, ComplEx) and table-based transformers cannot directly model. Achieves near-perfect performance on microbial growth media prediction (MRR: 0.9966, Precision@1: 0.9932, Hit@10: 1.0000) while maintaining explainability through attention-based reasoning over biological pathways. Training Data: - KG-Microbe merged knowledge graph: 1,379,337 nodes, 2,960,472 edges - 24 biological relation types including taxonomic hierarchies, metabolic interactions, phenotype associations, and environmental relationships - Primary prediction task: Growth media suitability for microbial taxa (biolink:occurs_in, 50K edges) - Multi-relation capability: Predicts links for any of the 24 relation types, including chemical consumption/production, phenotype associations, and taxonomic classification Citation: Original RelGT Architecture: Dwivedi et al., "Relational Graph Transformer", arXiv:2505.10960, 2025 KOGUT Implementation: Knowledge Oriented Graph Unified Transformer for Microbial Growth Media Prediction Developed at Lawrence Berkeley National Laboratory (LBNL) Trained on NERSC Perlmutter supercomputer

Joachimiak, Marcin [Lawrence Berkeley National Lab↗

Comparison Study of Upper Subcritical Limits Derived Using Sensitivity/Uncertainty Tools Case Studies of Benchmarks and Applications

Neutron transport methods used to establish subcriticality require validation by comparison to critical experiments considered to be benchmarks. Whisper is a sensitivity/uncertainty analysis tool developed to assist with the task of validation in nuclear criticality safety. Details on the Whisper methodology can be found in References 1-3 on the MCNP ® reference collection website at https://mcnp.lanl.gov. Whisper-1.0 was originally developed in 2014 and used to assist with nuclear criticality safety validation at Los Alamos National Laboratory. Whisper was upgraded in 2016 to Whisper-1.1 and prepared for release with MCNP6.2. Whisper contains a library of over 1100 critical experiment benchmarks and quantifies neutronic similarity of an application to benchmarks in the library. Using highest similarity benchmarks, Whisper computes a calculational margin (CM) encompassing of the worst-case bias and bias uncertainty at a 99% confidence level for each application. In addition, portions of the margin of subcriticality (MOS) for nuclear data uncertainty and potential code errors are computed. The baseline upper subcritical limit (USL) computed by Whisper is comprised of the CM, MOS nuclear data , and MOS code errors . The Whisper baseline USL is absent a portion of the MOS due to the area of application, which is applied based upon judgment by the criticality safety analyst. An objective of this paper is to present the baseline USL, CM and portions of the MOS as computed by Whisper for comparison with similar sensitivity/uncertainty tools, such as those used by IRSN and ORNL. The initial comparison involves four critical experiment benchmarks: HEU-MET-FAST-013-001, HEU-SOLTHERM-001-008, PU-MET-FAST-022-001, AND PU-SOL-THERM-001-001, which have been: 1. modeled independently by LANL, IRSN, and ORNL based upon information provided in the ICSBEP Handbook, 2. are common in S/U libraries for LANL, IRSN, and ORNL, 3. span a range of energy spectrum and fissile material, and 4. taken as applications for the purposes of this study and therefore excluded from use as a benchmark for calculating the upper subcritical limit. Results presented in this paper have been computed using covariance data for all isotopes in ENDF/BVII.0 using a 44-group energy structure. Benchmarks in the Whisper library were run in MCNP6.2 using 100,000 neutrons per cycle, skipping 100 cycles for 500 active cycles. Reference 10 also compares the results for baseline USL with an order of magnitude greater neutrons, using the same total number of cycles with 1,000,000 neutrons per cycle. Subsequent to the results presented in Reference 10 changes were made to the benchmark library, as discussed in Reference 11. Newer results using the revised benchmark library are presented herein.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Surface Manipulation on Pt 2.2 Ni(111) Nanocatalysts for Boosting Their ORR Performance in Alkaline Media

We have previously shown that Pt–Ni alloy nano-octahedra with {111} facets exhibit outstanding electrochemical performance in the oxygen reduction reaction (ORR) in acidic media when their surfaces are finely tailored at the atomic level. Here, in this investigation, we further refine the surface structure of Pt 2.2 Ni octahedral nanocatalysts to improve ORR performance in a 0.1 M KOH solution using diverse surface manipulation techniques. Through systematic analysis using electrochemical CO stripping, cyclic voltammetry, and X-ray photoelectron spectroscopy, we examined the surfaces of Pt 2.2 Ni octahedral nanocatalysts pretreated with various methods, including etching in acetic acid or perchloric acid, and subsequent electrochemical activation in an alkaline solution or an acidic solution. Among these treatments, those involving acidic media, particularly electrochemical cycling in acidic electrolytes, demonstrated significantly enhanced ORR activity in 0.1 M KOH. The latter exhibited a mass activity of 2.95 A/mg pt and a specific activity of 8.71 mA/cm 2 at 0.90 V, surpassing state-of-the-art Pt/C by 12-fold and 34-fold, respectively. Furthermore, this identified nanocatalyst displayed robust stability, with negligible activity decay observed after 10,000 cycles. This study suggests that the improved ORR activity can be attributed to the Pt-rich surfaces with well-preserved {111} lattices on the surface-modified Pt–Ni nano-octahedra.

36 MATERIALS SCIENCE↗

Direct Recycling of Blended Cathode Materials by Froth Flotation

We report that direct Li-ion battery recycling involves separating cathode active materials in the solid phase while preserving their electrochemical performance. To reuse the recycled ones in new batteries, it is necessary to separate individual cathode components, which would typically occur prior to the rejuvenation and any compositional reformulation processes. Herein, a froth flotation process is developed to separate pristine lithium nickel-manganese-cobalt oxide (LiNi 0.333 Mn 0.333 Co 0.333 O 2 , NMC111) and lithium manganese oxide (LMO) materials. The flotation results show that with multiple stages of the separation processes, a satisfactory separation is achieved with 95% grade or above of NMC111 in the froth product and 95% grade of LMO in the tailing product. The electrochemistry results show that the flotation chemicals have negligible impact on the electrochemical performance of recycled active materials, whereas the NMC111 exhibits a minor capacity fade after being in contact with deionized water at 2% solid concentration. An improvement in both the rate and cycling performance is achieved at 10% solid concentration or higher. It is found that there is little compositional and structural change to the aqueous recycled NMC111 powders. An effective and low-cost separation method for direct recycling mixed cathode compositions is demonstrated.

25 ENERGY STORAGE↗

The Influence of Environment on Post-Detonation Chemistry and Debris Formation (Abbreviated Final Report: 20-SI-006)

Predicting, responding to, or interpreting the chemical record preserved in debris derived from nuclear events can be challenging due to chemical fractionation. Chemical fractionation is where different species of the evolving radionuclide inventory segregate and/or are lost from the system over the timescales of debris formation. Both historic data and recent research suggest that the interaction and character of the local environment may exert controls on chemical fractionation by influencing the cooling and evolution of the associated fireball as well as the composition of the vapor term and resultant speciation. Prior to this work, an integrated platform permitting dynamic and concurrent consideration of physical and chemical evolution of early time post-detonation event environments did not exist. Our work merged historic data and experimental approaches to support development of a computational framework able to simulate fundamental processes (e.g., entrainment of local environment, oxidation chemistry, and cooling time scales) that may perturb the radionuclide inventory captured in post-detonation debris. Work with historic debris confirmed that entrained environmental material affect debris composition, structure, and radionuclide incorporation. Complementary work utilizing a readily controllable and tunable benchtop setup (a plasma flow reactor) simulated the late cooling of a nuclear fireball (e.g., T < 6000 K) and bounded the sensitivity of actinide speciation and particle size distribution to variations in oxygen concentration and cooling rates. Concurrent laser ablation and laser heating experiments were used to investigate the chemistry and physics of processes occurring in vaporized and/or rapidly heated actinides and other elements in the presence of oxygen. A more computationally efficient microphysical model was developed for predicting and evolving size distributions of particles forming from mixed vapor terms and simulating particle formation processes under a variety of extreme conditions. Continued study of historic nuclear event film confirmed that shockwave data and physics codes agree to within the uncertainty of the data. Good agreement was achieved for thermal emission from an airburst, however the paucity of low-temperature molecular opacity data for mixtures of air, bomb debris, entrained dirt, and water vapor complicate agreement for more elaborate scenarios. A multiphysics code (ALE3D) was modified to bring the necessary physics and chemistry, including these new data and insights, onto a single platform. Code development included improved initialization of large physical systems, modernization of chemistry capabilities, and modifications to enable inclusion of particle transport.

07 ISOTOPE AND RADIATION SOURCES↗

Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics

Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this library, or “suspects,” were derived from unannotated spectra that could be linked in a molecular network to an annotated spectrum. Annotations were propagated to unknowns based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer’s brain phenotype. The nearest neighbor suspect spectral library is openly available for download or for data analysis through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

59 BASIC BIOLOGICAL SCIENCES↗