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Prospects for detecting UF6 hydrolysis intermediates by mass spectrometry, resonance Raman, and NQR spectroscopy
Simulations are performed to consider several spectrometric and spectroscopic candidates for elucidating the mechanism of the hydrolysis of uranium hexafluoride (UF6). This study is among the first to benchmark the def-mTZVP basis sets for actinide-containing molecules, and it is shown to be a suitable basis set for surveying geometrical structures and vibrational spectra when used in conjunction with density functional theory. An experiment is proposed coupling mass spectrometric ion selection with vibrational spectroscopy, and supporting infrared and Raman spectral simulations demonstrate that ionization blue-shifts bands and can change their qualitative features. Ultraviolet resonance Raman is shown to have good prospects for discriminating U–O–U bridged intermediates, evidence for which was observed recently [L. E. McNamara et al., J. Phys. Chem. A 130, 775–786 (2026)]. As a more speculative approach, we also consider the prospect of addressing 233U or 235U nuclei by quadrupole resonance (NQR) spectroscopy for assigning early stage intermediate complexes. In doing so, we provide a first order-of-magnitude estimate for the collision-induced NQR signal for the UF6 dimer, which is of interest for the interpretation of a fast decoherence time observed in liquid-phase nuclear magnetic resonance. Having provided critical insights into the formation and stability of UF6 hydrolysis intermediates in previous studies, this computational spectroscopy survey is expected to help guide and expedite future laboratory campaigns.
Noise-aware machine learning accelerates development of wide-hysteresis NiTi-based shape memory alloys
NiTi-based shape memory alloys (SMAs) with wide thermal hysteresis show great potential in engineering applications such as pipe couplings. However, traditional trial-and-error methods are costly and time-consuming, hindering the development of wide-hysteresis alloys. Although machine learning enables efficient exploration of NiTi-SMA compositions, most studies overlook experimental noise. To address this, we propose a noise-aware Kriging model that achieves high predictive accuracy (R2 = 0.91, RMSE = 6.02) for rapidly screening alloys with wide hysteresis. Using this approach, we designed novel NiTiNbTa alloys tailored to specific processing and storage requirements. Among them, Ni49.5Ti44.5Nb4.5Ta1.5 and Ni49.5Ti44.5Nb5.5Ta0.5 can be directly processed after low-temperature storage, while Ni49Ti45.5Nb4Ta1.5 remains stable under ambient conditions. All three exhibit a thermal hysteresis over 70 K without post-processing and a shape memory recovery rate above 90% under 400–900 MPa stress. This work offers a valuable strategy for designing high-performance wide-hysteresis SMAs.
Spectral leakage and masking effects in the measurement of hyperuniformity
Disordered hyperuniformity is a recently discovered novel state of matter, characterized by a complete suppression of normalized infinite-wavelength density fluctuations as in perfect crystals and lack of conventional long-range order nor broken symmetry as in glasses. The detection of hyperuniformity relies critically on accurate characterization of the small-wavenumber behavior of the static structure factor of the system. In practice, however, measurements are performed on finite subsystems or through incomplete observations that effectively mask portions of the underlying configuration. Inspired by a recent numerical study [Liu et al., J. Chem. Phys. 164, 094102 (2026)], we develop a unified theoretical framework that quantifies how finite windows and spatially correlated binary masks modify the observed structure factor. We show that the measured structure factor Sobs(k) is the convolution of the intrinsic structure factor with the spectral density of the observation function, whether it is a compact window or an extended random mask. For generic hyperuniform systems with small-k scaling S(k) ∼ kα, finite observation window induces a universal quadratic leakage term at sufficiently small wavenumbers (i.e., k ≲ 1/L), leading to an apparent k2 scaling independent of the true exponent. The true hyperuniform exponent α can only be measured in the intermediate regime 1/L ≪ k ≪ qc. In stealthy hyperuniform systems, where the intrinsic structure factor possesses a spectral gap, all observed small-k power arises entirely from this convolution mechanism. For spatially correlated masks, we derive the corresponding convolution relation in terms of the mask spectral density and identify conditions under which hyperuniform signatures are suppressed, preserved, or distorted. Our results establish quantitative criteria for reliably extracting intrinsic scaling exponents and distinguishing genuine hyperuniform order from measurement-induced artifacts.
Review: Structural properties of binary metal nitrides
Thin films of binary metal nitrides with cubic or hexagonal crystal structures have a wide range of industrial applications. Their potential and that of their alloys range from metallic protective coatings for cutting tools and quantum wells in light-emitting devices to current-carrying channels in high-frequency and power transistors, as well as piezoelectric actuators and resonators in microelectromechanical and acoustic components. For the epitaxy of the required films and layer structures as well as for the design of metal nitride-based piezoelectric, electronic, and optoelectronic devices, precise knowledge of their structural properties is particularly important. It is, therefore, surprising that simulated and experimental data on lattice parameters, even for binary nitrides that have been studied for many years, differ too widely or are not sufficiently consistent for targeted design, e.g., for piezoelectric resonators with applications in future mobile communication systems. This review combines two complementary approaches to select and improve the accuracy and consistency of the physical data. First, based on a search of published data and supplementary simulations, two cubic (rock-salt and zinc-blende) and two hexagonal crystal structures (layered hexagonal and wurtzite) are described for each binary metal nitride, regardless of whether the respective crystal lattices are mechanically and thermodynamically stable under normal conditions. Second, all metal nitrides present in these crystal lattices, from the metal atomic number of 5 for BN to 81 for TlN, are comparatively examined. The systematic comparison of the structural properties of related cubic and hexagonal crystal structures of each binary metal nitride, combined with comparing different metal nitrides with each other by varying the atomic number of the metal atom over a wide range, reveals a clear dependence of the lattice parameters, bond lengths, nearest neighbor metal–metal distances, average volumes required per atom, and mass densities on the electron configuration of the metal atoms. In particular, the systematic changes in the structural properties of binary metal nitrides, whose metal atoms belong to the same period or group in the periodic table of elements, are presented here and are used to determine improved data sets of structural parameters.
Pause and change point detection in single-molecule motor trajectories by BIC-based model selection
Detecting pause events in single-molecule trajectories is essential for extracting kinetic information but remains challenging in noisy measurements. Here, we present a pause-detection method based on model selection using the Bayesian Information Criterion. The approach operates directly on raw trajectories, requires no preprocessing, and does not rely on user-defined parameter tuning. We provide a rigorous analysis of detection sensitivity that quantifies the probability of missing events under given experimental conditions, and the method naturally accommodates missing data in trajectories. Benchmarking shows that the approach outperforms commonly used pause-detection and change-point-detection strategies across simulated and experimental datasets. The method provides a robust and general framework for pause and change-point detection in single-molecule trajectories and is broadly applicable to single-molecule measurements obtained with magnetic tweezers, optical tweezers, and single-particle tracking.
Stable low-resistance ohmic contact on GaN via an oxynitride interlayer over 20–200 °C: Mechanisms and performance
Achieving reliable, low-resistance ohmic contacts in GaN-based devices is fundamentally limited by interfaces with high interface-state densities, which are a direct result of essential fabrication steps. For example, etching to expose the n-GaN layer in laser diodes introduces surface defects, while regrown n+-GaN surfaces in selective-area regrowth (SAG) HEMTs exhibit high interface states due to growth kinetics. These high-frequency and high-power devices typically operate at elevated junction temperatures (100–200 °C), where high interface-state density exacerbates Fermi-level pinning (FLP) effect, leading to unstable contact resistance and reliability concerns. To address this issue, we propose and validate a universal interface engineering strategy: inserting an oxynitride interlayer. We systematically study Ti-based ohmic contacts on SAG n+-GaN from 20 to 200 °C, comparing untreated interfaces with those modified by TiOxNy or GaOxNy interlayers. Through correlated microstructural analysis, temperature-dependent electrical measurements, and conductance-based interface-state characterization, we show that the interlayers effectively suppress interface-state density, mitigate FLP, and stabilize the Schottky barrier height. While untreated contacts display non-monotonic and degrading resistivity with temperature, interlayer-modified contacts exhibit a stable, monotonic decrease in specific contact resistivity. The GaOxNy interlayer yields the best performance, achieving ∼10−8 Ω cm2 order above 100 °C. This work elucidates the critical role of interface states in contact thermal instability and provides a viable materials solution for stable ohmic contacts in GaN-based devices that operate at high temperatures with damaged or low-quality contact interface.
Quantum dynamics of photoexcited charge transfer in bridge-mediated porphyrin–naphthalenetetracarboxylic dianhydride donor–acceptor system
Photoinduced charge transfer (CT) in donor–bridge–acceptor (D-B-A) systems is governed by the interplay between electronic coupling and vibronic interactions. Here, we investigated ultrafast CT dynamics in Zn-porphyrin–NTCDA complexes connected through either an extended 1,4-diethynylphenylene (DEP) bridge or an ethynyl linker. The excited-state dynamics are described using a linear vibronic coupling Hamiltonian combined with quantum dynamical wavepacket propagation, thereby allowing explicit treatment of multidimensional nuclear motions. Electronic-structure analysis shows that the conjugated DEP bridge provides stronger donor–acceptor communication and more favorable energetic alignment between locally excited and CT states. As a result, population transfer to the CT configuration occurs on an ultrafast timescale of ∼9 fs. In contrast, modifying the bridge reduces π-conjugation and electronic interaction, leading to slower CT dynamics of ∼25 fs. Systematic inclusion of increasing numbers of vibrational modes reveals that cooperative multimode coupling enhances vibronic dephasing, stabilizes the charge-separated population, and suppresses coherent recurrences in the electronic dynamics. The simulations, therefore, identify bridge-mediated conjugation and multidimensional vibronic interactions as key factors governing charge-separation efficiency in these architectures. These findings provide molecular-level insights into how bridge structure and vibrational motions cooperatively regulate CT dynamics in D-B-A systems.
Front-end bandwidth and observability limits in confined electronic systems
The progressive miniaturization of solid-state electronic systems drives device operation toward regimes characterized by increasingly rapid electronic dynamics, particularly in reduced-dimensional structures subject to quantum confinement. In this regime, the central issue is not only the intrinsic speed of electronic processes, but also the extent to which their temporal structure remains experimentally accessible through conventional readout chains. This work develops a phenomenological framework for the mismatch between intrinsic confined-state dynamics and the finite temporal resolution of the measurement front-end. The physical ingredients involved—quantum confinement, finite bandwidth, and detector-mediated filtering—are individually well established; the contribution here is to combine them into an explicit observability-based description with operational regime descriptors. To this end, we introduce a dimensionless observability parameter that identifies the crossover between observable and observability-limited regimes, together with an observability transfer efficiency that quantifies the fraction of intrinsic dynamical content preserved by the readout chain. A minimal analytical model shows that the same control parameter governs retained spectral content, signal attenuation, and peak delay, thereby linking spectral filtering to measurable time-domain distortions. Within this formulation, the measurable electrical response is treated as a property of the coupled system formed by the electronic states and the front-end, rather than of the confined system in isolation. The resulting framework provides a compact basis for analyzing observability limits in nanometric electronic systems and for identifying experimentally testable crossover behavior when intrinsic and instrumental timescales become comparable.
Nonequilibrium vibrational distribution and kinetics of OH chemiluminescence in the hydrogen–oxygen reaction
This paper describes a spectroscopic approach for studying the kinetics of the reaction H + O + M → OH(A2Σ+) + M (R1). Vibrational distributions of OH(A) produced during high-temperature reactions of H2/O2 mixtures diluted with Ar have been measured by observing the emission spectra of the OH A2Σ+–X2Π transition. The experiments were performed behind reflected shock waves at temperatures of 1600–2200 K and pressures of 1.4–5.2 bar in a high-repetition-rate shock tube. The observed emissions are attributed to the chemiluminescence of OH(A) formed in (R1). The recorded spectra were fitted with the simulated ones to determine the vibrational distributions of OH(A) for vibrational levels of υ = 0–4. The distributions were significantly nonthermal due to competition between vibrational energy transfer and other involved processes. Then, in order to model the kinetics of (R1), a master equation for the vibrational states of OH(A) is constructed based on the obtained vibrational distributions, as well as available data on predissociation, collisional quenching, spontaneous emission, and vibrational energy transfer of OH(A). The rate constants for (R1) predicted for certain mixtures are found to be fairly consistent with those reported previously based on OH(A) concentration measurements. Meanwhile, substantially smaller rate constants are predicted for highly diluted mixtures. This result is supported by the variation seen in the relative emission rates observed for different mixtures. It is suggested that the rate constant for (R1) depends significantly on third-body molecules due to the dependency of the vibrational energy transfer rate on collision partners.
Machine-learning-assisted multi-objective optimization of thermal conductivity, thermal expansion coefficient, and fracture toughness in rare-earth zirconate ceramics
Although rare-earth zirconates (RE2Zr2O7) are promising top-coat candidates for thermal barrier coatings, their thermal conductivity (TC) still requires further reduction, and their limited thermal expansion coefficient (TEC) and fracture toughness (KIC) restrict further performance improvement. However, trial-and-error experiments and first-principles calculations are not well suited for rapid screening of the large RE2Zr2O7 compositional space, while empirical models usually have limited transferability to complex multi-component systems. To address these challenges, this study develops an interpretable machine learning (ML) framework that integrates multi-property prediction, feature interpretation, and multi-objective composition optimization for RE2Zr2O7 ceramics. Experimental data sets are selected from the literature and handbooks, including 1167, 660, and 309 samples for TC, TEC, and KIC, respectively. Composition-derived features related to atomic mass, configurational entropy, electronegativity, ionic radius, and ionic volume are generated, and a four-step feature selection strategy is applied to obtain compact feature subsets. Multiple ML algorithms are evaluated, and random forest is found to provide the best performance for TC, while extra trees perform best for TEC and KIC. The selected models show strong agreement between predicted and experimental values on both test sets and independent compositions. SHapley Additive exPlanations are further employed to interpret the role of temperature, mass disorder, electronegativity dispersion, and ionic-radius mismatch in governing the predictions. Finally, the trained ML predictors are integrated with non-dominated sorting genetic algorithm II to perform multi-objective optimization in the (Gd–Yb–Sc)2Zr2O7 compositional system, enabling the identification of composition regions with coordinated thermophysical and mechanical performance.
Nitrogen-driven ferromagnetism and perpendicular magnetic anisotropy in two-dimensional transition-metal nitrides
Data-centric technologies demand energy-efficient, densely integrable spintronic building blocks, motivating the search for two-dimensional (2D) ferromagnets combining room-temperature Curie temperatures (TC) and perpendicular magnetic anisotropy (PMA). Compared with halides and chalcogenides, transition-metal nitrides (TMN2) feature short metal–nitrogen bonds and strong p-d hybridization, which can substantially reshape crystal-field splitting and magnetic exchange pathways. Through systematic first-principles screening of hexagonal h-TMN2 (TM = 3,4,5d) monolayers, we identify h-VN2 and h-CrN2 as the only stable candidates exhibiting intrinsic PMA and half-metallicity with sizable spin-flip gaps (Δsf = 0.27 eV for h-VN2 and 0.25 eV for h-CrN2). Phonon spectra and ab initio molecular dynamics simulations confirm their dynamical and thermal stability, with h-VN2 preserving crystalline integrity up to 800 K. Monte Carlo simulations confirm out-of-plane easy axes with TC values of ≈305 K for h-VN2 and ≈134 K for h-CrN2. Notably, h-VN2 exhibits pronounced magnetoelectric tunability: its half-metallicity and PMA are robustly preserved within a broad biaxial strain window (−2%–+3%), maintaining near-room-temperature TC. In bilayer configurations, vertical stacking further strengthens exchange interactions, enhancing TC to ∼477 K. Furthermore, h-VN2 sustains its ferromagnetism and PMA at both graphene and MoS2 interfaces, underscoring its compatibility with existing 2D platforms. These results highlight h-VN2 as a versatile platform where nitrogen-mediated exchange facilitates robust, high-temperature ferromagnetism for next-generation van der Waals spintronics.
Electronic and optical bandgaps of WO3 and WO3−x: Adsorbed water-induced Burstein–Moss shift
The reported bandgap of stoichiometric WO3 spans a range of 2.6–3.4 eV. The present study evaluated the underlying reason for this wide variation using multiple spectroscopic techniques that preferentially probe the surface, near-surface, or bulk region of WO3 and WO3−x. The results show that the bulk electronic bandgap of WO3 is ∼2.2 eV, which is much lower than the value of 2.7–2.8 eV measured through optical, photoelectrochemical, and photoemission probes that are more surface sensitive. The difference between the electronic and optical bandgap is likely due to the presence of a surface e− accumulation layer on the stoichiometric WO3 due to doping by adsorbed water. In contrast, the presence of oxygen vacancy defects in the bulk lattice of WO3−x causes degenerate bulk doping, a Burstein–Moss shift of Fermi energy to higher electron energies within the CB. However, exposure of WO3−x to ambient humid O2 causes surface oxidation and the formation of an e− depletion layer on the surface. This study highlights the important role of ambient O2 and water in modulating the carrier concentration and electron affinity of semiconductors.
Virial stress in systems of active Brownian particles in the presence of translational and rotational inertia
We elucidate the stress in a system of active Brownian particles augmented with translational and rotational inertia (ABP+TRI). Stress tensors are derived for periodic systems as well as systems confined between walls by employing Lagrange’s equations of motion of the first kind for the rotational motion. Using Langevin simulations of an ideal active gas in two dimensions, we confirm the existence of an equation of state for periodic systems that depends on translational and rotational inertia in general. Confinement implies a strong polarization of the propulsion direction near a wall and an enhanced density, both of which increase with increasing rotational inertia. This affects the local stress tensor normal to the confining walls, leading to a breakdown of the equation of state. Yet the local stress in the bulk part of the confined systems is identical with that of the periodic system. Importantly, for both kinds of boundary conditions, the so-called swim stress is not included in the local stress tensor; therefore, in general, the swim stress is not representative of the stress in systems of ABP+TRIs.
Ferromagnetic resonances in thin films—Electrodynamic analysis and experiments employing multimode rectangular cavity and broadband coplanar waveguide techniques
Rigorous electrodynamic analysis of resonances in rectangular TMn,m,0z mode resonators containing a thin in-plane magnetized ferromagnetic film is presented. Apart from the resonance frequencies and Q-factors, the electromagnetic field distribution is analyzed showing the appearance of a giant microwave magnetic field component perpendicular to the sample at the resonance frequencies of both the dominant and higher order modes. This confirms the plasmonic-like behavior of resonances in thin ferromagnetic films, where the term is used in the electrodynamic sense of subwavelength resonances. The conductivity of metallic ferromagnetic films is accounted for in computations. Resonance curve broadening due to conductivity is predicted for larger conductivities and/or for thicker samples. Results of rigorous computations are compared with the perturbation theory. A rectangular TMn,m,0z mode cavity is used for measurements of the saturation magnetization and Gilbert damping factor of thin CoFeB films at several frequencies in the range 4–12 GHz showing agreement with the broadband coplanar waveguide technique. The Gilbert damping factor of a single-crystal yttrium iron garnet film grown on a GGG substrate and an amorphous CoFeB thin film were determined from measurements of their Q-factors, employing a vector network analyzer, and considering the sample as a magnetic plasmon-like resonator coupled to the coplanar line.
Molecular dynamics study of ice melting on a silver plate
Ice fall incidents, such as detached ice chunks from bridge stay cables, pose not only serious safety hazards to pedestrians and vehicles below but also significant serviceability issues, as bridge closures required for inspection or ice removal can lead to costly disruptions. The current trend of climate change exacerbates this kind of hazard. The availability of a reliable engineering tool, such as an accurate numerical model grounded in nanoscale melt-front physics, is imperative to provide a clear insight into the ice detachment mechanism and develop effective de-icing solutions. Classical molecular dynamics simulations are conducted in the current study to investigate the melting of an ice cube in an atomically flat silver slab. The TIP4P/ice water model is adopted and the simulation is conducted in canonical ensemble with a layer-resolved Langevin thermostat. The phase evolution is tracked via the averaged tetrahedral order parameter, while systematically varying five controls: the depth of heated layers, the silver substrate thickness, the ice thickness, the lateral confinement, and the ice crystal contact orientation (basal vs prism). Results show that melting is controlled primarily by the substrate temperature; variations in heat-conducting-layer count had a minor influence and converged to similar end states. Doubling the ice thickness increases the melt time approximately by three times, whereas relaxing periodic boundaries reshapes the melt into domes or spreading films. Presenting the basal plane instead of a prism plane accelerates loss of crystalline order. Collectively, the simulations yield a numerically consistent set of parameters that not only advances the existing knowledge of nanoscale ice melting simulation but can also be transferred to continuum-scale de-icing simulations, enabling accurate modeling of melt-induced ice detachment from structural components, such as bridge stay cables.
Current sheet formation in planar inductive pulsed plasma thrusters
Formation of a well-defined, magnetically impermeable current sheet is central to the operation of pulsed plasma thrusters. Existing scaling laws for inductive pulsed plasma thrusters, however, are primarily derived from models that either overlook or greatly simplify the current sheet formation process. Data obtained from a compact, low discharge energy planar inductive pulsed plasma thruster were used to gain insight into the fundamental physics governing current sheet formation in these devices. It was found that the maximum inductive coupling and current density in the sheet scaled with the logarithm of the ratio of the resistive diffusion to ionization timescales. The ratio of these timescales was shown to describe the combined role of diffusion and ionization in influencing the electron population within the current sheet. When the ionization timescale was fast relative to the diffusive timescale, the thruster discharge was found to be much more effective at concentrating current in the sheet. A connection between the strength of the current sheet and the thruster design and operational parameters is derived and used to identify the parameter space over which efficient thruster operation is possible.
Interplay between electronic and phononic energy dissipation channels in the adsorption of CO on Cu(110)
In this work, we investigate the relative importance of electronic and phononic energy dissipation during the molecular adsorption of CO on Cu(110). Initial sticking probabilities as a function of impact energy for CO impinging at normal incidence at a surface temperature of 90 K were computed using classical trajectory simulations. To this aim, we use a full-dimensional potential energy surface constructed using an atomistic neural network trained on density functional theory data obtained with the nonlocal vdW-DF2 exchange–correlation functional. Two models are compared: one allowing only energy transfer and dissipation from the molecule to lattice vibrations, and the other also incorporating the effect of molecular energy loss due to the excitation of electron–hole pairs, modeled within the local-density friction approximation. Our results reveal, first, that the molecule mainly transfers energy to lattice vibrations, and this channel determines the adsorption probabilities, with electronic friction playing a minor role. Second, once the molecule is trapped near the surface (where electronic density is higher), electron–hole pair excitations accelerate energy dissipation, significantly promoting CO thermalization. Still, the faster energy dissipation when electron–hole pair excitations are accounted for accelerates the accommodation of the adsorbed molecules in the chemisorption well but does not significantly alter their lateral displacements over the surface.
Dynamic charges effect on infrared dielectric response of polar materials
Predictive modeling of the infrared dielectric function in polar materials is crucial for thermal management and infrared devices design. While the Green–Kubo molecular dynamics (MD) framework provides a nonperturbative route to compute dielectric responses from dipole fluctuations, yet it commonly relies on the fixed-charge approximation that neglects dynamic charge redistribution during atomic motion. Here, we employ a machine-learning neuroevolution potential with dynamic charges combined with Green–Kubo MD to investigate the dynamic charge effect on the infrared dielectric response of rutile TiO2, a material with large Born effective charges. Our results show that dynamic charge effects become increasingly important at elevated temperatures and are essential for accurately predicting longitudinal optical phonon features and infrared reflectance. This work establishes that accurate prediction of infrared optical properties in polar materials under thermal excitation requires explicit treatment of dynamic charge evolution.
Population transfer in quantum <i>β</i> -Fermi–Pasta–Ulam–Tsingou chains with fixed ends
We perform a series of numerically accurate tensor-train (TT) simulations of population dynamics and energy transfer in quantum β-Fermi–Pasta–Ulam–Tsingou (FPUT) chains comprising 10 to 30 nonlinear oscillators. The dynamics are propagated over timescales ranging from 18 to 60 fundamental vibrational periods. We demonstrate that the chain anharmonicity opens new energy-transfer channels, accelerates initial ballistic energy propagation, reduces (partial) recurrence periods relative to the harmonic limit, and regularizes oscillatory wavepacket motion. This work serves as the first proof-of-principle demonstration of the high efficiency of TT methods for simulating quantum FPUT dynamics.
Controlling the spin-wave nonreciprocity of a crescent-shaped nanowire via curvature and magnetic field
Recent studies on spin-wave propagation in ferromagnetic waveguides have highlighted the role of nonreciprocity resulting from the chiral nature of dipolar interactions in curved elements. However, the impact of spin-wave mode type on nonreciprocity remains unexplored. Using micromagnetic simulations supported by analytical modeling, we systematically analyzed the propagation of edge, fundamental, and width-quantized spin-wave modes in a ferromagnetic nanowire with a crescent-shaped cross section. Our results show that the strength and sign of nonreciprocity depend on the mode type, as well as on the curvature magnitude of the nanowire’s top and bottom surfaces and the strength of the external magnetic field. Interestingly, changing the mode type, for instance, induced by altering the curvature or magnetic field, results in a significant change in the dispersion relation asymmetry. This effect underscores the important role of spin-wave profiles in nonreciprocity, deepens our fundamental understanding of spin-wave dynamics in curved geometries, and paves the way for designing magnonic waveguides with tailored properties.