Large H2O solubility in dense silica and its implications for the interiors of water-rich planets
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99 GENERAL AND MISCELLANEOUS↗
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Results for “atomic volume”
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Oxide nucleation via threshold-driven volume instability in Ni oxidation
Oxide nucleation dictates the onset of metal oxidation, yet the atomistic pathways bridging initial oxygen adsorption to bulk phase transformation remain elusive. Here, we utilize in-situ atomic-resolution imaging to directly capture the nucleation of nickel oxide, revealing a threshold-driven, cooperative transformation of Ni into NiO. Our observations identify a distinct incubation period during which oxygen progressively accumulates in subsurface layers. Once a critical concentration and penetration depth are reached, a collective lattice reconfiguration is triggered, abruptly converting multiple Ni layers into NiO. Atomistic simulations corroborate this mechanism, identifying a cooperative lattice instability induced by subsurface oxygen saturation. These results establish subsurface oxygen incorporation as the missing mechanistic link between surface adsorption and three-dimensional oxide formation, providing an atomistic framework to understand and control reactive phase transformations in materials synthesis, catalysis, and degradation.
36 MATERIALS SCIENCE↗
Simulations of graphite boronization: A molecular dynamics study of amorphization resulting from bombardment
The molecular dynamics code LAMMPS was used to simulate the bombardment of a graphite structure by atomic boron with impact energies ranging from 50–250 eV. The transient structural evolution, penetration depth, and amorphous layer thickness were analyzed. Simulations show that larger impact energies lead to a greater volume of amorphization and penetration of boron, but that the growth rate of the amorphous layer decreases with increasing fluence. Furthermore, the change in surface chemistry of the amorphized structures was studied using the ReaxFF formalism, which found that the amorphization process introduces dangling bonds thus increasing reactivity in the amorphous region.
74 ATOMIC AND MOLECULAR PHYSICS↗
A solid-state extrusion pathway extensible to upcycling aluminum scrap and end-of-life permanent magnets into ductile Al-6061/SmCo 5 structural magnetic composites
Permanent magnets offer strong potential for multifunctional structural components, but their inherent brittleness limits direct integration. Here, SolidStir® Extrusion (SSE) is used to embed SmCo5 powder into AA6061 in the solid state, and the resulting microstructure, interfacial chemistry, mechanical properties, and magnetic response are systematically characterized. SSE fragments the initial SmCo 5 powder into predominantly fine particles dispersed within an ultrafine Al matrix, with a volume fraction of ∼ 4–6 % in this proof-of-concept study. Interfacial reactions form a continuous Al–Co reaction layer, with local atomic-resolution indexing consistent with Al 13 Co 4 , together with Sm–Si-rich reaction products, while the matrix contains Sm–Co–Si-rich precipitates and Mg 2 Si, producing features from nanometers to micrometers. Compared with an Al extrudate, this architecture increases yield strength by ∼ 42 % and tensile strength by ∼ 31 %, while preserving uniform elongation, and it sustains work hardening in compression from 150 to 400 °C. The composite retained hard-magnetic behavior, with axial magnetization of 12.7 A·m 2 kg −1 at 6 T and intrinsic coercivity of 9.6 kOe. These findings demonstrate that SSE can produce Al-based load-bearing magnetic composites while preserving useful SmCo5 functionality.
36 MATERIALS SCIENCE↗
Coordinatively and Spatially Coconfining High-Loading Atomic Sb in Sulfur-Rich 2D Carbon Matrix for Fast K + Diffusion and Storage
The atomically dispersed materials promise ultrafast redox kinetics for alkali-ion storage. However, their relatively low mass loading limits their application. In this work, well-dispersed Sb atoms with high-loading of 23.3 wt % anchored in sulfur-rich amorphous carbon-coated reduced graphene oxide matrix (SbSA/C) are prepared by a coordinative and spatial coconfinement methodology including freeze-casting the well-dissolved Sb-chelates (Sb-thioglycolate) within graphene oxide suspension and post heating-treatment. The reduced graphene oxide substrate features open two-dimensional spatial framework for loading atomically dispersive Sb species, and the pyrolyzed Sb-chelates would provide not only massive desirable heteroatoms (S, O) for coordinating the Sb atoms but also in situ pyrolytic carbon for further spatially separating those dispersive atoms. The coordinative and spatial coconfinement engineering also endows the SbSA/C composite with atomic-level Sb atoms against migration and agglomeration during electrochemical K-storage cycling. In situ TEM reveals the uniform potassiation behavior of the SbSA/C without obvious volume change; DFT calculation and electrochemical characterization suggest the significantly lower K-ion diffusion energy barrier. Therefore, on the basis of both the active Sb center and the coordinative heteroatom, the SbSA/C electrode delivers high fast-charging capacity, outstanding rate capability and long-lifespan performance in half/full K-ion batteries (e.g., a stable capacity of 331.3 mA h g –1 is maintained over 1100 cycles at 1.0 A g –1 for half-cell).
36 MATERIALS SCIENCE↗
Pulse Shape Discrimination in JSNS 2
JSNS 2 (J-PARC Sterile Neutrino Search at J-PARC Spallation Neutron Source) is an experiment that is searching for sterile neutrinos via the observation of $\overline{ν}$ μ → $\overline{ν}$ e appearance oscillations using neutrinos from muon decay-at-rest. For this search, rejecting cosmic-ray-induced neutron events by Pulse Shape Discrimination (PSD) is essential because the JSNS2 detector is located above ground, on the third floor of the building. We have achieved 94.95% ± 0.15% rejection of neutron events while keeping 92.82% ± 1.77% of signal, electron-like events using a data-driven likelihood method. This article will report the PSD technique using the full fiducial volume of the JSNS2 detector.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Analysis of the Stable Interphase Responsible for the Excellent Electrochemical Performance of Graphite Electrodes in Sodium-Ion Batteries
Considerable efforts have been exerted to understand the formation and properties of the solid electrolyte interphase (SEI) in sodium ion batteries. However, the puzzling existence and role of SEI behind the huge volume changes of the graphite electrodes need to be answered. Herein, the reason of how ether-derived SEI maintains excellent reversibility despite the huge volume changes during cycling is unraveled. Theoretical simulations and Fourier-transform infrared spectroscopy demonstrate the formation mechanism of an SEI between the graphite anode and electrolyte. Furthermore, the high mechanical tolerance of the ether-derived SEI is confirmed in atomic force microscopy. A depth profile of X-ray photoelectron spectroscopy points to a multilayer structure of the ether-derived SEI. The outer layer comprises organics (sodium alkoxide), while the inorganics (Na 2 CO 3 , NaF) in interior region are mixed with some organics. Notably, the presence of organics ensures the adaptability of the SEI to the volume expansion of graphite during cycling, and the concentrated distribution of inorganics improves the Young's modulus (resistance to deformation). Therefore, the graphite anode exhibits high cycle stability (96.6% capacity retention ratio at 1 A g –1 over 860 cycles) and efficiency (≈99.5%).
25 ENERGY STORAGE↗
Machine Learning Predictions of Transition Probabilities in Atomic Spectra
Forward modeling of optical spectra with absolute radiometric intensities requires knowledge of the individual transition probabilities for every transition in the spectrum. In many cases, these transition probabilities, or Einstein A-coefficients, quickly become practically impossible to obtain through either theoretical or experimental methods. Complicated electronic orbitals with higher order effects will reduce the accuracy of theoretical models. Experimental measurements can be prohibitively expensive and are rarely comprehensive due to physical constraints and sheer volume of required measurements. Due to these limitations, spectral predictions for many element transitions are not attainable. In this work, we investigate the efficacy of using machine learning models, specifically fully connected neural networks (FCNN), to predict Einstein A-coefficients using data from the NIST Atomic Spectra Database. For simple elements where closed form quantum calculations are possible, the data-driven modeling workflow performs well but can still have lower precision than theoretical calculations. For more complicated nuclei, deep learning emerged more comparable to theoretical predictions, such as Hartree–Fock. Unlike experiment or theory, the deep learning approach scales favorably with the number of transitions in a spectrum, especially if the transition probabilities are distributed across a wide range of values. It is also capable of being trained on both theoretical and experimental values simultaneously. In addition, the model performance improves when training on multiple elements prior to testing. The scalability of the machine learning approach makes it a potentially promising technique for estimating transition probabilities in previously inaccessible regions of the spectral and thermal domains on a significantly reduced timeline.
74 ATOMIC AND MOLECULAR PHYSICS↗
Tritiated Water Disposition Strategies
Tritium, a radioactive isotope of hydrogen, is typically confined within one or more confinement barriers. Tritium readily reacts with oxygen to form tritiated water or can exchange with protium or deuterium atoms in water to create tritiated water which is around 10,000 times more toxic than elemental tritium. Primary tritium confinement systems can create small volumes of highly tritiated water. Secondary confinement systems, like inert gloveboxes, will produce larger volumes of lower concentration tritiated water. Much larger volumes of tritiated water of very low tritium content are produced by tritium permeation/diffusion. Tritium from inside primary and secondary confinement barriers will diffuse from these systems into cooling water systems. Closed loop, recirculating cooling water systems will slowly accumulate tritium and create concentrations which exceed drinking water (or permitted discharge) concentrations. The cooling water systems designed as series of interconnected cooling loops that can slowly transfer tritium from one cooling loop to another cooling loop through heat exchangers. These large volumes of tritiated water may be above federal discharge limits and also lack convenient disposition pathways. This document will discuss tritiated water management strategies from the perspective of large volume, low tritium concentrations that exceed drinking water or permitted discharge limits. Applicable US regulatory requirements for a Molybdenum-99 (Mo-99) production facility concerning tritiated water are also cited. Tritiated water disposition options, based on typical waste minimization strategies will guide dispositions options. A Case Study example is presented to illustrate the pros and cons of several disposition options. The report does not recommend any particular disposition pathway but discusses strategies to be explored by a producer to guide selection of processes which best fits the needs of a particular waste stream.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Snowmass 2021 Cosmic Frontier White Paper: Cosmology with Millimeter-Wave Line Intensity Mapping
Next-generation tests of fundamental physics and cosmology using large scale structure require measurements over large volumes of the Universe, including high redshifts inaccessible to present-day surveys. Line intensity mapping, an emerging technique that detects the integrated emission of atomic and molecular lines without resolving sources, can efficiently map cosmic structure over a wide range of redshifts. Observations at millimeter wavelengths detect far-IR emission lines such as CO/[CII], and take advantage of observational and analysis techniques developed by CMB experiments. These measurements can provide constraints with unprecedented precision on the physics of inflation, neutrino masses, light relativistic species, dark energy and modified gravity, and dark matter, among many other science goals. In this white paper we forecast the sensitivity requirements for future ground-based mm-wave intensity mapping experiments to enable transformational cosmological constraints. We outline a staged experimental program to steadily improve sensitivity, and describe the necessary investments in developing detector technology and analysis techniques.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Crystal Growth of Cesium Hafnium Chloride (Cs2HfCl6) Scintillating Crystal
Crystal growth is the process where crystalline substance forms and increases in size through the addition of atoms, ions, or molecules. In this research we used the Bridgman technique to grow Cesium Hafnium Chloride (C2HfCl6). This technique is ideal for growing large volume crystal. Using a vertical furnace with two heating zones for heating and cooling. the material solidifies into a crystal as it slowly transitions from hot to cold zone.
Tribble, Jalen↗
Progress Report for W911NF-23-1-0323: Development of Scalable Three-Dimensional Ion Traps for Quantum Information Processing
Trapped atomic ions are a promising platform for scalable quantum information processing. They lead in many key metrics such as single and two qubit gate fidelities, as well as quantum volume. We recently realized novel 3D ion traps with a high resolution 3D-printing process. The traps combine the scalability potential of surface chip traps with the superior trap performance of macroscopic 3D ion traps. Like photolithography, 3D-printing is a digitally defined process and hence allows for rapid iteration between design and fabrication. In contrast to photolithography, it also allows for fully defined 3D structures and, thus, is an ideal process to develop large, well-defined trap arrays with complex 3D electrode structures. Our current goal is to implement key procedures and perform critical measurements that justify incorporation of 3D-printed traps into large-scale quantum computing efforts. En route, we recently realized trapping in horizontal traps that are operating at cryogenic temperatures.
74 ATOMIC AND MOLECULAR PHYSICS↗
Chapter 13: Time-of-Flight Secondary-Ion Mass Spectrometry and Atom Probe Tomography
Time-of-flight secondary-ion mass spectrometry (TOF-SIMS) and atom probe tomography (APT) have many similarities. Both detect the chemical makeup of a solid material at ppm or better sensitivity, while retaining the spatial location information from the signal. Both use a similar principle to measure a signal associated with a given charged secondary ion—the flight time it takes a secondary ion to reach the detector after it is generated. Both are destructive techniques—albeit destructive of very small volumes—because the signal measured is generated by the removal of material from the sample itself. Importantly, both techniques require ultra-high vacuum (UHV) to ensure that the secondary ions, once generated, can reach the detector without collision with other atoms in the gas phase. In the case of TOF-SIMS, the samples can vary from several mm to several inches in size, whereas for APT, the samples are cones several hundred microns in size that are prepared in a special manner (covered in detail later in the chapter). We will discuss the basic fundamentals of each technique and cover several examples of the technique applied to photovoltaic materials, which should give a good idea of the types of information one can gain from TOF-SIMS and APT and how they are complementary as they both operate at different length scales: at the hundreds of microns to hundreds of nanometer scale for TOF-SIMS and at the nanometer to a few angstroms scale for APT.
41 EE - Solar Energy Technologies Office (EE-4S)↗
A crystal plasticity finite element method modeling of Zircaloy with hydride phases based on scanning electron micrographs
This work developed a microstructure-based finite element model to predict the stress state of alloys with second phase inclusions. Quantitative microstructural details extracted from scanning electron microscopy (SEM) images were used to generate heterogeneous microstructures including the morphology and spatial distribution of hydrides. Generation of digital microstructure was achieved through two steps of tessellations using software Neper and Matlab. The process is demonstrated using an example of Zircaloy material with secondary phases of hydrides dispersed within and stress-strain response of Zircaloy containing hydrides was predicted. The constitutive material model for Zircaloy in this study was based on crystal plasticity theory which considers the hexagonal close-packed (HCP) atomic structure of Zircaloy material. The hydrides were modeled as isotropic elasto-plastic material. A parametric study had been conducted to understand the effect of volume fraction, and lamellae thickness of the hydride phase on the mechanical properties of the overall material. Results can help designers to alter the manufacturing process to obtain the enhanced mechanical properties for components used in nuclear applications made by Zircaloy material.
Kulkarni, Shank S.↗
A Finite Element Method for Compressible and Turbulent Multiphase Flow Instabilities with Heat Transfer
We present a new finite element framework for modeling compressible, turbulent multiphase flows with heat transfer. For two-fluid systems with a free surface, the Volume of Fluid (VOF) method is implemented without the need for interface reconstruction, while turbulence is resolved using a dynamic Vreman large eddy simulation (LES) model. Unlike most two-phase VOF studies, which neglect heat transfer, the present approach incorporates energy transport equations within the VOF formulation to account for heat exchange, an effect particularly important in turbulent flows. Conjugate heat transfer is often challenging in finite volume methods, which require explicit specification of heat fluxes at the solid–fluid interface, limiting accuracy and predictive capability. By contrast, the finite element formulation does not require heat flux inputs, allowing more accurate and robust simulation of heat transfer between solids and fluids. The method is demonstrated through three representative cases. First, a two-fluid instability with a single-mode perturbation is simulated and validated against analytical growth rates. Second, conjugate heat transfer is examined in a high-temperature flow over a cold metal cylinder, with validation performed both quantitatively—via pressure coefficient comparisons with experimental data—and qualitatively using vector field topology. Finally, compressible spray injection and breakup are modeled, demonstrating the ability of the framework to capture interfacial dynamics and atomization under turbulent, high-speed conditions. In the compressible spray injection and breakup case, the results indicate that the finite element formulation achieved higher predictive accuracy and robustness than the finite-volume method. With the same mesh resolution, the FEM reduced the root mean square error (RMSE) and mean absolute percentage error (MAPE) from 6.96 mm and 26.0% (for the FVM) to 4.85 mm and 12.7%, respectively, demonstrating improved accuracy and robustness in capturing interfacial dynamics and heat transfer. The study also introduced vector field topology to visualize and interpret coherent flow structures and instabilities, offering insights beyond conventional scalar-field analyses.
97 MATHEMATICS AND COMPUTING↗
ORNL_AISD_NiPt
This dataset describes the nickel-platinum (NiPt) solid solution binary alloy, where the two constituent elements nickel (Ni) and platinum (Pt) are randomly placed on the face centered cubic (FCC) crystal structure, with the lattice constant of 3.840 angstroms. The dataset comprises data for three different sizes of the crystal structure: 256 atoms, 864 atoms, and 2,048 atoms, each of which contains 1900 configurations. For each size of the crystal structure, the data set was generated for concentrations ranging from 0at% of Pt to 100at% of Pt in the NiPt binary system, with increasing the concentration of Pt in the system every 5at%. For each one of the chemical compositions, 100 random configurations were generated, each with a different random seed. Each of the output files contains the mass, type, atomic coordinates, energy per atom, and forces in x, y, and z directions respectively. For each atomic configuration, the output was collected every 150 steps during the minimization stage and every 1000 steps during the replica exchange stage. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) [1], which is a molecular dynamics code, was used to generate data for NiPt alloy. The simulation used the interatomic potential for NiPt binary system MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [3] from the OpenKIM library (Open Knowledgebase of Interatomic Models) [2]. This potential was developed based on the second nearest-neighbor modified embedded-atom method (2NN MEAM). The simulation process begins with the generation of the random NiPt structure and follows with the short minimization and replica exchange simulation. The minimization procedure adjusts atomic coordinates and performs energy minimization, which typically leads to a local potential energy minimum. The method used for the minimization was the conjugate gradient algorithm. A short replica exchange (parallel tempering) simulation involves four replicas (ensembles) of a system and follows the minimization stage. Multiple snapshots of the configuration were collected during the minimization and replica exchange stages. NiPt alloy is interesting due to its magnetic and charge transfer properties [4]. The data is provided in three compressed zipped folders: atoms256.zip, atoms864.zip, atoms2048.zip Each zipped folder contains the data that describes crystals of size 256 atoms, 864 atoms, and 2,048 atoms respectively. Each one of the three zipped folders contains the data structured in the following way: -Ni_ground_state.cfg --> atomic configuration for the pure nickel -Pt_ground_state.cfg --> atomic configuration for the pure platinum -Pt#_filtered --> folders containing atomic configurations for #at% concentration of platinum. The folder contains 100 atomic configurations, each saved in a subfolder. Each subfolder named config* is associated with a specific atomic configuration. Each of these subfolders contains files with .cfg format, corresponding to outputs for each atomic configuration The total number of atomic configurations contained in atoms256.zip is 65,046. The total number of atomic configurations contained in atoms864.zip is 63,936. The total number of atomic configurations contained in atoms2048.zip is 61,997. The total number of atomic configurations spanned by the entire dataset is 190,979. References [1] https://www.lammps.org/ [2] https://openkim.org/ [3] https://openkim.org/id/MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [4] El-Gendy, Ahmed A. and Hampel, Silke and Büccchner, Bernd and Klingeler, Rüdiger, Tuneable magnetic properties of carbon-shielded NiPt-nanoalloys, RSC Adv., volume 6, issue 57, pages 52427-52433, 2016, The Royal Society of Chemistry, doi:10.1039/C6RA05910D
36 MATERIALS SCIENCE↗
First Principles Simulations of Electrified Interfaces in Electrochemistry
This chapter discusses some of the recent advances made in the first principles modeling of electrochemical catalysts. It also discusses the key development, namely the ability to explicitly treat the effects of surface electrification due to electrochemical processes and applied voltages in a computationally efficient manner. The chapter introduces the thermodynamics and statistical mechanics of electrified metal-solution interfaces. It then discusses the structure of the electrode-electrolyte interface and the effects of applied voltages, followed by an overview of the first-principles model and a motivating example. The chapter also provides a brief summary of classical thermodynamics and describes the basics of thermodynamic detour. It considers the thermodynamics of macroscopic systems and introduces several useful fundamental relations. Here, the chapter also considers a system to exist in a certain macrostate, which is a particular thermodynamic state specified by a set of fixed properties such as constant particle number, constant volume, and constant temperature.
36 MATERIALS SCIENCE↗