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At least 721 records · Page 40

Chemically and Mechanically Recyclable Vitrimers from Carbon Dioxide-Based Polycarbonates

Designing thermoset materials with dynamic crosslinks is an important strategy to mitigate rising global carbon dioxide emission levels. The development of polymers from sustainable feedstocks, with efficient manufacturing methods, for high-value applications, and with circular end-of-use solutions is essential for advancing material technologies. One approach involves exploiting carbon dioxide itself as feedstock to create high performance, sustainable materials, by enchaining 50 mol% CO2 via copolymerization with epoxides to yield polycarbonates. This work describes the synthesis, end-functionalization, and curing of poly(propylene carbonate) (PPC) and poly(cyclohexene carbonate) (PCHC) into beta-hydroxy ester vitrimers. These vitrimers demonstrate the ability to be mechanically reprocessed up to 3 times with retention of the material’s properties through dynamic transesterification exchange reactions. The polycarbonate vitrimers with gel fractions exceeding 90 % exhibit high tensile strength (> 50 MPa) and Young’s modulus (> 2 GPa), achieved by varying repeat unit structure in the polymer backbone from the low Tg PPC to the more rigid high Tg PCHC structures. Owing to an entropically favorable chain back-biting mechanism, the network chains can be cleaved and depolymerized into cyclic small molecules. In the case of PCHC, this process enables repolymerization back to polycarbonates with 69 wt.% CO2 retention through life-cycles. The promising mechanical performance and recyclability of these CO2-based polycarbonate vitrimers indicate their potential for sustainable, high-performance materials, paving the way for future innovations in circular polymer technologies and carbon capture utilization.

36 MATERIALS SCIENCE↗

The nature of the chemical bond and the role of non-dynamical and dynamical correlation in Be2

In the spin-coupled generalized valence bond (SCGVB) description of Be2, there is a pair of electrons in highly overlapping “inner” orbitals corresponding to a traditional σ bond, but this bond is compromised by Pauli repulsion arising from its overlap with a second “outer” pair. The presence of this outer pair of electrons leads to a repulsive potential energy curve at long range and a bound, but metastable molecule at short range. To obtain further insights into the nature of the bond in Be2, we determined the non-dynamical and dynamical correlation contributions to the potential energy curve of Be2 using four different choices for the zero-order wave function: Restricted Hartree–Fock (RHF), SCGVB, valence-CASSCF(4,4), and valence-CASSCF(4,8). The SCGVB and valence-CASSCF(4,4) wave functions yield similar breakdowns of the total correlation energy, with non-dynamical correlation being the more important contribution. For the RHF and valence-CASSCF(4,8) wave functions, dynamical correlation is critical, without which the potential energy curve is purely repulsive. High accuracy calculations on the HBen−1Be–BeBen−1H molecule as a function of n (n = 1–6) suggest that the intrinsic strength of a Be–Be σ bond uncompromised by Pauli repulsion is on the order of 62–63 kcal/mol, and its length is 2.13–2.14 Å, ∼60 kcal/mol stronger and ∼0.35 Å shorter than in Be2.

Xu, Lu. T. (ORCID:0000000182064902)↗

Real-Time Wave Energy Converter Control Using Instantaneous Frequency

Wave Energy Converters (WECs) rely on effective Power Take-Off (PTO) control strategies to maximize energy absorption under dynamic sea conditions. Traditional hydrodynamic modeling techniques may require computationally intensive convolution calculations, making real-time control implementation challenging. This paper presents an alternative approach by leveraging instantaneous frequency estimation to dynamically adjust PTO damping in response to varying wave frequencies. Two real-time frequency estimation methods are explored: the Hilbert Transform (HT) and Phase-Locked Loop (PLL). The Hilbert Transform method provides accurate frequency tracking but introduces a delayed response due to its dependence on causal data. Conversely, the PLL approach demonstrates strong potential in frequency tracking but requires careful gain tuning, particularly in complex sea states. Comparative evaluations across multiple test cases—including sinusoidal variations, amplitude steps, frequency step changes, and real-world JONSWAP spectrum waves—highlight the strengths and limitations of each method. The two different PTO control techniques across the various frequency estimation methods were tested under real-sea states using a state-space model of a point-absorbing Wave Energy Converter. The Capture Width Ratio (CWR) is used as a performance metric, with results showing that the HT achieves a 10.6% improvement, while the PLL estimation yields a 0.9% improvement relative to the fixed parameter control baseline. These results highlight the effectiveness of real-time frequency estimation in improving energy absorption compared to static control parameters.

WEC control↗

Artificial Intelligence for Event Reconstruction and Higgs Physics at CMS and Future Colliders

This dissertation charts a trajectory in which advances in artificial intelligence (AI) play a central role in pushing the high-energy physics frontier, complementing progress driven by higher collision energies and larger colliders. The discovery potential of the LHC and future colliders relies on accurate reconstruction of increasingly complex particle collision events. In the CMS experiment, this task is performed by the particle-flow (PF) algorithm. This dissertation presents the first implementation of a machine-learning-based particle-flow (MLPF) reconstruction in the CMS detector based on transformer architectures. In simulated top quark--antiquark pair (ttbar) events under LHC Run~3 (2023--2024) conditions, MLPF improves jet energy resolution by 10--20\% compared to standard PF for jets with transverse momentum between 30--100\GeV. Runtime performance is evaluated using simulated multijet events, with a median inference time of 20\unit{ms} per event on an NVIDIA L4 GPU, compa red to approximately 110\unit{ms} for standard PF. The MLPF algorithm is also validated on Run~3 collision data, representing the first data-validated ML-based reconstruction pipeline at any LHC experiment. We then extend MLPF toward future electron--positron colliders and introduce the first full-simulation cross-detector transfer learning workflow for PF reconstruction. The model is pre-trained on simulated events from the Compact Linear Collider detector (CLICdet) and fine-tuned on the CLIC-like detector (CLD) proposed for the Future Circular Collider (FCC). This approach achieves up to a 40\% improvement in jet energy resolution over rule-based reconstruction while reducing the required training dataset size by an order of magnitude, demonstrating the potential of AI to accelerate detector development and optimization. This dissertation also demonstrates how modern AI techniques enhance the sensitivity of LHC physics analyses. A CMS search for highly Lorentz-boosted Higgs bosons decaying to \textrm{W} boson pairs is presented, focusing on the single-lepton final state. A dedicated fine-tuning strategy for \ParT yields an approximately 70\% increase in expected sensitivity relative to the baseline model. The analysis uses proton--proton collision data at a center-of-mass energy of \ensuremath{\sqrt{s}=13\TeV} collected by CMS between 2016 and 2018, corresponding to an integrated luminosity of 138\ensuremath{\ \mathrm{fb}^{-1}}. The expected significance of the search is $1.86\sigma$, with an observed signal strength of $-0.19^{+0.48}_{-0.46}$. Finally, explainable AI techniques are applied to the MLPF and \ParticleNet algorithms using layerwise relevance propagation, showing that both models base their predictions on physically meaningful features consistent with our physics intuition. Together, these results demonstrate how advanced AI methods can enhance reconstruction, analysis sensitivity, and interpretability, shaping the next era of experimental parti cle physics.

Mokhtar, Farouk [UC, San Diego]↗

Anisotropic strength behavior of single-crystal TATB

High-rate strength behavior plays an important role in the shock initiation of high explosives, with plastic deformation serving to localize heat into hot spots and as a mechanochemical means to enhance reactivity. Recent simulations predict that detonation-like shocks produce highly reactive nanoscale shear bands in the layered crystalline explosive TATB (1,3,5-triamino-2,4,6-trinitrobenzene), but the thresholds leading to this response are poorly understood. We utilize molecular dynamics to simulate the high-rate compressive stress–strain response of TATB, with a focus on understanding flow behavior. Here, the dependence of strength on pressure and loading axis (crystal orientation) is explored. The deformation mechanisms fall broadly into two categories, with compression along crystal layers activating a buckling/twinning mode and compression normal to the layers producing nanoscale shear bands. Despite the complexity of the underlying mechanisms, the crystal exhibits relatively straightforward stress–strain curves. Most of the crystal orientations studied show rapid strain softening following the onset of yielding, which settles to a steady flow state. Trajectories are analyzed using five metrics for local states and structural order, but most of these metrics yield similar distributions for these deformation mechanisms. On the other hand, a recently proposed measure of intramolecular strain energy is found to most cleanly distinguish between these mechanisms, while also providing a plausible connection with mechanochemically accelerated decomposition kinetics. Localization of intramolecular strain energy is found to depend strongly on crystal orientation and pressure.

36 MATERIALS SCIENCE↗

Approach to Evaluating Reorganization Energies of Interfacial Electrochemical Reactions

Reaction rate coefficients for electron-transfer processes at the electrode–electrolyte interface are commonly estimated by using the Butler–Volmer equation, but their values are inaccurate beyond a few tenths of volts of overpotential. The Marcus–Hush–Chidsey (MHC) formalism yields correct asymptotic behavior of the rate coefficients vs applied overpotential but has complex dependencies on the redox system’s intrinsic parameters, which can be difficult to model or measure. In this work, we bridge the two kinetics formalisms to estimate the reorganization energy, one of the important parameters for the MHC formalism, and investigate its dependence on other intrinsic parameters such as activation barriers, electronic coupling strength, and the density of states of the electrode surface. We examine the sensitivity of the reorganization energy to these parameters, establish some general relationships for accurately predicting rate coefficients using the MHC formalism over a wide range of applied overpotentials, and compare this approach to calculating MHC rate constants with other empirical approaches for the mechanisms of CO 2 reduction on different metal electrode surfaces.

Butler−Volmer↗

Detailed report on the measurement of the positive muon anomalous magnetic moment to 0.20 ppm

We present details on a new measurement of the muon magnetic anomaly, a μ =(g μ −2)/2. The result is based on positive muon data taken at Fermilab’s Muon Campus during the 2019 and 2020 accelerator runs. The measurement uses 3.1 GeV/c polarized muons stored in a 7.1-m-radius storage ring with a 1.45 T uniform magnetic field. The value of a μ is determined from the measured difference between the muon spin precession frequency and its cyclotron frequency. This difference is normalized to the strength of the magnetic field, measured using nuclear magnetic resonance. The ratio is then corrected for small contributions from beam motion, beam dispersion, and transient magnetic fields. We measure a μ =116592057(25)×10 −11 (0.21 ppm). This is the world’s most precise measurement of this quantity and represents a factor of 2.2 improvement over our previous result based on the 2018 dataset. In combination, the two datasets yield a μ (FNAL)=116592055(24)×10 −11 (0.20 ppm). Combining this with the measurements from Brookhaven National Laboratory for both positive and negative muons, the new world average is a μ (exp)=116592059(22)×10 −11 (0.19 ppm).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Combinatorial library design for improving isobutanol production in Saccharomyces cerevisiae

Saccharomyces cerevisiae is the dominant fermentative producer of ethanol in industry and a preferred host for production of other biofuels. That said, rewiring the metabolism of S. cerevisiae to produce other fermentation products, such as isobutanol, remains an academic challenge. Many studies report aerobic production of isobutanol, but ethanol remains a substantial by-product under these conditions due to the Crabtree effect. These studies indicate that the native isobutanol pathway is incapable of carrying sufficient flux to displace ethanol. In this report, we screened a combinatorial library of pathway enzymes to identify an isobutanol pathway cassette capable of supporting the growth of a non-ethanol producing S. cerevisiae . We began by identifying a diverse set of isobutanol pathway enzyme homologs and combined each open reading frame with varied-strength promoters in a combinatorial, pooled fashion. We applied a growth-coupled screen where a functional isobutanol pathway restored NAD + regeneration during glucose catabolism that is otherwise repressed via the Crabtree effect. Using this screen, we isolated a cassette consisting of a mosaic of bacterial and cytosol-localized fungal enzymes that conferred under aerobic conditions the ability to produce 364 mg/L isobutanol (8.8% of the theoretical maximum yield). We next shifted the cofactor usage of the isolated ketol-acid reductoisomerase enzyme in the cassette from NADPH to NADH-preferring to improve redox balance. The approach used herein isolated isobutanol producing strains that approach the best in the literature without producing substantial ethanol titers. Still, the best isolated cassette was insufficient to support anaerobic growth in the absence of ethanol fermentation - indicating the presence of further fundamental gaps in our understanding of yeast fermentation.

59 BASIC BIOLOGICAL SCIENCES↗

Status, Challenges, and Plans for Consistent Modeling and Evaluation of Fission Data: Nubar, PFNS, and FPY [Slides]

This presentation discusses the importance of consistent evaluations for fission observables. Currently, prompt fission quantities (e.g., neutron multiplicity, neutron energy spectrum, and fission product yields) are evaluated independently of one another, either with separate models or data-only/non-model evaluations (few – if any – shared model inputs) and inconsistencies can arise in evaluated data (e.g. NSE 190, 258 (2018)). They have found that consistent, model-based evaluations lead to more physical constraints on free parameters in the model, more robust predictions for other observables and other isotopes, that there are correlations between the uncertainties on different observables, and that uncertainties can be propagated to unmeasured quantities. They are working on developing models to the point where fission observables are calculated at the quality needed for an evaluation. They are striving to consistently calculate fission observables, such as $\bar{v}$, PFNS, and FPY, to a quality suitable for an evaluation. Current evaluations for fission observables use separate models for each observable (with minimal shared input) or are purely data driven. LANL models, such as the Monte Carlo CGMF and deterministic BeoH, have different strengths; the similar fission fragment initial conditions and decay models leads to consistency between the two codes (FPY can be connected to $\bar{v}$ and PFNS, even when calculated by different codes). Work is underway by Lovell to optimize the models and Neudecker is working to perform detailed uncertainty quantification. The PFNS, in particular, presents a significant challenge.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Constraining the $\overline{K}$N coupled channel dynamics using femtoscopic correlations at the LHC

The interaction of K – with protons is characterised by the presence of several coupled channels, systems like $\overline{K}$ 0 n and πΣ with a similar mass and the same quantum numbers as the K – p state. The strengths of these couplings to the K – p system are of crucial importance for the understanding of the nature of the Λ(1405) resonance and of the attractive K – p strong interaction. In this article, we present measurements of the K – p correlation functions in relative momentum space obtained in pp collisions at $\sqrt{s}$=13 Te, in p–Pb collisions at $\sqrt{s_{NN}}$= 5.02 Te, and (semi)peripheral Pb–Pb collisions at $\sqrt{s_{NN}}$= 5.02 Te. The emitting source size, composed of a core radius anchored to the K + p correlation and of a resonance halo specific to each particle pair, varies between 1 and 2 fm in these collision systems. The strength and the effects of the $\overline{K}$ 0 n and πΣ inelastic channels on the measured K – p correlation function are investigated in the different colliding systems by comparing the data with state-of-the-art models of chiral potentials. A novel approach to determine the conversion weights ω, necessary to quantify the amount of produced inelastic channels in the correlation function, is presented. In this method, particle yields are estimated from thermal model predictions, and their kinematic distribution from blast-wave fits to measured data. The comparison of chiral potentials to the measured K – p interaction indicates that, while the πΣ –K – p dynamics is well reproduced by the model, the coupling to the $\overline{K}$ 0 n channel in the model is currently underestimated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Environmental controls on simulated deep moist convection initiation occurring during RELAMPAGO-CACTI

This study synthesizes the results of 13 high-resolution simulations of deep convective updrafts forming over idealized terrain using environments observed during the RELAMPAGO and CACTI field projects. Using composite soundings from multiple observed cases, and variations upon them, we explore the sensitivity of updraft properties (e.g., size, buoyancy, and vertical pressure gradient forces) to influences of environmental relative humidity, wind shear, and mesoscale orographic forcing that support or suppress deep convection initiation (CI). Emphasis is placed on differentiating physical processes affecting the development of updrafts (e.g., entrainment-driven dilution of updrafts) in environments typifying observed successful and null (i.e., no CI despite affirmative operational forecasts) CI events. Thermally-induced mesoscale orographic lift favors the production of deep updrafts originating from ~1–2-km-wide boundary layer thermals. Simulations without terrain forcing required much larger ( ~5-km-wide) thermals to yield precipitating convection. CI outcome was quite sensitive to environmental relative humidity; updrafts with increased buoyancy, depth, and intensity thrived in otherwise inhospitable environments by simply increasing the free tropospheric relative humidity. This implicates the entrainment of free-tropospheric air into updrafts as a prominent governor of CI, consistent with previous studies. Sensitivity of CI to the environmental wind is manifested by: 1) low-level flow affecting the strength and depth of mesoscale convergence along the terrain, and 2) clouds encountering updraft-suppressing pressure gradient forces while interacting with vertical wind shear in the free-troposphere. Among the ensemble of thermals occurring in each simulation, the widest deep updrafts in each simulation were the most sensitive to environmental influences.

54 ENVIRONMENTAL SCIENCES↗

CO 2 Hydrogenation on ZrO 2 /Cu(111) Surfaces: Production of Methane and Methanol

The conversion and utilization of carbon dioxide is a critical challenge for the control of greenhouse gas pollution and in the production of high value chemicals in C1 chemistry. ZrO 2 /Cu(111) is an inverse oxide/metal catalyst that displays high activity and stability for the hydrogenation of CO 2 into methanol at 500-600 K. At elevated temperatures, ZrO 2 grows on a CuO x /Cu(111) substrate forming islands of 10-12 nm in size and an average height of ~ 3 Å. Reaction with H 2 leads to the removal of the copper oxide producing ZrO 2 /Cu(111) surfaces which are very active for the binding and dissociation of CO 2 into CO and C. After exposing ZrO 2 /Cu(111) to moderate or elevated pressures of a CO 2 /H 2 mixture at 300 K, atomic C and minor amounts of CH x O and CO x are deposited on the catalyst surface. The adsorbed CH x O and CO x disappear upon heating above 400 K. The catalytic tests for CO 2 hydrogenation give CO as the main reaction product and CH 4 and CH 3 OH as secondary products. The relative yields of methane and methanol change with time and track the amount of atomic C deposited on the active ZrO 2 /Cu(111) surface. The formation of methane stops once the catalyst surface is saturated with C. Under steady-state conditions, ZrO 2 /Cu(111) is a much better catalyst for methanol synthesis than ZnO/Cu(111). This trend reflects variations in the size of the oxide islands and in the strength of oxide-metal interactions. The use of an inverse oxide/metal configuration is an important synthetic tool when preparing active, selective, and stable catalysts for CO 2 hydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Strong, thermo-reversible salogels with boronate ester bonds as thermal energy storage materials

Inorganic salt hydrates are promising phase change materials (PCMs) but suffer from low viscosity at temperatures above their melting point resulting in leakage problems during thermal storage applications. To achieve shape stabilization of one type of molten inorganic PCM – calcium nitrate tetrahydrate (CNH) – this work explored gelation of polyvinyl alcohol (PVA) in this solvent and the effect of dynamic boronate ester bonds on salogel strength. The occurrence of gelation of PVA in molten CNH but not in water is rationalized by the extremely high salt content and scarcity of hydration water in CNH, enabling intermolecular hydrogen bonding between PVA chains. While neat PVA salogels in CNH were weak, with a gel-to-sol transition temperature (T gel ) below room temperature, the addition of small amounts of borax (<~0.3 wt%) introduced dynamic covalent crosslinks and yielded salogels with T gel tunable over a wide temperature range from 7 to 70 °C. Here, the PVA/borax salogels were about one order of magnitude stronger than their well-known PVA/borax hydrogel counterparts, and, unlike PVA/borax hydrogels, were capable of retaining their shape and preventing leakage of molten CNH. Moreover, the salogels exhibited reversible and repeatable temperature-triggered gel-to-sol transitions and the ability to self-heal. The low polymer and crosslinker concentration also ensured that more than 95% of the heat of fusion of neat CNH was maintained in the salogels and was retained after twenty cycles of melting and crystallization, demonstrating the robust nature of these energy storage materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

New Fe 59 Stellar Decay Rate with Implications for the Fe 60 Radioactivity in Massive Stars

The discrepancy between observations from γ-ray astronomy of the 60 Fe/ 26 Al γ-ray flux ratio and recent calculations is an unresolved puzzle in nuclear astrophysics. The stellar β-decay rate of 59 Fe is one of the major nuclear uncertainties impeding us from a precise prediction. The important Gamow-Teller strengths from the low-lying states in 59 Fe to the 59 Co ground state are measured for the first time using the exclusive measurement of the 59 Co(t,3He+γ) 59 Fe charge-exchange reaction. The new stellar decay rate of 59 Fe is a factor of 3.5±1.1 larger than the currently adopted rate at T=1.2 GK. Stellar evolution calculations show that the 60 Fe production yield of an 18 solar mass star is decreased significantly by 40% when using the new rate. Our result eliminates one of the major nuclear uncertainties in the predicted yield of 60 Fe and alleviates the existing discrepancy of the 60 Fe/ 26 Al ratio.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

STFM: Accurate Spatio-Temporal Fusion Model for Weather Forecasting

Meteorological prediction is crucial for various sectors, including agriculture, navigation, daily life, disaster prevention, and scientific research. However, traditional numerical weather prediction (NWP) models are constrained by their high computational resource requirements, while the accuracy of deep learning models remains suboptimal. In response to these challenges, we propose a novel deep learning-based model, the Spatiotemporal Fusion Model (STFM), designed to enhance the accuracy of meteorological predictions. Our model leverages Fifth-Generation ECMWF Reanalysis (ERA5) data and introduces two key components: a spatiotemporal encoder module and a spatiotemporal fusion module. The spatiotemporal encoder integrates the strengths of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), effectively capturing both spatial and temporal dependencies. Meanwhile, the spatiotemporal fusion module employs a dual attention mechanism, decomposing spatial attention into global static attention and channel dynamic attention. This approach ensures comprehensive extraction of spatial features from meteorological data. The combination of these modules significantly improves prediction performance. Experimental results demonstrate that STFM excels in extracting spatiotemporal features from reanalysis data, yielding predictions that closely align with observed values. In comparative studies, STFM outperformed other models, achieving a 7% improvement in ground and high-altitude temperature predictions, a 5% enhancement in the prediction of the u/v components of 10 m wind speed, and an increase in the accuracy of potential height and relative humidity predictions by 3% and 1%, respectively. This enhanced performance highlights STFM’s potential to advance the accuracy and reliability of meteorological forecasting.

54 ENVIRONMENTAL SCIENCES↗

Computational study of the effect of core–skin structure on the mechanical properties of carbon nanofibers

The effect of the core–skin structure on the mechanical properties of carbon nanofibers is investigated in large-scale molecular dynamics simulations of tensile deformation of carbon nanofibers with the core–skin and homogeneous structures. Contrary to an established notion of the deleterious effect of the skin layer on the strength of carbon fibers, the presence of a high-quality skin layer is found to increase both the Young’s modulus and tensile strength of the nanofiber. A detailed analysis of the fracture process indicates that the nanofiber strengthening is related to the ability of skin layer to suppress crack nucleation at the core–skin interface. Furthermore, the computational predictions suggest that the design of new approaches to carbon fiber manufacturing and processing leading to the generation of a high-quality skin layer while avoiding the introduction of structural defects at the core–skin interface may yield a significant enhancement of the mechanical properties of carbon fibers.

36 MATERIALS SCIENCE↗

Local atomic environment analysis of short and long-range solute-solute interactions in a symmetric tilt grain boundary

We develop an efficient molecular-statics algorithm for predicting local solute-solute interaction effects on grain-boundary segregation. This algorithm is applied to the segregation and interaction of Ni and Cu solutes in a Σ9 (221) symmetric tilt grain boundary in Ag. It is found that the strength of interaction between two solutes directly correlates with the change of average segregation energy in the local atomic environment of a fixed grain-boundary solute. It is shown that local interaction effects at grain boundaries can be either attractive or repulsive wherein long-range attractive effects increase the propensity for solute cluster nucleation. This study underscores the atomic nature of grain-boundary solute segregation and provides a tool that could yield meaningful insight into heterogeneous solute segregation phenomena in polycrystalline alloys beyond their dilute limit.

36 MATERIALS SCIENCE↗

Partial dynamical symmetry versus quasi dynamical symmetry examination within a quantum chaos analyses of spectral data for even–even nuclei

Statistical analyses of the spectral distributions of rotational bands in 51 deformed prolate even–even nuclei in the 152 ≤ A ≤ 250 mass region $R_{{4_{1}^{ + } /2_{1}^{ + } }} \ge 3.00$ are examined in terms of nearest neighbor spacing distributions. Specifically, the focus is on data for 0 + , 2 + , and 4 + energy levels of the ground, gamma, and beta bands. The chaotic behavior of the gamma band, especially the position of the $2_{\gamma }^{ + }$ band-head compared to other levels and bands, is clear. The levels are analyzed within the framework of two models, namely, a SU(3)-partial dynamical symmetry Hamiltonian and a SU(3) two-coupled quasi-dynamical symmetry Hamiltonian, with results that are further analyzed using random matrix theory. The partial and quasi dynamics both yield outcomes that are in reasonable agreement with the known experimental results. However, due to the degeneracy of the beta and gamma bands within the simplest SU(3) picture, the theory cannot be used to describe the fluctuation properties of excited bands. By changing relative weights of the different terms in the partial and quasi dynamical Hamiltonians, results are obtained that show more GOE-like statistics in the partial dynamical formalism as the strength of the pairing term is increased. Also, in the quasi-dynamical symmetry limit, more correlations are found because of the stronger couplings.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗