Materials Science
Controlled antivortex propagation at bifurcations in reconfigurable NdCo/NiFe racetracks
V.V. Fernandez, A.E. Herguedas-Alonso, C. Fernandez-Gonzalez et al. (+7 more)
The controlled propagation of
spin textures at bifurcations is a critical challenge for racetrack-based logic devices. Here, we investigate the effect of longitudinal and transverse
magnetic fields on the propagation of
magnetic antivortices at bifurcations within the stripe domain pattern of a reconfigurable NdCo/NiFe racetrack in order to control the preferred antivortex trajectory.
Magnetic Transmission X-ray Microscopy experiments were employed to correlate the observed propagation path with the local
magnetic configuration. We demonstrate that Zeeman coupling to the magnetization components at the bifurcation core enables switching of the preferred propagation branch using low-amplitude transverse
magnetic fields, without modifying the global stripe domain configuration that defines the guiding racetrack landscape. In-plane
magnetic anisotropy provides an additional mechanism to break the
symmetry between the upper and lower bifurcation branches by tuning the relative orientation between the stripe domain pattern and the longitudinal
magnetic fields.
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All authors V.V. Fernandez, A.E. Herguedas-Alonso, C. Fernandez-Gonzalez, R. Valcarcel, P. Suarez, A. G. Casero, C. Quiros, A. Sorrentino, A. Hierro-Rodriguez, M. Velez
Materials Science
Multiple Topological States in LaAgAs2, a Failed Square-Net Semimetal
Yang Liu, Tongrui Li, Xixi Yuan et al. (+15 more)
The rational design of new materials emerges as an important direction to explore new topological materials, which is based on the understanding of the correlation between
crystal and electronic structures. In this paper, we perform a comprehensive study on the
crystal and electronic structures in LaAgAs2 through a combination of single-
crystal x-ray diffraction (XRD),
quantum oscillation, and angle-resolved photoemission spectroscopy (ARPES) experimental measurements, and density functional theory (DFT) calculations. Single-
crystal XRD measurements reveal that LaAgAs2 crystallizes into a HfCuSi2-derived structure with the square net distorted into cis-trans chains.
Quantum oscillation measurements reveal two frequencies with small effective masses and quasi-two-dimensional (2D) characters. ARPES measurements reveal an electronic structure strikingly different from the square-net-based semimetals, such as LaAgAs2. The
Fermi surface is quasi-two-dimensional (2D), with Dirac-like hole pockets at the zone center and a quasi-1D elliptical electron pocket at the zone boundary. Based on the DFT calculations, the measured electronic structure can be well understood regarding the cis-trans distortion, which transforms the two-dimensional square net-derived Dirac bands into quasi-1D trivial bands. Intriguingly, multiple topological states can be identified around the zone center, including a nontrivial Z2 topological surface state and a bulk Dirac state. Our study clarifies the impact of cis-trans distortion and identifies LaAgAs2 as a topological material with multiple topological states near the
Fermi level, providing a guideline for intentionally designing new topological materials.
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All authors Yang Liu, Tongrui Li, Xixi Yuan, Nour Maraytta, Alexei V. Fedorov, Asish K. Kundu, Turgut Yilmaz, Elio Vescovo, Xueliang Wu, Long Zhang, Mingquan He, Yisheng Chai, Xiaoyuan Zhou, Michael Merz, Zhe Sun, Huixia Fu, Tonica Valla, Aifeng Wang
Materials Science · Cross-listed from cond-mat.mes-hall
Kinetics-Driven Selective Stoichiometric Shift and Structural Asymmetry in $Bi_4Te_3$ Nanostructures for Hybrid Quantum Architectures
Abdur Rehman Jalil, Helen Valencia, Christoph Ringkamp et al. (+6 more)
Advances in hybrid
quantum architectures hinge on topological materials that can be synthesized with precise stoichiometric and structural control at the nanoscale. While $Bi_4Te_3$ is a promising candidate due to its dual topological phases, acting as both a strong topological
insulator and a topological crystalline
insulator, high-quality growth remains challenging due to a narrow stoichiometric window and high sensitivity to surface kinetics. Here, we establish a reproducible molecular beam epitaxy (MBE) process to produce stoichiometric, twin-free $Bi_4Te_3$ thin films with ultra-smooth surfaces and atomically sharp van der Waals stacks. By employing selective area epitaxy (SAE), we realize laterally confined $Bi_4Te_3$ nanostructures that exhibit a feature-dependent stoichiometric deviation. This phenomenon, which we term the selective stoichiometric shift, arises from the unequal lateral
diffusion of Bi and Te adatoms, revealing a direct coupling between adatom kinetics and nanoscale compositional stability. Atomic-resolution imaging further uncovers asymmetric van der Waals gaps within the stacking sequence, identifying an intrinsic structural asymmetry between the quintuple and
bilayer units. These findings provide fundamental insights into the crystallization of Bi_4Te_3$ and demonstrate a scalable route for integrating functional topological materials into next-generation superconducting hybrid
quantum circuits.
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All authors Abdur Rehman Jalil, Helen Valencia, Christoph Ringkamp, Abbas Espiari, Michael Schleenvoigt, Peter Schüffelgen, Gregor Mussler, Martina Luysberg, Detlev Grützmacher
Materials Science
Revealing Charge Transfer in Defect-Engineered 4H$_\mathrm{b}$-TaS$_2$
Siavash Karbasizadeh, Wooin Yang, Wonhee Ko et al. (+4 more)
We present a comprehensive first-principles investigation of defects in 4$H_b$-TaS$_2$. In this layered transition metal dichalcogenide, charge transfer between alternating Mott-insulating 1T and metallic 1H layers gives rise to exotic
quantum phases such as the Kondo effect and topological superconductivity. Motivated by recent defect manipulation in 4$H_b$-TaS$_2$ via STM, we address their microscopic nature and impact on interlayer charge transfer. To this end, we systematically analyze over 90 defects using large-scale density functional theory (DFT) calculations. Our extensive
dataset, compiled from STM simulations, defect formation energies, work functions, and charge transfer, establishes a foundational resource for future theoretical and experimental studies on defect engineering in 4$H_b$-TaS$_2$.
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All authors Siavash Karbasizadeh, Wooin Yang, Wonhee Ko, Haidong Zhou, An-Ping Li, Tom Berlijn, Sai Mu
Materials Science
Fine-tuning universal machine learning potentials for transition state search in surface catalysis
Raffaele Cheula, Mie Andersen and John R. Kitchin
Determining transition states (TSs) of surface reactions is central to understanding and designing heterogeneous catalysts but remains computationally prohibitive with density functional theory (DFT). While machine learning potentials (MLPs) offer significant speedups, task-specific models have limited transferability across catalytic systems, and universal MLPs (uMLPs) lack the accuracy needed for reactive configurations. Here, we present a workflow based on active learning to iteratively fine-tune uMLPs for DFT-quality TS search. Using 250 TSs from the CO2 hydrogenation reaction network on metal and single-atom
alloy surfaces, we first
benchmark TS search
algorithms, identifying the Sella
algorithm as most robust, and propose a modification (Bond-Aware Sella) that substantially improves its success rate. We then explore sequential and batch active-learning strategies for fine-tuning and show that DFT-quality TS structures can be found using only 8 DFT single-point calculations on average per structure. This demonstrates the viability of fine-tuned uMLPs for high-throughput catalyst screening.
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Materials Science
Substrate-dependent pore formation in molybdenum disulfide monolayers under ion irradiation
Y. Liebsch, U. Javed, L. Skopinski et al. (+11 more)
Ion irradiation is a versatile tool for nanostructuring surfaces, yet the roles of energy deposition and dissipation at the surface and in ultrathin materials remain poorly understood. In this study, we investigate nanopore formation in monolayer MoS$_2$ on different substrates under irradiation of highly charged ions (HCIs) and swift heavy ions (SHIs): two types of ions that, despite having vastly different kinetic energies, interact primarily with the electronic system of the target. Using scanning transmission electron microscopy, we quantify pore radii and pore formation efficiencies for suspended MoS$_2$, MoS$_2$ on SiO$_2$,
bilayer MoS$_2$ and MoS$_2$ on gold. Both pore size and pore formation efficiency exhibit a pronounced dependence on the type of substrate. Pores are largest and most frequent in MoS$_2$ on SiO$_2$, while the gold substrate massively quenches pore formation. The results indicate that the observed pore dimensions under both HCI and SHI irradiation are consistent with a central role of substrate and interface-dependent electronic dissipation pathways.
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All authors Y. Liebsch, U. Javed, L. Skopinski, L. Daniel, F. Appel, R. Rahali, C. Grygiel, H. Lebius, C. Frank, L. Breuer, L. Kirsch, F. Koch, J. Kotakoski, M. Schleberger
Materials Science
Plasmonic Mediated Atomically Engineered 2D Aluminium Quasicrystals for Dopamine Biosensing
Saswata Goswami, Guilherme S. L. Fabris, Diganta Mondal et al. (+7 more)
Dopamine levels are linked to neurological illnesses like Parkinson's and Alzheimer's. Thus, reliable and sensitive detection of dopamine is crucial for early diagnosis and surveillance of neurodegenerative diseases. Non-noble-metal-based nanomaterials are ideal for light-mediated sensing of organic molecules. Among these, 2D quasicrystal structures consisting of five elements, namely Al70Co10Fe5Ni10Cu5, provide active sites due to their high surface-to-volume ratio, making them excellent for organic chemical sensing. Here, we propose a simple, label-free, spatial self-phase-modulation (SSPM)-based sensing method in
liquid form. SSPM-based time
evolution of the diffraction pattern for varied mixing levels of a 1100 ppb dopamine solution shows a shift in the active 2D Al QC solution. The 1100 ppb solution shows a distinct value, indicating a change in the nonlinear refractive index. Time-
evolution analysis is used to calculate sensitivities to changes in the nonlinear refractive index and time constant. The SPR-activated 2D Al QC nanostructure is used to demonstrate dopamine sensing and to perform qualitative and quantitative evaluations. The SSPM-based sensing has been further compared with other optical-based sensing methods such as Raman spectroscopy, UV-Vis spectroscopy, and FTIR spectroscopy. The experimental observations are also explained using DFT-based simulations. The current SSPM method can be used for rapid, large-scale medical diagnostics.
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All authors Saswata Goswami, Guilherme S. L. Fabris, Diganta Mondal, Raphael B. de Oliveira, Anyesha Chakraborty, Thakur Prasad Yadav, Nilay Krishna Mukhopadhyay, Samit K. Ray, Douglas S. Galvão, Chandra Sekhar Tiwary
Materials Science · Cross-listed from physics.comp-ph
Aluminum solidification and nanopolycrystal deformation via a Graph Neural Network Potential and Million-Atom Simulations
Ian Störmer and Julija Zavadlav
Solidification governs the microstructure and, therefore, the mechanical response of metal components, yet the atomistic details of nucleation and defect formation are often difficult to determine experimentally. Molecular dynamics can bridge this gap, but only if the interatomic model is both accurate and computationally efficient. Here, we develop a Machine Learning Potential (MLP) for aluminum and demonstrate its near ab initio fidelity when trained with the sequential-refinement workflow that fine-tunes the model on low-energy structures. The favorable scaling of the model enables nanosecond simulations involving millions of atoms, thereby overcoming finite-size effects in simulations of polycrystalline solidification and subsequent mechanical testing. Comparison with classical potentials and recent MLP models, including a general-purpose model, shows that inaccuracies in stacking-fault energetics and
diffusion can lead to qualitatively incorrect solidified grain structures and post-solidification mechanical behavior. Since our framework is based on an equivariant graph neural network, it allows for straightforward extensions to multi-component systems, providing valuable guidance for the future design and fine-tuning of both specialized and universal MLPs in computational mechanics simulations.
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Materials Science
Automated Spin-Assisted Layer-by-Layer Epitaxy Produces Highly Oriented Mixed-Linker MOF Thin Films
Eleonora Afanasenko, Benedetta Marmiroli, Behnaz Abbasgholi-NA et al. (+11 more)
Control over crystallographic orientation in metal-organic framework (MOF) thin films is crucial for exploiting their anisotropic properties in sensing, catalysis, and separation. Achieving reproducible, highly oriented films remains challenging, especially for mixed-linker, pillared-layered frameworks. Here we present an automated,
spin-assisted layer-by-layer
liquid-phase epitaxy (LbL-LPE) strategy that enables rapid, ambient-condition fabrication of highly oriented, mixed-linker MOF thin films, demonstrated for Zn2BDC2DABCO (BDC = terephthalate, DABCO = 1,4-diazabicyclo[2.2.2]octane). Correlative process monitoring by grazing-incidence wide-angle X-ray scattering (GIWAXS), grazing-angle infrared (GI-IR) and UV-Vis spectroscopy, contact-angle measurements, scanning electron microscopy (SEM), and time-of-flight secondary ion mass spectrometry (ToF-SIMS) ensure formation of uniform films with exceptional out-of-plane (001) orientation (degree of orientation >85%, Hermans parameter ~0.95) and excellent reproducibility. This strategy enables highly reproducible, high-throughput fabrication of orientation-controlled MOF thin films, providing a generalizable alternative to conventional LbL approaches. By enabling reproducible and entirely automated fabrication of highly anisotropic architectures, this work establishes a platform for integrating oriented MOFs into next-generation optoelectronic, sensing, and membrane devices where directional transport and ordered pore
alignment are essential.
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All authors Eleonora Afanasenko, Benedetta Marmiroli, Behnaz Abbasgholi-NA, Barbara Sartori, Giovanni Birarda, Chiaramaria Stani, Matjaž Finšgar, Peter E. Hartmann, Mark Bieber, Emma Walitsch, Rolf Breinbauer, Simone Dal Zilio, Sumea Klokic, Heinz Amenitsch
Materials Science · Cross-listed from cond-mat.str-el
Universal Quantum Suppression in Frustrated Ising Magnets across the Quasi-1D to 2D Crossover via Quantum Annealing
Kumar Ghosh
Quantum magnets in the $M\mathrm{Nb_2O_6}$ and BaCo$_2$V$_2$O$_8$ families realise frustrated transverse-field Ising models whose competing
ferromagnetic and
antiferromagnetic couplings generate a sign problem provably intractable for
quantum Monte Carlo at any system size, leaving their
quantum phase boundaries numerically Inaccessible. Using a D-Wave Advantage2
quantum annealer at $L\leq27$ (729
spins), we obtain the large-$L$ critical points for this model family, measuring
quantum-driven transitions at ${g_c^{\mathrm{QPU}}}\in\{0.286,\,0.210,\,0.156,\,0.093\}$ for $\alpha\in\{1.0,\,0.7,\,0.5,\,0.3\}$, where the analytically exact classical threshold is ${g_c^{\mathrm{class}}}(\alpha)=2\alpha/3$. The suppression ratio $r(\alpha)$ exhibits a sharp two-regime structure: the three quasi-1D geometries ($\alpha\leq0.7$) are mutually consistent with a universal plateau $\bar{r}=0.450$ ($\chi^2/\mathrm{dof}=1.10$, $p=0.33$), demonstrating that
quantum fluctuations destroy approximately $55\%$ of the classical FM stability window independently of coupling anisotropy, while $r$ steps down to the 2D limit above the empirical crossover scale $\alpha^*\approx0.7$. Inner Binder cumulant pairs, which converge fastest to the thermodynamic limit, resolve $r(1.0)\approx0.412$ and a step $\Delta r=0.038\pm0.015$ from the quasi-1D plateau. A four-point linear fit $r(\alpha)=0.494-0.063\,\alpha$ summarises both regimes; its $\alpha\to0$ intercept recovers the exact 1D result of Pfeuty within 1.7 standard deviations, and its slope is a lower bound on the true crossover amplitude concentrated in $\alpha\in[\alpha^*,1]$. Two sequential blind predictions, confirmed at $0.2\sigma$ and $0.7\sigma$ before each measurement, validate the crossover law. All four geometries show a direct ferromagnet-to-paramagnet transition, complete
quantum ergodicity ($f_{\rm uniq}=1.000$), and null valence-bond solid order.
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Materials Science
Lattice-Expansion-Driven Stabilization of Helical Magnetic Order in Ru-Doped MnP
Xin-Wei Wu, Deng-lu Hou, Li Ma et al. (+3 more)
The practical utilization of MnP in
chiral spintronic devices is fundamentally constrained by its low helical ordering temperature ($T_{\rm S}$). Here, we demonstrate that Ru substitution in Mn$_{1-x}$Ru$_x$P single
crystals drives a highly anisotropic
lattice expansion, where the $b$-axis elongation is one-quarter that of the $a$- and $c$-axes ($\sim$ 0.04 Å). This structural distortion profoundly stabilizes the helical ground state, elevating $T_{\rm S}$ from 51~K to 215~K and the critical field along the [010] direction at 5~K from 2.3 to 30.0~kOe, while suppressing the Curie temperature ($T_{\rm C}$) from 291~K to 215~K. Synthesizing these results with reported data on Mo- and W-doped analogues reveals that $T_{\rm S}$ and $T_{\rm C}$ are governed primarily by the $b$-axis parameter, exhibiting universal linear scaling relationships ($dT_{\rm S}/db = 1.59 \times 10^4\ \text{K\AA}^{-1}$, $dT_{\rm C}/db = 0.69 \times 10^4\ \text{K\AA}^{-1}$) far greater than those associated with the $a$- or $c$-axes. First-principles calculations reveal that the
lattice expansion selectively attenuates
ferromagnetic coupling while preserving
antiferromagnetic interactions between nearest-neighbor Mn atoms, thereby enhancing
magnetic frustration and stabilizing helimagnetism. These findings establish chemical pressure via directed $b$-axis engineering as a robust, generalizable paradigm for stabilizing helimagnetism in MnP.
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All authors Xin-Wei Wu, Deng-lu Hou, Li Ma, Cong-mian Zhen, De-wei Zhao, Guoke Li
Materials Science
Exploring the Structure and Chemistry of 1D and 2D Lepidocrocite TiO2 at Atomic Resolution
Eric Nestor Tseng, Jonas Björk, Risha Achaiah Iythichanda et al. (+6 more)
Low dimensional materials are critical for enabling next generation applications that are central to addressing critical global challenges. Titanium dioxide nanostructures stand out due to their structural versatility and relevance to catalysis, energy conversion, and environmental remediation. Here, we employ a combination of advanced electron microscopy, spectroscopy, and first principles theoretical calculations to investigate the structural and chemical properties of one and two dimensional lepidocrocite type titania. Special emphasis is placed on the one dimensional material, which exhibits anisotropic growth, extending exclusively along a single crystallographic direction. Our analysis suggests that this unusual growth behavior can be attributed to light element
impurities, such as carbon, that are incorporated during the bottom up synthesis. The results extend the understanding for these unexplored low dimensional titania materials and offer fundamental insights into their structure and chemistry.
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All authors Eric Nestor Tseng, Jonas Björk, Risha Achaiah Iythichanda, Wei Zheng, Hatim Alnoor, Wei Hsiang Huang, Ming-Hsien Lin, Johanna Rosén, Per O.Å. Persson
Materials Science
Mn substitution induced a ferrimagnetic to ferromagnetic transition in trigonal $\text{Cr}_5\text{Te}_8$
Ze-Xin Liu, Yu Liu, Sen-Miao Zhao et al. (+4 more)
Tailoring the
magnetic properties of chromium tellurides via heterointercalation with extrinsic transition metals remains largely unexplored. Here, we report a comprehensive investigation of trigonal Cr$_5$Te$_8$ and Cr$_4$MnTe$_8$ single
crystals, in which Mn substitution elevates the
magnetic ordering temperature from 226 to 249 K and enhances the saturation
magnetic moment per
magnetic ion ($m_{\text{S}}$) from 2.00 to 2.66 $\mu_{\text{B}}$ at 5 K. Remarkably, the observed $m_{\text{S}}$ enhancement significantly exceeds the contribution of Mn ion moments alone, indicating the relief of intrinsic
spin compensation within the parent
lattice. First-principles calculations definitively establish that pristine $\text{Cr}_5\text{Te}_8$ exhibits ferrimagnetic ordering with a computed $m_\text{S}$ of 1.98~$\mu_\text{B}$, and further reveal that preferential occupation of the van der Waals gaps by Mn ions induces a ferrimagnetic-to-
ferromagnetic transition, yielding a predicted $m_\text{S}$ of 2.94~$\mu_\text{B}$. These findings not only resolve the
magnetic ground state of trigonal Cr$_5$Te$_8$ but also identify heterointercalation as a robust strategy for engineering the
spin textures of chromium tellurides.
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All authors Ze-Xin Liu, Yu Liu, Sen-Miao Zhao, De-Wei Zhao, Li Ma, Deng-Lu Hou, Guo-Ke Li
Materials Science · Cross-listed from cond-mat.mes-hall
A material-agnostic platform to probe spin-phonon interactions using high-overtone bulk acoustic wave resonators
Q. Greffe, A. Hugot, S. Zhang et al. (+6 more)
Spin-
phonon interactions have a dual role in emerging
spin-based
quantum technologies. While they can be a limitation to device performance through decoherence, they also serve as a critical resource for coherent
spin control, detection, and the realization of
spin-based
quantum networks. However, their direct characterization remains a challenge and is usually material-dependent. Here, we introduce a technique to probe
spin-
phonon coupling at millikelvin temperatures and gigahertz frequencies, using high-overtone bulk acoustic wave resonators (HBARs) integrated with arbitrary
crystals via visco-elastic transfer of thin-film lithium niobate transducers. By tuning the Larmor frequency of dilute
spin ensembles into resonance with HBAR modes, we extract the anisotropy and strength of
spin-
phonon interactions from acoustic dispersion and dissipation measurements. We demonstrate this approach in calcium tungstate (CaWO4) and yttrium orthosilicate (Y2SiO5), achieving cooperativities up to 0.5 for erbium dopant ensembles. Our method enables the study of
spin-
phonon interactions in complex crystalline materials, with minimal fabrication constraints. These results will facilitate the design of hybrid
quantum systems and the quest for ion-
matrix combination with enhanced
spin-
phonon coupling.
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All authors Q. Greffe, A. Hugot, S. Zhang, J. Jarreau, L. Del-Rey, E. Bonet, F. Balestro, T. Chanelière, J. J. Viennot
Materials Science
Diffusion coefficients of multi-principal element alloys from first principles
Damien K. J. Lee and Anirudh Raju Natarajan
Vacancy-mediated
diffusion in multi-principal element
alloys (MPEAs) remains poorly understood. Existing computational methods face challenges in connecting electronic structure to macroscopic transport coefficients due to the large number of chemical elements. To address this, we introduce the embedded local cluster expansion (eLCE), which bridges first-principles calculations with kinetic Monte Carlo simulations to compute the
matrix of multicomponent
diffusion coefficients. Applying this approach to refractory MPEAs in the V-Cr-Nb-Mo-Ta-W system, we evaluate the complete mobility and
diffusion tensors of a six-component
alloy at finite temperatures. We find that local kinetic barriers, rather than thermodynamics or vacancy correlation factors, primarily control
diffusion in these materials. Whether
diffusion is sluggish or anti-sluggish depends on the mean vacancy migration barrier relative to the rule-of-mixtures estimate and on the availability of percolating pathways of fast-diffusing species. We use this insight to screen the senary composition space and identify compositions with anti-sluggish
diffusion. This study presents a predictive, first-principles approach for computing non-dilute transport coefficients and designing MPEAs with targeted transport properties.
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Materials Science · Cross-listed from cond-mat.mes-hall
Topological insulator single-electron transistors for charge sensing applications
Omargeldi Atanov, Junya Feng, Jens Brede et al. (+2 more)
We present topological
insulator (TI)-based single-electron transistors (SETs) as
magnetic-field-compatible charge sensing devices that are easily integrable with TI-
superconductor hybrid platforms. We observe well-resolved Coulomb diamonds in the charge-stability diagrams of our devices confirming the charge quantization and single-electron transport. In some devices, the Coulomb resonances show persistent shifts corresponding up to $\sim$ e/2 charge. An axial
magnetic field further displaces these shifts to higher or lower gate voltages. We find that the axial
magnetic-field dependence of the shifts is consistent with the Zeeman shift of a trap state coupled to the SET, and we reproduce the observations using numerical simulations. The resonance shifts are therefore identified as a consequence of the sensitivity of our TI-SET devices to charges in proximity. Establishing this charge sensing capability is a first step toward integrating TI-SETs as charge sensors in more complex TI-based hybrid devices, with the overarching goal of detecting and braiding Majorana zero modes.
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All authors Omargeldi Atanov, Junya Feng, Jens Brede, Oliver Breunig, Yoichi Ando
Materials Science · Cross-listed from cond-mat.str-el
Excitonic order in quantum materials: fingerprints, platforms and opportunities
Yande Que, Clara Rebanal, Liam Watson et al. (+4 more)
The
exciton insulator (EI) is a unique many-body ground state of condensed, spontaneously formed
excitons (electron-hole pairs) in
equilibrium, distinct from conventional band or Mott
insulators. Originally proposed over half a century ago, the concept has recently gained renewed experimental traction thanks to advances in spectroscopic resolution, ultrafast probes, and materials synthesis. In this Review, we outline the essential theoretical ingredients underpinning excitonic order and discuss how dimensionality, disorder and screening affect stability. We then examine the diverse experimental fingerprints of the excitonic state, with central focus on strategies to disentangle excitonic order from competing phases such as charge density waves, Mott insulating states, and hybridization-driven
insulators, particularly in systems where non-trivial band
topology plays a role. We survey the rapidly expanding family of candidate materials, from layered chalcogenides and correlated rare-earth compounds to artificial excitonic platforms and optically driven non-
equilibrium condensates. Finally, we discuss the key challenges and emerging opportunities in the field, identifying the theoretical and experimental frontiers that promise to shape the next decade of research.
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All authors Yande Que, Clara Rebanal, Liam Watson, Michael Fuhrer, Michał Papaj, Bent Weber, Iolanda Di Bernardo
Materials Science
First-principles high-throughput screening of ruthenium compounds for advanced interconnects
Gyungho Maeng, Subeen Lim, Bonggeun Shong et al. (+1 more)
As interconnect dimensions continue to shrink, the industry-standard copper faces a critical increase in resistivity, presenting a significant hurdle to overall device performance. To overcome this limitation, this work investigates the potential of ruthenium (Ru)-based compounds, encompassing binary, ternary, and quaternary systems, as viable alternatives to copper (Cu). Ruthenium is regarded as a strong candidate, owing to its inherent advantages in reliability and more favorable resistivity scaling at reduced dimensions. Moreover, forming compounds offers an effective strategy to engineer novel properties, expanding the material design space beyond the constraints of pure metals. Utilizing a high-throughput screening methodology, we systematically investigated a broad spectrum of 2,106 Ru-based compounds to identify candidates with superior electronic transport and reliability characteristics. Consequently, we successfully identified a total of 61 promising candidates that exhibit excellent resistivity scaling behavior and enhanced reliability. These findings demonstrate that Ru-based compounds offer a viable pathway to overcome the scaling limitations of next-generation interconnects.
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All authors Gyungho Maeng, Subeen Lim, Bonggeun Shong, Yeonghun Lee
Materials Science
Tunable intersublattice exchange coupling drives magnetic evolution in Mn$_{3+x}$Ga$_{1-x}$C ($0 \le x \le 0.60$)
Dong-Hui Xu, Cong-Mian Zhen, Deng-Lu Hou et al. (+3 more)
We investigate the
magnetic and transport
evolution in Mn$_{3+x}$Ga$_{1-x}$C ($0 \le x \le 0.60$), where Mn substitution at corner Ga sites induces
lattice contraction and suppresses the
antiferromagnetic order of Mn$_3$GaC. As $x$ increases, the
magnetic ground state of the system undergoes a sequential transition from an
antiferromagnetic state, via a canted ferrimagnetic state, to a robust ferrimagnetic state, accompanied by a surge in the
magnetic ordering temperature. Saturation
magnetic moments reaches a maximum of 3.63~$\mu_{\mathrm{B}}$/f.u. at $x = 0.10$, whereas the topological
Hall resistivity peaks at 1.47~$\mu\Omega\cdot$cm for $x = 0.20$ before decreasing with further doping. First-principles calculations demonstrate a $\sim\!40^{\circ}$ canting of face-centered Mn moments at $x = 0.20$, signifying
spin frustration, and an eventual antiparallel
alignment of face-centered and corner-site Mn moments at higher $x$. These results reveal that intersublattice
antiferromagnetic coupling governs the
magnetic transformation and emergent transport phenomena, thus providing a microscopic foundation for designing high-ordering-temperature antiperovskites.
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All authors Dong-Hui Xu, Cong-Mian Zhen, Deng-Lu Hou, Li Ma, De-Wei Zhao, Guo-ke Li
Materials Science
The domain-wall/metal-electrode injection barrier in lithium niobate: Which electrical transport model fits best?
Manuel Zahn, Elke Beyreuther, Iuliia Kiseleva et al. (+3 more)
The comprehensive description of both the electrical transport along conductive domain walls (CDWs) in lithium niobate (LNO) single
crystals and the charge injection at the interfacing metal electrodes, emerged to be a complex challenge. Recently, a heuristic evaluation allowed to postulate the "R2D2" equivalent-
circuit model (consisting of two parallel resistor-diode pairs) to appropriately match the DC current-voltage (I-V) characteristics. Here, we carefully revisit the interfacial electrical behavior, i.e., the diode part of the equivalent
circuit model, since many more processes beyond the diode-related electron hopping transport (HT) assumed so far, may concurrently occur, such as thermionic emission (TE), Fowler-Nordheim tunneling (FNT), space-charge limited conduction (SCLC), and others more. The "R2D2" model thus needs to be generalized into an "R2X2"
circuit model (with X = HT, TE, FNT, and others) to fit to the experimental data. Moreover, to double check for the best I-V curve fitting to the different theories, we apply a higher-harmonic DW current-contribution (HHCC) analysis, i.e., an AC I-V inspection, that allows us to discriminate between all these possible models with much higher precision than from pure DC I-V curve fitting. Both the AC and DC analysis reveal well consistent results, finally finding that the FNT model accounts best for the domain-wall/electrode junctions investigated here.
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All authors Manuel Zahn, Elke Beyreuther, Iuliia Kiseleva, Julius Ratzenberger, Michael Rüsing, Lukas M. Eng
Materials Science
When Trace Water Dominates: Hydration-Mediated Dielectric and Transport Behaviour in BiFeO$_3$
Subir Majumder, Gilad Orr and Paul Ben-Ishai
Traces of water can profoundly alter the dielectric response of functional
oxides, yet such effects have remained largely unrecognized in systems where colossal dielectric behaviour has been widely reported. Here, we investigate the impact of sub-percent hydration ($<$1 wt%) on the dielectric relaxation, charge transport, and interfacial polarization properties of porous BiFeO$_3$ ceramics. Broadband dielectric spectroscopy reveals, in the hydrated state, a dominant relaxation process characterized by an anomalously large dielectric strength ($\Delta\varepsilon \approx$ 10$^4$-10$^5$) and a pronounced saddle-point deviation from Arrhenius dynamics, indicative of non-Arrhenius relaxation behaviour in a porous
oxide system. These features appear only in the hydrated state and vanish upon dehydration, while the intrinsic activation barriers governing the thermally activated relaxation timescale remain comparable. Comparison with hydration-controlled dielectric responses in layered clay minerals shows that similar qualitative deviations can emerge in BiFeO$_3$ with nearly fifteen-fold lower water content, underscoring the effectiveness of confined water at grain boundaries, pore surfaces, and internal interfaces. Together, these results demonstrate that trace, confined water can make a major extrinsic contribution to dielectric and transport anomalies in porous
oxide ceramics. The use of dehydration-controlled dielectric cycling provides a practical diagnostic framework for reassessing colossal dielectric responses, Maxwell-Wagner-type effects, and hydration-induced phenomena in functional
oxide materials.
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Materials Science
On the configurational force associated with blocked slip bands at grain boundaries in {\alpha}-Ti
Abdalrhaman Koko
Grain boundaries can block slip-band propagation and generate intense local stress and strain fields that influence subsequent deformation and damage initiation in polycrystalline metals. Conventional
geometric criteria, such as Schmid factor and slip-transfer parameters, describe crystallographic compatibility but do not quantify the energetic severity of a blocked slip event. Here, we apply a configurational force framework to high-angular-resolution electron backscatter diffraction (HR-EBSD) measurements obtained from a blocked slip band in commercially pure titanium. By evaluating a J-type equivalent domain integral from the measured elastic field, we quantify both the magnitude and directional dependence of the local energetic driving force associated with the stress localisation; thus, providing an energetic descriptor of the tendency for deformation to extend into the neighbouring grain. The results show a marked decoupling between conventional
geometric metrics and the configurational force response, indicating that the local stress-localisation geometry strongly influences which crystallographically admissible extension directions in the neighbouring grain are energetically favoured. The framework provides a physically grounded basis for quantifying blocked-slip severity and for motivating future in situ studies aimed at defining a critical transfer threshold for transfer or cracking.
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Materials Science
Unified ab initio quantum-electrodynamical density-functional theory for cavity-modified electron-phonon-photon coupling in solids
Benshu Fan, I-Te Lu, Michael Ruggenthaler et al. (+1 more)
Quantum-electrodynamical density-functional theory (QEDFT) provides a first-principles framework for describing materials coupled to quantized electromagnetic fields. While QEDFT has successfully captured cavity-induced modifications of electronic structures in atoms and molecules, a fully self-consistent and accurate framework to simulate and predict the structural,
phonon-related, polarization and optical response of periodic solids in optical cavities has remained elusive. Here, we introduce a unified QEDFT approach that combines collective light-matter coupling parameter in the electronic ground state, density functional perturbation theory for
phonons, and real-time time-dependent QEDFT for optical excitations. This framework enables ab initio calculations of cavity-modified electronic and phononic dispersions, Born effective charges, dielectric tensors, and both resonant and non-resonant optical absorption spectra. Using wurtzite gallium nitride (GaN) in an optical cavity as a case study, we demonstrate that the quantized
vacuum field reshapes electronic, phononic and polarization properties, producing experimentally accessible signatures in the dielectric function and absorption spectra. These results establish QEDFT as a general first-principles platform for predicting and exploring cavity-modified
quantum materials.
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All authors Benshu Fan, I-Te Lu, Michael Ruggenthaler, Angel Rubio
Materials Science
Predicting Grain Growth Evolution Under Complex Thermal Profiles with Deep Learning through Thermal Descriptor Modulation
Pungponhavoan Tep and Marc Bernacki
Predicting microstructure
evolution during thermomechanical treatment is essential for determining the final mechanical properties of a material, yet conventional simulations based on Partial Differential Equations (PDEs) remain computationally expensive. Our prior Deep Learning (DL) framework using Convolutional Long Short-Term
Memory (ConvLSTM) has proven effective in accelerating grain growth prediction, though its applicability was limited to constant-temperature or single-rate thermal profiles. As the model was trained exclusively under constant thermal conditions, it cannot account for the thermal history dependence of grain boundary kinetics, fundamentally limiting its applicability to the time-varying thermal profiles characteristic of industrial heat treatment processes. This study extends the previous framework by incorporating Feature-wise Linear Modulation (FiLM) for thermal conditioning to predict grain growth under complex, time-varying thermal profiles. The model was trained on a large
dataset of grain growth
evolution under thermal profiles with heating and cooling rates ranging from 0.01 kelvin per second to 10 kelvin per second. The results demonstrate that the proposed thermal conditioning mechanism enables the model to capture the influence of variable thermal profiles on grain boundary migration kinetics. Across the three test scenarios of increasing complexity, the model achieved a Structural Similarity Index Measure (SSIM) of up to 0.93 and mean grain size error below 3.2%. Despite the architectural extensions, inference time remains on the order of seconds per prediction sequence, preserving the computational advantage over PDE-based simulations.
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Materials Science
Photoelectron angular distribution as a linear polarization analyzer for soft and tender X-rays
Yoshiyuki Ohtsubo and Hiroaki Kimura
Although the polarization of soft and tender X-rays is widely used to investigate the diverse physical properties of materials, experimental methods to determine the polarization of tender X-rays (1.5-3.0 keV) remain limited. To address this issue, we propose a method based on the photoelectron angular distribution to detect the polarization of X-rays in this energy range. The angular distribution of photoelectrons emitted from carbon targets was measured using linearly polarized 0.2 to 3.0 keV synchrotron radiation. The photoelectron intensity depends on the angle between the
photon's electric field vector and the direction at which the photoelectron is emitted from the target. This result indicates that the photoelectron angular distribution can be used to reliably determine the linear polarization of soft and tender X-rays over a wide range of energy.
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Materials Science
Stabilizing Magnetic Bubble Domains in Epitaxial 2D Magnet/Topological Insulator Heterostructures through Interfacial Interactions
Thow Min Jerald Cham, Mowen Zhao, Wenyi Zhou et al. (+14 more)
Epitaxial
heterostructures of two-dimensional van der Waals magnets and topological
insulators offer a powerful platform for probing interfacial
spin interactions that govern
magnetic textures in low-dimensional
quantum systems, while simultaneously enabling highly efficient, atomically thin
spin-orbit-torque
memory and computing architectures. Despite this promise, the fundamental role of these interfacial interactions in determining
magnetic domain-phase stability remain largely uncharted. Here, we perform scanning transmission X-ray microscopy to image nanoscale
magnetic textures in epitaxial Fe3GeTe2 Bi2Te3
heterostructures, enabled by a thermal-release-tape dry transfer process onto X-ray transparent silicon-rich nitride membranes. Under zero-field-cooled conditions, we observe robust bubble domain phases from 75 to 165 K, and across different number of folds of the multilayer Fe3GeTe2 Bi2Te3
heterostructures. This is in stark contrast with exfoliated single-
crystal Fe3GeTe2 flakes, where ZFC stripe domains are observed for flakes thicker than 20 nm and no domains have been reported for thin flakes less than 15 nm. First-principles calculations and micromagnetic simulations reveal that interfacial coupling to Bi2Te3 modifies the
magnetic anisotropy and introduces interfacial Dzyaloshinskii-Moriya interaction, shifting the
magnetic phase space towards bubble-domain stabilization without field-cooling. Together, our results offer a new strategy for phase-selective control of
magnetic domains through interfacial engineering.
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All authors Thow Min Jerald Cham, Mowen Zhao, Wenyi Zhou, Andrew Koerner, Dang-Khoa Le, Ziling Li, Lukas Powalla, Derek Bergner, Eklavya Thareja, Camelia Selcu, Sadikul Alam, Sebastian Wintz, Markus Weigand, Jinwoo Hwang, Jacob Gayles, Roland Kawakami, Yunqiu Kelly Luo
Materials Science
Fundamentals and applications of aberration corrected high resolution transmission electron microscopy in materials science
Ranjan Datta, Sneha Kobri M. and Sudip Mahato
In this review article fundamentals of aberration corrected phase contrast transmission electron microscopy for the structural characterization of materials at atomic length scale is presented. The word structure entails atomic arrangement as well as electronic structure information of the materials. The article summarily covers a range of topics on the basics of aberrations, aberration correctors, direct image interpretation with negative Cs phase contrast microscopy, a discussion in comparison with the competitive atomic resolution phase contrast methods for example, off-axis electron holography, electron ptychography, differential phase contrast microscopy. Additionally, various examples of quantitative imaging of materials at atomic length scale, associated image simulation and reconstruction methods for retrieving the phase information are presented. With the tremendous advancement in instrumentation and recording devices, potential future perspective of such tools and methods in solving challenging materials science problems are outlined.
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Materials Science
ChargeFlow: Flow-Matching Refinement of Charge-Conditioned Electron Densities
Tri Minh Nguyen, Sherif Abdulkader Tawfik, Truyen Tran et al. (+1 more)
Accurate charge densities are central to electronic-structure theory, but computing charge-state-dependent densities with density functional theory remains too expensive for large-scale screening and defect workflows. We present ChargeFlow, a flow-matching refinement model that transforms a charge-conditioned superposition of atomic densities into the corresponding DFT electron density on the native periodic real-space grid using a 3D U-Net velocity field. Trained on 9,502 charged Materials Project-derived calculations and evaluated on an external 1,671-structure
benchmark spanning perovskites, charged defects, diamond defects, metal-organic frameworks, and organic
crystals, ChargeFlow is not uniformly best on every in-distribution class but is strongest on problems dominated by nonlocal charge redistribution and charge-state extrapolation, improving deformation-density error from 3.62% to 3.21% and charge- response cosine similarity from 0.571 to 0.655 relative to a ResNet baseline. The predicted densities remain chemically useful under downstream analysis, yielding successful Bader partitioning on all 1,671
benchmark structures and high-fidelity electrostatic potentials, which positions flow matching as a practical density-refinement strategy for charged materials.
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All authors Tri Minh Nguyen, Sherif Abdulkader Tawfik, Truyen Tran, Svetha Venkatesh
Materials Science
An Efficient High-Degree, High-Order Equivariant Graph Neural Network for Direct Crystal Structure Optimization
Ziduo Yang, Wei Zhuo, Huiqiang Xie et al. (+2 more)
Crystal structure optimization is fundamental to materials modeling but remains computationally expensive when performed with density-functional theory (DFT). Machine-learning (ML) approaches offer substantial acceleration, yet existing methods face three key limitations: (i) most models operate solely on atoms and treat
lattice vectors implicitly, despite their central role in structural optimization; (ii) they lack efficient mechanisms to capture high-degree angular information and higher-order
geometric correlations simultaneously, which are essential for distinguishing subtle structural differences; and (iii) many pipelines are multi-stage or iterative rather than truly end-to-end, making them prone to error accumulation and limiting scalability. Here we present E$^{3}$Relax-H$^{2}$, an end-to-end high-degree, high-order equivariant graph neural network that maps an initial
crystal directly to its relaxed structure. The key idea is to promote both atoms and
lattice vectors to graph nodes, enabling a unified and
symmetry-consistent representation of structural degrees of freedom. Building on this formulation, E$^{3}$Relax-H$^{2}$ introduces two message-passing mechanisms: (i) a high-degree, high-order message-passing module that efficiently captures high-degree angular representations and high-order many-body correlations; and (ii) a
lattice-atom message-passing module that explicitly models the bidirectional coupling between
lattice deformation and atomic displacement. In addition, we propose a differentiable periodicity-aware Cartesian displacement loss tailored for one-shot structure prediction under periodic boundary conditions.
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All authors Ziduo Yang, Wei Zhuo, Huiqiang Xie, Xiaoqing Liu, Lei Shen
Materials Science · Cross-listed from quant-ph
Quantum Computing and Error Mitigation with Deep Learning for Frenkel Excitons
Yi-Ting Lee, Vijaya Begum-Hudde, Barbara A. Jones et al. (+1 more)
Quantum computers, currently in the noisy intermediate-scale
quantum (NISQ) era, have started to provide scientists with a novel tool to explore
quantum physics and chemistry. While several electronic systems have been extensively studied, Frenkel
excitons, as prototypical optical excitations, remain among the less-explored applications. Here, we first use variational
quantum deflation to calculate the eigenstates of the Frenkel
Hamiltonian and evaluate the observables based on the oscillator strength for each eigenstate. Furthermore, using NISQ
quantum computers requires performing error mitigation techniques alongside simulations. To deal with noisy
qubits, we developed a deep-learning-based framework combined with a post-selection technique to learn the noise pattern and mitigate the error. Our mitigation methods work well and outperform the conventional post-selection and remain valid on real hardware.
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All authors Yi-Ting Lee, Vijaya Begum-Hudde, Barbara A. Jones, André Schleife