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At least 127 records · Page 7

Ironing out the transition metal contribution to the magnetism of the n = 3 members of the homologous series Pr n +1 M n Ge 3 n +1 (M = Fe, Co): Pr 4 Fe 3 Ge 10 vs. Pr 4 Co 3 Ge 10

The Ln n+1 M n X 3n+1 (Ln = lanthanide, M = transition metal, and X = tetrel) homologous series provides a platform to study collective phenomena in quantum materials. Here, in this work, we compare the crystal growth, structure, and magnetic properties of the n = 3 members of the Pr n+1 M n Ge 3n+1 (M = Fe, Co) analogues, Pr 4 Fe 3 Ge 10 (a = 4.3207 (10) Å, b = 35.523 (8) Å, c = 4.2982 (15) Å, and V = 659.7 (3) Å 3 ) and Pr 4 Co 3 Ge 10 (a = 4.3091 (12) Å, b = 35.750 (9) Å, c = 4.2807 (11) Å, and V = 659.4 (3) Å 3 ). We determined that the ideal flux growth conditions for each compound are highly dependent on the concentration of Sn flux and quench temperature. Pr 4 Fe 3 Ge 10 orders ferromagnetically at 10 K along the c-direction while Pr 4 Co 3 Ge 10 orders antiferromagnetically at 16 K along the b-direction. For both compounds, we observed a magnetic moment higher than that expected for only Pr 3+ ions (3.58 µ B /Pr), implying that the transition metal ions contribute to magnetic ordering (3.91, 3.48, and 3.69 µ B /Pr for Pr 4 Fe 3 Ge 10 , and 3.76, 4.04, and 3.83 µ B /Pr for Pr 4 Co 3 Ge 10 measured along the a-, b-, and c-directions, respectively). Moreover, the zero-field Mössbauer spectrum obtained at 4.2 K for Pr 4 Fe 3 Ge 10 demonstrates that the iron sites participate in magnetic ordering.

36 MATERIALS SCIENCE↗

Co 3 Ga 2 Ge 5 : Probing site mixing of the Ru 3 Sn 7 structure type with elements difficult to distinguish by diffraction

Co 3 Ga 2 Ge 5 was synthesized through arc-melting stoichiometric ratios of the elements, and a Ru 3 Sn 7 -type structure was confirmed by X-ray diffraction. Because Co 3 Ga 2 Ge 5 contains Ga and Ge, which have very similar X-ray and neutron scattering factors, any Ga/Ge crystallographic site preference cannot be determined with diffraction alone. The purpose of this study is to highlight the importance of using multiple techniques to characterize otherwise structurally ambiguous intermetallic compounds. Here, we utilize 71 Ga nuclear magnetic resonance spectroscopy and an analysis of the X-ray absorption fine structure to clarify the amount of Ga/Ge site mixing. Our combined use of X-ray diffraction and spectroscopy provides a comprehensive structural analysis of Ga site mixing across the Ge crystallographic sites, enhancing the understanding of the structure and properties of Co 3 Ga 2 Ge 5 .

36 MATERIALS SCIENCE↗

Mesoporous Thin Film Architectures: Addressing Material Demands through Molecular Self-Assembly

Mesoporous thin films spark interest across a wide range of disciplines due to their tunable nanostructures, large internal surface areas, and strong compatibility with planar optical, electronic, and microfluidic devices. While attention in the porous materials community has shifted toward macroporous or disordered nanoporous systems, a resurgence in mesoporous thin film research is underway, driven by new molecular self-assembly methods, advanced materials chemistry, and improved characterization techniques. The integration of high-χN block copolymer design, kinetically persistent micelle templating, and postdeposition processing protocols now allows control over structural parameters such as pore size, wall thickness, porosity, and connectivity. These advances have overcome many of the thermodynamic and processing constraints that previously limited widespread adoption. Rather than serving only as high-surface-area supports, mesoporous thin films are engineered as active interfaces where responsive chemistries and nanoscale confinement act in tandem. Embedding switchable ligands, thermoresponsive polymers, redox mediators, or ion-selective groups directly within the pore walls enables real-time control over transport, optical, and electrochemical properties. These capabilities open up new directions in adaptive coatings, gated membranes, and fast-response biosensors. To further expand their functional scope, mesoporous films are integrated into hierarchical and multicomponent architectures. Techniques such as triblock terpolymer templating, crack-directed assembly, and nanoimprint lithography allow for control over spatial organization on the micron and submicron scale and pore system orientation. This enables programmable anisotropy, enhanced molecular diffusion, and wavelength-selective photonic behavior, essential for next-generation sensing, catalysis, and energy applications. Such structural and functional complexity requires equally sophisticated characterization. Multimodal and in situ techniques can track material dynamics under operational conditions. Recent progress includes extended-range ellipsometric porosimetry (EP) for hierarchical architectures, vacuum EP for interface energetics, time-resolved EP for diffusion kinetics, and correlative AFM-SAXS mapping. The introduction of advanced neutron-based spectroscopies, particularly quasielastic neutron scattering (QENS), promises to provide real-time access to ion transport dynamics and segmental motion under nanoscale confinement, offering a path toward deeper mechanistic understanding of structure-performance correlations in mesoporous systems. This Account reflects the technical advances made and the interdisciplinary collaborations that have shaped our collective vision. The particular dimensions of mesopores enable us to subtly tune interactions at the molecular, interfacial, and mesoscopic levels that permit us to harness nanoconfinement. What emerges is a versatile, modular platform capable of chemical gating, energy transduction, and sensing with a level of tunability unmatched by other porous materials. We highlight critical challenges including the need for more robust large-area processing, a deeper understanding of dynamic behavior under cycling, and better integration with device-level architectures. Our strategies support the transition of mesoporous thin films into active high-performance components in next-generation energy, environmental, and biomedical systems.

oxides↗

Resolving Dynamics in the Ensemble: Finding Paths through Intermediate States and Disordered Protein Structures

Proteins have been found to inhabit a diverse set of three-dimensional structures. The dynamics that govern protein interconversion between structures happen over a wide range of time scales-picoseconds to seconds. Our understanding of protein functions and dynamics is largely reliant upon our ability to elucidate physically populated structures. From an experimental structural characterization perspective, we are often limited to measuring the ensemble-averaged structure both in the steady-state and time-resolved regimes. Generating kinetic models and understanding protein structure–function relationships require atomistic knowledge of the populated states in the ensemble. Here, we present ensemble refinement methodologies that integrate time-resolved experimental signals with molecular dynamics models. We first discuss integration of experimental structural restraints to molecular models in disordered protein systems that adhere to the principle of maximum entropy for creating a complete set of ensemble structures. We then propose strategies to find kinetic pathways between the refined structures, using time-resolved inputs to guide molecular dynamics trajectories and the use of inference to generate tailored stimuli to prepare a desired ensemble of protein states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deciphering the Solvation Structure of Aqueous ZnCl 2 Solutions from X-ray Absorption Spectra Using the Interpretable Graph Neural Network

Machine learning (ML) provides powerful pathways for predicting spectroscopic observables from atomic structures, but its broader impact depends on making model predictions interpretable in terms of physical and chemical principles. Here, we introduce a physics-guided graph neural network (GNN) model that predicts Zn K-edge X-ray spectroscopy (XAS) spectra of aqueous ZnCl 2 solutions. Training data are generated from ab initio XAS calculations on molecular dynamics snapshots obtained using a machine learning interatomic potential. The GNN reproduces experimental spectra across concentrations from dilute (<0.1 m) to highly concentrated (30 m, “water-in-salt”) regimes and scales efficiently to large, disordered liquid systems beyond the reach of conventional ab initio approaches. Gradient-based attribution analysis reveals that the model learns physically meaningful structure-spectrum relationships. Ligand-specific attributions reflect orbital hybridization patterns and the origin of the excitations derived from the density functional theory. Bond-length attributions recover spectral shifts consistent with multiple-scattering theory. Finally, this work bridges data-driven prediction with electronic-structure theory, establishing a general paradigm for interpretable ML that links atomic structure, electronic structure, and spectroscopic observables.

25 ENERGY STORAGE↗

Pressure-Stabilized MnSb2 with Complex Incommensurate Magnetic Order

Marcasite-type compounds have been proposed as promising hosts of exotic magnetic quantum states, yet experimental realizations in stoichiometric, disorder-free systems remain limited. Here, we report the high-pressure stabilization and magnetic characterization of MnSb2, a marcasite-type compound that is thermodynamically metastable under ambient pressure. Single crystals were synthesized using a cubic multianvil press at 3.3 GPa and 490 °C for 24 h, and powder and single-crystal X-ray diffraction confirm the orthorhombic Pnnm structure. These crystals are stable at ambient pressure for a long time up to between 450 and 500 K. Heat-capacity measurements reveal phase transitions at approximately T0 ∼ 118 K and T1 ∼ 220 K. Neutron diffraction uncovers an unconventional magnetic state below T1 ∼ 220 K. Magnetic powder neutron diffraction refinements reveal possible multiple magnetic configurations that provide comparably acceptable fits to the experimental data. While most solutions are consistent with a spin-density-wave (SDW) description, helical models systematically yield inferior agreement factors. Across a broad range of models, the Mn ordered moment reaches a maximum value of approximately 2 μB and remains predominantly collinear, with minimal canting along the c-axis. At 200 K, the magnetic propagation vector is q = (0, 0.3975, 0.3783); upon cooling, the b component increases toward 0.5, reflecting a temperature-dependent evolution of the modulation. The need for modification of the magnetic model between high and low temperatures further highlights the complex and strongly temperature-dependent nature of the magnetic order in this system. These results establish MnSb2 as a pressure-stabilized marcasite magnet with a tunable, complex magnetic state and a compelling stoichiometric platform for exploring unconventional magnetic behavior, including potential altermagnetism.

Xu, Mingyu [Michigan State University , , , ,; Iow↗

High Entropy Protected Sharp Magnetic Transitions in Highly Disordered Spinel Ferrites

How disorder affects magnetic ordering is always an intriguing question, and it becomes even more interesting in the recently rising high entropy oxides due to the extremely high disorder density. However, due to the lack of high-quality single crystal samples, the strong compositional disorder effect on magnetic transition has not been deeply investigated. In this work, we have successfully synthesized high-quality single crystalline high entropy spinel ferrites (Mg 0.2 Mn 0.2 Fe 0.2 Co 0.2 Ni 0.2 ) x Fe 3-x O 4 . Our findings from high-temperature magnetization and neutron diffraction experiments showed ferrimagnetic transitions at 748, 694, and 674 K for x values of 1, 1.5, and 1.8, respectively. Notably, the magnetic transition almost showed no broadening for x values of 1 and 1.5, compared to Fe 3 O 4 . Extended X-ray absorption fine structure measurements provided insights into the elemental distribution among the octahedral and tetrahedral sites. The random distribution of elements across these sites reduced the formation of local clusters and short-range orders, enhancing sample homogeneity and preserving the sharpness of the magnetic transition, despite bond length variation. Here, our study not only marks the first successful synthesis of an HEO bulk single crystal exhibiting long-range magnetic order but also sheds light on the interaction between high configurational entropy and magnetic orderings. This opens new avenues for future research and applications of magnetic high entropy oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Universality and quantum criticality in quasiperiodic spin chains

Abstract Quasiperiodic systems are aperiodic but deterministic, so their critical behavior differs from that of clean systems and disordered ones as well. Quasiperiodic criticality was previously understood only in the special limit where the couplings follow discrete quasiperiodic sequences. Here we consider generic quasiperiodic modulations; we find, remarkably, that for a wide class of spin chains, generic quasiperiodic modulations flow to discrete sequences under a real-space renormalization-group transformation. These discrete sequences are therefore fixed points of a functional renormalization group. This observation allows for an asymptotically exact treatment of the critical points. We use this approach to analyze the quasiperiodic Heisenberg, Ising, and Potts spin chains, as well as a phenomenological model for the quasiperiodic many-body localization transition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Extracting structural motifs from pair distribution function data of nanostructures using explainable machine learning

Characterization of material structure with X-ray or neutron scattering using e.g. Pair Distribution Function (PDF) analysis most often rely on refining a structure model against an experimental dataset. However, identifying a suitable model is often a bottleneck. Recently, automated approaches have made it possible to test thousands of models for each dataset, but these methods are computationally expensive and analysing the output, i.e. extracting structural information from the resulting fits in a meaningful way, is challenging. Our Machine Learning based Motif Extractor (ML-MotEx) trains an ML algorithm on thousands of fits, and uses SHAP (SHapley Additive exPlanation) values to identify which model features are important for the fit quality. We use the method for 4 different chemical systems, including disordered nanomaterials and clusters. ML-MotEx opens for a type of modelling where each feature in a model is assigned an importance value for the fit quality based on explainable ML.

36 MATERIALS SCIENCE↗

Transition of a network of nonlinear interactions into a regime of strong nonlinear fluctuations: A paradigm for the edge localized mode onset

We study how a network of nonlinear oscillators transits into a regime of strong nonlinear fluctuations when perturbed by a triad. In this regime, most of the potential energy contained in the waves is made available to the system through strong nonlinear fluctuations. This analysis is motivated by recent experimental observations [Dominski and Diallo, Plasma Phys. Control. Fusion 62, 095011 (2020)] where it was found that magnetic fluctuations trigger the onset of edge localized modes by suddenly exciting a network of nonlinear interactions. In our study, we consider the simplest system of many harmonic oscillators that are organized in a network of nonlinear triads. We model and simulate the sudden transition of this network of triads into a regime of strong nonlinear fluctuations—reminiscent of the onset of edge localized modes in tokamaks. This transition is triggered by the activation of a nonlinear perturbation. An abrupt rise of the system's disorder (an entropy-like quantity) is measured during the transition. This transition from weak to strong nonlinear fluctuations is even more abrupt when these fluctuations are chaotic, i.e., when the timescale of the nonlinear interaction is comparable to the timescale of the wave oscillations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Extracting the excitonic Hamiltonian of a chlorophyll dimer from broadband two-dimensional electronic spectroscopy

We apply Frenkel exciton theory to model the entire Q-band of a tightly bound chlorophyll dimer inspired by the photosynthetic reaction center of photosystem II. The potential of broadband two-dimensional electronic spectroscopy experiment spanning the Qx and Qy regions to extract the parameters of the model dimer Hamiltonian is examined through theoretical simulations of the experiment. We find that the local nature of Qx excitation enables identification of molecular properties of the delocalized Qy excitons. Specifically, we demonstrate that the cross-peak region, where excitation energy is resonant with Qy while detection is at Qx, contains specific spectral signatures that can reveal the full real-space molecular Hamiltonian, a task that is impossible by considering the Qy transitions alone. System–bath coupling and site energy disorder in realistic systems may limit the resolution of these spectral signatures due to spectral congestion.

Chemistry↗

Medium-Range Order, Density Fluctuations, and Activated Relaxation in the Equilibrated Deep Glass Regime

A successful microscopic theory of activated relaxation in metastable supercooled liquids is extended to the equilibrated deep glass regime. Surprisingly, the predicted power-law scaling connections of the dynamic barrier with diverse scalar order parameters (medium-range order correlation length, dimensionless compressibility, shear modulus) remain unchanged up to astronomically long timescales, despite a fundamental crossover of equilibrium thermodynamics and structure near the laboratory kinetic vitrification point. Quantitative tests against experiments on aged to equilibrium glass-forming liquids up to nearly 20 decades in time scale reveal good agreement. This conflicts with the idea of a crossover from super-Arrhenius to literal Arrhenius relaxation around the laboratory glass transition temperature, and supports the robustness of the theoretical idea that ultraslow dynamics is causally related to medium-range structural order. Here, new avenues of experimental and theoretical research in the deep glass regime are suggested.

Amorphous materials↗

Geometric Delocalization in Two Dimensions

We demonstrate the existence of transient two-dimensional surfaces where a random-walking particle escapes to infinity in contrast to localization in standard flat two-dimensional space. We first prove that any rotationally symmetric two-dimensional membrane embedded in flat three-dimensional space cannot be transient. Then we formulate a criterion for the transience of a general asymmetric two-dimensional membrane. We use it to explicitly construct a class of transient two-dimensional manifolds with a nontrivial metric and height function but “zero average curvature,” which we dub “tablecloth manifolds.” The absence of the logarithmic infrared divergence of the Laplace-Beltrami operator in turn implies the absence of weak localization, nonexistence of bound states in shallow potentials, and breakdown of the Mermin-Wagner theorem and Kosterlitz-Thouless transition on the tablecloth manifolds, which may be realizable in both quantum simulators and corrugated two-dimensional materials.

Anderson localization↗

Kubo-Anderson theory of polariton line shape

We apply the Kubo-Anderson stochastic theory of molecular spectral line shapes to the case of polaritons formed in the collective strong-coupling regime. We investigate both the fast and slow limits of the random frequency modulation of the emitter as well as the intermediate regime and show how the interplay between the characteristic timescales of the cavity and the molecular disorder is expressed in the observed polaritons line shapes. The analytical solution obtained for the slow limit is valid for any ratio between the inhomogeneous broadening of the molecules and the Rabi splitting, which is especially relevant for molecular polaritons where these two quantities can be of the same order of magnitude.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tuning the Intrinsic Anisotropy with Disorder in the Ca K Fe 4 As 4 Superconductor

In this paper, we report on the anisotropy of the London penetration depth of CaKFe 4 As 4 , discussing how it relates to its electronic structure and how it modifies under introduction of disorder, both chemically induced (by Ni substitution) and irradiation induced (by 3.5-MeV protons). Indeed, CaKFe 4 As 4 is particularly suitable for the study of fundamental superconducting properties due to its stoichiometric composition, exhibiting clean-limit behavior in the pristine samples and having a fairly high critical temperature, T c ≈35 K. The London penetration depth λ L is measured with a microwave-coplanar-resonator technique that allows us to deconvolve the anisotropic contributions λ L,ab and λ L,c and obtain the anisotropy parameter γλ=λ L,c /λ L,ab . The γλ(T) found for the undoped pristine sample is in good agreement with previous literature and is here compared to ab initio density-functional-theory and Eliashberg calculations. The dependence of γλ(T) on both chemical and irradiation-induced disorder is discussed to highlight which method is more suitable to decrease the direction dependence of the electromagnetic properties while maintaining a high critical temperature. Lastly, the relevance of an intrinsic anisotropy such as γλ on application-related anisotropic parameters (critical current, pinning) is discussed in light of the recent employment of CaKFe 4 As 4 in the production of wires.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Averaged cluster approach to including chemical short-range order in KKR-CPA

The single-site Korringa-Kohn-Rostoker coherent potential approximation (KKR-CPA) ignores short-range ordering present in disordered metallic systems. Here in this paper, we establish a technique to fix this shortcoming by embedding an averaged cluster that displays chemical short-range order (SRO). The degree of SRO can be tuned by externally defined order parameters. This averaged cluster can be embedded in the single-site CPA medium or a self-consistently obtained effective medium that contains SRO information. The validity of this method is demonstrated by applying it to two alloy systems—the CuZn body-centered cubic (BCC) solid solution, and AlCrTiV, a four-element BCC high entropy alloy. A comparison between the non-self-consistent and self-consistent modes is also provided for the two above-mentioned systems. We make the code available on the internet. Planned extensions to this paper are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Robustness of vortex-bound Majorana zero modes against correlated disorder

Here, we investigate the effect of correlated disorder on Majorana zero modes (MZMs) bound to magnetic vortices in two-dimensional topological superconductors. By starting from a lattice model of interacting fermions with a p x ±ip y superconducting ground state in the disorder-free limit, we use perturbation theory to describe the enhancement of the Majorana localization length at weak disorder and a self-consistent numerical solution to understand the breakdown of the MZMs at strong disorder. We find that correlated disorder has a much stronger effect on the MZMs than uncorrelated disorder and that it is most detrimental if the disorder correlation length ℓ is on the same order as the superconducting coherence length ξ. In contrast, MZMs can survive stronger disorder for ℓ $\ll$ξ as random variations cancel each other within the length scale of ξ, while an MZM may survive up to very strong disorder for ℓ$\gg$ξ if it is located in a favorable domain of the given disorder realization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Fluctuation-induced odd-frequency spin-triplet pairing in a disordered electron liquid

Here we consider a two-dimensional disordered conductor in the regime when the superconducting phase is destroyed by the magnetic field. We analyze a combination of fluctuations of different origin which results in an effective interaction amplitude suitable for a spontaneous s-wave odd-frequency pairing instability. We observe that the end point of the superconductivity is a quantum critical point separating the conventional superconducting phase from a state with the odd-frequency spin-triplet pairing instability. We speculate that this could shed light on a rather mysterious insulating state observed in strongly disordered superconducting films in a broad region of the magnetic fields.

36 MATERIALS SCIENCE↗