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At least 685 records · Page 38

Melting down a tetraquark: D*D(*) interactions and T c c ( 3875 ) + in a hot environment

We discuss the modification of the properties of the tetraquark-like and its heavy quark spin partner, immersed in a hot bath of pions. We consider these exotic states as purely isoscalar DD* and D*D* S-wave bound states, respectively. Finite temperature effects are incorporated through the D and D* state-of-the-art thermal spectral functions calculated in [G. Montana et al., Phys. Rev. D, 102 (2020) 096020], using the imaginary-time formalism. We find important modifications of the DD* and D*D* scattering amplitudes already for MeV, and show that the hot-bath lineshapes of these tetraquark-like states strongly depend on their Weinberg molecular content. We find that the thermal and spectral functions change more rapidly with temperature for high molecular probabilities P0. For large values of P0, the widths significantly increase with temperature, leading to the melting of these exotic states for temperatures larger than 80 MeV. For small molecular components, the changes in the spectral functions of these states due to temperature become significantly less important. All these results show that any future experimental determination of the D(*)D* scattering amplitudes at finite temperature will provide valuable insights into the molecular content of the and exotics.

Montesinos, V. (ORCID:0000000261862777)↗

Learning energy-based representations of quantum many-body states

Efficient representation of quantum many-body states on classical computers is a problem of practical importance. An ideal representation of a quantum state combines a succinct characterization informed by the structure and symmetries of the system along with the ability to predict the physical observables of interest. Several machine-learning approaches have been recently used to construct such classical representations, which enable predictions of observables and account for physical symmetries. However, the structure of a quantum state typically gets lost unless a specialized is employed based on prior knowledge of the system. Moreover, most such approaches give no information about what states are easier to learn in comparison with others. Here, we propose a generative energy-based representation of quantum many-body states derived from Gibbs distributions used for modeling the thermal states of classical spin systems. Based on the prior information on a family of quantum states, the energy function can be specified by a small number of parameters using an explicit low-degree polynomial or a generic parametric family such as neural nets and can naturally include the known symmetries of the system. Our results show that such a representation can be efficiently learned from data using exact algorithms in a form that enables the prediction of expectation values of physical observables. Importantly, the structure of the learned energy function provides a natural explanation for the difficulty of learning an energy-based representation of a given class of quantum states when measured in a certain basis. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

IRDFF-II: A New Neutron Metrology Library

High quality nuclear data is the most fundamental underpinning for all neutron metrology applications. This paper describes the release of version II of the International Reactor Dosimetry and Fusion File (IRDFF-II) that contains a consistent set of nuclear data for fission and fusion neutron metrology applications up to 60 MeV neutron energy. The library is intended to support: a) applications in research reactors; b) safety and regulatory applications in the nuclear power generation in commercial fission reactors; and c) material damage studies in support of the research and development of advanced fusion concepts. The paper describes the contents of the library, documents the thorough verification process used in its preparation, and provides an extensive set of validation data gathered from a wide range of neutron benchmark fields. The new IRDFF-II library includes 119 metrology reactions, four cover material reactions to support self-shielding corrections, five metrology metrics used by the dosimetry community, and cumulative fission products yields for seven fission products in three different neutron energy regions. In support of characterizing the measurement of the residual nuclei from the dosimetry reactions and the fission product decay modes, the present document lists the recommended decay data, particle emission energies and probabilities for 68 activation products. It also includes neutron spectral characterization data for 29 neutron benchmark fields for the validation of the library contents. Additional six reference fields were assessed (four from plutonium critical assemblies, two measured fields for thermal-neutron induced fission on 233U and 239Pu targets) but not used for validation due to systematic discrepancies in C/E reaction rate values or lack of reaction-rate experimental data. Another ten analytical functions are included that can be useful for calculating average cross sections, average energy, thermal spectrum average cross sections and resonance integrals. The IRDFF-II library and comprehensive documentation is available online at www-nds.iaea.org/IRDFF/. Evaluated cross sections can be compared with experimental data and other evaluations at www-nds.iaea.org/exfor/endf.htm. The new library is expected to become the international reference in neutron metrology for multiple applications.

IAEA IRDFF↗

Comparative operando XPS studies of quasi-Fermi level splitting and open-circuit voltage in CZTSe/CdS and CIGS/CdS junctions and device structures

This contribution describes operando x-ray photoelectron spectroscopy (opXPS) studies of Cu(In,Ga)Se 2 (CIGS) and Cu 2 ZnSnSe 4 (CZTSe) absorber layers and device structures. X-ray-excited valence-band and core-level spectra were acquired on bare absorber surfaces and after CdS and ZnO:Al depositions in standard absorber/CdS/ZnO/ZnO:Al device stacks. OpXPS data sets were acquired at various x-ray fluxes, with and without white-light illumination. From these measurements, quasi-Fermi level splitting (ΔE F ) values in the absorber/CdS junctions were measured directly as a function of excitation conditions. For both CIGS and CZTSe, results show that ..delta..EF proportional to the full open-circuit voltage (V OC ) of the completed devices is present after the deposition of the CdS layer - i.e., E F = qV OC - demonstrating that the so-called V OC deficit in CZTSe solar cells is also present at this stage of processing. The authors find that photoexcitation due to x-rays or stray visible light during XPS or similar measurements can produce measurable photovoltages in materials, absorber/CdS junctions, and finished devices. In situ current density versus voltage measurements on a typical CIGS device reveal that x-ray-induced photoexcitation associated with typical XPS measurement conditions is equivalent to ~3 x 10 -3 suns, which in this study produced V OC = 440 mV. These findings demonstrate that accounting for photoexcitation conditions during XPS or similar measurements can improve band-offset determinations and produce more reliable values for the junction built-in voltage. The implications of the study findings on the CZTSe V OC deficit and device performance are discussed.

36 MATERIALS SCIENCE↗

First-principles investigation of the thermophysical properties of NaCl, PuCl 3 , and NaCl-PuCl 3 Molten salts

Molten salts have a variety of applications that span the nuclear and solar industries, and which involve thermal storage and heat transfer. There is a present knowledge gap in the thermophysical properties of molten salts, which limits the readiness level of molten salt applications. This is especially pertinent for molten salt reactors where the fissile material is dissolved within the molten salt. Ab initio molecular dynamics is a common method employed to investigate the structural and thermophysical properties at elevated temperatures. NaCl-PuCl 3 is a candidate fuel salt in molten salt reactors. The scope of this study is to investigate the seven unique compositions and a range of temperatures of NaCl-PuCl 3 and calculate the density, heat capacity, compressibility, enthalpy of mixing, and coefficient of thermal expansion. Within this work, the van der Waals (vdW) interactions are primarily handled with the vdW-DF2 functional but spot-checked with both the dDsC and DFT-D3 methods. The calculated densities are in good agreement with the NaCl and the eutectic compositions, and no experimental values exist for PuCl 3 at these temperatures. The densities are fit to a first-order Redlich-Kister expansion as a function of both composition and temperature. The heat capacity in the literature is scattered but the calculated values agree well with one of the experimental results. Here, the heat capacity increases as a linear function with respect to concentration at a rate of about 7.5 J/mol-K per 10 mol% PuCl 3 .

36 MATERIALS SCIENCE↗

Multirate Exponential Rosenbrock Methods

In this paper we propose a novel class of methods for high-order accurate integration of multirate systems of ordinary differential equation initial-value problems. The proposed methods construct multirate schemes by approximating the action of matrix φ functions within explicit exponential Rosenbrock (ExpRB) methods, thereby called multirate ExpRB (MERB) methods. They consist of the solution to a sequence of modified “fast” initial-value problems, which may themselves be approximated through subcycling any desired initial-value problem solver. In addition to proving how to construct MERB methods from certain classes of ExpRB methods, we provide rigorous convergence analysis of these methods and derive efficient MERB schemes of orders 2 through 6 (the highest-order infinitesimal multirate methods to date). Lastly, we then present numerical simulations to confirm these theoretical convergence rates and to compare the efficiency of MERB methods against other recently introduced high-order multirate methods.

97 MATHEMATICS AND COMPUTING↗

The developments in modifying functionality of lignin and its application in biocomposites

With the advancement of sustainable material innovations, renewable natural biopolymers are gradually replacing traditional metal and petroleum-based synthetic materials due to their environmental friendliness, biodegradability, and economic advantages. Lignin, the second most abundant natural aromatic polymer in the plant kingdom, has emerged as a key candidate raw material for the development of green polymer systems because of its unique phenylpropane unit network structure, high carbon content, and rich functional group characteristics. However, challenges such as the inherent structural complexity, chemical inertness, and uneven molecular weight distribution of lignin limit its direct application. By employing modification strategies such as chemical functionalization and physical regulation, researchers can precisely control its reactivity, thermal stability, and interfacial compatibility, enabling the preparation of high-performance lignin-based functional composites. Here, this paper systematically reviews the principles and methodological advancements in lignin's multi-dimensional modification technology. It analyzes the mechanisms by which various chemical and physical modification techniques enhance the mechanical properties, functional responsiveness, and environmental adaptability of materials, and discusses innovative applications in fields such as intelligent packaging, biomedical materials, and energy storage devices. Furthermore, this review addresses the key challenges encountered in the high-value transformation of lignin, with the aim of offering a theoretical framework and technical pathway for the transformative development of lignin from agricultural and forestry by-products to functional material platforms.

Functional composites↗

Self-interaction-corrected Kohn–Sham effective potentials using the density-consistent effective potential method

Density functional theory (DFT) and beyond-DFT methods are often used in combination with photoelectron spectroscopy to obtain physical insights into the electronic structure of molecules and solids. The Kohn–Sham eigenvalues are not electron removal energies except for the highest occupied orbital. The eigenvalues of the highest occupied molecular orbitals often underestimate the electron removal or ionization energies due to the self-interaction (SI) errors in approximate density functionals. Here, we adapt and implement the density-consistent effective potential method of Kohut, Ryabinkin, and Staroverov (2014) to obtain SI-corrected local effective potentials from the SI-corrected Fermi–Löwdin orbitals and density in the Fermi–Löwdin orbital self-interaction correction scheme. The implementation is used to obtain the density of states (photoelectron spectra) and HOMO–LUMO gaps for a set of molecules and polyacenes. Good agreement with experimental values is obtained compared to a range of SI uncorrected density functional approximations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electronic structure of boron and aluminum δ -doped layers in silicon

Recent work on atomic-precision dopant incorporation technologies has led to the creation of both boron and aluminum δ-doped layers in silicon with densities above the solid solubility limit. For this study, we use density functional theory to predict the band structure and effective mass values of such δ layers, first modeling them as ordered supercells. Structural relaxation is found to have a significant impact on the impurity band energies and effective masses of the boron layers, but not the aluminum layers. However, disorder in the δ layers is found to lead to a significant flattening of the bands in both cases. We calculate the local density of states and doping potential for these δ-doped layers, demonstrating that their influence is highly localized with spatial extents at most 4 nm. We conclude that acceptor δ-doped layers exhibit different electronic structure features dependent on both the dopant atom and spatial ordering. This suggests prospects for controlling the electronic properties of these layers if the local details of the incorporation chemistry can be fine-tuned.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bandgap and electronic structure of CaSiN 2 : Experiment and theory

Abstract We interrogate the electronic properties of the nitridosilicate CaSiN 2 as determined using soft X‐ray absorption and emission spectroscopy, which probe directly the partial electronic density of states. We compare our measurements to full potential, all electron density functional theory (DFT) calculations. Good agreement between experiment and theory is obtained, and the electronic bandgap of CaSiN 2 is determined to be 3.95 ± 0.3 eV, in contrast with our predicted value of 4.78 eV that was calculated using the modified Becke–Johnson exchange‐correlation functional with the DFT framework.

Materials Science↗

Adsorption of terbium (III) on DGA and LN resins: Thermodynamics, isotherms, and kinetics

Two commercially available extraction chromatography (EXC) resins containing N,N,N’,N’-tetra-n-octyldiglycolamide (DGA Resin, Normal, 50 – 100 μm) and Bis(2-ethylhexyl) phosphate (LN Resin, 100 – 150 μm) were used as adsorbents to study fundamental adsorption properties such as thermodynamic values, equilibrium isotherms, and kinetic uptake models for terbium(III) adsorption. Weight distribution ratios (D w ) for terbium on DGA and LN resins were measured using a [ 160 Tb]Tb 3+ radiometric tracer in nitric acid as a function of acidity, temperature, initial analyte concentration, and equilibrium time. The D w values showed increasing binding affinity for DGA resin at high nitric acid concentrations and decreasing binding affinity for LN resins. Thermodynamic studies for DGA and LN resins revealed that the Gibbs free energy (ΔG) increased consistently with temperature. To model equilibrium data, increasingly higher parameter equilibrium isotherm models (Henry (1) < Langmuir, Freundlich (2) < Redlich-Peterson (3) < Fritz-Schluender (4)) were compared on their root mean squared errors (RMSE) and adjusted determination coefficients to determine the most applicable model. In all cases, the empirical four-parameter Fritz-Schluender isotherm demonstrated a superior fit. Similar comparisons for reaction-based kinetic models (Pseudo-first-order < Pseudo-second-order < Pseudo-n-order) revealed that the higher-order PNO model yielded a superior fit of kinetic data for both resins. Furthermore, in some cases, adsorption isotherms and kinetic models could also be modeled by a lower-order model with minimal change in error parameters. Weber-Morris plots revealed that two linear sections are observed for each resin, where the first linear segment is attributed to fast (film diffusion) adsorption of terbium, followed by slower intraparticle diffusion of terbium through the pores as the rate-limiting step. Based on the Weber-Morris plot, both film and intraparticle diffusion are involved in controlling the kinetic rate of adsorption for DGA and LN resins.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Centrality and pseudorapidity dependence of the charged-particle multiplicity density in Xe–Xe collisions at s NN = 5.44 TeV

In this Letter, the ALICE Collaboration presents the first measurements of the charged-particle multiplicity density, dN ch /dη and total charged-particle multiplicity, N$tot\atop{ch}$, in Xe–Xe collisions at a centre-of-mass energy per nucleon–nucleon pair of $ \sqrt{s_{NN}}$=5.44TeV. The measurements are performed as a function of collision centrality over a wide pseudorapidity range of -3.5<η<5. The values of dN ch /dη at mid-rapidity and N$tot\atop{ch}$ for central collisions, normalised to the number of nucleons participating in the collision (N part ) as a function of $ \sqrt{s_{NN}}$ follow the trends established in previous heavy-ion measurements. The same quantities are also found to increase as a function of Npart, and up to the 5% most central collisions the trends are the same as the ones observed in Pb–Pb at a similar energy. For more central collisions, the Xe–Xe scaled multiplicities exceed those in Pb–Pb for a similar N part . The results are compared to phenomenological models and theoretical calculations based on different mechanisms for particle production in nuclear collisions. All considered models describe the data reasonably well within 15%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker–Planck Equations

The Fokker-Planck (FP) equation is a foundational partial differential equation (PDE) in stochastic processes involving Brownian motions. However, the curse of dimensionality (CoD) poses a formidable challenge when dealing with high-dimensional FP equations. Although Monte Carlo simulation and (vanilla) Physics-Informed Neural Networks (PINNs) have shown the potential to tackle CoD, both methods exhibit significant numerical errors in high dimensions when dealing with the probability density function (PDF) associated with Brownian motion. The point-wise PDF values tend to decrease exponentially as dimensionality increases, surpassing the precision of numerical simulations and resulting in substantial errors. In addition, due to its massive sampling, Monte Carlo fails to offer fast sampling. Modeling the logarithm likelihood (LL) via vanilla PINNs transforms the FP equation into a notoriously difficult Hamilton-Jacobi-Bellman (HJB) equation, which is impractical for PINN learning, whose error grows rapidly with dimension. To this end, we propose a novel approach utilizing a score-based solver to fit the score function in stochastic differential equations (SDEs). The score function, defined as the gradient of the LL, plays a fundamental role in inferring LL and PDF and enables fast SDE sampling, offering an effective means to overcome the CoD. Three fitting methods, Score Matching (SM), Sliced Score Matching (SSM), and Score-PINN, are introduced, each contributing unique advantages in computational complexity, accuracy, and generality. The proposed score-based SDE solver operates in two stages: first, employing score matching or Score-PINN to acquire the score function; and second, solving the LL via an ordinary differential equation (ODE) using the obtained score function. Comparative evaluations across these methods showcase varying trade-offs. The proposed methodology is evaluated across diverse SDEs, including anisotropic Ornstein-Uhlenbeck processes, geometric Brownian motion, and Brownian motion with varying eigenspace. We also test various distributions, including Gaussian, Log-normal, Laplace, and Cauchy distributions. The numerical results demonstrate the score-based SDE solver’s stability, speed, and performance across different experimental settings, solidifying its potential as a solution to CoD for high-dimensional FP equations.

97 MATHEMATICS AND COMPUTING↗

Smart Meters Enabling Voltage Monitoring and Control Functionalities: The Last-Mile Voltage Stability Issue

It is a demanding yet challenging task to design the next generation of smart meters. This work investigates the new voltage monitoring and control function for the next-generation smart meters, and identifies its added values for power system voltage stability issues. In terms of voltage monitoring, the risk benefit analysis for adding voltage magnitudes to smart meter measurements is presented, and the risk mitigation strategies along with the co-simulation validation via GridLAB-D and NS-3 are proposed, all providing insight into the new function evaluation. In terms of voltage control, a new voltage stability control scheme is developed, which uses voltage measurements from smart meters and utilizes the observability and controllability of distributed energy resources and controllable loads. Different from traditional voltage control schemes focusing on voltage regulation and power quality monitoring from the utility perspective, the proposed control scheme can achieve the maximum real power transfer margin at the end user side, enabling the voltage stability issues being solved at the grid edge, i.e. the last-mile segment. It is the first work that considers voltage monitoring and control collectively for smart meter investment. It can help power engineering community supplement smart meter applications and shape the next-generation smart meters.

42 ENGINEERING↗

Competitive B2 and B33 Nucleation during Solidification of Ni 50 Zr 50 Alloy: Molecular Dynamics Simulation and Classical Nucleation Theory

We studied the homogenous nucleation of the stoichiometric B2 and B33 phases in the Ni 50 Zr 50 alloy using the persistent embryo method and the classical nucleation theory. The two phases become very close competitors at large supercoolings, which is consistent with the experimental observations. In the case of the B2 phase, the linear temperature dependence of the solid–liquid interface (SLI) free energy extrapolated to the melting temperature leads to the same value as the one obtained from the capillarity fluctuation method (CFM). In the case of the B33 phases, the SLI free energy is also a linear function of temperature at large supercoolings, but the extrapolation to the melting temperature leads to a value which is considerably different from the CFM value. This is persistent with the large anisotropy of the SLI properties of the B33 phase nearby the melting temperature observed in the simulation of the nominally flat interface migration.

36 MATERIALS SCIENCE↗

pnnl/ZebrafishBMD

ZebrafishBMD: A software tool to perform benchmark dose calculations using toxicity screening data of high-throughput zebrafish assays. High-content imaging of larval zebrafish behavior can be used as a screening approach to rapidly evaluate the relative potential for chemicals to cause toxicity. However, most statistical methods applied to these data transform movement values to incidence-based “hits” and calculate lowest effect levels (LELs), which loses individual fish resolution of behavior and defies hazard ranking due to reliance on applied dose levels. We developed a parallelizable workflow to calculate benchmark dose (BMD) values from dynamic, high-content zebrafish behavior data that scales for high throughput chemical screening. To capture the zebrafish movement response from light to dark stimulus, we summarized time-dependent data using both area under the curve and the immediate change at the transition point into two novel metrics that characterized abnormal behavior as a function of chemical concentration. The BMD workflow was applied to calculate BMD10 values of 1,060 ToxCast chemicals for 24 zebrafish endpoints, including behavior, mortality and morphology. ZebrafishBMD implements the BMD workflow and provides Matlab scripts to read the data (stored in a specific structure) from a .mat file, to calculate the behavioral endpoint values from movement versus time data, to construct concentrationresponse curves, to perform curve-fitting, and to calculate BMD10 values.

Thomas, Dennis↗

Underlying event properties in pp collisions at $ \sqrt{s} $ = 13 TeV

This article reports measurements characterizing the Underlying Event (UE) associated with hard scatterings at midrapidity (|η| < 0.8) in pp collisions at √s = 13 TeV. The hard scatterings are identified by the leading particle, the charged particle with the highest transverse momentum ( p T l e a d i n g ) in the event. Charged-particle number-densities and summed transverse-momentum densities are measured in different azimuthal regions defined with respect to the leading particle direction: Toward, Transverse, and Away. The Toward and Away regions contain the fragmentation products of the hard scatterings in addition to the UE contribution, whereas particles in the Transverse region are expected to originate predominantly from the UE. The study is performed as a function of p T l e a d i n g with three different p T thresholds for the associated particles, $p^{track}_T$ > 0.15, 0.5, and 1.0 GeV/c. The charged-particle density in the Transverse region rises steeply for low values of $p^{leading}_T$ and reaches a plateau. The results confirm the trend that the charged-particle density in the Transverse region shows a stronger increase with $\sqrt{s}$ an the inclusive charged-particle density at midrapidity. The UE activity is increased by approximately 20% when going from 7 TeV to 13 TeV pp collisions. The plateau in the Transverse region (5 < $p^{leading}_T$ < 40 GeV/c) is further characterized by the probability distribution of its charged-particle multiplicity normalized to its average value (relative transverse activity, R T ) and the mean transverse momentum as a function of R T Experimental results are compared to model calculations using PYTHIA 8 and EPOS LHC. The overall agreement between models and data is within 30%. These measurements provide new insights on the interplay between hard scatterings and the associated UE in pp collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗