Papers

The cold source field-effect transistor (CSFET) is promising for reducing power dissipation in integrated circuits by engineering the density of states at the injecting source. Existing CSFET designs utilizing Dirac-source metals or p-Metal-n stacks are challenged by Schottky barriers at the metal-semiconductor interface. In this work, a 2D WTe$_2$/HfS$_2$ heterojunction with type-III band alignment is proposed to be an excellent design of cold source and CSFET. The architecture has a high band-to-band transport mechanism by removing the detrimental Schottky barrier issues. Importantly, the proposed CSFET has the same channel barrier modulation principle as conventional MOSFET to enable a high on-state current. Using first-principles-based quantum transport modeling, we predict a very high $I_{\rm on}$/$I_{\rm off}$ ratio at $\sim$ 10$^{10}$, a low subthreshold swing below the thermal limit for a wide range of gate voltages, reaching as small as 41.3 mV/dec, at low source-drain bias $V_{DS}=0.3$ $\rm V$. These findings establish a design principles for next-generation low-power nanoelectronic switches leveraging 2D van der Waals heterostructures.

Relaxation towards equilibrium is often assumed to be slower when a system starts farther from equilibrium, but this intuition fails in the Mpemba effect. Recent advances in controllable quantum platforms have enabled the exploration of its quantum analogue, the quantum Mpemba effect (QME), yet its microscopic origin remains largely unclear. Here we provide a general framework for understanding the QME in closed quantum many-body chaotic systems by reformulating the equilibration process of local subsystems in terms of Ruelle-Pollicott (RP) resonances. We show that suppressing the initial-state overlap with the dominant RP resonant mode accelerates subsystem equilibration and thereby yields the QME. We further uncover that a novel type of strong QME can occur via complete translation-symmetry breaking of initial states. We substantiate our predictions using the prototypical kicked Ising chain and a quantum automaton circuit. These findings cast the QME in closed many-body systems into a unified framework with open-system analogues and provide experimentally accessible signatures on state-of-the-art quantum platforms.

This work addresses the advanced degradation of plasticised PVC boards, which constitute Joseph Beuys multiples Phosphorus-Cross Sled, focusing on the mechanisms responsible for the extensive exudation of a viscous liquid. A multi-analytical approach combining chromatographic, spectroscopic, microscopic, and mechanical techniques was employed to characterise both the exuded surface layer and the polymer bulk, and to evaluate the consequences of degradation for long-term mechanical behaviour. The experimental results are supported by density functional theory simulations, which indicate a thermodynamic driving force for plasticiser migration towards the PVC surface and its tendency to self-associate. These molecular-level insights provide a mechanistic explanation for the observed migration and exudation phenomena. Overall, the study outlines a coherent deterioration pathway for exudate-covered plasticised PVC. The application of NMR spectroscopy proved to be an efficient method for studying accelerated migration of the plasticiser in PVC, opening the path to the development of non-destructive, in situ preventive conservation tools, supporting the early identification of PVC artefacts or parts of a collection that are at risk of severe phase separation.

A correspondence exists between the multi-orbital Hubbard model and the bilayer Hubbard model, in which superconductivity is optimized in an incipient-band regime in both cases. In the multi-orbital system, the orbital level offset $\Delta E$ plays a role analogous to the interlayer hopping in bilayer systems, and superconductivity is enhanced for large $\Delta E$. We refer to such a multi-orbital model as an orbital-space bilayer model (OSBM). In this study, we theoretically propose that a reduced bilayer nickelate La$_3$Ni$_2$O$_6$ can be a candidate for a superconductor described by OSBM when an appropriate amount of holes is doped. By constructing a tight-binding model based on first-principles calculations, a large $\Delta E$ between the Ni $d_{x^2-y^2}$ and the other $d$ orbitals is obtained due to the absence of outer apical oxygens. Furthermore, our fluctuation exchange approximation calculations indicate the emergence of $s\pm$-wave superconductivity driven by interorbital interactions in an incipient-band situation, where the superconducting gap function changes its sign between the $d_{x^2-y^2}$ and other $d$ orbital bands. We also investigate the energetic and dynamical stability of the crystal structure under atomic substitution and pressure. Although La$_3$Ni$_2$O$_7$ and La$_3$Ni$_2$O$_6$ share a similar chemical formula, our study shows that an entirely different pairing mechanism can take place in the latter.

The parameterization of simulation-based models is a central yet laborious task in computational chemistry and physics, often driven by human intuition and manual iteration. Automating this task necessitates the definition of suitable objective functions, which tend to be expensive to evaluate, noisy, non-differentiable, or composed of heterogeneous contributions originating from separate sets of simulations. Gradient-free and black-box optimization algorithms are powerful tools which are particularly well-suited to minimizing such objective functions. Here, we introduce ChemFit, a flexible Python framework for the definition, composition, and massively concurrent evaluation of simulation-based objective functions, which is designed to operate in conjunction with these algorithms. We demonstrate the broad applicability of this approach by using ChemFit for three representative examples of increasing complexity and real-world relevance. First, we obtain the parameters of the Lennard-Jones potential for liquid argon from experimental measurements of the density. Second, we parameterize a polarizable and flexible potential energy function to reproduce the structure of small H$_2$O clusters obtained from density functional theory calculations. Finally, we tune a small subset of the parameters of a residue-level coarse-grained protein force-field, with the goal to reproduce the experimental critical solution temperature of the low complexity domain of the wild-type hnRNPA1 sequence and an arginine-enriched mutant of this protein. hnRNPA1 is an RNA-binding protein linked to amyotrophic lateral sclerosis. Together, these examples illustrate how ChemFit enables scalable, reproducible, and optimizer-agnostic parameter fitting for broadly applicable multiscale models.

The structural, electronic, optical and transport properties of X3NbY4(X= Cu, Ag, Au; Y=S, Se, Te) sulvanite chalcogenides materials have been investigated using the Full Potential Linear Augmented Plane wave (FP-LAPW) within the density functional theory (DFT). The calculated structural information of X3NbY4 compounds is consistent with reported results of the same family compounds. The electronic band diagram exhibit indirect type band structures with bandgap value in the range of Eg 1.65- 0.50 eV using PBE-GGA functional and 1.80 eV-1.18 eV using TB-mBJ functional which indicates that these are semiconductor materials. The density of states (DOS) shows that the amount of bandgap decreases owing to move of valence band maximum (VBM) to the high energy level whereas the conduction band minimum (CBM) to the low energy level owing to the replacement of S-S-Te and Cu-Ag-Au atoms. The hybridized orbital by X-d, Nb-d and Y-p atomic orbitals dominate the VBM while hybridized by Nb-d and Y-p atomic orbitals mainly contribute the CBM. The elastic calculations exhibit that Cu-based materials have brittleness nature whereas Ag- and Au-based compounds are ductile nature. Furthermore, the phonon dispersion curves probes that these X3NbY4 compounds are dynamically stable. However, the calculated optical properties: dielectric function, absorption coefficient, refractive index, and energy loss function; specifically, the higher value of absorption coefficient (105 cm-1) indicates that these materials are attractive candidates in optoelectronics applications. Finally, thermoelectric parameters such as Seebeck coefficient, thermal conductivity, electrical conductivity, power factor (P.F) and ZT value of these compounds have also been investigated. Overall, the finding explores that these materials are potential candidates for the applications in optoelectronic and thermoelectric devices.

Entropic forces play a fundamental role in nanoscale phenomena, from colloidal self-assembly to biomolecular disaggregation. Here, we develop an exact analytical theory and find general scaling laws for the entropic separation of tether-mediated nanofilament bundles, revealing that a single dimensionless parameter–the ratio of the excluded-volume radius to the tether length–dictates whether filaments are pushed apart or, contrary to the usual expectation, pulled together. This unexpected regime challenges the view that entropic forces invariably promote disaggregation, instead uncovering conditions under which the bundles can remain in attractive metastable states. Brownian dynamics simulations confirm this paradoxical effect, offering predictive insights for applications in biophysics, soft matter physics, and nanotechnology.

Thermal stability of silicene and thin silicon films is studied by molecular dynamics using two machine-learning potentials, SNAP and GAP. For SNAP potential, systems ranging from a single silicene layer to films of 36 layers are considered. Silicene is found to lose its structure at 500 K. The decomposition temperature increases with film thikness and reaches saturation at about 28 layers, corresponding to the bulk melting point of the SNAP model (1380 K). Thin films up to 8 layers exibit two-phase coexistence upon decomposition, while thicker films undergo surface melting followed by complete collapse into the liquid state. The GAP potential, although more accurate for bulk silicon, fails to describe the gas phase: silicene modelled with GAP decomposes into a set of small clusters. The results are compared with earlier data for the Stillinger-Weber potential.

The Wiedemann-Franz (WF) law dictates a universal ratio between thermal and electrical conductivities, is widely obeyed by Fermi liquid systems. Here, we identify a fundamental yet often overlooked, thermodynamic mechanism for the violation of WF law: the temperature-dependent renormalization of the electronic band structure. We demonstrate that the interaction-induced energy drift $\partial\epsilon_k/\partial T$, acts as an effective driving force that fundamentally decouples heat transport from charge transport. We derive a generalized transport relation linking the Lorenz ratio deviation directly to the thermoelectric response. Our findings provide a unified framework for understanding thermal transport in interacting topological phases and suggest the Lorenz ratio as a probe for distinguishing topological robustness from Fermi liquid instabilities.

We show how to systematically construct weak integrability breaking perturbations (WIBs) for classical integrable models on the lattice. These perturbations, which allow quasi-conserved quantities, have mostly been explored in quantum systems, where they are expected to delay the onset of thermalization and diffusive transport to timescales far exceeding those predicted by Fermi's golden rule. However, accessing such long-time dynamics in quantum models is computationally challenging. Classical integrable lattice models offer a complementary setting for probing transport and long-time dynamics under WIBs. In this work, we specialize our general framework to construct several families of WIBs for the Ishimori model, the Toda chain, and the Harmonic Oscillator Chain (HOC). Such constructions can help quantify how WIBs contribute to anomalous transport and serve as a benchmark for thermalization studies in perturbed integrable models. An important example is the Fermi-Pasta-Ulam-Tsingou (FPUT) model: Starting from the HOC, we show that the cubic nonlinearity (the alpha-FPUT interaction) is a genuine WIB perturbation. Using the integrals of motion (IoMs) of the Toda lattice, we explicitly construct corrections to the entire hierarchy of the HOC IoMs, thereby obtaining an infinite tower of quasi-conserved quantities for the alpha-FPUT chain. We further identify the corresponding adiabatic gauge potential (AGP) as a nontrivial trilocal generator in real space, and show that, more generally, any cubic, translationally invariant, momentum-conserving perturbation of the HOC admits such a generator and is therefore a WIB. Together with our transport and AGP-variance studies, our results provide a unified classical framework for weak integrability breaking and for diagnosing anomalous thermalization and transport in nearly integrable Hamiltonian lattice systems.

The Mpemba effect, in which a system initially farther from equilibrium relaxes faster than a closer one, has been observed in a wide variety of linear and nonlinear systems. Here we develop a unified framework for the Mpemba effect in many-body systems near equilibrium based on the spectral geometry of the relaxation operator. We distinguish a non-uniform Mpemba effect, associated with a crossing of global distances to equilibrium, from a strict componentwise Mpemba effect, in which the initially hotter state remains larger in every degree of freedom yet relaxes faster. We show that reciprocal systems admit only the former, whereas reciprocity breaking renders the relaxation operator non-normal and can enable the latter. These results identify reciprocity and non-normality as key ingredients governing anomalous relaxation in linear many-body systems.

The three-dimensional (3D) microstructures of polycrystalline materials exert a critical influence on their mechanical and physical properties. Realistic, controllable construction of these microstructures is a key step toward elucidating structure-property relationships, yet remains a formidable challenge. Herein, we propose PolyCrysDiff, a framework based on conditional latent diffusion that enables the end-to-end generation of computable 3D polycrystalline microstructures. Comprehensive qualitative and quantitative evaluations demonstrate that PolyCrysDiff faithfully reproduces target grain morphologies, orientation distributions, and 3D spatial correlations, while achieving an $R^2$ over 0.972 on grain attributes (e.g., size and sphericity) control, thereby outperforming mainstream approaches such as Markov random field (MRF)- and convolutional neural network (CNN)-based methods. The computability and physical validity of the generated microstructures are verified through a series of crystal plasticity finite element method (CPFEM) simulations. Leveraging PolyCrysDiff's controllable generative capability, we systematically elucidate how grain-level microstructural characteristics affect the mechanical properties of polycrystalline materials. This development is expected to pave a key step toward accelerated, data-driven optimization and design of polycrystalline materials.

Grain growth (GG), driven by grain boundary (GB) migration, is a fundamental mechanism of microstructural evolution in polycrystalline materials. GB migration is frequently accompanied by a relative shear displacement of grains meeting at GBs, a phenomenon known as shear coupling. This coupling induces internal stresses within the microstructure, which recent studies have shown to play a decisive role in dictating the evolution of microstructure and GG pathways. This work provides a detailed characterization of the statistical features of two-dimensional GG in the presence of GB shear coupling through continuum modeling of GB migration that incorporates fundamental microscopic mechanisms and diffuse-interface simulations. We demonstrate that incorporating shear coupling produces a more heterogeneous, less equiaxed microstructure than conventional curvature-driven GG, while yielding topological and geometric properties consistent with experimental and atomistic observations. We further demonstrate that as grain grows, internal stress relaxes. Highly stressed grains shrink faster, and lightly stressed grains grow faster than other grains. These findings demonstrate that internal stress, an intrinsic feature of GG, profoundly changes essential features of GG microstructure and kinetics, consistent with experiments and atomic-scale simulations.

We study disorder effects in the extended Su-Schrieffer-Heeger (SSH) model using a convolutional neural network (CNN) trained on reduced correlation matrices (RCMs) of disorder-free systems to predict winding number phase diagrams in systems with off-diagonal and diagonal disorder. The trained CNN model generalizes to chiral-symmetry-preserving off-diagonal disorder system but fails in the presence of chiral-symmetry-breaking diagonal disorder system. Using principal component analysis (PCA) of the RCM feature space, we demonstrate that disorder-free and symmetry-preserving systems share overlapping feature manifolds, whereas symmetry-breaking disorder causes them to diverge. Inverse participation ratio (IPR) and energy spectrum analysis further demonstrate that off-diagonal disorder preserves topological edge states, whereas diagonal disorder drives a transition to an Anderson insulator. Our results show that the OOD behavior of a CNN trained on clean systems can be understood through the evolution of the RCM feature space under symmetry-preserving and symmetry-breaking disorder, with IPR and energy-spectrum analyses providing the corresponding physical interpretation.

Fracton phases are new types of phases of matter characterized by subsystem global symmetry, which is a generalized global symmetry whose symmetry operator is partially topological. Their continuum low-energy effective descriptions admit two different formulations: an exotic quantum field theory (QFT) using exotic tensor gauge fields, and a foliated QFT constructed from a foliation structure and foliated gauge fields. For certain fracton QFTs, these two descriptions are equivalent, which is called the foliated-exotic duality. In this dissertation, we extend the foliated-exotic duality by combining it with the anomaly inflow mechanism for 't Hooft anomalies of subsystem symmetries. This dissertation has two main results. First, we discuss the exotic and foliated $BF$ theories in 2+1 dimensions, which exhibit the mixed 't Hooft anomaly of $\mathbb{Z}_N \times \mathbb{Z}_N$ subsystem symmetry. This anomaly is captured by a subsystem symmetry-protected topological (SSPT) phase for $\mathbb{Z}_N \times \mathbb{Z}_N$ subsystem symmetry in one dimension higher. By extending the foliated-exotic duality in the fractonic $BF$ theory to the SSPT phase, we establish the field correspondences in the SSPT phase and construct the foliated description of the SSPT phase. Second, we discuss the exotic $\phi$-theory in 2+1 dimensions – a fractonic gapless scalar field theory, which has the 't Hooft anomaly of $U(1) \times U(1)$ subsystem symmetry. The anomaly is captured by an SSPT phase for $U(1) \times U(1)$ subsystem symmetry in 3+1 dimensions via the anomaly inflow mechanism. Extending the foliated-exotic duality to the $\phi$-theory, we establish field correspondences in the $\phi$-theory and construct the foliated $\phi$-theory that is equivalent to the exotic $\phi$-theory. This provides the first example of the foliated-exotic duality in gapless theories.

We report the experimental observation of atomic rainbow scattering of 40 keV Xe$^+$ ions transmitted through self-supporting single-layer graphene using time-of-flight medium energy ion scattering. Supported by molecular dynamics and binary collision approximation simulations, we show that the rainbow pattern of graphene consists of a small hexagonal inner rainbow, arising from projectiles with characteristic trajectories interacting with multiple carbon atoms, and a larger circular outer rainbow, arising from close binary collisions between projectiles and individual carbon atoms.

Accurate geometric decoding of moiré bilayers from imaging is essential for engineering quantum systems. Existing schemes, limited by identity or aligned assumptions requiring diagonal beating-to-moiré transformations, do not apply to general non-aligned geometries and become underdetermined when buried layers are unresolved. We establish a primitive-cell-resolved moiré crystallography framework that treats the beating-to-moiré relation in full generality and introduces a complete descriptor set $\{\theta_r,\boldsymbol{\varepsilon},(T_{Mt},T_{Mb}),N_B\}$, where the integer moiré–layer matrices $(T_{Mt},T_{Mb})$ and the beating number $N_B$ determine the commensurate unit cell. A hybrid analytical–numerical workflow reconstructs buried-layer lattices, solves Diophantine constraints to obtain $(T_{Mt},T_{Mb})$ and $N_B$, and extracts $(\theta_r,\varepsilon_b,\theta_u,\varepsilon_u)$ with Poisson effects and tensile/compressive branches treated on equal footing. Reanalyzing twisted bilayer graphene, we identify a $N_B=3$ primitive cell rather than a $N_B=9$ aligned supercell, reducing the atomistic basis threefold and correcting the moiré Brillouin-zone construction. The framework provides a crystallographically consistent route from imaging to primitive-cell-resolved atomistic and many-body models.

While current-induced bistate spin-orbit torque (SOT) switching has been well established, deterministic electrical control of multiple magnetic states remains a central challenge in spintronics. Here, we realize a conceptually new multistate SOT device in a SrIrO_3/SrRuO_3 bilayer, hosting four intrinsically stable yet electrically distinguishable magnetic states, including two in-plane canted (IP_c^$\pm$) and two out-of-plane canted (OP_c^$\pm$) states. Pulsed current excitations fully map all twelve deterministic transitions among the four states, establishing a robust switching protocol defined by two characteristic current densities. In-situ scanning nitrogen-vacancy (NV) center magnetometry provides direct real-space evidence for the previously unobserved IP_c^$\pm$ states, and spin dynamics simulations uncover a two-step switching pathway, driven by the concerted action of spin torques and the effective anisotropy field within the fourfold anisotropy landscape. Our demonstration of the intrinsic multistate SOT device directly addresses the density bottleneck of conventional bistate SOT technology, establishing a powerful paradigm for compact, high-speed, and energy-efficient multistate spintronics.

Differential phase contrast (DPC) imaging in scanning transmission electron microscopy (STEM) maps projected electric fields through the phase sensitivity of segmented low-angle detectors. Although typically applied to atomic-resolution imaging at low beam currents, STEM-DPC is here demonstrated as a rapid micro- and nanoscale image-segmentation tool for materials characterization in advanced aluminium alloys. Decomposition of false-colour DPC micrographs in hue-saturation-value space enables simultaneous identification and quantification of nanoclusters, GP zones, intermediate precipitate phases, dislocation cores, and associated strain fields within a single field of view. The method is demonstrated across multiple alloy systems, including clustering and strain-field mapping in a deformed AlMgZn(Cu) crossover alloy, precipitate identification in a paint-baked automotive sheet alloy, phase-variant segmentation in overaged AA7075-T7, and nanopore and nanoparticle detection in an anodic coating on AA2024-T3. Coupling DPC with neural-network segmentation further enables automated grain-boundary delineation and quantification in nanocrystalline aluminium thin films. Combined with STEM-EDX, DPC-based segmentation enables correlative microstructural analysis, establishing DPC as a rapid complement to techniques such as SPED and 4D-STEM.

We theoretically investigate the superconducting surface states of wallpaper fermions, which are surface quasiparticles of topological nonsymmorphic crystalline insulators protected by a wallpaper group $p4g$ symmetry, based on a tight-binding model for the space group $P4/mbm$ (No. 127). A symmetry-based analysis shows that four types of on-site pair potentials are allowed. Using the symmetries of the wallpaper group $p4g$ and the one-dimensional topological invariants, we clarify that for the $\mathrm{A_{1u}}$ representation, wallpaper fermions and two Majorana Kramers pairs coexist, and hybridization between them give rise to a double-twisted surface state and produces four peaks in the surface density of states. We further find that the mirror Chern number vanishes, indicating that our system realizes mirror-helicity-free surface states. This distinguishes superconducting wallpaper fermions from the other superconducting topological (crystalline) insulators, such as $\mathrm{Cu}_x\mathrm{Bi}_2\mathrm{Se}_3$ and $\mathrm{Sn}_{1-x}\mathrm{In}_x\mathrm{Te}$.

Valley degrees of freedom represent a promising resource for solid-state quantum information. This work demonstrates electrostatic control of the valley-dependent phase in tilted Dirac/Weyl semimetals. When wave packets traverse a shaped electrostatic barrier, the valley-dependent tilt induces differential spatial drift and dwell times, resulting in the accumulation of a continuously tunable relative dynamical phase. The barrier thereby functions as a valley-phase shift element. Time-dependent transport simulations employing a coupled two-valley model yield electrically tunable relative phases between equal-energy valleys, including $\pi/4$, $\pi/2$, and $\pi$, with high transmission probabilities.

Accurate modeling of polycrystalline microstructure evolution under strong crystallographic heterogeneities remains a major challenge for full-field numerical methods at the mesoscopic scale. In this work, we present a high-fidelity level-set framework for capillarity-driven grain growth in polycrystals with highly-heterogeneous, disorientation-dependent grain boundary energies. The novel framework represents a polycrystalline extension of our level-set formulation, previously developed and validated using a single triple junction benchmark case. In-depth comparisons with three established level-set models demonstrate that the proposed method yields the most energetically-consistent evolution of grain statistics, disorientation distribution function, and triple junction dihedral angles. Accuracy and robustness are maintained across the entire heterogeneity spectrum. To the best of our knowledge, this approach delivers the highest-fidelity front-capturing level-set modeling of grain growth based on Mullins' mean curvature flow theory, paving the way for state-of-the-art digital twins for annealing applications.

Hydrogen-rich ternary hydrides are promising candidates for high-Tc superconductivity at megabar pressures, yet their chemical space is vast and largely unexplored. Combining evolutionary structure searches with first-principles calculations, we comprehensively investigate the La-Zr-H ternary system in the 150-300 GPa pressure range. Zero-point energy-corrected convex hull analysis identifies multiple stable superconducting phases, including R3m-Zr2H17 at 300 GPa and P6/mmm-LaZr2H24 at 200 GPa, both of which are thermodynamically and dynamically stable and exhibit strong electron-phonon coupling. Solution of the Eliashberg equations predicts high superconducting transition temperatures of Tc = 209 K for R3m-Zr2H17 at 300 GPa and Tc = 202 K for P6/mmm-LaZr2H24 at 200 GPa. In addition to these stable phases, we identify a high-symmetry metastable compound, P6m2-LaZrH18, which lies just 0.027 eV/atom above the convex hull yet remains dynamically stable and exhibits a high predicted Tc of 206 K at 300 GPa. We find that, across all phases, the elevated Tc correlates with the high-symmetry structure with dense hydrogen cages, favorable electron counts per hydrogen, and a large hydrogen-derived density of states at the Fermi level. Finally, a random- forest machine learning model, trained on diverse hydrides superconductivity data, reproduces these structure-property trends across predicted structures, enabling to identify potential hydrides with high predicted Tc for targeted follow-up calculations and future high-pressure experiments.

In this work, we investigate the emergence of topological spin textures in a ferromagnetically coupled bilayer chiral magnet by means of Monte Carlo simulations of a classical spin model including exchange interaction, Dzyaloshinskii-Moriya interaction, magnetic anisotropy, and an external magnetic field. To characterize the topology of the system, we construct a scalar chirality map in the $(K/J,h/J)$ parameter space. Our results reveal several magnetic configurations, including labyrinth structures, skyrmion lattices, ferromagnetic states, and meron-antimeron crystal phases. In particular, we show that the transition from easy-axis to easy-plane anisotropy drives a continuous transformation from skyrmion textures to bimeron-type configurations. The bilayer geometry introduces an additional stabilization mechanism, where interlayer exchange coupling correlates the topological cores in the two layers and increases the energetic cost of defect collapse. These findings provide a systematic topological texture map for bilayer chiral magnets and highlight coupled magnetic layers as a promising platform for stabilizing bimeron-type spin textures in nanoscale spintronic systems.

Bragg coherent diffraction imaging (BCDI) fails to reliably retrieve phases in micro-crystals exhibiting strong strain inhomogeneities, which restricts its applicability. Here we show that three-dimensional Bragg ptychography (3DBP) overcomes this limitation by enabling stable inversion for large lattice distortions. Using a combination of experimental measurements and numerical tests, we compare the performance limits of the two approaches and demonstrate that 3DBP tolerates lattice distortions more than six times larger than BCDI. We also establish the sensitivity of both methods on a weakly distorted crystal, for which 3DBP yields smoother amplitude and phase fields with reduced short-length-scale artifacts. 3DBP thus provides a reliable route for imaging micro-crystals with large lattice distortions, expanding the scope of coherent X-ray Bragg microscopy to strongly deformed systems.

Millimeter-wave technologies are essential for future high-speed wireless communications. However, a fundamental challenge remains in the form of severe free-space path loss, where the power density decreases inversely with the square of the distance r (i.e., proportional to r^{-2}) as a spherical dependence. To overcome this limitation, we propose a flexible metasurface tape that is designed to guide electromagnetic energy as surface waves. Unlike conventional free-space propagation, this engineered metasurface confines the field to a subwavelength interface, thereby altering the power decay law to a circular dependence (i.e., proportional to r^{-1}). We numerically and experimentally, for the first time, demonstrate this concept using a periodic grounded-patch array fabricated on a flexible substrate and operated at approximately 100 GHz. The measurement results show that the metasurface tape significantly increases the transmitted power, yielding an average rate of improvement of approximately 40 per meter in received power relative to the free-space baseline in our measurement geometry (e.g., 29-dB increase at 2 m). This increase is realized over a broad bandwidth from 95 GHz to 105 GHz (i.e., approximately 10 %), accommodating wideband modulation schemes required for high-data-rate applications. The flexible, lightweight nature of the tape allows it to be easily installed on diverse surfaces. Our demonstration indicates that the metasurface tape is a promising platform for extending the effective range of millimeter-wave systems, thus offering a robust solution to the path-loss bottleneck in next-generation wireless networks.

We study the electronic and magnetic properties of monolayer Fe$_3$GeTe$_2$ within the DFT+DMFT approach in the paramagnetic phase. We argue that this compound is sufficiently far from the local magnetic moment limit, demonstrating non-linear temperature dependencies of the partial inverse local and uniform magnetic susceptibilities in a broad temperature range. We find that in the regime of moderate Coulomb interactions ($U=3-4$ eV), the iron atoms located above and below the Ge plane carry a substantial local magnetic moment ($\mu \gtrsim 4.5 \mu_B$), while the iron atom located within the Ge plane does not exhibit any pronounced magnetic moment. At the same time, the RKKY-type exchange interactions between these two symmetry-nonequivalent types of atoms turn out to be crucial for stabilizing long-range ferromagnetic order in Fe$_3$GeTe$_2$. The estimated spin-wave stiffness and Curie temperature are in good agreement with the experimental data, indicating that a dynamical treatment of electron correlations in Fe$_3$GeTe$_2$ is essential to properly describe its partially itinerant magnetic behavior.

Antiferromagnetic (AFM) materials are considered as promising building blocks of novel data storage devices, still, detecting and manipulating AFM domains have remained challenging. Here, we demonstrate that the two antiphase domains of the magnetoelectric antiferromagnet LiCoPO$_4$ can be distinguished by their light absorption difference. Using visible and infrared spectroscopy, we observed spontaneous non-reciprocal absorption, also termed as directional dichroism, at the crystal field excitations of Co$^{2+}$ ions coordinated by distorted oxygen octahedra. This absorption contrast is particularly pronounced near the telecommunication wavelength of 1550 nm. These findings allowed us to image the AFM domains in LiCoPO$_4$ using a simple transmission light microscopy setup. Our findings suggest that optical magnetoelectric effects offer promising routes for probing the AFM order parameter in non-centrosymmetric transition metal compounds.

We simulate nanoscale ice–glass friction from first principles and upscale it by modelling frictional heating. Nanoscale simulations alone overestimate friction and miss its velocity dependence. Frictional heating warms the contact toward the melting point, thickening the premelting film tenfold and cutting its viscosity a hundredfold; friction drops with velocity, matching experiment. Premelting forms the film without sliding or heating, but its slipperiness hinges on frictional heating, as Bowden and Hughes proposed in 1939, without melting. Snow, other materials and coatings remain open.

We study third-order transitions in the two-dimensional Ising and Potts model on regular lattices and Watts–Strogatz small-world networks. Cluster observables are used to track post-critical boundary reorganization and pre-critical cluster breakup. For the Ising model, the critical temperature $T_c$ is calibrated independently from Binder-cumulant crossings and susceptibility peaks, whereas for the Potts model on small-world networks it is identified operationally from the dominant critical peak of $\mathrm d\langle P\rangle/\mathrm dT$. The independent and dependent third-order transitions are identified from the isolated-spin peak and the post-critical structural extremum, respectively. For both lattice and small-world topologies, we find the robust ordering $T_{\mathrm{ind}}<T_c<T_{\mathrm{dep}}$. Increasing the rewiring probability shifts all three characteristic temperatures upward and enhances the visibility of the post-critical transition. The effect is especially clear in the Potts model, where perimeter-based observables are more sensitive to multistate boundary fluctuations. The systematic persistence of the characteristic temperature hierarchy across topologies and finite sizes argues against interpreting these features as incidental finite-size irregularities. Instead, our results support their interpretation as genuine third-order transitions whose structural detectability can be amplified by network topology.