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Physics Condensed Matter Materials Science

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Friday 24 July

Materials Science

Mechanical mapping of thin elastic films and living cells with spherical tip atomic force microscopy probes at large indentations

Gabriel Gomila, Mauricio Cano, Beatriz Cantero et al. (+7 more)

An analytical model to quantify large indentation force curves acquired on elastic thin films and living cells with spherical tip Atomic Force Microscopy (AFM) probes is presented. The model accounts for the bottom effect in the whole indentation range and overcomes the limitations of Sneddon's and Hertz's contact models, which are valid for semi-infinite thick samples, and of paraboloid tip models with bottom effect correction (BEC) that are applicable to spherical tips only for relatively small indentations. The model is experimentally validated with force volume measurements on polyacrylamide (PAA) hydrogel thin films, where an excellent agreement is obtained. The accurate correction of the bottom effect demonstrates that the intrinsic Young's modulus of PAA thin films increases for thickness below a critical value (~15 um). The model also shows excellent agreement with force curves acquired on live macrophages, providing accurate Young's modulus values for these very soft cells (E~200 Pa). Young's modulus values extracted with the proposed model significantly differ from those obtained from Sneddon's or paraboloid models with BEC, whose values deviate by 100% and -25%, respectively. Results show the potential of the proposed model for analysing force curve measurements with spherical tips at large indentations on thin film elastic materials and living cells at the micro and nanoscale.
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All authors Gabriel Gomila, Mauricio Cano, Beatriz Cantero, Sophie Strawbridge, Lara Aiassa, Loris Rizzello, Giuseppe Battaglia, Eleni Dalaka, Jordi Comelles, Annalisa Calò

Materials Science

Accelerating grain boundary modelling and simulation by automated pre-evaluation of the irreducible macroscopic representation

Wei Wan

A major challenge in the modelling and simulation of grain boundaries (GBs) is the conflict between the system size and computation capability, which inherently restricts the computationally accessible boundary characters. We present an algorithm to find the irreducible macroscopic representation of any given coincident-site-lattice GB character in the cubic lattice, and thus determine the irreducible size of its supercell. The algorithm is compared with the conventional orthogonal supercell and a published calculation method to assess its merits in saving computational resources. This supercell size parameter can be used to predict which GB character is relatively special across the vast 5D space, as those GBs possess small structural units are likely to exhibit particular structure-property relationships that are worthy of attention. The prediction is confirmed by examining the energy and mobility trends of aluminum mixed GBs obtained from the atomistic simulations.
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Materials Science

Quantitative Analysis of Composition and Contamination of Atomically Thin Materials by Recoil-Projectile Coincidence in Ion Transmission

Carolin Frank, Kevin Vomschee, Tuan Thien Tran et al. (+6 more)

Surface contamination strongly affects the intrinsic properties of nanoscale materials, making its reliable identification and quantification crucial for both accurate experimental interpretation and nanofabrication. Although scanning transmission electron microscopy can resolve contaminants at atomic resolution within nanometer-scale regions, it cannot easily provide a quantitative, large-area contamination measure. Here, we introduce a minimally destructive recoil-projectile coincidence method for ion transmission experiments that enables element-specific identification and quantification of surface contaminants with isotopic resolution. We demonstrate this approach by comparing self-supporting graphene samples prepared using either a polymethylmethacrylate (PMMA)-based or a PMMA-free transfer process. Carbon and hydrogen are identified as the dominant surface contaminants. PMMA-free transferred graphene exhibits the lowest native contamination levels. Following in-situ thermal annealing at 400 {\deg}C for 1 h, the measured carbon areal density approaches the value expected for atomically clean single-layer graphene within the experimental uncertainty, while hydrogen coverage is strongly reduced. Unlike PMMA-transferred graphene, which rapidly recontaminates after annealing, PMMA-free transferred graphene remains nearly contamination-free for at least 140 min under ultra-high vacuum conditions ($p_{\mathrm{base}} = 2 \times 10^{-8}$ mbar). Beyond graphene, the presented method establishes a quantitative characterization platform for ultrathin materials, enabling studies of surface cleanliness, adsorption, implantation and surface interaction dynamics in such systems.
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All authors Carolin Frank, Kevin Vomschee, Tuan Thien Tran, Barbara Maria Mayer, Radek Holeňák, Yossarian Liebsch, E. Harriet Åhlgren, Marika Schleberger, Daniel Primetzhofer

Materials Science · Cross-listed from cond-mat.supr-con

Structural stability, electronic structure, and magnetism of the $d^9$ double infinite-layer La$_3$Ni$_2$O$_5$F under chemical pressure and epitaxial strain

K. Madani, Q. N. Meier and A. Cano

Nickelate materials exhibit rich electronic properties that can be engineered toward cuprate-like regimes through topotactic and mixed-anion chemistry. Using first-principles calculations, we investigate the newly synthesized double infinite-layer oxyfluoride La$_3$Ni$_2$O$_5$F and its evolution under chemical pressure and epitaxial strain. The calculated phonon spectrum confirms the dynamical stability of the reported double infinite-layer crystal structure. Further, we find a highly two-dimensional cuprate-like Fermi surface dominated by Ni-$d_{x^2-y^2}$ states, with a moderate rare-earth-derived self-doping yielding an effective $\sim d^{1.2}_{x^2-y^2}$ filling. These electronic features remain remarkably robust under both chemical pressure and epitaxial strain. Spin-polarized calculations further reveal an extended manifold of nearly degenerate magnetic configurations with different in-plane and out-of-plane spin arrangements. Compressive strain further enhances this magnetic frustration while leaving the underlying electronic structure largely unchanged. Our results thus identify La$_3$Ni$_2$O$_5$F as a promising cuprate analogue and establish lattice engineering as an effective strategy for fine tuning its electronic and magnetic properties.
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Materials Science · Cross-listed from physics.bio-ph

Hair is a functionally graded composite, not a uniform fiber

Andrew K. Schulz, Svetlana Griego, Vesna Srot et al. (+11 more)

Hair provides mammals with diverse benefits, including protection, thermoregulation, and enhanced sensory perception. Unlike tendons and teeth, which are biomineralized, hair is hypothesized to accomplish its structure-function relationship purely through keratin, a fibrous protein that provides structural integrity. Recent research showed that mechanical properties can vary substantially both within and across hair types: the whiskers of Asian elephant (Elephas maximus) exhibit a two-order-of-magnitude material stiffness reduction from base to tip, whereas elephant body hairs are nearly homogenous. Here, we demonstrate that three hierarchical structures vary significantly along the body hairs and whiskers of domestic cat (Felis catus): the layered outer keratin wall, 250-nm-diameter melanosome-like granules in the cortex, and calcium enrichment of these granules. As occasionally described for human hair, the oblong granules are arranged in longitudinal channels, potentially reinforcing the cortex; their prevalence correlates with local mechanical properties along the hair's length. Prolonged chemical treatment of body hairs removes calcium from the granules while breaking down the outer cuticle and internal cortex, hardening bases and splitting tips. Though previously assumed uniform, morphology, composition, and elemental enrichment can change along hairs, producing composite structures with functional gradients.
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All authors Andrew K. Schulz, Svetlana Griego, Vesna Srot, Giulia Ballardini, Natalia Gonzalez-Vazquez, Devin Sheehan, Felicitas Predel, Cem Balda Dayan, Deepti S. Philip, Helena Vrencev, Jelena Lazovic, Peter A. van Aken, Gunther Richter, Katherine J. Kuchenbecker

Materials Science

Switchable Altermagnetism via Spin-Induced Improper Polarization

Zhihao Dai, Michele Reticcioli, Wei Ren et al. (+2 more)

Enabling reversible spin-splitting switching in stray-field-free altermagnets is promising for spintronic applications, but currently limited to a narrow class of polar materials. We propose a broader approach based on spin-induced improper polarization in nonpolar dual-sublattice magnets. We demonstrate this mechanism in DyFeO3, where the product of nonpolar Fe and Dy spin modes transforms as an induced polar mode. Density functional theory shows that the relative Dy–Fe spin alignment selects the polarization, while the Fe sublattice controls nonrelativistic spin splitting, thus enabling reversible switching. These results establish spin-induced improper polarization as a route to switchable altermagnetism in nonpolar bulk systems.
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All authors Zhihao Dai, Michele Reticcioli, Wei Ren, Hongjun Xiang, Alessandro Stroppa

Materials Science

Ferrimagnetic Skyrmions in a Tetragonal Mn1.9Co0.1Sb Single Crystal at Room Temperature

Huanhuan Zhang, YaJiao Ke, Weiwei Wang et al. (+10 more)

The development of room temperature small-sized ferrimagnetic skyrmion materials is significant for topological spintronic device applications. As a room temperature ferrimagnetic material, the tetragonal Mn1.9Co0.1Sb crystal exhibits multiple phase transitions, including spin reorientation transitions. However, the magnetic spin textures and their evolution mechanisms during magnetic phase transitions in Mn1.9Co0.1Sb crystals remain unexplored. Using Lorentz transmission electron microscopy, we discovered and verified dipolar skyrmion behavior and its magnetic evolution at room temperature. We established a stable phase diagram of magnetic textures as functions of temperature and magnetic field, while also investigating the evolution mechanisms of spin textures across multiple temperature-induced magnetic phase transitions. Through micromagnetic simulations, a ferrimagnetic configuration with in-plane ferromagnetic coupling and interlayer antiferromagnetic arrangement was established, which stands in contrast to synthetic ferrimagnetic/antiferromagnetic systems that exhibit interlayer antiferromagnetic coupling via the Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction. We determined that the intrinsic frequency of ferrimagnetic skyrmions can reach the THz regime due to strong interlayer antiparallel exchange interactions. These findings highlight the diversity of room temperature ferrimagnetic skyrmion regulation behaviors in Mn1.9Co0.1Sb and their dynamic evolution characteristics, opening new avenues for developing novel spintronic devices with enhanced functionalities capable of operating under ambient conditions.
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All authors Huanhuan Zhang, YaJiao Ke, Weiwei Wang, Lingyao Kong, Lin Chen, Sheng Qiu, Jialiang Jiang, Yongsen Zhang, Youhong Peng, Yaodong Wu, Mingliang Tian, Haifeng Du, Jin Tang

Materials Science

Enhanced Curie temperature and room-temperature 50-nm skyrmions achieved in hexagonal ferromagnet Mn5Ge3+x synthesized via a high-pressure method

Yongsen Zhang, Wei Liu, Meng Shi et al. (+14 more)

The development of new high-temperature ultrasmall-size skyrmion materials holds immense significance for the promising applications of topological spintronic devices. In this study, we demonstrate that a high-pressure synthesis technique can significantly elevate the Curie temperature of Mn5Ge3+x crystals, from 294 K to 350 K. This enhancement is attributed to the combined effects of lattice contraction and increased Ge content, the conclusion supported by Density Functional Theory calculations. Additionally, our real-space magnetic imaging reveals the stability of dipolar skyrmions with diameters of approximately 50 nm at room temperature. Our micromagnetic simulations closely replicate the diverse experimental topological magnetic textures observed. Furthermore, magnetotransport measurements indicate the potential for the electrical distinction between various topological magnetic textures in skyrmion-based devices. We also report deterministic manipulations on single dipolar skyrmions in confined nanostructures by using in-plane currents. The observation, electrical manipulation, and electrical detection of room-temperature ultrasmall topological magnetic textures underscore the potential of Mn5Ge3+x as a promising platform for spintronic device applications.
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All authors Yongsen Zhang, Wei Liu, Meng Shi, Shuisen Zhang, Sheng Qiu, Yaodong Wu, Jialiang Jiang, Huanhuan Zhang, Hui Han, Kang Wang, Dingfu Shao, Zhenfa Zi, Chao Ma, Haifeng Du, Mingliang Tian, Shouguo Wang, Jin Tang

Materials Science · Cross-listed from cond-mat.mes-hall

Current-induced creation and dynamics of embedded magnetic skyrmion bags

Yaodong Wu, Jialiang Jiang, Lingyao Kong et al. (+5 more)

Magnetic skyrmion bags-vortex-like structures hosting multiple skyrmions with tunable topological charge (Q)-hold significant promise for next-generation spintronic computing. However, while their creation using magnetic fields has been demonstrated, their direct electrical generation remains an outstanding challenge. Here, we report the direct current-induced formation and manipulation of embedded skyrmion bags in a FeGe nanoplate under zero magnetic field. Using in-situ Lorentz transmission electron microscopy, we capture the transformation of a distorted helical ground state into embedded skyrmion bags with diverse configurations, driven by nanosecond current pulses. Theoretical analysis indicates that this process is driven by the spin-transfer-torque-induced fracture of the helical state. Furthermore, we demonstrate electrically-induced transitions between skyrmion bags of different Q, leading to the stabilization of complex three-dimensional topological structures, including experimental signatures of magnetic monopoles and bobbers. Our work establishes a foundation for all-electrical control of high-Q topological spin textures and topological defects, paving the way for their application in functional spintronic devices.
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All authors Yaodong Wu, Jialiang Jiang, Lingyao Kong, Meng Shi, Shouguo Wang, Mingliang Tian, Haifeng Du, Jin Tang

Materials Science

Crystallization of pristine cubic ice from liquid at ambient pressure

Chenwei Zheng, Paul F. Henry, Aasim I. Shaffi et al. (+11 more)

The phase diagram of frozen water is famously rich: to date, over twenty crystalline polymorphs have been identified. Of the low-pressure 'ice I' family, hexagonal (Ih) is the principal form on Earth, while cubic (Ic) is much more elusive. Fundamental questions remain open as to whether cubic ice Ic can form directly from the liquid state, its thermodynamic stability and natural occurrence. Here we show that pristine cubic ice Ic can be formed at atmospheric pressure simply by cooling an aqueous solution confined within mesoporous silica. Using primarily neutron scattering, we show unambiguously that under these conditions, cubic ice Ic forms reproducibly and is the only thermodynamically stable crystalline phase of water. The discovery that cubic ice Ic is directly accessible from the liquid state, and stable at atmospheric pressure, strongly suggests that this polymorph plays a much more significant role in natural and synthetic processes than previously thought.
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All authors Chenwei Zheng, Paul F. Henry, Aasim I. Shaffi, Sanghamitra Mukhopadhyay, Miroslava Novoveska, Milz L. Beaumont, Yidan Wang, Camilla Di Mino, Tom F. Headen, Marta Falkowska, Christopher A. Howard, Adam J. Clancy, Christoph G. Salzmann, Neal T. Skipper

Thursday 23 July

Materials Science · Cross-listed from physics.geo-ph

High solubility of water in post-perovskite and bridgmanite in the Earth's deep lower mantle

Megumi Semba, Naoya Sakamoto, Shuhei Mita et al. (+5 more)

Water in the Earth's mantle induces melting, giving rise to strong chemical heterogeneity, and alters its rheological and transport properties, which are keys to understanding seismic-wave speeds anomalies, convective motions and electrical conductivity. However, the abundance of water and its role in the deep mantle remain uncertain and controversial, particularly at conditions of the core-mantle boundary (CMB) region. Here we carry out melting experiments on a hydrous, natural mantle composition including both $H_2O$ and $D_2O$ over the entire pressure range of the Earth's lower mantle, in which melt coexists with bridgmanite (Bdg) and/or post-perovskite (PPv), the primary constituents of the respective lower and lowermost mantle. High-resolution secondary-ion mass spectroscopy (Cryo-SIMS) measurements reveal high water concentrations in Bdg (up to 5,500 ppm by weight) and PPv (up to 1.22 wt%) with strong enrichment in deuterium/hydrogen (D/H) relative to coexisting melt. The high solubilities of water in Bdg and PPv at CMB conditions suggest that subducting slabs do not release water when they reach the bottom of the mantle, and such a process cannot account for strong chemical heterogeneities inferred in the lowermost mantle and the topmost outer core, nor for ultralow-velocity zone (ULVZ)-like structures in seismically fast regions. Water-rich Bdg and PPv may be present in the large low shear velocity provinces and ULVZs, which may be the residue of a basal magma ocean and are predicted to host a deep low D/H water reservoir inherited from the early Earth that is occasionally sampled by plumes of a lowermost-mantle origin.
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All authors Megumi Semba, Naoya Sakamoto, Shuhei Mita, Kei Hirose, Yutaro Tsutsumi, Keisuke Ozawa, John W. Hernlund, Shiro Miwa

Materials Science · Cross-listed from eess.IV

pyALDIC: A Python Implementation of Augmented Lagrangian Digital Image Correlation with a GUI, Adaptive Meshing, and Mask-Aware Subset Splitting

Zixiang Tong and Jin Yang

pyALDIC is an open-source Python implementation of augmented Lagrangian digital image correlation (AL-DIC) for full-field displacement and strain measurement. The software combines a graphical user interface with a scriptable Python API and supports adaptive quadtree meshing, mask-aware subset splitting near cracks and holes, and selectable Local DIC and AL-DIC solver modes. Numba acceleration enables efficient analysis, while automated tests, documentation, and reproducible examples support reliable use acrossWindows, macOS, and Linux. Verification cases include synthetic displacement fields, rigid-body motion, Mode-I cracking, adaptive refinement, and experimental uniaxial tension. pyALDIC is distributed through PyPI, GitHub, and Zenodo under a BSD-3-Clause license for reproducibility. pyALDIC is openly available at https://github.com/zachtong/pyALDIC.
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Materials Science

Effect of Al-Zn alloy wafer grain boundary diffusion on the magnetism and microstructure of sintered NdFeB magnets

Xi Liu, Wenxi Fang and Ken Perlin

This study investigates Al-Zn grain boundary diffusion (GBD) treatment on sintered Nd-Fe-B magnets using $Al_{80}Zn_{20}$ alloy sheets as the diffusion source. The alloy sheets were placed at both ends of cylindrical samples and diffusion-annealed at 900$^\circ$C and 700$^\circ$C for 7 hours under vacuum ($\leq5\times10^{-3}$ Pa), followed by tempering at 500$^\circ$C for 2 hours. Magnetic measurements show that coercivity increases from 951.5kA/m in the untreated sample to 1158.2kA/m at 900$^\circ$C (a gain of 206.7kA/m, 21.7%) and to 1039.6kA/m at 700$^\circ$C (a gain of 88.1kA/m, 9.3%), while remanence declines modestly from 1282mT to 1256mT after the high-temperature treatment. Scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray diffractometer (XRD) analyses reveal that the 900$^\circ$C treatment produces a thinner, more continuous grain boundary phase and a distinct core-shell structure around the main-phase grains. EDS mapping shows that Al preferentially enriches the shell region of the $Nd_2Fe_{14}B$ grains, while Zn predominantly resides in the grain boundary phase, where it lowers the melting point of the intergranular phase and improves its fluidity. XRD shows no detectable secondary phases, while the combined XRD, EDS results, and lattice expansion are consistent with possible limited Al incorporation into the main-phase lattice. Verified by computational analysis, the coercivity enhancement is attributed to three synergistic factors: improved grain boundary decoupling, the formation of a high-anisotropy shell layer that strengthens domain-wall pinning, and the smoothing of grain edges to suppress reverse-domain nucleation.
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Materials Science

Property-Guided Diffusion for Inverse Design of Crystalline Materials

Sourav Mal, Subhankar Mishra and Prasenjit Sen

Diffusion-based generative models with property guidance have emerged as a promising paradigm for inverse materials design by enabling the generation of crystalline materials with user-specified target properties. However, despite recent advances, the effectiveness of property guidance, its influence on crystallographic symmetry, and the physical viability of generated materials remain poorly understood. To address these questions, we develop a property-guided framework based on the lightweight diffusion model DiffCrysGen using parameter-efficient adapter fine-tuning and classifier-free guidance (CFG). The resulting framework enables efficient multi-property crystal generation while preserving the knowledge learned during unconditional pre-training. Using formation energy together with saturation magnetization and Vickers hardness as representative inverse-design tasks, we systematically investigate the influence of CFG across a broad range of guidance strengths. Increasing the guidance scale progressively steers the generated property distributions toward the prescribed targets while reducing the fraction of lowest-symmetry ($P1$) structures and increasing the proportion of higher-symmetry structures. To evaluate physical viability, generated structures are geometrically prescreened and subsequently validated using a machine-learning interatomic potential (MLIP)-based workflow comprising structural relaxation and thermodynamic, dynamical, and property-specific analyses. The framework identifies thermodynamically and dynamically stable magnetic and mechanically hard materials with overall success rates of 12.3% and 3.9%, respectively. These results establish property-guided DiffCrysGen as an efficient framework for inverse materials design while providing new insights into the role of classifier-free guidance in crystal generation.
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Materials Science · Cross-listed from physics.comp-ph

Learning Lattice Parameters from Powder X-Ray Diffraction Data Using Invariants

Elyssa Hofgard, Kyucheol Min, Nofit Segal et al. (+8 more)

We present a machine learning (ML) method to determine unit cell parameters from powder X-Ray diffraction (XRD) data using a novel invariant lattice representation. In ML, the data representation used can have a substantial impact on the prediction quality. Previous approaches have directly predicted lattice parameters ($a,b,c,\alpha,\beta,\gamma$) from XRD inputs. However, these parameters depend strongly on the unit cell reduction or convention used. In this work, we construct an invariant representation of the reciprocal lattice that is independent of primitive cell convention, based on the bispectrum–a descriptor built from spherical harmonic projections of lattice points. The calculation of the lattice bispectrum is differentiable, and we demonstrate how to invert it using gradient-based optimization initialized from a nearest-neighbor lookup. We show that with a fixed ML model architecture, using the lattice bispectrum as the ML target rather than the unit cell parameters leads to more accurate lattice parameter predictions. For example, using the MP-20 dataset, the bispectrum reduces length mean absolute percentage error (MAPE) from 11.08% to 2.43% and angle MAPE from 12.15% to 2.45% compared to direct prediction with the same model architecture. We additionally benchmark our approach against pre-existing XRD to crystal structure models such as Crystalyze and assess its performance on experimental data. Beyond unit cell representation, we anticipate this invariant lattice representation could serve more broadly as a geometry-aware target for other crystallographic machine learning tasks such as structure generation.
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All authors Elyssa Hofgard, Kyucheol Min, Nofit Segal, David W. Mittan-Moreau, Aria Mansouri Tehrani, Vanessa Oklejas, Rafael Gómez-Bombarelli, Jigyasa Nigam, Daniel W. Paley, Aaron S. Brewster, Tess Smidt

Materials Science · Cross-listed from cond-mat.mes-hall

Observation of room temperature intrinsic nonlinear thermoelectric effects in low-dimensional semimetals

Kurea Nakagawa, Krishnaraajan Sundararajan, Cédric A. Cordero-Silis et al. (+2 more)

Nonreciprocal control of thermoelectric responses offers a promising strategy for next-generation thermal-management and energy-conversion. While nonlinear electrical transport has recently emerged as an intrinsic property of low-symmetry quantum materials, their thermoelectric counterparts have not been demonstrated. Here, exploiting harmonic detection with gradient-reversal techniques, we report intrinsic nonlinear thermoelectric responses up to room temperature in the low-symmetry type-II Weyl semimetals $T_\mathrm{d}$-WTe$_2$ and TaIrTe$_4$ in the absence of magnetic fields or magnetic materials. We resolve all symmetry-allowed components of the second-order thermoelectric tensor, including the nonlinear Seebeck, nonlinear Nernst, and nonlinear mixed-directional thermoelectric effects and demonstrate that both Berry-curvature-related and scattering-induced contributions govern the different nonlinear thermoelectric responses. Our results show that nonlinear thermoelectricity arises intrinsically from reduced crystal symmetry and that engineering effects related to scattering in these materials provides a versatile platform for exploring higher-order heat-to-charge current conversion beyond the linear response.
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All authors Kurea Nakagawa, Krishnaraajan Sundararajan, Cédric A. Cordero-Silis, Bart J. van Wees, Marcos H.D. Guimarães

Materials Science · Cross-listed from physics.optics

Towards on-chip nascent all-van-der-Waals polarization optical components for nanoscale photonic applications

Dmitrii Litvinov, Ilia Begichev, Iakov Reznikov et al. (+8 more)

The integration of polarization-control elements into nanoscale photonic circuits remains a central challenge for modern on-chip optical technologies, which call for continuous miniaturization. Van der Waals (vdW) crystals provide a versatile platform for the creation of such components owing to their strong optical anisotropy, high-refractive indices and atomically precise heterostructure assembly capabilities. In this work, we demonstrate an approach towards the creation of all-vdW on-chip polarization optical components, exemplified with quarter-wave plates operating in the near-infrared (NIR) spectral region, realized in specifically twisted ReSe2/alpha-MoO3 vdW heterostructures on a Si/SiO2 platform. Here, low-symmetry ReSe2 layer serves as a source of exceptionally high linearly polarized excitonic emission, whereas in-plane birefringent alpha-MoO_3 provides polarization-state conversion. Furthermore, our finite-difference time-domain (FDTD) simulations quantitatively reproduce the experimental observations with high accuracy revealing the critical roles of layer thicknesses, twist-angle, Fabry-Perot interference and emitter distribution effects in the determination of polarization conversion efficiency, which yields up to 95 % degrees of circular polarization (DoCP) for the optimized parametrization. Our findings establish a practical route towards fully integrated all-vdW polarization optical components, providing a foundation for nanoscale photonic architectures based entirely on layered materials.
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All authors Dmitrii Litvinov, Ilia Begichev, Iakov Reznikov, Changyi Chen, Maksim Sargsyan, Sergey Y. Grebenchuk, Makars Siskins, Kostya S. Novoselov, Alexey I. Berdyugin, Maciej Koperski, Davit A. Ghazaryan

Materials Science

Ionic Diffusion Properties of Rare-Earth High-Entropy Oxides from a Machine-Learned Interatomic Potential

Mary Kathleen Caucci, Billy E. Yang, Saeed S.I. Almishal et al. (+2 more)

Rare-earth high-entropy oxides (RE-HEOs) have emerged as a promising class of functional ceramics for solid-state electrochemical applications due to their chemical complexity, structural tunability, and potential for fast oxygen-ion transport. In this work, we investigate oxygen diffusion in ceria-based RE-HEOs of the form Ce$_x$(YLaPrSm)$_{1-x}$O$_{2-\delta}$ using classical molecular dynamics simulations driven by the Crystal Hamiltonian Graph Neural Network (CHGNet) machine-learned interatomic potential. To improve predictive accuracy for lanthanide-containing systems, we benchmark three CHGNet variants, including a fine-tuned r$^2$SCAN-trained model, against targeted density functional theory (DFT) data that explicitly include f-valence electrons. Simulations across temperature, Ce content, oxygen vacancy concentration, and both fluorite and bixbyite structures reveal that oxygen transport in RE-HEOs is governed by the interplay of two factors: the concentration of mobile vacancies and the local cation environment through which they hop. At fixed composition, ionic conductivity exhibits a non-monotonic dependence on vacancy concentration, with optimal diffusion occurring at moderate vacancy levels and reduced mobility at higher concentrations. Increasing Ce content lowers migration activation energies and enhances diffusivity through low-barrier diffusion networks built from Ce-Ce and Ce-Y edges. Analysis of individual oxygen hopping events provides atomistic insight into how local chemical environments and short-range cation ordering govern transport in high-entropy oxides. Overall, this work demonstrates that machine-learned interatomic potentials can resolve composition-structure-transport relationships in chemically complex oxides, and identifies active pathways through which compositional tuning can enhance oxygen-ion conductivity in RE-HEO materials.
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All authors Mary Kathleen Caucci, Billy E. Yang, Saeed S.I. Almishal, Jon-Paul Maria, Susan B. Sinnott

Materials Science · Cross-listed from cond-mat.mes-hall

Real-Space Imaging of Band Topology via Wavefunction Zeros

Julian Ingham and Raquel Queiroz

We prove that the wavefunction of a crystal at a high-symmetry momentum, $\Psi_{\boldsymbol{k}_*}(\boldsymbol{r})$, has symmetry-enforced zeros at certain positions in the unit cell, using a new invariant fixed uniquely by the symmorphic symmetry representation of the wavefunction. This allows one to infer the topology of an electronic band by probing zeros of the charge density, and in turn to connect scanning tunnelling microscopy to the group representation theory of bandstructure. We apply the theorem to 1H transition metal dichalcogenides, where it detects the obstructed atomic limit of WSe$_2$, the Haldane model, where it detects the Chern number modulo three, and the Bernevig-Hughes-Zhang model, where it detects the $\mathbb{Z}_2$ index. In addition, the zeros have important consequences for interaction effects: in kagome metals, they fix the sublattice structure of Van Hove wavefunctions, and in twisted bilayer graphene, they explain the qualitative interaction-induced reshaping of the flat bands.
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Materials Science

Symmetry-Adapted Physical and Vibrational Properties of Ferroelectric Perovskite Oxides: Application to PbZrxTi1-xO3

Sumit Ranjan Maity and Brajesh Tiwari

Crystal symmetry governs macroscopic physical properties and lattice dynamics in functional materials. We present a systematic application of tensor analysis and group theory to determine allowed physical-property tensors, vibrational-mode symmetries, and Raman selection rules directly from crystallographic point-group symmetry. The approach is applied to the prototypical ferroelectric PbZrxTi1-xO3 (PZT). Symmetry lowering across the PZT phase diagram increases the number of independent pyroelectric, dielectric, and piezoelectric tensor components and modifies the symmetry classification of Raman-active vibrations. These mode classifications enable symmetry-based decomposition of reported room-temperature powder Raman spectra as a function of composition (x) across the morphotropic phase boundary, revealing the tetragonal-to-rhombohedral transition as a continuous redistribution of spectral intensity rather than emergence of new Raman modes. Persistent subpeak structure in selected modes indicates local symmetry breaking due to cation disorder and lattice anharmonicity, underscoring the importance of crystallographic symmetry analysis for interpreting functional and vibrational properties of ferroelectric perovskite oxides.
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Materials Science · Cross-listed from cond-mat.supr-con

Sequential Topological Superconductivity in a Square Lattice with Chiral Charge Density Waves

Zhong-Xian Jin, Junkang Huang, Yu-Xuan Li et al. (+1 more)

The interplay between charge order and superconductivity offers a fertile ground for emergent quantum phases. Here we theoretically investigate a square-lattice superconductor coexisting with a composite charge density wave (CDW) consisting of a real bond modulation (charge bond order, CBO) and an imaginary hopping modulation (chiral flux phase, CFP) that breaks time-reversal symmetry. We uncover that, while CFP alone does not induce topology in square lattices, its coexistence with CBO drives the system into two topologically nontrivial superconducting phases with Chern numbers $C=+2$ and $C=-2$. The low-temperature thermal Hall conductivity $\kappa_{xy}$ exhibits quantized plateaus proportional to the Chern number, providing a clear experimental fingerprint. Our results establish the square lattice as a pristine platform for engineering topological superconductivity through the synergy of real and imaginary bond modulations.
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All authors Zhong-Xian Jin, Junkang Huang, Yu-Xuan Li, Tao Zhou

Materials Science · Cross-listed from cond-mat.supr-con

Supercurrent effect in a charge density wave intertwined superconductor

Zhen Zhu, Wei Cheng, Dang Liu et al. (+15 more)

The energy-momentum (E-k) dispersion of quasiparticles constitutes a fundamental concept in condensed matter systems. The ability to modify the E-k dispersion, exemplified by supercurrent-induced Doppler shifts of Bogoliubov quasiparticle spectra in superconductors, enables manipulation of various emergent quantum properties. However, investigations into the supercurrent effect on superconductors intertwined with charge orders remain scarce. Here, we report that the Meissner current, generated by the diamagnetic response to an applied in-plane magnetic field, can tailor Bogoliubov quasiparticle excitations at the precursor charge density wave (CDW) vectors. Our scanning tunneling spectroscopic imaging reveals a field-driven symmetry breaking of CDW modulations, specifically a C3v-to-Cs transition, in superconducting NbSe2. Model calculations suggest that the observed anisotropy originates from a selective Doppler-shift-induced E-k dispersion reconstruction. Furthermore, altering the field direction enables on-demand tuning of anisotropic CDW modulations and visualization of their momentum-space distribution. These results highlight a novel mechanism for controlling emergent electronic phases through momentum-space engineering.
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All authors Zhen Zhu, Wei Cheng, Dang Liu, Pengyu Hu, Yi Yang, Qiaoyan Yu, Shasha Xue, Ruijun Xi, Xingsen Chen, Jice Sun, Dandan Guan, Yaoyi Li, Shiyong Wang, Canhua Liu, Zhuan Xu, Xin Liu, Hao Zheng, Jinfeng Jia

Materials Science · Cross-listed from physics.chem-ph

Graph Neural Network Force Fields (GPTFF-mol) for Organic Molecules from Optimization Trajectories (OpenGEM26)

Yifan Huang, Fankai Xie, Jiangnan Zheng et al. (+3 more)

Density functional theory (DFT) serves as a reliable tool for atomistic molecular simulations, while machine learning potentials have become powerful complements to balance accuracy and efficiency. In this work, we release OpenGEM26 (Open Generated Ensemble of Molecules, 2026), a large-scale dataset comprising 200,000 unique molecules and 4.4 million conformations composed of H, C, N, O, S and Cl with up to ten heavy atoms. All calculations are carried out at the {\omega}B97X-D/Def2-SVP and Def2-TZVP levels with dispersion corrections, and complete structural optimization trajectories and abundant non-equilibrium structures are recorded. Statistical analyses confirm that this dataset covers a broader conformational space than QM9 in terms of energy, bond lengths and bond angles. A graph neural network-based potential GPTFF-mol is trained using the new dataset, achieving an energy mean absolute error of 16 meV/molecule, which is equivalent to 0.82meV/atom, and superior force prediction performance compared with ANI-2x. Validated by butane rotation and keto-enol tautomerization tests, the model accurately describes molecular dynamical behaviors and reaction barriers at distorted geometries. This work provides a high-quality resource and robust ML potential for efficient simulations of sulfur- and chlorine-containing organic molecules.
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All authors Yifan Huang, Fankai Xie, Jiangnan Zheng, Tenglong Lu, Sheng Meng, Miao Liu

Materials Science · Cross-listed from cond-mat.mes-hall

Visualization of Defect Electronic States in Layered Semiconductor CrSBr

Jonathan Brunette, Joost Aretz, Kiyoung Jo et al. (+5 more)

Chromium sulfur bromide (CrSBr) is a layered magnetic semiconducting material combining a rich magnetic phase diagram with axis-dependent electronic and optical properties. While defects in CrSBr have been shown to affect magnetic order and excitonic responses, their microscopic nature, atomic structure, and electronic properties are not yet fully understood. In this work, we use scanning tunneling microscopy/spectroscopy (STM/STS) to explore the structure and electronic signatures of two prominent defects in bulk CrSBr. Their structure reflects the symmetries of the underlying lattice, with electronic features near the valence band edge. By comparing experimental data with ab initio simulated STM images, we infer that a common defect corresponds to a b-axis-aligned double sulfur vacancy, in line with findings from a recent growth analysis study. This result advances our understanding of the role of intrinsic defects in shaping the electronic structure of CrSBr.
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All authors Jonathan Brunette, Joost Aretz, Kiyoung Jo, Aljoscha Soll, Zdeněk Sofer, Malte Rösner, Nathan Guisinger, Adina Luican-Mayer

Materials Science

Lifetime effects and satellites in the photoelectron spectrum of platinum metal

Prajna Bhatt, José Julio Gutiérrez Moreno, Laura E. Ratcliff et al. (+9 more)

This work presents a comprehensive investigation of the electronic structure and many-body photoemission effects in metallic platinum using reflection high-energy electron energy-loss spec- troscopy (RHEELS), soft X-ray photoelectron spectroscopy (SXPS), and hard X-ray photoelectron spectroscopy (HAXPES), supported by ab initio calculations. Shallow and deep core state spectra enable the systematic characterisation of intrinsic line-shape asymmetries and satellite structures. Correlation of photoelectron satellites with RHEELS loss features allows the assignment of inter- band transitions, surface and bulk plasmons, plasmonic overtones, and semi-core ionisation losses across the Pt spectrum. Several previously unresolved satellite features and spin-orbit splittings are identified and discussed. Comparison of experimental valence band spectra with orbital-projected densities of states calculated using ab initio density functional theory (DFT) and G0W0 approaches, with and without spin-orbit coupling, demonstrates the critical role of relativistic effects in reproducing the Pt valence electronic structure. Together, these results establish a unified, internally consistent spectroscopic reference for metallic platinum, providing a robust framework for interpreting photoelectron spectra of Pt-containing catalysts, electronic materials, and related 5d transition metal systems.
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All authors Prajna Bhatt, José Julio Gutiérrez Moreno, Laura E. Ratcliff, Aysha A. Riaz, Charlotte. M. L. André, Ann S. Y. Lu, Robert G. Palgrave, Andrei Gloskovskii, Christoph Schlueter, Pardeep K. Thakur, Tien-Lin Lee, Anna Regoutz

Materials Science · Cross-listed from physics.chem-ph

Determination of fundamental properties of nitrogen from first principles. III. Temperature and frequency dependence of the molecular polarizability and magnetic susceptibility

Jakub Lang, Giovanni Garberoglio, Michał Przybytek et al. (+1 more)

This work is the third part of the series of papers that focus on the theoretical determination of the properties of nitrogen that are relevant in metrology. Here we present first-principles calculations of the temperature and frequency dependence of the molecular polarizability and magnetic susceptibility of the nitrogen molecule (N$_2$). The purely electronic contributions to the static polarizability, Cauchy coefficients (up to sixth order), and isotropic magnetic susceptibility are computed over a range of internuclear distances using a robust composite scheme combining several electronic structure methods. The temperature dependence, evaluated from $50$~K to $2000$~K, is determined using two independent methods: rovibrational averaging and path integral Monte Carlo (PIMC). The polarizabilities obtained from theory agree with the recent high-precision thermometry measurements, wherever the latter are available, but are significantly less accurate. However, the main usefulness of the theoretical data revolves around combining it with the available experimental results to generate semi-empirical estimates of various quantities that have never been measured thus far. As an example, we determine highly accurate semi-empirical estimates of the static polarizability at key reference temperatures, $\alpha_0(T)=11.735\,962$~a.u.\ at $T=303$~K and $\alpha_0(T)=11.735\,585$~a.u.\ at $T=273.16$~K. Furthermore, we report theoretical values for the magnetic susceptibility, highlighting the importance of the paramagnetic contribution, and address a significant discrepancy with the experimental data for this quantity.
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All authors Jakub Lang, Giovanni Garberoglio, Michał Przybytek, Michał Lesiuk

Materials Science

Machine learning based prediction of optical properties in two-dimensional Mo-W-S-Se-Te transition-metal dichalcogenide alloys through physics-informed sampling

Vivek Chowdhury, Tarvir Anjum Aditto, Md. Samrat et al. (+2 more)

Two-dimensional transition-metal dichalcogenide (TMD) alloys provide a compositionally tunable platform for controlling the optical and electronic properties. However, systematic prediction of their dielectric response across multicomponent alloy spaces remains challenging owing to the combinatorial cost of first-principles calculations. In this work, we combined ab initio optical-property calculations with a tabular foundation-model regression to predict the real and imaginary components of the frequency-dependent dielectric function for Mo-W-S-Se-Te TMD alloys. A dataset of 99 alloy structures spanning binary, ternary, quaternary, and quinary compositions was generated using density functional theory (DFT). The resulting polarization-dependent dielectric spectra were used to train a tabular prior-fitted network (TabPFN) and evaluated against the conventional Extra Trees and XGBoost models. To accommodate the in-context capacity limit of TabPFN, we introduced a non-uniform, physics-informed energy subsampling strategy that concentrates sampling in the optically active region above the band gap, where interband absorption is strongest. Trained solely on quaternary alloys, our TabPFN reconstructed the dielectric spectra of held-out quaternary compositions with an R2 > 0.98 and a mean absolute error below 0.10 for all four dielectric components, outperforming both baselines while requiring no gradient-based training or hyperparameter tuning. Our model further predicted derived optical quantities, including refractive index, extinction coefficient, and absorption coefficient. Additionally, our model generalized in a zero-shot manner to binary, ternary, and quinary alloys absent from the training set, with quinary predictions achieving an R2 > 0.97.
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All authors Vivek Chowdhury, Tarvir Anjum Aditto, Md. Samrat, Hafiz Imtiaz, Ahmed Zubair

Materials Science · Cross-listed from cond-mat.mes-hall

Emergent ferromagnetism in the NiI$_2$-NbSe$_2$ van der Waals heterostructure

Büşra Gamze Arslan, Mohammad Amini, Ziying Wang et al. (+6 more)

Multiferroicity arising from non-collinear spin textures and strong spin-orbit interactions offers a route to magnetoelectric functionality in the monolayer limit. Although theory predicts that the properties of monolayer multiferroics can be tuned by strain, gating, or proximity effects, experimental demonstrations of such control remain scarce. Here we show that the magnetic ground state of monolayer NiI$_2$, a prototypical two-dimensional multiferroic, is altered by proximity to a superconducting NbSe$_2$ substrate. Using low-temperature scanning tunnelling microscopy (STM) and spectroscopy (STS), we show that the metallic substrate renormalizes the exchange interactions within NiI$_2$ and drives it into a ferromagnetic ground state. This can be visualized by probing the Yu-Shiba-Rusinov (YSR) states within the superconducting gap of the NbSe$_2$ substrate. Our results establish YSR states as an in situ probe of two-dimensional magnetism and demonstrate substrate engineering as a means of controlling magnetic order in atomically thin materials.
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All authors Büşra Gamze Arslan, Mohammad Amini, Ziying Wang, Alessandro Orsini, Aleš Cahlík, Jose L. Lado, Adolfo O. Fumega, Robert Drost, Peter Liljeroth

Materials Science

Magneto-Caloric effect and Multiple magnetic phases in Al doped Ni2MnSn0.75Al0.25 Heusler Alloys

Satya Vijay Kumar, Simran, Madhusmita Jena et al. (+9 more)

Among Heusler compounds,Ni based alloys have been extensively investigated because they exhibit desirable properties such as high Curie temperatures, which are advantageous for advanced magnetic and spintronic devices.The effect of Al substitution on the magnetic ground state of Ni2MnSn was investigated using the Ni2MnSn0.75Al0.25 Heusler alloy.Temperature-dependent magnetisation measurements identify a second-order paramagnetic to ferromagnetic transition at TC is 734K,followed by a first-order martensitic transformation near 263K,demonstrating strong magnetostructural coupling.Curie Weiss analysis yields a positive Weiss temperature theta CW is 746.4K and an effective magnetic moment of 6.82muB,confirming the predominance of ferromagnetic exchange interactions. The bifurcation between the ZFC and FCW magnetization curves,together with non saturating hysteretic M vs H loops, indicates the coexistence of competing ferromagnetic and antiferromagnetic interactions.Further magnetic investigations establish the formation of an interacting reentrant cluster glass state accompanied by an exchange-bias effect.The observed magnetic behavior is attributed to the modification of Mn Mn exchange interactions induced by Al substitution and the associated atomic disorder,resulting in a complex magnetic ground state.
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All authors Satya Vijay Kumar, Simran, Madhusmita Jena, Mehroosh Fatema, Atul Gangwar, Srishti Dixit, Umashankar Rajput, Nisha Shahi, Chetna Gautam, Sanjay Singh, Anup K. Ghosh, Sandip Chatterjee

Materials Science · Cross-listed from physics.comp-ph

Matrix-free phase-field modeling of fracture in micromechanical testing simulations of inelastic materials

Fabio Di Gioacchino, Rezgar Shakeri, Zachary Atkins et al. (+4 more)

Resolving steep damage gradients across diffuse cracks in the phase-field modeling of fracture favors the use of high-order finite elements, for which matrix-free methods can provide superior performance and scalability. Here, we implement the Peric & Dettmer constitutive framework for visco-elastoplastic materials in an open source solid mechanics library supporting matrix-free operators for high-order finite elements with p-multigrid preconditioning on GPUs. We introduce a rheological fracture element assembled in series so that inelastic and fracture properties can appear to affect each other only at homogenization length scales. Numerical simulations of tensile and compressive tests are conducted for synthetic particle-matrix microstructures on an El Capitan high performance computing prototype. Results are shown to reproduce characteristic inelastic responses and crack propagation patterns.
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All authors Fabio Di Gioacchino, Rezgar Shakeri, Zachary Atkins, Karen Stengel, Layla Ghaffari, Jeremy Thompson, Jed Brown