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At least 235 records · Page 13

Wafer-Level Membrane-Transfer Process for Fabricating MEMS

A process for transferring an entire wafer-level micromachined silicon structure for mating with and bonding to another such structure has been devised. This process is intended especially for use in wafer-level integration of microelectromechanical systems (MEMS) that have been fabricated on dissimilar substrates. Unlike in some older membrane-transfer processes, there is no use of wax or epoxy during transfer. In this process, the substrate of a wafer-level structure to be transferred serves as a carrier, and is etched away once the transfer has been completed. Another important feature of this process is that two electrodes constitutes an electrostatic actuator array. An SOI wafer and a silicon wafer (see Figure 1) are used as the carrier and electrode wafers, respectively. After oxidation, both wafers are patterned and etched to define a corrugation profile and electrode array, respectively. The polysilicon layer is deposited on the SOI wafer. The carrier wafer is bonded to the electrode wafer by using evaporated indium bumps. The piston pressure of 4 kPa is applied at 156 C in a vacuum chamber to provide hermetic sealing. The substrate of the SOI wafer is etched in a 25 weight percent TMAH bath at 80 C. The exposed buried oxide is then removed by using 49 percent HF droplets after an oxygen plasma ashing. The SOI top silicon layer is etched away by using an SF6 plasma to define the corrugation profile, followed by the HF droplet etching of the remaining oxide. The SF6 plasma with a shadow mask selectively etches the polysilicon membrane, if the transferred membrane structure needs to be patterned. Electrostatic actuators with various electrode gaps have been fabricated by this transfer technique. The gap between the transferred membrane and electrode substrate is very uniform ( 0.1 m across a wafer diameter of 100 mm, provided by optimizing the bonding control). Figure 2 depicts the finished product.

Yang, Eui-Hyeok↗

Cryogenic Flow Boiling in Microgravity: Effects of Reduced Gravity on Two-Phase Fluid Physics and Heat Transfer

With the growing interest in space exploration, cryogenic technologies involving two-phase flow and heat transfer are in high demand to successfully procure advanced space applications such as fuel depots and nuclear thermal propulsion (NTP) systems for deep space missions. However, the unique and extreme thermal properties of cryogenic fluids introduce distinct flow boiling fluid physics and energy transport phenomena, which differ significantly from those observed with conventional fluids. Understanding the unique two-phase physics in cryogenic flow boiling remains an ongoing challenge. Furthermore, the lack of readily available microgravity cryogenic steady-state heat transfer data hinders the assessment of gravitational effects on cryogenic flow boiling. This study aims to elucidate the gravitational effects on two-phase fluid physics and heat transfer by conducting the first-ever experimental measurement of cryogenic flow boiling performance using a steady-state heated method in a reduced gravity environment. Parabolic flight experiments were performed to acquire both heat transfer measurements and high-speed video of interfacial behaviors, under varying gravity levels (microgravity, hypergravity, Lunar gravity, and Martian gravity). The experiments involved flow boiling of liquid nitrogen (LN 2 ) with a near-saturated inlet along a circular heated tube of dimensions 8.5-mm inner diameter and 680-mm heated length. The operating parameters varied are mass velocity of 398.3 - 1342.8 kg/m2s, inlet quality of -0.08 to -0.01, and inlet pressure of 413.68 - 689.48 kPa. Captured microgravity flow patterns range from bubbly to annular, all having vapor structures that are larger than those under higher gravity levels. Under microgravity, absence of buoyancy yields symmetrical vapor structures without flow stratification, laying a physical foundation for the distinct two-phase heat transfer trends during LN 2 flow boiling in microgravity. Transient data collected during the flight parabolas exhibited decreasing heated wall temperature as the aircraft transitioned from hypergravity to microgravity phases. The temperature variation indicated an enhancement in flow boiling heat transfer with decreasing gravity levels and a reduction with increasing gravity levels. The effect of reduced gravity on cryogenic flow boiling heat transfer coefficient (HTC) is discussed based on steady state heat transfer analysis. Seminal HTC correlations are evaluated against the measured microgravity HTC data, of which one is identified for superior accuracy in predicting microgravity data. Finally, a new HTC correlation is proposed to improve accuracy of microgravity predictions, yet there still exists room for further improvement with future terrestrial flow boiling experiments at different flow orientations relative to Earth gravity.

Microgravity↗

On Information Transfer in Dynamical Systems with applications in Control of Non-equilibrium Dynamics

In this paper we develop the concept of information transfer between the Borel-measurable sets for a dynamical system described by a measurable space and a non-singular transformation. The concept is based on how Shannon entropy is transferred between the measurable sets, as the dynamical system evolves. We show that the proposed definition of information transfer satisfies the usual notions of information transfer and causality, namely, zero transfer and transfer asymmetry. Furthermore, we show how the information transfer measure can be used to characterize ergodicity and mixing in dynamical systems. We also develop the computational methods for information transfer computation and apply the framework for optimal placements of actuators and sensors for control of non-equilibrium dynamics.

Sinha, Subhrajit↗

Performance Prediction of Big Data Transfer Through Experimental Analysis and Machine Learning

Big data transfer in next-generation scientific applications is now commonly carried out over connections with guaranteed bandwidth provisioned in High-performance Networks (HPNs) through advance bandwidth reservation. To use HPN resources efficiently, provisioning agents need to carefully schedule data transfer requests and allocate appropriate bandwidths. Such reserved bandwidths, if not fully utilized by the requesting user, could be simply wasted or cause extra overhead and complexity in management due to exclusive access. This calls for the capability of performance prediction to reserve bandwidth resources that match actual needs. Towards this goal, we employ machine learning algorithms to predict big data transfer performance based on extensive performance measurements, which are collected over a span of several years from a large number of data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated HPN testbeds. We first identify a comprehensive list of attributes involved in a typical big data transfer process, including end host system configurations, network connection properties, and control parameters of data transfer methods. We then conduct an in-depth exploratory analysis of their impacts on application-level throughput, which provides insights into big data transfer performance and motivates the use of machine learning. We also investigate the applicability of machine learning algorithms and derive their general performance bounds for performance prediction of big data transfer in HPNs. Experimental results show that, with appropriate data preprocessing, the proposed machine learning-based approach achieves 95% or higher prediction accuracy in up to 90% of the cases with very noisy real-life performance measurements.

Yun, Daqing↗

Theoretical Development of Controller Transfer applied to Dynamical Systems

Data-driven control strategies suffer from the necessity of training and its associated computational time and cost. This motivates the continuous increase of popularity of transfer learning based methods. In this paper, we have investigated transfer learning in the context of controller for dynamical systems. First, we have derived conditions under which controller can be transferred between two linear dynamical systems. Furthermore, we have introduced a novel algorithm to design the transferable and non-transferable control components for linear systems. Secondly, we have derived conditions under which a stabilizing controller can be transferred between two different nonlinear dynamical systems. Furthermore, we have used the notion of zero dynamics to transform the nonlinear dynamics into global normal form, to derive the transferability conditions on the controller. Finally, we have numerically evaluated the performance of our transfer learning based methods for two sets of example linear and nonlinear dynamical systems.

Chakraborty, Indrasis↗

Performance Prediction of Big Data Transfer Through Experimental Analysis and Machine Learning

Big data transfer in next-generation scientific ap- plications is now commonly carried out over connections with guaranteed bandwidth provisioned in High-performance Net- works (HPNs) through advance bandwidth reservation. To use HPN resources efficiently, provisioning agents need to carefully schedule data transfer requests and allocate appropriate band- widths. Such reserved bandwidths, if not fully utilized by the requesting user, could be simply wasted or cause extra overhead and complexity in management due to exclusive access. This calls for the capability of performance prediction to reserve bandwidth resources that match actual needs. Towards this goal, we employ machine learning algorithms to predict big data transfer perfor- mance based on extensive performance measurements, which are collected over a span of several years from a large number of data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated HPN testbeds. We first identify a comprehensive list of attributes involved in a typical big data transfer process, including end host system configurations, network connection properties, and control parameters of data transfer methods. We then conduct an in-depth exploratory analysis of their impacts on application- level throughput, which provides insights into big data transfer performance and motivates the use of machine learning. We also investigate the applicability of machine learning algorithms and derive their general performance bounds for performance prediction of big data transfer in HPNs. Experimental results show that, with appropriate data preprocessing, the proposed machine learning-based approach achieves 95% or higher pre- diction accuracy in up to 90% of the cases with very noisy real-life performance measurements.

Yun, Daqing↗

Effect of Drying on Corrosion Mitigation of Hanford Transfer Lines

Radioactive waste is stored in underground, carbon-steel double-shell tanks at the Department of Energy Hanford site. The waste is transferred between the tanks and other assets using the transfer lines spanning throughout the various tank farms at Hanford. The transfer lines consist of a pipe-in-pipe design, small diameter pipes, and are not piggable. Recent inspection data of the transfer lines have shown areas with corrosion on both interior of the encasements and exterior of the primary pipes, with nearly 50 percent wall loss on the primary pipes and nearly 25% wall loss on the encasement pipes due to pitting corrosion. The visual inspections of the transfer lines have shown presence of corrosion products near the pipeline risers and beyond. It has been hypothesized that the corrosion is predominantly due to the high humidity conditions and in some cases is driven by the presence of residual hydrotest water in the encasement and the associated contact with the safety significant primary pipe. Therefore, drying of the transfer lines could lead to corrosion mitigation. Experimental studies are being conducted to understand the effect of environmental conditions, especially, relative humidity and temperature, on transfer line grade carbon steel corrosion and on mitigating corrosion. The experimental conditions are selected based on the seasonal temperature changes, and relative humidity conditions ranging from 30 to 100 percent. The experimental data will be used as guidance for maintaining a dry environment that will help mitigate the transfer-line corrosion caused by the high humidity conditions.

Shukla, Pavan K.↗

Elucidation of Marcus Relationships for Hydride Transfer Reactions Involving Transition Metal Hydrides

The rate of hydride transfer from three Ir hydride complexes of the type Cp*Ir( R bpy)H + (Cp* = C 5 Me 5 ; R bpy = 4,4′-R-2,2′-bipyridine, R = OMe, H, CO 2 Me) to six N-methylacridinium ( R Acr + ) acceptors with electronically different substituents in the 2- or 2,7-positions were measured. Using the thermodynamic hydricity of the donors and the hydride affinity of the acceptors the thermodynamic driving forces for hydride transfer were determined. Brønsted plots, which correlate kinetic and thermodynamic hydricity, demonstrate distinct linear free energy relationships for each complex, with different Brønsted α values. Thus, at the same driving force hydride transfer from Cp*Ir( OMe bpy)H + is faster than for Cp*Ir(bpy)H + or Cp*Ir( CO2Me bpy)H + . Experimental and computational analyses are consistent with a concerted hydride transfer mechanism for all Ir complexes. As the thermodynamic driving force increases an earlier transition state is observed and all transition states also include π-stacking interactions between the donor and acceptor, which likely contribute to the different α values. The experimental data fits well to the Marcus model, enabling the determination of reorganization energies (λ) that range from 58 to 69 kcal mol -1 . These are lower than λ values for hydride transfer reactions involving organic donors and acceptors. This work provides a rare example of the correlation of kinetic and thermodynamic hydricity using only experimental data and shows that hydride transfer reactions involving metal hydrides can follow Marcus theory. Furthermore, the findings offer insight into controlling metal-catalyzed hydride transfer reactions, which is valuable for designing improved systems for a range of transformations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterization of Fuel-to-Coolant Heat Transfer During Reactivity-Initiated Accidents Using Tightly Coupled Thermal Hydraulics and Fuel Thermomechanics

The reactivity-initiated accident (RIA) is a complex scenario with several tightly interacting physical phenomena. Accurately predicting fuel behavior during these transients is difficult due to limitations in the modeling of fuel-to-coolant heat transfer. Common approaches to simulate RIAs involve standalone calculations using either a fuel performance code or a thermal-hydraulic code. The complex interdependencies of thermal-hydraulic and fuel mechanical behavior suggest that a tight coupling between these codes may provide more accurate predictions of fuel-to-coolant heat transfer and cladding mechanical response. Here, RELAP5-3D and BISON are coupled in this paper to simulate RIAs, and a sensitivity analysis is performed to rank key thermal properties and two-phase heat transfer parameters relevant for fuel-to-coolant heat transfer and cladding failure mechanisms in UO 2 –Zircaloy-4 systems. Gas gap conductance, film boiling heat transfer uncertainty, pulse width, fuel-specific heat capacity, and cladding-specific heat capacity were identified as important parameters. Variations in figures of merit resulting from changes to pulse width and the material thermal properties indicate that time-dependent heat transfer rates are significant for safety-relevant mechanical parameters due to the time dependence of cladding ductility and pellet-cladding mechanical interaction loading. The results suggest that the thermal-hydraulic factors have a nonnegligible influence on the thermomechanical solution and vice versa. Tight coupling of both sets of physics is recommended to improve prediction of fuel behavior during RIAs. Highlights include the following: 1. The RELAP5-3D thermal-hydraulic code and the BISON fuel performance code are tightly coupled for simulation of RIA transients with energy depositions at the Zircaloy-4 cladding failure threshold. 2. Departure from nucleate boiling occurred for all simulated cases. Due to the ductility of fresh fuel, substantial ballooning occurred in most cases. 3. Gas gap conductance, fuel-specific heat capacity, cladding-specific heat capacity, transient pulse width, and film boiling heat transfer were the dominant thermal factors impacting the safety figures of merit at energy depositions.

Critical Heat Flux (CHF)↗

Transfer Learning-Based Independent Component Analysis

Understanding the underlying component structure is crucial for multivariate signal analysis. Among all the techniques that try to learn the latent structure, independent component analysis (ICA) is one of the most important and popular methods, which aims to extract independent components from multivariate signals and enables further analysis. For example, in electroencephalogram (EEG) analysis, artifacts filtering and disease detection are conducted based on the independent components of the signals. One critical challenge in existing ICA approaches is that the component extraction accuracy may degrade when the available data of a unit are limited. To address this issue, this paper proposes a transfer learning-based ICA method by innovatively transferring component distribution from a source domain, so that accurate component extraction results can be achieved even when only limited data are available in the target domain. To the best of our knowledge, this is the first work that leverages transfer learning to improve ICA accuracy with limited available data. In particular, we first extract all the independent components from the source domain by maximizing the log-likelihood function with a Newton-like method on a smooth manifold. Then for the target domain, the component with the largest negentropy is extracted in each round. To effectively leverage the knowledge from the source domain and to prevent the negative transfer, we try to find a component in the source domain that matches the component we are extracting. The probability density function of the matched component will then be used to improve the component extraction accuracy if such matched component can be found; otherwise, no knowledge will be transferred. Finally, numerical simulations and a case study with electrocardiogram (ECG) data are conducted, showing the effectiveness of the proposed method in transferring knowledge and reducing negative transfer.

42 ENGINEERING↗

Radiative heat transfer in FLiBe molten salt participating medium in a vertical heated tube under forced and mixed convection laminar flows

The contribution of radiative heat transfer (RHT) to convective heat transfer in a heated vertical pipe with laminar flow and constant wall temperature, for FLiBe molten salt, is investigated computationally. The combined effects of conduction in the fluid, forced convection, buoyancy, temperature-dependent physical properties, and thermal radiation are investigated. The P1 approximation is employed in the discretization of the Radiative Transfer Equation (RTE). The COMSOL Multiphysics software is used to generate the numerical solutions. The theoretical analysis developed here demonstrates that only for intermediate values of the optical thickness, i.e. τ D ~ O 1 , the participating media effects are expected to be important. This analysis is confirmed computationally and a value of τ D ≈ 4 is shown to lead to the highest increase in overall heat transfer behavior. Under forced convection, the Nusselt ratio N u total / N u no - rad reaches a peak value of 1.76 at τ D = 4 and z/D = 200 , and is less than 1.1 for τ D < 0 . 1 and τ D > 60 . Under aiding-flow mixed convection, N u total / N u no - rad reaches a peak of 1.34 at τ D = 4 . 2 and is less than 1.1 for τ D < 0 . 4 and τ D > 36 . Under opposing-flow mixed convection, Nu total / Nu no - rad reaches a peak of 1.81 at τ D = 4 . 2 and is less than 1.1 for τ D < 0 . 2 and τ D > 50 . RHT effects on the overall heat transfer are most pronounced in opposing mixed convection, where N u total / N u no - rad is 2.26 observed at z/D = 50 . The sensitivity to wall emissivity is evaluated; in forced convection, the peak N u total / N u no - rad is 1.66 at ε = 0 (reflective wall) and 2.04 at ε = 1 (absorptive wall). Finally, the sensitivity to pipe diameter is also discussed. Overall, for a vertical heated tube, radiative heat transfer effects lead to enhancement of heat transfer by as high as a factor of two, and they depend on the optical thickness of the flow, mixed convection environment ( Gr / R e 2 and direction of flow relative to the gravitational force), surface emissivity, and entrance effects.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Long-Lived Charge-Transfer Excitons in a Graphene–PTCDI–TiOPc Trilayer Heterostructure

Excitation transfer across the interfaces between graphene, perylenetetracarboxylic diimide (PTCDI), and titanyl phthalocyanine (TiOPc) was studied by using transient absorption and photoluminescence spectroscopy. Both photoluminescence quenching and transient absorption measurements confirm the presence of a type-II interface between PTCDI and TiOPc. While the graphene/PTCDI interface is expected to exhibit type-I behavior, transient absorption measurements indicate that only electrons transfer from PTCDI to graphene, with no evidence of hole transfer. Density functional theory calculations reveal significant ground-state electron transfer from graphene to PTCDI, resulting in band bending that prevents excited holes from transferring from PTCDI to graphene. This feature is exploited in a trilayer heterostructure of graphene/PTCDI/TiOPc, where the spatial separation of photoexcited electrons and holes in graphene and TiOPc, respectively, leads to the formation of long-lived photoexcitations with a lifetime of approximately 500 ps. Furthermore, spatially resolved transient absorption measurements reveal the immobile nature of these excitations, confirming that they are charge-transfer excitons rather than free electrons and holes. Furthermore, these results provide valuable insights into the complex interlayer photoexcitation transfer properties and demonstrate precise control over the layer population and the recombination lifetime of photocarriers in such hybrid heterostructures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Deciphering Charge Transfer Processes in Transition Metal Complexes from the Perspective of Ultrafast Electronic and Nuclear Motions

Chemical transformations in charge transfer states result from the interplay between electronic dynamics and nuclear reorganization along excited-state trajectories. Here, in this study, we investigate the ultrafast structural dynamics following photoinduced electron transfer from the metal-metal-to-ligand charge transfer state of an electron donor, a Pt dimer complex, to a covalently linked electron acceptor group using ultrafast time-resolved wide-angle X-ray scattering and optical transient absorption spectroscopy methods to disentangle the interdependence of the excited-state electronic and nuclear dynamics. Following photoexcitation, Pt-Pt bond formation and contraction takes up to 1 ps, much slower than the corresponding process in analogous complexes without electron acceptor groups. Because the Pt-Pt distance change is slow with respect to excited-state electron transfer, it can affect the rate of electron transfer. These results have potential impacts on controlling electron transfer rates via structural alterations to the electron donor group, tuning the charge transfer driving force.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Isopotential Electron Titration: Hydrogen Adsorbate-Metal Charge Transfer

The extent of charge transfer between an adsorbate and thermocatalytic surface plays a key role in determining catalytic activity, but direct and quantitative measures have remained elusive. Here, we report the method of isopotential electron titration (IET), an approach that directly measures charge transfer between adsorbates and catalytic surfaces. Charge transfer between Pt and adsorbed hydrogen adatoms was investigated using a catalytic condenser, where the Pt surface was separated from a p-type silicon layer by a hafnia dielectric film. By forcing the Pt and Si layers into isopotential conditions, charge transfer between the adsorbate and Pt surface was titrated through an external circuit. Hydrogen atoms donated electrons to Pt upon adsorption, which was quantitatively reversed upon desorption. Across a temperature range of 125–200 °C (surface hydrogen fractional coverages of 80–100%), the charge transferred to Pt by an adsorbed hydrogen atom was measured to be 0.19 ± 0.01% |e|/H. Bader charge analysis of the extent of charge transfer was in agreement with experimental measurements, with a calculated net donation of 0.4% |e|/H. The ability to experimentally quantify surface charge transfer provides an electronic-based approach to characterize catalytic surfaces, the adsorbed moieties residing on them, and the chemical reactions they accelerate.

Adsorption↗

Pick-and-Place Transfer of Arbitrary-Metal Electrodes for van der Waals Device Fabrication

Van der Waals electrode integration is a promising strategy to create nearly perfect interfaces between metals and 2D materials, with advantages such as eliminating Fermi-level pinning and reducing contact resistance. However, the lack of a simple, generalizable pick-and-place transfer technology has greatly hampered the wide use of this technique. Here, we demonstrate the pick-and-place transfer of prefabricated electrodes from reusable polished hydrogenated diamond substrates without the use of any sacrificial layers due to the inherent low-energy and dangling-bond-free nature of the hydrogenated diamond surface. The technique enables transfer of arbitrary-metal electrodes and an electrode array, as demonstrated by successful transfer of eight different elemental metals with work functions ranging from 4.22 to 5.65 eV. We also demonstrate the electrode array transfer for large-scale device fabrication. The mechanical transfer of metal electrodes from diamond to van der Waals materials creates atomically smooth interfaces with no interstitial impurities or disorder, as observed with cross-section high-resolution transmission electron microscopy and energy-dispersive X-ray spectroscopy. As a demonstration of its device application, we use the diamond transfer technique to create metal contacts to monolayer transition metal dichalcogenide semiconductors with high-work-function Pd, low-work-function Ti, and semimetal Bi to create n- and p-type field-effect transistors with low Schottky barrier heights. We also extend this technology to air-sensitive materials (trilayer 1T’ WTe 2 ) and other applications such as ambipolar transistors, Schottky diodes, and optoelectronics. This highly reliable and reproducible technology paves the way for new device architectures and high-performance devices.

2D materials↗

Isopotential Electron Titration of Ammonia Charge Transfer on Metal Catalysts

Electron transfer between adsorbates and surfaces determines the binding strength and reactivity of chemical moieties on materials designed for separations and catalysis. To quantify electron exchange, the extent of charge transfer resulting from ammonia adsorption on a Ru surface was measured by isopotential electron titration (IET) on a Ru catalytic condenser, where isopotential conditions were maintained between Ru and silicon separated by an insulating HfO 2 layer during gas phase ammonia adsorption. Charge transfer upon ammonia adsorption on a Ru catalytic condenser increased from 40 to 1200 nC/cm 2 at 75 and 225 °C, respectively. Charge transfer measurements provided a direct estimate of ammonia adsorption thermodynamics on Ru without knowing surface coverages a priori, revealing an adsorption enthalpy of −53 ± 10 kJ/mol and entropy of −61 ± 26 J/mol·K. Combining experimentally-measured charge transfer with kinetic Monte Carlo simulations informed adsorbate surface coverages determined that 0.058 electrons were transferred to the Ru surface for each molecular ammonia adsorption event (δ NH 3 = 0.058 ± 0.005 e – /NH 3 *), consistent with calculated Bader charges. The ability to measure the extent of charge transfer for adsorbed species provides a fundamental descriptor to understand existing and new chemically functional surfaces, providing a foundational method for the emerging field of thermochemical surface coulometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Delocalized Excitation Transfer in Open Quantum Systems with Long-Range Interactions

The interplay between coherence and system-environment interactions is at the basis of a wide range of phenomena, from quantum information processing to charge and energy transfer in molecular systems, biomolecules, and photochemical materials. In this work, we use a Frenkel exciton model with long-range interacting qubits coupled to a damped collective bosonic mode to investigate vibrationally assisted transfer processes in donor-acceptor systems featuring internal substructures analogous to light-harvesting complexes. We find that certain delocalized excitonic states maximize the transfer rate and that the entanglement is preserved during the dissipative transfer over a wide range of parameters. We investigate the reduction in transfer caused by static disorder, white noise, and finite temperature and study how transfer efficiency scales as a function of the number of dimerized monomers and the component number of each monomer, finding which excitonic states lead to optimal transfer. Finally, we provide a realistic experimental setting to realize this model in analog trapped-ion quantum simulators. Analog quantum simulation of systems comprising many and increasingly complex monomers could offer valuable insights into the design of light-harvesting materials, particularly in the nonperturbative intermediate parameter regime examined in this study, where classical simulation methods are resource intensive.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantal diffusion approach for multinucleon transfer processes in the 58,64 Ni + 208 Pb reactions: Toward the production of unknown neutron-rich nuclei

In recent years, substantial efforts have been made for the study of multinucleon transfer reactions at energies around the Coulomb barrier both experimentally and theoretically, aiming at the production of unknown neutron-rich heavy nuclei. It is crucial to provide reliable theoretical predictions based on microscopic theories with sufficient predictive power. Purpose: This article aims to clarify the applicability of the quantal diffusion approach based on the stochastic mean-field (SMF) theory for multinucleon transfer processes. Isotope production cross sections are evaluated for the reactions of 64 Ni + 208 Pb at E c.m. = 268 MeV and 58 Ni + 208 Pb at E c.m. = 270 MeV and are compared with available experimental data. Methods: Three-dimensional time-dependent Hartree-Fock (TDHF) calculations are carried out for a range of initial orbital angular momenta with Skyrme SLy4d functional. Quantal diffusion equations, derived based on the SMF theory, for variances and covariance of neutron and proton numbers of reaction products are solved, with microscopic drift and diffusion coefficients obtained from time evolution of occupied single-particle orbitals in TDHF. Secondary de-excitation processes, both particle evaporation and fission, are simulated by a statistical compound-nucleus de-excitation model, gemini++. Dynamics of a fast isospin equilibration process followed by a slow drift toward the mass symmetry are commonly observed, as expected. Various reaction outcomes are evaluated, including average mass and charge numbers of reaction products, total kinetic energy loss (TKEL), scattering angle, contact time, and production cross sections for primary and secondary products. By comparing with the experimental data, we find that SMF and TDHF quantitatively reproduce experimental data for few-nucleon-transfer channels around the average values. In contrast, for many-nucleon-transfer channels, we find that the SMF approach provides much better description of the experimentally measured isotopic distributions. The results underline the importance of beyond-mean-field effects, especially one-body (mean-field) fluctuations and correlations, in describing multinucleon transfer processes. Moreover, through a combined analysis of SMF with a statistical model, gemini++, we find a significant contribution of transfer-induced fission, which is consistent with the experimental observation. In some cases, the SMF approach overestimates the isotopic width, requiring further improvements of the theoretical description. Possible ways to improve the description are discussed. The SMF approach is designed to describe the quantum many-body problem according to an ensemble of mean-field trajectories, taking into account part of many-body correlations in the description. As it requires feasible computational costs comparable to the ordinary TDHF approach, together with further model improvements, it will be a promising tool in the search for optimal reaction conditions to produce yet-unknown neutron-rich heavy nuclei through the multinucleon transfer reaction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗