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463 records · Page 20

Monolayer Films of Binary Metal Oxide Nanoparticles for Carbon Nanotube Synthesis

Binary metal oxide nanoparticles (biMO-NPs) combining transition and main-group metals with well-organized atomic architectures have unique potential as robust and economical heterogeneous catalysts. Herein, metal oxide nanoparticles (CoAlxOy) using cobalt and aluminum were synthesized, and their structure, morphology, and chemical composition were investigated using various characterization techniques. The biMO-NPs, which had a Gaussian-type size distribution (∼6 nm), were assembled on plain silicon substrates modified chemically with linker molecules bearing suitable end groups. Surface analysis revealed an ordered, uniform, close-packed arrangement of biMO-NPs forming a monolayer architecture with nanoscale thickness (∼12 nm), high surface uniformity, and negligible defects. The nanoparticle monolayer film (NP-MF) was employed as a catalyst to grow carbon nanotube (CNT) forests via the thermal chemical vapor deposition (CVD) method, similar to those grown from catalyst thin films deposited by physical vapor deposition. Structural characterization confirmed the growth of a dense, uniform, high-quality vertically aligned carbon nanotube (VA-CNT) forest with a length of ∼125 µm, which is comparable to the VA-CNTs grown from expensive thin films. Thus, CNT growth was successfully catalyzed by the biMO-NPs, highlighting a simple and inexpensive alternative for catalyst deposition. In this innovative wet-chemistry approach, the catalyst and catalyst support are combined within a single nanoparticle before NP-MF assembly. Interestingly, this approach provides a scalable and cost-effective pathway for CNT growth, eliminating the need for expensive thin deposition techniques.

Regmi, Bishow [University of Cincinnati]

Complex-Concentrated Anion Doping Enables Ultra-Stable Lattice Oxygen and Structural Integrity in Lithium-Rich Layered Oxide Cathodes

Lithium- and manganese-rich layered oxides (LMR) stand out as next-generation lithium-ion cathode chemistries, which harness both transition-metal and lattice-oxygen redox processes to deliver exceptional capacity and energy density. However, their full potential is hindered by intrinsic oxygen instability and structural degradation, resulting in pronounced voltage fade and capacity decay. Here, we present a complex-concentrated anion-doping paradigm in which multiple anions, F, Br, and S, are incorporated into the oxygen sublattice to enhance oxygen-redox and structural stability. X-ray absorption spectroscopy and aberration-corrected scanning transmission electron microscopy confirm ultra-stable local oxygen coordination environments during long-term cycling, with detrimental phase transformations and oxygen-loss-induced cavitation dramatically inhibited. Notably, we show that the characteristic LiTM6 transition metal (TM) honeycomb ordering is preserved even after electrochemical cycling. Concurrently, this strategy yields an unprecedented volume change of only 0.63% upon charging to 4.8 V vs. Li+/Li, achieving the first zero-strain LMR cathode. The resulting LMR cathode delivers ultralow voltage fade (1 mV per cycle during the first 100 cycles and becomes negligible in subsequent cycles) and outstanding energy retention (93% after 200 cycles) in a pouch cell configuration. Our complex-concentrated anion-doping concept establishes a broadly applicable strategy for resolving chemo-mechanical failure mechanisms in ceramic intercalation electrodes for next-generation energy storage.

Li-ion batteries

Stabilizer Scars

Quantum many-body scars are eigenstates in nonintegrable isolated quantum systems that defy typical thermalization paradigms, violating the eigenstate thermalization hypothesis and quantum ergodicity. Here, we identify exact analytic scar solutions in a 2+1 dimensional lattice gauge theory in a quasi-1D limit as zero-magic resource stabilizer states. Our results also highlight the importance of magic resources for gauge theory thermalization, revealing a connection between computational complexity and quantum ergodicity.

eigenstate thermalization

The impact of aerosol mixing state on immersion freezing: insights from classical nucleation theory and particle-resolved simulations

Immersion freezing, initiated by ice-nucleating particles (INPs) in supercooled aqueous droplets, plays an important role in the formation of ice crystals within clouds. The efficiency of immersion freezing depends strongly on INP composition and, crucially, on the mixing state – how chemical species are distributed across the particle population. Here, we quantify the impact of aerosol mixing state on immersion freezing using a combined theoretical and particle-resolved modeling approach. We derive analytical expressions for the frozen fraction of internally and externally mixed INP populations based on classical nucleation theory, showing that the frozen fraction is sensitive to whether ice-active species are present in all particles or only in a subset of the population. We introduce a multi-species immersion freezing scheme into the particle-resolved model PartMC, using the water activity-based immersion freezing model (ABIFM) to compute freezing probabilities for mixed-composition particles. To improve computational efficiency, we implement a Binned Tau-Leaping algorithm and demonstrate an order-of-magnitude speedup with minimal accuracy loss. Simulations reproduce the analytical trends in limiting cases and extend the analysis to more general aerosol populations, where mixing state continues to exert a substantial control on frozen fraction. Sensitivity analyses across particle size, species type, and cooling condition reveal that the mixing state effect is most pronounced when small amounts of highly efficient INPs are mixed with less efficient materials. These findings underscore the need to represent aerosol mixing state explicitly in models of heterogeneous ice nucleation to reduce uncertainty in cloud-phase partitioning.

54 ENVIRONMENTAL SCIENCES

A comparison of wrought and powder metallurgical FeCrAl claddings under simulated LWR accident transients

Iron-chromium-aluminum (FeCrAl) alloys are potential accident tolerant fuel (ATF) cladding candidates for light-water reactors but are difficult to fabricate as thin-walled tubes via conventional cast-and-wrought routes. Powder metallurgy (PM) offers a manufacturing alternative with improved compositional control, but its transient accident performance has not been directly benchmarked against wrought variants. This study evaluates the burst behavior of commercially developed PM-processed FeCrAl alloys, PM-C26M (Fe-12Cr-6Al-2Mo) and the high precipitate density FA-SMT (Fe-22Cr-5Al-3Mo), under simulated light-water reactor accident transient conditions. Burst testing was conducted using the Severe Accident Test Station with heating rates of 5 °C/s and 50 °C/s and internal pressures ranging from 25 MPa to 100 MPa. PM-C26M reproduced wrought C26M burst behavior within 7–37 °C across the stress range, indicating that PM processing does not compromise transient strength. FA-SMT exhibited markedly higher burst temperatures and reduced heating-rate sensitivity, consistent with its engineered precipitate strengthening. FA-SMT rupture exhibited axial "unzipping" rather than the lateral tearing characteristic of PM- and wrought C26M. Post-test EBSD and fractography indicate that this behavior is strongly correlated with strain-gated intergranular void nucleation associated with the dense precipitate architecture of FA-SMT, a response absent in the comparatively clean PM-C26M matrix and consistent with rupture morphologies reported for oxide-dispersion strengthened (ODS) FeCrAl of similar base-matrix chemistry to PM-C26M. These findings highlight the potential of powder metallurgy as a viable fabrication route for ATF claddings from an accident performance standpoint.

Bell, Sam [ORNL] (ORCID:0000000251905657)

Charm and bottom hadrons in hot hadronic matter

Heavy quarks, and the hadrons containing them, are excellent probes of the QCD medium formed in high-energy heavy-ion collisions, as they provide essential information on the transport properties of the medium and how quarks color-neutralize into hadrons. Large theoretical and phenomenological efforts have been dedicated thus far to assess the diffusion of charm and bottom quarks in the quark–gluon plasma and their subsequent hadronization into heavy-flavor (HF) hadrons. However, the fireball formed in heavy-ion collisions also features an extended hadronic phase, and therefore any quantitative analysis of experimental observables needs to account for the rescattering of charm and bottom hadrons. This is further reinforced by the presence of a QCD cross-over transition and the notion that the interaction strength is maximal in the vicinity of the pseudo-critical temperature. We review existing approaches for evaluating the interactions of open HF hadrons in a hadronic heat bath and the pertinent results for scattering amplitudes, spectral functions and transport coefficients. While most of the work to date has focused on D -mesons, we also discuss excited states as well as HF baryons and the bottom sector. Both the HF hadro-chemistry and bottom observables will play a key role in future experimental measurements. We also conduct a survey of transport calculations in heavy-ion collisions that have included effects of hadronic HF diffusion and assess its impact on various observables.

effective field theories

Nine lensed quasars and quasar pairs discovered through spatially extended variability in Pan-STARRS

We present the proof of concept of a method for finding strongly lensed quasars using their spatially extended photometric variability through difference imaging in cadenced imaging survey data. We applied the method to Pan-STARRS, starting with an initial selection of 14 107Gaiamultiplets with quasar-like infrared colours from WISE. We identified 229 candidates showing notable spatially extended variability during the Pan-STARRS survey period. These include 20 known lenses and an additional 12 promising candidates for which we obtained long-slit spectroscopy follow-up. This process resulted in the confirmation of four doubly lensed quasars, four unclassified quasar pairs, and one projected quasar pair. Only three are pairs of stars or quasar+star projections. The false-positive rate accordingly is 25%. The lens separations are between 0.81″ and 1.24″, and the source redshifts lie betweenz = 1.47 andz = 2.46. Three of the unclassified quasar pairs are promising dual-quasar candidates with separations ranging from 6.6 to 9.3 kpc. We expect that this technique is a particularly efficient way to select lensed variables in the upcomingRubin-LSST, which will be crucial given the expected limitations for spectroscopic follow-up.

Astronomy & Astrophysics

Liquified SO 2 induced solid/cathode electrolyte interphase for lithium ion batteries

Formation of robust solid/cathode electrolyte interphases (S/CEI) is vital for long-term stability and high-performance operation of lithium-ion batteries (LIBs), particularly under high voltage regimes. However, engineering electrochemically stable S/CEIs that effectively suppress interfacial side reactions remains a key challenge. Herein, we introduce a liquefied sulfur dioxide (SO 2 )– ionic liquid complex as a fluorine-free multifunctional electrolyte additive for the first time that significantly improves the formation of sulfate/sulfite-rich S/CEI layers at both graphite and NMC811 interfaces. The unique SO 2 -N coordination with a 1,2,4-triazolide-based ionic liquid enables homogeneous SO 2 dissolution, resulting in controlled SO 2 decomposition during the initial electrochemical cycle. This decomposition yields sulfur-rich interphase species that stabilize the electrolyte-electrode interface, reduce impedance growth, and lessen electrolyte decomposition. Electrochemical tests show significantly improved cycle life, reduced polarization, and increased Coulombic efficiency for both anodes and cathodes. XPS confirms the presence of SO 2 -derived surface species that contribute to interfacial stability. In conclusion, this approach highlights a new direction for interphase engineering using liquefied gas additives and opens pathways for sulfur-based S/CEI chemistry in advanced battery systems.

Graphite

NOx mediated formation of ε – UO 3 during thermal decomposition of uranyl nitrate hexahydrate under static air conditions

The thermal decomposition of uranyl nitrate hexahydrate in air at temperatures of 650 – 800 °C is expected to yield α – U 3 O 8 through intermediate UO 3 phases. Here, n this study, Raman spectroscopy complimented by powder X-ray diffraction revealed the unexpected formation of ε – UO 3 as an accompanying phase during thermal decomposition of UNH at 700 °C under static air conditions. Experiments demonstrated that ε – UO 3 does not form during the initial ramp up stage nor during the high temperature heating period; but instead forms during the cooling stage between 250 – 400 °C. Additional experiments revealed that UNH initially decomposes through an amorphous UO 3 intermediate prior to α – U 3 O 8 formation. Attempts to bypass the U 3 O 8 precursor in the formation of ε – UO 3 were unsuccessful, supporting the necessity of U 3 O 8 (α – U 3 O 8 in this study) in the formation of ε – UO 3 . The observed phase evolution is proposed to result from the NOx species generated during UNH thermal decomposition, which create localized oxidizing conditions within the furnace under static air conditions. Furthermore, a predominantly phase pure ε – UO 3 was synthesized under static air conditions through the addition of an extra plateau at 250 °C during the cooling step. These findings demonstrate the importance of gas-phase chemistry and cooling conditions in uranium oxide phase evolution and provide additional insight into ε – UO 3 formation pathways.

Epsilon uranium trioxide

Flame stabilization in DME spray flames under engine-relevant conditions characterized by OH* chemiluminescence and formaldehyde laser-induced fluorescence

The transient and quasi-steady flame structures of Dimethyl Ether (DME) fuel sprays, produced by a single-hole injector (Spray D), were investigated using Planar Laser-Induced Fluorescence (PLIF) and chemiluminescence imaging in a constant-volume chamber under Engine Combustion Network (ECN) Spray A conditions (900 K ambient temperature, 60 bar ambient pressure, 1500 bar injection pressure, and 22.8 kg/m 3 ambient density). Low-temperature chemical reaction zones were visualized using formaldehyde (CH 2 O) PLIF with 355 nm excitation, while high-temperature flame regions were captured via chemiluminescence imaging of excited-state hydroxyl radicals (OH*). Both transient and quasi-steady flame structures clearly show the transition from CH 2 O to OH*, highlighting the progression from low- to high-temperature combustion, while the position of the flame is displaced for DME compared to reference hydrocarbon n-dodecane. Homogeneous reactor calculations with detailed chemistry and using adiabatic mixing for initial temperature show that CH 2 O peaks are significantly higher for DME at the same equivalence ratio, with a higher heat-release during the cool-flame regime with respect to the fuel heating value. Thus, the cool-flame dynamic as a precursor to high-temperature combustion and flame stabilization exhibit distinct behavior for DME relative to conventional hydrocarbons, and these phenomena are effectively resolved through the soot-free nature of DME and the high-speed, time-resolved diagnostics.

CH2O laser-induced fluorescence

Cyclic Peptides for Lanthanide Binding

Lanthanide ions are difficult to separate from one another due to their similar chemical properties. The discovery of lanthanide-binding peptides and proteins in nature has led to an increased interest in the possibility of utilizing the strong binding of peptides to lanthanide ions for their separations; as such, there has been an effort to identify or design peptides with improved lanthanide binding and selectivity toward particular lanthanide ions. Here, in this study, we designed and characterized lanthanide-binding cyclic peptides (LBCPs) with molecular dynamics simulations, electronic structure calculations, and emission spectroscopy. Luminescent decay measurements were done to determine the number of water molecules coordinated to the Eu 3+ ion in Eu-LBCP complexes and compare to the predicted number of water molecules by computation to assess the lanthanide-binding affinity of LBCPs. Measured stability constants show binding of the LBCPs to the Eu 3+ ion with stronger than micromolar affinity. We were able to identify multiple peptides that selectively bind to middle lanthanides. We describe the structural basis of the lanthanide-binding selectivity trend with strongest binding to the middle lanthanides, followed by the heavier lanthanides, and finally to the lighter ions.

ions

Nuclear–Electronic Orbital General Rate Theory: Predicting Hydrogen Kinetic Isotope Effects in the Deep Tunneling Regime

Hydrogen transfer is a critical component of many chemical and biological processes. The ratio of rate constants for hydrogen and deuterium transfer defines the H/D kinetic isotope effect (KIE), which is a powerful tool for elucidating hydrogen transfer mechanisms. Interpretation of experimental H/D KIEs relies on accurate and affordable computational methods. However, due to their light mass, hydrogen and deuterium can undergo tunneling, which is challenging to describe in multidimensional molecular systems. Herein, we introduce the nuclear–electronic orbital general rate theory (NEO-GRT), which enables the efficient prediction of H/D KIEs based on full-dimensional molecular quantum chemistry calculations. The NEO-GRT approach describes the hydrogen transfer rate constant with a general expression that spans the vibrationally adiabatic and nonadiabatic hydrogen tunneling regimes. The input quantities are computed using NEO density functional theory, which treats the transferring hydrogen or deuterium nucleus quantum mechanically on the same level as the electrons. We investigate two intramolecular proton transfer reactions in organic molecules at temperatures down to 50 K to evaluate the performance of NEO-GRT by comparison to transition state theory and ring-polymer instanton theory. The KIEs computed with NEO-GRT agree with those calculated using ring-polymer instanton theory for the full-dimensional molecular systems at the same level of electronic structure theory. This agreement indicates that NEO-GRT captures the deep hydrogen tunneling effects, in contrast to transition state theory, which neglects such effects. Given its relatively low computational cost, NEO-GRT is a promising approach for predicting H/D KIEs in large organic and organometallic systems.

Hydrogen

Reconstruction and Dissolution of Copper Catalysts during Electrocatalytic Nitrate Reduction

Copper-based electrocatalysts are widely explored for electrochemical nitrate remediation, yet their stability under operating conditions remains poorly understood. While nanoscale and subnanoscale Cu motifs are known to restructure during the nitrate reduction reaction (NO 3 RR), how these transformations translate into irreversible material loss remains unclear. Here, we quantify Cu dissolution during NO 3 RR as a function of catalyst architecture and electrolyte chemistry using two model systems: single-atom Cu (Cu 1 ) and Cu nanoparticles (Cu NP ). Time-resolved leaching measurements, integrated with in situ X-ray absorption spectroscopy (XAS), reveal measurable Cu loss for both catalysts during NO 3 RR. Dissolution is concentrated at the initiation of electrolysis, coinciding with rapid restructuring, and depends strongly on morphology, with Cu NP consistently exhibiting greater Cu loss than Cu 1 . In situ XAS reveals that Cu 1 forms transient metallic clusters under reduction that largely redisperse upon returning to open-circuit voltage, whereas Cu NP undergoes reduction of an oxidized surface layer accompanied by sustained Cu loss during electrolysis. Notably, the presence of nitrate significantly intensifies restructuring and Cu loss, highlighting the critical role of electrolyte composition. Furthermore, these findings establish a direct link between electrochemical restructuring and Cu dissolution, unveiling electrolyte-dependent interactions as key determinants of catalyst durability in electrochemical nitrate conversion.

36 MATERIALS SCIENCE

Grain boundary segregation and chemical ordering in CoCrFeMnNi multi-principal element alloy

Owing to their far-from-dilute compositions, multi-principal element alloys (MPEAs) can exhibit unique combinations of engineering properties. As nearly all MPEAs are polycrystalline aggregates, it is necessary to understand the interactions of various elemental species with grain boundaries (GBs). This is of particular importance in extreme environments, such as radiation and elevated temperatures, where such interactions have implications on the properties of MPEAs. Herein, we employ atomistic simulations to generate a series of [001] asymmetric tilt GBs in a model CoCrFeMnNi MPEA and quantify solute interactions and segregation to these boundaries. We employ the Warren-Cowley order parameters to investigate the interplay between GB segregation and chemical short-range order (SRO). At temperatures above 800 K, simulation results reveal the segregation of Cr and Mn to CoCrFeMnNi GBs and show weak dependence of boundary solute excess on GB geometry, at least for the boundaries explored in this work. At temperatures in the range of 673–800 K, formation of domains rich in Cr is observed at GBs in agreement with experimental observations. Quantitative analysis shows that solute excess of various alloying elements decreases rapidly with the increase in temperature in the range of 1000–1200 K. Furthermore, we show that GB regions exhibit SRO characteristics that are distinct from the bulk crystals, leading to spatial variations in SRO. In broad terms, our study highlights the need to account for GB interactions with alloying elements when designing advanced MPEAs with novel chemistries.

Wang, Yitao [Lehigh University, Bethlehem, PA (Uni

Patchy nanoparticles by atomic stencilling

Stencilling, in which patterns are created by painting over masks, has ubiquitous applications in art, architecture and manufacturing. Modern, top-down microfabrication methods have succeeded in reducing mask sizes to under 10 nm, enabling ever smaller microdevices as today’s fastest computer chips. Meanwhile, bottom-up masking using chemical bonds or physical interactions has remained largely unexplored, despite its advantages of low cost, solution-processability, scalability and high compatibility with complex, curved and three-dimensional (3D) surfaces. Here we report atomic stencilling to make patchy nanoparticles (NPs), using surface-adsorbed iodide submonolayers to create the mask and ligand-mediated grafted polymers onto unmasked regions as ‘paint’. We use this approach to synthesize more than 20 different types of NP coated with polymer patches in high yield. Polymer scaling theory and molecular dynamics (MD) simulation show that stencilling, along with the interplay of enthalpic and entropic effects of polymers, generates patchy particle morphologies not reported previously. These polymer-patched NPs self-assemble into extended crystals owing to highly uniform patches, including different non-closely packed superlattices. We propose that atomic stencilling opens new avenues in patterning NPs and other substrates at the nanometre length scale, leading to precise control of their chemistry, reactivity and interactions for a wide range of applications, such as targeted delivery, catalysis, microelectronics, integrated metamaterials and tissue engineering.

36 MATERIALS SCIENCE

Tradeoffs and Synergies in Tropical Forest Root Traits and Dynamics for Nutrient and Water Acquisition: Field and Modeling Advances

Vegetation processes are fundamentally limited by nutrient and water availability, the uptake of which is mediated by plant roots in terrestrial ecosystems. While tropical forests play a central role in global water, carbon, and nutrient cycling, we know very little about tradeoffs and synergies in root traits that respond to resource scarcity. Tropical trees face a unique set of resource limitations, with rock-derived nutrients and moisture seasonality governing many ecosystem functions, and nutrient versus water availability often separated spatially and temporally. Root traits that characterize biomass, depth distributions, production and phenology, morphology, physiology, chemistry, and symbiotic relationships can be predictive of plants’ capacities to access and acquire nutrients and water, with links to aboveground processes like transpiration, wood productivity, and leaf phenology. In this review, we identify an emerging trend in the literature that tropical fine root biomass and production in surface soils are greatest in infertile or sufficiently moist soils. We also identify interesting paradoxes in tropical forest root responses to changing resources that merit further exploration. For example, specific root length, which typically increases under resource scarcity to expand the volume of soil explored, instead can increase with greater base cation availability, both across natural tropical forest gradients and in fertilization experiments. Also, nutrient additions, rather than reducing mycorrhizal colonization of fine roots as might be expected, increased colonization rates under scenarios of water scarcity in some forests. Efforts to include fine root traits and functions in vegetation models have grown more sophisticated over time, yet there is a disconnect between the emphasis in models characterizing nutrient and water uptake rates and carbon costs versus the emphasis in field experiments on measuring root biomass, production, and morphology in response to changes in resource availability. Closer integration of field and modeling efforts could connect mechanistic investigation of fine-root dynamics to ecosystem-scale understanding of nutrient and water cycling, allowing us to better predict tropical forest-climate feedbacks.

54 ENVIRONMENTAL SCIENCES

Agentic workflow enables the recovery of critical materials from complex feedstocks via selective precipitation

We present a multi-agentic workflow for critical materials recovery that deploys a series of AI agents and automated instruments to recover critical materials from produced water and magnet leachates. This approach achieves selective precipitation from real-world feedstocks using simple chemicals, accelerating the development of efficient, adaptable, and scalable separations to a timeline of days, rather than months and years.

Ritchhart, Andrew J.

EvoDiffMol: evolutionary diffusion framework for 3D molecular design with optimized properties

Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a computational framework that integrates evolutionary algorithms with three-dimensional diffusion models for property-driven molecular generation. The method operates through adaptive evolutionary optimization, where population-based selection guides the generation process toward desired property landscapes. EvoDiffMol supports both unconstrained molecular design and scaffold-constrained generation that preserves fixed substructures while optimizing complementary regions. Comprehensive evaluation demonstrates exceptional performance, achieving the highest drug-likeness score (0.94) among all compared state-of-the-art methods while maintaining excellent validity, uniqueness, and novelty. Beyond single property optimization, the framework demonstrates flexible multi-property optimization capabilities, simultaneously controlling multiple molecular descriptors including synthetic accessibility, lipophilicity, topological polar surface area, and clinically relevant ADMET properties such as cardiotoxicity (hERG) and intestinal permeability (Caco-2). This adaptability spans from simple descriptors to practical pharmaceutical endpoints without requiring complete model retraining. The framework achieves precise control over target property values, generating molecules with properties closely matching specified targets for both single and multiple descriptors. Scaffold-constrained experiments preserve fixed molecular cores while maintaining effective property optimization. The three-dimensional representation offers advantages in maintaining structural validity during iterative optimization, with potential for geometry-aware applications in materials science and drug discovery.

3D molecular generation