Materials Science
Probabilistic calibration of crystal plasticity material models with synthetic global and local data
Joshua D. Pribe, Patrick E. Leser, Saikumar R. Yeratapally et al. (+1 more)
Calibrating full-field
crystal plasticity (CP) models using global stress-strain curves alone often produces non-unique parametrizations: multiple parameter sets can predict the same global behavior but different local, grain-scale behavior. Incorporating local calibration data can mitigate uniqueness issues, but this typically requires specialized experiments like high-energy X-ray diffraction microscopy. The computational expense of full-field simulations also prevents uncertainty quantification with sampling-based probabilistic calibration
algorithms like Markov chain Monte Carlo. In this study, a two-stage probabilistic calibration procedure is developed that uses both global and local data and balances the efficiency of a surrogate model with the accuracy of a full-field CP model. To enable tractable
Bayesian inference via sampling from the full-field model, an efficient, parallelized sequential Monte Carlo (SMC)
algorithm is used to perform the calibration, which involves more than 100,000 CP simulations. Synthetic measurement data is used in the calibration to assess uncertainty and accuracy of the parameter posterior distributions relative to a "ground-truth" simulation with a microstructure representative of Inconel 718. The two-stage calibration is shown to be robust to limited and noisy local data. Posterior distributions 'and computational costs are compared between the two-stage calibration and a one-stage calibration using only the full-field model, which is also enabled by SMC, as well as an efficient but biased one-stage calibration using a surrogate model. Overall, including local measurement data is shown to reduce parameter uncertainty, while joint distributions of the calibrated parameters highlight important considerations in choosing constitutive models and calibration data, including challenges resulting from correlated parameters.
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All authors Joshua D. Pribe, Patrick E. Leser, Saikumar R. Yeratapally, George Weber
Materials Science · Cross-listed from physics.chem-ph
Micropatterning photopolymerizable hydrogels for diffusion studies using pillar arrays or photomasks
Sevgi Onal, Edmondo Battista, Hilal Nasir et al. (+4 more)
In situ polymerization and micropatterning of hydrogels on-chip opens the potential for many applications such as tracking and controlling the
diffusion of molecules, stimulants, inhibitors, as well as nutrients and drugs, from their source to a target. To enable such applications, we developed hydrogel-on chip platforms for molecular
diffusion studies by refining PEGDA-PEG hydrogel in terms of micropatterning and
diffusion properties. In the first platform that we introduce here, the design has multiple adjacent microfluidic channels separated with pillar arrays shaping the flow of our custom-prepared photopolymerizable hydrogels and thus enabling the localization of photopolymerization. In the second platform, a photomask formation has been achieved by coupling the micro-milling of 250-\textmu m thickness of PMMA substrate with Platinum (Pt)-coating onto the PMMA mask. In this way the design was obtained to have opaque and transparent regions for light-based polymerization of the PEGDA-PEG hydrogels. The developed method of in situ polymerization of the hydrogel on-chip through photomask has enabled direct transfer of the design of interest to the pre-hydrogel in channel. Next, the developed platforms will be further used to test various compositions of photopolymerizable hydrogels and track and control the
diffusion of molecules across hydrogel interfaces. The micropatterning methods and platforms developed here could be tailored to device design and development needs in various application fields from molecular transport to biosensing to electronic devices.
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All authors Sevgi Onal, Edmondo Battista, Hilal Nasir, Fabio Formiggini, Valentina Mollo, Raffaele Vecchione, Paolo Netti
Materials Science · Cross-listed from physics.chem-ph
Matlantis-PFP v8: Universal Machine Learning Interatomic Potential with Better Experimental Agreements via r2SCAN Functional
Chikashi Shinagawa, So Takamoto, Daiki Shintani et al. (+7 more)
Universal Machine Learning Interatomic Potentials (uMLIPs) enable atomistic simulations and high-throughput screening at scales far beyond those accessible with density functional theory (DFT). However, most existing uMLIPs are trained on Perdew–Burke–Ernzerhof (PBE) generalized gradient approximation (GGA) data and are therefore fundamentally limited by PBE-level accuracy. In this paper, we argue that better zero-shot predictions versus experiments must be an explicit design target for uMLIPs and present PFP v8, a uMLIP available on the Matlantis service that overcomes the inherent limitations of the PBE functional by being trained to reproduce the regularized-restored strongly constrained and appropriately normed (r2SCAN) meta-GGA potential-energy surface across a wide range of chemical domains. Without requiring domain-specific fine-tuning, PFP v8 delivers systematically improved agreement with experimental data or high-accuracy references for
crystals, molecules, and surfaces, outperforming PBE-based DFT calculations. Crucially, in long-time molecular dynamics simulations that are computationally impractical with DFT, PFP v8 predicts melting points with an average error of approximately 130 K, halving the error relative to PBE-trained models. These results establish that uMLIPs can move beyond the limitations of their training approximations and achieve substantially improved agreement with experiment across diverse chemical domains, further narrowing the gap between simulation and reality.
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All authors Chikashi Shinagawa, So Takamoto, Daiki Shintani, Yong-Bin Zhuang, Yuta Tsuboi, Katsuhiko Nishimra, Kohei Shinohara, Shigeru Iwase, Yuta Tanaka, Ju Li
Soft Condensed Matter
Dynamics of viscous liquids and the Random Barrier Model
Thomas B. Schrøder, Jeppe C. Dyre and Camille Scalliet
This paper combines the particle-swap Monte Carlo
algorithm with long GPU molecular dynamics simulations to analyze the dynamics of a ternary Lennard-Jones glass-forming
liquid in the extremely viscous regime. The focus is on the inherent dynamics, obtained by quenching configurations along the configuration-space trajectory into their inherent state. We compare how two functional forms, the von Schweidler law and the random barrier model (RBM) prediction in the extreme disorder limit, fit data for the inherent mean-squared displacement as a function of time. We find that the RBM, which has no dimensionless free parameters, generally fits the data better than the von Schweidler law, despite the latters one dimensionless free parameter. In particular, this implies that the RBM predicts the value of the
diffusion coefficient from short-time simulation data more accurately than does the von Schweidler expression. It remains an open question why the RBM reproduces well the inherent data despite this models (unrealistic) assumption of identical energy minima.
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Strongly Correlated Electrons · Cross-listed from hep-th
Hydrodynamics as cospans of field theories into the BF theory
Simon Jonsson and Hyungrok Kim
Hydrodynamics is based on conservation laws of currents: one starts from the conserved currents of the theory describing the microscopic dynamics, and provides an alternative parameterisation of these currents in terms of hydrodynamic variables (density, pressure, velocity, etc.). This paradigm has recently been extended to incorporate higher-form
symmetries. The conservation law of the $p$-form conserved currents can be regarded as the equations of motion of a $BF$ theory that treats the currents as fundamental fields. We argue that the hydrodynamic approximation to a microscopic theory can be regarded as a cospan of differential graded
manifolds $X_\mathrm{micro}\to X_{BF}\leftarrow X_\mathrm{hydro}$, where $X_\mathrm{micro}$ and $X_\mathrm{hydro}$ describe the microscopic and hydrodynamic theories, respectively, and $X_{BF}$ describes the $BF$ theory of conserved currents.
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Other Condensed Matter
Predictive first-principles simulations for co-designing next-generation energy-efficient AI systems
Denis Mamaluy, Md Rahatul Islam Udoy, Juan P. Mendez et al. (+3 more)
In modern generative-AI workloads,
matrix-vector/
matrix-
matrix multiplications (MatMul) dominate the compute and energy cost. Achieving dramatic reductions in energy per
token therefore requires a novel, specialized hardware that is co-designed across materials, devices, interconnects,
circuits, and architectures rather than optimized at any single layer in isolation. In this Perspectives article, we argue that predictive (first-principles, fitting-parameter-free) device and interconnect simulations can close the loop between nanoscale physics and workload-level metrics, enabling the identification of device/interconnect operating regimes that plausibly support orders-of-magnitude improvements in energy efficiency of AI accelerators.
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All authors Denis Mamaluy, Md Rahatul Islam Udoy, Juan P. Mendez, Ben Feinberg, Wei Pan, Ahmedullah Aziz
Statistical Mechanics
Rényi exponent landscape of multipartite entanglement in free-fermion systems
Aleksandrs Sokolovs
We show that the Rényi tripartite information $I_3^{(\alpha)}$ of free
fermions exhibits a qualitatively $\alpha$-dependent scaling at small
Fermi momentum, in sharp contrast to bipartite
entropy where only the prefactor changes. In the rank-1 regime ($z = k_F w \ll 1$), $I_3^{(\alpha)}$ receives contributions from two competing channels – a fractional-moment channel $\sim z^\alpha$ (active for non-integer $\alpha$) and a
polynomial channel $\sim z^m$ from the first nonvanishing inclusion-exclusion moment $\sigma_m$ – yielding the scaling exponent $\beta_m(\alpha) = \min(\alpha, m)$ for $m$-partite information of $m$ adjacent strips. Integer Rényi indices $\alpha = 2, 3, \ldots$ are anomalous: the fractional channel closes and the exponent jumps to $m$ or higher. A direct consequence is a replica obstruction: $I_m^{(n)}/I_m^{(1)} \sim z^{m-1} \to 0$ for all integer $n \geq 2$, so the leading von Neumann signal cannot be reconstructed from integer Rényi data at the level of leading scaling – a situation with no bipartite analog. Conversely, negativity-based measures ($\alpha = 1/2$) give a $20\times$ enhanced signal compared to von Neumann. We derive the underlying product formula for the coefficient $c(w_A, w_B, w_D)$, prove an $m$-partite generating function for the inclusion-exclusion moments, and verify all results numerically to high precision.
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Materials Science
3D Mapping of Intragranular Residual Strain and Microstructure in Recrystallized Iron Using Dark-Field X-ray Microscopy
Virginia Sanna, Yubin Zhang, Wolfgang Ludwig et al. (+4 more)
Grain growth is a key process in the thermomechanical treatment of metals. Recently, the presence of local residual stresses within fully recrystallized grains has attracted increasing interest in connection with shear-coupled grain boundary migration mechanisms. In this work, we provide the first direct experimental measurements of residual elastic strain variations in fully recrystallized commercial-purity iron, on the order of $10^{-4}$. Using dark-field X-ray microscopy (DFXM), we performed non-destructive three-dimensional measurements of strain and orientation variations within individual grains. Our results reveal heterogeneous strain distributions across all measured grains. In one case, we observed several isolated dislocations accommodating two second-phase particles, exhibiting a localized strain signature with no detectable long-range effect. The formation mechanisms of intragranular residual strains and their potential influence on grain boundary migration during subsequent grain growth are discussed. This work highlights the importance of accounting for such residual elastic strains in future grain growth models.
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All authors Virginia Sanna, Yubin Zhang, Wolfgang Ludwig, Aditya Shukla, Abderrahmane Benhadjira, Marilyn Sarkis, Can Yildirim
Materials Science
Ionic-instability induced color tuning in lead-based, mixed-halide perovskites
Anthony Ruth, Halyna Okrepka, Michele Vergari et al. (+5 more)
Contrary to conventional wisdom, intermediate photoluminescence energies can be stabilized in mixed-halide lead perovskites during photosegregation. These intermediate energies reside between those of the parent, mixed-halide
alloy and fully photosegregated specimens. This demonstrates rudimentary color tuning and has practical implications for potential uses of mixed-halide perovskites in lighting applications. More fundamentally, such color tuning begs the question of how intermediate photosegregation energies arise and how they are kinetically stabilized. What follows is a study of the kinetics of terminal photosegregation energies under pulsed
laser excitation. Through concerted continuous wave and pulsed
laser photosegregation measurements, we develop a kinetic rationalization for how photosegregations repetition rate or duty cycle and peak fluence dependencies lead to intermediate, terminal photoluminescence energies. The developed model, in turn, explains prior observations of pulsed illumination photosegregation and offers potential insights into other, yet to be explained, phenomena such as spectral blueshifting under high intensity, pulsed illumination.
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All authors Anthony Ruth, Halyna Okrepka, Michele Vergari, Charlie Desnoyers, Minh Nguyen, Luca Gavioli, Prashant V. Kamat, Masaru Kuno
Materials Science
Competing Hydrogenation Pathways to Metastable CaH$_6$ Revealed by Machine-Learning-Potential Molecular Dynamics
Ryuhei Sato, Peter I. C. Cooke, Maélie Caussé et al. (+7 more)
The synthesis of the high-$T_c$ superhydride CaH$_6$ has stimulated significant interest in understanding synthesis pathways for metastable hydrides. However, the microscopic mechanisms governing such hydrogenation reactions remain poorly understood. Here, we show that machine-learning potential molecular dynamics (MLP-MD) simulations can reproduce and distinguish competing reaction pathways leading to metastable and stable hydrides. By simulating hydrogenation reactions at CaH$_2$/H$_2$ and CaH$_4$/H$_2$ interfaces, we identify two distinct pathways that produce clathrate-type CaH$_6$ and A15-type CaH$_{5.75}$, respectively. CaH$_{5.75}$ lies on the convex hull but requires extensive Ca sublattice rearrangement and therefore forms only at elevated temperatures. In contrast, CaH$_6$ becomes kinetically accessible when CaH$_2$ is used as the precursor. The crystallographic compatibility between the Ca sublattice of CaH$_2$ and the bcc framework of CaH$_6$ enables a martensitic-like topotactic transformation that bypasses the reconstructive pathway leading to CaH$_{5.75}$. These results reveal how precursor structure and thermodynamic stability compete to determine superhydride formation pathways and demonstrate that machine-learning molecular dynamics can directly capture the kinetic selection of metastable phases in reactive materials systems.
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All authors Ryuhei Sato, Peter I. C. Cooke, Maélie Caussé, Hung Ba Tran, Seong Hoon Jang, Di Zhang, Hao Li, Shin-ichi Orimo, Yasushi Shibuta, Chris J. Pickard
Strongly Correlated Electrons
Proximate Spin Liquid Ground State Arising from Competing Stripy and 120$^{\circ}$ Spin Correlations in the Triangular Quantum Antiferromagnet ErMgGaO$_4$
S.H.-Y. Huang, S. Petit, Bo Yuan et al. (+13 more)
ErMgGaO$_4$ is a
quantum antiferromagnet wherein the pseudospin-1/2 degrees of freedom of Er$^{3+}$ decorate two-dimensional triangular planes separated by disordered non-
magnetic bilayers of Mg$^{2+}$ and Ga$^{3+}$. Unlike its sister compound, YbMgGaO$_4$, our powder ErMgGaO$_4$ sample shows a clear
spin glass transition near $T_g \sim 2.5$~K, about 1/6 of its Curie-Weiss temperature. We have carried out new inelastic
neutron scattering measurements on these powder ErMgGaO$_4$ samples. At high energies, we observed crystalline electric field (CEF) transitions within the $J=15/2$ multiplet of Er$^{3+}$, but with the first excited CEF level sufficiently low in energy ($\sim$ 3~meV) so as to allow the possibility that virtual CEF transitions influence the exchange couplings. At E=0, we observe diffuse elastic scattering which is analysed using Warren lineshapes appropriate for two dimensional correlations. This reveals dominant 2D stripy correlations below $T_g$, coexisting with 2D 120$^\circ$-type correlations that persist above $T_g$. At low temperatures, the low energy inelastic component of the scattering shows a continuum with bandwidth of $\sim$ 0.8~meV. This dynamic
magnetic spectral weight can be modeled at all $Q$, energies, and temperatures as the sum of high energy and low energy damped harmonic oscillators (DHO), with the high energy DHO defining the bandwidth of $\sim$ 0.8~meV. We use linear
spin wave theory to model this inelastic scattering and to estimate its
spin Hamiltonian parameters in terms of a $J_1-J_2-\Delta$ model on the triangular
lattice. This gives a good description of the low lying spectral weight for ErMgGaO4, and allows us to place it on the theoretical $J_1-J_2-\Delta$ phase diagram with $\frac{J_1}{J_2}=0.13 \pm 0.03$ and $\Delta=0.4 \pm 0.1$, which is close to the expected
quantum phase boundary between the
spin liquid and the stripy ordered phases.
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All authors S.H.-Y. Huang, S. Petit, Bo Yuan, Z. W. Cronkwright, C. Pinvidic, Y. Wang, E. M. Smith, S. Bhattacharya, C. Yang, J.-M. Zanotti, Q. Berrod, M. B. Stone, A. I. Kolesnikov, R.J. Cava, E. Kermarrec, B. D. Gaulin
Soft Condensed Matter
When velocity autocorrelations mirror force autocorrelations: Exact noise-cancellation in interacting Brownian systems
Anton Lüders, Suvendu Mandal and Thomas Franosch
Resolving the mean-squared displacement (MSD) and velocity autocorrelation function (VACF) of interacting Brownian particles remains a central challenge in simulations of soft-matter systems, especially at low densities where particle-particle interactions are sparse and signals are dominated by thermal noise. A recently proposed noise-cancellation (NC)
algorithm [Mandal et al. Phys. Rev. Lett. 123, 168001 (2019)] addresses this by decomposing particle trajectories into two components: free Brownian motion and interaction-induced displacements. The NC approximation enhances signal clarity by neglecting cross-correlations between the total particle displacements and the extracted interaction-induced contributions of the trajectories - an assumption that has so far lacked rigorous theoretical justification. In this work, we establish an exact theoretical relation between the VACF, the force autocorrelation function (FACF) characterizing the interaction-induced contributions, and these cross-correlations, which is valid for Brownian systems. We show that in thermal
equilibrium, the cross-correlations vanish for Brownian systems because the VACF is strictly proportional to the negative FACF, which establishes the NC
algorithm as an exact method. In contrast, for Brownian nonequilibrium systems, the cross-correlations remain finite, providing a direct fingerprint of nonequilibrium physics in such systems and a criterion to distinguish
equilibrium from nonequilibrium states. Here, suitable corrections must be applied for the NC method to remain accurate. Our results expand the scope of the NC
algorithm to a broad range of soft-matter systems in and out of
equilibrium, where it has the potential to strongly enhance the resolution of VACF data obtained through simulations in future studies.
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Statistical Mechanics · Cross-listed from math.DS
A Dynamical Approach to Non-Extensive Thermodynamics
Artur O. Lopes and Paulo Varandas
We develop a non-extensive thermodynamic formalism for the one-sided shift on a finite alphabet, inspired by Tsallis' generalization of Boltzmann
entropy in statistical physics. We introduce notions of $q$-
entropy, $q$-pressure, and $q$-transfer operators which extend the classical thermodynamic formalism when $q=1$. We prove a Bowen-type relation linking the $q$-pressure with a $(2-q)$-Ruelle transfer operator and show that $q$-
equilibrium states correspond to classical
equilibrium states for a related potential. We establish the existence and uniqueness of $q$-
equilibrium states for Lipschitz potentials, prove the differentiability of the $q$-pressure, and obtain variational principles for both the $q$-pressure and a related asymptotic pressure. Finally, we study cohomological equations associated with $(2-q)$-transfer operators and prove the differentiable dependence of their solutions on the potential, yielding an alternative construction of eigenfunctions for classical Ruelle operators.
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Superconductivity
Intrinsic magnetization of the superconducting condensate in Fe(Te,Se)
Mohammad Javadi Balakan, Shiva Heidari, Genda Gu et al. (+4 more)
A
spin-polarized superconducting condensate generates a net magnetization with measurable signatures. We present evidence for an intrinsic
magnetic field in mesoscopic Fe(Te,Se) rings. The intrinsic field, encoded in the phase of superconducting
quantum oscillations, scales linearly with the DC bias current, and its orientation exhibits an anomalous dependence on polarity and magnitude of the applied current. The magnetoresistance displays a dual flux-quantization effect with respect to the external
magnetic field and the DC current. A minimal model incorporating Rashba coupling with an effective anisotropic out-of-plane interaction accounts for the experimental observations. These results provide evidence for
spin-polarized superconductivity at the device scale and open new opportunities for superconducting spintronic and
quantum information platforms.
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All authors Mohammad Javadi Balakan, Shiva Heidari, Genda Gu, Qiang Li, Kenji Watanabe, Takashi Taniguchi, Ji Ung Lee
Materials Science
From Word2Vec to Transformers: Text-Derived Composition Embeddings for Filtering Combinatorial Electrocatalysts
Lei Zhang and Markus Stricker
Compositionally complex solid solution electrocatalysts span vast composition spaces, and even one materials system can contain more candidate compositions than can be measured exhaustively. Here we evaluate a label-free screening strategy that represents each composition using
embeddings derived from scientific texts and prioritizes candidates based on similarity to two property concepts. We compare a corpus-trained Word2Vec baseline with
transformer-based
embeddings, where compositions are encoded either by linear element-wise mixing or by short composition
prompts. Similarities to `concept directions', the terms conductivity and dielectric, define a 2-dimensional descriptor space, and a symmetric Pareto-front selection is used to filter candidate subsets without using electrochemical labels. Performance is assessed on 15 materials libraries including noble metal
alloys and multicomponent
oxides. In this setting, the lightweight Word2Vec baseline, which uses a simple linear combination of element
embeddings, often achieves the highest number of reductions of possible candidate compositions while staying close to the best measured performance.
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Materials Science
Machine-learning assistant DFT study of half-metallic full-Heusler alloy N2CaNa: structural, electronic, mechanical, and thermodynamics properties
E. B. Ettah, M.E. Ishaje, K. A. Minakova et al. (+2 more)
We studied the structural, electronic, mechanical, and thermodynamic properties of N2CaNa full Heusler
alloys using density functional theory (DFT). Results for the structural analysis establishes structural stability with a minimum formation energy of 29.90eV. The compounds is brittle and mechanically stable, having checked out with the Pugh criteria. B/G ratio for N2CaNa is 4.766 as computed in Tab.2, hence the material is ductile. N2CaNa
alloy is ductile in nature. Debye model correctly predicts the low temperature dependence of heat capacity, which is proportional to the debye T3 law. Just like the Einstein model, it also recovers the Dulong-Petit law at high temperatures, suggests thermodynamic stability of the compounds at moderate temperatures. The results demonstrate potential for applications in spintronics, structural engineering, and other fields requiring materials with tailored properties.
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All authors E. B. Ettah, M.E. Ishaje, K. A. Minakova, V.A. Sirenko, I. S. Bondar
Materials Science
Aligning van der Waals heterostructures using electron backscatter diffraction
R. Bangari, M. Mosayebi, J. Buchner et al. (+3 more)
Precise and accurate determination of crystallographic orientation is crucial for engineering van der Waals
heterostructures, where the twist angle between layers controls emergent electronic and optical properties. While Electron Backscatter Diffraction (EBSD) has been extensively used for bulk materials, its application to van der Waals materials remains largely unexplored. In this work, we demonstrate EBSD as a robust and versatile tool for determining crystallographic orientations of van der Waals materials with high precision. We show quantitative agreement between EBSD-determined orientations and facet orientations in orthorhombic {\alpha}-MoO3 flakes on silicon substrates. We use Grain Reference Orientation Distribution (GROD) and Kernel Average Misorientation (KAM) across the flakes to demonstrate precision better than 0.2{\deg}. We extend this technique to other low-
symmetry materials, specifically, monoclinic {\alpha}-As2Te3, monoclinic GaTe and triclinic ReSe2, demonstrating broad applicability across van der Waals materials with different
crystal structures. Finally, as a proof-of-concept application, we leverage EBSD-determined orientations to engineer twisted {\alpha}-MoO3
heterostructure with precisely controlled twist angle, enabling observation of recently reported canalized
phonon polaritons. Our results establish EBSD as a powerful characterization method for van der Waals materials, enabling precise orientation control essential for twistronics and twist-optics.
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All authors R. Bangari, M. Mosayebi, J. Buchner, J.D. Caldwell, N. Bassim, T. G. Folland
Materials Science
Uncovering the properties of homo-epitaxial GaN devices through cross-sectional infrared nanoscopy
Hossein Zandipour, Felix Kaps, Robin Buschbeck et al. (+19 more)
Validating material performance in electrical devices is crucial to product development. For Gallium Nitride (GaN) devices, evaluating material factors such as defects, dopant concentration, and overall production quality is essential to ensure their performance in advanced electronic and optoelectronic applications. This work demonstrates that scattering-type scanning near-field optical microscopy (s-SNOM) can meet the demanding performance requirements for characterizing homoepitaxial GaN devices. Specifically, we show that combining s-SNOM results in the mid-IR and terahertz (THz) spectral ranges can disentangle carrier and
lattice changes in a GaN p-i-n diode, which is not possible using one spectral range alone. We observe strong, resonant near-field signals near the LO
phonon mode of GaN that correlate well with point-dipole models. This data shows great sensitivity to the local carrier density, with changes on the order of 1018 cm-3 easily resolved experimentally. Further, we demonstrate high sensitivity to sub-surface defects, which remain a significant challenge for other non-destructive techniques. To validate the power of s-SNOM imaging, our results are compared to traditional metrologies, including micro-Raman mapping and Kelvin Probe Force Microscopy (KPFM). Our results show that s-SNOM shows superior resolution and sensitivity to perturbations, highlighting the power of this technique in
semiconductor device characterization.
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All authors Hossein Zandipour, Felix Kaps, Robin Buschbeck, Maximilian Obst, Aditha Senarath, Richarda Niemann, Niclas S. Mueller, Gonzalo Alvarez-Perez, Katja Diaz-Granados, Ryan A Kowalski, Jakob Wetzel, Raghunandan Balasubramanyam Iyer, Matthew Wortel, J. Michael Klopf, Travis Anderson, Alan Jacobs, Mona Ebrish, Lukas M. Eng, Alexander Paarman, Susanne C. Kehr, Joshua D. Caldwell, Thomas G. Folland
Materials Science
Ground-State Structure Search of Defective High-Entropy Alloys Using Machine-Learning Potentials and Monte Carlo Sampling
Siya Zhu and Raymundo Arroyave
Resolving the atomic-scale structure of defective high-
entropy alloys (HEAs) containing interstitial species remains a major computational challenge due to the vast configurational space and the limitations of existing methods. Here we introduce PAIPAI (Package for
Alloy Interstitial Predictions using Artificial Intelligence), a Monte Carlo framework coupled with machine-learning interatomic potentials (MLIPs) that searches for ground-state atomic configurations in HEAs with defects and interstitials. PAIPAI employs a dual-worker architecture-fast workers for rapid configurational screening and slow workers for high-accuracy refinement-coordinated through a shared waiting pool, enabling efficient parallel sampling. We demonstrate PAIPAI through three case studies: (i) surface segregation in a Ti-V-Cr-Re slab; (ii) interstitial oxygen and boron aggregation in bulk BCC Nb-Ti-Ta-Hf; and (iii) coupled metallic and interstitial segregation at grain boundaries in Nb-Ti-Ta-Hf. In all cases, Monte Carlo-optimized structures are significantly lower in energy than any configuration obtained by random sampling, and MLIP energy rankings are validated against density functional theory calculations. PAIPAI provides a general and efficient framework for predicting atomic ordering, segregation, and interstitial behavior in complex, defective HEA systems.
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Materials Science
Weyl-Transition-Driven Giant Reversible Orbital Hall Conductivity
Bo Zhao, Hao Wang, Wei Ren et al. (+1 more)
Orbital
Hall conductivity (OHC) is a central ingredient of orbitronics, yet how to control it microscopically remains largely unexplored. Here we identify a general mechanism in which tilted Weyl crossings formed by orbitally distinct bands generate a strongly asymmetric orbital Berry
curvature (OBC) distribution, whose imbalance survives Brillouin-zone integration and yields a sizable OHC already at zeroth order. Using first-principles calculations, we show that monolayer PtBi2 realizes this mechanism and hosts a
giant OHC dominated by a type-II Weyl point. A small biaxial tensile strain drives a type-II $\rightarrow$ type-I $\rightarrow$ type-II Weyl transition, leading to a reversible sign change of the OHC through the
evolution of the OBC imbalance. This process is governed by the
chiral orbital texture of the crossing bands and is further assisted by a strain-induced first-order structural phase transition through bonding reconstruction and polarization change. Our results establish Weyl engineering of orbital
quantum geometry as a powerful route to generating and reversibly controlling OHC in polar multi-orbital materials.
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All authors Bo Zhao, Hao Wang, Wei Ren, Hongbin Zhang
Quantum Gases
Analog Simulation of Massive Relativistic Quantum Fields in 2 + 1 Dimensions
Yansheng Zhang, Feiyang Wang, Paul H. C. Wong et al. (+8 more)
Quantum field theories provide fundamental models of complex interacting systems, from high-energy physics and cosmology to condensed matter. However, solving these models in non-perturbative and dynamical regimes is often challenging, particularly in more than one spatial dimension. Analog simulation using tunable synthetic
quantum systems can both verify existing theoretical predictions and lead to new physical insights. Here, we realize analog simulation of massive relativistic
quantum fields in $2+1$ dimensions (two spatial dimensions and time), using two coherently coupled
spin components in a uniform two-dimensional atomic Bose–Einstein condensate. Specifically, we encode the paradigmatic sine-Gordon model in the long-wavelength modes of the field describing the relative phase, $\phi$, of the two components. In the perturbative regime, collective field excitations exhibit a relativistic dispersion with a tunable mass gap. We also observe explicitly non-perturbative phenomena, including the existence of topological domain walls across which $\phi$ rapidly winds by $2\pi$. Our work opens possibilities for studies of cosmologically relevant phenomena including preheating, dynamics of topological defects, and relativistic false-
vacuum decay.
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All authors Yansheng Zhang, Feiyang Wang, Paul H. C. Wong, Alexander C. Jenkins, Yi Jiang, Konstantinos Konstantinou, Gehrig Carlse, Nishant Dogra, Joseph H. Thywissen, Christoph Eigen, Zoran Hadzibabic
Strongly Correlated Electrons · Cross-listed from hep-th
Introduction to Generalized Symmetries
Justin Kaidi
These notes were prepared for a series of intensive lectures delivered at Hokkaido University, Nagoya University, Kyoto University, and Kyushu University. We begin with a brief review of higher-form
symmetries, anomalies, and discrete gauge theories, before introducing non-invertible
symmetries in $(1+1)$-dimensional systems. The basic structure of fusion categories is then discussed, including a discussion of categorical analogs of discrete gauging and representation theory. We subsequently turn to $(3+1)$-dimensional theories, where several physical applications of non-invertible
symmetries are discussed. These notes are intended to be largely self-contained, and require no prior familiarity with subjects such as conformal field theory or
lattice models.
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Quantum Gases
Interplay of local and global quantum geometry in the stability of flat-band superfluids
Kukka-Emilia Huhtinen, Matteo Dürrnagel, Valerio Peri et al. (+1 more)
Quantum geometry strongly impacts physical properties in flat-band systems. We consider its role in bosonic condensation and superfluidity on flat bands, and show that the superfluid weight has an important contribution proportional to the condensate
quantum metric. Based on this result, we uncover conditions under which flat-band superfluidity is unlikely. For instance, we find that stable flat-band superfluidity in a two-dimensional system requires at least three bands within Bogoliubov theory. Because the
quantum geometry at the condensation momentum plays a disproportionately large role, a large integrated
quantum metric is not sufficient for flat-band superfluidity, but how the
quantum metric is distributed in the Brillouin zone is crucial.
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All authors Kukka-Emilia Huhtinen, Matteo Dürrnagel, Valerio Peri, Sebastian D. Huber