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Physics Condensed Matter Materials Science

cond-mat.mtrl-sci Watch Materials Science

Tuesday 28 July

Materials Science

Thermodynamics-Informed Machine Learning for Energy Materials Discovery

Pol Benítez, Cibrán López and Claudio Cazorla

Machine learning (ML) is transforming materials discovery by enabling rapid prediction of properties that previously required computationally expensive first-principles calculations. Yet most current ML models remain fundamentally limited to zero-temperature descriptions, learning static lattice energies while neglecting the thermodynamic effects that govern materials behaviour at finite temperature. Because phase stability, functional response, and performance are governed by free-energy landscapes rather than static energies alone, this limitation represents a major barrier to predictive materials design under realistic operating conditions. In this Perspective, we argue that developing thermodynamics-informed ML constitutes one of the most important and least explored frontiers in materials discovery. We examine the fundamental shortcomings of energy-based models, highlighting the essential roles of entropy and anharmonicity in determining free energies and materials functionality. We review emerging strategies, including machine-learned interatomic potentials and hybrid ML-statistical mechanics frameworks, while identifying key challenges related to data availability, transferability, and thermodynamic consistency. Building on these advances, we outline a roadmap for thermodynamics-informed ML centred on direct free-energy learning, entropy-aware representations, and adaptive sampling across temperature. We highlight the transformative opportunities this paradigm offers for energy materials and argue that the next generation of ML models must move beyond static energy predictions towards a thermodynamic description of materials behaviour under realistic operating conditions.
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Materials Science

Dynamic phase-field model for brittle fracture in grounded glaciers

Aarosh Dahal, Umar Khayaz, Ravindra Duddu et al. (+1 more)

Fracture and calving of glaciers are key contributors to ice-mass loss and sea-level rise, yet predictive modeling remains challenging. Fracture in grounded glaciers is driven by gravitational forces and is typically studied within the framework of quasi-static linear elastic fracture mechanics. In this work, we show that purely quasistatic brittle fracture simulations within the phase field fracture framework under fixed self-weight can become strongly overdriven after crevasse initiation, producing unphysical thickening of the diffusive crack band and diffuse damage patterns. This pathology arises because gravity drives a growing region ahead of the crack tip beyond the strength surface. To resolve this, we show that the post-nucleation propagation is fundamentally a dynamic instability rather than a quasistatic process and propose the use of dynamic formulations of fracture. We demonstrate that accounting for inertia results in sharp, localized cracks that propagate through the ice thickness. As a second objective, this paper introduces a new dynamic formulation of the phase-field fracture model of Kumar et al. (J. Mech. Phys. Solids 2018) in which elastic, inertial, and gravitational contributions are degraded consistently in fractured regions.
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All authors Aarosh Dahal, Umar Khayaz, Ravindra Duddu, Aditya Kumar

Materials Science

Influence of BaTiO_3 nanoparticles on the anisotropy of the dielectric properties of nematic liquid crystal 5CB

Juliya M. Gudenko, Oleksandr S. Pylypchuk, Victor V. Vainberg et al. (+6 more)

This work is devoted to the mechanisms of dielectric response and electric conductivity of suspensions consisting of the nematic liquid crystal 5CB with different concentrations (from 0 to 10 wt.%) of ferroelectric BaTiO_3 nanoparticles with an average size of 24 nm. We revealed that the incorporation of nanoparticles influences significantly the dielectric permittivity magnitude and anisotropy, as well as dielectric losses of the suspension. A pronounced temperature dependence of the anisotropic dielectric permittivity of the suspensions was found at lower temperatures corresponding to the mesophase state; but it is also present at higher temperatures corresponding to the isophase. The dependence of the mesophase-isophase transition temperature on the concentration of BaTiO_3 nanoparticles appeared nonmonotonic. With increasing temperature, both the capacitance and the electrical resistance of the pure liquid crystal increase, as well as it increases in the suspensions with small concentration of BaTiO_3 nanoparticles. Due to space charge accumulation in the shells of nanoparticles, larger concentrations of BaTiO_3 nanoparticles influence strongly the ionic transport by promoting the formation of ionic-electronic screening. This effect modifies the dielectric properties and conduction mechanisms of the suspension, leading to the nonmonotonic dependence of the mesophase - isophase transition temperature versus the nanoparticle concentration.
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All authors Juliya M. Gudenko, Oleksandr S. Pylypchuk, Victor V. Vainberg, Denis O. Stetsenko, Igor A. Gvozdovskyy, Serhii E. Ivanchenko, Eugene A. Eliseev, Vladimir N. Poroshin, Anna N. Morozovska

Materials Science

Isolation of spin-valley locked nodal-line fermions in $d$-wave $\mathrm{AV_2X_2O}$ altermagnets

Pritesh Srivastava, Rahul Verma and Bahadur Singh

Crystalline symmetries stabilize topological states with distinct electronic properties, while altermagnets exhibit momentum-dependent spin splitting without net magnetization. Here, we combine first-principles calculations with a minimal tight-binding model to realize $C$-paired spin-valley-locked nodal-line fermions in the $d$-wave altermagnet $\mathrm{AV_2X_2O}$ (A = Rb, Cs, or K; X = Te, Se, or S). The low-energy electronic structure hosts coexisting spin-degenerate and spin-polarized nodal lines around $C_{4z}$-paired valleys near the Fermi level. The spin-polarized nodal lines are protected by the out-of-plane mirror symmetry $\mathcal{M}_z$ and remain robust against spin-orbit coupling. The minimal model reveals their microscopic origin and establishes a general design principle for their isolation. Layer engineering and electronic correlations serve as material-specific knobs for realizing these isolated spin-valley-locked nodal lines near the Fermi level. Our results establish the $\mathrm{AV_2X_2O}$ family as a versatile platform for exploring topological spin-valley locking in $d$-wave altermagnets.
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Materials Science

Soft-mode nonlinearities away from ferroelectric phase transition

Payel Shee, Ipek Efe, Jingwen Li et al. (+3 more)

The interplay between ionic and electronic subsystems dictates the behavior of structural phase transitions in polar dielectrics, a coupling mediated by soft optical phonon modes. In incipient ferroelectrics such as SrTiO$_3$ (STO), strong local-field effects can drive the lattice into a non-perturbative regime near the phase boundary. However, disentangling the distinct contributions of local fields from those of spontaneous macroscopic polarization remains an experimental challenge. Here, we isolate these mechanisms by probing paraelectric STO deep within its symmetric phase, where macroscopic spontaneous polarization is suppressed. Linear terahertz (THz) spectroscopy reveals that the soft mode exhibits a hybrid character, predominantly driven by electronic polarizability. Utilizing two-dimensional THz spectroscopy, we map the underlying nonlinear signals, demonstrating that the system persists in a perturbative regime characterized by robust local-field coherence. By implementing a microscopic model of coupled electronic and lattice degrees of freedom mediated by local fields, we qualitatively reproduce these multidimensional coherent signatures. Our findings highlight that while local fields are necessary to initiate non-perturbative lattice dynamics, they are insufficient on their own. This reveals that spontaneous polarization plays a deterministic role in dictating soft-mode nonlinearities in strongly correlated polar dielectrics.
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All authors Payel Shee, Ipek Efe, Jingwen Li, Kshitij V. Goyal, Morgan Trassin, Shovon Pal

Materials Science

The interplay of crystal-field transitions and exchange spin dynamics in a ferrimagnet

Arpita Dutta, Pratyay Mukherjee, Ritwik Mondal et al. (+1 more)

Rare-earth iron garnets offer an ideal platform for exploring the interplay of low-energy excitations and the complex temperature-dependent magnetization dynamics. In these systems, exchange coupling between rare-earth and iron sublattices generates high-frequency collective spin excitations. In addition, the robust spin-orbit coupling of localized 4$f$ electrons triggers the crystal-electric-field (CEF) transitions at THz frequencies. Despite extensive research into the garnet spin dynamics, the interplay between CEF excitations and exchange modes has remained largely unmapped. Using temperature-dependent THz time-domain spectroscopy, we demonstrate a hybridization between the Yb-ion CEF excitation and the Yb-Fe exchange mode in Gd$_{3/2}$Yb$_{1/2}$BiFe$_{5}$O$_{12}$. This coupling is characterized by a significant redistribution of spectral and temporal weights as the material approaches its magnetization compensation temperature. Notably, the Yb-Fe exchange mode exhibits an anomalous redshift upon cooling – a reversal of the conventional blue shift typically driven by increased exchange coupling. We trace this phenomenon to a modification of Yb-Fe exchange anisotropy, driven by the interplay of the Fe exchange field and Yb CEF excitations. These findings highlight the critical role of CEF-mediated exchange coupling in shaping low-energy spin dynamics, positioning rare-earth garnets as a cornerstone for future THz spintronic technologies.
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All authors Arpita Dutta, Pratyay Mukherjee, Ritwik Mondal, Shovon Pal

Materials Science

Extracting Atomic Environments for Machine Learning Interatomic Potentials

Jared C. Stimac, Fei Zhou, Kyle Bushick et al. (+4 more)

In order to appropriately capture large-scale material features and emergent phenomena via atomistic simulations, such as Molecular Dynamics (MD), the system scale can range up to hundreds of millions of atoms. However, the force-field models that drive those simulations are generally trained with Density Functional Theory (DFT) reference data, limited to relatively small configurations on the order of 100s or 1000s of atoms. To compute DFT forces on atoms in regions of interest, for example for active-learning or on-the-fly training of interatomic potentials, one needs to extract a small set of atoms from the larger simulation box, and typically work with periodic boundary conditions for DFT. However, methods to select the shape and size of this extracted set of atoms, as well as to generate a potentially necessary passivating envelope, have not been systematically analyzed. In this work, we benchmark several techniques, including a generative diffusion-based artificial intelligence (AI) approach, for extracting atomic environments from large, bulk configurations and embedding them into smaller configurations suitable for DFT calculations with periodic boundary conditions. We test with a diverse set of material systems, which includes amorphous $\mathrm{SiO_2}$, Ta with screw dislocations, and molten C. We demonstrated a notably simple procedure, a method we refer to as deletions, yields superior performance over an array of alternative extraction methods.
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All authors Jared C. Stimac, Fei Zhou, Kyle Bushick, Bo Lei, Sebastien Hamel, Amit Samanta, Vincenzo Lordi

Materials Science

Singular geometry and eigenframe topology in local rank-2 tensor observables

I. C. J. Yap, B. Doerschel, S. Q. Jin et al. (+6 more)

Many observables are symmetric second-rank tensors, reported through magnitude-ordered principal values and axes. This chart folds tensor space: the parameters develop cusps and exchange labels where the tensor is smooth. It also hides a global effect: an arrow carried along a principal axis around a loop encircling a degeneracy can return reversed, defining a binary return parity, invariant under smooth deformations of the loop avoiding degeneracy. For tensor fields, this structure is long established, but the parameters are coordinates of the domain on which the field is defined, and the degeneracies are a feature of that particular field. Here we show that the electric field gradient (EFG) carries the same structure in a control space: a traceless observable at a single probe site, steered through its five-dimensional tensor space by symmetry-adapted strain, with the encircling loop applied rather than found. First-principles calculations reveal an isolated degeneracy with nontrivial parity in rutile TiO$_2$, point- or line-like degeneracies in SnO$_2$ depending on the control slice, and access to all five EFG components in cubic MgO. Thus, return parity becomes accessible for a local observable, and strain-tuned, orientation-resolved hyperfine spectroscopy offers a route to reconstruct it.
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All authors I. C. J. Yap, B. Doerschel, S. Q. Jin, T. T. Dang, P. M. Scott, H. C. Hofsaess, D. C. Lupascu, A. Krawczuk, J. H. Schell

Materials Science · Cross-listed from cond-mat.mes-hall

Element-Specific Visualization of Layer-Parity and Twist-Dependent Magnetism in CrSBr

Aalok Tiwari, Shubhada Patil, Ravi Kumar Bandapelli et al. (+16 more)

Van der Waals (vdW) based antiferromagnets (AFMs) are an ideal platform for probing and understanding thickness- and twist-angle-dependent emergent spin phenomena. However, element-specific nanoscale characterization of the spin structure in atomically thin vdW-based AFMs systems and layer-parity effects remain elusive, making them crucial for both fundamental insight into low-dimensional magnetism and the rational design of spintronic devices based on these materials. Here, we utilize X-ray magnetic circular and linear dichroisms paired with photoemission electron microscopy to resolve the magnetic order in atomically thin CrSBr. Our comprehensive measurements reveal CrSBr magnetic structure at the nanoscale and its dependence on the layer number, surface encapsulation, temperature, and applied field. Moreover, in the orthogonally twisted bilayer configuration, obtained by twisting two CrSBr ferromagnetic monolayers by 90$^\circ$, the magnetic easy axis fundamentally differs from the individual monolayers, unlocking a new pathway for moiré magnetism.
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All authors Aalok Tiwari, Shubhada Patil, Ravi Kumar Bandapelli, Alevtina Smekhova, Abhishek Kumar, Wenhao Liu, I-Hsuan Kao, Zhenhong Cui, Raghvendra Posti, Brandon Tran, Zixin Zhai, Priti Yadav, Sandy Adhitia Ekahana, Alexander X. Gray, Bing Lv, Vivekanand Shukla, Florian Kronast, Simranjeet Singh, Jyoti Katoch

Materials Science

Facet-Dependent Electronic Properties and Interfacial Point Defect Interactions in WS$_2$/ZnO Heterostructures

Dedi Sutarma and Peter Kratzer

Aiming at two-dimensional materials for high-efficiency optoelectronics, WS$2$/ZnO heterostructures are computationally screened for their facet-dependent electronic properties and interfacial defect thermodynamics using first-principles hybrid functional calculations. Interface comparison identifies the non-polar ($10\overline{1}0$) $m$-plane as the optimal substrate facet, maintaining a direct 2.42~eV bandgap and a robust type-I band alignment. Isolated sulfur ($\mathrm{V_S}$) and interfacial oxygen ($\mathrm{V_O}$) vacancies introduce deep non-radiative recombination centers. Conversely, zinc vacancies ($\mathrm{V{Zn}}$) act as shallow acceptors near the valence band edge, contributing to unintentional $p$-type behavior. Analysis of defect pairs reveals that neutral vacancies cluster across the van der Waals gap due to favorable binding energies. Under $n$-type conditions, defects stabilize as charged species. Although inter-layer Coulomb repulsion weakens the binding energy of $(\mathrm{V_S} - \mathrm{V_{Zn}})''''$ pairs, their formation energy drops to 2.61~eV under anion-poor conditions, making the $-4$ cluster the most thermodynamically abundant defect pair at the interface. Furthermore, native $\mathrm{V_{Zn}}$ prevents the Fermi level rise typically induced by interstitial hydrogen ($\mathrm{H_i}$), distributing donated electrons into shallow acceptor states and preserving host band edge rigidity. These findings establish a microscopic framework for substrate selection and defect engineering in 2D/3D hybrid light-emitting diodes.
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Materials Science

Accurate Prediction of the $\alpha \to \beta$ Phase Transformation Temperature in Tin via Full Anharmonic Treatment

Petr Šesták, Matous Mrovec and Martin Friák

Predicting the $\alpha \to \beta$ (grey-to-white) transition temperature in tin presents a longstanding challenge for atomistic simulations, with existing theoretical approaches over- or underestimating the experimental boundary (286 K) by up to several hundred Kelvin. In this work, we construct an Atomic Cluster Expansion (ACE) potential trained on density functional theory data to evaluate the finite-temperature free energies of both phases. Evaluated on the same potential energy surface, the quasi-harmonic approximation predicts a transformation temperature of 377 K, whereas full thermodynamic integration, which accounts for explicit vibrational anharmonicity, yields 288 K. This shift directly quantifies the explicit anharmonic free energy, which is substantial for metallic $\beta$-Sn but negligible for semiconducting $\alpha$-Sn. The anisotropic anharmonicity in $\beta$-Sn is corroborated by its excess heat capacity, temperature-driven renormalization of its vibrational spectrum, and deviations of its atomic forces and displacements from the harmonic reference. Our results demonstrate that capturing full lattice anharmonicity is essential for predicting the phase stability of tin, while the absolute transition temperature remains limited by the accuracy of the underlying 0 K energetics.
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Materials Science

Stacking Polarity-Controlled Interlayer Photocarrier Dynamics in MoSe2/MoS2 Heterostructures

Gbenga S. Agunbiade, Ting Zheng and Hui Zhao

Control of interlayer photocarrier dynamics is central to optoelectronic applications of van der Waals heterostructures, yet deterministic and spatially uniform tuning strategies remain limited. Here we show that stacking polarity provides a global control parameter for photocarrier dynamics in MoSe$_2$/MoS$_2$ heterostructures. By comparing hexagonal (2H) and rhombohedral (3R) MoS$_2$ bilayers and engineering opposite interface terminations in 3R stacking, we resolve stacking-dependent interlayer charge-transfer dynamics using ultrafast pump–probe spectroscopy. While charge transfer in the 2H heterostructure occurs faster than the experimental resolution, the 3R heterostructures show time-resolvable charge transfer that slows from $0.25$ to $0.37$~ps depending on stacking polarity. Furthermore, the interlayer exciton lifetime is tuned from $\sim$$40$ to $\sim$$170$~ps. These effects arise from stacking-induced layer polarization in 3R MoS$_2$, which modulates interfacial wavefunction overlap.
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Materials Science

Pressure-Induced Irreversible Disorder in $\beta^{\prime}$-Mn$_3$(PO$_4$)$_2$: A High-Pressure X-ray Diffraction and Density-Functional Theory Study

Ana Melissa P. Brito, Neha Bura, Pablo Botella et al. (+7 more)

The high-pressure structural behavior of $\beta^\prime$-Mn$_3$(PO$_4$)$_2$ was investigated using synchrotron X-ray diffraction up to 20 GPa combined with density-functional theory calculations. At ambient conditions, $\beta^\prime$-Mn$_3$(PO$_4$)$_2$ crystallizes in a monoclinic structure that exhibits strongly anisotropic compression. The pressure dependence of the unit-cell volume was described using a third-order Birch–Murnaghan equation of state, and the principal axes of compressibility were determined. Above 14.1 GPa, significant broadening and weakening of the diffraction peaks are attributed to the onset of irreversible pressure-induced structural disorder associated with the loss of long-range crystallographic order. The disordered state persists after decompression to ambient pressure, demonstrating the irreversible nature of the transformation. The calculations accurately reproduce the experimental compressional behavior and provide insights into the microscopic structural evolution under pressure. Compression is mainly accommodated through distortions of the Mn–O polyhedra, whereas the PO$_4$ tetrahedra behave as comparatively rigid units. Several initially penta-coordinated Mn sites progressively evolve toward octahedral coordination under compression, while selected MnO$_6$ polyhedra exhibit anomalous distortions and elastic softening preceding the onset of disorder. Elastic constant calculations further reveal that the crystalline phase becomes mechanically unstable near the experimentally observed transition pressure. The combined experimental and computational results suggest that the HP response of $\beta^\prime$-Mn$_3$(PO$_4$)$_2$ is influenced by the interplay between framework complexity, anisotropic polyhedral compressibility, and elastic instability, providing new insight into pressure-induced structural degradation in structurally complex phosphate frameworks.
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All authors Ana Melissa P. Brito, Neha Bura, Pablo Botella, Robert Oliva, Alanna Khesley L. da Costa, Fabiana V. da Motta, Mauricio R. D. Bomio, Alfonso Munoz, Joao Elias Rodrigues, Daniel Errandonea

Materials Science · Cross-listed from cond-mat.soft

Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility

Zakiya Shireen and Sujin B. Babu

Transport in crowded media is governed by the interplay of multiple physical mechanisms. Quantitatively disentangling their individual and coupled contributions remains a longstanding challenge because the evolving microstructure continuously modifies their relative influence. Here, we develop a physics-guided interpretable machine-learning framework that couples Brownian Cluster Dynamics simulations with surrogate machine-learning models and SHAP-based interpretation to quantitatively disentangle the individual and coupled effects of total volume fraction, explorer fraction, and template bond flexibility on explorer-particle transport. We demonstrate the framework using binary colloidal systems in which explorer particles diffuse through a template network formed by irreversible bonds with tunable flexibility. Structural descriptors, mean-squared displacement, intermediate scattering functions, and displacement distributions reveal that network formation localizes explorer particles through enhanced transient caging. Bond flexibility emerges as an independent regulator of post-network relaxation by promoting local bond rearrangements that facilitate the release of transiently caged particles without altering the irreversible network topology. Although crowding and composition dominate the overall transport response, quantitative attribution reveals how the relative contributions of crowding, composition, and template bond flexibility evolve as the confining environment develops. Beyond establishing bond flexibility as a distinct control parameter for relaxation in heterogeneous colloidal networks, this work provides a general physics-guided interpretable machine-learning framework for quantitatively disentangling coupled physical mechanisms in complex transport phenomena.
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Materials Science

Integrating moment tensor potentials with finite-element modeling for heat transfer prediction in FLiBe-based molten salt systems

Mikhail Polovinkin, Ksenia Abramova, Oksana Rahmanova et al. (+8 more)

Molten fluoride salts are promising heat-transfer media for advanced molten salt reactors (MSRs), where reliable thermophysical property determination is critical for component design and safety. We present an integrated multiscale framework that couples machine-learning-driven atomistic simulations with finite-element (FE) modeling to predict the heat-transfer performance of FLiBe-based salts in a linear heat exchanger. At the atomistic scale, Moment Tensor Potentials (MTPs), actively trained on ab initio data, are developed for pure FLiBe (66-34 and 74-26 LiF-BeF2 mol%), FLiBe-LaF3, and FLiBe-UF4. These potentials are used in molecular dynamics simulations to obtain temperature- and composition-dependent transport properties (density, viscosity, thermal conductivity, and isobaric heat capacity), which are mapped as inputs to a three-dimensional FE model of the experimental thermal loop. The FE model with literature transport properties reproduces the experimental heat-transfer behavior of pure FLiBe to within 10% in the laminar regime and 18% in the transitional and turbulent regimes, validating the end-to-end pipeline for this composition. The same model with MTP-MD-derived transport properties systematically overestimates the heat-transfer coefficient by 25-28%, an offset consistent with the MTP-MD biases on thermal conductivity and viscosity. Applied to the ternary systems FLiBe-LaF3 and FLiBe-UF4 over 0-5 mol%, the MTP-MD-driven FE model predicts a mean reduction in heat-transfer efficiency of 8-11% relative to pure FLiBe, with UF4 exhibiting the strongest effect. The qualitative ordering of the three systems is the more robust result; the absolute value of the 8-11% figure is contingent on the MTP accuracy. The framework is complementary to high-temperature experiments and provides a physics-based pathway for the rapid screening of MSR coolant formulations.
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All authors Mikhail Polovinkin, Ksenia Abramova, Oksana Rahmanova, Farit Valiev, Andrey Isakov, Andrey Goryachikh, Alexander Galashev, Yurii Zaikov, Dmitrii Maksimov, Alexander Shapeev, Nikita Rybin

Materials Science · Cross-listed from cond-mat.mes-hall

Quantum metric quadrupoles in elemental bismuth thin films

Rhonald Burgos Atencia, Pavlo Makushko, Gabriele Naselli et al. (+11 more)

The nonlinear transport properties of solids are deeply rooted in the quantum geometry of their electronic wavefunctions, which is encoded in the quantum geometric tensor. Its real part, known as the quantum metric, has been recently identified as a primary origin of nonlinear transport in quantum materials where time-reversal and inversion symmetries are not simultaneously present. Consequently, the influence of the quantum metric on the largest class of materials – non-magnetic and centrosymmetric systems – has remained entirely elusive. Here, we demonstrate that third-order transport in centrosymmetric materials hosting relativistic fermions is governed by quantum metric quadrupoles (QMQs). We show that these QMQs can originate from both the non-Abelian quantum geometry of bulk three-dimensional Dirac fermions and the Abelian quantum geometry of spin-orbit-coupled surface states. In stark contrast to all zero-field nonlinear transport signatures known to date, the current driven by these QMQs persists as a robust, non-vanishing observable even in highly scalable polycrystalline thin films. We experimentally validate this quantum metric footprint by measuring nonlinear transport in thin films of elemental bismuth, observing a robust, surface-dominated, and broadband third-harmonic generation that persists up to room temperature. Our findings uncover a hidden role of the quantum metric in polycrystalline systems, establishing third-order nonlinear transport as a high-precision diagnostic tool of wavefunction geometry under ambient conditions.
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All authors Rhonald Burgos Atencia, Pavlo Makushko, Gabriele Naselli, Debottam Mandal, Paul Chekhonin, Sergey Kovalev, Steffen Kober, Zhe Wang, Igor Veremchuk, Oleksiy Pashkin, Fabian Ganss, Maria Teresa Mercaldo, Denys Makarov, Carmine Ortix

Materials Science

Laser induced optical reconfiguration in Ge_Sb_Te Films with composition dependent response

M. Zhezhu, A. Vasilev, M. Sukiasyan et al. (+5 more)

Phase change Ge_Sb_Te (GST) materials exhibit pronounced optical contrast and tunability driven by structural transformations, enabling a diverse range of photonic and optoelectronic applications. GST materials undergo reversible amorphous crystalline phase transitions during which the refractive index and extinction coefficient increase significantly in the crystalline phase across a broad spectral range. However, a systematic correlation between local composition, crystalline microstructure, and broadband optical response within as deposited crystalline GST films has not been established, particularly for films spanning various compositions within a single growth process and in the absence of amorphous-crystalline transitions. Here, we report a systematic study of composition resolved optostructural property relationships in as-deposited crystalline GST films spanning Ge3Sb2Te6, Ge2Sb2Te5, and GeSb2Te4 within a single CVD process, avoiding intermediate phase transitions. This enables direct correlations between composition, microstructure, morphology, and broadband optical response across 400-1700 nm. Specifically, the compositional gradient results in a shift of the absorption minimum from 815.9 nm to 889.8 nm, accompanied by a 5.9 fold change in the intensity, reflecting the strong dependence of optical behavior on composition and microstructure. We further show that femtosecond laser irradiation enables spatially selective tuning of the optical response. These findings establish crystalline GST films as a platform for broadband-tunable, spatially programmable photonic elements, controllable through both compositional design and localized laser processing.
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All authors M. Zhezhu, A. Vasilev, M. Sukiasyan, A. Kutuzyan, N. Anosov, M. Yaprintsev, D. A. Ghazaryan, H. Gharagulyan

Materials Science · Cross-listed from cond-mat.mes-hall

First-Principles Wannier Representation of Proximity Effects

Yaroslav Zhumagulov, Johan Félisaz, Stepan S. Tsirkin et al. (+2 more)

Proximity effects in layered heterostructures are usually represented by static parameters fitted to first-principles bands, which discards the energy dependence of the virtual hybridization, the momentum transfer, and the spatial structure. We overcome this limitation by deriving a dynamical proximity operator $\mathcal{V}(\mathbf{k},\mathbf{k}';\omega)$ directly from density functional theory, downfolding the Kohn-Sham Hamiltonian of the heterostructure onto a fixed low-energy target Wannier subspace and reproducing its spectrum exactly within that subspace. The construction separates direct matrix elements from virtual hybridization through all remaining states. In graphene on hBN/Co(0001), virtual hybridization generates more than $99\%$ of the proximity exchange and gives it a resonant frequency dependence set by the Co $d$ states. In graphene/PtSe$_2$ it resolves a sublattice-selective intervalley coupling with a $\sqrt{3}\times\sqrt{3}$ charge modulation, and in graphene/WSe$_2$ a bond-resolved Rashba coupling of $0.24$~meV, against below $1$~$\mu$eV for the direct projection alone. Our results expose the limitations of static projections and establish a fitting-free microscopic foundation for low-energy modeling, spin-relaxation theory, and transport calculations.
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All authors Yaroslav Zhumagulov, Johan Félisaz, Stepan S. Tsirkin, Denis Kochan, Oleg V. Yazyev

Materials Science

Transformer Atomic Cluster Expansion: TRACE

Paramvir Ahlawat

Designing machine-learning interatomic potentials involves achieving the precise representation of complex many-body interactions alongside the efficiency required for scalable molecular dynamics. We introduce Transformer Atomic Cluster Expansion (TRACE), an energy-conserving architecture that combines atomic cluster expansion density correlations with local multihead cross-attention. The correlations form an O(3)-equivariant state for each center, which queries tensorial neighbor features that remain fixed functions of species and geometry. No learned state is passed between atoms. On a laptop MacBook-M1, we train and test TRACE for polymorphic cesium lead iodide, liquid water, and intramolecular methyl migration against experiments. For cesium lead iodide, TRACE reproduces the r$^2$SCAN+rVV10 ordering of four polymorphs and gives a classical edge-sharing hexagonal non-perovskite($\delta$) to corner-sharing cubic perovskite($\alpha$) Gibbs-free-energy crossing $\simeq$580K near the experimental observations of $\simeq$600K. By employing enhanced sampling to cross high energy barriers, the same TRACE potential successfully captures the $\delta$-to-$\alpha$ perovskite transformation without any reinforcement learning. A water potential trained on a reduced set of CCSD(T) configurations places the first oxygen–oxygen maximum at 2.85~Å, compared to the experimental value of 2.80~Å. For the gas-phase methyl migration in 2,2-dimethylisoindene, umbrella sampling yields an activation free energy of $27.92\pm0.03$~kcal~mol$^{-1}$, in close agreement with the experimental measurement of $29.2\pm1.1$~kcal~mol$^{-1}$. Across these diverse benchmarks, a single unified architecture successfully captures multi-species crystallization, liquid structures, phase diagrams, and chemical reactivity.
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Materials Science

Ferroelectricity and antiferroelectricity in the BaS-PbS system with the rocksalt structure

Alexander I. Lebedev

The ferroelectric instability in superstructures, superlattices, quantum wires, and disordered solid solutions in the BaS–PbS system with the NaCl structure has been discovered and investigated using first-principles calculations within the density functional theory. The emergence of ferroelectricity in these structures is associated with the instability of TO phonons in linear –Pb–S–Pb–S– chains, which arises as a result of stretching of the structures upon the introduction of large barium atoms. Additionally, it has been discovered that, alongside ferroelectric phases, the structures also exhibit stable, competing antiferroelectric phases and those with a mixed ferroelectric–antiferroelectric ordering (ferroelectrically polarized one-dimensional Pb–S chains arranged in an ordered or disordered manner in the perpendicular direction). These phases often become the ground state of the studied systems. The closeness of the energies of the ferroelectric, antiferroelectric, and mixed states indicates the emergence of a multi-minimum potential with an infinite number of wells separated by potential barriers in the configuration space. This suggests a possible emergence of nonergodicity in the structures at low temperatures.
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Materials Science · Cross-listed from cond-mat.mes-hall

Anisotropic domain wall velocity profiles in the creep regime: the interplay of chiral damping, stiffness and Dzyaloshinskii-Moriya interaction

Adriano Di Pietro, Alessandro Magni, Stefania Pizzini et al. (+11 more)

The asymmetric expansion of magnetic bubble domains in ultrathin ferromagnets provides a powerful route to probe the interfacial Dzyaloshinskii-Moriya interaction (DMI). While conventional analyses rely on domain wall velocities measured along selected directions as a function of in-plane field, recent approaches have highlighted the additional insight contained in the angular dependence of the velocity, $v(\theta)$. Here, we develop an extended angular creep model that incorporates both the dispersive domain wall stiffness and a chirality-dependent prefactor associated with chiral damping. This generalization captures the full anisotropic dynamics of domain wall motion around a bubble domain. We show that these contributions significantly modify the angular velocity profile and can lead to features not accessible within existing models. Our results establish a more complete framework for interpreting creep-driven domain expansion and provide improved sensitivity for the quantitative extraction of DMI and chiral dynamical effects.
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All authors Adriano Di Pietro, Alessandro Magni, Stefania Pizzini, Frowin Dörr, Yasser Shokr, Gianfranco Durin, Silvia Tacchi, Marco Madami, Giovanni Carlotti, Emily Darwin, Alexandra J. Huxtable, Christopher H. Marrows, Bryan J. Hickey, Michaela Kuepferling

Materials Science

Imaging the Néel Vector in Two-Dimensional Antiferromagnets using Antisymmetric Compton Scattering

Wuxuan Li, Zhuocheng Lu, Jingshan Qi et al. (+2 more)

We demonstrate that antisymmetric Compton scattering can detect both the switching and the continuous rotation of the Néel vector in two-dimensional (2D) antiferromagnets. By probing magnetoelectric (ME) multipoles, which couple electric and magnetic dipoles, this approach overcomes the limitations of conventional techniques that rely on a finite net magnetization. Using a group-theoretical decomposition of the staggered moments in 2D MnPS$_3$ into irreducible representations, combined with first-principles calculations, we show that the antisymmetric Compton profile (ACP) is highly sensitive to the Néel vector orientation: it reverses sign under Néel vector reversal and exhibits distinct anisotropies under in-plane rotation. These results establish the ACP as a versatile probe of antiferromagnetic (AFM) order and magnetoelectric phenomena in van der Waals materials.
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All authors Wuxuan Li, Zhuocheng Lu, Jingshan Qi, Hua Wang, Kai Chang

Materials Science · Cross-listed from cond-mat.mes-hall

Everything is a Spin: The Secret Lives of SU(2)

Avik W Ghosh

Spin, pseudospin, valley, polarization, and other two-component degrees of freedom share the geometry of SU(2), yet their topological manifestations are usually discussed as separate phenomena. This review develops a common geometric language for their winding in momentum and real space,beginning with Berry phase and the Dirac Hamiltonian and extending to graphene, topological insulators, Weyl semimetals, and magnetic skyrmions. We argue that the common thread is not merely topology itself, but the continuity constraints imposed on two-component wavefunctions. Whenever the relevant symmetry is preserved, winding determines which states can continuously connect across an interface or deformation, thereby governing transmission, torque generation, optical selection rules, and other physical responses. We then ask a practical question: what does topology buy an engineer? In skyrmions, winding partitions magnetic configuration space and stabilizes ultrasmall information carriers with tunable dynamics. In graphene, pseudospin matching governs Klein tunneling, enabling a gate-controlled transmission gap without sacrificing the massless Dirac dispersion. In topological insulators and Weyl semimetals, spin-momentum locking and Berry-curvature engineering generate electrically selectable spin currents, while helicity-dependent optical transitions produce circular photogalvanic responses. Together, these examples suggest that topology is not merely a classification of quantum matter, but a design language in which symmetry-protected wavefunction continuity can be engineered for memory, switching, actuation, and sensing.
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Materials Science

A Catalogue of Topological Moiré Bands in Twisted Semiconductors

Jiaheng Li, Yan Zhang, Jiaxuan Liu et al. (+5 more)

Twisted two-dimensional semiconductors provide a route to flat and topological moiré minibands, but systematic principles for organizing their material dependence have remained unclear. Here, we establish a high-throughput framework that integrates structural relaxation, first-principles electronic structure calculations, and moiré band topology. We apply this framework to 43 experimentally realized monolayers and 91 symmetry-inequivalent bilayer prototypes, yielding over 1,000 angle-resolved moiré electronic band structures. This database reveals that the low-energy moiré electronic structure is organized primarily by the valley character of the parent band edge together with stacking symmetry. In $\Gamma$-valley systems, the miniband width usually follows a nearly quadratic twist-angle scaling, consistent with a folding-dominated kinetic-energy scale. In $K$-valley systems, stacking-controlled interlayer hybridization governs whether parent Berry curvature is redistributed into isolated valley Chern minibands. By contrast, $M$-valley systems form a more material-specific class associated with anisotropic and symmetry-constrained band folding. The same valley-and-stacking hierarchy rationalizes the emergence or suppression of $\mathbb{Z}_2$ minibands, and surface termination in Janus bilayers provides a microscopic knob for changing the relevant valley character. These results establish a materials-level organizing principle for designing flat and topological moiré bands in twisted semiconductors.
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All authors Jiaheng Li, Yan Zhang, Jiaxuan Liu, Caiyuan Ye, Tiannian Zhu, Zhong Fang, Hongming Weng, Quansheng Wu

Monday 27 July

Materials Science

Identifying Contact Barrier Types in Few-Layer MoS2 Devices Using Correlative IV, LBIC, and Bias-Dependent KPFM

Ariane Ufer, Zeinab Eftekhari, Benjamin Mayer et al. (+4 more)

Electrical contacts between metals and two-dimensional (2D) semiconductors such as molybdenum disulfide (MoS2) critically govern device performance, yet their microscopic nature remains difficult to disentangle using any single characterization technique. Here we present an integrated experimental framework that combines current-voltage (IV) characterization, laser beam induced current (LBIC) mapping, and bias-dependent Kelvin probe force microscopy (KPFM) to comprehensively resolve the contact properties of few-layer MoS2-based two-terminal devices under ambient conditions. IV measurements deliver macroscopic transport characteristics as a function of bias voltage and illumination conditions. LBIC maps the local photocurrent response with micrometer spatial resolution, revealing the position and nature of internal electric fields at MoS2-metal interfaces. KPFM, operated under an applied static bias rather than in the conventional work-function mode, provides nanoscale-resolved potential distributions that quantify the relative magnitudes and spatial locations of contact barriers. We apply this framework to three representative devices - one exhibiting ohmic-like and two exhibiting diode-like contact behavior - and demonstrate that the combined analysis can unambiguously identify whether the dominant barrier is of Schottky or tunnel type and determine the asymmetry between the two contacts. We further demonstrate that thermal annealing significantly reduces the total resistance, while contact barriers remain the dominant source of resistance. The methodology is directly transferable to other 2D semiconductor-metal systems and provides a practical yet comprehensive route toward a quantitative microscopic understanding of 2D device contacts.
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All authors Ariane Ufer, Zeinab Eftekhari, Benjamin Mayer, Hendrik Lambers, Hubert J. Krenner, Rebecca Saive, Ursula Wurstbauer

Materials Science

First-Principles Origins of Charge Transport in Molecular Semiconductors

Tong Jiang and Joonho Lee

Charge transport governs organic transistors and photovoltaics, yet predicting it from atomic structure remains challenging. Electron–phonon interactions span disparate frequencies, strengths and spatial ranges, and collectively generate nonperturbative carrier dynamics. Existing methods regain tractability only by assuming a mechanism or reducing electron–phonon coupling to a few modes. We introduce a parameter-free framework that instead computes transport from ab initio electron–phonon Hamiltonians, propagating carriers across hundreds-of-molecule domains with the full phonon spectrum and letting transport regimes and bottlenecks emerge from nonperturbative Green–Kubo dynamics. Across five representative crystals, it captures measured mobilities, temperature exponents, and optical-conductivity fingerprints. Our results overturn the prevailing microscopic mechanism for DNTT, tracing its transient localization to correlated on-site disorder from acoustic phonons rather than independent hopping fluctuations. The resulting two-axis transport map provides design principles and highlights the underexplored phenacene family, exemplified by the high-mobility picene, as a promising direction.
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Materials Science

Citrine Informatics: Chemical & Materials Development Platform

Maxwell C. Venetos, Steven J. Brown, Kenneth Kroenlein et al. (+6 more)

Today the Citrine Platform regularly powers data-driven materials discovery across industries, having moved beyond one-off demonstrations into routine industrial practice. Getting there required solving a core set of recurring obstacles: experimental data are scarce, costly, and published in formats that resist reuse; conventional accuracy metrics overstate model performance under the extrapolative conditions that define discovery; and realistic design spaces are bounded by physics, manufacturability, supply, and cost. Developed over more than a decade as an integrated response to these obstacles, the Citrine Platform is organized as four cooperating stages within a closed sequential learning loop. Stage 1 ingests and featurizes data through the Graphical Expression of Materials Data (GEMD) model, which treats process history, measurement uncertainty, and provenance as first-class features. Stage 2 builds machine learning models with well-calibrated uncertainty, including multivariate prediction intervals for correlated objectives, and validates them with extrapolative cross-validation and dynamic discovery metrics rather than random held-out splits. Stage 3 encodes compositional, physical, processing, and economic constraints directly into the design space, and Stage 4 applies the FUELS sequential learning framework with uncertainty-aware acquisition functions to navigate large constrained spaces under tight evaluation budgets. Published case studies spanning organic semiconductors, autonomous nanoparticle synthesis, and benchmark optimization tasks demonstrate two- to nine-fold reductions in experimental effort relative to random search, illustrating a stack in which data, modeling, and design-space layers continuously co-evolve.
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All authors Maxwell C. Venetos, Steven J. Brown, Kenneth Kroenlein, Steven K. Kauwe, James E. Saal, Marco Musto, Matthew D. Gerboth, Kyle D. Miller, Gregory J. Mulholland

Materials Science

Machine-Learning Potentials for sodium-potassium chloride mixtures: Predicting thermophysical properties and phase behavior of multicomponent salts

Karim Zongo, Hao Sun, Zijian Meng et al. (+3 more)

Predicting the properties of multicomponent molten salts using density functional theory (DFT) remains challenging because the spatial and temporal scales required to evaluate transport properties and phase behavior are computationally prohibitive. In this work, we develop a moment tensor potential trained using a a DFT dataset of NaCl, KCl, NaCl-KCl mixtures, and the NaK alloy, enabling large-scale molecular dynamics simulations across wide ranges of temperatures and compositions. We systematically evaluate the effect of D3 dispersion corrections and apply the resulting potential to predict liquid densities, diffusion coefficients, radial distribution functions, heat capacities, thermal conductivities, and the NaCl-KCl phase diagram. The model successfully reproduces many temperature- and composition-dependent trends. However, systematic deviations in several absolute properties persist, highlighting the importance of experimental validation and calibration. These findings support a hybrid modeling framework in which first-principles-informed machine-learning potentials provide transferable predictive capability and mechanistic insight, while experimental data incorporated during model development or subsequent engineering assessments is necessary to improve quantitative accuracy.
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All authors Karim Zongo, Hao Sun, Zijian Meng, Christopher Maxwell, Edmanuel Torres, Laurent Karim Béland

Materials Science

MANDALA: An E(3)-Equivariant Graph Neural Network Framework for Learning Electronic-Structure Operators with Observable Guidance

Bartosz Brzoza, Wiktoria Szopa, Zakaria Elabid et al. (+5 more)

Electronic-structure calculations based on Kohn-Sham density functional theory remain indispensable in computational materials science and chemistry. Their computational cost, however, limits accessible system sizes and simulation times. At the same time, conventional machine-learning interatomic potentials (MLIPs), which are becoming the workhorse of large-scale materials modeling, usually target only energies and forces. They therefore leave out the quantum-operator-level information required to reconstruct band structures, densities of states, spatial charge distributions, and other electronic observables. Mandala fills this methodological gap. It is a modular software framework for learning block-sparse electronic-structure matrices with E(3)-equivariant graph neural networks. The framework is built around a unified representation of atom-resolved Hamiltonian, overlap, and density matrices, together with reusable abstractions for basis conversion, sparse block handling, irreducible representation mapping, graph construction, model definition, and training. This design allows Mandala to support heterogeneous chemical compositions, a wide range of neural architecture variants within one workflow, and multiple electronic-structure backends. Mandala evaluates selected observables directly from the predicted operators, including band energy, electron count, density of states, and band structure. This connects electronic-structure learning and observable-guided modeling while retaining a representation tied to quantum-mechanical operators rather than only scalar or vector targets as in MLIPs. In this form, Mandala is intended to complement atomistic interatomic potential workflows by resolving electronic structure and operator-derived observables within one scalable implementation.
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All authors Bartosz Brzoza, Wiktoria Szopa, Zakaria Elabid, Vincent Martinetto, Varadarajan Rengaraj, Mani Lokamani, Thomas D. Kühne, Attila Cangi

Materials Science

Organizing Principles for Moiré Quantum Matter

Qiaoling Xu, Yifan Gao, Tao Zhang et al. (+16 more)

Moiré flat bands in van der Waals bilayers are usually discussed through a small set of mechanisms associated with the $\Gamma$ and $K$ valleys of hexagonal crystals, and more recently with $M$-valleys systems. Here we show that this view is incomplete. The momentum-space location and effective local orbital character of the monolayer's band edge, in conjunction with the moiré symmetry and the symmetry representations of the resulting bands, provide a general set of organizing variables for the emergent low-energy moiré Hamiltonian. Applying fully relaxed first-principles calculations, band unfolding and symmetry-representation analysis to more than 600 commensurate twisted bilayers spanning all 2D lattice classes, we identify several routes to moiré quantum matter beyond the conventional single-orbital paradigm. The resulting flat bands realize trigonal, honeycomb, square, checkerboard and kagome-like Hubbard models with single-orbital, multi-orbital and multi-site Hilbert spaces; spin-orbit-coupled multi-orbital flat bands exhibit symmetry-indicated topology beyond the conventional $K$-valley setting; and nonsymmorphic moiré symmetries enforce semimetallic flat-band connectivity. Analogous quasi-one-dimensional flat-band structures are found in $M$-valley hexagonal systems and $X$-valley square or rectangular systems resulting from emergent momentum-space nonsymmorphic symmetries. Separately, coupled multi-valley manifolds with kagome-like connectivity are identified in several systems whose parent band edges lie at non-high-symmetry points. These results establish a valley-orbital-symmetry framework for connecting parent-material electronic structure to emergent moiré Hamiltonians relevant to correlated, topological and symmetry-enforced moiré phases.
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All authors Qiaoling Xu, Yifan Gao, Tao Zhang, Ammon Fischer, Yi Jiang, Hanqi Pi, Zike Fan, Dongdong An, Kun Zhou, Yingjian Li, Yongqing Li, Yuhao Fu, Lei Wang, Lijun Zhang, B. Andrei Bernevig, Dante M. Kennes, Enge Wang, Angel Rubio, Lede Xian