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At least 325 records · Page 18

Exploring NaCl-PuCl 3 molten salts with machine learning interatomic potentials and graph theory

Actinide molten salts are the basis of the liquid fuels used in molten salt reactors. Due to the inherent difficulties associated with high temperature and hazardous conditions, experimental investigations of fundamental properties of these materials are usually challenging. In this work, we describe the structure and transport of NaCl-PuCl 3 mixtures using computational techniques. Three compositions were considered (16, 25, and 36 mol% PuCl 3 ) over a temperature range (730 – 1257K) using ab initio molecular dynamics, which provided the necessary data sets for training machine learned interatomic potentials. Further, molecular dynamics simulations based on these potentials were then used to determine structure and transport properties. A substantial change was noted in the structure factor when increasing the PuCl 3 content from 25 to 36 mol%. This change is linked to the aggregation of larger Pu 3+ clusters. In addition, the similarity of the atomic environments of metal cations in molten salt systems to their solid states counterparts was investigated using an unsupervised learning technique. Finally, graph theory was employed to explore the structure and size of actinide networks. Consistent with the structure factor, a dense Pu 3+ intermolecular structure is observed within the 36 mol% PuCl 3 mixture. The structure of cation-cation inter-junctions is also discussed. In all cases, the diffusion of Pu 3+ is significantly lower than that of Na + and Cl - .

36 MATERIALS SCIENCE↗

Reversible motions and disordered structure of soft particles in amorphous solids

In amorphous solids, soft vibrational modes derived from normal mode analysis can be utilized to identify the soft particles that are prone to irreversible rearrangements. However, the normal mode analysis approach cannot explain why the spatial distributions of clustered soft particles do not change over time. We define a softness parameter based on the vibrational density of states calculated directly from molecular dynamics simulations with both the harmonic vibrations and anharmonic relaxations being properly captured at finite temperatures. This parameter spontaneously correlates with the real space atomic motions and the dynamics heterogeneity. Using the softness parameter, we show that the softest particles are confined within rigid cages. These particles keep rearranging reversibly without long-range diffusion. The moderately soft particles rearrange irreversibly, and the hard particles mainly participate in vibrations without rearrangement. Here, we also show that the soft particles form locally disordered structures, while the hard particles present strong ordering. These findings confirm the defective nature of soft particles, and provide insights on the nature of softness as the ability to rearrange, but not necessarily irreversibly.

36 MATERIALS SCIENCE↗

Dynamics of deuterium retention and desorption from plasma-facing materials in fusion reactor-relevant conditions

Hydrogen isotopes retention and desorption during and after discharges in fusion devices are still not well understood due to the complex device conditions and limitations of in-situ diagnostics and measurements. Here, we simulated well-diagnosed recent experiments at the DIII-D facility to benchmark our ITMC-DYN integrated package of modeling deuterium diffusion, retention, and desorption during and after D discharge irradiation. Modeling results were compared with detail experimental data of D desorption fluxes for various irradiation conditions. We predicted the temporal evolution of free and trapped D distribution in tungsten (W) plasma-facing material (PFM). Effects of key parameters namely diffusion coefficient, recombination rate, trapping energies against different defect types, were examined in these simulations. Existing experimental data of these parameters in literature varies significantly which makes it harder to identify key mechanisms and physics responsible for hydrogen isotope retention and desorption. The purpose of this work is to accurately simulate recent well-diagnosed reactor experiments given the uncertainties in such parameters and identify mechanisms responsible for the retention and desorption. We implemented the best identified diffusion, recombination, and trapping parameters in ITMC-DYN package that integrate both various collisional and thermal processes. We predicted, for example, that sample cooling between discharges in DIII-D operations can significantly affect the spatial distribution of trapped D in W under reactor irradiation conditions. Correct prediction of desorption spectra from samples irradiated during 10 DIII-D discharges showed that up to 35% of D can be retained in high binding energy defects such as vacancy clusters or voids.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Applying Magnetic Curvature to MMS Data to Identify Thin Current Sheets Relative to Tail Reconnection

Thin current sheets (TCSs) have been postulated to be a necessary precondition for reconnection onset. Magnetic reconnection X-lines in the magnetotail have been observed to be more common duskward of midnight. We take advantage of the MMS tetrahedral formation during the 2017–2020 MMS tail seasons to calculate the thickness of the cross-tail neutral sheet relative to ion gyroradius. While a similar technique was applied to Cluster data, current sheet thickness over a broader range of radial distances has not been robustly explored before this study. We compare our analysis to recent theories regarding mechanisms of tail current sheet thinning and to recent simulations. We find MMS spent more than twice as long in ion-scale TCSs in the pre-midnight sector than post-midnight, despite nearly even plasma sheet dwell time. The dawn-dusk asymmetry in the distribution of Ion Diffusion Regions, as previously reported in relation to regions of TCSs, is also analyzed.

79 ASTRONOMY AND ASTROPHYSICS↗

Constraining the Galactic bar using the M92 stellar stream

Stellar streams are excellent probes of the gravitational potential in which they evolve. In the Milky Way (MW), globular cluster (GC) streams are routinely used to infer properties about time-dependent perturbations of the underlying potential. This implies that streams with Galactocentric radii small enough to be perturbed by the MW bar should offer constraints on it, such as its pattern speed, which currently has a wide range of values reported in the literature and is important when studying stellar kinematics. The GC M92 has a small pericentre and should be affected by the bar. It has a diffuse stellar stream, but confirming stream members has previously been hindered by a lack of spectroscopic data. In this paper, we use Dark Energy Spectroscopic Instrument (DESI) observations together with photometric and astrometric data to obtain spectroscopic members of the M92 stream for the first time. We identify a clear spatial distribution and gradients in distance moduli, proper motions, and radial velocities that confirm the stream's existence. We compare the observed stream to mock streams generated in different barred potentials and estimate the MW bar's pattern speed $Ω= 29.1^{+0.7}_{-0.4}$ km s$^{-1}$ kpc$^{-1}$ and $\dot Ω= 0.7^{+3.5}_{-2.3}$ km s$^{-1}$ kpc$^{-1}$ Gyr$^{-1}$. This is the first time a stellar stream is used to probabilistically infer these bar properties, and it opens up an exciting realm of inner Galactic potential characterisation using stellar streams.

Byström, Amanda [Edinburgh U., Inst. Astron.] (ORC↗

Stellar splashback: the edge of the intracluster light

We examine the outskirts of galaxy clusters in the C-EAGLE simulations to quantify the ‘edges’ of the stellar and dark matter distribution. The radius of the steepest slope in the dark matter, commonly used as a proxy for the splashback radius, is located at $\sim \, r_{200 \rm m}$; the strength and location of this feature depends on the recent mass accretion rate, in good agreement with previous work. Interestingly, the stellar distribution (or intracluster light, ICL) also has a well-defined edge, which is directly related to the splashback radius of the halo. Thus, detecting the edge of the ICL can provide an independent measure of the physical boundary of the halo, and the recent mass accretion rate. We show that these caustics can also be seen in the projected density profiles, but care must be taken to account for the influence of substructures and other non-diffuse material, which can bias and/or weaken the signal of the steepest slope. This is particularly important for the stellar material, which has a higher fraction bound in subhaloes than the dark matter. Finally, we show that the ‘stellar splashback’ feature is located beyond current observational constraints on the ICL, but these large projected distances (>> 1 Mpc) and low surface brightnesses (μ>>32 mag arcsec -2 ) can be reached with upcoming observational facilities such as the Vera C. Rubin Observatory, the Nancy Grace Roman Space Telescope, and Euclid.

79 ASTRONOMY AND ASTROPHYSICS↗

Cobalt Carbonyl Clusters Enable Independent Control of Two Proton Transfer Rates in the Mechanism for Hydrogen Evolution

Abstract Metal carbonyl clusters (MCC's) are atomically defined nanomaterials which can be characterized using the precise tools of molecular (electro)chemistry. HER mechanisms involve two proton transfer (PT) steps in the catalytic cycle. For HER catalyzed by [Co 11 C 2 (CO) 23 ] 3− ( 1 3− ), cyclic voltammetry measurements were used to determine the rate for PT1 as k PT1 =3×10 8 M −1 s −1 , whereas the rate for PT2 is k PT2 =3.7×10 3 M −1 s −1 . The fast, diffusion‐limited rate for PT1 is consistent with a previous report describing [Co 13 C 2 (CO) 24 ] 4− ( 2 4− ), with PT=2.9×10 9 M −1 s −1 . In both cases rate enhancement in PT1 is promoted by the many Co−Co bonds on the surface of the MCC that serve as PT sites: a statistical enhancement of rate akin to the effects of proton relays. In contrast, k PT2 varies and is five orders of magnitude slower for 1 2− compared with 2 4− . Thus, MCC's and nanomaterials offer an opportunity to enhance the rate for PT1 while maintaining thermochemical or kinetic control of PT2.

Pattanayak, Santanu↗

Observations of grain-boundary phase transformations in an elemental metal

The theory of grain boundary (the interface between crystallites, GB) structure has a long history 1 and the concept of GBs undergoing phase transformations was proposed 50 years ago 2,3 . The underlying assumption was that multiple stable and metastable states exist for different GB orientations 4,5,6 . The terminology ‘complexion’ was recently proposed to distinguish between interfacial states that differ in any equilibrium thermodynamic property 7 . Different types of complexion and transitions between complexions have been characterized, mostly in binary or multicomponent systems 8,9,10,11,12,13,14,15,16,17,18,19 . Simulations have provided insight into the phase behaviour of interfaces and shown that GB transitions can occur in many material systems 20,21,22,23,24 . However, the direct experimental observation and transformation kinetics of GBs in an elemental metal have remained elusive. In this work we demonstrate atomic-scale GB phase coexistence and transformations at symmetric and asymmetric $[11\bar{1}]$ tilt GBs in elemental copper. Atomic-resolution imaging reveals the coexistence of two different structures at Σ19b GBs (where Σ19 is the density of coincident sites and b is a GB variant), in agreement with evolutionary GB structure search and clustering analysis 21,25,26 . We also use finite-temperature molecular dynamics simulations to explore the coexistence and transformation kinetics of these GB phases. Our results demonstrate how GB phases can be kinetically trapped, enabling atomic-scale room-temperature observations. Our work paves the way for atomic-scale in situ studies of metallic GB phase transformations, which were previously detected only indirectly 9,15,27,28,29 , through their influence on abnormal grain growth, non-Arrhenius-type diffusion or liquid metal embrittlement.

36 MATERIALS SCIENCE↗

Carrier recombination and diffusion in high-purity diamond after electron irradiation and annealing

Carrier-transport mechanisms are studied in high-purity diamond irradiated with 6 MeV electrons in the dose range of 10 12 –10 16 cm -2 and annealed at different temperatures up to 1450°C. Lifetimes and diffusion coefficients are extracted using two pump–probe techniques based on free-carrier absorption and transient-grating principles and then correlated with the corresponding defect evolution from spectroscopic measurements. Furthermore, the neutral monovacancy is revealed as the main carrier recombination center in the as-irradiated diamond, providing bipolar carrier lifetimes of a few nanoseconds at the highest irradiation dose. Carrier-capture cross sections are reduced during annealing as vacancies aggregate into divacancies at ≤1000°C and extended vacancy clusters at 1450°C.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The role of irradiation-enhanced interstitial diffusion in over-pressurizing fission gas bubbles in UO 2

Fission gas bubbles in UO 2 nuclear fuel have been observed to exhibit pressures in excess of the equilibrium bubble pressure; however, the cause of bubble over-pressurization has not yet been demonstrated. The mechanical interaction between a bubble and the surrounding matrix or grain boundary depends on the internal pressure of the bubble and local stress state, such that over-pressurized bubbles are thought to be responsible for fragmentation and pulverization, when exposed to a temperature ramp. Here, in this work, we investigate the role of U interstitials, produced through irradiation, in over-pressurizing bubbles by using a combined molecular dynamics (MD) and cluster dynamics approach. Firstly, the energies for the capture of interstitials and vacancies by bubbles have been determined from MD as a function of the ratio of gas atoms to vacancies that make up the bubble. Secondly, these reaction energies have been implemented in the cluster dynamics code Centipede to predict bubble over-pressurization as a function of temperature for typical fission rates. It was found that there is a transition from low pressure bubbles (at high temperatures) to high pressure bubbles (at lower temperatures). The cause of this behavior was shown to be the creation of irradiation-induced interstitials that are highly mobile relative to vacancies at low temperature; whereas, vacancies are sufficiently mobile at high temperatures to limit bubble pressures. This result supports the hypothesis that over-pressurized bubbles form during steady-state operation and that this behavior is highly sensitive to the local pellet temperature.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Temporal and spatial separations between spin glass and short-range order

Broken-symmetry-induced order parameters account for many phenomena in physics. For spin glasses, this framework dictates the theoretical construction, whereas experiments have only established dynamical behaviors but not the physical entity. Experimental techniques have limitations when the spin glass is probed as an isolated state. Here, we create an evolution from a long-range order using well-controlled non-magnetic substitution on a sublattice. Neutron magnetic diffuse scattering of pico-second timescale reveals that the dynamics of short- and long-range order formation are not affected by disorder, but their spatial ranges are. Across all specimens, the inflection point of spin correlation length’s temperature dependence fully matches with the peak in heat capacity, while spin glass can freeze at millisecond timescale either above or below this characteristic temperature of spin-order formation. Our results identify the spin glass as single, uncorrelated spins at domain walls between spin clusters, and an uncorrelated coexistence of the two.

Dronova, Margarita G [Okinawa Institute of Science↗

The Effective Fragment Molecular Orbital Method: Achieving High Scalability and Accuracy for Large Systems

The effective fragment molecular orbital (EFMO) method has been developed to predict the total energy of a very large molecular system accurately (with respect to the underlying quantum mechanical method) and efficiently by taking advantage of the locality of strong chemical interactions and employing a two-level hierarchical parallelism. The accuracy of the EFMO method is partly attributed to the accurate and robust intermolecular interaction prediction between distant fragments, in particular, the many-body polarization and dispersion effects, which require the generation of static and dynamic polarizability tensors by solving the coupled perturbed Hartree–Fock (CPHF) and time-dependent HF (TDHF) equations, respectively. Solving the CPHF and TDHF equations is the main EFMO computational bottleneck due to the inefficient (serial) and I/O-intensive implementation of the CPHF and TDHF solvers. In this work, the efficiency and scalability of the EFMO method are significantly improved with a new CPU memory-based implementation for solving the CPHF and TDHF equations that are parallelized by either message passing interface (MPI) or hybrid MPI/OpenMP. Here, the accuracy of the EFMO method is demonstrated for both covalently bonded systems and noncovalently bound molecular clusters by systematically examining the effects of basis sets and a key distance-related cutoff parameter, R cut . R cut determines whether a fragment pair (dimer) is treated by the chosen ab initio method or calculated using the effective fragment potential (EFP) method (separated dimers). Decreasing the value of Rcut increases the number of separated (EFP) dimers, thereby decreasing the computational effort. It is demonstrated that excellent accuracy (<1 kcal/mol error per fragment) can be achieved when using a sufficiently large basis set with diffuse functions coupled with a small R cut value. With the new parallel implementation, the total EFMO wall time is substantially reduced, especially with a high number of MPI ranks. Given a sufficient workload, nearly ideal strong scaling is achieved for the CPHF and TDHF parts of the calculation. For the first time, EFMO calculations with the inclusion of long-range polarization and dispersion interactions on a hydrated mesoporous silica nanoparticle with explicit water solvent molecules (more than 15k atoms) are achieved on a massively parallel supercomputer using nearly 1000 physical nodes. In addition, EFMO calculations on the carbinolamine formation step of an amine-catalyzed aldol reaction at the nanoscale with explicit solvent effects are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nature of molybdenum carbide surfaces for catalytic hydrogen dissociation using machine-learned potentials: an ensemble-averaged perspective

Molybdenum carbides with an electronic structure similar to noble metals have gained attention as a promising low-cost catalyst for biomass valorization and the hydrogen evolution reaction. However, our fundamental understanding of the catalyst surface and how different phases of these catalysts behave at varying reaction conditions is limited to ground state density functional theory calculations as ab initio molecular dynamics (AIMD) is computationally prohibitive at relevant length and time scales. Here, in this work, we train a multi-atomic cluster expansion (MACE) machine-learned interatomic potentials (MLIP) to study hydrogen dissociation and dynamics over Mo, δ-MoC, α-Mo 2 C, and β-Mo 2 C surfaces at varying temperatures and hydrogen partial pressures. Our simulations identify unique and different molecular and atomic hydrogen adsorption sites on different surfaces that do not depend on the temperature. At low hydrogen pressures, the surface coverage is monolayer, which transitions to two-layer adsorption at higher pressures. We find that atomic hydrogen diffusion and recombinations are preferred over molybdenum atom hollow sites, while the diffusion over carbon-terminated facets was negligible, signifying particularly strong C–H interactions. In contrast, molecular hydrogen adsorption occurs mostly atop Mo or the bridging sites. At a comparable hydrogen loading, β-Mo 2 C (001) is the most active surface for hydrogen dissociation reaction. This work provides insights into the dynamic nature of the hydrogen dissociation chemistry and the diversity of hydrogen adsorption sites on molybdenum carbides.

08 HYDROGEN↗

A unique, ring-like radio source with quadrilateral structure detected with machine learning

ABSTRACT We report the discovery of a unique object in the MeerKAT Galaxy Cluster Legacy Survey (MGCLS) using the machine learning anomaly detection framework astronomaly. This strange, ring-like source is 30′ from the MGCLS field centred on Abell 209, and is not readily explained by simple physical models. With an assumed host galaxy at redshift 0.55, the luminosity (1025 W Hz−1) is comparable to powerful radio galaxies. The source consists of a ring of emission 175 kpc across, quadrilateral enhanced brightness regions bearing resemblance to radio jets, two ‘ears’ separated by 368 kpc, and a diffuse envelope. All of the structures appear spectrally steep, ranging from −1.0 to −1.5. The ring has high polarization (25 per cent) except on the bright patches (<10 per cent). We compare this source to the Odd Radio Circles recently discovered in ASKAP data and discuss several possible physical models, including a termination shock from starburst activity, an end-on radio galaxy, and a supermassive black hole merger event. No simple model can easily explain the observed structure of the source. This work, as well as other recent discoveries, demonstrates the power of unsupervised machine learning in mining large data sets for scientifically interesting sources.

Astronomy & Astrophysics↗

Fracture Network Quantification during CO2 Injection

This is the presentation prepared for the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗

Fracture Network Quantification during CO2 Injection

This is the conference paper accompanying an oral presentation at the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗

Influence of Al location on formation of silver clusters in mordenite

Formation of zeolite supported Ag 0 clusters depends on a combination of thermodynamically stable atomic configurations, charge balance considerations, and mobility of species on the surface and within pores. Periodic density functional theory (DFT) calculations were performed to evaluate how the location of Al in the mordenite (MOR) framework and humidity control Ag 0 nanocluster formation. Four Al framework sites were studied (T1-T4) and the Al positions in the framework were identified by the shifts in the differential Al…Al pair distribution function (PDF). Furthermore, structural information about the Ag 0 nanoclusters, such as dangling bonds, can be identified by Ag…Ag PDF data. For Ag 0 formation in vacuum MOR structures with a Si:Al ratio of 5:1 with Al in the T1 position resulted in the most framework flexibility and the lowest Ag 0 nanocluster charge, indicating the best result for formation of charge neutral nanoclusters. When water is present, Al in the T3 and T4 positions results in the formation of the smallest average Ag 0 nanoclusters plus greater expansion of the O-T-O bond angle than in vacuum, indicating easier diffusion of the Ag 0 nanoclusters to the surface. Here, the presence of Al in 4-membered rings and in pairs indicates favorable MOR structures for formation of single Ag atoms, despite the existence of synthesis challenges. Therefore, Al in the T2 position is the least favorable for Ag 0 nanocluster formation in both vacuum and in the presence of water. Al in the T1, T3, and T4 positions provides beneficial effects through framework flexibility and changes in nanocluster size or charge that can be leveraged for design of zeolites for formation of metallic nanoclusters.

36 MATERIALS SCIENCE↗

Direct Visualization of Magnetic Correlations in Frustrated Spinel ZnFe 2 O 4

Magnetic materials with the spinel structure (A 2+ B 3+ 2 O 4 ) form the core of numerous magnetic devices, and ZnFe 2 O 4 constitutes a peculiar example where the nature of the magnetism is still unresolved. Susceptibility measurements revealed a cusp around T c = 13 K resembling an antiferromagnetic transition, despite the positive Curie–Weiss temperature determined to be Θ CW = 102.8(1) K. Bifurcation of field-cooled and zero-field-cooled data below T c in conjunction with a frequency dependence of the peak position and a non-zero imaginary component below T c shows it is in fact associated with a spin-glass transition. Highly structured magnetic diffuse neutron scattering from single crystals develops between 50 K and 25 K revealing the presence of magnetic disorder which is correlated in nature. Here, the 3D-mΔPDF method is used to visualize the local magnetic ordering preferences, and ferromagnetic nearest-neighbor and antiferromagnetic third nearest-neighbor correlations are shown to be dominant. Their temperature dependence is extraordinary with some flipping in sign and a strongly varying correlation length. The correlations can be explained by orbital interaction mechanisms for the magnetic pathways and a preferred spin cluster. This study demonstrates the power of the 3D-mΔPDF method in visualizing complex quantum phenomena thereby providing a way to obtain an atomic-scale understanding of magnetic frustration.

36 MATERIALS SCIENCE↗