Materials Science · Cross-listed from physics.app-ph
Machine learning-enabled inverse design of bimaterial thermoelastic lattice metamaterials
Xiang-Long Peng and Bai-Xiang Xu
The thermoelastic metamaterial based on a bimaterial hybrid-honeycomb structure, exhibiting simultaneously negative Poisson's ratios and negative thermal expansion coefficients is very promising for various application. This work is dedicated to the machine learning (ML)-enabled inverse design of such structure, on the basis of high-throughput simulation and neural network models. A large
dataset is generated through computational homogenization of structures with varying geometrical features and base material properties. A forward ML model is first trained to efficiently and accurately predict the effective thermoelastic properties for a given structure design. Subsequently, inverse ML models are developed to suggest geometrical features and base materials for desired target properties. To address various inverse design scenarios, six different models are proposed, each defined by different combinations of target effective properties and structural design variables. The trained forward model is integrated into the loss functions of the inverse models and is also employed to generate additional
datasets for cases with fixed base materials. The good predictive performance of the forward and inverse ML models is demonstrated by representative design examples. These ML models can be applied to efficiently solving specific inverse design tasks involved in the practical application of the thermoelastic metamaterial in novel engineering systems.
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Materials Science · Cross-listed from physics.optics
Graded anisotropic metamaterials for elastic wave mode conversion
Jagannadh Boddapati, Jihoon Ahn, Alexander C Ogren et al. (+1 more)
Efficient transmission of elastic waves across interfaces is central to several applications, including medical imaging, seismic isolation, and transducer design. Interfaces with abrupt changes in the material properties significantly impede wave transmission, leading to reflections. This limitation, known as impedance mismatch, becomes even more prominent for mode conversion between different wave types due to polarization mismatch. In this study, we investigate a mechanism employing two-dimensional functionally graded anisotropic metamaterials to facilitate longitudinal–shear mode conversion as waves propagate from a stiff to a compliant medium. By
embedding density and anisotropic shape gradients within the functionally graded metamaterial, polarization-induced impedance mismatch is mitigated and efficient mode conversion is enabled. We use unit
cell dispersion analysis to tailor the frequency range for mode conversion through gradation in the dispersion behavior and coupling between modes. Using frequency-domain finite element analysis, we demonstrate broadband mode conversion across interfaces with large stiffness contrast operating in the 1–10 kHz range. We then experimentally validate and quantify mode conversion through full-field velocity measurements on an additively manufactured specimen. We further apply the methodology to design a device capable of converting radial–tangential wave modes.
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All authors Jagannadh Boddapati, Jihoon Ahn, Alexander C Ogren, Chiara Daraio
Materials Science · Cross-listed from cond-mat.soft
Velocity Weakening in Anisotropic Friction on a Tilted Titania Nanorod Forest
Debottam Datta, Enrico Gnecco, J. P. Singh et al. (+1 more)
In this study, we demonstrate velocity-dependent directional friction on a surface structured with tilted (~57{\deg}) titania nanorods using standard and colloidal probe force microscopy. Friction is measured at four different sliding speeds in two configurations, along and opposite to the tilt and perpendicular to the tilt direction, exhibiting anisotropic friction. Furthermore, friction decreases logarithmically with increasing sliding speed, which is attributed to the viscoelastic bending of the nanorods caused by stress-induced defect migration. The velocity weakening is more pronounced in the direction perpendicular to the tilt than along and opposite to it. The experimental findings are corroborated by creep measurements, which are well-reproduced by the Standard Linear Solid (SLS) model of viscoelasticity. Our results may be applied to the development of direction- and velocity-dependent sensors for microscale sliding motion as a robust alternative to structured interfaces based on polymeric materials.
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All authors Debottam Datta, Enrico Gnecco, J. P. Singh, Nitya Nand Gosvami
Materials Science
Re-evaluating photoluminescent defects in Cu$_2$O
Alistair Brewin, Matthew P A Jones and Stewart J Clark
Defects in cuprous
oxide (Cu$_2$O) strongly influence its performance in applications ranging from photovoltaics to emerging
quantum technologies based on Rydberg
excitons where microscopic
crystal purity is essential. Photoluminescence (PL) spectroscopy is widely used as a diagnostic of material quality yet the origins of the sub-band-gap PL lines remain controversial despite decades of study. Using density functional theory we systematically evaluate native point defects in Cu$_2$O and identify which produce robust electronic states within the band gap. By combining supercell-size convergence criteria and cross-functional consistency checks we show that the widely accepted assignments of the 1.35\,eV, 1.5\,eV, and 1.7\,eV PL lines to copper and oxygen vacancies are unsupported. Instead we find that oxygen interstitials, copper interstitials and one form of split copper vacancy are the only native defects that consistently introduce true in-gap states. These results provide a revised framework for interpreting PL spectra and offer a more reliable basis for diagnosing
crystal quality in Cu$_2$O-based
quantum-device platforms.
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Materials Science
A variational critical-state theory of friction
Mary Agajanian, Nadia Lapusta, Anna Pandolfi et al. (+1 more)
Friction plays a fundamental role in many natural processes, including earthquakes, landslides, and volcanic eruptions. Earthquakes occur when highly compressed fault surfaces accumulate large enough shear stresses, causing the faults to move relative to one another, or slip. The slip is accommodated within a thin layer of comminuted granular material – called fault gouge – between the fault surfaces. As a result, characterizing the mechanical behavior of fault gouge in response to shear is a major open problem in earthquake source physics. Modeling gouge is complicated by large deformations, inelasticity, rate dependence, and volumetric changes. As such, researchers typically rely on empirical formulations to capture the effective response. Here, we systematically develop a variational, finite-kinematics framework for fault gouge. We first describe a general theory for a rigid-viscoplastic, pressure-sensitive material, where the plasticity
evolution follows from the principle of maximum dissipation. Then, we specialize the governing equations for a Cam-Clay material within a shearing and dilating layer. We rely on convexity considerations and experimental observations from consolidation tests of granular layers to calibrate the model and develop explicit solutions for the rate- and state- dependent response of the model to shear tests under constant compressive normal stress and prescribed shearing rate. To validate the model, we select common rate functions and compare numerical material point tests and theoretical solutions to standard laboratory experiments of shearing granular layers. Lastly, we discuss connections of the model to empirical rate-and-state friction laws.
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All authors Mary Agajanian, Nadia Lapusta, Anna Pandolfi, Michael Ortiz
Materials Science
A Transformer-based Model for Rapid Microstructure Inference from Four-Dimensional Scanning Transmission Electron Microscopy Data
Kwanghwi Je, Ellis R. Kennedy, Sungin Kim et al. (+2 more)
Properties of crystalline materials are closely linked to microstructure arising from the spatial arrangement, orientation, and phase of nanocrystals. Rapid characterization of crystalline microstructure can accelerate the identification of these links and the development of materials with desired properties. Here, we combine a machine learning framework with four-dimensional scanning transmission electron microscopy (4D-STEM) to enable fast inference of crystalline microstructure over large fields of view. The framework employs a
transformer-based architecture to predict crystallographic orientations and phases from 4D-STEM diffraction patterns, yielding spatially resolved maps of microstructural features at the nanoscale. With this framework, crystallographic orientations are inferred up to two orders of magnitude faster than widely used correlative template-matching approaches. This capability enables high-throughput characterization of complex crystalline materials and facilitates the establishment of structure-property relationships central to materials design and optimization.
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All authors Kwanghwi Je, Ellis R. Kennedy, Sungin Kim, Yao Yang, Erik H. Thiede
Materials Science
Fan Yang, Rafael M. Fernandes and Turan Birol
Spin-orbit coupling (SOC) leads to splitting of otherwise
spin-degenerate bands in noncentrosymmetric materials, even if time-reversal
symmetry is present. While this gives rise to well-known phenomena such as the Rashba and Dresselhaus effects, various other terms are allowed based on the point group of the
crystal and the electronic
Hamiltonian. In this study, we utilize point group representations to illustrate that four different types of SOC terms (Rashba, Dresselhaus, Weyl, and Ising) can emerge in periodic solids. We construct reciprocal-space energy expressions for each type of SOC-induced splitting of opposite-
spin bands, and follow a similar procedure to also obtain minimal tight-binding models that capture all types of
spin-splittings for subgroups of two high-
symmetry groups $m\bar{3}m$ and $6/mmm$. Furthermore, we also obtain a complete list of nodal features in the electronic band structure in these systems, distinguishing between crystallographic-
symmetry-imposed nodal lines and those imposed by time-reversal-
symmetry only. Finally, we conclude by presenting a list of materials that host each type of inversion-breaking SOC effects. Our classification of the
spin-splitting
symmetries in non-
magnetic systems with SOC is the counterpart of the recent classification of
spin-splitting
symmetries in unconventional
magnetic systems without SOC, such as altermagnets and odd-parity magnets. More broadly, our work provides a basis for studying superconductivity and other collective electronic phenomena that are impacted by SOC-induced band splittings in noncentrosymmetric materials.
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Materials Science · Cross-listed from physics.chem-ph
Fast Generation of Pipek-Mezey Wannier Functions via the Co-Iterative Augmented Hessian Method
Gengzhi Yang and Hong-Zhou Ye
We report a $k$-point extension of the second-order co-iterative augmented Hessian (CIAH)
algorithm, termed $k$-CIAH, for Pipek-Mezey (PM) localization of Wannier functions (WFs). By exploiting an efficient evaluation of the Hessian-vector product, $k$-CIAH achieves $O(N_k^2 n^3)$ scaling in both CPU time and
memory, matching that of previously reported first-order $k$-space approaches while improving upon the $O(N_k^3 n^3)$ scaling of $\Gamma$-point CIAH, where $N_k$ denotes the number of $k$-points sampling the first Brillouin zone and $n$ characterizes the unit-
cell size.
Benchmark calculations on a diverse set of solids – including
insulators,
semiconductors, metals, and surfaces – demonstrate the fast and robust convergence of $k$-CIAH-based PMWF optimization, which yields an overall computational efficiency approximately 2-3–fold higher than first-order $k$-space methods and orders of magnitude higher than $\Gamma$-point CIAH for localizing 1000-5000 orbitals. The quality of the resulting PMWFs is further validated by accurate electronic band structures obtained via PMWF-based Wannier interpolation.
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Materials Science
Investigating the Electronic and Magnetic Properties of Na$_x$Fe$_{1/2}$Mn$_{1/2}$O$_2$ Cathode Materials with X-ray Compton Scattering
Veenavee Nipunika Kothalawala, Kosuke Suzuki, Johannes Nokelainen et al. (+21 more)
We discuss electronic and
magnetic properties of Na$_x$Fe$_{1/2}$Mn$_{1/2}$O$_2$, a promising Na-ion battery cathode material. Using x-ray Compton scattering, SQUID magnetometry, and density-functional-theory based modeling, we probe how electrons and
spins evolve during sodiation. By comparing Compton profiles of sodiated and desodiated samples, we show that oxygen 2$p$ orbitals drive the redox process, while transition-metal 3$d$ electrons become more delocalized, explaining the metallic phase at $x=2/3$. These profile differences define a quantitative descriptor for the sodiation range associated with improved conductivity. Electron holes on oxygen, reflected in oxygen magnetization, confirm the important role of oxygen in the electrochemical activity of the cathode.
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All authors Veenavee Nipunika Kothalawala, Kosuke Suzuki, Johannes Nokelainen, Ilja Makkonen, Erica West, Lassi Roininen, Jere Leinonen, Pekka Tynjälä, Petteri Laine, Juho Välikangas, Ulla Lassi, Assa Aravindh Sasikala Devi, Matti Alatalo, Yuki Mizuno, Naruki Tsuji, Hikaru Usami, Yuju Nagasaki, Tsuyoshi Takami, Yoshiharu Sakurai, Hiroshi Sakurai, Mohammad Babar, Venkat Vishwanathan, Arun Bansil, Bernardo Barbiellini
Materials Science · Cross-listed from physics.optics
Vision Transformer for Multi-Domain Phase Retrieval in Coherent Diffraction Imaging
Jialun Liu, David Yang and Ian Robinson
Bragg coherent diffraction imaging (BCDI) phase
retrieval becomes rapidly difficult in the strong-phase regime, where a
crystal contains distortions beyond half a
lattice spacing. An important special case is the phase domain problem, where blocks of a
crystal are displaced with sharp jumps at domain walls. The strong-phase, here defined as beyond $\pm \pi/2$, generates split Bragg peaks and dense fringe structure for which classical iterative solvers often stagnate or return different solutions from different initialisations. Here, we introduce an unsupervised
Fourier Vision Transformer (
Fourier ViT) to solve this block-phase, multi-domain phase-
retrieval problem directly from measured 2D Bragg diffraction intensities.
Fourier ViT couples reciprocal-space information globally through multiscale
Fourier token mixing, while shallow convolutional front and back-ends provide local filtering and reconstruction. We validate the approach on large-scale synthetic
datasets of Voronoi multi-domain
crystals with strong-phase contrast under realistic noise corruptions, and on experimental diffraction from a $\mathrm{La}_{2-x}\mathrm{Ca}_x\mathrm{MnO}_4$ nanocrystal. Across the regimes considered,
Fourier ViT achieves the lowest reciprocal-space mismatch ($\chi^2$) among the compared methods and preserves domain-resolved phase reconstructions for increasing numbers of domains. On experimental data, with the same real-space support,
Fourier ViT matches the iterative
benchmark $\chi^2$ while improving robustness to random initialisations, yielding a higher success rate of low-$\chi^2$ reconstructions than the complex convolutional neural network baseline.
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Materials Science
A Stochastic Cluster Expansion for Electronic Correlation in Large Systems
Annabelle Canestraight, Anthony J. Dominic, Andres Montoya-Castillo et al. (+2 more)
Accurate many-body treatments of condensed-phase systems are challenging because correlated solvers such as full configuration interaction (FCI) and the density
matrix renormalization group (DMRG) scale exponentially with system size. Downfolding and
embedding approaches mitigate this cost but typically require prior selection of a correlated subspace, which can be difficult to determine in heterogeneous or extended systems. Here, we introduce a
stochastic cluster expansion framework for efficiently recovering the total correlation energy of large systems with near-DMRG accuracy, without the need to select an active space a priori. By combining correlation contributions from randomly sampled environment orbitals with an exactly treated subspace of interest, the method reproduces total energies for non-reacting and reactive systems while drastically reducing computational cost. The approach also provides a quantitative diagnostic for molecule-solvent correlation, guiding principled
embedding decisions. This framework enables systematically improvable many-body calculations in extended systems, opening the door to high-accuracy studies of chemical processes in condensed phase environments.
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All authors Annabelle Canestraight, Anthony J. Dominic, Andres Montoya-Castillo, Libor Veis, Vojtech Vlcek
Materials Science
Kagome edge states under lattice termination, spin-orbit coupling, and magnetic order
Sajid Sekh, Annica M. Black-Schaffer and Andrzej Ptok
We study the edge state properties of a two-dimensional kagome
lattice using a tight-binding approach, focusing on the role of
lattice termination,
spin-orbit coupling, and
magnetic order. In the pristine limit, we show that the existence of localized edge states is highly sensitive to boundary geometry, with certain terminations completely suppressing edge modes. Kane-Mele
spin-orbit coupling opens a bulk gap and stabilizes topologically protected helical edge states, yielding a robust $\mathbb{Z}_2$ insulating phase that is insensitive to termination details. In contrast, the combined effect of a Zeeman field and Rashba
spin-orbit coupling drives the system into Chern insulating phases, with Chern numbers consistent with the number of
chiral edge modes. We further demonstrate that non-coplanar
magnetic textures generate multiple Chern phases through finite scalar
spin chirality, with Kane-Mele coupling strongly tuning the topological gaps. Our results provide important insights into the tunability of edge states in the kagome
lattice, which can be key to designing materials with novel electronic properties and topological phases.
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Materials Science · Cross-listed from cond-mat.str-el
Magnetopological mechanics in Maxwell lattice frustrated Mott insulators
Hong-Hao Song, Pengwei Zhao and Gang v. Chen
Topological boundary modes, a hallmark of
quantum topological phases, remarkably occur in classical mechanical systems through an interesting correspondence with the
quantum case. Here, we explore the Maxwell
lattice frustrated Mott
insulators and argue that the combination of the intrinsic
spin-
lattice coupling and the
spin exchanges could induce the topological mechanics with topological boundary floppy modes in the
phonon spectra. This mechanism and phenomena are dubbed
magnetic topological mechanics, or, magnetopological mechanics in short. Focusing on a two-dimensional kagomé
lattice spin model, we illustrate how strong
spin-
lattice coupling drives a spontaneous
lattice distortion, resulting in the topological Maxwell
lattice with the topological polarization and non-trivial
phonon spectra. Moreover, the
magnetic field, that directly changes the
spin state, indirectly influences the
lattice structure via the
spin-
lattice coupling, thereby providing a method to control the Maxwell
lattice and the boundary modes. We expect this work to inspire interests in the Maxwell
lattice Mott insulating materials and the coupling between
lattices and electronic orders.
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Materials Science
A critical assessment of bonding descriptors for predicting materials properties
Aakash Ashok Naik, Nidal Dhamrait, Katharina Ueltzen et al. (+4 more)
Most machine learning models for materials science rely on descriptors based on materials compositions and structures, even though the chemical bond has been proven to be a valuable concept for predicting materials properties. Over the years, various theoretical frameworks have been developed to characterize bonding in solid-state materials. However, integrating bonding information from these frameworks into machine learning pipelines at scale has been limited by the lack of a systematically generated and validated database. Recent advances in high-throughput bonding analysis workflows have addressed this issue, and our previously computed
Quantum-Chemical Bonding Database for Solid-State Materials was extended to include approximately 13,000 materials. This database is then used to derive a new set of
quantum-chemical bonding descriptors. A systematic assessment is performed using statistical significance tests to evaluate how the inclusion of these descriptors influences the performance of machine-learning models that otherwise rely solely on structure- and composition-derived features. Models are built to predict elastic, vibrational, and thermodynamic properties typically associated with chemical bonding in materials. The results demonstrate that incorporating
quantum-chemical bonding descriptors not only improves predictive performance but also helps identify intuitive expressions for properties such as the projected force constant and
lattice thermal conductivity via symbolic regression.
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All authors Aakash Ashok Naik, Nidal Dhamrait, Katharina Ueltzen, Christina Ertural, Philipp Benner, Gian-Marco Rignanese, Janine George
Materials Science
Stacking theory for bilayer two-dimensional magnets
Jun-Xi Du, Sike Zeng and Yu-Jun Zhao
Two-dimensional unconventional magnetism has recently attracted growing interest due to its intriguing physical properties and promising applications in spintronics. However, existing studies on stacking-induced unconventional magnetism mainly focus on specific materials and stacking configurations. Here, we develop a general
symmetry-based stacking theory for two-dimensional magnets. We first introduce
spin layer groups as the fundamental
symmetry framework, providing the essential
magnetic symmetry information for the stacking theory. Based on this framework, we construct the complete set of 448 collinear
spin layer groups for describing two-dimensional collinear magnets. Subsequently, we develop a general
magnetic stacking theory applicable to arbitrary
magnetic systems and derive its general solutions. Using CrF$_3$ as an illustrative example, we show how this theory enables designs of two-dimensional unconventional magnetism, as validated by first-principles calculations. We realize two-dimensional fully compensated ferrimagnetism through our stacking theory. Our work provides a general
symmetry-guided platform for discovering and designing stacking-induced unconventional magnetism.
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Materials Science
Bond failure in peridynamics: Nonequivalence of critical stretch and critical energy density criteria
Pablo Seleson, Pablo Raúl Stinga and Mary Vaughan
This paper rigorously analyzes bond failure in the peridynamic theory of solid mechanics, which is a fundamental component of fracture modeling. We compare analytically and numerically two common bond-failure criteria:~critical stretch and~critical energy density. In the former, bonds fail when they stretch to a critical value, whereas in the latter, bonds fail when the bond energy density exceeds a threshold. By focusing the analysis on bond-based models, we prove mathematically that the critical stretch criterion and the critical energy density criterion are not equivalent in general and result in different bond-breaking and fracture phenomena. Numerical examples showcase the striking differences between the effect of the two criteria on crack dynamics, including the crack tip
evolution, crack propagation, and crack branching.
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Materials Science
Thermodynamic Stability and Hydrogen Bonds in Mixed Halide Perovskites
Liz Camayo-Gutierrez, Javiera Ubeda, Ana L. Montero-Alejo et al. (+2 more)
The stability of mixed halide perovskites against phase separation is crucial for their optoelectronic applications, yet difficult to rationalize due to the interplay of enthalpic, configurational, and dynamical effects. Here we present a simple thermodynamic framework for multicomponent halide perovskites of composition FA$_{1-x}$MA$_{x-y}$Cs$_y$Pb(I$_{1-z}$Br$_z$)$_3$, based on ab initio molecular dynamics. By decomposing the free energy of mixing into enthalpic, configurational, and rotational entropic contributions, we show that although the enthalpy of mixing is generally positive, the solid solutions are thermodynamically stable against phase separation due to the large configurational
entropy associated with random substitution on cation and halide sublattices. Mixing reduces the rotational
entropy of the organic cations, partially offsetting the configurational stabilization. However, within our model, this rotational penalty is not sufficient to overcome the configurational driving force, and a
curvature analysis within a regular-solution model does not predict a miscibility gap for any of the mixing channels considered. Analysis of hydrogen-bond dynamics shows that MA–Y (Y = I, Br) interactions are more persistent than FA–Y interactions, while the dominant FA-donated N$-$H$\cdots$I hydrogen bonds remain nearly composition-invariant. Cs-containing mixtures, in which Cs$^{+}$ forms no hydrogen bonds, can nevertheless be thermodynamically stable. These results demonstrate that hydrogen bonding does not control thermodynamic stability in mixed halide perovskites. Instead, phase stability is governed by the balance between strong configurational
entropy and a smaller, systematically destabilizing rotational-
entropy correction.
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All authors Liz Camayo-Gutierrez, Javiera Ubeda, Ana L. Montero-Alejo, Ricardo Grau-Crespo, Eduardo Menéndez-Proupin
Materials Science · Cross-listed from cond-mat.stat-mech
Topological chiral random walker
Saeed Osat, Ellen Meyberg, Jakob Metson et al. (+1 more)
Understanding how biological and synthetic systems achieve robust function in noisy environments remains a fundamental challenge across the physical and life sciences. To connect robust behavior with non-trivial topological features present already in the dynamics of individual units, here we introduce the topological
chiral random walker (TCRW) model. While exploring the system, a TCRW locates edges and boundaries in the system and develops topologically protected edge currents even in the presence of defects and disorder. Drawing on the bulk-boundary correspondence found in hard condensed matter systems allows us to rationalize the emergence of robust edge currents through topological features of the dynamic spectrum. We show that
chiral motion and rotational noise with opposite chirality are two crucial components in our inherently non-Hermitian model. As proofs of principle, we first show that a topological walker outperforms diffusive motion to efficiently solve complex mazes due to its property of remaining on the edge with some rare detachments. Second, we use this model to design building blocks that can perform efficient self-assembly overcoming the timescale bottlenecks of
diffusion-limited growth and reducing self-assembly times by approximately 80%.
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All authors Saeed Osat, Ellen Meyberg, Jakob Metson, Thomas Speck
Materials Science · Cross-listed from physics.plasm-ph
Tuning Optical Properties of FTO via Carbonaceous Al2O3 Microdot Deposition by DC plasma sputtering
Sarah Salah, Ahmed Atlam, Nagat Elkahwagy et al. (+2 more)
Fluorine-doped tin
oxide (FTO) is a key transparent conductive
oxide for photovoltaic and optoelectronic devices, yet its high reflectance limits light-trapping efficiency. This work demonstrates a simple DC
plasma sputtering approach to deposit carbonaceous Al2O3 microdots on FTO under controlled Ar, O2, and Ar-O2 atmospheres. For
plasma discharge in the normal mode, with
plasma density 10^9 cm^-3 and temperature of 2 eV, Volmer-Weber growth produced discrete microdots whose size and distribution were tuned by gas composition: dense, uniform dots in Ar (approximately 0.89 um radius), agglomerated structures in O2, and intermediate morphologies in mixed atmospheres. Structural analysis confirmed Al2O3 formation with carbon incorporation, while SEM revealed morphology-driven optical behavior. UV-Vis measurements showed that Ar-O2 coatings achieved the lowest reflectance across the visible range, outperforming bare FTO and other conditions. These findings establish a clear link between sputtering parameters, surface morphology, and optical performance, offering a scalable route to anti-reflective, light-trapping coatings for next-generation
solar cells and optoelectronic devices.
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All authors Sarah Salah, Ahmed Atlam, Nagat Elkahwagy, Abdelhamid Elshaer, Mohammed Shihab
Materials Science · Cross-listed from cond-mat.mes-hall
Emergence of a Helical Metal in Rippled Ultrathin Topological Insulator Sb\textsubscript{2}Te\textsubscript{3} on Graphene
Francisco Munoz, Manuel Fuenzalida, Paula Mellado et al. (+3 more)
The integration of topological
insulators (TIs) with
graphene offers a pathway to engineer hybrid
quantum states, yet the impact of strain at the 2D limit remains a critical open question. Here, we investigate the structural properties of ultrathin (1 quintuple layer) Sb$_2$Te$_3$ grown on single-layer
graphene and, motivated by the structural modulations observed at the TI surface, explore theoretically how such nanoscale corrugations may influence the electronic behavior of the system. Using low-temperature scanning tunneling microscopy (LT-STM), we observe a periodic rippling of the
heterostructure with a wavelength of ~$\sim8.7$ nm. Energetic analysis reveals that these ripples are not intrinsic but are driven by strain from the substrate during cooling. Density functional theory (DFT) calculations show that while the ideal flat
heterostructure exhibits a hybridization gap of $\sim40$ meV, the ripple-induced structural modulation closes this gap, restoring a metallic state. This gapless phase is not a trivial metal. By combining an effective moiré ladder model with
spin-resolved DFT, we find that the proximity-induced
spin-orbit coupling is redistributed across a dense
manifold of minibands. The resulting “Helical Metal” has a complex
spin-texture beyond a simple Rashba splitting. Remarkably, while the flat system is effectively spinless in this ultrathin limit due to hybridization, the ripples actively restore the
spin polarization. Our findings suggest that rippled TI/
graphene heterostructures provide an interesting platform to develop spintronics, where
geometric modulation unlocks dense helical states that are inaccessible in the pristine flat limit.
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All authors Francisco Munoz, Manuel Fuenzalida, Paula Mellado, Hari C. Manoharan, Valentina Gallardo, Carolina Parra
Materials Science
Phaseless auxiliary-field quantum Monte Carlo method with spin-orbit coupling
Zheng Liu, Shiwei Zhang and Fengjie Ma
Spin-orbit coupling (SOC) is incorporated into the phaseless plane-wave-based auxiliary-field
quantum Monte Carlo (pw-AFQMC) method. This integration is implemented using optimized multiple-projector norm-conserving pseudopotentials, which are derived from the fully-relativistic (FR) atomic all-electron Dirac-like equation. The inclusion of SOC enables accurate phaseless pw-AFQMC calculations that capture both electronic correlation and SOC effects concurrently, greatly improving the method's applicability for studying systems containing heavy atoms. We discuss the form of FR pseudopotentials and detail the corresponding formulations of phaseless pw-AFQMC with a two-component
Hamiltonian in the spinor basis. The accuracy of our approach is demonstrated by computing the dissociation energy of molecule I2 and the cohesive energy of bulk Pb, highlighting the large influence of SOC in both. Subsequently, we determine the transition pressure of the III-V compound InP from its zinc-blende to rock-salt phase by constructing and analyzing their respective equations of state.
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