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At least 451 records · Page 25

Jordan–Wigner Transformation for the Description of Strong Correlation in Fermionic Systems

Seniority is a useful way of organizing Hilbert space for strongly correlated systems. The exact zero-seniority wave function, doubly occupied configuration interaction (DOCI), provides accurate results (given the right orbitals) for many strongly correlated electronic systems but has a combinatorial computational cost. In many cases, pair coupled cluster doubles provide a polynomial-cost approximation that closely reproduces the energies of DOCI, but it breaks down in some cases and, as shown herein, it does not provide particularly good density matrices. In this article, we demonstrate that by using the Jordan–Wigner transformation to turn the seniority zero problem back into a Fermionic one, we can provide mean-field variational results of DOCI quality for the Hubbard model and a few small molecular dissociation examples, with polynomial cost, both for the energies and for density matrices, all while being protected from collapse. This success is rooted in the proof we provide, showing that the Hartree–Fock wave function on the Jordan–Wigner-transformed Hamiltonian transforms back to variational coupled cluster doubles in the seniority zero representation, but restricted to have determinant rather than permanent amplitude coefficients, without compromising its overall accuracy.

74 ATOMIC AND MOLECULAR PHYSICS↗

A Perspective into Operando Methods for Probing Catalytic Interfaces

Rational design of electrocatalysts for (photo)electrochemical (PEC) processes like hydrogen and oxygen evolution and CO2 reduction reactions is aided by the recent improvements in capabilities of operando measurements, where morphology, composition, and/or function are probed during active catalysis. Through operando microscopy and spectroscopy, structure, catalytic microenvironment, oxidation state, adsorbates, and products can be measured to gain a better understanding of catalyst behavior and suggest possible improvements. Visualizing evolving catalyst morphologies, surface compositions, and electrochemical behavior also helps address many fundamental research questions for a better understanding of catalytic mechanisms. Correlating morphology with chemical identity or functional behavior using a variety of innovative microscopy methods is particularly promising for guiding development of next generation catalysts, and there are also many recent examples of using AI and robotics tools to innovate and speed development. In this Perspective, advances made over the past few years in operando imaging of catalysts relevant to solar fuels will be explored, followed by an outlook on technological developments in instrumentation, sample design, and computational power that may be applied to this field.

Catalysts↗

Gaussian processes for inferring parton distributions

The extraction of parton distribution functions (PDFs) from experimental or lattice QCD data is an ill-posed inverse problem, where regularization strongly impacts both systematic uncertainties and the reliability of the results. We study a framework based on Gaussian Process Regression (GPR) to reconstruct PDFs from lattice QCD matrix elements. Within a Bayesian framework, Gaussian processes serve as flexible priors that encode uncertainties, correlations, and constraints without imposing rigid functional forms. We investigate a wide range of kernel choices, mean functions, and hyperparameter treatments. We quantify information gained from the data using the Kullback-Leibler divergence. Synthetic data tests demonstrate the consistency and robustness of the method. Our study establishes GPR as a systematic and non-parametric approach to PDF reconstruction, offering controlled uncertainty estimates and reduced model bias in lattice QCD analyses.

hadronic spectroscopy↗

Structural features of xylan dictate reactivity and functionalization potential for bio-based materials

Plant-based materials have the potential to replace some petroleum-based products, offering compostability and biodegradability as critical advantages. Xylan-rich biomass sources are gaining recognition due to their abundance and underutilization in current industrial applications. Research of potential xylan applications has been complicated by the complex and heterogeneous structure that varies for different xylan feedstocks. Acylation is a broadly used reaction in functionalization of polysaccharides at an industrial scale. However, the efficiency of this reaction varies with the xylan source. To optimize xylan valorization, a systematic understanding of structure–reactivity relationships is essential. This study explores, characterizes, and compares various xylan feedstocks in the acylation process. Xylan feedstocks were analyzed for their chemical composition, degree of polymerization, branching, solubility, and presence of impurities. These features were correlated with xylan glycotypes’ reactivity toward functionalization with succinic anhydride in an optimized DMSO/KOH condition, achieving carboxyl contents of up to 1.46. We used principal component analysis and hierarchical clustering to identify key structural features of xylan that promote its reactivity. Our findings reveal that xylans with higher xylose content and lower degrees of branching exhibit enhanced reactivity, achieving higher carboxyl content and yields. Structural analyses confirmed successful modification, and light scattering analyses showed dramatic changes in the solution properties. Succinylation improves the solubility and film-forming properties of native xylans. This study shows key structure–reactivity relationships in xylan succinylation, establishing that low branching, high xylose content, and reduced lignin impurity enhance chemical functionalization. The results offer a framework for selecting optimal biomass feedstocks and support future efforts in genetic and synthetic biology to design plants with tunable xylan architectures. These findings advance the hemicellulose valorization for applications in coatings and packaging.

Acylation↗

Modulating Oxide‐Based Quantum Materials by Ion Implantation

Ion implantation has emerged as a powerful tool for manipulating and investigating oxide quantum materials, where strong electron correlations give rise to exotic phases and functionalities. This Review examines how controlled ion bombardment enables targeted modulation of structural, electronic, and magnetic properties in complex oxides. Recent advances in ion beam techniques is analyzed that provide unprecedented control over defect profiles, from point defects to extended damage cascades. In application, ion irradiation has demonstrated the ability to tune quantum phenomena including metal‐insulator transitions, magnetism, and superconductivity through selective doping, defect creation, and lattice strain. The ability to write quantum states with nanoscale precision using focused ion beams is opening new paths for quantum device fabrication. Challenges in understanding radiation damage mechanisms in strongly correlated systems is discussed, and identify opportunities for designing quantum functionality through defect‐engineering approaches. The technique's demonstrated capability to write quantum states with nanoscale precision, combined with its compatibility with existing semiconductor processing infrastructure, suggests a clear pathway for translating fundamental discoveries in quantum materials into practical technological applications.

defect engineering↗

Reference Correlations for the Density and Viscosity of Molten Alkali and Alkaline Earth Fluoride Salts

While there is a significant body of literature pertaining to thermophysical property measurements of molten salts, there is often a wide degree of variability among independent measurements of the same compounds. As such, the scientific community benefits greatly from an unbiased, independent assessment of duplicate datasets, so that reference correlations which describe these thermophysical properties as functions of temperature can be determined and then commonly used by researchers, scientists, and engineers. With regard to molten fluoride compounds, a significant time has elapsed since density and viscosity reference correlations have been determined; Janz conducted the most recent effort, in 1988, to provide reference correlations for the densities and viscosities of molten fluoride compounds via the National Standard Reference Data System coordinated by the National Bureau of Standards. Since then, new data have been published for molten fluoride compounds, and a new precedent has surfaced for putting forth reference correlations that involve fitting to multiple primary datasets. In this work, reference correlations are put forth for molten alkali and alkaline earth fluoride compounds in an effort to provide updated, improved correlations for general use. For molten alkali fluoride densities, estimated uncertainties with a 95% confidence interval are summarized as follows: LiF (0.63%), NaF (0.48%), KF (0.76%), RbF (0.93%), and CsF (0.75%). For molten alkaline earth fluoride densities, an estimated uncertainty was not able to be quantified for BeF 2 because of limited data; however, estimated uncertainties with a 95% confidence interval are summarized as follows for the remaining alkaline earth fluorides: MgF 2 (1.5%), CaF 2 (0.92%), SrF 2 (1.6%), and BaF 2 (0.23%). For molten alkali fluoride viscosities, uncertainty was not able to be quantified for RbF and CsF because of limited data; however, estimated uncertainties with a 95% confidence interval are summarized as follows for the remaining alkali fluorides: LiF (4.4%), NaF (3.0%), and KF (4.0%). For molten alkaline earth fluoride viscosities, limited consistent data resulted in the recommendation of single datasets (from literature) that are deemed to be the most trustworthy based on the quality of the underlying experimental studies.

Birri, A. [Oak Ridge National Laboratory (ORNL), O↗

Plasmons in the Kagome metal CsV 3 Sb 5

Plasmon polaritons, or plasmons, are coupled oscillations of electrons and electromagnetic fields that can confine the latter into deeply subwavelength scales, enabling novel polaritonic devices. While plasmons have been extensively studied in normal metals or semimetals, they remain largely unexplored in correlated materials. In this paper, we report infrared (IR) nano-imaging of thin flakes of CsV3Sb5, a prototypical layered Kagome metal. We observe propagating plasmon waves in real-space with wavelengths tunable by the flake thickness. From their frequency-momentum dispersion, we infer the out-of-plane dielectric function that is generally difficult to obtain in conventional far-field optics, and elucidate signatures of electronic correlations when compared to density functional theory (DFT). We propose correlation effects might have switched the real part of ϵ c from negative to positive values over a wide range of middle-IR frequencies, transforming the surface plasmons into hyperbolic bulk plasmons, and have dramatically suppressed their dissipation.

36 MATERIALS SCIENCE↗

Seniority eigenstate configuration interaction

Zero-seniority methods have shown great promise for the description of strongly correlated electronic systems. Other seniority sectors have been much less explored, and in particular, the maximal seniority sector and zero seniority have the same underlying algebraic structure. We introduce a seniority eigenstate configuration interaction in which the wave function is constrained to have good fixed local seniority for each paired orbital, by which we mean we partition orbitals into a pairing set with seniority zero, and a spin set with seniority one. Here, we show how to build the effective Hamiltonian for this ansatz, and demonstrate that high-seniority wave functions have unexpectedly excellent accuracy for strongly correlated fermionic systems, with accuracy competitive with or better than seniority zero for the Hubbard model and for the dissociation of the nitrogen molecule.

74 ATOMIC AND MOLECULAR PHYSICS↗

Transverse-momentum-dependent pion structures from lattice QCD: Collins-Soper kernel, soft factor, TMDWF, and TMDPDF

We present the first lattice quantum chromodynamics (QCD) calculation of the pion valence-quark transverse-momentum-dependent parton distribution function (TMDPDF) within the framework of large-momentum effective theory (LaMET). Using correlators fixed in the Coulomb gauge (CG), we computed the quasi-TMD beam function for a pion with a mass of 300 MeV, a fine lattice spacing of 𝑎 =0.06 fm, and multiple large momenta up to 3 GeV. The intrinsic soft functions in the CG approach are extracted from form factors with large momentum transfer, and as a byproduct, we also obtain the corresponding Collins-Soper (CS) kernel. Our determinations of both the soft function and the CS kernel agree with perturbation theory at small transverse separations (𝑏 ⊥ ) between the quarks. At larger 𝑏 ⊥ , the CS kernel remains consistent with recent results obtained using both CG and gauge-invariant TMD correlators in the literature. By combining next-to-leading logarithmic factorization of the quasi-TMD beam function and the soft function, we obtain an 𝑥-dependent pion valence-quark TMDPDF for transverse separations 𝑏 ⊥ ≳1 fm. Interestingly, we find that the 𝑏 ⊥ dependence of the phenomenological parametrizations of TMDPDF for moderate values of 𝑥 are in reasonable agreement with our QCD determinations. In addition, we present results for the transverse-momentum-dependent wave function for a heavier pion with 670 MeV mass.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Collins-type fragmentation energy correlator in semi-inclusive deep inelastic lepton-hadron scattering

We initiate a systematic study of fragmentation energy correlators (FECs), which generalize traditional fragmentation functions and encode non-perturbative information about transverse dynamics in parton fragmentation processes. We define boost-invariant, non-perturbative FECs and derive a corresponding collinear factorization formula. A spin decomposition of the FECs is carried out, analogous to that of transverse-momentum-dependent fragmentation functions. In this work we focus particularly on the Collins-type quark FEC, which is sensitive to chiral symmetry breaking and characterizes the azimuthal asymmetry in the fragmentation of a transversely polarized quark. We perform a next-to-leading-order calculation of the corresponding hard coefficient in semi-inclusive deep-inelastic scattering for the quark non-singlet component, thereby validating the consistency of our theoretical framework.

Deep Inelastic Scattering or Small-x Physics↗

Quenching of the quantum p -strength in light exotic nuclei

One-nucleon spectroscopic overlaps, their strength or spectroscopic factors (SFs), and nucleon removal cross sections for light nuclei in the mass range A≤12 were evaluated using the fully correlated Quantum Monte Carlo (QMC) wave functions (WFs). Harder (AV18+UX) and softer (NV2+3) bare interactions were used providing consistent results. The SFs were also taken from simple Shell Model (SM) calculations. This structure information was incorporated in the standard three-body Faddeev/Alt-Grassberger-Sandhas reaction formalism to evaluate the (p,pN) cross sections. The results further our understanding of the quenching of the quantum p-shell strength obtained from structure and reactions. We have found the ratios of the total QMC sums of SFs to the SM ones to be uniform and ∼ 3/4. The corresponding ratios of the sums Below Particle Threshold (BPT) of SFs, as well as of total cross sections, deviate strikingly from the uniform trend in some special cases. We find these ratios to be close to unit for 9 Li → 8 Li + n and 9 C → 8 B + p. In contrast, they are strongly reduced for 11 C → 10 C + n and 11 B → 10 Be + p mirror transitions, resulting from the quenching of the strength for low-lying 2 + final state transitions. The QMC theoretical cross section BPT for 11 C(p,pn) is about two times smaller than the experimental data.

(p,pN) reactions↗

Unraveling Anion-Specific Inhibition and Structural Modulation of Gibbsite Crystallization: Implications for Aluminum Mobility in Natural and Engineered Systems

Gibbsite (α-Al(OH) 3 , sometimes designated as γ-Al(OH) 3 ) plays a crucial role in the chemistry of aluminum in the environment and industry, yet its crystallization behavior under multianionic conditions is not well understood. Here, in this study, we investigate how six common anions─fluoride (F – ), chloride (Cl – ), bromide (Br – ), nitrate (NO 3 – ), sulfate (SO 4 2– ), and phosphate (PO 4 3– )─influence the mineralization, structure, and morphology of gibbsite at room temperature. The results show that PO 4 3– , SO 4 2– , and F – strongly inhibit gibbsite formation, stabilizing amorphous or alternative crystalline phases such as nordstrandite and cryolite. On the contrary, Cl – , Br – , and NO 3 – allow partial to complete crystallization of gibbsite without significant morphological changes. Solid-state 27 Al magic angle spinning nuclear magnetic resonance provides crucial insight into aluminum coordination environments in both crystalline and amorphous phases, distinguishing between octahedral, pentahedral, and tetrahedral Al species. The density functional theory calculations reveal a direct correlation between the Al–X bond strength and the inhibition of crystallization, following the order: PO 4 3– > SO 4 2– > F – > NO 3 – > Cl – > Br – . These findings offer molecular-scale insights into anion-specific effects on aluminum hydroxide nucleation and transformation, improving the understanding of gibbsite formation and aluminum cycling in soils, phosphate retention, contaminant immobilization, and waste treatment strategies in nuclear and industrial settings. These insights can also guide the controlled synthesis of aluminum hydroxide materials with tailored crystallinity and morphology via liquid-assisted methods.

Anions effect↗

Electron Transfer Theory Elucidates the Hidden Role Played by Triethylamine and Triethanolamine during Photocatalysis

Triethylamine (TEA) and triethanolamine (TEOA) are renowned, in part, for their ability to reductively quench excited states by outer-sphere electron transfer with vast and still growing applications as sacrificial electron donors for photocatalytic systems. Upon amine oxidation, the resulting TEA •+ and TEOA •+ radical cations undergo proton transfer (or hydrogen atom transfer), resulting in the formation of a chemical reductant that has an α-carbon centered radical adjacent to the nitrogen center (TEA • and TEOA • ). In this contribution, we have electrochemically and spectroscopically characterized a set of electron acceptors which, upon accepting an electron, are a series of photocatalysts, [ReCl(R 1 R 2 -bpy)(CO) 3 ] •– , where R 1 and R 2 are electron-donating and electron-withdrawing groups in the 4,4′- and 5,5′-positions on the bipyridyl ligand. Here, we substantiated the formation of the electron donors, TE(O)A • , by spin trapping electron paramagnetic resonance spectroscopy, where TE(O)A • reacts with 2,4,6-tri-tert-butylnitrosobenzene to generate N-centered and O-centered radical adducts. Having established the chemical behaviors of the electron acceptors and donors individually, the electron transfer rate constants were determined across a 1.43 V range in driving force. The redox potential of TEA • was benchmarked to within ±80 mV on an absolute scale in V vs Fc + /Fc in CH 3 CN by using an empirical rate vs free-energy correlation, electron transfer theory, and density functional theory calculations. The equilibrium potentials for TEA • and TEOA • were determined to be −1.98 V and −1.76 V, respectively. Based on the kinetic and thermochemical analysis presented for TEA • and TEOA • , these transient radicals can be broadly considered strong homogeneous chemical reductants within the wider context of photoredox potentials. Thus, this work clarifies a frequently unnoticed secondary function for these sacrificial electron donors during photocatalysis and rationalizes the possibility of a one-photon/two-electron conversion process that is dependent on the free-energy exchange between TE(O)A • and photocatalysts.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation

Machine learning (ML) is rapidly emerging as a pivotal tool in the hydrogen energy industry for the creation and optimization of electrocatalysts, which enhance key electrochemical reactions like the hydrogen evolution reaction (HER), the oxygen evolution reaction (OER), the hydrogen oxidation reaction (HOR), and the oxygen reduction reaction (ORR). This comprehensive review demonstrates how cutting-edge ML techniques are being leveraged in electrocatalyst design to overcome the time-consuming limitations of traditional approaches. ML methods, using experimental data from high-throughput experiments and computational data from simulations such as density functional theory (DFT), readily identify complex correlations between electrocatalyst performance and key material descriptors. Leveraging its unparalleled speed and accuracy, ML has facilitated the discovery of novel candidates and the improvement of known products through its pattern recognition capabilities. This review aims to provide a tailored breakdown of ML applications in a format that is readily accessible to materials scientists. Hence, we comprehensively organize ML-driven research by commonly studied material types for different electrochemical reactions to illustrate how ML adeptly navigates the complex landscape of descriptors for these scenarios. We further highlight ML's critical role in the future discovery and development of electrocatalysts for hydrogen energy transformation. Potential challenges and gaps to fill within this focused domain are also discussed. As a practical guide, we hope this work will bridge the gap between communities and encourage novel paradigms in electrocatalysis research, aiming for more effective and sustainable energy solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Iron-assisted growth of anisotropic ZnO nanostructures

Anisotropic nanostructures offer a promising pathway to modulate structure-function relationships of materials. However, the correlation between growth direction of high-quality anisotropic nanostructures, the synthesis conditions and mechanisms controlling their growth, and their magnetic and optical properties remain underexplored. In this study, we developed an iron-assisted anisotropic growth method to form zinc oxide nanostructures on the O-polar (0001̄) surface, resulting in two distinct ZnO-based nanostructures: hand-shaped nanostructures and truncated hexagonal nanopyramids. In contrast to most reports of anisotropic nanostructure synthesis, which primarily focus on morphology control through ligand-ligand interactions, the current study probes the effects of doping on anisotropic growth, and how doping, along with ligand-ligand interactions and facet-specific ligand binding, control nanostructure morphology. The reaction mechanisms leading to formation of these novel structures were thoroughly probed by systematically manipulating synthesis parameters. A two-step formation mechanism was identified: first, a hexagonal platform forms through an initial homogeneous nucleation process, followed by secondary heterogeneous nucleation, which results in metastable secondary nanostructures growing on the oxygen-rich template. Optical and magnetic properties of these Fe/ZnO nanostructures were characterized. Our findings provide a new strategy that uses a magnetic element as a dopant to build new nanostructures of ZnO with controllable size and shape growing on an oxygen-rich crystal plane. These materials could have applications in novel technologies where both optoelectronic and magnetic properties are of interest.

Xuan, Zhengxi↗

Atomistic characterization of hydration-dependent fuel cell ionomer nanostructure: validation by vibrational spectroscopy

The development of Nafion alternatives for fuel cells and electrolyzers requires a fundamental understanding of hydration-dependent ion-exchange site acid/base chemistry. We present here reactive force field (ReaxFF) molecular dynamics (MD) simulations of Nafion at varying molar water/ion-exchange-site ratios (λ), which we correlate to our experimental and density functional theory-based vibrational spectra. ReaxFF describes the formation and breaking of covalent bonds, enabling simulations of proton exchange between sulfonic acid/sulfonate groups and water/hydronium. Our MD simulations determine the λ-dependent equilibrium proportions of protonated and deprotonated sites. We find that protonated sites persist across all λ from 0 to 20, challenging the widely accepted notion that all sites are ionized above a threshold λ value (e.g., 3 or 4). Our simulations generate hundreds of realistic exchange site environments, the characterization of which are based on 6 Å radii sulfur-centered ‘inner-spheres’. These inner- and outer-sphere regions elucidate an interplay of stereoelectronic factors that influence protonation states, including the number of inner-sphere waters (Λ). Our simulations produce broad λ-dependent distributions of Λ values, representing non-uniform exchange site hydration. Moreover, we demonstrate that these distributions are specific to both protonated and deprotonated sites, with significant overlap between the two distributions for all non-zero λ. These distributions underpin the IR spectra of hydrated membranes, with each exchange site contributing an IR spectrum characteristic of its protonation state and Λ. We expect that these nanostructural characterizations of Nafion exchange sites will contribute to the development of new ionomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparative Performance Evaluation of Large Language Models for Extracting Molecular Interactions and Pathway Knowledge

Understanding the interactions and regulatory relationships among biomolecules is essential for deciphering complex biological systems and elucidating the mechanisms behind diverse biological functions. Traditionally, the collection of such molecular interaction data has relied on expert curation, a process that is both time-consuming and labor-intensive. To address these limitations, this study explores the use of large language models (LLMs) to automate the genome-scale extraction of molecular interaction knowledge. Here, we evaluate the performance of various LLMs on key biological tasks, including the identification of protein-protein interactions, detection of genes associated with pathways influenced by low-dose radiation, and inference of gene regulatory relationships. Our findings demonstrate that larger LLMs tend to perform better, particularly in extracting intricate gene and protein interactions. Despite their strengths, these models face challenges in recognizing functionally diverse gene groups and highly correlated regulatory relationships. Through a comprehensive analysis using established molecular interaction and pathway databases, we show that LLMs possess the potential to identify relevant biomolecules and predict their interactions, offering valuable insights and marking a significant step toward AI-driven biological knowledge discovery.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Electronic structure complexity and extremely large magnetoresistance in antiferromagnetic semimetal SmAgSb 2

SmAgSb 2 , a layered magnetic semimetal in the tetragonal 𝑅⁢𝑇⁢ Sb 2 family (𝑅 = Y, Sc, rare earth; 𝑇 = transition metal), is known to exhibit extremely large magnetoresistance (XMR) below its antiferromagnetic (AFM) transition temperature. Here, in this work, we present a comprehensive investigation combining magnetotransport measurements, density functional theory calculations accounting for electron correlation, and angle-resolved photoemission spectroscopy. Our results reveal a complex electronic structure characterized by a multiband Fermi surface and intricate magnetic ground states. We demonstrate that simple two-band models, previously employed in the literature, fail to consistently describe the observed transport phenomena. Notably, we report an XMR of approximately 25200% at 2 K under a 14 T magnetic field, significantly exceeding earlier reports for this material family and rivaling the performance of prominent nonmagnetic XMR systems. This pronounced enhancement below 𝑇 𝑁 suggests that the XMR originates from a combination of multiband electron-hole compensation and enhanced magnetic scattering in this correlated AFM semimetal.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗