Mesoscale and Nanoscale Physics
Enabling the bulk photovoltaic effect in centrosymmetric materials through an external electric field
Guilherme J. Inacio, Juan José Esteve-Paredes, Maurício F. C. Martins Quintela et al. (+2 more)
We develop a practical approach to electrically tuning the nonlinear photoresponse of two-dimensional
semiconductors by explicitly incorporating a static out-of-plane electric field into the electronic ground state prior to optical excitation, as a gate bias. The method is implemented by dressing a Wannier-interpolated
Hamiltonian with the field through its position
matrix elements, which allows the gate bias to modify orbital hybridization and band dispersion beyond perturbative treatments. Within the independent-particle approximation, the resulting second-order (shift) conductivity is evaluated for both centrosymmetric and non-centrosymmetric layered systems. Applied to MoS$_2$, the approach captures the emergence of a finite shift current in centrosymmetric
bilayers and the tunability of intrinsic responses in polar structures. The shift conductivity rises linearly at small fields and saturates at higher intensities, reflecting the competition between the growing shift vector and the weakening interband coupling as resonant transitions move away from high-
symmetry valleys. A Taylor expansion of the field-dressed conductivity connects this behavior to the third-order optical response, revealing a unified picture of field-induced nonlinearities. These results establish field dressing of Wannier
Hamiltonians as a practical route to model and predict nonlinear photocurrents in layered materials.
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All authors Guilherme J. Inacio, Juan José Esteve-Paredes, Maurício F. C. Martins Quintela, Wendel S. Paz, Juan José Palacios
Quantum Gases
Dynamics of interacting bosons in a two-leg ring ladder with artificial magnetic flux and ac-driven modulations
L. Q. Lai
We investigate the nonequilibrium dynamics of interacting
bosons in a two-leg ring ladder pierced by an artificial
magnetic flux, where the particles are initially localized in the central sites of both rings, and the ac-driven local energy shifts are applied to the remaining
lattice sites. Within the mean-field approximation, we demonstrate the emergence of nonlinear self-trapping for strong interparticle interactions, and characterize the distinct excitation regimes in the absence of the inter-ring tunneling. The artificial
magnetic flux typically introduces Peierls phase factors, which induces complex-valued hopping amplitudes and leads to directed net particle currents along the chains. By further incorporating the finite inter-ring coupling and biased intra-ring hopping, we reveal that the tuning of the drive frequency and Peierls phase allows the precise control over both the intensity and direction of particle currents, which facilitates the transition between
chiral and antichiral dynamics. These findings offer insights into the coherent manipulation of matter-wave transports in closed-loop
lattice configurations and the exploration of nonequilibrium synthetic
quantum systems in related fields.
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Strongly Correlated Electrons
Antiferromagnetism and Kekulé valence bond order in the honeycomb optical Su-Schrieffer-Heeger-Hubbard model
Sohan Malkaruge Costa, Benjamin Cohen-Stead and Steven Johnston
The precise role of e-ph coupling in
graphene and related materials on a honeycomb
lattice is not yet fully understood, despite extensive research on these systems. Here, we perform sign-problem-free determinant
quantum Monte Carlo (DQMC) simulations of the optical Su-Schrieffer-Heeger (oSSH)-Hubbard model on the honeycomb
lattice, focusing on the parameters relevant to
graphene. Performing finite-size scaling analyzes, we obtain the model's ground state phase diagram, which includes the semi-metal (SM), Kekulé Valence Bond Solid (KVBS), and anti-
ferromagnetic (AFM) phases, as well as indications of a small KVBS/AFM coexistence region. We find that a weak to moderate Hubbard repulsion, tuned toward the SM-AFM critical value in the pure honeycomb Hubbard model, enhances KVBS correlations and can even stabilize the KVBS phase. Estimating the effective parameters for
graphene places it in the SM region of the phase diagram, but near the SM-KVBS phase boundary. Notably, we predict that increasing either the on-site Hubbard repulsion or the e-ph coupling strength drives
graphene toward the KVBS phase rather than the AFM phase, highlighting a synergistic effect that can be exploited to further control the remarkable properties of
graphene and related materials.
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Statistical Mechanics
Dynamics of a tracer trapped in a correlated medium in the presence of a wall
Marcin Piotr Pruszczyk and Andrea Gambassi
We describe the random motion of a particle immersed in a thermally fluctuating medium and harmonically trapped at a certain distance from a wall. The medium, modeled by a Gaussian field with a tunable correlation length $\xi$, is linearly coupled to the particle and evolves according to dissipative relaxational dynamics. Dirichlet boundary conditions imposed on the field at the wall give rise to a repulsive fluctuation-induced force acting on the particle, causing a shift in its average position and a renormalization of the strength of the harmonic trap. We describe the effective overdamped dynamics of the particle, which features a nonlinear
memory term depending on the wall-particle separation. We show that the two-time correlation function of the particle position features a
memory-induced term that depends on the distance of the particle from the wall. At the critical point, this term decays algebraically upon increasing time and it displays a crossover from the behavior observed in the bulk to that corresponding to having the particle at the wall.
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Mesoscale and Nanoscale Physics
Size optimization for observeing Majorana fermions
Guo-Jian Qiao, Zhi-Lei Zhang, Xin Yue et al. (+1 more)
Majorana
fermions (zero modes) are predicted to emerge in nanowire-
superconductor heterostructures. This theoretical prediction typically relies on an oversimplified model, where both the nanowire and the
superconductor are idealized as one-dimensional systems. In reality,
heterostructures have finite sizes that deviate from this idealization-and as a result, smoking-gun evidence confirming the existence of these zero modes remains elusive. Here, we investigate the finite-size effects of both the nanowire and the
superconductor, and optimize their sizes to ensure that only one Majorana
fermion exists at each end of the
heterostructure. It is discovered that the optimal transverse sizes of the nanowire are less than 100nm in width and approximately 1nm in thickness. For the
superconductor layer, its optimal thickness (a key aspect of its size) must exceed its coherence length. We also present the optimal sizes of the two types of materials used in the experiment in a quantitative manner. Notably, the identified optimal thickness of the
superconductor (Al films, $\sim$1000nm)–a critical size parameter–is two orders of magnitude larger than the thickness of Al films currently utilized in experimental devices (e.g., InSb-Al and InAs-Al
heterostructures). Our findings could explain why Majorana
fermions have not been observed in current experiments, and offer guidance for the size selection of
heterostructures to implement Majorana
fermions in future studies.
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All authors Guo-Jian Qiao, Zhi-Lei Zhang, Xin Yue, C. P. Sun
Materials Science
Lattice-Distortion-Mediated Proton Pairing and Trapping in Solid State Oxides
Hang Ma, Jiajun Linghu, Nannan Han et al. (+4 more)
Experiments have evidenced
proton pairing in Y-doped BaZrO3. However, the nature of
proton pairing and its impact on conduction remain insufficiently understood theoretically. Here, through quantitative computational analysis of
proton-
proton interactions in Y-doped BaZrO3, we identify
lattice-distortion-mediated elastic interaction as the key factor determining whether two
protons form a stable pair or exhibit net repulsion. When a
proton resides at an inward-bending distortion site induced by another
proton, the resulting net repulsive interaction leads to an unstable configuration. In contrast, the
proton tends to be trapped at a nearby outward-bending site that favors the formation of a stable
proton pair. Moreover, the site where the two
protons form the lowest-energy configuration also corresponds to a
proton trapping site. By calculating the long-range
diffusion pathways accessible to
protons under different local environments in both single- and two-
proton cases, we find that the range of rate-limiting barriers is 0.24-0.45 eV for two-
proton conduction and 0.19-0.39 eV for single-
proton conduction. The higher and more experimentally consistent barriers in the two-
proton pathways indicate that the
proton trapping effect induced by pairing hinders
proton conduction. Our study elucidates the multi-
proton diffusion mechanism, providing a theoretical foundation for the experimental design of electrolytes with enhanced
proton conductivity.
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All authors Hang Ma, Jiajun Linghu, Nannan Han, Ying Liang, Yiyang Sun, Tianxing Ma, Zhi-Peng Li
Materials Science
Controlled nucleation in methylamine-treated perovskite films by artificial seeding and phase-field simulations
Emilia R. Schütz, Martin Majewski, Olivier J.J. Ronsin et al. (+2 more)
Large perovskite
crystals with reduced defect density enable superior charge transport and stability. Therefore, controlling their nucleation and growth is key to advancing high-performance optoelectronic devices based on perovskite
semiconductors. Millimeter-scale perovskite
crystals can be synthesized as a continuous film through methylamine treatment, with nucleation sites directed by pre-patterned seeds. Nonetheless, certain configurations may lead to unwanted parasitic nucleation. To predict and mitigate this effect, we employ phase-field simulations alongside an analytical model. Their predictive capability is demonstrated across three distinct material-substrate systems, enabling precise control over nucleation and subsequent
crystal growth. Notably, the only material-specific input required is the nucleation density (i.e., the number of
crystals nucleated per unit area on an unpatterned substrate). This generality makes the models broadly applicable to diverse material systems for achieving controlled two-dimensional crystallization for improved optoelectronic device performance.
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All authors Emilia R. Schütz, Martin Majewski, Olivier J.J. Ronsin, Jens Harting, Lukas Schmidt-Mende
Materials Science
Revealing Fast Ionic Conduction in Solid Electrolytes through Machine Learning Accelerated Raman Calculations
Manuel Grumet, Takeru Miyagawa, Olivier Pittet et al. (+4 more)
Fast ionic conduction is a defining property of solid electrolytes for all-solid-state batteries. Previous studies have suggested that
liquid-like cation motion associated with fast ionic transport can disrupt crystalline
symmetry, thereby lifting Raman selection rules. Here, we exploit the resulting low-frequency, diffusive Raman scattering as a spectral signature of fast ionic conduction and develop a machine learning-accelerated computational pipeline to identify promising solid electrolytes based on this feature. By overcoming the steep computational barriers to calculating Raman spectra of strongly disordered materials at finite temperatures, we achieve near-ab initio accuracy and demonstrate the predictive power of our approach for sodium-ion conductors, revealing clear Raman signatures of
liquid-like ion conduction. This work highlights how machine learning can bridge atomistic simulations and experimental observables, enabling data-efficient discovery of fast-ion conductors.
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All authors Manuel Grumet, Takeru Miyagawa, Olivier Pittet, Paolo Pegolo, Karin S. Thalmann, Waldemar Kaiser, David A. Egger
Mesoscale and Nanoscale Physics
Torsion-induced Dzyaloshinskii-Moriya interaction in helical magnets
M.A. Kuznetsov and A.A. Fraerman
It has been shown that in magnets possessing an inversion center in the absence of deformations, a torsion-induced Dzyaloshinsky-Moriya interaction (tiDMI) can arise. A microscopic mechanism for this interaction is described, involving the transfer of angular momentum to the
lattice upon electron reflection from the magnet's boundary. An estimate of the tiDMI constant is provided. It is demonstrated that tiDMI can lift the
chiral degeneracy in helimagnets, and a way for experimentally observing this effect is proposed.
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Statistical Mechanics
Kibble-Zurek Meets Tricriticality: Breakdown of Adiabatic-Impulse and New Scaling Forms
Chengshu Li
The Kibble-Zurek effect is studied around a tricritical point, where the adiabatic-impulse scenario breaks down. Several new scaling forms are also proposed.
Soft Condensed Matter · Cross-listed from physics.optics
White light interferometry analysis for measuring thin film thickness down to few nanometers
Victor Ziapkoff, François Boulogne, Anniina Salonen et al. (+1 more)
We present a practical white-light interferometric method, supported by an open-source Python library optifik for automated spectrum-to-thickness deduction, enabling foam film measurements down to a few nanometers. We describe three typical spectral scenarii encountered in this method: spectra exhibiting numerous interference fringes, spectra with a moderate number of peaks, and spectra with only a few identifiable features, providing illustrative examples for each case. We also discuss the main limitations of the technique, including spectral range constraints, the necessity of knowing the refractive index, and the influence of spectral resolution and signal quality. Finally, we demonstrate the application of the method in a time-resolved study of a TTAB (tetradecyltrimethylammonium bromide) foam film undergoing elongation and thinning. This method can be adapted to measure any thin non-opaque layer.
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All authors Victor Ziapkoff, François Boulogne, Anniina Salonen, Emmanuelle Rio
Soft Condensed Matter
The 2/3 Rule of Glass Physics Implies Universalities in Crystal Melting
Peter Lunkenheimer, Konrad Samwer and Alois Loidl
Since more than 100 years, melting is thought to be governed by the Lindemann criterion. It assumes that a
crystal melts when, upon heating, the growing atomic vibration amplitudes become sufficiently large to destabilize its crystalline
lattice. However, it is unclear why the viscosities eta or the related relaxation times tau of the resulting
liquids, measured directly at the melting point Tm, differ by up to nine decades, depending on the material. Based on the empirical rule that the ratio of the glass-transition temperature and Tm is about 2/3, here we show that this strong variation is due to differences in the
liquid's fragilities, a property associated with pronounced non-Arrhenius behavior and often ascribed to cooperative motions. We propose that, without cooperativity, all
crystals would melt into
liquids with a universal viscosity value and relaxation time. Hence, the real melting point is only partly determined by the Lindemann criterion and strongly enhanced by the cooperativity of the resulting
liquid. Our findings are corroborated by the determination of the idealized, fragility-free melting temperatures, and of the corresponding eta and tau values for various example materials.
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Materials Science
Large longitudinal and anomalous transverse Magneto-thermoelectric effect in kagome antiferromagnet FeGe
Jiajun Ma, Rong Chen, Yazhou Li et al. (+14 more)
Topological Kagome magnets, characterized by nontrivial electronic band structures featuring flat band, Dirac cone and van Hove singularities, provide a new avenue for the realization of thermoelectric devices. Unlike the conventional longitudinal Seebeck effect, transverse thermoelectric (TE) effects like the Nernst effect have attracted growing interest due to their unique transverse geometry and potential advantages. Here, we report the observation of a significant transverse thermoelectric conductivity alpha A_zx of 15 A K-1m-1 at low temperatures, together with a pronounced anomalous Nernst effect in the Kagome antiferromagnet FeGe, which exhibits a charge density wave inside the
antiferromagnetic (AFM) state. This value is the highest record among known AFM materials. Furthermore, the thermopower at 14 T increases by 102-104% around the canted-AFM (CAFM) transition temperature, Tcant, comparable to that of the well-known AFM thermoelectric materials. These effects are attributed to large Berry
curvature arising from the non-collinear
spin texture in FeGe, highlighting its potential for enhancing thermoelectric performance and its candidacy for magneto-TE applications in Kagome
antiferromagnetic materials.
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All authors Jiajun Ma, Rong Chen, Yazhou Li, Chenfei Shi, Yantao Cao, YuWei Zhang, Jiaxing Liao, Yunfei Han, Guangxi Wen, Jialu Wang, Hanjie Guo, Jianhui Dai, Chenguang Fu, Jin-Ke Bao, Yan Sun, Zhu-An Xu, Yuke Li
Soft Condensed Matter
Spatiotemporal Control of Charge +1 Topological Defects in Polar Active Matter
Birte C. Geerds, Abhinav Singh, Mathieu Dedenon et al. (+4 more)
Topological defects are a conspicuous feature of active
liquid crystals that have been associated with important morphogenetic transitions in organismal development. Robust development thus requires a tight control of the motion and placement of topological defects. In this manuscript, we study a mechanism to control +1 topological defects in an active polar fluid confined to a disk. If activity is localized in an annulus within the disk, the defect moves on a circular trajectory around the center of the disk. Using an ansatz for the polar field, we determine the dependence of the angular speed and the circle radius on the boundary orientation of the polar field and the active annulus. Using a proportional integral controller, we guide the defect along complex trajectories by changing the active annulus size and the boundary orientation.
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All authors Birte C. Geerds, Abhinav Singh, Mathieu Dedenon, Daniel J. G. Pearce, Frank Jülicher, Ivo F. Sbalzarini, Karsten Kruse
Strongly Correlated Electrons
Helical Quasiperiodic Chains with Engineered Dissipation: Liouvillian Rapidity Diagnostics of Transport and Localization
Mohammad Pouranvari
We study relaxation spectra of a quadratic spinless–
fermion helical chain with an Aubry–Andre–type quasiperiodic potential and a single N–th neighbor (helical) hopping. Dissipation and pumping are introduced via local linear Lindblad jump operators and treated exactly using the third–quantization / Majorana covariance formalism. Focusing on periodic boundary conditions (to avoid edge artefacts) we compute the Liouvillian rapidities and their smallest nonzero real part (the rapidity gap) for several spatial dissipation patterns: uniform (all), single–site (one–site) and two–site (two–site) placement, plus pairwise gain/loss on helical partner sites. We show that uniform dissipation yields large, weakly lambda–dependent gaps, while sparse local dissipation produces gaps that shrink rapidly as the quasiperiodic potential lambda induces localization. Increasing t_N enhances relaxation by improving mode overlap with dissipative channels. Finite–size scaling, rapidity level statistics (Poisson vs Wigner–Dyson), and spatial profiles of slow modes provide a consistent picture linking Liouvillian spectral structure to transport and localization. Our results highlight Liouvillian rapidities as compact, experimentally relevant diagnostics of relaxation and sensitivity in engineered open
quantum lattices.
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Superconductivity
Stabilization of Tetragonal Phase and Aluminum-Doping Effect in a Bilayer Nickelate
Jia-Yi Lu, Yi-Qiang Lin, Kai-Xin Ye et al. (+7 more)
Recent studies suggest that the tetragonal phase of the Ruddlesden-Popper (RP)
bilayer nickelate, La$_3$Ni$_2$O$_7$ or La$_2$PrNi$_2$O$_7$, which is stabilized under high pressures, is responsible for high-temperature superconductivity (HTSC). In this context, realization of the tetragonal phase at ambient pressure could be a rational step to achieve the goal of ambient-pressure HTSC in the nickelate system. By employing the concept of Goldschmidt tolerance factor, we succeed in stabilizing the tetragonal phase by aluminum doping together with post annealing under moderately high oxygen pressure. X-ray and
neutron diffractions verify the tetragonal $I4/mmm$ structure for the post-annealed samples La$_3$Ni$_{2-x}$Al$_x$O$_{7-\delta}$ (0.3 $\leq x \leq$ 0.5). The Al-doped samples, including the tetragonal ones, show semiconducting properties, carry localized
magnetic moments, and exhibit
spin-glass-like behaviors at low temperatures, all of which can be explained in terms of charge carrier localization. Furthermore, high-pressure resistance measurements on post-annealed samples reveal that even a low Al doping ($x$ = 0.05) suppresses superconductivity almost completely. This work gives information about the effect of nonmagnetic
impurity on
metallicity as well as superconductivity in
bilayer nickelates, which would contribute to understanding the superconducting mechanism in RP nickelates.
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All authors Jia-Yi Lu, Yi-Qiang Lin, Kai-Xin Ye, Xin-Yu Zhao, Jia-Xin Li, Ya-Nan Zhang, Hao Li, Bai-Jiang Lv, Hui-Qiu Yuan, Guang-Han Cao
Disordered Systems and Neural Networks · Cross-listed from cs.SD
Acoustic neural networks: Identifying design principles and exploring physical feasibility
Ivan Kalthoff, Marcel Rey and Raphael Wittkowski
Wave-guide-based physical systems provide a promising route toward energy-efficient analog computing beyond traditional electronics. Within this landscape, acoustic neural networks represent a promising approach for achieving low-power computation in environments where electronics are inefficient or limited, yet their systematic design has remained largely unexplored. Here we introduce a framework for designing and simulating acoustic neural networks, which perform computation through the propagation of sound waves. Using a digital-twin approach, we train conventional neural network architectures under physically motivated constraints including non-negative signals and weights, the absence of bias terms, and nonlinearities compatible with intensity-based, non-negative acoustic signals. Our work provides a general framework for acoustic neural networks that connects learnable network components directly to physically measurable acoustic properties, enabling the systematic design of realizable acoustic computing systems. We demonstrate that constrained recurrent and hierarchical architectures can perform accurate
speech classification, and we propose the SincHSRNN, a hybrid model that combines learnable acoustic bandpass filters with hierarchical temporal processing. The SincHSRNN achieves up to 95% accuracy on the AudioMNIST
dataset while remaining compatible with passive acoustic components. Beyond computational performance, the learned parameters correspond to measurable material and
geometric properties such as attenuation and transmission. Our results establish general design principles for physically realizable acoustic neural networks and outline a pathway toward low-power, wave-based neural computing.
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Mesoscale and Nanoscale Physics
Unveiling Micrometer-Range Spin-Wave Transport in Artificial Spin Ice
Syamlal Sankaran Kunnath, Mateusz Zelent, Pawel Gruszecki et al. (+1 more)
Artificial
spin ice (ASI) systems exhibit fascinating phenomena, such as frustration and the formation of
magnetic monopole states, and Dirac strings. However, exploring the wave phenomena in these systems is elusive due to the weak dipolar coupling that governs their interactions. In this study, we demonstrate coherent
spin-wave propagation in an hybrid ASI system, which is based on a multilayered
ferromagnetic thin film with perpendicular
magnetic anisotropy and in-plane magnetized nanoelements embedded within it. We show that this system enables
spin-wave transmission over a one-micrometer distance via exchange-mediated coupling between subsystems and evanescent
spin-wave tunneling through the out-of-plane magnetized parts. This system overcomes the limitations of purely dipolar interactions in standard ASIs while preserving their fundamental properties. Thus, it provides a platform for studying
spin-wave phenomena in frustrated ASI systems and paves the way for exploiting them in analog signal processing with
spin waves.
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All authors Syamlal Sankaran Kunnath, Mateusz Zelent, Pawel Gruszecki, Maciej Krawczyk
Materials Science
Discovery and recovery of crystalline materials with property-conditioned transformers
Cyprien Bone, Matthew Walker, Bradley A. A. Martin et al. (+6 more)
Generative models have recently shown great promise for accelerating the design and discovery of new functional materials. Conditional generation enhances this capacity by allowing inverse design, where specific desired properties can be requested during the generation process. However, conditioning of
transformer-based approaches, in particular, is constrained by discrete tokenisation schemes and the risk of catastrophic forgetting during fine-tuning. This work introduces CrystaLLM-{\pi} (property injection), a conditional autoregressive framework that integrates continuous property representations directly into the
transformer's
attention mechanism. Two architectures, Property-Key-Value (PKV) Prefix
attention and PKV Residual
attention, are presented. These methods bypass inefficient sequence-level tokenisation and preserve foundational knowledge from unsupervised pre-training on Crystallographic Information Files (CIFs) as textual input. We establish the efficacy of these mechanisms through systematic robustness studies and evaluate the framework's versatility across two distinct tasks. First, for structure recovery, the model processes high-dimensional, heterogeneous X-ray diffraction patterns, achieving structural accuracy competitive with specialised models and demonstrating applications to experimental structure recovery and polymorph differentiation. Second, for materials discovery, the model is fine-tuned on a specialised photovoltaic
dataset to generate novel, stable candidates validated by Density Functional Theory (DFT). It implicitly learns to target optimal band gap regions for high photovoltaic efficiency, demonstrating a capability to map complex structure-property relationships. CrystaLLM-{\pi} provides a unified, flexible, and computationally efficient framework for inverse materials design.
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All authors Cyprien Bone, Matthew Walker, Bradley A. A. Martin, Kuangdai Leng, Luis M. Antunes, Ricardo Grau-Crespo, Amil Aligayev, Javier Dominguez, Keith T. Butler
Materials Science
Active Learning Driven Materials Discovery for Low Thermal Conductivity Rare-Earth Pyrochlore for Thermal Barrier Coatings
Amiya Chowdhury, Acacio Rincon Romero, Grazziela Figueredo et al. (+1 more)
High-
Entropy/multicomponent rare-earth
oxides (HECs and MCCs) show promise as alternative materials for thermal barrier coatings (TBC) with the ability to tailor properties based on the combination of rare-earth elements present. By enabling the substitution of scarce or supply-risk rare-earths with more readily available alternatives while maintaining comparable material performance, HECs and MCCs offer a valuable path towards alternative TBC material design. However, navigating this search space of compositionally complex materials is both time and resource intensive. In this study, an active learning (AL) framework was employed to identify HEC/MCC materials with a pyrochlore structure, with acceptable thermal conductivity (TC) for TBC applications. The AL framework was applied through a
Bayesian optimisation (BO) strategy, coupled with a random forest surrogate model. TC was selected as the optimisation criterion as that is the most basic requirement of TBC materials. Over two iterations of the AL cycle, four compositions were generated and synthesized in the lab for experimental evaluation. The first iteration yielded two single-phase pyrochlores, $(La_{0.29}Nd_{0.36}Gd_{0.36})_2Zr_2O_7$ and $(La_{0.333}Nd_{0.26}Gd_{0.15}Ho_{0.15}Yb_{0.111})_2Zr_2O_7$, with measured thermal conductivities of 2.03 and 1.90 $W/mK$, respectively. The surrogate model predicted a TC of 2.009 $W/mK$ for both compositions, demonstrating it's accuracy for completely new compositions. The second iteration compositions showed dual-phase when synthesized, highlighting the need to take into account phase formation in the AL framework.
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All authors Amiya Chowdhury, Acacio Rincon Romero, Grazziela Figueredo, Tanvir Hussain
Statistical Mechanics · Cross-listed from quant-ph
Floquet thermalization by power-law induced permutation symmetry breaking
Manju C and Uma Divakaran
Permutation
symmetry plays a central role in the understanding of collective
quantum dynamics. By introducing power law couplings that algebraically decay with the distance between the
spins $r$ as $1/r^{\alpha}$, we break this
symmetry with a non-zero $\alpha$. This allows us to probe the emergence of new dynamical behaviors, including thermalization in an otherwise permutation symmetric
Hamiltonian with all-to-all
spin interactions along $x$ direction subjected to periodic kicks in transverse direction. As we increase $\alpha$, the system interpolates from an infinite range
spin system at $\alpha=0$ exhibiting permutation
symmetry, to a short range integrable model as $\alpha \rightarrow \infty$ where this permutation
symmetry is absent. We focus on this change in the behavior of the system as $\alpha$ is tuned, using dynamical quantities like total angular momentum and von Neumann
entropy. Starting from the chaotic limit of the permutation symmetric
Hamiltonian at $\alpha=0$, for the finite system sizes considered, we find that for small $\alpha$, the steady state values of these quantities remain close to the permutation symmetric subspace values corresponding to $\alpha=0$. At intermediate $\alpha$ values, these show signatures of thermalization exhibiting values corresponding to that of random states in full
Hilbert space. On the other hand, the large $\alpha$ limit approaches the values corresponding to integrable kicked Ising model. In addition, we also study the dependence of thermalization on the driving period $\tau$, with results indicating the onset of thermalization for smaller values of $\alpha$ when $\tau$ is large, thereby extending the thermalizing window in the intermediate range of $\alpha$. We further confirm these results using effective dimension and spectral statistics.
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Materials Science
Coupled Structural and Electronic Requirements in Alpha-FASnI3 Imposed by the Sn(II) Lone Pair
Mridhula Venkatanarayanan, Vladislav Slama, Madhubanti Mukherjee et al. (+3 more)
Alpha-Formamidinium-tin-iodide (alpha-FASnI3) is a leading candidate for lead-free photovoltaic applications, adopting a nearly cubic structure at room temperature, but its stability remains limited by oxidation-driven degradation. Reliable first-principles modelling of the photovoltaic alpha-phase is further complicated by inconsistent structural models and levels of theory in the literature. Here, we identify the structural and electronic requirements needed for a physically sound description of alpha-FASnI3, whose behaviour is governed by a pseudo-Jahn-Teller (PJT) instability arising from the stereochemically active Sn(II) lone pair. Using 0 K relaxations, cross-code hybrid-functional
benchmarks, and finite-temperature ab initio molecular dynamics, we show that a 4x4x4 supercell with randomly oriented FA+ cations is the smallest model that removes macroscopic dipoles, preserves cubic
symmetry, recovers local octahedral tilts, and captures the characteristic PJT-driven Sn off-centering. Accurate band edges and a reliable band gap require a PBE0-level hybrid functional with
spin-orbit coupling to treat Sn relativistic effects, together with nonlocal dispersion (rVV10) to capture the enhanced Sn-I covalency. Finite-temperature simulations reveal that Sn off-centering remains local, <111>-oriented, and robust against thermal fluctuations, and that reproducing the experimental 300 K band gap requires a 6x6x6 supercell. These results define the essential ingredients for reliable modelling of alpha-FASnI3 and provide a rigorous foundation for studying lone-pair-driven physics in tin halide perovskites.
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All authors Mridhula Venkatanarayanan, Vladislav Slama, Madhubanti Mukherjee, Andrea Vezzosi, Ursula Rothlisberger, Virginia Carnevali
Materials Science
Mechanisms of Resistive Switching in 2D Monolayer and Multilayer Materials
M. Kaniselvan, Y. R. Jeon, M. Mladenović et al. (+2 more)
The power and energy consumption of resistive switching devices can be lowered by reducing their active layer dimensions. Efforts to push this low-energy switching property to its limits have led to the investigation of active regions made with two-dimensional layered materials (2DLM). Despite their small dimensions, 2DLM exhibit a rich variety of switching mechanisms, each involving different types of atomic structure reconfigurations. In this review, we highlight and classify the mechanisms of resistive switching in mono and bulk 2DLM, with a subsequent focus on those occurring in a monolayer and/or localized to point defects in the crystalline sheet. We discuss the complex energetics involved in these fundamentally defect-assisted processes, including the co-existence of multiple mechanisms and influence of the contacts used. Examining the highly localized 'atomristor'-type switching, we provide insights into the atomic motions and electronic transport across the metal-2D interfaces underlying their operation. Finally, we present the progress and our perspective on the challenges associated with the development of 2D resistive switching devices. Promising application areas and material systems are identified and suggested for further research.
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All authors M. Kaniselvan, Y. R. Jeon, M. Mladenović, M. Luisier, D. Akinwande
Materials Science · Cross-listed from quant-ph
The effects of decoherence on Fermi's golden rule
Caihong Zheng and Fan Zheng
Fermi's golden rule which describes the transition rates between two electronic levels under external stimulations is used ubiquitously in different fields of physics. The original
Fermi's golden rule was derived from perturbative time-dependent Schrödinger's equation without the direct contribution by decoherence effect. However, as a result of recent developments of
quantum computing and ultra fast carrier dynamics, the decoherence becomes a prominent topic in fundamental research.Here, by using the non-adiabatic molecular dynamics which goes beyond the time-dependent Schrödinger's equation by introducing decoherence, we study the effect of decoherence on
Fermi's golden rule for the fixed basis and the adiabatic basis, respectively. We find that when the decoherence time becomes short, there is a significant deviation from the
Fermi's golden rule for both bases. By using monolayer $\mathrm{WS_2}$ as an example, we investigate the decoherence effect in the carrier transitions induced by the electron-
phonon coupling with first-principle method.
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Quantum Gases
Nucleation and wetting transitions in three-component Bose-Einstein condensates in Gross-Pitaevskii theory: exact results
Jonas Berx, Nguyen Van Thu and Joseph O. Indekeu
Nucleation and wetting transitions are studied in a three-component Bose-Einstein condensate mixture within Gross-Pitaevskii theory. For special cases of intermediate segregation between components 1 and 2, the nucleation phase transition of a surfactant film of component 3 is obtained by exact solution. Additional exact results for the nucleation transition are derived in the limit of strong segregation between components 1 and 2. In this limit the exact first-order wetting phase boundary is obtained using analytical and numerical methods, and is contrasted with the exact nucleation and wetting phase boundary derived previously for a two-component Bose-Einstein condensate mixture at a hard optical wall. Exact results for the three-component mixture are compared with results from the double-parabola approximation used in an earlier work.
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Materials Science
Lattice-to-Total Thermal Conductivity Ratio: A Phonon-Glass Electron-Crystal Descriptor for Data-Driven Thermoelectric Design
Yifan Sun, Zhi Li, Tetsuya Imamura et al. (+3 more)
Thermoelectrics (TEs) are promising candidates for energy harvesting with performance quantified by figure of merit, $ZT$. To accelerate the discovery of high-$ZT$ materials, efforts have focused on identifying compounds with low thermal conductivity $\kappa$. Using a curated
dataset of 71,913 entries, we show that high-$ZT$ materials reside not only in the low-$\kappa$ regime but also cluster near a
lattice-to-total thermal conductivity ratio ($\kappa_\mathrm{L}/\kappa$) of approximately 0.5. This optimal ratio provides a quantitative descriptor for the well-known
phonon-glass electron-
crystal (PGEC) design concept. Building on this insight, we construct a framework consisting of two machine learning models for the
lattice and electronic components of thermal conductivity that jointly provide both $\kappa$ and $\kappa_\mathrm{L}/\kappa$ for screening and guiding the optimization of TE materials. By applying this framework to 104,567 inorganic compounds, we identify 2,522 ultralow-$\kappa$ candidates while simultaneously evaluating their proximity to the optimal PGEC regime. A follow-up case study on chemical doping demonstrates how the framework can qualitatively provide optimization strategies that shift pristine materials toward the ideal $\kappa_\mathrm{L}/\kappa$ $\approx$ 0.5 target. Ultimately, by integrating rapid screening with PGEC-guided optimization, our data-driven framework takes a critical step towards closing the gap between materials discovery and performance enhancement.
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All authors Yifan Sun, Zhi Li, Tetsuya Imamura, Yuji Ohishi, Chris Wolverton, Ken Kurosaki
Superconductivity
Giant critical current peak induced by pressure in kagome superconductor RbV$_{3}$Sb$_{5}$
Lingfei Wang, Wenyan Wang, Tsz Fung Poon et al. (+11 more)
Superconductivity can coexist or compete with other orders such as magnetism or density waves. Optimizing superconductivity requires identifying competing orders that may disrupt Cooper pair coherence. Here, we use the self-field critical current ($I_{\rm c,sf}$) to probe pressure-tuned superconductivity in the kagome
superconductor RbV$_3$Sb$_5$. As pressure destabilizes the charge-density wave (CDW) state, $I_{\rm c,sf}$ drastically enhances, peaking near the critical pressure where the CDW state is completely suppressed at zero temperature. Surprisingly, a weaker $I_{\rm c,sf}$ peak emerges within the CDW phase. Near the pressure of the weaker peak, the superconducting phase transition temperature shifts from an increasing trend with pressure to a near plateau. Our analysis suggests the possibility of a sudden change in the CDW pattern or a Lifshitz transition, highlighting the need for microscopic examinations of the CDW state for understanding the pressure
evolution of superconductivity in RbV$_3$Sb$_5$.
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All authors Lingfei Wang, Wenyan Wang, Tsz Fung Poon, Zheyu Wang, Chun Wai Tsang, Xinyou Liu, Shanmin Wang, Kwing To Lai, Wei Zhang, Jeffery L. Tallon, Youichi Yamakawa, Hiroshi Kontani, Rina Tazai, Swee K. Goh
Materials Science
Accelerated Discovery of Crystalline Materials with Record Ultralow Lattice Thermal Conductivity via a Universal Descriptor
Xingchen Shen, Jiongzhi Zheng, Michael Marek Koza et al. (+9 more)
Ultralow glass-like
lattice thermal conductivity in crystalline materials is crucial for enhancing energy conversion efficiency in thermoelectrics and thermal
insulators. We introduce a universal descriptor for thermal conductivity that relies only on the atomic number in the primitive
cell and the sound velocity, enabling fast and scalable materials screening. Coupled with high-throughput workflows and universal machine learning potentials, we identify the candidate materials with ultralow thermal conductivity from over 25, 000 materials. We further validate this approach by experimentally confirming record-low thermal conductivity values of 0.15-0.16 W/m/K from 170 to 400 K in the halide metal CsAg2I3. Combining inelastic
neutron scattering with first-principles calculations, we attribute the ultralow thermal conductivity to the intrinsically small sound velocity, strong anharmonicity, and structural complexity. Our work illustrates how a universal descriptor, combined with high-throughput screening, machine-learning potential and experiment, enables the efficient discovery of materials with ultralow thermal conductivity.
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All authors Xingchen Shen, Jiongzhi Zheng, Michael Marek Koza, Petr Levinsky, Jiri Hejtmanek, Philippe Boullay, Bernard Raveau, Jinghui Wang, Jun Li, Pierric Lemoine, Christophe Candolfi, Emmanuel Guilmeau
Statistical Mechanics
From Static Pathways to Dynamic Mechanisms: A Committor-Based Data-Driven Approach to Chemical Reactions
Radu A. Talmazan and Christophe Chipot
As computational chemistry methods evolve, dynamic effects have been increasingly recognized to govern chemical reaction pathways in both organic and inorganic systems. Here, we introduce a committor-based workflow that integrates a path-committor-consistent artificial neural network (PCCANN) with an iteratively trained hybrid-DFT-level message passing atomic convolutional encoder (MACE) potential. Beginning with a static nudged elastic band path, PCCANN extracts a committor-consistent string to represent the reactive ensemble. We illustrate the power of this methodology through two representative applications. First, we investigate an SNAr reaction using MACE trained at hybrid DFT level with implicit solvent. The mechanism is found to be concerted, and the dynamic approach reveals a lower barrier than static treatments. Second, we apply the same protocol to the isomerization of protonated isobutanol to protonated 2-butanol, yielding a quantitatively accurate free-energy landscape. We uncover three competing channels: the established concerted mechanism and two asynchronous stepwise routes mediated by water and methyl transfer, all with comparable activation barriers. Notably, the stepwise pathways traverse metastable intermediates that, to the best of our knowledge, have not been described in prior mechanistic studies. Calculated barrier heights and intermediate stabilities are in close agreement with high-level DFT
benchmarks, demonstrating the framework's accuracy. Together, these studies highlight mechanistic diversity across distinct systems and establish the synergistic PCCANN-MACE protocol as a proof-of-concept approach for committor-based discovery of complex reaction dynamics.
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Statistical Mechanics
Quantum Hard Spheres with Affine Quantization
Riccardo Fantoni
We study a fluid of
quantum hard-spheres treated with affine-quantization. Assuming that the fluid obeys to Bose-Einstein statistics we solve for its thermodynamic properties using the path integral Monte Carlo method.