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Physics Condensed Matter

cond-mat Watch Condensed Matter

Wednesday 19 November

Statistical Mechanics

Pair distribution function of the cell fluid model with Curie-Weiss interaction

R.V. Romanik, O.A. Dobush, M.P. Kozlovskii et al. (+2 more)

In this paper we present results for the pair distribution function for the cell fluid model with Curie-Weiss interaction. As a supplementary result, one- and two-particle densities are calculated.
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All authors R.V. Romanik, O.A. Dobush, M.P. Kozlovskii, I.V. Pylyuk, M.A. Shpot

Mesoscale and Nanoscale Physics

Refraction-induced transverse charge transport

Ronika Sarkar, Arka Bandyopadhyay, Awadhesh Narayan et al. (+1 more)

We introduce a mechanism that produces a Hall-like transverse response in time-reversal-invariant materials, driven entirely by geometric effects. Specifically, we demonstrate that a tilted potential interface causes electron wave packets to undergo a refractionlike deflection upon transmission through the barrier, leading to a finite transverse current and a corresponding Hall-like conductance. Our analytical framework captures the essential features of this refraction-driven charge transport, and the resulting transverse conductance profile is corrob- orated by numerical simulations across different lattice models and device geometries. We further visualize our predicted effect through real-time wave packet dynamics, which reveals its purely geometric origin and the robustness of the transverse response. These findings establish a fundamentally distinct class of Hall-like transport phenomena in mesoscopic systems that preserve time-reversal symmetry.
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All authors Ronika Sarkar, Arka Bandyopadhyay, Awadhesh Narayan, Diptiman Sen

Materials Science

Photoluminescence Mapping of Mobile and Fixed Defects in Halide Perovskite Films

Sarah C. Gillespie, Jérome Gautier, Linde M. van de Ven et al. (+6 more)

Metal halide perovskites exhibit coupled electronic and ionic properties that determine their photovoltaic performance and operational stability. Understanding and quantifying ionic transport are therefore essential for advancing perovskite optoelectronics. Conventional electrical methods such as impedance spectroscopy require fully integrated devices, and their interpretation is often complicated by interfacial and contact effects, limiting the ability to isolate intrinsic ionic behavior. Here, a localized adaptation of intensity-modulated photoluminescence spectroscopy (IMPLS) is utilized to optically probe lateral ionic transport in perovskite films. The frequency-dependent photoluminescence response is measured under controlled carrier injection levels and correlated with the photoluminescence quantum yield (PLQY). The proposed diffusion model indicates that mobile ionic defects laterally migrate from high light intensity regions, giving rise to characteristic photoluminescence modulations. Ionic diffusion coefficients extracted from IMPLS agree well with literature values obtained from electrical measurements. Importantly, IMPLS mapping separates mobile and immobile defect contributions through a defect contrast coefficient (DCC), which quantifies the normalized difference between the area-averaged photoluminescence intensity and phase data. This work ultimately demonstrates that localized IMPLS provides a contact-free means to extract lateral ion diffusion coefficients while spatially distinguishing defect types across the sample.
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All authors Sarah C. Gillespie, Jérome Gautier, Linde M. van de Ven, Agustin O. Alvarez, Bruno Ehrler, L.J. Geerligs, Veronique S. Gevaerts, Gianluca Coletti, Erik C. Garnett

Mesoscale and Nanoscale Physics

Photoinduced topological phase transition in monolayer 1T$^\prime$-MoS$_2$

Mohammad Mortezaei Nobahari

We investigate the systematic competition between perpendicular electric field and circularly polarized light in nonequilibrium topological phases of monolayer 1T$^\prime$–MoS$_2$ using a low-energy $k\!\cdot\!p$ Hamiltonian and Floquet theory. The off-resonant field generates spin- and valley-dependent mass corrections that reshape the Berry curvature (BC) and shift the conditions for band inversion. By evaluating the quasienergy bands, BC, and spin- valley-resolved Chern numbers, we identify a sequence of light and electric field controlled topological transitions by gap closing. Depending on the Floquet coupling strength and the electric-field parameter, the system evolves between the equilibrium quantum spin Hall (QSH) state and a set of driven phases including spin-polarized quantum Hall insulator (S-QHI), band insulator (BI) and photo-induced quantum Hall insulator (P-QHI) regimes. The results establish 1T$^\prime$–MoS$_2$ as a tunable platform where circular driving selectively manipulates spin and valley degrees of freedom, enabling controlled access to non-equilibrium topological phases in transition metal dichalcogenides (TMDs).
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Superconductivity

Identifying the structure of La3Ni2O7 in the pressurized superconducting state

Hengyuan Zhang, Jielong Zhang, Mengwu Huo et al. (+6 more)

The crystal structure of La3Ni2O7 in its high-pressure superconducting state has been the subject of intense debate, with conflicting reports proposing orthorhombic (Amam or Fmmm) and tetragonal (I4/mmm) symmetries. Here, using high-pressure Raman spectroscopy down to 3 K, we resolve this controversy by tracking the structural evolution of La3Ni2O7 up to 32.7 GPa. Leveraging rigorous symmetry-based selection rules, we identify a single structural transition from the orthorhombic Amam phase to the Fmmm phase at ~14.5 GPa, signaled by a profound phonon renormalization. Crucially, the persistence of D2h symmetry across the transition rules out the tetragonal I4/mmm phase in the superconducting state in our measurements. The emergence of bulk superconductivity coincides precisely with this transition. Our results establish the orthorhombic Fmmm structure as the intrinsic host of superconductivity in La3Ni2O7 below 19.45 GPa, resolving a central structural controversy and providing a critical foundation for understanding the superconducting mechanism in bilayer nickelates.
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All authors Hengyuan Zhang, Jielong Zhang, Mengwu Huo, Junfeng Chen, Deyuan Hu, Dao-Xin Yao, Hualei Sun, Kun Cao, Meng Wang

Materials Science

Ab initio calculations of the thermoelectric figure of merit, within the relaxation time approximation

Laurent Chaput, Henrique Miranda, Atsushi Togo et al. (+4 more)

In this paper, we propose a computational framework, based on the VASP and phono3py computer codes, to obtain the thermoelectric figure of merit from the electron-phonon and phonon-phonon interactions using finite displacements in supercells. Several numerical techniques are developed for efficiency. The method is applied to several thermoelectric materials. We found different behaviors for the lifetimes of the electrons in PbTe, PbSe, and in compounds of the half-Heusler and magnesium silicide family. This is traced back to the different frequencies of the phonons involved in the scattering around the Fermi level. They have a lower frequency in PbTe and PbSe. The magnitude of the thermoelectric figures of merit we computed compare well with experiments, but the agreement is far from perfect. The role of the defects, not explicitly considered in our calculations, but abundant in thermoelectric materials, is discussed as a possible explanation. It is also shown that the choice of the exchange-correlation functional can strongly impact the results.
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All authors Laurent Chaput, Henrique Miranda, Atsushi Togo, Manuel Engel, Martin Schlipf, Martijn Marsman, Georg Kresse

Materials Science

Dynamic precipitation during high-pressure torsion of a magnesium-manganese alloy

Julian M. Rosalie and Anton Hohenwarter

An ultrafine grained magnesium alloy has been produced through room temperature high-pressure torsion (HPT) of solutionised Mg-1.35 wt.%Mn. Dynamic precipitation of nanometer-scale Mn particles occurred during deformation. These particles populated the grain boundaries, acting as pinning sites which allowed the alloy to develop a grain size of 140 nm after 0.5 rotations. Further HPT deformation resulted in a gradual increase in grain size with no increase in precipitate size. Despite the extensive deformation applied, the alloy did not develop a bimodal grain structure and retained a grain size of 230 nm after 10 complete rotations, demonstrating the stability and effectiveness of these pinning particles.
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Materials Science

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties with Phonon-Informed Datasets

Pol Benítez, Cibrán López, Edgardo Saucedo et al. (+2 more)

Machine learning (ML) methods have become powerful tools for predicting material properties with near first-principles accuracy and vastly reduced computational cost. However, the performance of ML models critically depends on the quality, size, and diversity of the training dataset. In materials science, this dependence is particularly important for learning from low-symmetry atomistic configurations that capture thermal excitations, structural defects, and chemical disorder, features that are ubiquitous in real materials but underrepresented in most datasets. The absence of systematic strategies for generating representative training data may therefore limit the predictive power of ML models in technologically critical fields such as energy conversion and photonics. In this work, we assess the effectiveness of graph neural network (GNN) models trained on two fundamentally different types of datasets: one composed of randomly generated atomic configurations and another constructed using physically informed sampling based on lattice vibrations. As a case study, we address the challenging task of predicting electronic and mechanical properties of a prototypical family of optoelectronic materials under realistic finite-temperature conditions. We find that the phonons-informed model consistently outperforms the randomly trained counterpart, despite relying on fewer data points. Explainability analyses further reveal that high-performing models assign greater weight to chemically meaningful bonds that control property variations, underscoring the importance of physically guided data generation. Overall, this work demonstrates that larger datasets do not necessarily yield better GNN predictive models and introduces a simple and general strategy for efficiently constructing high-quality training data in materials informatics.
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All authors Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla

Soft Condensed Matter

Particle deformability stabilizes hexatic order and suppresses crystallization

Jatin Kumar, Wu Zeng, Anshuman Pasupalak et al. (+1 more)

We show that two-dimensional systems of deformable particles undergo a continuous liquid-hexatic transition upon compression or cooling, but no hexatic-solid transition-even at zero temperature and high density. Numerical simulations reveal that solid-like configurations do not possess a lower energy than hexatic ones, so that at low temperatures the hexatic phase is thermodynamically favored due to its higher entropy. Dislocation condensation, necessary for solid formation, is suppressed as the system accommodates strain via particle shape changes, responding affinely to compression. Our findings identify a generic route by which microscopic mechanical properties control defect energetics and reshape phase behavior in two dimensions, with broad relevance for soft and biological materials such as microgels and epithelial tissues.
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All authors Jatin Kumar, Wu Zeng, Anshuman Pasupalak, Massimo Pica Ciamarra

Materials Science

Wannier based analysis of the direct-indirect bandgap transition by stacking MoS$_2$ layers

Shunsuke Hirai, Ibuki Terada and Michi-To Suzuki

Molybdenum disulfide (MoS$_2$), a layered van der Waals material, has attracted considerable attention as a promising alternative to graphene for applications in field-effect transistors and nanophotonic devices because of its sizable band gap, high carrier mobility, large on/off ratio, and strong photoluminescence efficiency. A particularly intriguing property of MoS$_2$ is the transition of its band gap character with layer thickness: while the monolayer exhibits a direct gap, the band gap becomes indirect in multilayer and bulk forms.In this study, we clarify the microscopic mechanism underlying this transition. Focusing on the roles of atomic orbitals and interlayer interactions, we perform an analysis combining first-principles calculations with a Wannier-based model. Although interlayer $p_z$–$p_z$ coupling between neighboring sulfur atoms has been recognized as a key factor in this transition, we find that a complete quantitative description additionally requires interlayer $p_z$–$p_x$ and $p_z$–$p_y$ couplings between neighboring sulfur atoms. These findings highlight the importance of both out-of-plane and in-plane orbital contributions in governing the electronic structure of layered MoS$_2$, providing deeper insight into its band gap engineering for future device applications.
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Statistical Mechanics

Critical exponents of the Ising model with quenched structural disorder and long-range interactions at spatial dimension $d=3$

D. Shapoval and M. Dudka

We analyse the critical properties of a weakly diluted (random) Ising model with the long-range interaction decaying with distance $x$ as $\sim x^{-d-\sigma}$ in a $d$-dimensional space. It is known to belong to a new long-range random universality class for certain values of the decay parameter $\sigma$. Exploiting the field-theoretic renormalization group approach within the minimal subtraction scheme, we compute the three-loop renormalization group functions. On their basis, with the help of asymptotic series resummation methods, we estimate the correlation length critical exponent $\nu$ characterising the new universality class for $d=3$ and for those values of $\sigma$ for which long-range interactions are relevant for the critical behaviour.
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Materials Science

Effects of Interactions and Defect Motion on Ramp Reversal Memory in Locally Phase Separated Materials

Y. Sun, M. Alzate Banguero, P. Salev et al. (+4 more)

The ramp-reversal memory (RRM) effect in metal-insulator transition metal oxides (TMOs), a non-volatile resistance change induced by repeated temperature cycling, has attracted considerable interest in neuromorphic computing and non-volatile memory devices. Our previously introduced defect motion model successfully explained RRM in vanadium dioxide (VO$_2$), capturing observed critical temperature shifts and memory accumulation throughout the sample. However, this approach lacked interactions between metallic and insulating domains, whereas the RRM only appears when TMOs are brought into the metal-insulator coexistence regime. Here, we extend our model by combining the Random Field Ising Model with defect diffusion-segregation, thereby enabling accurate hysteresis modeling while predicting the relationship between RRM and domain interactions. Our simulations demonstrate that maximum RRM occurs when the turnaround temperature approaches the warming branch inflection point, consistent with experimental observations on VO$_2$. Most significantly, we find that increasing nearest-neighbor interactions enhances the maximum memory effect, thus providing a clear mechanism for optimizing RRM performance. Since our model employs minimal assumptions, we predict that RRM should be a widespread phenomenon in materials exhibiting patterned phase coexistence of electronic domains. This work not only advances fundamental understanding of memory behavior in TMOs but also establishes a much-needed theoretical framework for optimizing device applications.
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All authors Y. Sun, M. Alzate Banguero, P. Salev, Ivan K. Schuller, L. Aigouy, A. Zimmers, E. W. Carlson

Strongly Correlated Electrons

Characterizing entanglement at finite temperature: how does a "classical" paramagnet become a quantum spin liquid?

Snigdh Sabharwal, Matthias Gohlke, Paul Skrzypczyk et al. (+1 more)

Quantum spin liquids (QSL) are phases of matter which are distinguished not by the symmetries they break, but rather by the patterns of entanglement within them. Although these entanglement properties have been widely discussed for ground states, the way in which QSL form at finite temperature remains an open question. Here we introduce a method of characterizing both the depth and spatial structure of entanglement, and use this to explore how patterns of entanglement form as temperature is reduced in two widely studied models of QSL, the Kitaev honeycomb model, and the spin-1/2 Heisenberg antiferromagnet on a Kagome lattice. These results enable us to evaluate both the temperature at which spins within the high-temperature paramagnet first become entangled, and the temperature at which the system first develops the structured, multipartite entanglement characteristic of its QSL ground state.
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All authors Snigdh Sabharwal, Matthias Gohlke, Paul Skrzypczyk, Nic Shannon

Superconductivity

Microscopic Investigation of rf Vortex Nucleation in Nb3Sn Films Using a Near-Field Magnetic Microwave Microscope

Chung-Yang Wang, Zeming Sun, Thomas Oseroff et al. (+2 more)

We use a near-field magnetic microwave microscope to investigate and compare rf vortex nucleation in two superconducting radio-frequency (SRF)-quality Nb3Sn films fabricated by different methods: a conventional vapor-diffused film and an electrochemically plated film followed by thermal annealing, both of which are deposited on Nb substrates. The microscope applies a localized rf magnetic field to the sample surface and measures the resulting third-harmonic response P3f, which is particularly sensitive to rf vortex nucleation triggered by surface defects. Both Nb3Sn films exhibit nontrivial P3f(T) structures below 7 K that display the key signatures associated with rf vortex nucleation at local defects. The electrochemical film additionally shows multiple P3f(T) structures between 14 K and 16 K that are absent in the vapor-diffused sample. Our results highlight the influence of fabrication method on rf vortex penetration properties and demonstrate the utility of third-harmonic response as a local diagnostic tool for surface defects in Nb3Sn films.
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All authors Chung-Yang Wang, Zeming Sun, Thomas Oseroff, Matthias U. Liepe, Steven M. Anlage

Materials Science

Deep Learning Assisted Prediction of Electrochemical Lithiation State in Spinel Lithium Titanium Oxide Thin Films

Devin Chugh, Bhagath Sreenarayanan, Steven Suwito et al. (+4 more)

Machine Learning (ML) and Deep Learning (DL) based framework have evolved rapidly and generated considerable interests for predicting the properties of materials. In this work, we utilize ML-DL framework to predict the electrochemical lithiation state and associated electrical conductivity of spinel Li4Ti5O12 (LTO) thin films using Raman spectroscopy data. Raman spectroscopy, with its rapid, non-destructive, and high-resolution capabilities, is leveraged to monitor dynamic electrochemical changes in LTO films. A comprehensive dataset of 3,272 Raman spectra, representing lithiation states from 0% to 100%, was collected and preprocessed using advanced techniques including cosmic ray removal, smoothing, baseline correction, normalization, and data augmentation. Classical machine learning models such as Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and Random Forest (RF) were evaluated alongside a Convolutional Neural Network (CNN). While traditional models achieved moderate to high accuracy, they struggled with generalization and noise sensitivity. In contrast, the CNN demonstrated superior performance, achieving over 99.5% accuracy and robust predictions on unseen samples. The CNN model effectively captured non-linear spectral features and showed resilience to experimental variability. This pipeline not only enables accurate lithiation state classification but also facilitates conductivity estimation, offering a scalable approach for real-time battery material characterization and potential extension to other spectroscopic datasets.
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All authors Devin Chugh, Bhagath Sreenarayanan, Steven Suwito, Ganesh Raghavendran, Bing Joe Hwang, Ying Shirley Meng, Weinien Su

Materials Science

Anisotropic in-plane lattice thermal conductivity in bilayer ReS2

Ashutosh Srivastava, Nikhilesh Maiity and Abhishek Kumar Singh

The significantly weak interlayer coupling strength and puckered structure provide the novel layer-tolerant and anisotropic features in two-dimensional (2D) ReS2. These unique features offer an opportunity to modulate the optoelectronic, vibrational, and transport properties along different lattice directions in ReS2. Here, using first-principles density functional theory (DFT), we investigated the thermal transport properties of ReS2 in AA and AB stacking orders. The anisotopic ratios for lattice thermal conductivities (ąppa}) are found to be 1.08 and 1.12 for AA and AB stacking, respectively. This anisotropic nature remains intact even at higher temperatures up to 1000K, demonstrating anisotropic robustness. Lower symmetry in AB stacking leads to higher phonon scattering, which results in lower group velocity, smaller phonon lifetime, and thereby lower ąppa} along both directions as compared to AA stacking. The strong breathing and shear Raman modes in AB stacking indicate stronger layer coupling, further confirming the dominant contribution of acoustic modes towards thermal transport. The findings underscore that the stacking-order-driven preferential heat flow in ReS2 and opens up a new dimension for optimizing device performance.
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Materials Science

Integrating Atomic Scale Catalyst Design with Transport Engineering for Stable and Efficient CO2 Electrolysis to CO in a Membrane Electrode Assembly

Zahra Teimouri, Mahtab Masouminia, Ashkan Irannezhad et al. (+8 more)

Electrochemical CO2 reduction (CO2R) offers a promising approach to decarbonize chemical manufacturing through production of carbon-neutral fuels. However, insufficient performance and instability of membrane electrode assembly (MEA) reactors limit commercial viability, with both metrics directly impacted by the CO2R catalysts. Here we develop an atomically dispersed nickel-nitrogen-carbon (Ni-NC) catalyst through a scalable synthesis approach using two different carbon supports. When using carbon nanotubes as the support, the resulting Ni-NCNT electrode achieves a partial current density toward CO of 558 mA cm-2 with 92 percent Faradaic efficiency toward CO at a cell voltage of 3.2 V and an energy efficiency of 39 percent toward CO at a total current density of 607 mA cm-2. The MEA demonstrates stable operation at 100 mA cm-2 over 210 hours, outperforming previously reported Ni-NC catalysts. Focused ion beam scanning electron microscopy (FIB-SEM) tomography illustrates the key role of catalyst support on the performance of the electrode. COMSOL Multiphysics simulations using 3D reconstructed images of the catalyst layers from FIB-SEM tomography demonstrate that the higher CO2R performance of the Ni-NCNT electrode is due to improved CO2 diffusion and a more uniform current-density distribution compared to the Ni-NCB electrode prepared with carbon black as the support. The stability and performance of the Ni-NCNT compare favorably to state-of-the-art Ag-based catalysts, while bottom-up cost analysis estimates the purchase cost of the Ni-NCNT catalyst to be about 589 USD per kg, substantially lower than the 1900 USD per kg estimated for Ag-based catalysts.
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All authors Zahra Teimouri, Mahtab Masouminia, Ashkan Irannezhad, Reza Eslami, Joseph Deering, Navid Noor, Shunquan Tan, Amirhossein Foroozan, Shayan Angizi, Sung-Fu Hun, Drew Higgins

Materials Science

A Novel Strategy to Strengthen Directionally Solidified Superalloy Through Grain Boundary Simplified Design

Yunpeng Fan, Xinbao Zhao, Yu Zhou et al. (+4 more)

Conventional strategies for enhancing creep resistance often rely on grain boundary strengthening, yet this approach can inadvertently promote premature grain boundary fracture. This study presents a subtractive alloy design strategy for nickel-based directionally solidified superalloys (DS superalloy) through elimination of conventional grain boundary strengthening elements (C, B, Zr) and the strategy improves the creep performance by 60% rivaling 2nd generation single crystal superalloys. Through characterization of heat-treated and heat-exposed microstructures, we confirm the suppression of deleterious grain boundary phases. Creep tests and fracture analysis reveal a critical transition in failure mechanism: the removal of these elements shifts the fracture mode from transgranular to intergranular. Our discussion comprehensively links this microstructural engineering to the underlying creep deformation mechanisms, showing that the enhanced performance stems from stabilization of {\gamma} channel and phase interfaces within grains, as well as strengthening of grain boundaries through serration. This work establishes a novel materials design principle that decouples grain boundary strengthening from elemental additions, offering transformative potential for next-generation high-efficiency turbine blade applications.
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All authors Yunpeng Fan, Xinbao Zhao, Yu Zhou, Quanzhao Yue, Wanshun Xia, Yuefeng Gu, Ze Zhang

Materials Science

Pressure-Induced Reversal of Thermal Anisotropy in Bi2O2Se

Zunyi Deng, Wenwen Xuan, Bin Wei et al. (+1 more)

Bi2O2Se is an emerging semiconductor with intrinsically low thermal conductivity, making it a promising material for thermoelectric applications. Hydrostatic pressure can effectively tunes the thermal conductivity, with various pressure-dependent trends reported. However, its impact on thermal anisotropy, particularly in the highly anisotropic Bi2O2Se, remains poorly understood. Here, we report a pressure-driven reversal of thermal anisotropy: k_z < k_x at 0 GPa transforms into k_z > k_x at 60 GPa without phase transition. This stems from distinct phonon dispersions along the x- and z-directions under pressure, leading to a reshaped group velocity landscape. Below 10 meV, vz > vx at both pressures, with a much greater advantage at 60 GPa. Above 10 meV, vx > vz at 0 GPa; however, the difference nearly vanishes at 60 GPa. These changes result from anisotropic lattice compression, with the z-axis shrinking more significantly than the x-axis and suppressing the lone pair activity of Bi atoms. This study calls for revisiting the pressure dependence of thermal conductivity anisotropy and provides insights for pressure-driven thermal switching applications.
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All authors Zunyi Deng, Wenwen Xuan, Bin Wei, Yongheng Li

Superconductivity

Synthetic area spread in two-dimensional arrays of superconducting quantum interference filters

Ross D. Monaghan, Jonathan L. Marenkovic and Giuseppe C. Tettamanzi

Superconducting Quantum Interference Devices (SQUIDs), formed by incorporating Josephson junctions into loops of superconducting material, are the backbone of many modern quantum sensing systems. It has been demonstrated that, by combining multiple SQUID loops into a two-dimensional (2D) array, it is possible to fabricate ultra-high-performing radio-frequency sensors. However, to function as absolute magnetometers, current-in-use arrays require the area of each SQUID loop in the array to be incommensurate. Doing so forbids the achievement of their full potential of performance, limited only by the standard quantum limit. This is because imposing incommensurability in the areas contrasts with optimised performance in each single SQUID loop. In this work, we report that by selectively inserting bare sections of a superconducting circuit with no Josephson junctions, 2D SQUID arrays can operate as an absolute magnetometer even when no physical area spread is applied. Based on a generalisation of currently available theories, a complete analytical formulation for the one-to-one correspondence between the distribution of these bare loops and what we call a synthetic areas spread is unveiled. This synthetic spread represents the equivalent physical spread of incommensurate SQUID loops that you would use to obtain the absolute Voltage-Magnetic Flux response if no bare loops were in use. Our work opens the way to a broader use of this technology for the fabrication of ultra-high-performance absolute quantum sensors. Our approach is also experimentally verified by fabricating several 2D Superconducting Quantum Interference Filter (SQIF) arrays incorporating bare superconducting loops and by demonstrating that they behave in alignment with what is suggested by our theory.
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Statistical Mechanics

On Entropic Characterization of Symmetry Breaking in Dynamical Systems I: Spontaneous Symmetry Breaking

Subhrajit Sinha and Parvathi Kooloth

Symmetry breaking is a central organizing principle of nonlinear dynamics, yet its information-theoretic signatures remain poorly understood. In this work, we develop an entropic framework for analysing spontaneous symmetry breaking in equivariant dynamical systems, that distinguishes between local and global mechanisms of symmetry loss and shows that each requires a different analytical lens. For local spontaneous symmetry breaking, where a symmetric equilibrium loses stability through bifurcation, we show that critical slowing down broadens the regularized invariant density, increases Shannon entropy, and sharply amplifies steady-state directional information transfer. For global spontaneous symmetry breaking, where the invariant measure itself undergoes qualitative reorganization, we derive a general entropy law for invariant-density restructuring. The broken-phase entropy decomposes into an internal sector entropy and a symmetry-label information term, with classical invariant-set splitting arising as the disjoint-sector limit. Consequently, global symmetry breaking may either increase or decrease entropy depending on how probability is redistributed across symmetry-related sectors. Analytical results are illustrated through canonical examples, providing a quantitative bridge between symmetry, bifurcation structure, invariant measures, and information theory in dynamical systems.
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Disordered Systems and Neural Networks

Impact of Random Spatial Truncation and Reciprocal-Space Binning on the Detection of Hyperuniformity in Disordered Systems

Yuan Liu, Xurui Li, Jianxiang Tian et al. (+2 more)

We study how finite-window sampling (random spatial truncation) and reciprocal-space radial binning influence the detection of hyperuniformity in disordered systems. Using thirteen representative two-dimensional simulation systems (two stealthy hyperuniform systems with distinct constraint parameters and ; hyperuniform Gaussian pair statistics system; six hyperuniform targeted systems with distinct alpha=0.5, 0.7, 1.0, 1.3, 1.5, 3.0, random sequential addition system; Poisson points distribution system; Lennard-Jones fluid system and Yukawa fluid system) and two real biological systems (avian photoreceptor patterns and looped leaf vein networks) We find that moderate random spatial truncation (i.e., randomly extracting a smaller subwindow from the original full-field configuration) does not change qualitatively the hyperuniformity classification of the systems. Specifically, disordered hyperuniform systems retain their respective hyperuniformity classes despite a modest reduction in measured hyperuniformity exponent alpha (i.e., reduction in small-k suppression). Moreover, spatial truncation commonly induces configuration-dependent fluctuations of small-k values of S(k). We show that modest reciprocal-space radial pooling (controlled by a binning parameter m) effectively smooths such spurious wiggles without changing the hyperuniformity class. Practical guidelines for choosing m, cross-checking spectral fits with the local number variance scaling, and increasing effective sampling are provided. These results provide concrete, low-cost and effective methodology for robust spectral detection of hyperuniformity in finite and truncated datasets which abound in experimental systems.
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All authors Yuan Liu, Xurui Li, Jianxiang Tian, Xunwang Yan, Ge Zhang

Tuesday 18 November

Statistical Mechanics · Cross-listed from physics.hist-ph

DNNs, Dataset Statistics, and Correlation Functions

Robert W. Batterman and James F. Woodward

This paper argues that dataset structure is important in image recognition tasks (among other tasks). Specifically, we focus on the nature and genesis of correlational structure in the actual datasets upon which DNNs are trained. We argue that DNNs are implementing a widespread methodology in condensed matter physics and materials science that focuses on mesoscale correlation structures that live between fundamental atomic/molecular scales and continuum scales. Specifically, we argue that DNNs that are successful in image classification must be discovering high order correlation functions. It is well-known that DNNs successfully generalize in apparent contravention of standard statistical learning theory. We consider the implications of our discussion for this puzzle.
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Materials Science · Cross-listed from physics.chem-ph

Catalytic Resonance Theory: Kinetics and Frequency Response of Light-Promoted Catalysis

Paul J Dauenhauer

The illumination of catalytic surfaces with a continuous or pulsed stream of photons dynamically modulates surface chemistry for faster rates, higher conversion, or product selectivity control. To establish fundamental principles of dynamic photon-modulated catalysis, the photocatalytic conversion of a generic surface reaction was simulated to understand the kinetic implications of an independent stream of photons promoting surface product desorption. Simulations were conducted via the microkinetic model and kinetic Monte Carlo methods for the scenarios of a Poisson distribution, constant spacing between photons, and coordinated on/off pulsing of photon sources. The time-averaged photocatalytic rate at differential conditions for varying photon flux and temperatures indicated three kinetic regimes described by product thermal desorption control, surface reaction control, and an intermediate kinetic regime with a zero slope Arrhenius plot, consistent with a degree of rate control dominated by the photon arrival frequency (i.e., per-site photon flux). The maximum photocatalytic rate occurred orders of magnitude above the Sabatier limit at the resonance frequency, identified as the photon arrival frequency that matched the surface reaction rate constant. Non-equilibrium photocatalytic conversion occurred when the rate of photon-promoted product desorption was comparable to the rate of thermal product desorption. Results indicated the general utility of photon-promoted catalysis, with negligible benefit for rate enhancement and quantum yield with photon source pulsing or chopping due to the inherent dynamic nature of photons from light sources.
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Disordered Systems and Neural Networks

Transferable potential for molecular dynamics simulations of borosilicate glasses and structural comparison of machine learning optimized parameters

Kai Yang, Ruoxia Chen, Anders K.R. Christensen et al. (+4 more)

The simulation of borosilicate glasses is challenging due to the composition and temperature dependent coordination state of boron atoms. Here, we present a newly developed machine learning optimized classical potential for molecular dynamics simulations that achieves transferability across diverse borosilicate glass compositions. Our potential accurately predicts the glass structural variations in short- and medium-range order in different glass compositions, including validating our potential against experimental X-ray structure factor data. Notably, these data are not included in the optimization framework, which focuses exclusively on density and four-fold coordinated boron fraction. We further investigate the impact of empirical parameters in the force field formulation on the microscopic bond lengths, bond angles and the macroscopic densities, providing new insights into the relationship between interatomic potentials and bulk glass behaviors.
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All authors Kai Yang, Ruoxia Chen, Anders K.R. Christensen, Mathieu Bauchy, N.M. Anoop Krishnan, Morten M. Smedskjaer, Fabian Rosner

Materials Science

Electric-Field-Dependent Thermal Conductivity in Fresh and Aged Bulk Single Crystalline $\mathrm{BaTiO_3}$

Fanghao Zhang, Guanchun Rui, Yujie Quan et al. (+4 more)

Active thermal management requires advances in thermal switching materials, whose thermal conductivity responds to external stimuli. The electric field, as one of the most convenient and effective stimuli, has shown great potential in tuning the thermal conductivity of ferroelectric materials. While previous studies on electric-field-induced ferroelectric thermal switching have primarily focused on thin films and bulk solid solutions with strong extrinsic interface and defect scatterings, bulk single crystals, which can offer clear insights into intrinsic thermal switching mechanisms, have received comparatively less attention. Here, we demonstrate electric-field-induced thermal switching in bulk single-crystalline $\mathrm{BaTiO_3}$ (BTO) at room temperature and elucidate the critical role of domain evolution and aging in governing heat transport. Using a customized steady-state platform with in-situ electric fields up to $\pm$10 kV/cm, we observe a modulation of thermal conductivity up to 35% in fresh BTO driven by polarization reorientation and domain restructuring. First-principles finite-temperature lattice-dynamics calculations confirm that the switching behavior primarily originates from anisotropic phonon transport associated with domain configuration rather than strain-induced changes in phonon velocities. We further reveal that both ambient aging and controlled thermal aging can enhance the switching contrast through the formation and alignment of defect dipoles that modulate phonon-defect scattering. These results establish defect-domain interactions as a powerful design parameter for ferroelectric thermal switches and demonstrate a versatile experimental platform for exploring field-tunable heat transport and phase behavior in bulk functional materials.
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All authors Fanghao Zhang, Guanchun Rui, Yujie Quan, Shantal Adajian, Matthew Delmont, Q. M. Zhang, Bolin Liao

Quantum Gases

Generalized one-dimensional nonpolynomial Schrödinger equation for Bose-Einstein condensates with generic transverse confinement

Andréia M. Basso and Wesley B. Cardoso

This work presents a dimensional reduction of Bose-Einstein condensates confined by generalized transverse potentials, parametrized by an exponent $n$. Starting from the three-dimensional Gross-Pitaevskii equation, we employ a variational ansatz to derive an effective one-dimensional nonpolynomial Schrödinger equation, which self-consistently determines the transverse width dynamics. The model generalizes existing formalisms for cigar- and funnel-shaped geometries. We validate the approach through comprehensive numerical tests, demonstrating excellent agreement with full 3D simulations for ground-state properties across various interaction regimes. Finally, real-time simulations of matter-wave scattering at potential barriers verify the model's dynamical robustness, successfully replicating the spatiotemporal evolution and energy-dependent transmission characteristics observed in full 3D calculations.
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Strongly Correlated Electrons

Spin-quenching in molecule-transition-metal-dichalcogenide heterostructure through inverse proximity effect

Swagata Acharya, Dimitar Pashov, Daphne Lubert-Perquel et al. (+2 more)

A functional heterostructure is central to integrated circuitry in quantum photonics, optoelectronics, neuromorphic computing, spintronics, and straintronics. Recently, heterostructures combining 2D magnets and nonmagnetic transition metal dichalcogenides (TMDs) have been explored. In these, electron and hole wavefunctions are localized in 2D magnets but delocalized in TMDs. When combined, a proximity induced magnetic inter layer exciton can emerge, with energy differing by 20 to 30 meV from intra layer excitons and being two orders of magnitude darker, making it hard to detect and functionalize. Using a high fidelity ab initio many body diagrammatic approach, we show that functionality can be significantly enhanced in a transition metal molecule TMD interface. The molecular exciton exhibits charge transfer character and is extended, unlike the localized Frenkel excitation in 2D magnets. Moreover, the degree of localization and magnetic moment can be tuned by varying the molecular orientation relative to the TMD. This changes the proximity to the magnetic ion, altering screening and enabling a pathway to quench the ion's spin moment. This inverse proximity effect tunes the energies, spin states, and brightness of molecular and inter layer magnetic excitons, a mechanism absent in 2D magnet TMD systems. We also identify conditions under which the interlayer exciton becomes well separated and brighter than intra layer excitons, making it promising for protocols that probe and manipulate magnetic excitonic states.
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All authors Swagata Acharya, Dimitar Pashov, Daphne Lubert-Perquel, Mark van Schilfgaarde, Justin C. Johnson

Materials Science

Third-Body Stabilization of Supercritical CO2 in CO Oxidation: Development and Application of a ReaxFF Force Field for the CO/O/CO2 System

Emdadul Haque Chowdhury, Masoud Aryanpour, Yun Kyung Shin et al. (+3 more)

Supercritical CO2 (scCO2) plays a crucial role as a solvent in separation processes, advanced power cycles, and materials processing. Nonetheless, the atomistic comprehension of how the dense scCO2 matrix influences the fundamental reaction of carbon monoxide (CO) is still insufficiently explored. Experimental studies and molecular dynamics (MD) simulations frequently fail to detect the highly reactive, transient intermediates, such as atomic oxygen (O), that drive these reactions. To address this issue, we have developed a novel ReaxFF reactive force field for the CO2/CO/O system. The force field parameters were calibrated using density functional theory and second-order Moller-Plesset calculations to model CO2 crystal properties, intermolecular interactions, bond dissociation curves, and reaction energy barriers. The force field reproduces the cohesive energy of the CO2 crystal, the pressure characteristics of bulk scCO2, the equation-of-state behavior over a wide pressure-density range, the pressure dependence of the C-O bond length under compression, and the structural properties of liquid and scCO2, as documented by experiments, ab-initio MD, and prominent non-reactive models. The force field was subsequently applied to study the CO + O -> CO2 reaction. In a dilute environment, the reaction is inefficient as the newly formed CO2 rapidly dissociates due to excess kinetic and potential energy acquired from the exothermic reaction. Conversely, in a dense scCO2 environment, the surrounding matrix acts as an efficient third body, stabilizing the emerging CO2 product via molecular collisions. Statistical analysis confirms an average excess energy dissipation of 133.9 +/- 3.6 kcal/mol over 112.4 +/- 17.9 ps. Kinetic energy decomposition reveals that approximately 92% of the excess kinetic energy is stored in internal (rotational and vibrational) degrees of freedom.
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All authors Emdadul Haque Chowdhury, Masoud Aryanpour, Yun Kyung Shin, Bladimir Ramos-Alvarado, Matthias Ihme, Adri van Duin

Strongly Correlated Electrons

Origin of metal-insulator transition in rare-earth Nickelates

Swagata Acharya, Brooks Tellekamp, Jerome Jackson et al. (+4 more)

Rare-earth nickelates RNiO3 (R=rare-earth element) exhibit three kinds of phase transitions with decreasing temperature: a structural transition from a pseudo-cubic to a monoclinic phase, a metal- insulator transition (MIT), and a magnetic transition from a paramagnetic state to an ordered one. The first two occur at the same temperature, which has led to a consensus that the MIT is driven by lattice distortions. We show here that the primary driving force for the MIT is magnetic; however because of the unusual d7 configuration of Ni, additional flexibility in spin configurations are also needed which symmetry-lowing structural deformations make possible. The latter enable Ni to disproportionate into two kinds: a high-spin and a low-spin configuration, which allow the system to reduce its unfavorable orbital moment and also open a gap.
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All authors Swagata Acharya, Brooks Tellekamp, Jerome Jackson, Dimitar Pashov, Jeffrey L. Blackburn, Kirstin Alberi, Mark van Schilfgaarde