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Physics Condensed Matter

cond-mat Watch Condensed Matter

Friday 31 October

Materials Science · Cross-listed from math.NA

Approximating Young Measures With Deep Neural Networks

Rayehe Karimi Mahabadi, Jianfeng Lu and Hossein Salahshoor

Parametrized measures (or Young measures) enable to reformulate non-convex variational problems as convex problems at the cost of enlarging the search space from space of functions to space of measures. To benefit from such machinery, we need powerful tools for approximating measures. We develop a deep neural network approximation of Young measures in this paper. The key idea is to write the Young measure as push-forward of Gaussian measures, and reformulate the problem of finding Young measures to finding the corresponding push-forward. We approximate the push-forward map using deep neural networks by encoding the reformulated variational problem in the loss function. After developing the framework, we demonstrate the approach in several numerical examples. We hope this framework and our illustrative computational experiments provide a pathway for approximating Young measures in their wide range of applications from modeling complex microstructure in materials to non-cooperative games.
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Strongly Correlated Electrons · Cross-listed from quant-ph

Closed-loop calculations of electronic structure on a quantum processor and a classical supercomputer at full scale

Tomonori Shirakawa, Javier Robledo-Moreno, Toshinari Itoko et al. (+18 more)

Quantum computers must operate in concert with classical computers to deliver on the promise of quantum advantage for practical problems. To achieve that, it is important to understand how quantum and classical computing can interact together, and how one can characterize the scalability and efficiency of hybrid quantum-classical workflows. So far, early experiments with quantum-centric supercomputing workflows have been limited in scale and complexity. Here, we use a Heron quantum processor deployed on premises with the entire supercomputer Fugaku to perform the largest computation of electronic structure involving quantum and classical high-performance computing. We design a closed-loop workflow between the quantum processors and 152,064 classical nodes of Fugaku, to approximate the electronic structure of chemistry models beyond the reach of exact diagonalization, with accuracy comparable to some all-classical approximation methods. Our work pushes the limits of the integration of quantum and classical high-performance computing, showcasing computational resource orchestration at the largest scale possible for current classical supercomputers.
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All authors Tomonori Shirakawa, Javier Robledo-Moreno, Toshinari Itoko, Vinay Tripathi, Kento Ueda, Yukio Kawashima, Lukas Broers, William Kirby, Himadri Pathak, Hanhee Paik, Miwako Tsuji, Yuetsu Kodama, Mitsuhisa Sato, Constantinos Evangelinos, Seetharami Seelam, Robert Walkup, Seiji Yunoki, Mario Motta, Petar Jurcevic, Hiroshi Horii, Antonio Mezzacapo

Soft Condensed Matter · Cross-listed from math.DG

How periodic surfaces bend without stretching

Hussein Nassar and Andrew Weber

Many compliant shell mechanisms are periodically corrugated or creased. Being thin, their preferred deformation modes are inextensional, i.e., isometric. Here, we report on a recent characterization of the isometric deformations of periodic surfaces. In a way reminiscent of Gauss theorem, the result builds a constraint that relates the ways in which the periodic surface stretches, effectively but isometrically, to the ways in which it bends and twists. Several examples and use cases are presented.
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Mesoscale and Nanoscale Physics

Dragging of electric current by hydrodynamic flow at charge neutrality

Dmitry Zverevich, Alex Levchenko and A. V. Andreev

We develop a theory of drag in graphene double layers near charge neutrality. We work in the regime of electron hydrodynamics and account for interlayer correlations of charge puddle disorder. The drag resistivity is expressed in terms of the viscosity, intrinsic conductivity of the electron liquid, and the correlation function of the puddle disorder. The contributions of the interlayer transfer of momentum and energy to drag have opposite signs. This leads to a nonmonotonic dependence of the drag resistivity on the carrier density. For layer-symmetric doping, the drag resistivity changes sign as a function of the carrier density. At interlayer separations shorter than the disorder correlation length, the transconductivity saturates to the disorder-induced enhancement of the intralayer conductivity. We provide quantitative estimates of the effect for Dirac electron liquids in monolayer graphene and bilayer graphene double-layer devices.
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Materials Science

Interface-mediated softening and deformation mechanics in amorphous/ amorphous nanolaminates

Vivek Devulapalli, Fedor F. Klimashin, Manuel Bärtschi et al. (+4 more)

Interfaces govern the unique mechanical response of amorphous multilayers. Here, we examine nanoindentation hardness and deformation behaviour of amorphous-amorphous Ta$_2$O$_5$/SiO$_2$ nanolaminates with bilayer thicknesses ranging from 2 nm to 334 nm. Whilst monolithic SiO$_2$ exhibits catastrophic failure through a single dominant shear band, multilayer architectures demonstrate varied deformation mechanisms. Hardness decreases with reduced bilayer thickness, from 7.7 GPa at 334 nm to 5.5 GPa at 2 nm spacing, contrasting with crystalline systems, which strengthen with decreasing spacing. Cross-sectional transmission electron microscopy reveals that fine bilayer spacings promote closely spaced vertical shear bands with bilayer compression, while coarser spacings show fewer, widely spaced shear bands with chemical intermixing. Scanning electron diffraction mapping demonstrates significant densification beneath indents. The high interface density facilitates strain accommodation that prevents catastrophic failure typical of brittle amorphous materials.
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All authors Vivek Devulapalli, Fedor F. Klimashin, Manuel Bärtschi, Stephan Waldner, Silvia Schwyn Thöny, Johann Michler, Xavier Maeder

Materials Science

Transfer learning discovery of molecular modulators for perovskite solar cells

Haoming Yan, Xinyu Chen, Yanran Wang et al. (+10 more)

The discovery of effective molecular modulators is essential for advancing perovskite solar cells (PSCs), but the research process is hindered by the vastness of chemical space and the time-consuming and expensive trial-and-error experimental screening. Concurrently, machine learning (ML) offers significant potential for accelerating materials discovery. However, applying ML to PSCs remains a major challenge due to data scarcity and limitations of traditional quantitative structure-property relationship (QSPR) models. Here, we apply a chemical informed transfer learning framework based on pre-trained deep neural networks, which achieves high accuracy in predicting the molecular modulator's effect on the power conversion efficiency (PCE) of PSCs. This framework is established through systematical benchmarking of diverse molecular representations, enabling lowcost and high-throughput virtual screening over 79,043 commercially available molecules. Furthermore, we leverage interpretability techniques to visualize the learned chemical representation and experimentally characterize the resulting modulator-perovskite interactions. The top molecular modulators identified by the framework are subsequently validated experimentally, delivering a remarkably improved champion PCE of 26.91% in PSCs.
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All authors Haoming Yan, Xinyu Chen, Yanran Wang, Zhengchao Luo, Weizheng Huang, Hongshuai Wang, Peng Chen, Yuzhi Zhang, Weijie Sun, Jinzhuo Wang, Qihuang Gong, Rui Zhu, Lichen Zhao

Materials Science

Constructing a bifunctional platform based on Mn2+-doped Mg2Y8(SiO4)6O2 phosphors for multi-parameter optical thermometry and manometry

Zhiyu Pei, Shuailing Ma, Maja Szymczak et al. (+4 more)

Series of the Mn2+-doped Mg2Y8(SiO4)6O2 phosphors were synthesized. Upon excitation at 408 nm, these phosphors exhibited intense orange emission originating from Mn2+, with concentration quenching observed beyond x = 0.07, and they also demonstrated excellent thermal stability. For optical thermometry, two independent parameters, emission band centroid ({\lambda}) and lifetime, were employed as thermal indicators, yielding sensitivities of d{\lambda}/dT = 0.053 nm K-1 and SR = 0.86% K-1, respectively. High-pressure in-situ X-ray diffraction revealed that the phosphors retained structural integrity under compression, accompanied by a progressive lattice contraction. With increasing pressure (0.13-10.89 GPa), a spectral red-shift was observed, corresponding to a pressure sensitivity of d{\lambda}/dp = 4.75 nm GPa-1. Additionally, pressure-dependent shifts in color coordinates allowed the development of a colorimetric manometric response, achieving a relative sensitivity of 3.27% GPa-1. Remarkably, the pressure-induced spectral shift of Mn2+ emission, characterized by low thermal cross-sensitivity, enabled a highly reliable ratiometric manometric strategy, with a relative sensitivity of 72% GPa-1. Notably, the system delivered the highest TIMF reported to date above 3 GPa, peaking at 1940 K GPa-1 at 7 GPa. These results position Mn2+-doped Mg2Y8(SiO4)6O2 phosphors as a highly promising bifunctional material for next-generation, multi-parameter optical sensing applications under extreme conditions.
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All authors Zhiyu Pei, Shuailing Ma, Maja Szymczak, Lukasz Marciniak, Tian Cui, Laihui Luo, Peng Du

Mesoscale and Nanoscale Physics

Visualizing interaction-driven restructuring of quantum Hall edge states

Jiachen Yu, Haotan Han, Kristina G. Wolinski et al. (+10 more)

Many topological phases host gapless boundary modes that can be dramatically modified by electronic interactions. Even for the long-studied edge modes of quantum Hall phases, forming at the boundaries of two-dimensional (2D) electron systems, the nature of such interaction-induced changes has been elusive. Despite advances made using local probes, key experimental challenges persist: the lack of direct information about the internal structure of edge states on microscopic scales, and complications from edge disorder. Here, we use scanning tunneling microscopy (STM) to image pristine electrostatically defined quantum Hall edge states in graphene with high spatial resolution and demonstrate how correlations dictate the structures of edge channels on both magnetic and atomic length scales. For integer quantum Hall states in the zeroth Landau level, we show that interactions renormalize the edge velocity, dictate the spatial profile for copropagating modes, and induce unexpected edge valley polarization that differ from those of the bulk. While some of our findings can be understood by mean-field theory, others show breakdown of this picture, highlighting the roles of edge fluctuations and inter-channel couplings. We also extend our measurements to spatially resolve the edge state of fractional quantum Hall phases and detect spectroscopic signatures of interactions in this chiral Luttinger liquid. Our study establishes STM as a promising tool for exploring edge physics of the rapidly expanding 2D topological phases, including newly realized fractional Chern insulators.
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All authors Jiachen Yu, Haotan Han, Kristina G. Wolinski, Ruihua Fan, Amir S. Mohammadi, Tianle Wang, Taige Wang, Liam Cohen, Kenji Watanabe, Takashi Taniguchi, Andrea F. Young, Michael P. Zaletel, Ali Yazdani

Statistical Mechanics

The hybrid exact scheme for the simulation of first-passage times of jump-diffusions with time-dependent thresholds

Sascha Desmettre, Devika Khurana and Amira Meddah

The first-passage time is a key concept in stochastic modeling, representing the time at which a process first reaches a specified threshold. In this work, we consider a jump-diffusion (JD) model with a time-dependent threshold, providing a more flexible framework for describing stochastic dynamics. We are interested in the Exact simulation method developed for JD processes with constant thresholds, where the Exact method for pure diffusion is applied between jump intervals. An adaptation of this method to time-dependent thresholds has recently been proposed for a more general stochastic setting. We show that this adaptation can be applied to JD models by establishing a formal correspondence between the two frameworks. A comparative analysis is then performed between the proposed approach and the constant-threshold version in terms of algorithmic structure and computational efficiency. Finally, we show the applicability of the method by predicting neuronal spike times in a JD model driven by two independent Poisson jump mechanisms.
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Statistical Mechanics · Cross-listed from quant-ph

Simulated outperforms quantum reverse annealing in mean-field models

Christopher L. Baldwin

Adiabatic reverse annealing (ARA) has been proposed as an improvement to conventional quantum annealing for solving optimization problems, in which one takes advantage of an initial guess at the solution to suppress problematic phase transitions. Here we interpret the performance of ARA through its effects on the free energy landscape, and use the intuition gained to introduce a classical analogue to ARA termed “simulated reverse annealing” (SRA). This makes it more difficult to claim that ARA provides a quantum advantage in solving a given problem, as not only must ARA succeed but the corresponding SRA must fail. As a solvable example, we analyze how both protocols behave in the infinite-range (non-disordered) $p$-spin model. Through both the thermodynamic phase diagrams and explicit dynamical behavior, we establish that the quantum algorithm has no advantage over its classical counterpart: SRA succeeds not only in every case where ARA does but even in a narrow range of parameters where ARA fails.
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Superconductivity

Chimeric states of matter: Meissner effect without superconductivity

Michael J Landry and Mingda Li

Symmetry is central to how we classify phases of matter: solids break spatial translations, superfluids break particle-number conservation, and superconductors "break" gauge symmetry. Mixed anomalies involving higher-form symmetries, however, present a generalization of spontaneous symmetry breaking that admits a wider and more versatile set of possibilities. We introduce chimeric states of matter, in which aspects of broken and unbroken phases coexist. We find that the Meissner effect – usually regarded as the defining hallmark of superconductivity – can occur in media that are resistive or even insulating when probed by electric fields. We demonstrate this by constructing an effective field theory of "symmetry chimerization" and propose that Josephson junction networks could provide a laboratory realization. These results broaden the landscape of possible phases of matter, showing that physical media can mix features of symmetry-restored and symmetry-broken states in a single substrate.
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Materials Science · Cross-listed from physics.class-ph

Mechanically concealed holes

Kanka Ghosh and Andreas M. Menzel

When a hole is introduced into an elastic material, it will usually act to reduce the overall mechanical stiffness. A general ambition is to investigate whether a stiff shell around the hole can act to maintain the overall mechanical properties. We consider this effect from a macroscopic continuum perspective down to atomistic scales. For this purpose, we focus on the basic continuum example situation of an isotropic, homogeneous, linearly elastic material loaded uniformly under compressive plane strain for low concentrations of holes. As we demonstrate, the thickness of the shell can be adjusted in a way to maintain the overall stiffness of the system. We derive a corresponding mathematical expression for the thickness of the shell that conceals the hole. Thus, one can work with given materials to mask the presence of the holes simply by adjusting the thickness of the surrounding shells, with no need to change the materials. Our predictions from linear elasticity continuum theory are extended to atomistic levels using molecular dynamics simulations of a model Lennard-Jones solid. These extensions attest the robustness of our predictions down to atomistic scales. Thus, they open a straightforward possibility to adjust the strategy of mechanical cloaking via atomistic manipulations. From both perspectives, the underlying concept is important in the context of light-weight construction.
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Statistical Mechanics

From Three-Particle Dynamics to the Structural Origin of the Arrow of Time in Classical and Quantum Mechanics

Shuhei Kobayashi

This paper presents a unified formulation of the origin of the arrow of time in classical and quantum mechanics. We begin with a mechanical analysis of a one-dimensional three-particle system, which provides a concrete example in which macroscopic irreversibility emerges despite microscopically reversible dynamics. By abstracting this mechanism, we identify coarse-graining as the essential ingredient responsible for macroscopic time asymmetry. We then formulate a general structural criterion for the thermodynamic arrow of time. We show that when microscopic time evolution forms a group while the induced macroscopic evolution forms only a semigroup, macroscopic time-reversal symmetry is necessarily broken. We prove that this semigroup structure arises if and only if the coarse-graining map from microscopic to macroscopic states is non-injective. This result holds independently of whether the underlying system is classical or quantum. In the quantum case, using density matrices, antiunitary time reversal, and CPTP coarse-graining maps, we show that macroscopic irreversibility follows inevitably from information loss, without requiring any asymmetry in the microscopic laws. Our results demonstrate that the thermodynamic arrow of time has a universal structural origin: the loss of microscopic information inherent in coarse-graining.
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Statistical Mechanics

Approximate Approach to Compute Characteristics of Inhomogeneous TASEP with Open Boundaries

Marina V. Yashina and Alexander G. Tatashev

A discrete-time totally asymmetric simple exclusion process on a lattice with open boundaries is considered. There are particles of different types. The type of a particle is characterized by the probability that a particle moves to a vacant site and the probability that a particle occupying the rightmost site departs the system. An approximate approach to compute the particle flow rate and density in sites is proposed. A version of the approach is proposed for an analogous continuous-time process. The accuracy of the approximation is estimated. The approach can be used in traffic models and models of statistical physics.
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Statistical Mechanics · Cross-listed from cs.LG

Cross-fluctuation phase transitions reveal sampling dynamics in diffusion models

Sai Niranjan Ramachandran, Manish Krishan Lal and Suvrit Sra

We analyse how the sampling dynamics of distributions evolve in score-based diffusion models using cross-fluctuations, a centered-moment statistic from statistical physics. Specifically, we show that starting from an unbiased isotropic normal distribution, samples undergo sharp, discrete transitions, eventually forming distinct events of a desired distribution while progressively revealing finer structure. As this process is reversible, these transitions also occur in reverse, where intermediate states progressively merge, tracing a path back to the initial distribution. We demonstrate that these transitions can be detected as discontinuities in $n^{\text{th}}$-order cross-fluctuations. For variance-preserving SDEs, we derive a closed-form for these cross-fluctuations that is efficiently computable for the reverse trajectory. We find that detecting these transitions directly boosts sampling efficiency, accelerates class-conditional and rare-class generation, and improves two zero-shot tasks–image classification and style transfer–without expensive grid search or retraining. We also show that this viewpoint unifies classical coupling and mixing from finite Markov chains with continuous dynamics while extending to stochastic SDEs and non Markovian samplers. Our framework therefore bridges discrete Markov chain theory, phase analysis, and modern generative modeling.
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Quantum Gases

Quantum Hall correlations in tilted extended Bose-Hubbard chains

Hrushikesh Sable, Subrata Das and Vito W. Scarola

We demonstrate characteristics of a bosonic fractional quantum Hall (FQH) state in a one-dimensional extended Bose-Hubbard model (eBHM) with a static tilt. In the large tilt limit, quenched kinetic energy leads to emergent dipole moment conservation, enabling mapping to a model generating FQH states. Using exact diagonalization, density matrix renormalization group, and an analytical transfer matrix approach, we analyze energy and entanglement properties to reveal FQH correlations. Our findings set the stage for the use of quenched kinetics in simple time-reversal invariant eBHMs to explore emergent phenomena.
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Materials Science · Cross-listed from cs.CV

Deep learning denoising unlocks quantitative insights in operando materials microscopy

Samuel Degnan-Morgenstern, Alexander E. Cohen, Rajeev Gopal et al. (+4 more)

Operando microscopy provides direct insight into the dynamic chemical and physical processes that govern functional materials, yet measurement noise limits the effective resolution and undermines quantitative analysis. Here, we present a general framework for integrating unsupervised deep learning-based denoising into quantitative microscopy workflows across modalities and length scales. Using simulated data, we demonstrate that deep denoising preserves physical fidelity, introduces minimal bias, and reduces uncertainty in model learning with partial differential equation (PDE)-constrained optimization. Applied to experiments, denoising reveals nanoscale chemical and structural heterogeneity in scanning transmission X-ray microscopy (STXM) of lithium iron phosphate (LFP), enables automated particle segmentation and phase classification in optical microscopy of graphite electrodes, and reduces noise-induced variability by nearly 80% in neutron radiography to resolve heterogeneous lithium transport. Collectively, these results establish deep denoising as a powerful, modality-agnostic enhancement that advances quantitative operando imaging and extends the reach of previously noise-limited techniques.
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All authors Samuel Degnan-Morgenstern, Alexander E. Cohen, Rajeev Gopal, Megan Gober, George J. Nelson, Peng Bai, Martin Z. Bazant

Quantum Gases · Cross-listed from quant-ph

Probing non-equilibrium physics through the two-body Bell correlator

Abhishek Muhuri, Tanoy Kanti Konar, Leela Ganesh Chandra Lakkaraju et al. (+1 more)

Identifying equilibrium criticalities and phases from the dynamics of a system, known as a dynamical quantum phase transition (DQPT), is a challenging task when relying solely on local observables. We exhibit that the experimentally accessible two-body Bell operator, originally designed to detect nonlocal correlations in quantum states, serves as an effective witness of DQPTs in a long-range (LR) XY spin chain subjected to a magnetic field, where the interaction strength decays as a power law. Following a sudden quench of the system parameters, the Bell operator between nearest-neighbor spins exhibits a distinct drop at the critical boundaries. In this study, we consider two quenching protocols, namely sudden quenches of the magnetic field strength and the interaction fall-off rate. This pronounced behavior defines a threshold, distinguishing intra-phase from inter-phase quenches, remaining valid regardless of the strength of long-range interactions, anisotropy, and system sizes. Comparative analyses further demonstrate that conventional classical and quantum correlators, including entanglement, fail to capture this transition during dynamics.
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All authors Abhishek Muhuri, Tanoy Kanti Konar, Leela Ganesh Chandra Lakkaraju, Aditi Sen De

Soft Condensed Matter

Local ion environment in polyamide membranes revealed by molecular dynamics

Nathanael S. Schwindt, Anthony P. Straub, Michael F. Toney et al. (+1 more)

In reverse osmosis (RO) and nanofiltration (NF) membranes, the polymer structure and interactions with solvent and solutes dictate the permeability and selectivity. However, these interactions have not been fully characterized within hydrated polymer membranes. In this study, we elucidate the local atomic neighborhood around ions within a RO membrane using molecular dynamics (MD). We built a MD model of a RO membrane closely following experimental synthesis and performed long time scale simulations of ions moving within the polymer. We find that the ion-oxygen nearest neighbor distance within the membrane is essentially the same as in solution, indicating that ions coordinate similarly in the confined membrane as in water. However, we do find that the average coordination number decreases in the polymer, which we attribute primarily to shifting the outer portion of the solvation shell beyond the cutoff, rather than being entirely stripped away. We find that cations bind tightly to both the carboxylate and amide oxygen atoms within the membrane. Even in ionized membranes, binding to amide oxygen atoms appears to play a substantial role in hindering ion mobility. Finally, we find that commonly used measures of ionic solvation structure such as coordination numbers do not fully capture the solvation structure, and we explore other measures such as the chemical composition of the nearest neighbors and the radial distribution function.
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All authors Nathanael S. Schwindt, Anthony P. Straub, Michael F. Toney, Michael R. Shirts

Materials Science

Evolution of Magnetoresistance in the magnetic topological semimetals NdSbxTe2-x

Santosh Karki Chhetri, Rabindra Basnet, Krishna Pandey et al. (+6 more)

Magnetic topological semimetals LnSbTe (Ln = lanthanide elements) provide a platform to study the interplay of structure, magnetism, topology, and electron correlations. Varying Sb and Te compositions in LnSbxTe2-x can effectively control the electronic, magnetic, and transport properties. Here, we report the evolution of transport properties with Sb and Te contents in NdSbxTe2-x, (0 < x < 1). Our work reveals nonmonotonic evolution in magnetoresistance with varying composition stoichiometry. Specifically, reducing Sb content x leads to strong negative magnetoresistance up to 99.9%. Such a strong magnetoresistance, which is likely attributed to the interplay between structure, magnetism, and electronic bands, establishes this material as a promising platform for investigating topological semimetal for future device applications.
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All authors Santosh Karki Chhetri, Rabindra Basnet, Krishna Pandey, Gokul Acharya, Sumaya Rahman, Md Rafique Un Nabi, Dinesh Upreti, Hugh O.H. Churchill, Jin Hu

Soft Condensed Matter

Poroelasticity in the presence of active fluids

Riccardo Cavuoto, Stefania Scala, Arsenio Cutolo et al. (+2 more)

This work presents a model for characterizing porous, deformable media embedded with magnetorheological fluids (MRFs). These active fluids exhibit tunable mechanical and rheological properties that can be controlled through the application of a magnetic field, which induces a phase transition from a liquid to a solid-like state. This transition profoundly affects both stress transmission and fluid flow within the composite, leading to a behaviour governed by a well-defined threshold that depends on the ratio between the pore size and the characteristic size of clusters of magnetic particles, and can be triggered by adjusting the magnetic field intensity. These effects were confirmed through an experimental campaign conducted on a prototype composite obtained by imbibing a selected MRF into commercial sponges. To design and optimize this new class of materials, a linear poroelastic formulation is proposed and validated through comparison with experimental results. The constitutive relationships, i.e. overall elastic constitutive tensor and permeability, of the model are updated from phenomenological observations, exploiting the experimental data obtained for both the pure fluid and the composite material. The findings demonstrate that the proposed simplified formulation is sufficiently robust to predict and optimize the behaviour of porous media containing MRFs. Such materials hold significant promise for a wide range of engineering applications, including adaptive exosuits for human tissue and joint rehabilitation, as well as innovative structural systems.
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All authors Riccardo Cavuoto, Stefania Scala, Arsenio Cutolo, Giuseppe Mensitieri, Massimiliano Fraldi

Superconductivity

Reducing the strain required for ambient-pressure superconductivity in bilayer nickelates

Yaoju Tarn, Yidi Liu, Florian Theuss et al. (+7 more)

The remarkable discovery of high temperature superconductivity in bulk bilayer nickelates under high pressure has prompted the conjecture that epitaxial compressive strain might mimic essential aspects of hydrostatic pressure. The successful realization of superconductivity in films on SrLaAlO4 (001) (SLAO) supports this correspondence, yet it remains unclear whether the rich pressure-temperature phase diagram of bilayer nickelates can be systematically mapped (and studied at ambient pressure) as a function of epitaxial strain. To this end, experimental access near the elusive edge of the superconducting phase boundary would provide invaluable insight into the nature of the superconducting state and the ground state from which it emerges. It would also offer a benchmark for theoretical models. Here we report superconducting bilayer nickelates grown on LaAlO3 (001) (LAO), where the compressive strain required for ambient-pressure superconductivity is nearly halved to -1.2%. These films exhibit a superconducting onset above 10 K and reach zero resistance at 3 K, with normal-state transport properties differing from those of films grown on SLAO. Our results offer a new opportunity to probe emergent phenomena near the superconducting phase boundary in the strain-temperature phase diagram of bilayer nickelates.
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All authors Yaoju Tarn, Yidi Liu, Florian Theuss, Jiarui Li, Bai Yang Wang, Jiayue Wang, Vivek Thampy, Zhi-Xun Shen, Yijun Yu, Harold Y. Hwang

Mesoscale and Nanoscale Physics · Cross-listed from physics.ins-det

Magnetic wideband VHF localized field probe using magnon polaritons

Gabriel Soares, Nicolò Crescini, Giovanni Carugno et al. (+1 more)

We present here an optimisation and demonstration of a wide band instrument capable of measuring localised and directionally alternated magnetic fields below pT in the very high frequency (VHF) range. We take advantage of the magnon-photon hybridization between a yttrium iron garnet (YIG) sphere and a copper resonant cavity to employ a resonant heterodyne detection scheme. The measurement is near instantaneous due to the strong coupling attained between magnons and photons.In this work measurements are reported showing a significant widening of the measurement bandwidth, obtained by tuning the YIG Larmor frequency with a bias magnetic field and adjusting the magnon-photon coupling strength. Minimum sensitivity in the sub pT regime is demonstrated in the range 150 – 225 MHz at room temperature and expected to go to fT in cryogenic temperatures. Dynamic range is estimated to be above 100 dB. The sensitivity is found to be independent on size, being ready to in-chip miniaturization. Such device can be an important building block to quantum circuits, such as baluns, transducers or signal processing units.
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All authors Gabriel Soares, Nicolò Crescini, Giovanni Carugno, Giuseppe Ruoso

Materials Science

Kinematical and dynamical contrast of dislocations in thick GaN substrates observed by synchrotron-radiation X-ray topography under six-beam diffraction conditions

Yongzhao Yao, Yoshiyuki Tsusaka and Yukari Ishikawa

Dislocations in a thick ammonothermal GaN substrate were investigated using synchrotron-radiation X-ray topography (SR-XRT) under six-beam diffraction conditions. The high brilliance of the synchrotron source enabled the observation of the super-Borrmann effect, which markedly enhanced the anomalous transmission of X-rays through the 350~$\mu$m-thick crystal. Systematic variation of the deviation angle~$\Delta\omega$ revealed a clear transition from kinematical to dynamical diffraction, consistent with theoretical predictions based on dynamical diffraction theory. By selectively exciting five equivalent two-beam diffraction conditions near the six-beam configuration, the Burgers vectors of individual threading edge dislocations (TEDs) were determined according to the $g\cdot b$ invisibility criterion. The measured dislocation image widths agreed well with calculated values derived from the extinction distance and $|g\cdot b|$ dependence, confirming that most dislocations possess Burgers vectors containing an $a$-type component of $\frac{1}{3}\langle 11\bar{2}0\rangle$ or $\frac{2}{3}\langle 11\bar{2}0\rangle$. These results demonstrate that SR-XRT under multibeam diffraction provides a powerful, nondestructive method for quantitative dislocation analysis in thick GaN crystals, offering valuable insights into defect structures critical for high-performance GaN-based electronic devices.
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Strongly Correlated Electrons

Magnetic properties of $R$Rh$_6$Ge$_4$ ($R$ = Pr, Nd, Sm, Gd-Er) single crystals

Jiawen Zhang, Yongjun Zhang, Yuxin Chen et al. (+6 more)

Single crystals of $R$Rh$_6$Ge$_4$ ($R$ = Pr, Nd, Sm, Gd - Er) were synthesized using a Bi flux and their physical properties were characterized by magnetization, resistivity, and specific heat measurements. These compounds crystallize in the noncentrosymmetric LiCo$_6$P$_4$-type structure (space group $P\bar{6}m2$), where rare-earth atoms form a triangular lattice in the $ab$-plane and chains along the $c$-axis. PrRh$_6$Ge$_4$ and ErRh$_6$Ge$_4$ do not exhibit magnetic transitions above 0.4 K. NdRh$_6$Ge$_4$ and SmRh$_6$Ge$_4$ are ferromagnets, while GdRh$_6$Ge$_4$ and DyRh$_6$Ge$_4$ show antiferromagnetic transitions, \red{whereas HoRh$_6$Ge$_4$ is a ferrimagnet}. In addition, DyRh$_6$Ge$_4$ shows multiple transitions and magnetization plateaus when a magnetic field is applied along the $c$-axis. In SmRh$_6$Ge$_4$, like the Ce counterpart, the crystalline-electric field (CEF) effect leads to an easy plane anisotropy, while in other compounds it gives rise to a pronounced uniaxial anisotropy.
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All authors Jiawen Zhang, Yongjun Zhang, Yuxin Chen, Zhaoyang Shan, Jin Zhan, Mingyi Wang, Yu Liu, Michael Smidman, Huiqiu Yuan

Materials Science

First-Principles Study of Transition Metal Doped in 2D Polyaramid for Novel Material Modelling

Ravi Trivedi, Chaithanya Purushottam Bhat, Shakti S. Ray et al. (+1 more)

We present a first–principles density functional theory (DFT) study of transition metal (TM = Ti, Cr, Mn, Fe, Co, Ni) functionalized two–dimensional polyaramid (2DPA) to explore their structural, electronic, and magnetic properties. Mechanical parameters, such as bulk modulus, shear modulus, Young's modulus, Poisson's ratio, and Pugh ratio, together with phonon dispersion, confirm the mechanical and dynamic stability of all doped systems. Electronic structure analysis shows strong binding of Co, Cr, Fe, Ni, and Ti with formation energies between –1.15 eV and –2.96 eV, while Mn binds more weakly (–0.67 eV). TM doping introduces new electronic states that reduce the band gap, with Fe-doped 2DPA exhibiting the lowest value of 0.26 eV. The systems display predominantly ferromagnetic ordering, with magnetic moments of 1.14 {\mu}B (Co), 3.57 {\mu}B (Cr), 2.26 {\mu}B (Fe), 4.19 {\mu}B (Mn), and 1.62 {\mu}B (Ti). These results demonstrate that TM–doped 2DPA possesses tunable magnetic and electronic characteristics, highlighting its potential for spintronic applications.
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All authors Ravi Trivedi, Chaithanya Purushottam Bhat, Shakti S. Ray, Debashis Bandyopadhyay

Materials Science

Learning viscoplastic constitutive behavior from experiments: II. Dynamic indentation

Andrew Akerson, Aakila Rajan, Daniel Casem et al. (+1 more)

We continue the development of a method to accurately and efficiently identify the constitutive behavior of complex materials through full-field observations that we started in Akerson, Rajan and Bhattacharya (2024). We formulate the problem of inferring constitutive relations from experiments as an indirect inverse problem that is constrained by the balance laws. Specifically, we seek to find a constitutive behavior that minimizes the difference between the experimental observation and the corresponding quantities computed with the model, while enforcing the balance laws. We formulate the forward problem as a boundary value problem corresponding to the experiment, and compute the sensitivity of the objective with respect to the model using the adjoint method. In this paper, we extend the approach to include contact and study dynamic indentation. Contact is a nonholonomic constraint, and we introduce a Lagrange multiplier and a slack variable to address it. We demonstrate the method on synthetic data before applying it to experimental observations on rolled homogeneous armor steel and a polycrystalline aluminum alloy.
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All authors Andrew Akerson, Aakila Rajan, Daniel Casem, Kaushik Bhattacharya

Materials Science

Synthesis of organic-inorganic perovskite and all-inorganic lead-free double perovskite nanocrystals by femtosecond laser pulses

Volodymyr Vasylkovskyi, Andrey Evlyukhin, Elena Schlein et al. (+5 more)

Perovskite materials are at the forefront of modern materials science due to their exceptional structural, electronic, and optical properties. The controlled fabrication of perovskite nanostructures is crucial for enhancing their performance, stability, and scalability, directly impacting their applications in next-generation devices such as solar cells, LEDs, and sensors. Here, we present a novel, ligand-free approach to synthesize perovskite nanocrystals (NCs) with average sizes up to 100 nm, using femtosecond pulsed laser ablation (PLA) in ambient air without additional liquid media. We demonstrate this method for both organic-inorganic (methylamino lead) hybrid perovskites (MAPbX3, X = Cl, Br, I) and fully inorganic lead-free double perovskites (Cs2AgBiX6, X = Cl, Br), achieving high-purity NCs without stabilizing ligands - a critical advancement over conventional chemical synthesis methods. By tailoring laser parameters, we systematically elucidate the influence of perovskite composition (halide type, organic vs. inorganic cation, single versus double perovskite structure) on the ablation process and the resulting nanocrystal properties. Transmission electron microscopy and X-ray diffraction confirm the preservation of crystallinity, with MAPbX3 forming larger (approximately 90 nm) cubic NCs and Cs2AgBiX6 forming smaller (approximately 10 nm) rounded NCs. Photoluminescence spectroscopy reveals pronounced size-dependent blue shifts (17-40 nm) due to quantum confinement, particularly for Br and I containing perovskites. This clean, scalable, and versatile PLA approach not only provides direct access to high-purity, ligand-free perovskite NCs with tunable optical properties but also represents a significant advance in the fabrication of nanostructures, enabling the exploration of new perovskite-based optoelectronic and quantum devices.
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All authors Volodymyr Vasylkovskyi, Andrey Evlyukhin, Elena Schlein, Mykola Slipchenko, Roman Kiyan, Kestutis Kurselis, Vladimir Dyakonov, Boris Chichkov

Soft Condensed Matter

Extreme breakdown of the Einstein relation in liquid water under centrifugation

Joseph F. Wild, Yihan Li, Keyue Liang et al. (+5 more)

We present evidence that the Einstein relation (ER) breaks down completely in pure water and dilute aqueous solutions under strong centrifugation fields at 40 oC. Isotopologues (e.g., H2O-18) and solutes migrate at a speed of only 5% of that predicted based on the ER. The ER is restored with the addition of solutes above a transition concentration (ct). We further discovered a new scaling law between the solute's partial molar density, the centrifugal acceleration, and ct, which can be quantitatively described by a two-phase model in analog to the Avrami model for phase transformation. The breakdown may stem from long-range dipole interactions or the hydrogen bond network in water, which are disrupted by the presence of solutes. This report shows that studying transport under centrifugation can be a new strategy to understand fundamental transport properties and complex interactions in liquids.
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All authors Joseph F. Wild, Yihan Li, Keyue Liang, Aishwarya S. Gujarathi, Heng Chen, Alex N. Halliday, Stephen E. Cox, Yuan Yang