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At least 271 records · Page 15

Revealing two-stage phase transition process in defective KTaO 3 under inelastic interactions

Here, the interactions of ions with defective KTaO 3 has been studied by irradiating pre-damaged single crystal KTaO 3 with 5 MeV C, 7 MeV Si and 12 MeV O ions at 300 K. By exploring these processes in KTaO 3 , the results show that, for a pre-damaged fractional disorder level of 0.3 and inelastic electronic energy loss, S e , ≥ 4.65 keV/nm (7 MeV Si ions), the synergistic interaction of Se with defects enables amorphous ion track creation. At lower values of S e (5 MeV C and 12 MeV O), minor increases in disorder are observed initially over a region of depth at an ion fluence of 10 ions/nm 2 , which may be due to dissolution of pre-existing interstitial or amorphous clusters; however, with further increase in ion fluence, a transition from irradiation-induced disorder production to ionization-induced damage recovery processes, not previously reported in KTaO 3 , is observed.

36 MATERIALS SCIENCE↗

Baryon preclustering at the freeze-out of heavy-ion collisions and light-nuclei production

Following the idea of nucleon clustering and light-nuclei production in relativistic heavy-ion collisions close to the QCD critical-end point, we address the quantum effects affecting the interaction of several nucleons at finite temperature. For this aim we use the $\textit{K}$-harmonics method to four-nucleon states (α particle), and also develop a novel semiclassical “flucton” method at finite temperature, based on certain classical paths in Euclidean time, and apply it to two- and four-particle configurations. To study possible effects on the light-nuclei production close to the QCD critical point, we also made such calculations with modified internuclear potentials. For heavy-ion experiments, we propose new measurements of light-nuclei multiplicity ratios which may show enhancements due to baryon preclustering. Further, we point out the special role of the $\mathcal{O}$(50) four-nucleon excitations of α -particle, feeding into the final multiplicities of $\textit{d, t,}$ 3 He, and 4 He, and propose to directly look for their two-body decays.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A machine learning study on spinodal clumping in heavy ion collisions

Possible observables of baryon number clustering due to the instabilities occurring at a first order QCD phase transition are discussed. The dynamical formation of baryon clusters at a QCD phase transition can be described by numerical fluid dynamics, augmented with a gradient term and an equation of state with a mechanically unstable region. It is shown that the dynamical description of this phase transition, in nuclear collisions, will lead to the formation of dense baryon clusters at the phase boundary. State-of-the-art machine learning methods find that the coordinate space clumping leaves characteristic imprints on the spatial net density distribution in almost every event. On the other hand the momentum distributions do not show any clear event-by-event features. Lastly, it is shown that the 'third order' cumulant, the skewness, shows a peak at the beam energy where the system, created in the heavy ion collision, reaches the deconfinement phase transition.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A reaction mechanism for plasma electrolysis of AgNO 3 forming silver nanoclusters and nanoparticles

In plasma-driven solution electrolysis (PDSE), gas-phase plasma-produced species interact with an electrolytic solution to produce, for example, nanoparticles. An atmospheric pressure plasma jet (APPJ) directed onto a liquid solution containing a metallic salt will promote reduction of metallic ions in solution, generating metallic clusters that nucleate to form nanoparticles. In this article, results from a computational investigation are discussed of a PDSE process in which a radio-frequency APPJ sustained in helium impinges on a silver nitrate solution, resulting in growth of silver nanoparticles. A reaction mechanism was developed and implemented in a global plasma chemistry model to predict nanoparticle growth. To develop the reaction mechanism, density functional theory was used to generate probable silver growth pathways up to Ag 9 . Neutral clusters larger than Ag 9 were classified as nanoparticles. Kinetic reaction rate coefficients for thermodynamically favorable growth pathways were estimated based on an existing, empirically determined base reaction mechanism for smaller Ag particle interactions. These rates were used in conjunction with diffusion-controlled reaction rate coefficients that were calculated for other Ag species. The role of anions in reduction of Agn ions in forming nanoparticles is also discussed. Oxygen containing impurities or admixtures to the helium, air entrainment into the APPJ, and dissociation of saturated water vapor above the solution can produce additional reactive oxygen species in solution, resulting in the production of anions and O 2 – in particular. For a given molarity, delivering a sufficient fluence of reducing species will produce similar nanoparticle densities and sizes for all applied power levels. In conclusion, comparisons are made to alternate models for nanoparticle formation, including charged nanoparticles and use of direct current plasmas.

36 MATERIALS SCIENCE↗

Phase-Slip Lines and Anomalous Josephson Effects in Tungsten Nanoscale Cluster-Based Topological Insulator Nanobridges: Implications for Topologically Protected Qubits and Quantum Sensors

Superconducting topological systems formed by a strong 3D topological insulator (TI) in proximity to a conventional s-wave superconductor (SC) have been intensely studied, as they may host Majorana zero modes. However, there are limited experimental realizations of TI-SC systems in which robust superconducting pairing is induced on the surface states of the TI and a topological superconducting state is established. Here, we fabricate a TI-SC system by depositing, via a focused ion beam, tungsten (W) nanoscale clusters on the surface of TI Bi 0.91 Sb 0.09 . We find that the resulting heterostructure supports phase-slip lines (PSLs) that act as effective Josephson junctions (JJs). Here, we probe the response of the system to microwave radiation. We find that for some ac frequencies, and powers, the resulting Shapiro steps’ structure of the voltage–current characteristic exhibits a missing first step and an unexpectedly wide second Shapiro step. The theoretical analysis of the measurements shows that the unusual Shapiro response arises from the interplay between a static JJ and a dynamic one and allows us to identify the conditions under which the missing first step can be attributed to the topological nature of the JJs formed by the PSLs. Our results suggest an approach to induce superconductivity in a TI, a route to realizing highly transparent topological JJs, and show how the response of superconducting systems to microwave radiation can be used to infer the dynamics of PSLs. Highly transparent topological junctions are promising candidates to realize vector field sensors with very high sensitivity. In addition, due to the nontrivial Berry phase of the TI’s surface states such junctions can be in a topological state which is ideal to create topologically protected qubits.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Mapping the Temperature-dependent and network site-specific onset of spectral diffusion at the surface of a water cluster cage

We explore the kinetic processes that sustain equilibrium in a microscopic, finite system. This is accomplished by monitoring the spontaneous, time-dependent frequency evolution (the frequency autocorrelation) of a single OH oscillator, embedded in a water cluster held in a temperature-controlled ion trap. The measurements are carried out by applying two-color, IR-IR photodissociation mass spectrometry to the D3O+?(HDO)(D2O)19 isotopologue of the “magic number” protonated water cluster, H+?(H2O)21. The OH group can occupy any one of the five spectroscopically distinct sites in the distorted pentagonal dodecahedron cage structure. The OH frequency is observed to evolve over tens of milliseconds in the temperature range (90-120 K). Starting at 100 K, large “jumps” are observed between two OH frequencies separated by ~300 cm-1 indicating migration of the OH group from the bound OH site at 3350 cm-1 to the free position at 3686 cm-1. Increasing the temperature to 110 K leads to partial interconversion among many sites. All sites are observed to interconvert at 120 K such that the distribution of the unique OH group among them adopts the form one would expect for a canonical ensemble. The spectral dynamics displayed by the clusters thus offer an unprecedented view into the molecular-level processes that drive spectral diffusion in an extended network of water molecules.

Yang, Nan↗

Insights into palladium poisoning of Cu/SSZ-13 selective catalytic reduction catalysts

Here, the impacts of Pd poisoning to the activity, selectivity, and hydrothermal stability of Cu/SSZ-13 selective catalytic reduction (SCR) catalysts are reported. Pd lowers DeNOx efficiency of Cu/SSZ-13 via two mechanisms: (1) displacing SCR active sites in the form of isolated Pd-ions, and (2) catalyzing non-selective NH 3 oxidation in the form of PdO. The first mechanism works by the diffusion of isolated Pd-ions into chabazite cages to displace ZCu II OH SCR active species, and it occurs on Cu/SSZ-13 catalysts with and without external surface CuO clusters in similar fashion. In contrast, the second mechanism works differently with and without external surface CuO clusters. For Cu/SSZ-13 catalyst without external CuO clusters (i.e., primarily isolated Cu-ions), PdO leads to significant decrease of DeNOx efficiency at reaction temperatures above ~400°C due to its non-selective NH 3 oxidation activity at high temperatures. However, this poisoning effect becomes much less impactful on Cu/SSZ-13 catalyst containing CuO clusters. This is due to the formation of CuO-PdO solid solution via interactions between CuO and PdO, which reduces non-selective NH 3 oxidation potential. Furthermore, this solid solution formation even mitigates adverse effects caused by hydrothermal aging. Hence, the poisoning effects of Pd are closely related to Cu speciation and spatial distribution of a Cu/SSZ-13 catalyst. Finally, this study suggests a strategy in eliminating Pd poisoning, that is, the introduction of an oxide phase that effectively traps PdO but does not adversely influence SCR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular-level insights into structure and dynamics in ionic liquids and polymer gel electrolytes

We report designing new electrolytes requires a better understanding of the correlation between their transport properties and their molecular structure. In this work, we present a detailed study of ionic liquids and polymer gel electrolytes probing their structure and dynamics by nuclear magnetic resonance (NMR) spectroscopy. In particular, ammonium- and phosphonium-based ionic liquids (ILs) are combined with different LiTFSI concentrations, and then with different ratios of poly(methylmethacrylate) polymer. The temperature dependence of self-diffusion coefficients of mobile species, D Li+ , D TFSI- and D P4441+ or D N4441+ , measured by pulsed field gradient (PFG) NMR spectroscopy obeys the Arrhenius equation. Diffusivity of [P4441][TFSI] ILs is found to be greater than those of the [N4441][TFSI] ILs in both liquid and gel electrolytes. Solid state NMR experiments including 13 C and 19 F MAS, 13 C{ 19 F}, 13 C{ 1 H} CPMAS probe the local structure and molecular-level interactions between ions and polymer in gel electrolytes, particularly for samples with higher PMMA content (≥25 wt%). Finally, the fast field cycling relaxometry has been used to unveil the rotational and translational dynamics of P4441 + or N4441 + and TFSI - by measuring 1 H and 19 F R 1 relaxation rate profiles at different temperatures. A comprehensive NMR analysis including relaxation studies at low magnetic field provides decisive new insights regarding the formation of ionic clusters and the interaction of ions with the polymer chain in the case of the gel electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Model ionospheres of Jupiter

The principal concepts presently involved in modeling the Jovian ionosphere are reviewed. A model ionosphere is developed on the basis of our present knowledge of atmospheric composition, relevant chemical and ion-molecule reactions, with their associated rate constants. The shortcomings of this model are discussed when it is compared with the electron density profile obtained from the Pioneer 10 radio occultation data. It is demonstrated that the apparent great extent of the observed topside ionosphere may imply a hot thermosphere, as if Jupiter sustained a corona. Some of the layers observed in the electron density profile may be due to sporadic-E like clustering of protons and other ions.

Atreya, S. K.↗

The Relationship between Ionic Conductivity and Solvation Structures of Localized High-Concentration Fluorinated Electrolytes for Lithium-Ion Batteries

Localized high concentration electrolyte (LHCE) combines a diluent with high concentration electrolyte (HCE), offering promising properties. The ions, solvent, and diluent interact to form a complex heterogenous liquid structure, where high salt concentration clusters are embedded in diluent. Optimizing LHCE for desired electrolyte properties like high ionic conductivity, low viscosity, effective solid electrolyte interphase (SEI) formability, within the vast chemical and compositional design space requires deeper understanding and theoretical guidance. For this work, we investigated the structures and conductivity of LHCEs based on a fluorinated solvent with two different diluents at varying concentrations. The 2,2,3,3-tetrafluoropropyl trifluoroacetate (TFPTFA) enters the solvation cluster due to its stronger Li-ion interactions, whereas 1,1,2,2-tetrafuoroethyl 2,2,2-trifuoroethyl ether (TFETFE) enters only at extremely high diluent concentrations. The ionic conductivity increases with decreasing diluent concentrations, with a slope change during cluster percolation. Overall, TFETFE demonstrates higher effectiveness than TFPTFA, forming higher local salt concentration clusters, and resulting in higher ionic conductivity.

cluster chemistry↗

Catalyst design for small molecule activation of energy consequence

This project targets the conversion of ubiquitous small molecules (e.g. NO, CO, H 2 O) into viable precursors to synthetic fuels. Current state of the art catalyst design has not directly targeted transition metal complexes capable of mediating the multi-electron redox processes necessary to reduce the overpotential (energy loss) required achieve efficient activation of small molecule substrates. In this vein, a new strategy has been developed for the assembly of polynuclear architectures; allowing for the construction of tunable polymetallic centers that assemble easily within a pre-organized template (conferring stability, selectivity and tunability) that can effect multi-electron redox processes for reactions. Catalyst development has commenced with the following target design elements: (1) catalysts featuring multiple transition metal ions in the same reaction space to greatly expand accessible molecular redox capabilities; (2) catalysts are assembled in a polynucleating ligand framework that permits control over the cluster morphology as well as the local steric and electronic environment of the transition metal ions within the cluster. The high-tunability of the catalyst composition (metal content) and geometric flexibility has permitted a rigorous assessment of electronic-structure-to-function relationship to be developed, further guiding synthetic efforts to realize more potent catalysts. The numerous permutations possible showcase the high degree of generality to this approach with many synthetic handles to tune redox and reaction chemistry. Trinuclear complexes have been synthesized featuring homo- and hetero-trinuclear cores featuring a variety of first row transition metal ions (Cr→Ni). The molecular clusters have been shown to successfully mediate multi-electron redox processes in a cooperative fashion without requiring strong chemical reductants or oxidants. The reactive molecular complexes are being utilized to activate and breakdown the robust bonds within typical waste stream small molecules (e.g., greenhouse gases) and convert them into value-added commodity chemicals. Ultimately, the catalysts developed by this approach will be required to convert energy acquired via renewable resources (e.g., solar or wind) into synthetic fuels as an energy storage mechanism.

10 SYNTHETIC FUELS↗

Ultraviolet gas absorption and dust extinction toward M8

Interstellar absorption lines are analyzed using high-resolution IUE spectra of 11 stars in the young cluster NGC 6530 located in the M8 region. High-velocity clouds at -35 km/s and -60 km/s are seen toward all cluster stars. The components arise in gases that are part of large interstellar bubbles centered on the cluster and driven by stellar winds of the most luminous members. Absorption lines of species of different ionization states are separated in velocity. The velocity stratification is best explained as a 'champagne' flow of ionized gas away from the cluster. The C IV/Si IV ratios toward the hotter cluster members are consistent with simple photoionization models if the gas-phase C/Si ratio is increased by preferential accretion onto dust grains. High ion column densities in the central cluster decline with distance from W93, suggesting that radiation from a hot source near W93 has photoionized gas in the central cluster.

Boggs, Don↗

Computationally Guided and Experimentally Validated Design of Custom Chelators for Critical Mineral Recovery

Selective, high throughput separation of target critical metals from complex environments such as fly ash leachates and mining process streams presents a significant challenge for economical production. Custom chelators and sorbents are an attractive technology for selective metal extraction, however it can be difficult to predict their performance, and significant experimental efforts are often required to develop chelating technologies. Here, we present a computational strategy focused on modelling chelator-metal binding interactions and benchmark these results versus experimental data. A computational pipeline combining forcefield, semiempirical, and meta-GGA methods with a thermodynamic framework optimized for error cancellation has been developed to predict binding energies of chelator complexes towards critical mineral recovery applications. This approach, originally validated on [2.2.2] cryptates binding mono- and divalent cations, demonstrated robust predictive capabilities with an R2 of 0.850 against experimental aqueous binding energies. The workflow includes metadynamics for exploring high-dimensional potential energy surfaces and a cluster-continuum model for accurate yet computationally efficient solvation modeling. Error cancellation between solvation energies of free and chelator-coordinated ions enables faster convergence, even with finite cluster sizes. Initial studies on the cryptates revealed consistent metal-ligand coordination patterns, with systematic variations influenced by ion size and charge, highlighting key structural features linked to binding selectivity. Further studies of a proprietary chelator have resulted in identification of previously unreported selectivity towards economically significant metals, which in-house experiments have confirmed, demonstrating the feasibility of this approach. By applying this methodology to new chelators targeting critical minerals such as lithium, cobalt, nickel and other strategic metals, we aim to accelerate the discovery of next-generation chelators for efficient recovery, recycling, and separation processes. This computational framework serves as the backbone of a high-throughput design pipeline tailored for sustainable resource utilization and may be applied to a wide range of systems to meet experimental needs.

computational materials↗

The structure of small metal clusters

One metal atom surrounded by its 12 nearest neighbors is considered for both D(3d) (face-centered cubic-like) and D(3h) (hexagonal close-packed-like) geometries. For Al and Be, the neutral cluster and the positive and negative ions are considered for idealized (all bonds equal) and distorted geometries. The D(3d) geometry is found to be the lowest for Be13, while the D(3h) geometry is lower for Al13. This is the reverse of what is expected based upon the bulk metal structures, Be(hcp) and Al(fcc). Al13 is found to have only small distortions, while Be13 shows large distortions for both the D(3d) and D(3h) geometries. The ions have geometries which are similar to those found for the neutral systems. Both all-electron and effective core potential calculations were carried out on the X13 clusters; the agreement is very good.

Bauschlicher, C. W., Jr.↗

GCR Transport in the Brain: Assessment of Self-Shielding, Columnar Damage, and Nuclear Reactions on Cell Inactivation Rates

Radiation shield design is driven by the need to limit radiation risks while optimizing risk reduction with launch mass/expense penalties. Both limitation and optimization objectives require the development of accurate and complete means for evaluating the effectiveness of various shield materials and body-self shielding. For galactic cosmic rays (GCR), biophysical response models indicate that track structure effects lead to substantially different assessments of shielding effectiveness relative to assessments based on LET-dependent quality factors. Methods for assessing risk to the central nervous system (CNS) from heavy ions are poorly understood at this time. High-energy and charge (HZE) ion can produce tissue events resulting in damage to clusters of cells in a columnar fashion, especially for stopping heavy ions. Grahn (1973) and Todd (1986) have discussed a microlesion concept or model of stochastic tissue events in analyzing damage from HZE's. Some tissues, including the CNS, maybe sensitive to microlesion's or stochastic tissue events in a manner not illuminated by either conventional dosimetry or fluence-based risk factors. HZE ions may also produce important lateral damage to adjacent cells. Fluences of high-energy proton and alpha particles in the GCR are many times higher than HZE ions. Behind spacecraft and body self-shielding the ratio of protons, alpha particles, and neutrons to HZE ions increases several-fold from free-space values. Models of GCR damage behind shielding have placed large concern on the role of target fragments produced from tissue atoms. The self-shielding of the brain reduces the number of heavy ions reaching the interior regions by a large amount and the remaining light particle environment (protons, neutrons, deuterons. and alpha particles) may be the greatest concern. Tracks of high-energy proton produce nuclear reactions in tissue, which can deposit doses of more than 1 Gv within 5 - 10 cell layers. Information on rates of cell killing from GCR, including patterns of cell killing from single particle tracks. can provide useful information on expected differences between proton and HZE tracks and clinical experiences with photon irradiation. To model effects on cells in the brain, it is important that transport models accurately describe changes in the GCR due to interactions in the cranium and proximate tissues. We describe calculations of the attenuated GCR particle fluxes at three dose-points in the brain and associated patterns of cell killing using biophysical models. The effects of the brain self-shielding and bone-tissue interface of the skull in modulating the GCR environment are considered. For each brain dose-point, the mass distribution in the surrounding 4(pi) solid angle is characterized using the CAM model to trace 512 rays. The CAM model describes the self-shielding by converting the tissue distribution to mass-equivalent aluminum, and nominal values of spacecraft shielding is considered. Particle transport is performed with the proton, neutron, and heavy-ion transport code HZETRN with the nuclear fragmentation model QMSFRG. The distribution of cells killed along the path of individual GCR ions is modeled using in vitro cell inactivation data for cells with varying sensitivity. Monte Carlo simulations of arrays of inactivated cells are considered for protons and heavy ions and used to describe the absolute number of cell killing events of various magnitude in the brain from the GCR. Included are simulations of positions of inactivated cells from stopping heavy ions and nuclear stars produced by high-energy ions most importantly, protons and neutrons.

Shavers, M. R.↗

Unexpected Hydroxide Ion Structure and Properties at Low Hydration

Understanding the behavior of hydroxide ions in aqueous and non-aqueous media is fundamental to many chemical, biological, and electrochemical processes. Research has primarily focused on a single fully solvated hydroxide ion, either as an isolated cluster or in bulk. This work presents the first computational study to consider hydroxide under low hydration levels in detail, where the anion may not be fully solvated. Under such conditions, we find that the anions are predominantly present as unique water-bridged hydroxide pair complexes, distinct from previously reported structures under fully hydrated conditions. Although similar hydroxide pair structures were previously reported, we analyze these structures for the first time in the disordered liquid state where they are found to be unusually stable in the presence of bulky quaternary ammonium cations. Our findings help explain the unusual diffusion behavior as well as the higher reactivity of hydroxide anions observed under low hydration conditions.

computational studies↗

Permutationally Invariant Networks for Enhanced Sampling (PINES): Discovery of Multimolecular and Solvent-Inclusive Collective Variables

The typically rugged nature of molecular free energy landscapes can frustrate efficient sampling of the thermodynamically relevant phase space due to the presence of high free energy barriers. Enhanced sampling techniques can improve phase space exploration by accelerating sampling along particular collective variables (CVs). A number of techniques exist for data-driven discovery of CVs parameterizing the important large scale motions of the system. A challenge to CV discovery is learning CVs invariant to symmetries of the molecular system, frequently rigid translation, rigid rotation, and permutational relabeling of identical particles. Of these, permutational invariance has proved a persistent challenge in frustrating the data-driven discovery of multi-molecular CVs in systems of self-assembling particles and solvent-inclusive CVs for solvated systems. In this work, we integrate Permutation Invariant Vector (PIV) featurizations with autoencoding neural networks to learn nonlinear CVs invariant to translation, rotation, and permutation, and perform interleaved rounds of CV discovery and enhanced sampling to iteratively expand sampling of configurational phase space and obtain converged CVs and free energy landscapes. Here, we demonstrate the Permutationally Invariant Network for Enhanced Sampling (PINES) approach in applications to the self-assembly of a 13-atom Argon cluster, association/dissociation of a NaCl ion pair in water, and hydrophobic collapse of a C 45 H 92 n-pentatetracontane polymer chain. We make the approach freely available as a new module within the PLUMED2 enhanced sampling libraries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermophysical Properties of NaCl–UCl 3 –PuCl 3 Molten Salts: A Combined Computational and Experimental Study

Actinide-bearing molten salts for use as fuels are an essential part of next generation molten salt reactors. Yet, numerous multicomponent salt mixtures are underdeveloped or have not been investigated. Here, this study, based on a combination of experimental and modeling techniques, is dedicated to determining and understanding a variety of properties of the ternary system of NaCl–UCl 3 –PuCl 3 , which represents a scenario for burnup of NaCl–UCl 3 fuel, at two compositions (∼10 and 5 mol % PuCl 3 in eutectic NaCl–UCl 3 pseudobinary) and a range of temperatures. Evaluation of the heat flow and mass loss data showed the 0.61NaCl–0.30UCl 3 –0.09PuCl 3 salt had a melting temperature of 551 ± 5 °C. Two additional thermal effects were observed occurring at approximately 410 and 494 °C. The transition occurring at 410 °C may be due to the presence of oxide in the salt. Extrapolation of thermodynamic data indicates the transition occurring at 494 °C is due to the formation of a liquid phase. Experimental testing determined the density of this system is a linear function of temperature and can be represented by the equation ρ = 4.014–0.0010T(°C), R 2 = 0.992. Additionally, by using atomistic modeling, we found that increasing the PuCl 3 content from 5 to 10 mol % led to the formation of larger Pu 3+ clusters and slower transport of ions.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗