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At least 1,225 records · Page 68

Pt Nanoparticle Disintegration at Oxide Interfaces Enhances CO Oxidation Catalysis

Understanding how supported metal nanoparticles dynamically evolve under reaction conditions is critical for controlling their catalytic function. Here, the mechanism behind the dynamic disintegration of Pt nanoparticles (NPs) supported on CeOx-TiO2 (CT) during CO oxidation is elucidated, leading to the formation of single atoms (SAs) and/or sub-nanometer clusters. Density functional theory (DFT) calculations reveal that strong Pt-CO interactions weaken Pt─Pt cohesion, while electronic coupling between Pt and Ce ions stabilizes Pt-CO* intermediates at the oxide interface. Surface oxygen vacancies kinetically trap Pt-CO*, but the vacancies are replenished under oxygen-rich conditions, enabling Pt-CO* surface diffusion and subsequent structural reorganization. In situ spectroscopic analyses confirm the oxygen-driven transformation of Pt NPs, correlating with a threefold increase in mass-specific activity at 150 °C. These findings demonstrate that interfacial oxygen dynamics and metal-support interactions can be leveraged to induce nanoparticle disintegration and optimize catalytic performance, highlighting the catalytic potential of interface-engineered Pt nanostructures.

CO oxidation↗

Line operators, vortex statistics, and Higgs versus confinement dynamics

We study a 2+1D lattice gauge theory with fundamental representation scalar fields which has both Higgs and confining regimes with a spontaneously-broken U(1) 0-form symmetry. We show that the Higgs and confining regimes may be distinguished by a natural gauge invariant observable: the phase Ω of a correlation function of a vortex line operator linking with an electric Wilson line. We employ dualities and strong coupling expansions to analytically explore parameter regimes which were inaccessible in previous continuum calculations, and discuss possible implications for the phase diagram.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Spontaneous breaking of U(1) symmetry in coupled complex SYK models

As shown in [1], two copies of the large N Majorana SYK model can produce spontaneous breaking of a Z 2 symmetry when they are coupled by appropriate quartic terms. In this paper we similarly study two copies of the complex SYK model coupled by a quartic term preserving the U(1) x U(1) symmetry. We also present a tensor counterpart of this coupled model. When the coefficient α of the quartic term lies in a certain range, the coupled large N theory is nearly conformal. We calculate the scaling dimensions of fermion bilinear operators as functions of α. We show that the operator c$^†_{1i}$c 2i , which is charged under the axial U(1) symmetry, acquires a complex dimension outside of the line of fixed points. We derive the large N Dyson-Schwinger equations and show that, outside the fixed line, this U(1) symmetry is spontaneously broken at low temperatures because this operator acquires an expectation value. We support these findings by exact diagonalizations extrapolated to large N.

1/N expansion↗

Quark sivers function at small x: spin-dependent odderon and the sub-eikonal evolution

We apply the formalism developed earlier for studying transverse momentum dependent parton distribution functions (TMDs) at small Bjorken x to construct the small- x asymptotics of the quark Sivers function. First, we explicitly construct the complete fundamental “polarized Wilson line” operator to sub-sub-eikonal order: this object can be used to study a variety of quark TMDs at small x . We then express the quark Sivers function in terms of dipole scattering amplitudes containing various components of the “polarized Wilson line” and show that the dominant (eikonal) term which contributes to the quark Sivers function at small x is the spin-dependent odderon, confirming the re- cent results of Dong, Zheng and Zhou. Our conclusion is also similar to the case of the gluon Sivers function derived by Boer, Echevarria, Mulders and Zhou. We also analyze the sub-eikonal corrections to the quark Sivers function using the constructed “polarized Wilson line” operator. We derive new small- x evolution equations re-summing double-logarithmic powers of α s ln 2 (1 /x ) with α s the strong coupling constant. We solve the corresponding novel evolution equations in the large- N c limit, obtaining a sub-eikonal correction to the spin-dependent odderon contribution. We conclude that the quark Sivers function at small x receives contributions from two terms and is given by ${f}_{1T}^{\perp q}\left(x,{k}_T^2\right)={C}_O\left(x,{k}_T^2\right)\frac{1}{x}+{C}_1\left({k}_T^2\right){\left(\frac{1}{x}\right)}^0+\cdots$ with the function C O ( x, ${k}_T^2$) varying slowly with x and the ellipsis denoting the subasymptotic and sub-sub-eikonal (order- x ) corrections.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Strong Zeeman splitting in orbital-hybridized valleytronic interfaces

We report stacked heterointerfaces of two-dimensional (2D) materials are well-suited to obtain novel electronic functionality at small length scales, because the intrinsic properties of both materials can be blended by interlayer coupling with remarkable effects on the electronic band structure. In particular, band degeneracy at the K and K' Brillouin zone valleys of 2D materials can be broken by symmetry reductions by applying an external magnetic field, with possible application in valleytronic devices. Nevertheless, this usually requires impractically large external magnetic fields > 100 T. An alternative and more practical route is provided via stacking a non-centrosymmetric layered material on a magnetic substrate to induce valley splitting through the magnetic proximity effect; however, the splitting magnitude can vary sharply between similar interfaces. In this work, first-principle calculations are used to calculate the valley splitting of eight low-strain interfaces with transition metal dichalcogenides stacked on 2D magnetic substrates. It is shown that the interlayer band hybridization plays a major role when the two layers’ bands are closely aligned in energy, with the resulting band repulsion and the total valley splitting being strongly dependent on the Hubbard U correction , showing up to an order of magnitude change. The WSe 2 /CrGeTe 3 interface in particular shows strong interlayer interactions, which can potentially lead to a significantly high valley splitting of 26 meV; however further experimental investigations will be needed to resolve uncertainties in the predicted valley splitting.

36 MATERIALS SCIENCE↗

Dislocation-Limited Thermal Conductivity in LiF: Revisiting Perturbative Models

We revisit models to describe phonon-dislocation interactions and resulting dislocation-limited thermal conductivity (k), particularly as applied to describe the temperature-dependent k behavior of LiF with significant dislocation densities. Coupling semiempirical models of phonon scattering from dislocation strain fields provided by Klemens and Carruthers with density functional theory description of the phonons and input parameters, we find that both models significantly overpredict the measured k of LiF, as found previously. However, more direct application of the quantum perturbation theory description, from which the models were derived, gives significantly stronger phonon-dislocation scattering and strongly underpredicts the measured k data. We revisit the derivation of phonon-dislocation-strain field scattering and provide numerical details regarding its implementation. This work demonstrates that quantum perturbative calculations, now accessible to modern computational architectures, may provide a reasonable description of dislocation-limited k in materials as governed by phonon-strain field interactions provided that questions regarding the relevant strain field range can be resolved.

36 MATERIALS SCIENCE↗

Modeling discontinuous dynamic recrystallization containing second phase particles in magnesium alloys utilizing phase field method

Pre-existing second phase particles can induce particle stimulated nucleation (PSN) and pinning effect on grain boundaries during DRX process of magnesium alloys. The interaction among pinning effect, PSN mechanism and strain-induced grain boundary migration (SIBM) nucleation mechanism imposes challenge in quantitative study of microstructure evolution. A phase field model that describes discontinuous dynamic recrystallization process considering second phase particles (PF-DDRX-SP) which mainly distribute along grain boundaries is developed. The second phase order parameter with diffusion interface is introduced to the free energy function. With considering the pinning effect of second phase particles on grain boundaries, the grain boundary energy couples the interaction between second phase and grains. The effect of second phase on dislocation density evolution is considered in the model, and the PSN and SIBM mechanism are both executed by limiting the nucleation position to the grain boundary and the second phase interface. For the validation, the initial topology consistent with initial microstructure is applied to the simulation of DRX kinetics and flow behavior of AZ80 magnesium alloy, and great reliability and accuracy of developed model is indicated. Furthermore, through the model, the microstructure evolution with different particle size and with different volume fraction of round particle during DRX process were simulated. Finally, the results show that particles with higher dispersion reduce the number of DRX nuclei, which indicate that second phase particles suppress the nucleation at grain boundaries because of the pinning effect. More importantly, the proposed model could also quantitatively predict the relationships between the parameters of second phase particles and DRX behaviors, and enable to optimize the initial second phase structure in a uniform grain structure during thermomechanical process.

36 MATERIALS SCIENCE↗

Electrochemically induced fracture in LLZO: How the interplay between flaw density and electrostatic potential affects operability

Fracture and short circuit in the Li 7 La 3 Zr 2 O 12 (LLZO) solid electrolyte are two key issues that prevent its adoption in battery cells. In this paper, we utilize phase-field simulations that couple electrochemistry and fracture to evaluate the maximum electric potential that LLZO electrolytes can support as a function of crack density. In the case of a single crack, we find that the applied potential at the onset of crack propagation exhibits inverse square root scaling with respect to crack length, analogous to classical fracture mechanics. Here, we further find that the short-circuit potential scales linearly with crack length. In the realistic case where the solid electrolyte contains multiple cracks, we reveal that failure fits the Weibull model. The failure distributions shift to favor failure at lower overpotentials as areal crack density increases. Furthermore, when flawless interfacial buffers are placed between the applied potential and the bulk of the electrolyte, failure is mitigated. When constant currents are applied, current focuses in near-surface flaws, leading to crack propagation and short circuit. We find that buffered samples sustain larger currents without reaching unstable overpotentials and without failing. Our findings suggest several mitigation strategies for improving the ability of LLZO to support larger currents and improve operability.

25 ENERGY STORAGE↗

Innovative recycling of high purity silver from silicon solar cells by acid leaching and ultrasonication

Precious and scarce silver (Ag) is used as a front electrical contact in silicon solar panels. With massive amounts of solar panel waste coming to end-of-life, it is imperative to recover all the Ag from these modules. In this paper, we propose a novel method to easily reclaim Ag from end-of-life silicon solar cells using low concentration sulfuric acid (H 2 SO 4 ) leaching followed by ultrasonication. Our process simplifies the Ag recycling procedure by directly recovering the Ag contacts from solar cells, eliminating the need for secondary precipitation/electrodeposition. First, scanning electron microscopy (SEM) with energy dispersive X-ray spectroscopy (EDX) and X-ray photoelectron spectroscopy (XPS) was used to study the leaching and ultrasonication process on rejected solar wafers. Next, a solar panel from landfill was heated in a furnace to burn off the polymer encapsulant. The silicon wafers were then collected from the burning process and leached in 2 M H 2 SO 4 at two different shaking speeds for 48 hours at room temperature. Finally, the end-of-life silicon wafer pieces were collected, sonicated in water, and then the sonication water was centrifuged to show a proof-of-concept to recover the Ag contacts. Inductively coupled plasma optical emission spectroscopy (ICPOES) is used to monitor dissolved elements in the leachate as a function of time and shaking speed. XPS is used to evaluate the composition of the silicon cell wafer surface before and after H 2 SO 4 leaching. SEM is used to image the recovered Ag contacts morphology and EDX confirms the recovered particles contain high amounts of Ag. Furthermore, a proposed schematic illustrates the authors’ hypothesis for the peeling mechanism.

14 SOLAR ENERGY↗

Understanding Binder–Silicon Interactions during Slurry Processing

The conformation of poly(acrylic acid) (PAA) as a function of shear during slurry processing to construct silicon-based anodes is elucidated via rheology-coupled ultra-small-angle neutron scattering (rheo-USANS). Rheo-USANS shows that PAA with encapsulated silicon exists as discrete aggregates that do not interact with one another. As a result, a well-connected matrix of silicon and carbon black dispersed in PAA does not exist; thus, the electrode is inhomogeneous. Raman mapping and X-ray photoelectron spectroscopy were used to confirm the electrode heterogeneity and further understand the cycling properties. These results are correlated to silicon surface chemistry to provide a pathway to making better electrodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Rise of Neural Networks for Materials and Chemical Dynamics

Machine learning (ML) is quickly becoming a premier tool for modeling chemical processes and materials. ML-based force fields, trained on large data sets of high-quality electron structure calculations, are particularly attractive due their unique combination of computational efficiency and physical accuracy. This Perspective summarizes some recent advances in the development of neural network-based interatomic potentials. Designing high-quality training data sets is crucial to overall model accuracy. One strategy is active learning, in which new data are automatically collected for atomic configurations that produce large ML uncertainties. Another strategy is to use the highest levels of quantum theory possible. Transfer learning allows training to a data set of mixed fidelity. A model initially trained to a large data set of density functional theory calculations can be significantly improved by retraining to a relatively small data set of expensive coupled cluster theory calculations. These advances are exemplified by applications to molecules and materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of Confinement and Zwitterionic Ligand Chemistry on Ion–Ion Selectivity of Functionalized Nanopores

Membranes incorporating zwitterionic chemistries have recently emerged as promising candidates for facilitating challenging ion–ion separations. Transport of ions in such membranes predominantly occurs in hydrated nanopores lined with zwitterionic monomers. Here, to shed light on the physics of ion–ion selectivity underlying such materials, we conducted molecular dynamics simulations of sodium halide transport in model nanopores grafted with sulfobetaine methacrylate molecules. Our results reveal that in both functionalized and unfunctionalized nanopores smaller ions prefer to reside near the pore center, while the larger ions tend to reside near the pore walls. An enhancement in the selective transport of larger anions is observed within the unfunctionalized nanopores relative to that in salt-in-water solutions. Upon functionalization of the nanopores with zwitterions (ZIs), the disparities in the anionic distribution profiles within the pores coupled with differences in the anion-ZI interactions result in a slowdown of larger anions relative to smaller anions. Increasing the ZI grafting density exacerbates these effects, further promoting the selective transport of smaller anions. Our results suggest that selectivity toward large anions can be realized by using nanoporous membranes with ZI content that is high enough to facilitate ion/water partitioning into the pores while preserving the characteristic tendency of the unfunctionalized pores to facilitate faster transport of the larger anions. On the other hand, selectivity toward smaller anions can be achieved by targeting ZI content within the pores that is high enough to significantly slow down the transport of large anions but not high enough to hinder the partitioning of ions/water molecules into the pore due to steric effects.

anions↗

Nonreciprocal Supercurrents in a Field-Free Graphene Josephson Triode

Superconducting diodes are proposed non-reciprocal circuit elements that should exhibit nondissipative transport in one direction while being resistive in the opposite direction. Multiple examples of such devices have emerged in the past couple of years, however their efficiency is typically limited, and most of them require magnetic field to function. Here we present a device achieving efficiencies upwards of 90% while operating at zero field. Our samples consist of a network of three graphene Josephson junctions linked by a common superconducting island, to which we refer as a Josephson triode. The triode is tuned by applying a control current to one of the contacts, thereby breaking the time-reversal symmetry of the current flow. The triode’s utility is demonstrated by rectifying a small (tens of nA amplitude) applied square wave. Finally, we speculate that devices of this type could be realistically employed in the modern quantum circuits.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Fabrication of Catalytic Distillation Membranes with Atomic Layer Deposition

The integration of catalysts onto the surface of membranes enables simultaneous physical separation and catalytic transformation of constituents in a feed stream, facilitating improved contaminant removal and fouling mitigation. Distillation membranes are a particularly attractive platform for catalytic membranes because they reject nonvolatile species and exhibit exceptional resistance to oxidative and radical-driven degradation. However, imparting catalytic functionality onto hydrophobic, porous distillation membranes has proven challenging since the membranes used are chemically inert and difficult to modify. Furthermore, catalysts on the membrane surface can decrease hydrophobicity and increase the membrane’s susceptibility to pore wetting and failure. In this work, we create a catalytic distillation membrane by coating a polytetrafluoroethylene membrane surface with titanium dioxide (TiO 2 ) via plasma-assisted atomic layer deposition (ALD). By precisely tuning the ALD parameters, we demonstrate localized growth of TiO 2 near (within approximately 1 μm) the surface of polytetrafluoroethylene membranes, forming a catalytically active interface while preserving the underlying hydrophobic pore structure. Localized growth of TiO 2 is confirmed by electron microscopy and spectroscopy techniques, and membranes coated with 500 cycles of ALD show pressure tolerance up to 12.8 bar and higher than 95% salt rejection in pressure-driven distillation. Photocatalytic activity is demonstrated via the degradation of methylene blue dye under UV irradiation, where increasing TiO2 loading leads to an enhancement in dye degradation. These results establish a general strategy for integrating catalytic functionality into chemically inert, hydrophobic membranes without compromising distillation performance, providing a pathway toward multifunctional membranes that couple advanced oxidation with membrane separation for water treatment.

atomic layer deposition↗

Magnetic Response of Excitons and Excitonic Complexes in Defective Hexyl Ammonium Lead Iodide Self-Assembled Quantum Wells

Correlating the magnetic behavior of low-dimensional semiconductors with the chemistry used to form these excitonic materials remains crucial to the development of devices applied to quantum technologies. In this study, we apply large magnetic fields during the collection of low-temperature photoluminescence (PL) to assess the magnetic properties of excitons in hexyl ammonium lead iodide (HA 2 PbI 4 ) self-assembled quantum wells (SAQWs) formed at liquid−liquid interfaces. The effect of incident laser power and temperature was used to assign lower energy features in these samples’ PL spectra to both excitons trapped at defect sites and trions. Measured peaks shifts allow us to estimate coupling between the applied magnetic fields and the charged defect excitons. Our conclusions are supported by density functional theory calculations on supercells of the proposed defective HA 2 PbI 4 SAQW structure. Additionally, we find an anomalous magnetic response from trion states that resembles the behavior of interacting excitonic complexes in similar, quantum-confined materials at low temperatures. These results highlight the crucial role that chemical conditions can play in the magnetic response of 2D semiconductors applied in quantum technologies.

defect chemistry↗

The role of electron correlations in the electronic structure of putative Chern magnet TbMn6Sn6

Abstract A member of the RMn 6 Sn 6 rare-earth family materials, TbMn 6 Sn 6 , recently showed experimental signatures of the realization of a quantum-limit Chern magnet. In this work, we use quantum Monte Carlo (QMC) and density functional theory with Hubbard U (DFT + U ) calculations to examine the electronic structure of TbMn 6 Sn 6 . To do so, we optimize accurate, correlation-consistent pseudopotentials for Tb and Sn using coupled-cluster and configuration–interaction (CI) methods. We find that DFT + U and single-reference QMC calculations suffer from the same overestimation of the magnetic moments as meta-GGA and hybrid density functional approximations. Our findings point to the need for improved orbitals/wavefunctions for this class of materials, such as natural orbitals from CI, or for the inclusion of multi-reference effects that capture the static correlations for an accurate prediction of magnetic properties. DFT + U with Mn magnetic moments adjusted to the experiment predict the Dirac crossing in bulk to be close to the Fermi level, within ~120 meV, in agreement with the experiments. Our non-stoichiometric slab calculations show that the Dirac crossing approaches even closer to the Fermi level, suggesting the possible realization of Chern magnetism in this limit.

36 MATERIALS SCIENCE↗

Data-driven analysis and prediction of stable phases for high-entropy alloy design

High-entropy alloys (HEAs) represent a promising class of materials with exceptional structural and functional properties. However, their design and optimization pose challenges due to the large composition-phase space coupled with the complex and diverse nature of the phase formation dynamics. In this study, a data-driven approach that utilizes machine learning (ML) techniques to predict HEA phases and their composition-dependent phases is proposed. By employing a comprehensive dataset comprising 5692 experimental records encompassing 50 elements and 11 phase categories, we compare the performance of various ML models. Our analysis identifies the most influential features for accurate phase prediction. Furthermore, the class imbalance is addressed by employing data augmentation methods, raising the number of records to 1500 in each category, and ensuring a balanced representation of phase categories. The results show that XGBoost and Random Forest consistently outperform the other models, achieving 86% accuracy in predicting all phases. Additionally, this work provides an extensive analysis of HEA phase formers, showing the contributions of elements and features to the presence of specific phases. We also examine the impact of including different phases on ML model accuracy and feature significance. Notably, the findings underscore the need for ML model selection based on specific applications and desired predictions, as feature importance varies across models and phases. This study significantly advances the understanding of HEA phase formation, enabling targeted alloy design and fostering progress in the field of materials science.

36 MATERIALS SCIENCE↗

Three-dimensional imaging of grain boundaries via quantitative fluorescence X-ray tomography analysis

Abstract Three-dimensional visualization of material composition within multiple grains and across complex networks of grain boundaries at nanoscales can provide new insight into the structure evolution and emerging functional properties of the material for diverse applications. Here, using nanoscale scanning X-ray fluorescence tomography, coupled with an advanced self-absorption correction algorithm developed in this work, we analyze the three-dimensional gain distributions and compositions in a Ce 0.8 Gd 0.2 O 2-δ -CoFe 2 O 4 mixed ionic-electronic conductor system with high accuracy and statistical significance. Our systematic investigation reveals an additional emergent phase and uncovers highly intriguing composition stability ranges for the multiple material phases within this system. The presented visualization of composition variations across complex interfaces, supported by our quantitative composition analysis, discloses mechanistic pathways of the diverse phase transformations occurring in the material synthesis, providing insights for the optimization of transport properties in the mixed ionic-electronic conductor system.

36 MATERIALS SCIENCE↗