Materials Science · Cross-listed from physics.med-ph
Crossover Frequency as a Model-Independent Viscoelastic Constant for Soft Tissue Biomechanics
Laura Ruhland, Jing Guo, Ingolf Sack et al. (+1 more)
Magnetic resonance elastography (MRE) and related elastography techniques are emerging as quantitative diagnostic tools for assessing tissue microstructure and pathology. To determine descriptive parameters of the tissues' properties, a frequency-dependent viscoelastic material model is required, which is calibrated to the measured response in a parameter identification process. However, the selection of this model and the fitting strategy is challenging, since it may influence the identified viscoelastic parameters notably. Here, we address this limitation by proposing the crossover frequency (fc, defined as the frequency at which storage and loss
moduli intersect G'(fc) = G”(fc)) as a model-independent viscoelastic constant for soft tissues. Fresh porcine specimens of the corona radiata, the putamen, the thalamus, and the liver were investigated using tabletop MRE and the frequency-dependent viscoelasticity was characterized with a fractional Kelvin-Voigt model. By validating the crossover frequency against the viscoelastic parameters, we demonstrated that the crossover frequency accurately reflects the viscoelastic behavior, independent of the material model or the fitting strategy. Across all samples, fc distinguished
brain regions and separated
brain from liver tissue by median frequencies of 85Hz (95% CI: 69-269Hz) in the corona radiata, 423Hz (95% CI: 316-575Hz) in the putamen, 426Hz (95% CI: 302-601Hz) in the thalamus and 1174Hz (95% CI: 1074-1300Hz) in the liver (p<0.001). These results suggest that crossover frequencies capture distinct viscoelastic fingerprints without requiring viscoelastic model selection. The crossover frequency may therefore serve as a practical, model-independent biomaterial constant to improve comparability of viscoelastic measurements across elastography studies.
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All authors Laura Ruhland, Jing Guo, Ingolf Sack, Kai Willner
Materials Science · Cross-listed from physics.chem-ph
Chemical Reaction Engineering and Catalysis: AI/ML Workflows and Self-Driving Laboratories
Rigoberto Advincula and Jihua Chen
Chemical reaction engineering is key to industrial might and sustainable chemistry. This will be enabled using smart, efficient catalysts or catalysis ecosystems. This is possible with advanced artificial intelligence and machine learning (AI/ML) workflows that need to be employed as agentic AI projects. The fundamentals of catalysis need to be emphasized. A strong focus on catalyst design, mechanistic studies, reaction engineering, and scale-up must use ML-driven workflows, along with high-throughput experimentation (HTE) and an autonomous, self-driving laboratory (SDL). Laboratory experience and data-driven approaches are valuable when working together to accelerate this development. Parametrize and create a virtuous circle for data-driven discovery across heterogeneous, homogeneous, and biocatalysts to enable utility in many chemical process industries as agentic AI tasks. This article builds the case for discovery science in catalysis and continuous improvement in chemical reaction engineering with this new ecosystem.
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Strongly Correlated Electrons
Generic Long-Range Order-Parameter Correlations in Metallic Quantum Magnets
T.R. Kirkpatrick and D. Belitz
It is shown that in all types of metallic magnets the coupling of the order parameter to the conduction electrons leads to an order-parameter susceptibility that is long-ranged at zero temperature. This is true for all known classes of ferromagnets, and also for antiferromagnets and
spin-density wave systems, helimagnets,
magnetic nematics, and altermagnets. The consequences for the
magnetic quantum phase transition vary between different classes of magnets. In almost all 3-d systems with a homogeneous magnetization, as well as in
magnetic nematics and in altermagnets, the long-ranged correlations generically modify the nature of the
magnetic quantum phase transition from second order to first order. The only exception are non-centrosymmetric ferromagnets with a strong
spin-orbit interaction, where the correlations change the order of the transition in 2-d systems, but not in 3-d ones. In helimagnets,
spin-wave systems, and Neel antiferromagnets their effect is even weaker and does not change the order of the transition if the ordering wave number is sufficiently large, except in flat-band systems. In systems with quenched disorder the transition generically is of second order, but the correlations modify the critical behavior. These conclusions are reached by very simple considerations that are based entirely on the single-particle excitations in the nonmagnetic phase and their modifications by a field conjugate to the order parameter, augmented by renormalization-group considerations.
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Superconductivity
Diode Effect May Assist Finding Proper Superconductivity Mechanism in Copper Oxides
Armen Gulian, Serafim Teknowijoyo and Vahan Nikoghosyan
We present measurements demonstrating that copper-
oxide high-temperature
superconductors can exhibit broken time-reversal
symmetry in the absence of external
magnetic fields. Using $Tl_{2}Ba_{2}CaCu_{2}O_{8}$ microbridges, we observe a pronounced superconducting diode effect at 100 K under strictly zero-field conditions. This nonreciprocal response remains unchanged in
magnetic fields up to $\pm 100 Oe$. Our results are consistent with recent reports of zero-field diode behavior in $Bi_{2}Sr_{2}CaCu_{2}O_{8+{\delta} }$ and together indicate that time-reversal
symmetry breaking may be an intrinsic property of the cuprate superconducting state. These findings significantly constrain theoretical models of high-temperature superconductivity that rely on time-reversal-symmetric mechanisms.
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Strongly Correlated Electrons
Spontaneous altermagnetism in multi-orbital correlated electron systems
Nitin Kaushal, Adarsh S. Patri and Marcel Franz
Altermagnets have attracted considerable
attention in recent years owing to their potential technological applications in spintronics and magnonics. Recently, a new class of spontaneous altermagnets has been theoretically predicted in a correlated two orbital model, driven by the coexistence of
antiferromagnetic spin and staggered orbital ordering, thus broadening the scope of altermagnetic phenomena to systems with strong correlations. It has been noted, however, that the required
spin and orbital order violates the well-established Goodenough-Kanamori (GK) rules, which underlie much of our understanding of magnetism in complex systems. Here we show that materials with three active orbitals may offer a more realistic route to this exotic state. Specifically, we consider a two-dimensional system with $t_{2g}^{2}$ electrons and identify a novel microscopic mechanism that allows the formation of a spontaneous altermagnetic Mott
insulator. We explain how the GK rules are circumvented and provide the stability criteria by employing unbiased mean-field and density
matrix renormalization group calculations. In addition, for the first time, we uncover the presence and microscopic origin of chirally split
magnons in these spontaneous altermagnets, with experimentally measurable
spin conductivities. Finally, we predict that the application of a small in-plane
magnetic field induces, in the presence of weak atomic
spin-orbit coupling, an as-yet unreported hybrid
chiral magnon-orbiton mode with a non-zero orbital polarization giving rise to finite longitudinal and transverse orbital conductivities under a thermal gradient.
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Materials Science
Performance of universal machine learning potentials in global optimization of inorganic crystal structures
Edan T. Marcial, Laxman Chaudhary, Olesya Gorbunova et al. (+1 more)
Rapid development of universal machine learning potentials (uMLPs) and expansion of training data sets are reshaping the state of the art in atomistic simulation, highlighting the need for concurrent systematic benchmarking of their capabilities. Global optimization is among the most demanding uMLP applications because unconstrained exploration includes probing motifs not present in reference sets. We examined twelve pretrained uMLPs in unconstrained evolutionary searches to assess whether these models can consistently predict complex nonmagnetic
crystal structure ground states under ambient pressure across diverse inorganic systems. Our findings demonstrate that the considered M3GNet, MACE-MATPES, MACE-mh-1, SevenNet, EquiformerV2, EquiformerV3, MatterSim, GRACE, eSEN, Orb-v3, PET-MAD, and PET-OAM models span a wide performance range, from near ab initio to essentially non-predictive, in their ability to resolve competing phases within low-energy basins. Additional tests on hcp-Zn, MB$_4$ (M = Cr, Mn, and Fe), and LiB$_{y}$ ($y\approx 0.9$) ground states reveal that several uMLPs capture fine energy differences arising from subtle electronic structure features.
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All authors Edan T. Marcial, Laxman Chaudhary, Olesya Gorbunova, Aleksey N. Kolmogorov
Materials Science
Strain patterning of flexomagnetism
Tamalika Samanta, Zachary T. LaDuca, An-Hsi Chen et al. (+15 more)
Flexomagnetism, the coupling of
magnetic ordering to strain gradients, provides access to novel
symmetry-broken
magnetic phases that cannot be accessed via uniform strain. However, flexomagnetism is hard to understand because it is extremely difficult to control a spatially varying strain. Here, we develop a top-down strategy to pattern transverse strain gradients using helium ion implantation through a lithographically defined mask. Using epitaxial films of the
antiferromagnetic nodal line semimetal GdAuGe, we demonstrate that transverse strain gradients $\partial \varepsilon_{zz}/\partial x$ induce near-room-temperature
ferromagnetic response, compared to the retained para or antiferromagnetism for homogeneously strained GdAuGe. We spatially correlate the
magnetic response with the regions of largest strain gradient, via
magnetic force microscopy and nanobeam x-ray diffraction, respectively, to confirm the flexomagnetic response. Our approach opens new avenues for the precise control of
magnetic phases in thin films of
quantum materials via a patterned strain gradient.
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All authors Tamalika Samanta, Zachary T. LaDuca, An-Hsi Chen, Sangsoo Kim, Ying-Ting Chan, Jiaxuan Wu, Yujia Teng, Debarghya Mallick, Matthew Brahlek, T. Zac Ward, Katherine Su, Jia-Mian Hu, Weida Wu, Turan Birol, Hanfei Yan, Michael S. Arnold, Karin M. Rabe, Jason K. Kawasaki
Materials Science
Defect-Engineered h-BN as a Platform for Single-Atom HER Catalysts: Descriptor Screening Refined by Electrochemical Stability Analysis
Ana S. Dobrota, Natalia V. Skorodumova and Igor A. Pašti
Defect engineering enables hexagonal boron nitride (h-BN) to act as a platform for stabilizing isolated metal atoms, yet systematic identification of catalytically viable motifs remains limited. Here, density functional theory is used to screen transition and coinage metals anchored at B, N, and BN vacancies in h-BN for hydrogen
evolution reaction (HER) activity. Cohesive-energy benchmarking reveals that B vacancies provide the strongest thermodynamic stabilization of single atoms, while electronic-structure analysis demonstrates vacancy-dependent modulation of conductivity and metal charge state. Hydrogen adsorption free energies identify Cu@VN and Pd@VB as near-thermoneutral candidates comparable to Pt(111). However, incorporation of electrochemical stability through Pourbaix analysis significantly refines this selection: Cu@VN is unstable at low pH and susceptible to OHads poisoning, whereas Pd@VB remains stable and catalytically accessible across a broad potential-pH range. These results show that descriptor-based HER screening can generate an expanded pool of candidates, but rigorous electrochemical filtering is essential to identify truly robust systems. The presented multi-step strategy provides a general framework for rational discovery of single-atom catalysts on defect-engineered 2D supports.
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Materials Science
Exploring the extremes: atomic basis for multi-elemental materials science under complex thermodynamic conditions
Anton Bochkarev, Yury Lysogorskiy, Aparna Subramanyam et al. (+2 more)
Modern materials science has historically been founded on combining restricted subsets of the periodic table, favoring high-purity, few-element systems. However, the demands of an emerging circular economy, together with the need to understand materials behavior under planetary and industrial extremes, increasingly require mastering Mendeleev materials - chemically and structurally complex systems that span large portions of the periodic table. In these regimes, current universal machine-learning interatomic potentials often fail, largely due to systematic gaps in traditional training
datasets that heavily emphasize low-energy, near-
equilibrium structures. We address this limitation by introducing a chemistry-agnostic, information-
entropy-maximization protocol for data generation. By decoupling structural sampling from thermodynamic bias, our approach provides a robust physical prior for atomic interactions across the entire periodic table, including regimes far from
equilibrium and under extreme conditions. Training a Graph Atomic Cluster Expansion (GRACE) model on the resulting statistically maximized
entropy (SMAX)
dataset yields markedly improved robustness across a range of stringent
benchmarks. These include large-strain phase transformations in tin, defect
evolution in tungsten-based
alloys, and catalytic reaction barrier prediction. More broadly, our approach establishes a scalable and principled methodology for navigating the vast chemical and configurational space relevant to future materials design. It enables a paradigm of discovery by simulation in which unbiased sampling protocols autonomously resolve emergent structures in multi-elemental mixtures-such as systems containing the nine most abundant elements in the Earth's crust-without reliance on a priori chemical assumptions.
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All authors Anton Bochkarev, Yury Lysogorskiy, Aparna Subramanyam, Ralf Drautz, Danny Perez
Strongly Correlated Electrons
Nonequilibrium topological response under charge dephasing
Shuangyuan Lu, Lucas Q Silveira and Yizhi You
We explore nonequilibrium topological responses of
symmetry-protected topological (SPT) states in open
quantum systems subject to decoherence. For SPT wavefunctions protected by a product
symmetry G $\times$ S , where G defects are decorated with S charge, we show that local dephasing of the S charge density generically induces spontaneous strong-to-weak
symmetry breaking (SWSSB) of G in the resulting mixed-state ensemble. We extend this mechanism to SPT phases protected by higher-form and spatially modulated
symmetries, and further to gapless SPT states, demonstrating that dephasing-induced SWSSB persists well beyond conventional gapped 0-form settings. Our results provide a qualitative, channel-defined fingerprint of SPT order that is intrinsic to open-system dynamics and goes beyond
equilibrium linear response.
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Strongly Correlated Electrons
Signatures of Green's function zeros and their topology using impurity spectroscopy
Sayan Mitra, Fang Xie, Marek Kolmer et al. (+2 more)
Topology without quasiparticles has emerged as a key framework for understanding Mott
insulators, where Green's-function zeros encode nontrivial topological structure. Yet, experimental detection of these zeros represents a challenge. Using exact diagonalization of the one-dimensional Hubbard model with an
impurity and Zeeman field, supported by exact analytic results, we show that Green's-function zeros manifest as an in-gap spectral weight in the
unitary scattering regime. In this limit, we map the
impurity problem onto a doped Mott
insulator and identify the resulting in-gap state as a "zeron" excitation which is a localized doublon (holon) for an attractive (repulsive) potential. The zeron spectral weight and its associated zero vanish above a critical Zeeman field. Our results imply that Green's function zeros have in fact already been observed in experiments, and establish
impurity and
magnetic-field tuning as practical tools for controlling their
topology.
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All authors Sayan Mitra, Fang Xie, Marek Kolmer, Qimiao Si, Chandan Setty
Soft Condensed Matter
Transport properties of monodisperse and bidisperse hard-sphere colloidal suspensions from multiparticle collision dynamics simulations
Michael P. Howard
The shear viscosities, long-time self-
diffusion coefficients, and sedimentation velocities in monodisperse and bidisperse hard-sphere colloidal suspensions are simulated for volume fractions up to 0.40 using multiparticle collision dynamics with a discrete particle model. The bidisperse suspensions have diameter ratios of 2 and 4 and equal amounts of each particle by volume. All measured properties for monodisperse suspensions are found to be in good agreement with prior literature; however, they highlight the sensitivity of the simulation method to discretization effects. The sedimentation velocities for the bidisperse suspensions are also in reasonable agreement with prior literature, including direction reversal for the smaller particles when the diameter ratio is 4. This work provides reference data for transport properties of colloidal suspensions and establishes the suitability of multiparticle collision dynamics for modeling suspensions of particles with different sizes.
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Materials Science
Band Renormalization in a Metal-Organic Framework/Au(111) Triple-Lattice Heterostructure
Xiaoqing Yuan, Shaoze Wang, Xiaoyue He et al. (+4 more)
Two-dimensional conjugated metal-organic frameworks (2D c-MOFs) hold great promise for chemiresistive sensing, electrocatalysis, and energy storage. Their interfacial interactions with metal electrodes can significantly influence electronic properties and device functionality. As a representative 2D c-MOF, Ni3(HITP)2 (HITP = 2,3,6,7,10,11-hexaiminotriphenylene) exhibits excellent performance in various electronic devices, yet the microscopic mechanism of interfacial interactions in Ni3(HITP)2/metal
heterostructures remains unclear. Here, we combine molecular beam epitaxy synthesis, scanning tunneling microscopic and spectroscopic characterization, and tight-binding analysis to investigate monolayer Ni3(HITP)2 epitaxially grown on Au(111). The resulting
heterostructure forms a commensurate kagome-hexagonal-honeycomb triple-
lattice architecture. Energy-dependent local density of states mapping resolves a ligand-derived state at 0.4 eV and dispersive bands dominated by Au surface states near the
Fermi level, both of which are reproduced by the tight-binding model. These results demonstrate that the Au(111) substrate induces charge transfer, which in turn leads to
Fermi-level pinning, while substrate-mediated hopping reconstructs the band structure. This atomic-scale study of Ni3(HITP)2/Au(111) epitaxial
heterostructures elucidates interlayer coupling mechanisms and advances the understanding of MOF/metal interfaces that are integral to electronic and energy-storage devices.
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All authors Xiaoqing Yuan, Shaoze Wang, Xiaoyue He, Zhecheng Sun, Zihao Wang, Fei Song, Lei Sun
Mesoscale and Nanoscale Physics
Resonance-Enhanced Four-Wave Mixing Imaging for Mapping Defect Regions in Vanadium-Doped WS2 Monolayers
Felipe Menescal, Frederico B. Sousa Mingzu Liu, Ana P. M. Barboza et al. (+8 more)
Defect engineering is crucial for tuning 2D transition metal dichalcogenide properties for
quantum and optoelectronic applications. While conventional photoluminescence (PL) and Raman spectroscopies are important characterization tools, their mapping in large area samples can be time-consuming and lacks direct sensitivity for comprehensive defect characterization. Here, we introduce resonance-enhanced four-wave mixing (FWM) imaging for precise imaging and characterization of vanadium-induced defect states in WS2 monolayers. Our multi-modal investigation, integrating hyperspectral PL, Raman, and supported by density functional calculations, reveals nanoscale doping inhomogeneities, their influence on excitonic and vibrational properties. We observe resonance-enhanced FWM signals correlating with vanadium-induced defect regions, evidencing their unique nonlinear optical response. This work establishes FWM as an essential platform for high-resolution, defect-sensitive imaging, advancing defect-engineered excitonic devices and enabling novel nonlinear
quantum photonics.
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All authors Felipe Menescal, Frederico B. Sousa Mingzu Liu, Ana P. M. Barboza, Igor F. Curvelo, Matheus J. S. Matos, Da Zhou, Bernardo R. A. Neves, Helio Chacham, Mauricio Terrones, Bruno R. Carvalho, Leandro M. Malard
Other Condensed Matter
Flux-induced strengthening of the magnetic couplings in a flat-band diamond chain
Biplab Pal, Maxime Thumin and Georges Bouzerar
The physics in flat bands has emerged as an essential field in condensed matter physics where a plethora of phenomena can be unveiled, such as anomalous transport properties, superconductivity dominated by
quantum geometry or exotic topological phases. Our goal here is to show that even in
magnetic systems, the presence of flat bands can give rise to unexpected features. More precisely, we address the impact of an Aharonov-Bohm (AB) flux on the exchange couplings in
magnetic diamond chains. The most remarkable result is the significant amplification of
magnetic couplings at short distances induced by the AB flux, leading to a considerable increase in the thermal conductivity of the
magnons. We have also shown that the flux-dependent decaying length of the couplings is connected to the
quantum metric of the flat bands. Our results could be of interest for the control of
magnetic properties in spintronic devices and relevant for the heat transport by
magnons at the nanoscale in
quantum technologies.
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Strongly Correlated Electrons
From QED$_3$ to Self-Dual Multicriticality in the Fradkin-Shenker Model
Thomas T. Dumitrescu, Pierluigi Niro and Ryan Thorngren
We consider the Fradkin-Shenker ${\mathbb Z}_2$ gauge-
Higgs lattice model in 2+1 dimensions, i.e. the toric code deformed by an in-plane
magnetic field. Its phase diagram contains a multicritical CFT with gapless, mutually non-local electric and
magnetic particles, exchanged by a ${\mathbb Z}_2^{\mathsf{D}}$ self-duality
symmetry. We introduce a staggered generalization of the model in which these particles carry global $U(1)_e$ and $U(1)_m$ charges, respectively, and we propose a continuum QFT description in terms of QED$_3$ with $N_f = 2$ Dirac
fermion flavors and a charge-two
Higgs field with Yukawa couplings. The conjectured phase diagram harbors a multicritical CFT with $(O(2)_e \times O(2)_m)\rtimes\mathbb{Z}_2^\mathsf{D}$
symmetry, some of which is emergent in the QFT description. We compute the scaling dimensions of some operators using a large-$N_f$ expansion and find agreement with the emergent selection rules. The staggered model admits a deformation to the original Fradkin-Shenker model, which maps to unit-charge monopole operators in
Higgs-Yukawa-QED$_3$ that break the $U(1)_e \times U(1)_m$
symmetry. We show explicitly that this deformation reproduces all features of the Fradkin-Shenker phase diagram. Finally, we propose a multicritical duality between
Higgs-Yukawa-QED$_3$ and the easy-plane $\mathbb{ CP}^1$ model (i.e. two-
flavor scalar QED$_3$ with a suitable potential), which describes
spin-1/2 anti-ferromagnets on a square
lattice. This duality implies a first-order line of Néel-VBS transitions ending in a deconfined
quantum multicritical point, described by the same $O(2)_e \times O(2)_m$ symmetric CFT that arises in the staggered Fradkin-Shenker model, which separates it from a gapped ${\mathbb Z}_2$
spin liquid phase.
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Materials Science
A high-performance cobalt-free cathode for proton-conducting solid oxide fuel cells via multi-element doping in Sr2Fe2O6
Le Zhou, Yanru Yin, Dilshod Nematov et al. (+4 more)
The development of efficient and stable intermediate-temperature solid
oxide fuel
cells (SOFCs) necessitates high-performance cathode materials that are cobalt-free, cost-effective, and compatible with
proton-conducting electrolytes. While Sr2Fe2O6 (SFO)-based ferrites offer a promising cobalt-free alternative, their electrochemical performance requires further enhancement to compete with state-of-the-art cathodes. This study proposes and validates a multi-element doping strategy as a superior approach to tailor the properties of SFO. The specific
oxide Sr2Fe1.5Mo0.125Sn0.125Sc0.125Zr0.125O6 (SFO-ZSSM) is designed, synthesized via a solid-state reaction method, and systematically evaluated as a cathode for
proton-conducting SOFCs (H-SOFCs). Its performance is benchmarked against a series of SFO cathodes modified with single dopants (Mo, Sn, Sc, Zr). Structural characterization confirms the successful formation of a phase-pure perovskite structure with homogeneous elemental distribution. Electrical conductivity relaxation (ECR) measurements reveal that SFO-ZSSM exhibits dramatically enhanced oxygen and
proton transport kinetics compared to all singly-doped counterparts, demonstrating a significant synergistic effect. Consequently, fuel
cells employing the SFO-ZSSM cathode deliver exceptional peak power densities of 1580, 1137, and 854 mW cm-2 at 700, 650, and 600 {\deg}C, respectively, significantly outperforming
cells with single-doped cathodes. Electrochemical impedance spectroscopy further corroborates its superior catalytic activity, showing the lowest polarization resistance. Moreover, the SFO-ZSSM
cell demonstrates excellent operational stability over 100 hours, attributed to its robust microstructure and Ba-free composition.
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All authors Le Zhou, Yanru Yin, Dilshod Nematov, Hailu Dai, Yuyuan Gu, Shoufu Yu, Lei Bi
Strongly Correlated Electrons
Arrested Relaxation in a Disorder-Free Coulomb Spin Liquid
Souvik Kundu, Arnab Seth, Sthitadhi Roy et al. (+2 more)
We investigate Coulomb
spin liquids in classical
spin-3/2 ice and show that the enlarged on-site
Hilbert space gives rise to a qualitatively new class of such phases. Beyond the conventional
magnetic monopoles of
spin-1/2 ice, the system hosts additional low-energy
crystal-field excitations, whose interplay with monopoles significantly modifies both
equilibrium and non-
equilibrium properties. Following a thermal quench, we find a pronounced dynamical arrest manifested in an exponentially long-lived {athermal} plateau in
spin autocorrelations. This constitutes a rare example of dynamical arrest in a short-range interacting, disorder-free system. We demonstrate that the arrested dynamics originate from novel composite excitation structures unique to
spin-3/2 ice and from kinetically constrained relaxation pathways that require activated processes. Our results establish higher-
spin ice as a fertile platform for realising unconventional Coulomb
spin liquids and dynamical arrest without quenched disorder.
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All authors Souvik Kundu, Arnab Seth, Sthitadhi Roy, Subhro Bhattacharjee, Roderich Moessner
Disordered Systems and Neural Networks · Cross-listed from math-ph
Stark localization of interacting particles
Wojciech De Roeck, Amirali Hannani, Alessio Lerose et al. (+1 more)
We consider N interacting
quantum particles on a one-dimensional
lattice, and subjected to an external linear potential. For N = 1, the corresponding
Hamiltonian is explicitly diagonalizable, with superexponentially localized eigenstates. This is called Stark localization. We prove that superexponential spectral localization persists for arbitrary N and every interaction strength.
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All authors Wojciech De Roeck, Amirali Hannani, Alessio Lerose, Nathan Vandenbosch
Materials Science
Molecular Beam Epitaxy Growth of Wafer-scale SnSe van der Waals Ultrathin Layers
Qihua Zhang, Maria Hilse, Joshua Bardsley et al. (+2 more)
Tin selenide (SnSe) is a van der Waals (vdW) layered post-transition metal monochalcogenide compound which is promising for a wide range of device applications when its thickness is reduced to a few layers. Hence, developing a mature synthesis technique to obtain wafer-scale, high-quality ultrathin SnSe layers is crucial. In this work, we present a comprehensive study on the effect of growth parameters on the material quality of ultrathin SnSe thin films grown by molecular beam epitaxy. A growth window including substrate temperature of 210-270{\deg}C and low Se/Sn flux ratio with Se valve position of 10-30 mils has been identified which results in SnSe films with root-mean-square (RMS) roughness as low as 0.6 nm and full-width-at-half-maximum (FWHM) of 0.1{\deg} in SnSe (400) x-ray diffraction (XRD) rocking curve. Finally, using a three-step growth approach, we demonstrate wafer-scale coalesced ultrathin SnSe layers with thicknesses from 20 nm down to 5 nm, with good crystallinity, structural quality, and surface morphology. This work establishes a growth condition framework for MBE-grown SnSe and presents a viable route for developing wafer-scale single-layer films, unlocking the potential of this highly promising material for advanced device integration.
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All authors Qihua Zhang, Maria Hilse, Joshua Bardsley, Morgan Applegate, Stephanie Law
Statistical Mechanics
Memory-induced active particle ratchets: Mean currents and large deviations
Venkata D. Pamulaparthy and Rosemary J. Harris
We analyse a continuous-time random walk model with
stochastic reversals of direction. There is no external potential but the reorientation mechanism generates a non-zero current from asymmetry in the forward and backward waiting-time distributions (even when they have the same mean); the system can therefore be considered as a type of active particle ratchet. We derive an explicit expression for the mean ratchet current with exponentially distributed reorientation times and also develop a general renewal-theory framework to obtain the full large deviations, using this to comment on the possibility of dynamical phase transitions.
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Disordered Systems and Neural Networks · Cross-listed from math.PR
Spin Glass Concepts in Computer Science, Statistics, and Learning
Andrea Montanari
Spin glass theory studies the structure of sublevel sets and minima (or near-minima) of certain classes of random functions in high dimension. Near-minima of random functions also play an important role in high-dimensional statistics and statistical learning, where minimizing the empirical risk (which is a random function of the model parameters) is the method of choice for learning a statistical model from noisy data. Finally, near-minima of random functions are obviously central to average-case analysis of optimization
algorithms. Computer science, statistics, and machine learning naturally lead to questions that are traditionally not addressed within physics and mathematical physics. I will try to explain how ideas from
spin glass theory have seeded recent developments in these fields. (This article was written on the occasion of the 2024 Abel Prize to Michel Talagrand.)
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Statistical Mechanics · Cross-listed from physics.bio-ph
Discrete turn strategies emerge in information-limited navigation
Jose M. Betancourt, Matthew P. Leighton, Thierry Emonet et al. (+2 more)
Navigation up a smooth sensory gradient is one of the simplest behavioural tasks, and some organisms solve it by making continuous adjustments to their course. Bacteria instead employ a variety of discrete strategies, including run and tumble motion, direction reversals, and turns by specific angles. Here we ask what drives the choice of these strategies, framing the problem as maximising up-gradient speed with a given amount of sensory information per unit time. We find that, without directional information on which way to turn, behavioural strategies that take discrete actions perform better than gradual steering. As the amount of information is increased, we see a series of transitions between optimal strategies, including a shift from direction reversals to fully re-orienting tumbles. Among more complex re-orientation strategies, we show that discrete turn angles are best, and observe transitions in the number of angles employed by the optimal strategy. More broadly, such emergent simplicity in behaviour is a tractable example of a widespread phenomenon in which biology chooses a discrete solution, despite the underlying physics being continuous.
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All authors Jose M. Betancourt, Matthew P. Leighton, Thierry Emonet, Benjamin B. Machta, Michael C. Abbott