Materials Science · Cross-listed from physics.optics
Strong light-matter interactions in hybrid polaritonic systems
Ben Johns, Andrea Schirato, Federico Toffoletti et al. (+12 more)
Strong light-matter coupling gives rise to polaritons - hybrid excitations whose mixed photonic and matter character enables control over optical, electronic and chemical properties. This Feature Article surveys the main architectures supporting polariton formation, including photonic microcavities, plasmonic nanostructures, open cavities and metasurfaces, and outlines how inorganic
semiconductors, organic aggregates and hybrid systems access strong and ultrastrong coupling. Key phenomena such as coherent dynamics, vibronic interactions, dark-state reservoirs and polariton-mediated energy and electron transport are discussed, together with the experimental and theoretical tools used to study them. We highlight examples where strong coupling modifies charge transport, energy flow and chemical reactivity, and we summarize emerging regimes, including intermediate and dark-strong coupling, that broaden the landscape of hybrid light-matter physics.
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All authors Ben Johns, Andrea Schirato, Federico Toffoletti, Tommaso Giovannini, Mirko Vanzan, Margherita Marsili, Giovanni Parolin, Giulia Dall'Osto, Ajay Kumar Poonia, Chiara Cappelli, Francesca Baletto, Stefano Corni, Elisabetta Collini, Margherita Maiuri, Nicolò Maccaferri
Statistical Mechanics · Cross-listed from quant-ph
Cavity-mediated localization and collective electron correlation phases
Dominik Sidler, Francesco Greco, Michael Ruggenthaler et al. (+1 more)
Collective strong coupling of molecular ensembles to optical cavities opens a route to modifying matter through genuinely collective electronic correlations. Yet even in the absence of a cavity, Coulomb correlations are notoriously difficult to describe, and cavity coupling adds transverse correlation channels extending over the entire molecular ensemble. Here we show that this seemingly intractable problem admits a controlled description by
spin glass theory, i.e., by the analytically solvable spherical Sherrington-Kirkpatrick model. Our results predict two collective correlation phases, a paracorrelated phase and a
spin-glass correlation phase, beyond the conventional uncorrelated molecular regime. These phases reveal an
entropy-driven localization-delocalization mechanism that transfers molecular electronic states into collectively degenerate cavity-dressed states. Analytic calculation suggest that this collective correlated state can either remain insulating or even turn metallic if the entropic occupations favor a fractional filling. Our work reveals cavity-mediated electron correlations as a microscopic mechanism for emergent phases in strongly coupled molecular ensembles.
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All authors Dominik Sidler, Francesco Greco, Michael Ruggenthaler, Angel Rubio
Soft Condensed Matter
Dimple-Encoded Reprogrammable Origami
Qun Zhang, Weicheng Huang, Amir Hajiyavand et al. (+4 more)
Programmable folding of elastic sheets typically relies on predefined flexible creases or active materials-enabled hinges, which lack intrinsic bistability and limit reprogrammability within a single structure. Here, we present a dimple-encoded origami platform that converts bistable dimple snapping into spatially addressable hinges with prescribed folding angles in a continuous sheet. This interaction-enabled mechanism enables the design of distributed hinge networks through the arrangement and selective inversion of dimples. We establish folding-angle design charts that can be directly used to select local dimple arrangements for target fold angle, forming a practical hinge library without altering the underlying unit geometry. Using this approach, a single dimpled sheet can be reprogrammed to realize multiple distinct configurations, such as triangle, square, and pentagon shapes. We further extend the method to flat-to-3D morphing of polyhedral origami and validate the results through experiments and finite element simulations. As demonstrations, we realize self-supporting cubic shells with enhanced impact resistance and partially deployable cube configurations that remain stable upon opening, highlighting their potential for protective enclosures and deployable architectural structures. The proposed strategy provides a fabrication-friendly route to reprogrammable shape-morphing and adaptive mechanical systems.
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All authors Qun Zhang, Weicheng Huang, Amir Hajiyavand, Hyunyoung Kim, Claire Dancer, Karl Dearn, Mingchao Liu
Soft Condensed Matter
Colloidal layer deposition with a controllable number of layers and compositional order
Akshaya Kumar Jena, Aashima Aashima, Pritam Kumar Jana et al. (+1 more)
We design a system with a binary suspension of colloids and a surface that triggers the self-assembly of crystallites with a finite thickness. The proposed design allows controlling the number of layers forming the aggregate and constrains the two types of particles to lie on different planes. These functionalities are achieved by decorating the colloids and the surface with multiple DNA oligomers featuring specific interactions. Similarly to what was proposed in previous studies, the surface triggers a chain of reactions between DNA oligomers, leading to localized self-assembly. System parameters control the thickness of the aggregates. In this work, compositional order is achieved by engineering the reaction kinetics between DNA oligomers in a way that limits interactions between colloids of the same type. We validate our design using theory and reaction-
diffusion simulation
algorithms, which capture the multibody nature of the interactions. This work demonstrates how engineering the reaction kinetics provides a new tool for controlling the morphology of aggregates assembled by DNA.
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All authors Akshaya Kumar Jena, Aashima Aashima, Pritam Kumar Jana, Bortolo Matteo Mognetti
Materials Science
Deterministic Realization of Complex Local Strain Fields and Bandgap Profiles in Two-Dimensional Materials
Lottie L. Murray, Eric Herrmann, Igor Evangelista et al. (+5 more)
Emerging classical and
quantum device concepts demand precise spatial control over the optoelectronic properties of two-dimensional (2D) materials, but deterministic engineering via local multiaxial strain distributions remains challenging. Using Ga$_2$Se$_2$, we demonstrate a material-agnostic platform in which nanostructure geometry deterministically prescribes in-plane strain profiles in suspended van der Waals membranes. We first use hyperspectral photoluminescence mapping and experimentally-constrained finite element analysis to quantify the experimental biaxial and uniaxial strain gauge factors that relate strain to the change in bandgap. We next show that a two-component analytical model can predict, with less than 12% error, spatially-resolved bandgap shifts arising from multiaxial strain distributions in complex geometries, including the interactions between adjacent nanostructures. Finally, we demonstrate that this approach can be extended to other materials. The results demonstrate that nanostructure design provides a quantitative, deterministic framework for the realization of designed strain and bandgap distributions in 2D materials.
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All authors Lottie L. Murray, Eric Herrmann, Igor Evangelista, Sai Rahul Sitaram, Ke Ma, Anderson Janotti, Xi Wang, Matthew F. Doty
Materials Science
Revealing the kinetics of interfacial surfactant phase transitions through multiscale simulations and in-situ plasmonic sensing
Esmée Berger, Narjes Khosravian, Ferry Anggoro Ardy Nugroho et al. (+3 more)
Surfactant self-assembly at solid-
liquid interfaces governs interfacial stability, transport, and reactivity across many technologies, yet resolving interfacial surfactant phases and their transition kinetics in situ remains challenging. Here, we establish an atomistically grounded plasmonic framework that quantitatively maps interfacial surfactant phases and phase transitions onto optical signatures. Distinct morphologies differ in packing and hydration, modifying the effective permittivity within the optical near field and producing surfactant phase-specific plasmonic extinction peak shifts. Using cetyltrimethylammonium bromide on silica as a prototypical surfactant-surface system, we combine atomistic simulations, electronic-structure calculations, and continuum electrodynamics to translate molecular morphologies into predicted spectral shifts for literature-reported surface phases. We experimentally confirm the predicted ordering and magnitude of steady-state peak shifts during stepwise concentration changes, and extract transition kinetics from exponential relaxations of the time-resolved peak shift. A key mechanistic signature is reversal of the spectral shift direction upon transition from an impermeable
bilayer to a water-accessible, channel-containing phase, consistent with hydration-driven reduction of the local effective permittivity. Because the approach relies on dielectric contrast in the plasmonic near field and works through a dielectric overlayer, it provides a broadly applicable route for real-time identification of interfacial surfactant phases and their kinetics in aqueous conditions.
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All authors Esmée Berger, Narjes Khosravian, Ferry Anggoro Ardy Nugroho, Joakim Löfgren, Christoph Langhammer, Paul Erhart
Strongly Correlated Electrons
Collinear ferromagnetism with reduced moment length in kagome magnet Nd3Ru4Al12
Yuki Ishihara, Ryota Nakano, Rinsuke Yamada et al. (+14 more)
We determine the
magnetic ground state of the kagome
lattice magnet Nd3Ru4Al12 by single-
crystal neutron diffraction, supported by experiments with polarized
neutrons. We identify this material as a collinear ferromagnet ("hex-FM") with uniform moment length mc = 2.1 {\mu}B/Nd and ordering vector Q = 0, in contrast to a previous, seminal report that proposed unequal moment lengths on two Nd sites, here called the "ortho-FM" state. Our analysis of the flipping ratio in polarized
neutron scattering is consistent with the hex-FM state. The results provide a microscopic basis for understanding the large fluctuation-induced
Hall and Nernst responses near TC = 41 K, as previously reported for Nd3Ru4Al12.
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All authors Yuki Ishihara, Ryota Nakano, Rinsuke Yamada, Takuya Nomoto, Priya R. Baral, Moritz M. Hirschmann, Kamini Gautam, Kamil K. Kolincio, Akiko Kikkawa, Seno Aji, Hiraku Saitoh, Masaaki Matsuda, Yasujiro Taguchi, Taka-hisa Arima, Yoshinori Tokura, Taro Nakajima, Max Hirschberger
Statistical Mechanics
Microscopic theory of soft run-and-tumble particles
Rosalba Garcia-Millan, Ziluo Zhang, Luca Cocconi et al. (+4 more)
Soft, repulsive run-and-tumble particles display emergent effective interactions as they appear to stick to each other in spite of the absence of attractive forces. This effective attraction emerges at strong enough repulsion and large self-propulsion. Complementing a companion paper that characterises effective attraction between two soft run-and-tumble particles [Garcia-Millan et al., Effective attraction by repulsion (2026)], here we provide a thorough derivation of our microscopic theory, which is an exact representation of the particle dynamics. We report the systematic calculation of the effective interaction vertices iteratively, in a perturbation expansion about the interaction couplings, by adding, order by order, loop corrections. We use the effective interaction vertices to calculate the two-point correlation function, fully characterising the stationary state. Other observables, such as the structure factor, overlap probability and
entropy production rate are calculated as well.
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All authors Rosalba Garcia-Millan, Ziluo Zhang, Luca Cocconi, Marius Bothe, Letian Chen, Zigan Zhen, Gunnar Pruessner
Statistical Mechanics
Effective attraction by repulsion
Rosalba Garcia-Millan, Luca Cocconi, Ziluo Zhang et al. (+4 more)
Repulsive self-propelled particles tend to cluster, leading to Motility-Induced Phase Separation (MIPS). By analogy with
equilibrium phase separation, the onset of MIPS has been associated with a transition to effective attraction between particles. Using an exact microscopic theory, we quantify the emergence of effective attraction in a minimal model: two soft run-and-tumble particles in a periodic domain. We show that, as repulsion increases, the leading-order behaviour is that of effective repulsion, while effective attraction emerges as a higher-order contribution to the renormalisation of the pair potential.
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All authors Rosalba Garcia-Millan, Luca Cocconi, Ziluo Zhang, Marius Bothe, Letian Chen, Zigan Zhen, Gunnar Pruessner
Disordered Systems and Neural Networks · Cross-listed from cs.LG
Sequential Learning and Catastrophic Forgetting in Differentiable Resistor Networks
Maniru Ibrahim
Differentiable physical networks provide a simple setting in which learning can be studied through the interaction between trainable parameters and physical
equilibrium constraints. We investigate sequential learning in differentiable resistor networks governed by Kirchhoff's laws. Although individual input–output mappings can be learned by gradient-based adjustment of edge conductances, sequential training on conflicting tasks produces catastrophic forgetting. We show that forgetting is controlled by task conflict and by the degree of adaptation to the new task. Uniform anchoring and normalised gradient-weighted anchoring reduce forgetting only by increasing the final loss on the new task, giving a clear forgetting–adaptation trade-off. We also show that forgetting is associated with localised conductance changes on high-current edges, giving a physical interpretation as reconfiguration of dominant transport pathways. Broader random-task ensembles show that the strongest forgetting occurs when the second task reverses the output ordering imposed by the first task. Finally, comparisons across Erdős–Rényi, small-world, scale-free, and random-
geometric graph ensembles show that
topology changes the forgetting–adaptation balance. These results position differentiable resistor networks as compact, physically interpretable testbeds for studying continual learning in tunable matter.
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Quantum Gases
Emergent Kinetic Constraints and Subspace Fragmentation in Rydberg Arrays
Wen-Jie Geng, Zhenming Zhang and Wei Yi
In a strongly interacting Rydberg atom array, the dynamics are often constrained to the decoupled
Hilbert subspaces, representing an intriguing paradigm for nonergodicity. By considering a variable detuning of the global Rydberg coupling, we show that, not only is the existence of these
Hilbert subspaces dependent on the interplay of detuning and interaction, but they are also strongly fragmented, with the fragment dimensions exhibiting various scaling behaviors with increasing system size. The resulting constrained dynamics of the system are thus governed by the dimension and connectivity of these fragments. We then adopt an auxiliary
fermion description to reveal the underlying emergent kinetic constraints for the subspace fragmentation and fragment-confined dynamics. Our results provide a systematic understanding of
Hilbert-space fragmentation in Rydberg arrays, and shed light on engineering nonergodic many-body dynamics beyond the PXP model.
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Disordered Systems and Neural Networks
Reservoir computing by thin film embedded with magnetic impurities
Shuto Kamakura, Tomi Ohtsuki and Jun-ichiro Ohe
The reservoir computing based on the thin film embedded with
magnetic impurities in the presence of the long-range (the dipole-dipole) interaction is numerically investigated. We simulated the magnetization dynamics by taking into account the dipole-dipole interaction and performed the handwritten-digit recognition task. Although the training data is prepared by taking spatial average in the sample, the high classification accuracy is achieved. Our result demonstrates that the long range interaction effectively encodes the complex spatial input pattern into the time domain, even when only a spatially averaged output is accessible. The proposed system paves the way for easily realizable
magnetic reservoir computing.
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Superconductivity
Impurity-Scattering Assisted Umklapp Scattering as the Origin of Low-Temperature Resistivity in the Normal-State of Cuprate Superconductors
Xingyu Ma, Minghuan Zeng, Huaiming Guo et al. (+1 more)
The transport experiments reveal that the low-temperature resistivity in the normal-state of cuprate
superconductors is quadratic in temperature (T-quadratic) in the underdoped pseudogap phase, while it is linear in temperature (T-linear) in the overdoped strange-metal phase, however, the full understanding of these different behaviours is still a challenging issue. Here starting from the microscopic electronic structure of cuprate
superconductors, the low-temperature resistivity in the normal-state is investigated from the underdoped pseudogap phase to the overdoped strange-metal phase. It is shown that the mechanism requires both the
impurity scattering and the umklapp scattering: the
impurity scattering is needed to restrict the modification of the distribution function to at around the antinodal region,while the
impurity-scattering assisted umklapp scattering from a
spin excitation is at the heart of the behaviour in the low-temperature resistivity, where the doping dependence of the temperature scale exists, and presents a similar behavior of the antinodal
spin pseudogap crossover temperature. In the low-temperature region above the temperature scale in the overdoped strange-metal phase, the resistivity is T-linear, however, in the low-temperature region below the temperature scale in the underdoped pseudogap phase, the opening of the
spin pseudogap lowers the
spin excitation density of states at around the antinodal region, which reduces the strength of the electron umklapp scattering from a
spin excitation associated with the antinode, and thus leads to a T-quadratic behaviour of the resistivity.
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All authors Xingyu Ma, Minghuan Zeng, Huaiming Guo, Shiping Feng
Strongly Correlated Electrons
Multi-probe detection of domain nucleation across the metal-insulator transition in VO$_2$
Shubhankar Paul, Giordano Mattoni, Amitava Ghosh et al. (+7 more)
Electronic and structural degrees of freedom are often intimately coupled in strongly correlated systems, which result in intriguing macroscopic and microscopic phenomena. Using the well-studied material VO$_2$ as a prototype, here we explore the domain distribution across the metal-
insulator transition (MIT). We use macroscopic as well as microscopic techniques, such as first-order reversal curve (FORC) and infrared imaging, to probe the domain distributions across the MIT. This study compares MIT in thin films of VO$_2$ with different grain sizes grown by pulsed
laser deposition and dc sputtering. We explore the relation between the nature of the FORC distribution and the corresponding thermal hysteresis due to interactions between the supercooled metallic domains and surrounding insulating
matrix. Our multi-probe study with quantitative analysis provides a correlation between the growth, domain interaction, and domain nucleation process in MIT.
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All authors Shubhankar Paul, Giordano Mattoni, Amitava Ghosh, Pooja Kesarwani, Dipak Sahu, Monika Ahlawat, Ashok P, Amit Verma, Vishal Govind Rao, Chanchal Sow
Materials Science
SR-CGCNN: Shared Recurrent Convolution in Crystal Graph Neural Networks for Materials Property Prediction
Satadeep Bhattacharjee
Crystal graph neural networks predict materials properties by propagating information through local atomic environments. In conventional
crystal graph convolutional neural networks (CGCNNs), this propagation depth is increased by stacking independently parameterized convolutional layers. This coupling between message-passing depth and parameter count raises a simple question: can repeated application of the same learned local update recover most of the benefit of a deeper CGCNN? We address this question by introducing a shared-recurrent CGCNN (SR-CGCNN), in which the main
crystal-graph convolutional weights are tied across recurrent message-passing steps. The graph construction, pooling operation, and prediction head are kept unchanged, allowing a controlled comparison with standard CGCNN baselines. On Materials Project-derived formation-energy and band-gap
datasets, a three-step SR-CGCNN approaches the accuracy of a standard three-layer CGCNN while using only $34.5\%$ of its trainable convolutional parameters. The formation-energy test mean absolute error changes from $0.0945$ to $0.0986~\mathrm{eV\,atom^{-1}}$, while the band-gap error changes from $0.4346$ to $0.4503~\mathrm{eV}$. These results indicate that repeated shared message passing can provide a parameter-efficient approximation to stacked CGCNN depth, offering a compact recurrent interpretation of
crystal graph convolution.
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Disordered Systems and Neural Networks · Cross-listed from cs.LG
A Theory of Saddle Escape in Deep Nonlinear Networks
Divit Rawal and Michael R. DeWeese
In deep networks with small initialization, training can exhibit long plateaus separated by sharp feature-acquisition transitions. Whereas shallow nonlinear networks and deep linear networks are well studied, extending these analyses to deep nonlinear networks remains challenging. We derive exact scalar and
matrix identities for the imbalance of layer weight norms, holding for any smooth activation and any differentiable loss, and use the resulting approximate balance law to control the full finite-width gradient flow through its first escape. This gives a scaling law in the escape time: with a prefix of $r$ layers initialized at the bottleneck scale $\varepsilon$, the escape time is $\Theta(\Gamma^{-1})$ for $r=1$, $\Theta(\Gamma^{-1}\log(1/\varepsilon))$ for $r=2$, and $\Theta(\Gamma^{-1}\varepsilon^{-(r-2)})$ for $r\geq3$, where $\Gamma=\|\mathbb{E}[yx]\|$. We further show that a multimode teacher leaves the saddle once rather than in stages: with scalar output, all mode overlaps grow through a common amplitude, with relative weights fixed in advance. We find close agreement between our theory and experiment.
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Materials Science
Inverse Materials Design via Joint Generation of Crystal Structures and Local Electronic Descriptors
Ibuki Okuda, Izumi Takahara and Teruyasu Mizoguchi
Inverse design of inorganic
crystals, in which structures are generated to satisfy a target property while preserving diversity and physical plausibility, remains more demanding than ab initio generation, as property conditioning can degrade the structural quality that current generative models otherwise achieve. We propose a
diffusion framework that jointly denoises
crystal-structure variables and site-resolved local electronic descriptors through a shared score network. As representative descriptors, we adopt Bader charge and atomic density of states (atomic DOS). Under both band-gap and formation energy conditioned generation, the joint models achieved higher success rates than the structure-only baseline in most target conditions, while simultaneously increasing the fraction of generated structures that satisfy uniqueness, novelty, thermodynamic stability, and physical validity (VSUN criteria). A dummy-variable control confirms that these gains originate from the electronic content of the descriptors rather than from auxiliary site-wise variables. The generated Bader charges agree with DFT references with an MAE of 5.5e-2 e on stable structures, and the generated atomic DOS captures the coarse spectral profile of the DFT reference around the modal accuracy range, although finer details and accuracy vary with elemental species. These results establish local electronic descriptors as effective generative variables that serve two complementary roles: broadening the explored materials space through increased structural diversity, and mitigating the trade-off between property targeting and structural quality by guiding the structural trajectory toward electronically plausible configurations during joint denoising.
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Materials Science
Composition-Driven Tunable Optical and Electrical Properties in Van der Waals Ferroelectric NbOI2-xClx Alloys
Gaolei Zhao, Juhe Liu, Jinkai Huo et al. (+10 more)
Layered niobium
oxide dihalides NbOX2 (X = I, Cl), as a new family of Van der Waals (vdW) ferroelectrics, have attracted extensive
attention, while achieving non-volatile modulation of their optical and electrical properties remains challenging, thereby limiting their integration into next-generation nanoelectronics and optoelectronics. Here, we report the controlled fabrication of highly crystalline NbOI2-xClx vdW
alloys with composition-driven tunable optical and electrical properties via a chemical vapor transport method. Comprehensive experimental characterization combined with first-principles calculation shows that the
crystal lattices,
phonon modes, and band structures of NbOI2-xClx can be well tailored, which are distributed between NbOI2 and NbOCl2. Both the amplitude and polarization of second harmonic generation optical signal in NbOI2-xClx exhibit pronounced compositional dependence, offering optical evidence for tunable in-plane ferroelectric characteristic. Moreover, field-effect transistors based on NbOI2-xClx display robust n-type semiconducting behavior, with threshold voltage and carrier mobility precisely modulated through adjustment of I/Cl molar ratio. Furthermore, 2D NbOI2-xClx photodetectors across all compositions exhibit exceptional gate-tunable current on/off ratio and strong polarization-sensitive photo-response. This study thus provides a new vdW ferroelectric material platform with tunable optical and electrical properties, paving the path for its implementation in modern nanophotonics and nanoelectronics.
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All authors Gaolei Zhao, Juhe Liu, Jinkai Huo, Tian Han, Yunhao Tong, Hu Wang, Konstantin Kozadaev, Andrei Zheltkovich, Changsen Sun, Alexei Tolstik, Andrey Novitsky, Lujun Pan, Dawei Li
Strongly Correlated Electrons
Interplay of Valley, Orbital, Spin, and Layer Degrees of Freedom in Ta$_2$CS$_2$ MXene
Kunal Dutta, Anupam Mondal, Sayantika Bhowal et al. (+2 more)
We show that the MXene Ta$_2$CS$_2$ provides an excellent platform for hosting multiple coupled degrees of freedom, viz., valley,
spin, orbital, and layer. The interplay among these degrees of freedom gives rise to a range of intriguing properties in reciprocal space, including valley-orbital and orbital-layer coupling. In the presence of
spin-orbit interaction, these couplings lead to valley-dependent and layer-dependent
spin splitting of the electronic bands. We further show that the intrinsic electric polarization in Ta$_2$CS$_2$ introduces an additional tuning parameter, enabling control over these coupled degrees of freedom and resulting in switchable valley-dependent orbital moments and Zeeman-like
spin splitting. We demonstrate that these nontrivial orbital and
spin textures manifest in the orbital and
spin Hall effects, respectively. Our results establish noncentrosymmetric MXenes as a promising platform for exploring the interplay among multiple degrees of freedom, their tunability, and the resulting orbital and
spin transport phenomena in these two-dimensional materials, thereby paving the way for next-generation
spin-orbitronic devices.
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All authors Kunal Dutta, Anupam Mondal, Sayantika Bhowal, Subhradip Ghosh, Indra Dasgupta
Soft Condensed Matter
Loop expansion in polymer field theory: application to phase separation
Kiyoharu Kawana and Kyosuke Adachi
Liquid-
liquid phase separation underlies phenomena ranging from
protein condensate formation to the phase coexistence of synthetic
polymers. Although the random phase approximation (RPA) is widely used to predict such phase behavior, its quantitative accuracy for binodals of
polymer solutions, particularly outside the high-density regime, remains incompletely characterized. Here, we develop a field-theoretic loop expansion in homopolymer systems by identifying the inverse
polymer density $\rho^{-1}$ as the Planck constant $\hbar$ in
quantum field theory. We calculate the leading-order and next-to-leading-order corrections to the RPA free energy, denoted as RPA+ and RPA++, respectively. Testing the binodal predicted by the RPA+ against molecular dynamics simulations of bead-spring chains with Gaussian pair interactions, we find that the RPA+ qualitatively improves the dilute-phase coexistence density over the RPA, while the critical point error remains comparable to that of the RPA. Our results establish the loop expansion as a systematic route for refining the RPA-based binodal predictions for
polymer phase separation.
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Mesoscale and Nanoscale Physics
Vector Magnonics: Electrical Injection and Control of Spin Flow in Altermagnets
Yanmeng Lei, Rui-Chun Xiao, Weiwei Lin et al. (+1 more)
Altermagnets host chirally split
magnons that promise unique functionalities for information processing. However, their distinctive transport signatures, crucial for experimental identification and manipulation, remain elusive. Here, we predict that a
spin accumulation electrically injects a “vector" or multidirectional
magnon spin current into an altermagnet, comprising both longitudinal and sizable transverse components. Notably, this transverse current exhibits a sign reversal away from the source and can be switched on or off by reorienting the Néel vector. While such a transverse current is found to be not forbidden even in conventional antiferromagnets, we demonstrate through
quantum-kinetic calculations that in altermagnets, the transverse response is enhanced by two orders of magnitude due to broken parity-time
symmetry. This
giant enhancement provides a decisive transport fingerprint for detecting
magnon spin splitting and Néel-vector orientation, offering a clear criterion to experimentally distinguish altermagnets from conventional antiferromagnets.
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All authors Yanmeng Lei, Rui-Chun Xiao, Weiwei Lin, Tao Yu
Mesoscale and Nanoscale Physics
Phase-shift instanton approach to tunneling duality in Read–Rezayi state
Ryoi Ohashi, Hiroki Isobe, Ryota Nakai et al. (+1 more)
We study the duality between quasi-particle and electron tunneling in point-contact geometries of fractional
quantum Hall states. To treat non-Abelian edge operators, we introduce a "phase-shift instanton" that incorporates phase factors from primary fields into the instanton gas framework. Using this method, we reformulate the Moore–Read duality and obtain an explicit dual description for the $k=3$ Read-Rezayi state. Our results clarify how quasi-particle tunneling produces characteristic phase shifts in instantons and how these shifts map strong quasi-particle tunneling to weak electron tunneling. Based on this dual description, we analytically evaluate the non-linear differential conductance in the strong-coupling regime. We reveal that, due to the physical requirement that the tunneling particle across the
vacuum gap must be a true
fermion, the transport behavior universally converges to a $G \propto V^4$ scaling for both the Moore–Read and Read–Rezayi states. This universal transport signature highlights a fundamental topological constraint underlying non-Abelian fractional
quantum Hall edges.
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All authors Ryoi Ohashi, Hiroki Isobe, Ryota Nakai, Kentaro Nomura
Soft Condensed Matter · Cross-listed from physics.flu-dyn
Effects of surface viscosities on the motion of a droplet enclosing a translating particle
Ali Gürbüz, Hervé Nganguia, Guangpu Zhu et al. (+3 more)
We investigate the influence of interfacial rheology on the motion of a compound particle consisting of a viscous droplet enclosing a translating rigid particle in the Stokes flow regime. The droplet interface is modeled using the Boussinesq-Scriven constitutive law, incorporating both surface shear and dilatational viscosities. An exact analytical solution is derived for the concentric configuration, and the analysis is extended to eccentric geometries using a spectral boundary integral method, enabling a systematic examination of confinement, viscosity contrast, and interfacial properties. For concentric configurations, we show that the induced droplet velocity is independent of surface shear viscosity, while surface dilatational viscosity can either enhance or suppress the droplet motion depending on the interplay between confinement and viscosity ratio. This behavior is rationalized in terms of competing effects between reduced interfacial mobility and increased driving force required to maintain the prescribed particle speed. In contrast, when the particle is eccentrically positioned within the droplet, a dependence on surface shear viscosity emerges, leading to a consistent enhancement of droplet motion that becomes more pronounced with increasing eccentricity. The analytical and numerical results are in excellent agreement and reveal how interfacial rheology, confinement, and
symmetry breaking jointly govern the dynamics of compound particle systems. These findings provide mechanistic insight and establish a quantitative
benchmark for future studies of active compound particles with complex interfaces.
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All authors Ali Gürbüz, Hervé Nganguia, Guangpu Zhu, Lailai Zhu, Y. N. Young, On Shun Pak
Materials Science
Grain boundary segregation of light elements and their effects on cohesion in ferritic steels
Han Lin Mai, Xiang-Yuan Cui, Tilmann Hickel et al. (+2 more)
Light elements play an important role in influencing the macroscale properties of engineering
alloys through grain boundary (GB) segregation phenomena. However, the scarcity and scattered nature of ab initio
datasets for light elements in steels makes reproduction and extraction of general trends from the literature difficult. Here, we present a comprehensive ab initio evaluation of the segregation energies and cohesive effects for H, He, B, C, N, O, P, S, extensively sampling both substitutional and interstitial sites in six model coincident site
lattice (CSL) ferritic iron GBs using density functional theory (DFT). Cohesive effects are evaluated in both a
quantum-chemistry bond-order and rigid Rice-Wang interfacial cohesive strength framework. Our calculations indicate that, compared at the same concentration, B and C enhance GB cohesion, N, P, H are mildly detrimental, and He, O, S as powerful decohesive
agents/embrittlers. Sampling both interstitial and substitutional starting positions is necessary to accurately capture segregation spectra. Commonly utilised sampling criteria such as site volumes prove insufficient for identifying deepest GB binding sites. Solutes placed in either kind of site can induce large relaxations to the same final configuration, resulting in site classification ambiguity. The nearest neighbour distance of a solute to its neighbours after relaxation is shown to be a controlling factor for the lower threshold of segregation energies at sites. The freely available DFT
dataset and analysis repositories are expected to advance understanding of GB segregation behaviours of light elements in steels and serve as a resource for developing machine learning interatomic potentials.
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All authors Han Lin Mai, Xiang-Yuan Cui, Tilmann Hickel, Simon P. Ringer, Jörg Neugebauer