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At least 1,207 records · Page 67

A theoretical study of the upper bound of surface elevation variance in the Phillips initial stage during wind-wave generation

The resonance mechanism in the initial of wind-wave generation proposed by Phillips is a foundation of wind-wave generation theory, but a precise theoretical quantification of wave energy growth in this initial stage has not been obtained yet after more than six decades of research. In this study, we aim to address this knowledge gap by developing an analytical approach based on a novel complex analysis method to theoretically investigate the temporal evolution of the wave energy in the Phillips initial stage. We quantitatively derive and analyse the growth behaviour of the surface wave energy and obtain an analytical solution for its upper bound. Our result highlights the crucial effects of surface tension. Because the phase velocity of gravity–capillary waves has a minimal value at a critical wavenumber, gravity–capillary waves and gravity waves (which neglect surface tension) exhibit distinct resonance curve properties and wave energy growth behaviours. For gravity waves, the resonance curve extends indefinitely; for gravity–capillary waves, it either forms a finite-length curve or does not exist, depending on the wind speed. The leading-order term of the upper-bound solution of the energy of gravity waves increases linearly over time, while for gravity–capillary waves, the term increases linearly over time under strong wind conditions but remains finite under weak wind conditions. This theoretical study provides an analytical framework for the generation of wind-waves in the Phillips initial stage, which may inspire further theoretical, numerical and experimental research.

58 GEOSCIENCES↗

Tunable and Robust Optical and Structural Properties of a Cooperative Squaraine-Dye Aggregate-DNA DX-DAE Tile System

Molecular excitons, which are excitations delocalized over multiple dyes in a wavelike manner, are of interest for a wide range of applications, including quantum information science. Numerous studies have templated a variety of synthetic dyes via a DNA scaffold to induce dye aggregation to create molecular excitons upon photoexcitation. Dye aggregate optical properties are critically dependent on relative dye geometry and local environment; therefore, an understanding of dye-dye and DNA-dye interactions is critical for advancing toward more complex DNA-dye systems. The extensively studied DNA Holliday junction (HJ) and less-studied double-crossover (DX) tile motif are fundamental test beds for designing complex and ultimately modular DNA-dye architectures. Here, we report the first study of single-linked squaraine dye aggregation and exciton delocalization on a larger and more stable (compared with the HJ) DX tile motif. We first highlight a few DNA-dye constructs that support single dyes and aggregates with distinct optical properties that are both tunable—through sample design, buffer conditions, and heat treatment—and robust to environment changes, including transfer to solid phase. Next, we assess several experimental and design considerations that demonstrate directed dye-driven assembly of a novel double-tile DNA configuration. Our results demonstrate that single-linked squaraine dyes templated to DX tiles provide a viable research path to design and evaluate dye aggregate networks that support exciton delocalization. We include herein the first report of exciton delocalization in the solid phase in a DNA-dye construct. Additionally, our findings indicate that dye aggregation impacts the assembly of the DNA-dye construct, and, in some cases, thereby cooperates with the DNA to determine a final robust system configuration. Finally, we show that a controlled annealing schedule can be employed to promote the homogeneous assembly of DNA-dye constructs. The findings in this study contribute to the understanding of DNA-dye systems and the relevant factors involved in their directed assembly to achieve specific constructs with desirable properties.

36 MATERIALS SCIENCE↗

Reproducibility of fixed-node diffusion Monte Carlo across diverse community codes: The case of water–methane dimer

Fixed-node diffusion quantum Monte Carlo (FN-DMC) is a widely trusted many-body method for solving the Schrödinger equation, known for its reliable predictions of material and molecular properties. Furthermore, its excellent scalability with system complexity and near-perfect utilization of computational power make FN-DMC ideally positioned to leverage new advances in computing to address increasingly complex scientific problems. Even though the method is widely used as a computational gold standard, reproducibility across the numerous FN-DMC code implementations has yet to be demonstrated. This difficulty stems from the diverse array of DMC algorithms and trial wave functions, compounded by the method’s inherent stochastic nature. Here, this study represents a community-wide effort to assess the reproducibility of the method, affirming that yes, FN-DMC is reproducible (when handled with care). Using the water–methane dimer as the canonical test case, we compare results from eleven different FN-DMC codes and show that the approximations to treat the non-locality of pseudopotentials are the primary source of the discrepancies between them. In particular, we demonstrate that, for the same choice of determinantal component in the trial wave function, reliable and reproducible predictions can be achieved by employing the T-move, the determinant locality approximation, or the determinant T-move schemes, while the older locality approximation leads to considerable variability in results. These findings demonstrate that, with appropriate choices of algorithmic details, fixed-node DMC is reproducible across diverse community codes—highlighting the maturity and robustness of the method as a tool for open and reliable computational science.

Della Pia, Flaviano [Univ. of Cambridge (United Ki↗

Nonequilibrium universality of the nonreciprocally coupled 𝑂⁡(𝑛 1 ) × 𝑂⁡(𝑛 2 ) model

Nonequilibrium dynamics play an important role in all contexts of physics, both classical and quantum as well as living and nonliving, so it is crucial to develop a foundational understanding of nonequilibrium phase transitions. In this work we investigate an important class of nonequilibrium dynamics in the form of nonreciprocal interactions. In particular we study how nonreciprocal coupling between two 𝑂⁡(𝑛𝑖) order parameters (with 𝑖 = 1,2) affects the universality at a multicritical point, extending the analysis of J. T. Young et al. [Phys. Rev. X 10, 011039 (2020)], which considered the case 𝑛 1 = 𝑛 2 = 1, i.e., a ℤ 2 × ℤ 2 model. We show that nonequilibrium fixed points (NEFPs) emerge for a broad range of 𝑛 1 ,𝑛 2 and exhibit intrinsically nonequilibrium critical phenomena, namely a violation of fluctuation-dissipation relations at all scales and underdamped oscillations near criticality in contrast to the overdamped relaxational dynamics of the corresponding equilibrium models. Furthermore, the NEFPs exhibit an emergent discrete scale invariance in certain physically relevant regimes of 𝑛 1 ,𝑛 2 , but not others, depending on whether the critical exponent 𝜈 is real or complex. The boundary between these two regions is described by an exceptional point in the renormalization group (RG) flow, leading to distinctive features in correlation functions and the phase diagram. Another contrast with the previous work is the number and stability of the NEFPs as well as the underlying topology of the RG flow. Lastly, we investigate an extreme form of nonreciprocity where one order parameter is independent of the other order parameter but not vice versa. Unlike the ℤ 2 × ℤ 2 model, which becomes nonperturbative in this case, we identify a distinct nonequilibrium universality class whose dependent field similarly violates fluctuation-dissipation relations but does not exhibit discrete scale invariance or underdamped oscillations near criticality.

Critical phenomena↗

Capturing Surface Coverage Effects in Heterogeneous Catalysis

Adsorbate–adsorbate lateral interactions at relevant surface coverages have a significant effect on chemical kinetics, thereby influencing the activity of a heterogeneous catalyst. Coverage-dependent kinetic and thermodynamic parameters therefore must be included in studies of such complex systems to properly predict the turnover frequencies and kinetic trends. Thus, it becomes extremely important to accurately capture the strength of lateral interactions between neighboring species under realistic reaction conditions. In this Perspective, we discuss the various existing computational and experimental methods for determining adspecies coverage and configurational effects. The choice of the tools and methods employed in such studies depends on factors such as time, length scales, computational cost, the presence of solvents, and reaction conditions. The applications of each method and the respective challenges are also discussed here. As a result, we discuss the recent developments and future of the state-of-the-art for inclusion of surface coverage and configuration into a holistic picture for accurate predictions of catalytic behavior.

09 BIOMASS FUELS↗

Orientation reversal and the Chern-Simons natural boundary

We show that the fundamental property of preservation of relations, underlying resurgent analysis, provides a new perspective on crossing a natural boundary, an important general problem in theoretical and mathematical physics. This reveals a deeper rigidity aspect of resurgence in a quantum field theory path integral. The physical context here is the non-perturbative completion of complex Chern-Simons theory that associates to a 3-manifold a collection of q-series invariants labeled by Spinc structures, for which crossing the natural boundary corresponds to orientation reversal of the 3-manifold. Our new resurgent perspective leads to a practical numerical algorithm that generates q-series which are dual to unary q-series composed of false theta functions. Until recently, these duals were only known in a limited number of cases, essentially based on Ramanujan’s mock theta functions, and the common belief was that the duals might not even exist in the general case. Resurgence analysis identifies as primary objects Mordell integrals: up to changes of variables, they are Laplace transforms of resurgent functions. Their unique Borel summed transseries decomposition on either side of the Stokes line is simply the unique decomposition into real and imaginary parts. In turn, the latter are combinations of unary q-series in terms of q and its modular counterpart $\overset{\sim }{q}$ , and are resurgent by construction. The Mordell integral is analytic across the natural boundary of the q and $\overset{\sim }{q}$ series, and uniqueness of a similar decomposition which preserves algebraic relations on the other side of the boundary defines the unique boundary crossing of the q series. We demonstrate that this continuation can be efficiently implemented numerically. In the cases where unique mock modular identities are known, they are found by this numerical procedure, but the procedure can go well beyond the known list of identities. A particularly interesting feature of the resurgent approach is that it reveals new aspects, and is very different from other known approaches based on indefinite theta series, Appell-Lerch sums, and representation theory of logarithmic vertex operator algebras.

Chern-Simons theories↗

A machine learning approach to quantify degradation of nuclear fuels and the effects of fission products

Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial radiation damage during fission. Traditionally, property evolution has been determined via empirical data collected following irradiation. However, these empirical correlations are limited in their applicability beyond the specific conditions in which they were obtained. This study explores a novel approach to address this challenge by applying materials informatics to develop a machine learning random forest (ML-RF) model that captures the effects of fission products on fuel compounds. The model predicts formation enthalpy (ΔH f ) by leveraging extensive quantum materials property data and correlating it with material descriptors such as composition, atomic and site features, and crystal lattice properties. This ML-RF model enables rapid interpolation across the compositional and structural spaces covered by the training data, thus supporting high-throughput screening and energetic ranking of candidate phases. The model demonstrates the ability to predict ΔH f with a mean absolute error (MAE) of approximately 0.1 to 0.2 eV/atom across a wide range of compounds, including key nuclear fuel systems (U-O, U-N, U-C, U-Si, and U-Mo). For example, it was used to assess shifts in stoichiometry for UO 2 (O/M) and UN (N/M) fuels, revealing their distinct tendencies in chemical potential variation and enabling preliminary convex hull analyses. Furthermore, the model provides insights into how individual fission products affect fuel properties. Results indicate that larger fission products (e.g., Nd, Pu, Ce) have a more pronounced impact on UO 2 , while lighter ones (e.g., Zr) strongly influence UN. Here, the model developed in this work can be used to support the Accelerated Fuel Qualification approach by facilitating preliminary evaluations prior to extensive materials modeling and experimentation. To this end, the trained model has been made available to the fuel community to support ongoing fuel development efforts.

Accelerated fuel qualification↗

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗

Mesoscale Modeling of Hydrogels Under Frictional Shear Stress

Hydrogels are three-dimensional networks of hydrophilic polymers often used as a simplified model of hydrated biological materials, from cartilaginous joints to the ocular tear film. However, the lubrication mechanisms of hydrogels remain poorly understood, partly due to their complex polymeric structure, which creates blurred interfaces during sliding that are challenging to study experimentally. In this study, we employ dissipative particle dynamics (DPD) to investigate the frictional behavior of a polymeric hydrogel network sliding against a solid wall in an explicit viscous solvent. This computational approach enables us to model hydrodynamic interactions and mesoscale polymer dynamics, capturing key aspects of hydrogel friction. Our simulations reveal that hydrogel friction is governed by the interplay between polymer relaxation and viscous shear, characterized by the Weissenberg number (Wi). At low Wi, friction coefficient remain nearly constant, dominated by polymer relaxation. However, at higher Wi, friction is dominated by viscous drag within a near-wall solvent layer, leading to a linear increase in friction coefficient with Wi. Furthermore, our results demonstrate an inverse relationship between the friction coefficient and the applied normal load, consistent with experimental observations. This work provides new insights into the fundamental tribological properties of hydrogels, shedding light on the micromechanics of hydrogel friction. Improving our understanding of hydrogel structure and dynamics under friction advances our knowledge of the mechanisms regulating biological lubrication in health and disease.

36 MATERIALS SCIENCE↗

Alkali Metal Control of Triplet-Mediated C–H Activation in Iron-Mediated Coupling of Dinitrogen and Benzene

Direct coupling of N 2 with abundant feedstocks like benzene to form N-containing organic compounds is a promising strategy for N 2 fixation pathways. The challenge of coupling N 2 activation and C–H bond oxidative addition was recently solved by introducing a reversible benzene C–H bond activation process mediated by a low-valent Fe(0) complex, which gave an organometallic product that could couple with partially reduced N 2 . Interestingly, the energetics of the C–H oxidative addition/reductive elimination step depends on the choice of alkali metal. However, the reason why the alkali metal influences the C–H bond activation remained elusive. In this work, we present a comprehensive study on this Fe(0)-mediated reversible C–H activation. Through density functional theory combined with high-level coupled cluster calculations, we discovered that the intermediate-spin triplet (S = 1) controls the energy of the transition state for C–H cleavage, while the high-spin quintet (S = 2) controls the position of the equilibrium. Na + drives the equilibrium toward oxidative addition due to an electrostatic effect, while K + and Rb + are dominated by a steric effect that favors the iron(0) species. The key role played by nonbonding interactions in the Fe-mediated C–H activation provides a conceptual model for alkali control over organometallic transformations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum limits of superconducting-photonic links and their extension to millimeter waves

Photonic addressing of superconducting circuits has been proposed to overcome wiring complexity and heat-load challenges. However, such superconducting-photonic links suffer from an efficiency-noise trade-off that limits scalability. This trade-off arises because increasing power conversion efficiency entails reducing optical power, which makes the converted signal susceptible to shot noise. We analyze this trade-off and find that the laser-driven qubit gate infidelity scales inversely with the number of photons used. While methods such as nonlinear detection or squeezed light could mitigate this effect, we consider generating higher-frequency electrical signals, such as millimeter waves (100 GHz), using laser light. At these higher frequencies, circuits have higher operating temperatures and cooling power budgets and alleviate constraints posed by the trade-off. Therefore, we demonstrate an optically driven cryogenic millimeter-wave source with a maximum power efficiency of 8 ×10 −5 that can generate a maximum of 0.7 μ⁢W of 80 GHz power, with a 1200-thermal-photon equivalent of added noise at 4K. Using this source, we perform frequency-domain spectroscopy of superconducting NbTiN resonators at 80–90 GHz. Our results show a promising approach to lessen the efficiency-noise constraints on superconducting-photonic links, while leveraging the benefits of photonic signal delivery. Further optimization of power efficiency and noise at high frequencies could make scalable photonic control of superconducting qubits viable at temperatures exceeding 1K.

Optoelectronics↗

Characterizing Ultrafast Intersystem Crossing Pathways in Molecular Pt Dimers Using Time-Resolved Wide-Angle X-ray Scattering

Vibronic coupling between transition metal charge transfer states is a potential mechanism for enhancing the intersystem crossing (ISC) rate. Vibronic coupling-driven ISC has been observed in Pt­(II) dimer complexes, where the trajectory across excited-state pathways is tuned by atomic displacements via Pt–Pt stretching vibrations. Time-resolved wide-angle X-ray scattering (TR-WAXS) was utilized to quantify the Pt–Pt contraction following metal–metal-to-ligand charge transfer (MMLCT) excitation in Pt dimers with different bridging ligands. Both complexes exhibit Pt–Pt bond formation with a decrease in Pt–Pt distance of ∼ 0.25 Å and coherent vibrational wavepackets (CVWPs) encoded in the Pt–Pt contraction of both dimers. However, the complexes exhibit different time-dependent evolution of their CVWPs. Analysis of interference patterns between different CVWPs is used to track the trajectory across the excited-state surfaces. Furthermore, this work demonstrates that the interference between CVWPs in ultrafast TR-WAXS encodes indirect information regarding electronic excited-states to reveal the Pt dimer bridge-dependent ISC mechanism.

Computational chemistry↗

First-Principles Simulation of Beam-Induced Processes Underlying Atomic Manipulation in Electron Microscopes

The development of experimental methods and apparatuses capable of promoting atomically precise material manipulations holds great promise for realizing the ultimate limit of feature miniaturization in materials and devices. The ability to modify materials atom by atom is anticipated to usher in new technologies in areas as diverse as separation science, medicine, and quantum information science. Historically, scanning probe-based techniques have been the most prominent approaches in this space. However, these methods are best suited for the manipulation of surface-exposed regions of materials, as the strong perturbations required for bond scission are delivered most effectively to atoms in the near-proximity to the scanning probe. In contrast, convergent electron beams with energies tuned slightly below the threshold for inducing irreversible knock-on damage have recently been employed (within scanning transmission electron microscopy) to promote atomic-scale bond rearrangements in various beam-stable solids. Currently, however, the efficiency and selectivity of beam-induced atomic manipulation processes with focused electron beams are such that long irradiation times are required to induce a desired atomic rearrangement. With a better understanding of the underlying physics dictating the outcome of a given irradiation event, methods can be devised to improve the efficiency of these techniques so that their promise can be fully realized through widespread adoption.To this end, this Account details our recent efforts to develop and apply tractable first-principles simulation approaches for studying the response of materials to electric beam-like external electric potentials applied in real space. We briefly review the concepts and capabilities in the area of atomically precise materials manipulation and review the early demonstrations of accomplishments in this area, focusing on studies using scanned convergent electron beam probes in particular. We expound upon the depth of the challenge and identify critical shortcomings of theoretical methods that have previously been employed in the simulation of beam-induced processes. We then describe the computational methods that we have generalized from the concepts and tools most commonly applied to the study of molecular photochemistry and how our adaptations of these methods can be employed to capture the relevant dynamical phenomena for beam-induced processes ranging from the initial electron scattering to the ensuing multistate reactions. Here, we contextualize these methods within the current state of the art in this area, which has historically focused primarily on the simulation of inelastic image formation in the electron microscope for the purpose of interpreting the results of quantitative electron microscopy experiments. We demonstrate that the spatial distribution of state-specific excitation rates due to the presence of an external (probe) electric charge is inhomogeneous, such that irradiation at particular locations in materials can favor specific electronic transitions (and disallow others). In addition to the potential for excited-state reaction pathways to be accessed through the initial inelastic scattering of the tightly focused electron beam from the targeted atoms, we also identify favorable conditions for the electronically nonadiabatic evolution of the highly vibrationally excited system to open complex multistate reaction pathways. Implications of the early results for understanding the mechanisms and potential routes to improved efficiency and selectivity in beam-induced reactions are discussed. We conclude with a summary of the current state of theory and modeling capabilities in this area and provide our perspective on future directions for theoretical and experimental developments that we view as crucial to advancing the use of convergent electron beams in mode-specific, atomically precise platforms for direct-write materials modifications.

36 MATERIALS SCIENCE↗

Identification of Solid-Electrolyte Interphase Species by Joint Characterization of Li-Ion Battery Chemistry by Mass Spectrometry and Electrochemical Reaction Networks

The formation and stability of the solid-electrolyte interphase (SEI) play central roles in determining the long-term performance and safety of modern electrochemical energy storage systems. Despite decades of research, the SEI’s heterogeneous, dynamic, and multiphase nature has defied comprehensive molecular-level characterization, creating a critical knowledge gap that limits rational battery design. In this work, we introduce a computational−experimental framework that integrates high-throughput quantum chemistry calculations, data-driven electrochemical reaction networks (eCRNs), stochastic algorithms, and laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (LDI-FTICR-MS) to unravel SEI formation in carbonatebased electrolytes without imposing predefined mechanisms. We constructed the most comprehensive eCRN to date, spanning over 10,000 species and 209 million reactions. Through stochastic network analysis, we successfully recovered 27 species that were previously reported in the literature and predicted 28 novel SEI species nearly doubling our scientific knowledge in this area. Each new species was rigorously confirmed through advanced mass spectral analysis of its distinct molecular and isotopic signatures. We kinetically refined the formation pathways for a select set of both previously reported and novel SEI products, revealing kinetically feasible elementary reaction mechanisms with activation barriers below 1 eV. This computational−experimental approach deepens our molecular-level understanding of SEI chemistry by resolving which species form and through which decomposition mechanisms they emerge. Such knowledge provides the foundation necessary to connect electrolyte composition to the resulting SEI components, a critical step toward a more informed electrolyte development in next-generation lithium-based batteries.

25 ENERGY STORAGE↗

Ambiguities in the partial-wave analysis of the photoproduction of pairs of pseudoscalar mesons

Applying the technique of partial-wave analysis, there are cases where more than one set of underlying complex-valued amplitudes can describe the measured observables. These ambiguities can sometimes be resolved using additional information, but assumptions are often required. It is known that the partial-wave analysis of two-pseudoscalar meson systems produced in photoproduction with a linearly polarized photon beam is free from discrete ambiguities stemming from the Barrelet zeros when the nucleon spin is ignored. In this article, we show that continuous ambiguities are possible for certain wave sets, even though the discrete ambiguities do not appear. We also explore ways to resolve these ambiguities and determine the maximal amount of information that can be obtained from analyses that suffer from these continuous ambiguities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High-Pressure Effects on an Octa-Hydrated Curium Complex: An Experimental and Theoretical Investigation

An octa-hydrated curium compound [Cm(H 2 O) 8 ](Hdtp)(dtp)·H 2 O (Cm1,H 2 dtp = 2,3-di(tetrazol-5-yl)pyrazine) along with its lanthanide analogues [Ln(H 2 O) 8 ](Hdtp)-(dtp)·H 2 O (Ln1, Ln 3+ = La 3+ –Nd 3+ , Sm 3+ –Lu 3+ ) were synthesized and characterized using single crystal X-ray diffraction and spectroscopic methods. Bond length analysis of VIII Cm(III)–OH 2 (where VIII refers to the coordination number) was compared to VIII Ln(III)–OH 2 (Ln 3+ = Nd 3+ and Sm 3+ ), indicating similar VIII M(III)–OH 2 bond lengths owing to the similar eight-coordinate ionic radii of these VIII M(III) cations. Owing to the reduced coordination number, the VIII Cm(III)–OH 2 bond lengths were shorter than previously reported IX Cm(III)–OH 2 bonds in [Cm(H 2 O) 9 ](CF 3 SO 3 ) 3 . The octa-aquo complexes were also characterized by solid-state UV–vis–NIR spectroscopy in addition to variable-temperature and variable-pressure photoluminescence. Variable-pressure absorption spectra of Cm1 were compared with Ln1 and show that the Cm(III) f → f transitions have a stronger dependence on pressure than that observed in Ln1 (Ln 3+ = Nd 3+ and Sm 3+ ). The experimental and computational analyses reveal that the monotonic decrease in the computed energy difference between the ground state and the first excited state corresponds to the observed red shift of the photoluminescence peak. This is accompanied by a gradual reduction in the average Cm(III)–OH 2 bond length and a delocalization of spin densities, alongside an intensified interaction involving the 5f orbitals under increasing pressure. Furthermore, these changes accommodate the new geometry and collectively modify the energy landscape, resulting in peak broadening and quenching.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pursuing Heteroleptic Ligand Design Principles for Photoactive Fe Complexes with Ultrafast X-ray Emission and Variable-Temperature Optical Spectroscopies

Understanding the key parameters that govern the photophysical and photochemical properties of transition metal complexes is essential for the development of efficient photosensitizers for photocatalytic applications. Achieving this objective necessitates clear and detailed investigations of their electronic excited states, for which time-resolved metal Kβ X-ray emission spectroscopy (XES) has proven highly effective. Here, we present a time-resolved Fe Kβ XES study of a heteroleptic Fe(II) polypyridyl carbene complex, [Fe(phen) 2 (C 4 H 10 N 4 )] 2+ (1; phen = 1,10-phenanthroline), utilizing both the valence-to-core and Kβ mainline spectral regions, complemented by variable-temperature transient optical absorption (VT-TA) spectroscopy. Detailed analysis of the time-resolved Kβ XES data, supported by density functional theory (DFT) calculations and an Eyring analysis of the VT-TA data, reveals parallel excited state relaxation dynamics that support an assignment of the long-lived excited state to a triplet metal-centered state. Placing these results in the context of prior studies of heteroleptic Fe(II) polypyridyl cyanide complexes motivated a series of DFT calculations to investigate the effects of ligand structural flexibility and arrangement. These calculations reinforce the experimentally derived conclusion that constraining structural flexibility with multidentate ligands significantly impacts the excited state relaxation dynamics. Furthermore, our study emphasizes that the arrangement of strong field ligands in heteroleptic complexes substantially affects the energy of Jahn–Teller active triplet metal-centered states in low-spin d 6 metal complexes. Together, these findings provide synthetic design principles for extending metal-to-ligand charge transfer excited state lifetimes of heteroleptic Fe complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗