Materials Science · Cross-listed from cond-mat.soft
LiquiFab – Building with liquids in weightlessness
Erez Hochman, Aaron Sprecher, Kateryna Suzina et al. (+4 more)
Existing digital manufacturing methods can be broadly divided into subtractive approaches, where material is removed from a bulk to reveal the desired form, and additive methods, in which material is introduced voxel-by-voxel to create an object. We here show a fundamentally different method for the fabrication of three-dimensional objects that is neither subtractive nor additive. Instead of removal or layer-by-layer material deposition, in LiquiFab we shape an entire volume of
liquid polymer by subjecting it to a set of geometrical constraints under conditions of weightlessness. The physics of
liquid interfaces then drives the
polymer to naturally adopt a configuration that minimizes its surface energy. On Earth, we achieve weightlessness through neutral buoyancy, and show that a small, well-defined set of boundary surfaces can be used to drive the
liquid into a desired form that is then solidified. By sequentially applying this process, complex architectures can be assembled from successive
liquid-formed elements. Unlike additive manufacturing, where every point within the object must be individually visited by a print head or light field, LiquiFab forms the entire structure simultaneously. This makes the process highly scalable and opens the door to rapid manufacturing of large objects both on Earth and in space.
Read the full abstract ▾
All authors Erez Hochman, Aaron Sprecher, Kateryna Suzina, Amir Mann, Yuval Mihalovich, Valeri Frumkin, Moran Bercovici
Materials Science
QMBench: A Research Level Benchmark for Quantum Materials Research
Yanzhen Wang, Yiyang Jiang, Diana Golovanova et al. (+10 more)
We introduce QMBench, a comprehensive
benchmark designed to evaluate the capability of large
language model
agents in
quantum materials research. This specialized
benchmark assesses the model's ability to apply condensed matter physics knowledge and computational techniques such as density functional theory to solve research problems in
quantum materials science. QMBench encompasses different domains of the
quantum material research, including structural properties, electronic properties, thermodynamic and other properties,
symmetry principle and computational methodologies. By providing a standardized evaluation framework, QMBench aims to accelerate the development of an AI scientist capable of making creative contributions to
quantum materials research. We expect QMBench to be developed and constantly improved by the research community.
Read the full abstract ▾
All authors Yanzhen Wang, Yiyang Jiang, Diana Golovanova, Kamal Das, Hyeonhu Bae, Yufei Zhao, Huu-Thong Le, Abhinava Chatterjee, Yunzhe Liu, Chao-Xing Liu, Felipe H. da Jornada, Binghai Yan, Xiao-Liang Qi
Materials Science
The Madelung Problem of Finite Crystals
Yihao Zhao, Yang He and Zhonghan Hu
The Coulomb potential at an interior ion in a finite
crystal of size $p$ is given by a linear superposition of contributions from displacement vectors ${\mathbf r}=(x,y,z)$ to its neighbors. This additive structure underlies universal relationships among Madelung constants and applies to both standard periodic boundary conditions and alternative Clifford supercells. Each pairwise contribution decomposes into three physically distinct components: a periodic bulk term, a quadratic boundary term, and a finite-size correction whose leading order term is $[24r^4-40(x^4+y^4+z^4)]/[9\sqrt{3} (2p+1)^2]$ for cubic
crystals with unit
lattice constant. Combining this decomposition with linear superposition yields a rapidly convergent direct-summation scheme, accurate even at $p=1$ ($3^3$ unit
cells), enabling hands-on calculations of Madelung constants for a wide range of ionic
crystals.
Read the full abstract ▾
Materials Science · Cross-listed from cs.LG
Microstructure-based Variational Neural Networks for Robust Uncertainty Quantification in Materials Digital Twins
Andreas E. Robertson, Samuel B. Inman, Ashley T. Lenau et al. (+4 more)
Aleatoric uncertainties - irremovable variability in microstructure morphology, constituent behavior, and processing conditions - pose a major challenge to developing uncertainty-robust digital twins. We introduce the Variational Deep Material Network (VDMN), a physics-informed surrogate model that enables efficient and probabilistic forward and inverse predictions of material behavior. The VDMN captures microstructure-induced variability by
embedding variational distributions within its hierarchical, mechanistic architecture. Using an analytic propagation scheme based on Taylor-series expansion and automatic differentiation, the VDMN efficiently propagates uncertainty through the network during training and prediction. We demonstrate its capabilities in two digital-twin-driven applications: (1) as an uncertainty-aware materials digital twin, it predicts and experimentally validates the nonlinear mechanical variability in additively manufactured
polymer composites; and (2) as an inverse calibration engine, it disentangles and quantitatively identifies overlapping sources of uncertainty in constituent properties. Together, these results establish the VDMN as a foundation for uncertainty-robust materials digital twins.
Read the full abstract ▾
All authors Andreas E. Robertson, Samuel B. Inman, Ashley T. Lenau, Ricardo A. Lebensohn, Dongil Shin, Brad L. Boyce, Remi M. Dingreville
Materials Science
Breaking the 800 mV open-circuit voltage barrier in antimony sulfide photovoltaics
Jiacheng Zhou, Xinwei Wang, Tianle Shi et al. (+6 more)
Sb2S3 is a promising material for low-toxicity, high-stability next-generation photovoltaics. Despite high optical limits in efficiency, progress in improving its device performance has been limited by severe voltage losses. Recent spectroscopic investigations suggest that self-trapping occurs in Sb2S3, limiting the open-
circuit voltage (Voc) to a maximum of approximately 800 mV, which is the level the field has asymptotically approached. In this work, we surpass this voltage barrier through reductions in the defect density in Sb2S3 thin films by modulating the growth mechanism in chemical bath deposition using citrate ligand additives. Deep level transient spectroscopy identifies two deep traps 0.4-0.7 eV above the valence band maximum, and, through first-principles calculations, we identify these to likely be S vacancies, or Sb on S anti-sites. The concentrations of these traps are lowered by decreasing the grain boundary density from 1114+/-52 nm/um2 to 585+/-10 nm/um2, and we achieve a Voc of 824 mV, the record for Sb2S3
solar cells. This work addresses the debate in the field around whether Sb2S3 is limited by defects or self-trapping, showing that it is possible to improve the performance towards the radiative limit through careful defect engineering.
Read the full abstract ▾
All authors Jiacheng Zhou, Xinwei Wang, Tianle Shi, Lei Wan, Junzhi Ye, Zhiqiang Li, Aron Walsh, Robert L. Z. Hoye, Ru Zhou
Materials Science · Cross-listed from physics.comp-ph
Long-range electrostatics for machine learning interatomic potentials is easier than we thought
Dongjin Kim and Bingqing Cheng
The lack of long-range electrostatics is a key limitation of modern machine learning interatomic potentials (MLIPs), hindering reliable applications to interfaces, charge-transfer reactions, polar and ionic materials, and biomolecules. In this Perspective, we distill two design principles behind the Latent Ewald Summation (LES) framework, which can capture long-range interactions, charges, and electrical response just by learning from standard energy and force training data: (i) use a Coulomb functional form with environment-dependent charges to capture electrostatic interactions, and (ii) avoid explicit training on ambiguous density functional theory (DFT) partial charges. When both principles are satisfied, substantial flexibility remains: essentially any short-range MLIP can be augmented; charge equilibration schemes can be added when desired; dipoles and Born effective charges can be inferred or finetuned; and charge/
spin-state
embeddings or tensorial targets can be further incorporated. We also discuss current limitations and open challenges. Together, these minimal, physics-guided design rules suggest that incorporating long-range electrostatics into MLIPs is simpler and perhaps more broadly applicable than is commonly assumed.
Read the full abstract ▾
Materials Science
Topical Review: The rise of Klein tunneling in low-dimensional materials and superlattices
Yonatan Betancur-Ocampo, Guillermo Monsivais and Vít Jakubský
We review recent advances in Klein and anti-Klein tunneling in one- and two-dimensional materials. Using a general tight-binding framework applied to multiple periodic systems, we establish the criteria for the emergence of Klein tunneling based on the conservation of an effective reduced pseudospin. The inclusion of higher-order terms in the wave vector leads to nontrivial matching conditions for wave scattering at interfaces. We further examine the emergence of multiple types of Klein tunneling in two-dimensional materials beyond
graphene, including phosphorene and borophene, as well as in one-dimensional systems such as Su-Schrieffer-Heeger
lattices. Finally, we discuss how these tunneling phenomena can be tested in both synthesized and artificial
lattices, including elastic metamaterials, optical, photonic, phononic, and superconducting platforms, demonstrating the universality of Klein tunneling across different wave natures and length scales.
Read the full abstract ▾
Materials Science · Cross-listed from hep-ph
A Numerical Method for the Efficient Calculation of Scattering Form Factors
Carlos Blanco, Benjamin Lillard and Jack D. Shergold
Scintillating molecular
crystals have emerged as
prime candidates for directional dark matter detector targets. This anisotropy makes them exquisitely sensitive due to the daily modulation induced by the directional dark matter wind. However, predicting the interaction rate for arbitrary molecules requires accurate modeling of the many-body ground as well as excited states, a task that has been historically computationally expensive. Here, we present a theory and computational framework for efficiently computing dark matter scattering form factors for molecules. We introduce SCarFFF, a GPU-accelerated code to compute the fully three-dimensional anisotropic molecular form factor for arbitrary molecules. We use a full time-dependent density functional theory framework to compute the lowest-lying singlet excited states, adopting the B3YLP exchange functional and a double-
zeta Gaussian basis set. Once the many-body electronic structure is computed, the form factors are computed in a small fraction of the time from the transition density
matrix. We show that ScarFFF can compute the first 12 form factors for a molecule of 10 heavy atoms in approximately 5 seconds, opening the door to accurate, high-throughput material screening for optimal directional dark matter detector targets. Our code can perform the calculation in three independent ways, two semi-analytical and one fully numeric, providing optimised methods for every precision goal.
Read the full abstract ▾
Materials Science · Cross-listed from cond-mat.supr-con
Net Magnetization and Inhomogeneous Magnetic Order in a High-Tc Nickelate Superconductor
Alexander J. Grutter, Nurul Fitriyah, Brian B. Maranville et al. (+10 more)
High-temperature and high-
magnetic-field-induced re-entrant superconductivity has been discovered in the infinite-layer nickelate $\mathrm{Sm_{1-x-y} Eu_x Ca_y Ni O_2}$ (SECNO). Infinite-layer nickelates are the closest known analogues of high-$\mathrm{T}_c$ cuprate
superconductors, yet they host distinct
magnetic ground states. Using low-energy
muon spin relaxation and polarized
neutron reflectometry, we reveal the
magnetic order in SECNO. We find that
magnetic freezing occurs at a higher-temperature than in other nickelate compounds, and that a substantial net magnetization of 55 $\,\mathrm{kA}\,\mathrm{m}^{-1}$ $\pm10 \,\mathrm{kA}\,\mathrm{m}^{-1}$ emerges and remains largely unchanged across the superconducting transition. The magnetism in SECNO is disordered and nonuniform.
Read the full abstract ▾
All authors Alexander J. Grutter, Nurul Fitriyah, Brian B. Maranville, Saurav Prakash, Andreas Suter, Jochen Stahn, Gianluca Janka, Xing Gao, King Yau Yip, Zaher Salman, Thomas Prokscha, Julie A. Borchers, Ariando Ariando
Materials Science
An interface crack in 1d piezoelectric quasicrystal under antiplane mechanical loading and electric field
Mohammed Altoumaimi and V.V. Loboda
The present study provides the consideration of a mode III interface crack in one-dimentional (1D) piezoelectric quasicrystal under antiplane
phonon and phason loading and inplane electric field. Due to complex function approach all required electromechanical parameters are presented through vector-functions analytic in the whole complex plane except the crack region. The cases of electrically impermeable (insulated) and electrically limited permeable conditions on the crack faces are considered. In the first case a vector
Hilbert problem in the complex plane is formulated and solved exactly and in the second one the quadratic equation with respect to the electric flux through the crack region is obtained additionally. Its solution permits to find
phonon and phason stresses, displacement jumps (sliding) and also electric characteristics along the material interface. Analytical formulas are also obtained for the corresponding stress intensity factors related to each field. The numerical computations for three selected variants of the loading conditions was conducted and the resulting field distributions are visualised on the crack continuation beyond the crack and also inside of the crack region.
Read the full abstract ▾
Materials Science
Experimentally Mapping the Phase Diagrams of Photoexcited Small Polarons
Jocelyn L. Mendes and Scott K. Cushing
Understanding the fundamental properties that dictate photoexcited polarons in materials is critical to tuning their properties. Theoretical models of polarons have only recently been extended to the excited state. Experimental measurements of polaron formation and transport have been widely undertaken across a range of materials, from photocatalysts and
superconductors to soft conducting
polymers. Here, we map thermalized excited state experimental measurements of quantities such as polaron strength onto phase diagrams of the Holstein, Hubbard-Holstein, and t-J-Holstein models. This work demonstrates that tuning electron-
phonon coupling strength, electron localization, and
spin exchange can be leveraged to suppress or control polarons in transition metal
oxides. We find that the t-J-Holstein model provides the clearest qualitative description of electron polarons in the measured iron
oxides and could be generally applied to a wide range of systems that exhibit polaron formation in the excited state. This work combines experimental data with ground state models to provide a qualitative parameter space for informing photoexcited electron polaron design, under which excited state polaronic behavior can be classified within ground-state calculable models.
Read the full abstract ▾
Materials Science
Interplay of Defects and the Charge Density Wave State in Hf-Doped ZrTe$_{3}$
Ghilles Ainouche, Resmi Sudheer, Susree Mohapatra et al. (+6 more)
We carry out temperature-dependent scanning tunneling microscopy (STM) studies of the charge density wave (CDW) compound ZrTe$_3$ which is intentionally doped with Hf. Previous bulk studies tie Hf doping to an enhancement of the CDW transition temperature (T$_{CDW}$). In our work, by combining STM measurements with density functional theory (DFT) calculations, we observe and identify multiple defects in Zr$_{0.95}$Hf$_{0.05}$Te$_3$. Surprisingly, instead of finding clear structural or electronic signatures associated with Hf dopants, we determine the origin of the observed defects are consistent with Te and Zr vacancies. Further, our temperature dependent STM measurements allow us to examine CDW pinning to both types of observed defects below and above T$_{CDW}$.
Read the full abstract ▾
All authors Ghilles Ainouche, Resmi Sudheer, Susree Mohapatra, Boning Yu, Muhammad Suhayb Malik, Yu Liu, Cedomir Petrovic, Abhilash Ravikumar, Michael C. Boyer
Materials Science
InfinityEBSD : Metrics-Guided Infinite-Size EBSD Map Generation With Diffusion Models
Sterley Labady, Youssef Mesri, Daniel Pino Munoz et al. (+2 more)
Materials performance is deeply linked to their microstructures, which govern key properties such as strength, durability, and fatigue resistance. EBSD is a major technique for characterizing these microstructures, but acquiring large and statistically representative EBSD maps remains slow, costly, and often limited to small regions. In this work, we introduce InfinityEBSD, a
diffusion-based method for generating monophase realistic EBSD maps of arbitrary size, conditioned on physically meaningful microstructural metrics. This approach supports two primary use cases: extending small experimental EBSD maps to arbitrary sizes, and generating entirely new maps directly from statistical descriptors, without any input map. Conditioning is achieved through eight microstructural descriptors, including grain size, grain perimeter, grain inertia ratio, coordination number and disorientation angle distribution, allowing the model to generate maps that are both visually realistic and physically interpretable. A patch-wise
geometric extension strategy ensures spatial continuity across grains, enabling the model to produce large-scale EBSD maps while maintaining coherent grain boundaries and orientation transitions. The generated maps can also be exported as valid Channel Text Files (CTF) for immediate post-processing and analysis in software such as MTEX or simulation environments like DIGIMU. We quantitatively validate our results by comparing distributions of the guiding metrics before and after generation, showing that the model respects the statistical targets while introducing morphological diversity. InfinityEBSD demonstrates that
diffusion models, guided by physical metrics, can bridge the gap between synthetic and realistic materials representation, paving the way for future developments such as 3D realistic microstructure generation from 2D data.
Read the full abstract ▾
All authors Sterley Labady, Youssef Mesri, Daniel Pino Munoz, Baptiste Flipon, Marc Bernacki
Materials Science · Cross-listed from cond-mat.soft
Dynamics of Reversible Plasticity in an Amorphous Solid
Zhicheng Wang and Nathan C. Keim
Local rearrangements are the elements of plastic deformation in an amorphous solid. In oscillatory shear, they can switch reversibly between two distinct configurations. While these repeating relaxations are typically considered in the limit of slow driving, their dynamics is less well understood. We perform experiments on a colloidal amorphous solid at an oil-water interface. The rearrangement timescales we observe span at least 1 decade, with no apparent upper bound. As frequency is increased, individual rearrangements appear faster and more hysteretic, but may disappear entirely above a crossover frequency – suggesting that in practical experiments, the slowest rearrangements may be latent. We show how to find the effective potential energy that reproduces a particle's frequency-dependent motion. In rare cases, this potential energy has only one minimum. Our results have implications for the energy landscapes and rheology of amorphous or glassy solids, for sound propagation in nonlinear media, and for mechanical
memory and history-dependence.
Read the full abstract ▾
Materials Science
Bayesian Methods for the Investigation of Temperature-Dependence in Conductivity
Andrew R. McCluskey, Samuel W. Coles and Benjamin J. Morgan
Temperature-dependent transport data, including
diffusion coefficients and ionic conductivities, are routinely analysed by fitting empirical models such as the Arrhenius equation. These fitted models yield parameters such as the activation energy, and can be used to extrapolate to temperatures outside the measured range. Researchers frequently face challenges in this analysis: quantifying the uncertainty of fitted parameters, assessing whether the data quality is sufficient to support a particular empirical model, and using these models to predict behaviour at temperatures outside the measured range.
Bayesian methods offer a coherent framework that addresses all of these challenges. This tutorial introduces the use of
Bayesian methods for analysing temperature-dependent transport data, covering parameter estimation, model selection, and extrapolation with uncertainty propagation, with illustrative examples from molecular dynamics simulations of superionic materials.
Read the full abstract ▾
Materials Science
Mechanistic Origin of Charge Separation and Enhanced Photocatalytic Activity in D-$\pi$-A-Functionalized UiO-66-NH$_2$ MOFs
Anastasiia Kultaeva, Volodymyr Vasylkovskyi, Andreas Sperlich et al. (+4 more)
Donor-$\pi$-acceptor (D-$\pi$-A) functionalization of MOF linkers can enhance visible-light photocatalytic activity, yet the mechanisms responsible for these effects remain unclear. Here we combine EPR spectroscopy, transient photoluminescence, and first-principles calculations to examine how diazo-coupled anisole, diphenylamine (DPA), and N,N-dimethylaniline (NNDMA) groups modify the photophysics of UiO-66-NH$_2$. All donor units introduce new occupied states near the valence-band edge, enabling charge separation through dye-to-framework electron transfer. Among them, the anisole-modified material stands out for facilitating efficient intersystem crossing into a triplet charge-transfer configuration that suppresses fast recombination and yields long-lived charge carriers detectable by photo-EPR. Meanwhile, bulkier donors such as DPA and NNDMA - despite their stronger electron-donating character - also tend to introduce defect-associated trap states. These results underscore the interplay between donor-induced electronic-structure changes, triplet pathways, and defect-mediated recombination, offering a mechanistic basis for tuning photocatalytic response in D-$\pi$-A-modified MOFs.
Read the full abstract ▾
All authors Anastasiia Kultaeva, Volodymyr Vasylkovskyi, Andreas Sperlich, Eugenio Otal, Katsuya Teshima, Wolf Gero Schmidt, Timur Biktagirov
Materials Science · Cross-listed from cond-mat.mes-hall
MOF-derived Fe-doped $\delta$-MnO$_2$ nanoflowers as oxidase mimics: Chromogenic sensing of Hg$^{2+}$ and hydroquinone in aqueous media
Udisha Duhan, Arnab Pan, Ritesh Dubey et al. (+3 more)
Structure and morphology play a crucial role in enhancing the biomimetic oxidase activity of nanozymes. In this study, a facile in situ chemical oxidation strategy was employed to synthesize MOF-derived MnO$_x$, utilizing the structural features of the parent MOF to enhance oxidase-mimicking activity. We systematically investigated the effects of phase
evolution, structural modulation, and morphology on the oxidase activity of MnO$_x$ with Fe substitution. The oxidase-like activity was evaluated using the chromogenic substrate 3,3$'$,5,5$'$-tetramethylbenzidine (TMB), which produced a blue-colored oxidized TMB (ox-TMB) with an absorption peak at 652~nm upon oxidation. While all Fe-doped MnO$_x$ nanostructures exhibited oxidase-like activity, the 10% Fe-doped sample (10Fe-MnO$_x$) demonstrated the highest performance, likely due to a synergistic effect of structure, morphology, and the presence of oxygen vacancies. The underlying oxidase mechanism was investigated using steady-state kinetics and electron paramagnetic resonance (EPR) analysis. In addition, a colorimetric assay was developed for the detection of Hg$^{2+}$ and hydroquinone (HQ) in real water samples collected from industrial and natural sources. The calculated detection limits of the 10Fe-MnO$_x$ colorimetric probe for HQ (1.74~$\mu$M) and Hg$^{2+}$ (0.47~$\mu$M) outperformed those of conventional metal
oxide-based nanozymes. These findings pave the way for the development of easily synthesizable, scalable, and highly sensitive oxidase-based MOF-derived metal
oxide nanomaterials with significant potential in biological and environmental applications.
Read the full abstract ▾
All authors Udisha Duhan, Arnab Pan, Ritesh Dubey, Samar Layek, Sushil Kumar, Tapas Goswami
Materials Science
Corrosion-resistant and conductive Ti-Nb-O coatings tailored for ultra-low Pt-loaded BPPs and PTLs in PEM electrolyzers
David Kolenatý, Jiří Čapek, Stanislav Haviar et al. (+6 more)
We develop highly corrosion-resistant and conductive Ti-Nb-O coatings for metallic components – bipolar plates (BPPs) and porous transport layers (PTLs) – in PEM water electrolyzers. Using reactive high-power impulse magnetron sputtering (HiPIMS), we deposit compact 200 nm
bilayer coatings onto SS316L substrates, systematically tailoring their composition. By precisely controlling oxygen partial pressure and Nb/Ti ratio, we adjust stoichiometry and structure, directly affecting electrical resistivity and corrosion resistance. We examine interfacial contact resistance (ICR) and electrochemical parameters before and after accelerated corrosion testing. Optimized coatings exhibit resistivity on the order of 10^-4 Ohmcm and extremely low corrosion current densities (J_corr = 0.01-0.08 uA/cm^2), well below the U.S. DOE 2026 target. Most importantly, these coatings enable the ICR target after accelerated corrosion testing with a Pt overlayer as thin as 5 nm, reducing Pt loading by up to two orders of magnitude compared to conventional approaches.
Read the full abstract ▾
All authors David Kolenatý, Jiří Čapek, Stanislav Haviar, Jiří Rezek, Radomír Čerstvý, Akash Kumar, Kalyani Shaji, Mariia Zhadko, Petr Zeman
Materials Science
Design principles for metal-organic receptors targeting optical recognition of Pd(II) in environmental matrices
Sudhanshu Naithani, Pramod Kumar, Ritesh Dubey et al. (+4 more)
A precise detection of palladium (Pd) ions is a critical challenge with significant socio-economic implications across various industrial and chemical sectors. Due to its widespread use and poor biodegradability, Pd2+ accumulates in environmental ecosystems, posing severe risks to both the environment and living organisms. Consequently, there is a strong demand for selective, sensitive, and user-friendly detection methods. Among emerging strategies, optical detection techniques (both luminescent and colorimetric) using metal-based receptors have gained considerable
attention. These sensors offer distinct advantages over traditional organic probes, including large Stokes shifts, long emission lifetimes, exceptional photostability, enhanced water solubility, recyclability, and remarkable chemical versatility. These attributes make them highly suitable for diverse applications in sensing and bioanalytical fields. This review provides a comprehensive overview of recent advancements in luminescent and colorimetric metal-based probes, including metal complexes and metal-organic frameworks (MOFs), for the selective detection of Pd2+. It discusses key design strategies, critical performance factors, and future prospects, offering valuable insights for researchers working on next-generation sensing platform.
Read the full abstract ▾
All authors Sudhanshu Naithani, Pramod Kumar, Ritesh Dubey, Franck Thetiot, Samar Layek, Tapas Goswami, Sushil Kumar
Materials Science
Lanthanide Ion Electronic Structure Controls Magnetic Excitations in Topological Quantum Ferrimagnets $LnMn_{6}Sn_{6}$ (Ln = Tb, Dy, Ho)
Kelsey A. Collins, Jacob Pfund, Michael R. Page et al. (+3 more)
The $LnMn_{6}Sn_{6}$ family of topological magnets is a promising platform for next-generation spintronic and magnonic technologies. However, the influence of the lanthanide ion ($Ln^{3+}$) on the excited-state
spin dynamics, or
magnons, remains a critical knowledge gap. Here, we present the first comparative study of the
magnetic dynamics in $LnMn_{6}Sn_{6}$ materials (Ln = Tb, Dy, Ho) using Brillouin light scattering. Our findings reveal a direct correlation between the lanthanide ion's intrinsic properties and the
magnon behavior. We demonstrate that the
magnon frequency in the absence of an applied
magnetic field is primarily dictated by the strength of the lanthanide exchange coupling, as modeled by its relationship with the de Gennes factor. The response of the
magnon to an applied field is influenced by material's gyromagnetic ratio and the overall anisotropy of the material, which are dictated by total angular momentum and the anisotropy of the lanthanide sublattice, respectively. These results establish that simple lanthanide substitution provides a powerful and predictable method for tuning
magnon properties, enabling the rational design of materials for advanced technological applications.
Read the full abstract ▾
All authors Kelsey A. Collins, Jacob Pfund, Michael R. Page, Menka Jain, Michael A. Susner, Michael J. Newburger
Materials Science · Cross-listed from cond-mat.str-el
Revisiting the Broken Symmetry Phase of Solid Hydrogen: A Neural Network Variational Monte Carlo Study
Shengdu Chai, Chen Lin, Xinyang Dong et al. (+4 more)
The
crystal structure of high-pressure solid hydrogen remains a fundamental open problem. Although the research frontier has mostly shifted toward ultra-high pressure phases above 400 GPa, we show that even the broken
symmetry phase observed around 130~GPa requires revisiting due to its intricate coupling of electronic and
nuclear degrees of freedom. Here, we develop a first principle
quantum Monte Carlo framework based on a deep neural network wave function that treats both electrons and
nuclei quantum mechanically within the constant pressure ensemble. Our calculations reveal an unreported ground-state structure candidate for the broken
symmetry phase with $Cmcm$ space group
symmetry, and we test its stability up to 96 atoms. The predicted structure quantitatively matches the experimental equation of state and gives the closest x-ray diffraction peak-position match among the tested candidates. Furthermore, our group-theoretical analysis provides a
symmetry-counting compatibility check between the $Cmcm$ structure and existing Raman and infrared spectroscopic data. Crucially, static density functional theory calculation reveals the $Cmcm$ structure as a dynamically unstable saddle point on the Born-Oppenheimer potential energy surface, demonstrating that a full
quantum many-body treatment of the problem is necessary. These results shed new light on the phase diagram of high-pressure hydrogen and call for further experimental verifications.
Read the full abstract ▾
All authors Shengdu Chai, Chen Lin, Xinyang Dong, Yuqiang Li, Wanli Ouyang, Lei Wang, X.C. Xie
Materials Science · Cross-listed from quant-ph
Quantum heat current in Terahertz-driven phonon systems
Yulong Qiao and Richard. Matthias Geilhufe
The advent of high-intensity ultrafast
laser pulses has opened new opportunities for controlling and designing
quantum materials. In particular, terahertz (THz) pulses can resonantly drive optical
phonon modes, enabling dynamic manipulation of
lattice degrees of freedom. In this work, we investigate the ultrafast
quantum thermodynamics of optical
phonon mode driven by a THz pulse by treating the
phonon as an open
quantum system coupled to a thermal environment within a Caldeira-Leggett-type framework. We derive the
quantum heat current between the
phonon and the bath and analyze its behavior under realistic pulse protocols. Our results demonstrate that ultrafast
laser driving can reveal and even induce significant deviations from the commonly adopted Markovian approximation, thereby providing a pathway to probe and control non-Markovian dissipation in driven solid-state systems.
Read the full abstract ▾
Materials Science · Cross-listed from stat.ML
Generative Multi-Objective Bayesian Optimization with Scalable Batch Evaluations for Sample-Efficient De Novo Molecular Design
Madhav R. Muthyala, Farshud Sorourifar, Tianhong Tan et al. (+2 more)
Designing molecules that must satisfy multiple, often conflicting objectives is a central challenge in molecular discovery. The enormous size of chemical space and the cost of high-fidelity simulations have driven the development of machine learning-guided strategies for accelerating design with limited data. Among these,
Bayesian optimization (BO) offers a principled framework for sample-efficient search, while generative models provide a mechanism to propose novel, diverse candidates beyond fixed libraries. However, existing methods that couple the two often rely on continuous latent spaces, which introduces both architectural
entanglement and scalability challenges. This work introduces an alternative, modular "generate-then-optimize" framework for de novo multi-objective molecular design/discovery. At each iteration, a generative model is used to construct a large, diverse pool of candidate molecules, after which a novel acquisition function, qPMHI (multi-point Probability of Maximum Hypervolume Improvement), is used to optimally select a batch of candidates most likely to induce the largest Pareto front expansion. The key insight is that qPMHI decomposes additively, enabling exact, scalable batch selection via only simple ranking of probabilities that can be easily estimated with Monte Carlo sampling. We
benchmark the framework against state-of-the-art latent-space and discrete molecular optimization methods, demonstrating significant improvements across synthetic
benchmarks and application-driven tasks. Specifically, in a case study related to sustainable energy storage, we show that our approach quickly uncovers novel, diverse, and high-performing organic (quinone-based) cathode materials for aqueous redox flow battery applications.
Read the full abstract ▾
All authors Madhav R. Muthyala, Farshud Sorourifar, Tianhong Tan, You Peng, Joel A. Paulson
Materials Science
Thermal Control of Size Distribution and Optical Properties in Gallium Nanoparticles
S. Catalan-Gomez, M. Ibanez, J. Rico et al. (+5 more)
Gallium nanoparticles (Ga-NPs) exhibit promising plasmonic properties spanning ultraviolet to infrared spectral regions, making them suitable for diverse nanophotonic applications. However, the synthesis of uniform and ordered Ga-NP arrays remains challenging due to size heterogeneity arising from coarsening during physical deposition. Here, we systematically investigate the influence of substrate temperature on the nucleation, growth, and homogenization dynamics of Ga-NPs formed via Joule-effect thermal evaporation on GaAs substrates. Atomic force microscopy and scanning electron microscopy reveal temperature-dependent transitions from broad, bimodal size distributions to narrow dispersed arrays within an optimal substrate temperature range of 300-350{\deg}C. Above this window, increased
diffusion and desorption induce size increase, decreased density, and morphological relaxation manifested as NP shape flattening. Optical reflectance measurements identify distinct localized surface plasmon resonance (LSPR) modes whose energies are closely correlated with NP dimensions and aspect ratios. A figure of merit combining NP density and size uniformity quantifies optimal conditions at intermediate substrate temperatures, consistent with enhanced plasmonic quality factors derived from spectral LSPRs. In-situ post-deposition annealing experiments confirm Ostwald ripening as the dominant coarsening mechanism at elevated temperatures and highlight the necessity of rapid cooling and
oxide shell formation to stabilize homogeneous arrays. Cross-sectional transmission electron microscopy with electron energy-loss spectroscopy validates the core-shell structure of individual Ga-NPs, quantifies temperature-dependent
oxide shell thickening, and confirms the
liquid metal character of the Ga within the core...
Read the full abstract ▾
All authors S. Catalan-Gomez, M. Ibanez, J. Rico, V. Braza, D. F. Reyes, M. Villanueva-Blanco, E. Squiccimarro, J. M. Ulloa
Materials Science · Cross-listed from physics.optics
Hyperbolic-enhanced Raman scattering in van der Waals MoOCl2: from Fano resonances to picomolar detection
Anton Minnekhanov, Gleb Tikhonowski, Georgy Ermolaev et al. (+13 more)
Natural van der Waals (vdW)
crystals with
hyperbolic dispersion challenge artificial metamaterials but remain confined to the mid-infrared. The emergence of MoOCl2, a quasi-one-dimensional metal with in-plane hyperbolicity, overcomes this spectral limit, shifting the focus to the practical visible range. Here, using angle-resolved polarized Raman spectroscopy, we uncover pronounced polarization-dependent Fano lineshapes that reveal coupling between
phonons and the anisotropic metallic continuum, together with strong wavelength-dependent reshaping of the Raman polarization patterns governed by the anisotropic optical response of MoOCl2. Harnessing this optical anisotropy, we demonstrate "
Hyperbolic-Enhanced Raman" (HypER) scattering, where MoOCl2 provides polarization-tunable analytical enhancement factors exceeding 10^7 and picomolar-level detection of Rhodamine 6G down to 100 pM, without deliberate surface nanostructuring. These results establish air-stable MoOCl2 as a simple, wafer-compatible platform for visible-range
hyperbolic nanophotonics and lithography-free sensing.
Read the full abstract ▾
All authors Anton Minnekhanov, Gleb Tikhonowski, Georgy Ermolaev, Konstantin V. Kravtsov, Gleb Tselikov, Adilet Toksumakov, Aleksandr Slavich, Ivan Kazantsev, Ilia Fradkin, Andrey Vyshnevyy, Ivan Kruglov, Ilya Radko, Zdenek Sofer, Aleksey Arsenin, Kostya S. Novoselov, Valentyn Volkov
Materials Science · Cross-listed from cond-mat.str-el
Charge fluctuations and topological phases in Kitaev-Heisenberg ladders
M. G. Sousa, O. Ávalos-Ovando, E. Vernek et al. (+1 more)
We investigate the stability of topological phases in doped Kitaev-Heisenberg ladders by studying the competition with itinerant electrons and the associated charge fluctuations in a Hubbard model on a honeycomb ribbon geometry. We analyze the
evolution of string order parameters,
spin correlations, and charge fluctuations as functions of hopping amplitude and interaction strength in a half-filled band. Our results from density
matrix renormalization group (DMRG) calculations show that increasing electron bandwidth progressively suppresses the topological phases, shifting and narrowing their stability regions in the phase diagram. We identify the critical values of hopping where string order vanishes and characterize the interplay between
magnetic order and charge fluctuations. These findings provide insight into the robustness of topological phases against doping and charge dynamics, with implications for candidate Kitaev materials and engineered
quantum systems.
Read the full abstract ▾
All authors M. G. Sousa, O. Ávalos-Ovando, E. Vernek, S. E. Ulloa
Materials Science
Multipoles as quantitative order parameters for altermagnetic spin splitting
Francesco Martinelli, Anouk Droux and Claude Ederer
We establish a quantitative relation between the altermagnetic
spin-splitting and different higher order multipoles of the charge and magnetization density around the
magnetic atoms.
Magnetic multipoles such as octupoles or triakontadipoles have been suggested as potential ferroic order parameters for d- and g-wave altermagnetism, respectively, based mainly on qualitative
symmetry arguments. We use first-principles-based electronic structure calculations to establish a clear quantitative relation between the strength of the altermagnetic
spin splitting and the magnitude of certain local multipoles. We vary the magnitude of these multipoles either by applying an appropriate constraint on the charge density or by varying a corresponding structural distortion mode, using two simple perovskite materials, SrCrO3 and LaVO3, as model systems. Our analysis indicates that in general the altermagnetic
spin splitting is not exclusively determined by the lowest order nonzero
magnetic multipole, but results from a superposition of contributions from different multipoles with comparable strength, suggesting the need for a multi-component order parameter to describe altermagnetism. We also discuss different measures to quantify the overall
spin-splitting of a material, without relying on features that might be specific to only individual bands.
Read the full abstract ▾