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At least 127 records · Page 7

Ultrafast Formation of Jahn–Teller Polarons Revealed by State-Selective Excitation in Correlated Spinel Co 3 O 4

Jahn–Teller polarons are quasiparticles that stem from symmetry breaking and strong local electron–phonon coupling. They originate from an excess charge carrier being dressed by a local lattice distortion, caused by the Jahn–Teller effect, and they critically impact electrical, structural, and magnetic properties in transition metal oxides. The observation of the microscopic steps involved in their formation is essential for enabling control over material properties through the targeted activation of local, site-specific modifications with light pulses. While Jahn–Teller distortion associated with polaron formation was predicted to contribute significantly to changes in electronic band gap and optical properties in Co 3 O 4 , its experimental observation remains elusive, requiring signatures of local symmetry reduction. In this work, we demonstrate Jahn–Teller polaron formation in spinel Co 3 O 4 . By exciting electronic transitions at 3.10 eV and 1.55 eV, we target either the Oh Cobalt(III) or the Td Cobalt(II) ions, and drive the subsequent coherent responses of the system through two different pathways. For the former, we demonstrate that ligand-to-metal charge transfer leads to Jahn–Teller polaron formation, which is linked to the deformation potential and magnetoelastic coupling. For the latter, we identify the coherent excitation of a T 2g phonon mode launched by on-site d-d electronic transitions. Key to our observations is the ability to target site-specific electronic excitations in spinel Co 3 O 4 using ultrafast optical pulses, while monitoring the ensuing low-energy collective modes through the coherent time-domain response of the material. Our approach, which combines the comparative analysis of experimental fingerprints with the support from density functional theory calculations, is broadly applicable to systems in which Jahn–Teller polaron physics has been theoretically predicted but remains experimentally unverified, and it underscores the potential of electronic-state targeting as a route to selectively excite and probe quasiparticle dynamics in solids.

Lattices↗

Autonomous and dynamic precursor selection for solid-state materials synthesis

Abstract Solid-state synthesis plays an important role in the development of new materials and technologies. While in situ characterization and ab-initio computations have advanced our understanding of materials synthesis, experiments targeting new compounds often still require many different precursors and conditions to be tested. Here we introduce an algorithm (ARROWS 3 ) designed to automate the selection of optimal precursors for solid-state materials synthesis. This algorithm actively learns from experimental outcomes to determine which precursors lead to unfavorable reactions that form highly stable intermediates, preventing the target material’s formation. Based on this information, ARROWS 3 proposes new experiments using precursors it predicts to avoid such intermediates, thereby retaining a larger thermodynamic driving force to form the target. We validate this approach on three experimental datasets, containing results from over 200 synthesis procedures. In comparison to black-box optimization, ARROWS 3 identifies effective precursor sets for each target while requiring substantially fewer experimental iterations. These findings highlight the importance of domain knowledge in optimization algorithms for materials synthesis, which are critical for the development of fully autonomous research platforms.

36 MATERIALS SCIENCE↗

FunDiff: diffusion models over function spaces for physics-informed generative modeling

Recent advances in generative modeling-particularly diffusion models and flow matching-have been widely used for synthesizing discrete data such as images and videos. However, adapting these models to physical applications remains challenging, as the quantities of interest are continuous functions governed by complex physical laws. To address this, we introduce FunDiff, an efficient and robust framework for generative modeling in function spaces. FunDiff combines a latent diffusion process with a function autoencoder architecture to handle input functions with varying discretizations, generates continuous functions that can be evaluated at arbitrary locations, and seamlessly incorporate physical priors. These priors are enforced through architectural constraints or physics-informed loss functions, ensuring that generated samples satisfy fundamental physical laws. We theoretically establish minimax optimality guarantees for density estimation in function spaces, demonstrating that diffusion-based estimators achieve optimal convergence rates under suitable regularity conditions. We further demonstrate the practical effectiveness of FunDiff across diverse applications in fluid dynamics and solid mechanics. Empirical results indicate that our method can generate physically consistent samples with high fidelity to the target distribution, and exhibit robustness to noisy and low-resolution data.

Wang, Sifan [Yale University, New Haven, CT (Unite↗

Tunable angle-dependent electrochemistry at twisted bilayer graphene with moiré flat bands

Tailoring electron transfer dynamics across solid–liquid interfaces is fundamental to the interconversion of electrical and chemical energy. Stacking atomically thin layers with a small azimuthal misorientation to produce moiré superlattices enables the controlled engineering of electronic band structures and the formation of extremely flat electronic bands. Here, we report a strong twist-angle dependence of heterogeneous charge transfer kinetics at twisted bilayer graphene electrodes with the greatest enhancement observed near the ‘magic angle’ (~1.1°). Furthermore, this effect is driven by the angle-dependent tuning of moiré-derived flat bands that modulate electron transfer processes with the solution-phase redox couple. Combined experimental and computational analysis reveals that the variation in electrochemical activity with moiré angle is controlled by a structural relaxation of the moiré superlattice at twist angles of <2°, and ‘topological defect’ AA stacking regions, where flat bands are localized, produce a large anomalous local electrochemical enhancement that cannot be accounted for by the elevated local density of states alone.

36 MATERIALS SCIENCE↗

Insights on the dissolution of water in an albite melt at high pressures and temperatures from a direct structural analysis

The water dissolution mechanism in silicate melts under high pressures is not well understood. Here we present the first direct structure investigation of a water-saturated albite melt to monitor the interactions between water and the network structure of silicate melt at the molecular level. In situ high-energy X-ray diffraction was carried out on the NaAlSi 3 O 8 -H 2 O system at 800 °C and 300 MPa, at the Advanced Photon Source synchrotron facility. The analysis of the X-ray diffraction data was augmented with classical Molecular Dynamics simulations of a hydrous albite melt, incorporating accurate water-based interactions. The results show that metal–oxygen bond breaking at the bridging sites occurs overwhelmingly at the Si site upon reaction with H 2 O, with subsequent Si–OH bond formation and negligible Al–OH formation. Furthermore, we see no evidence for the dissociation of the Al 3+ ion from the network structure upon breaking of the Si–O bond in the hydrous albite melt. The results also indicate that the Na + ion is an active participant in the modifications of the silicate network structure of the albite melt upon water dissolution at high P–T conditions. We do not find evidence for the Na + ion dissociating from the network structure upon depolymerization and subsequent formation of NaOH complexes. Instead, our results show that the Na + ion persists as a structure modifier with a shift away from Na–BO bonding to an increase in the extent of Na-NBO bonding, in parallel with pronounced depolymerization of the network. Our MD simulations show that the Si–O and Al–O bond lengths are expanded by about 6% in the hydrous albite melt compared to those of the dry melt at high P–T conditions. The changes in the network silicate structure of a hydrous albite melt at high pressure and temperature, as revealed in this study, must be considered in the advancement of water dissolution models of hydrous granitic (or alkali aluminosilicate) melts.

36 MATERIALS SCIENCE↗

Skyrmion fluctuations at a first-order phase transition boundary

Magnetic skyrmions are topologically protected spin textures with promising prospects for applications in data storage. They can form a lattice state due to competing magnetic interactions and are commonly found in a small region of the temperature—magnetic field phase diagram. Recent work has demonstrated that these magnetic quasi-particles fluctuate at the μeV energy scale. Here, we use a coherent x-ray correlation method at an x-ray free-electron laser to investigate these fluctuations in a magnetic phase coexistence region near a first-order transition boundary where fluctuations are not expected to play a major role. Surprisingly, we find that the relaxation of the intermediate scattering function at this transition differs significantly compared to that deep in the skyrmion lattice phase. The observation of a compressed exponential behavior suggests solid-like dynamics, often associated with jamming. We assign this behavior to disorder and the phase coexistence observed in a narrow field-window near the transition, which can cause fluctuations that lead to glassy behavior.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Predicting Phonon-Induced Spin Decoherence from First Principles: Colossal Spin Renormalization in Condensed Matter

Developing a microscopic understanding of spin decoherence is essential to advancing quantum technologies. Electron spin decoherence due to atomic vibrations (phonons) plays a special role as it sets an intrinsic limit to the performance of spin-based quantum devices. Two main sources of phonon-induced spin decoherence—the Elliott-Yafet and Dyakonov-Perel mechanisms—have distinct physical origins and theoretical treatments. Here, we show calculations that unify their modeling and enable accurate predictions of spin relaxation and precession in semiconductors. We compute the phonon-dressed vertex of the spin-spin correlation function with a treatment analogous to the calculation of the anomalous electron magnetic moment in QED. We find that the vertex correction provides a giant renormalization of the electron spin dynamics in solids, greater by many orders of magnitude than the corresponding correction from photons in vacuum. Finally, our Letter demonstrates a general approach for quantitative analysis of spin decoherence in materials, advancing the quest for spin-based quantum technologies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Volcanic arc rigidity variations illuminated by coseismic deformation of the 2011 Tohoku-oki M9

Rock strength has long been linked to lithospheric deformation and seismicity. However, independent constraints on the related elastic heterogeneity are missing, yet could provide key information for solid Earth dynamics. Using coseismic Global Navigation Satellite Systems (GNSS) data for the 2011 M9 Tohoku-oki earthquake in Japan, we apply an inverse method to infer elastic structure and fault slip simultaneously. We find compliant material beneath the volcanic arc and in the mantle wedge within the partial melt generation zone inferred to lie above ~100 km slab depth. We also identify low-rigidity material closer to the trench matching seismicity patterns, likely associated with accretionary wedge structure. Along with traditional seismic and electromagnetic methods, our approach opens up avenues for multiphysics inversions. Those have the potential to advance earthquake and volcano science, and in particular once expanded to InSAR type constraints, may lead to a better understanding of transient lithospheric deformation across scales.

58 GEOSCIENCES↗

Maskless Fourier transform holography

Fourier transform holography is a lensless imaging technique that retrieves an object's exit-wave function with high fidelity. It has been used to study nanoscale phenomena and spatio-temporal dynamics in solids, with sensitivity to the phase component of electronic and magnetic textures. However, the method requires an invasive and labor-intensive nanopatterning of a holography mask directly onto the sample, which can alter the sample properties, forces a fixed field-of-view, and leads to a low signal-to-noise ratio at high resolution. In this work, we propose using wavefront-shaping diffractive optics to create a structured probe with full control of its phase at the sample plane, circumventing the need for a mask. We demonstrate in silico that the method can image nanostructures and magnetic textures and validate our approach with a visible light-based experiment. The method enables investigation of a plethora of phenomena at the nanoscale including magnetic and electronic phase coexistence in solids, with further uses in soft and biological matter research.

Keskinbora, Kahraman↗

Structural characterization of tin in toothpaste by dynamic nuclear polarization enhanced 119 Sn solid-state NMR spectroscopy

Stannous fluoride (SnF 2 ) is an effective fluoride source and antimicrobial agent that is widely used in commercial toothpaste formulations. The antimicrobial activity of SnF 2 is partly attributed to the presence of Sn(II) ions. However, it is challenging to directly determine the Sn speciation and oxidation state within commercially available toothpaste products due to the low weight loading of SnF 2 (0.454 wt% SnF 2 , 0.34 wt% Sn) and the amorphous, semi-solid nature of the toothpaste. Here, we show that dynamic nuclear polarization (DNP) enables 119 Sn solid-state NMR experiments that can probe the Sn speciation within commercially available toothpaste. Solid-state NMR experiments on SnF 2 and SnF 4 show that 19 F isotropic chemical shift and 119 Sn chemical shift anisotropy (CSA) are highly sensitive to the Sn oxidation state. DNP-enhanced 119 Sn magic-angle turning (MAT) 2D NMR spectra of toothpastes resolve Sn(II) and Sn(IV) by their 119 Sn chemical shift tensor parameters. Fits of DNP-enhanced 1D 1 H → 119 Sn solid-state NMR spectra allow the populations of Sn(II) and Sn(IV) within the toothpastes to be estimated. This analysis reveals that three of the four commercially available toothpastes contained at least 80% Sn(II), whereas one of the toothpaste contained a significantly higher amount of Sn(IV).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kinetics of solid–liquid interface motion in molecular dynamics and phase-field models: crystallization of chromium and silicon

The results of molecular dynamics (MD) simulations of the crystallization process in one-component materials and solid solution alloys reveal a complex temperature dependence of the velocity of the crystal–liquid interface featuring an increase up to a maximum at 10–30% undercooling below the equilibrium melting temperature followed by a gradual decrease of the velocity at deeper levels of undercooling. At the qualitative level, such non-monotonous behaviour of the crystallization front velocity is consistent with the diffusion-controlled crystallization process described by the Wilson–Frenkel model, where the almost linear increase of the interface velocity in the vicinity of melting temperature is defined by the growth of the thermodynamic driving force for the phase transformation, while the decrease in atomic mobility with further increase of the undercooling drives the velocity through the maximum and into a gradual decrease at lower temperatures. At the quantitative level, however, the diffusional model fails to describe the results of MD simulations in the whole range of temperatures with a single set of parameters for some of the model materials. The limited ability of the existing theoretical models to adequately describe the MD results is illustrated in the present work for two materials, chromium and silicon. It is also demonstrated that the MD results can be well described by the solution following from the hodograph equation, previously found from the kinetic phase-field model (kinetic PFM) in the sharp interface limit. The ability of the hodograph equation to describe the predictions of MD simulation in the whole range of temperatures is related to the introduction of slow (phase field) and fast (gradient flow) variables into the original kinetic PFM from which the hodograph equation is obtained. The slow phase-field variable is responsible for the description of data at small undercoolings and the fast gradient flow variable accounts for local non-equilibrium effects at high undercoolings. The introduction of these two types of variables makes the solution of the hodograph equation sufficiently flexible for a reliable description of all nonlinearities of the kinetic curves predicted in MD simulations of Cr and Si. This article is part of the theme issue ‘Transport phenomena in complex systems (part 1)’.

Science & Technology - Other Topics↗

Formation and dissociation of shear-induced high-energy dislocations: insight from molecular dynamics simulations

Solid-phase processing (SPP) allows one to create complex microstructures, not achievable via thermal processing alone. The resulting structures exhibit a rich palette of defects, both thermal and non-thermal, including defect substructures, such as dislocation networks. It is essential to understand the mechanisms of deformation and defect structure formation to guide SPP towards achieving desired microstructures and material properties. In this study, large-scale molecular dynamics simulations are used to investigate the effects of inhomogeneous strain distribution, that mimics deformation conditions of tribological tests, on the evolution of defects under severe shear deformation in polycrystalline Al. Analysis of defect nucleation and reaction pathways reveals that strong geometric constraints suppress the nucleation and slide of low energy dislocation 1/2$\langle110\rangle${111} but promote the nucleation and slide of high energy dislocations, such as [$1\bar1$0] (001) and 1/2 [$1\bar1$$\bar2$]($1\bar1$1). Further, a rough contact surface, characteristic to tribological tests, imposes an inhomogeneous stress field leading to inhomogeneous defect substructures due to location-dependent activation of slip systems. The results suggest that high-energy dislocations can dominate the evolution of grain structures in highly constrained environments, which should be considered in modeling plastic deformation and grain refinement during SPP.

42 ENGINEERING↗

The phantom menace of dynamic soft-shorts in solid-state battery research

Solid-state batteries with lithium metal anodes present the highest energy density batteries for applications in electric vehicles, leading to massive R&D investments over the past decade. Although most research focuses on preventing lithium metal dendrites that eventually short the battery, the nature of these shorts remains elusive. Soft-shorts, in particular, receive little attention or are not recognized, even in published data. Here, in this study, we present a comprehensive outline of the detection and analysis of soft -shorts in solid-state lithium metal cells with composite polymer electrolytes as well as a fundamental understanding of the dynamics of soft -shorts. Transient un-shorting of soft -shorts that occurs on the micro-to-millisecond timescale-driven by joule heating, chemical reactivity, and other processes-limits one's ability to determine whether the cell was or is still shorted. We provide numerous experimental methods to detect and analyze soft-shorts in any battery type as a resource to all battery researchers.

25 ENERGY STORAGE↗

Ionic Dynamics of the Charge Carrier in Layered Solid Materials for Mg Rechargeable Batteries

Multivalent-ion batteries have attracted growing attention due to their high theoretical energy density that potentially outperforms Li-ion batteries. One of the critical challenges of realizing a multivalent-ion battery is the strong polarization that results in the sluggish intercalation of ions in the host lattice, which motivates a fundamental understanding of multivalent-ion dynamics in solid-state materials. In this contribution, we investigate the diffusion mechanisms of divalent ions in a novel Mg anode coating, BiOCl, using first-principles informed learning-on-the-fly molecular dynamics. Based on nanosecond-scale dynamics observations, we gained insights into the concerted diffusion mechanism of Mg cation site-to-site hopping facilitated by synchronous anion rotational motion. Furthermore, we compute the Mg-ion diffusion in additional candidate host structures screened from available layered materials space. Here, the results suggest the co-operative divalent cation-anion motion is likely a common phenomenon in layered oxyhalide structures. Our findings provide a new perspective on how to enhance multivalent-ion diffusion in layered materials.

25 ENERGY STORAGE↗

Modeling Dynamic Evolution of Oxygen Vacancies in Solid Oxide Materials

SOEC is a promising H 2 generation technology for mitigating climate change. Novel material design and optimization strategies, such as oxygen vacancy chemistries, can enhance SOEC efficiency. In this study, Monte Carlo-ReaxFF and eReaxFF simulations were used to study oxygen vacancies (O v ) and electron migration in BZY20 solid oxide material. Our results shows that O v migrate towards the surface, increasing surface O v concentration by 10%. Yttrium restricts electron mobility and functions as an electron trapping site, while Zr accelerates electron mobility and migration. These insights could improve solid-state electrolytes’ electrochemical performance in renewable energy applications.

13 HYDRO ENERGY↗

Effect of Polymer Topology on Microstructure, Segmental Dynamics, and Ionic Conductivity in PEO/PMMA-Based Solid Polymer Electrolytes

We report Poly(ethylene oxide) (PEO)-based solid polymer electrolytes (SPEs) have attracted much interest due to their high ionic conductivity resulting from inherently fast segmental dynamics and high salt solubility, yet they lack mechanical stability in their neat form. Blending PEO with another rigid, or high glass transition temperature, polymer is a versatile way to improve the mechanical stability; however, the ionic conductivity is strongly reduced due to slower segmental dynamics of highly interpenetrating linear polymer chains. In this work, we used model PEO/PMMA blend systems prepared with various well-defined PEO architectures (linear, stars, hyperbranched, and bottlebrushes) doped with lithium bis(trifluoromethane-sulfonyl)-imide (LiTFSI) and investigated, for the first time, the role of macromolecular architecture of PEO on crystallization, segmental dynamics, and ionic conductivity in the blends and electrolytes. The results suggest that room-temperature miscibility of these polymers can be dramatically extended by using nonlinear PEO in the blends instead of linear chains, which crystallize above 35 wt %. The broadband dielectric spectroscopy results revealed enhanced decoupling of PMMA and PEO segmental dynamics in compact branched architectures, which helps to achieve faster segmental motion of star PEO in glassy PMMA. This manifests as nearly three-fold higher ionic conductivity in these nonlinear blends compared to the conventional linear PEO/PMMA system. Regardless of the PEO architectures, the temperature dependence of ionic conductivity blends with PMMA and LiTFSI is well defined using the Vogel–Fulcher–Tammann mechanism, suggesting that ion transport is mainly affected by the segmental motion. The activation energy values decrease with the increasing ionic conductivity. Overall, our results show that macromolecular architecture can be a tool to decouple segmental dynamics and ion mobility to rationally design SPEs with improved performance.

36 MATERIALS SCIENCE↗