Materials Science
Defect Engineered Hexagonal-Boron Nitride Enables Ionic Conduction for Lithium Metal Batteries
Yecun Wu, Yan-Kai Tzeng, Hao Chen et al. (+7 more)
The practical implementation of lithium-metal anodes has been hindered by uncontrollable dendrite formation and interfacial instability. This study presents a defect-engineering approach of a chemically stable and electrically insulating interfacial layer of hexagonal boron nitride (h-BN) that markedly enhances ionic conductivity through argon ion irradiation. Initially, the electrochemical performance from commercially available, large-area chemical vapor deposition (CVD)-grown h-BN films with industrial-scale argon ion implantation motivated our subsequent detailed investigations using lab-scale exfoliated single-
crystal h-BN flakes. Integration of these exfoliated flakes into a hybrid microfluidic-microelectronic chip provided direct evidence that controlled vacancy defects transform h-BN into an efficient lithium-ion conductor while preserving its intrinsic electrical insulation. Experimental validation confirmed improved lithium-metal anode stability, achieving dendrite-free cycling with Li plating/stripping Coulombic efficiencies exceeding 99.5% about 1000 cycles. Further assemble of irradiated h-BN in lithium-sulfur batteries effectively mitigates the polysulfide shuttle effect, sustaining over 97% specific capacity around 300 cycles. These results establish a robust, scalable interface-engineering route for next-generation lithium-metal batteries that combine high ionic transport with excellent electrical insulation.
Read the full abstract ▾
All authors Yecun Wu, Yan-Kai Tzeng, Hao Chen, Kun Xu, Gangbin Yan, Takashi Taniguchi, Kenji Watanabe, Arun Majumdar, Yi Cui, Steven Chu
Materials Science
Stability and Dynamics of Sn-based Halide Perovskites: Insights from MACE-MP-0 and Molecular Dynamics Simulations
Thiago Puccinelli, Lucas Martin Farigliano and Gustavo Martini Dalpian
Tin-based halide perovskites have emerged as promising lead-free alternatives for optoelectronic applications, yet their structural stability and phase behavior at finite temperatures remain challenging to predict. Here, we assess the predictive capabilities of the foundational machine learning model MACE-MP-0 - trained on a broad chemical space and applied without system-specific fine-tuning - for the temperature-dependent behavior of CsSnBr3 and Cs2SnBr6. Molecular Dynamics simulations in the NpT ensemble were performed from 100 K to 500 K, and thermodynamic and structural descriptors including enthalpy, specific heat, radial distribution functions, translational order, bond angle distributions, and vibrational spectra were analyzed. Our results show that CsSnBr3 undergoes a low-temperature orthorhombic-to-cubic phase transition, evidenced by both the
evolution of
lattice parameters and subtle anomalies in enthalpy and specific heat, although the experimentally observed intermediate tetragonal phase is not captured. In contrast, Cs2SnBr6 remains cubic and maintains a more rigid octahedral framework across the entire temperature range. Overall, MACE-MP-0 qualitatively reproduces key thermal and structural features of these materials, highlighting its usefulness as a first step for studying new materials. For cases where capturing more subtle phase behavior is required, system-specific fine-tuning with Density Functional Theory data should be considered.
Read the full abstract ▾
Materials Science · Cross-listed from cond-mat.mes-hall
Metallic electro-optic effects in topological chiral crystals
C. O. Ascencio, D. J. P. de Sousa and Tony Low
Topological
chiral crystals have emerged as a fertile material platform for investigating optical phenomena derived from the distinctive
Fermi surface Berry
curvature and orbital
magnetic moment textures around multifold
chiral band crossings pinned at the time-reversal invariant momenta. In this work, by means of tight-binding model and first principles based calculations, we investigate metallic electro-optic (EO) responses stemming from the Berry
curvature and orbital
magnetic moment of Bloch electrons across 37 materials belonging to space group 198 (SG198). Previously thought to vanish in SG198, our findings reveal a nonzero Berry
curvature dipole attributed to the energetic misalignment between topologically charged point nodes of opposite chirality. Moreover, we find that the recently predicted magnetoelectric EO effects, which arise from the interplay between the Berry
curvature and
magnetic moment on the
Fermi surface, are readily accessible in BeAu under experimentally feasible electric biases.
Read the full abstract ▾
Materials Science
Atomistic Simulations of H-Cu Vacancy Cosegregation and H Diffusion in Cu Grain Boundary
Vasileios Fotopoulos and Alexander L. Shluger
Hydrogen embrittlement remains a critical challenge in structural and electronic applications of copper (Cu) but its mechanism is still not fully understood. In this study, we combine density functional theory (DFT) and bond-order potential (BOP) simulations to determine the atomistic pathways for hydrogen adsorption/incorporation and fast interfacial
diffusion at Cu grain boundaries (GBs), including its interaction with vacancies. Undercoordinated regions, such as surfaces and GBs, serve as preferential adsorption/incorporation sites for atomic hydrogen, especially in the presence of Cu vacancies. The presence of hydrogen in GB further enhances the segregation of Cu vacancies, leading to the formation of stable H-$V_\mathrm{Cu}$ complexes with cosegregation energy gains of up to $-0.8$ eV. Furthermore, our simulations reveal that the migration barriers for hydrogen within the GB networks are as low as $0.2$ eV and significantly lower than in bulk Cu ($0.42$ eV). The results presented in this paper suggest an atomistic mechanism that links $H_2$ exposure to H accumulation in GBs, providing information on the early stages of hydrogen-induced degradation.
Read the full abstract ▾
Materials Science · Cross-listed from cond-mat.soft
Nanomechanics of Shear Rate-Dependent Stiffening in Micellar Electrically Conductive Polymers
Jingchen Wang, Tianqi Hu and Jingjie Yeo
Electrically conducting
polymers with mechanical adaptability are essential for flexible electronics, yet most suffer structural degradation under rapid deformation. In this study, multiscale coarse-grained (MSCG) simulations are used to uncover the nanoscale origins of an unusual strain-rate-dependent stiffening in a poly(2-acrylamido-2-methyl-1-propanesulfonic acid) (PAMPSA)-polyaniline (PANI) blend. The self-assembled morphology consists of semi-crystalline PANI-rich micellar cores dispersed in a soft, viscoelastic PAMPSA
matrix. At low shear rates, micelles migrate and coalesce into larger aggregates, enhancing local crystallinity and transient
entanglement density while dissipating stress through
matrix deformation. At high shear rates, micelles cannot reorganize quickly enough, leading to core dissociation and the emergence of highly aligned PANI filaments that directly bear the load, with PAMPSA serving as a weak but extended support phase. These contrasting regimes (densification-driven local
alignment versus dissociation-driven global
alignment) enable reversible mechanical stiffening across three orders of magnitude in shear rate. The results provide a molecular-level framework for designing solid-state
polymers with tunable, rate-adaptive mechanical properties.
Read the full abstract ▾
Materials Science
Generative diffusion modeling protocols for improving the Kikuchi pattern indexing in electron back-scatter diffraction
Meghraj Prajapat and Alankar Alankar
Electron back-scatter diffraction (EBSD) has traditionally relied upon methods such as the Hough transform and dictionary Indexing to interpret diffraction patterns and extract crystallographic orientation. However, these methods encounter significant limitations, particularly when operating at high scanning speeds, where the exposure time per pattern is decreased beyond the operating sensitivity of CCD camera. Hence the signal to noise ratio decreases for the observed pattern which makes the pattern noisy, leading to reduced indexing accuracy. This research work aims to develop generative machine learning models for the post-processing or on-the-fly processing of Kikuchi patterns which are capable of restoring noisy EBSD patterns obtained at high scan speeds. These restored patterns can be used for the determination of
crystal orientations to provide reliable indexing results. We compare the performance of such generative models in enhancing the quality of patterns captured at short exposure times (high scan speeds). An interesting observation is that the methodology is not data-hungry as typical machine learning methods.
Read the full abstract ▾
Materials Science
MaterialsGalaxy: A Platform Fusing Experimental and Theoretical Data in Condensed Matter Physics
Tiannian Zhu, Zhong Fang, Quansheng Wu et al. (+1 more)
Modern materials science generates vast and diverse
datasets from both experiments and computations, yet these multi-source, heterogeneous data often remain disconnected in isolated "silos". Here, we introduce MaterialsGalaxy, a comprehensive platform that deeply fuses experimental and theoretical data in condensed matter physics. Its core innovation is a structure similarity-driven data fusion mechanism that quantitatively links cross-modal records - spanning diffraction,
crystal growth, computations, and literature - based on their underlying atomic structures. The platform integrates artificial intelligence (AI) tools, including large
language models (LLMs) for knowledge extraction, generative models for
crystal structure prediction, and machine learning property predictors, to enhance data interpretation and accelerate materials discovery. We demonstrate that MaterialsGalaxy effectively integrates these disparate data sources, uncovering hidden correlations and guiding the design of novel materials. By bridging the long-standing gap between experiment and theory, MaterialsGalaxy provides a new paradigm for data-driven materials research and accelerates the discovery of advanced materials.
Read the full abstract ▾
All authors Tiannian Zhu, Zhong Fang, Quansheng Wu, Hongming Weng
Materials Science
Higher-dimensional Fermiology in bulk moiré metals
Kevin P. Nuckolls, Nisarga Paul, Alan Chen et al. (+10 more)
In the past decade, moiré materials have revolutionized how we engineer and control
quantum phases of matter. Among incommensurate materials, moiré materials are aperiodic composite
crystals whose long-wavelength moiré superlattices enable tunable properties without chemically modifying their layers. To date, nearly all reports of moiré materials have investigated van der Waals
heterostructures assembled far from thermodynamic
equilibrium. Here we introduce a conceptually new approach to synthesizing high-mobility moiré materials in thermodynamic
equilibrium. We report a new family of foliated superlattice materials (Sr$_6$TaS$_8$)$_{1+\delta}$(TaS$_2$)$_8$ that are exfoliatable van der Waals
crystals with atomically incommensurate
lattices.
Lattice mismatches between alternating layers generate moiré superlattices, analogous to those of 2D moiré heterobilayers, that are coherent throughout these
crystals and are tunable through their synthesis conditions without altering their chemical composition. High-field
quantum oscillation measurements map the complex Fermiology of these moiré metals, which can be tuned via the moiré superlattice structure. We find that the
Fermi surface of the structurally simplest moiré metal is comprised of over 40 distinct cross-sectional areas, the most observed in any material to our knowledge. This can be naturally understood by postulating that bulk moiré materials can encode electronic properties of higher-dimensional superspace
crystals in ways that parallel well-established crystallographic methods used for incommensurate
lattices. More broadly, our work demonstrates a scalable synthesis approach potentially capable of producing moiré materials for electronics applications and evidences a novel material design concept for accessing a broad range of physical phenomena proposed in higher dimensions.
Read the full abstract ▾
All authors Kevin P. Nuckolls, Nisarga Paul, Alan Chen, Filippo Gaggioli, Joshua P. Wakefield, Avi Auslender, Jules Gardener, Austin J. Akey, David Graf, Takehito Suzuki, David C. Bell, Liang Fu, Joseph G. Checkelsky
Materials Science · Cross-listed from quant-ph
Programmable digital quantum simulation of 2D Fermi-Hubbard dynamics using 72 superconducting qubits
Faisal Alam, Jan Lukas Bosse, Ieva Čepaitė et al. (+41 more)
Simulating the time-dynamics of
quantum many-body systems was the original use of
quantum computers proposed by Feynman, motivated by the critical role of
quantum interactions between electrons in the properties of materials and molecules. Accurately simulating such systems remains one of the most promising applications of general-purpose digital
quantum computers, in which all the parameters of the model can be programmed and any desired physical quantity output. However, performing such simulations on today's
quantum computers at a scale beyond the reach of classical methods requires advances in the efficiency of simulation
algorithms and error mitigation techniques. Here we demonstrate programmable digital
quantum simulation of the dynamics of the 2D
Fermi-Hubbard model – one of the best-known simplified models of electrons in crystalline solids – at a scale beyond exact classical state-vector simulation. We implement simulations of this model on
lattice sizes up to ${6\times 6}$ using 72
qubits on Google's Willow
quantum processor, across a range of physical parameters, including different on-site electron-electron interaction strengths and
magnetic flux values, and study phenomena including formation of
magnetic polarons (charge carriers surrounded by local
magnetic polarisation), dynamical
symmetry-breaking in stripe-ordered states, attraction of charge carriers on an entangled background state known as a valence bond solid, and the approach to
equilibrium through thermalisation. We validate our results against exact calculations in parameter regimes where these are feasible, and compare them to approximate classical simulations performed using tensor network and operator propagation methods. Our results demonstrate that meaningful programmable digital
quantum simulation of many-body interacting electron models is now feasible on state-of-the-art
quantum hardware.
Read the full abstract ▾
All authors Faisal Alam, Jan Lukas Bosse, Ieva Čepaitė, Adrian Chapman, Laura Clinton, Marcos Crichigno, Elizabeth Crosson, Toby Cubitt, Charles Derby, Oliver Dowinton, Paul K. Faehrmann, Steve Flammia, Brian Flynn, Filippo Maria Gambetta, Raúl García-Patrón, Max Hunter-Gordon, Glenn Jones, Abhishek Khedkar, Joel Klassen, Michael Kreshchuk, Edward Harry McMullan, Lana Mineh, Ashley Montanaro, Caterina Mora, John J. L. Morton, Dhrumil Patel, Pete Rolph, Raul A. Santos, James R. Seddon, Evan Sheridan, Wilfrid Somogyi, Marika Svensson, Niam Vaishnav, Sabrina Yue Wang, Gethin Wright, Dmitry Abanin, Mohammed Alghadeer, Jaehong Choi, Tyler Cochran, Gaurav Gyawali, Shashwat Kumar, Ricky Oliver, Eliott Rosenberg, Pedram Roushan
Materials Science · Cross-listed from cond-mat.mes-hall
Impact of hydrogenation on the structure, chemistry, and electrical properties of flame-synthesized carbon nanoparticle films
Luca Basta, Francesca Picca, Pegah Darvehi et al. (+8 more)
The interaction between hydrogen atoms and carbon nanoparticles is a fundamental process governing the properties of carbonaceous materials in environments ranging from combustion systems to the interstellar medium. This study investigates the effects of controlled atomic hydrogen exposure on young and mature soot nanoparticles, generated in premixed ethylene-air flames, and deposited on substrates. We employed a multi-technique approach to characterize the chemical, mechanical, and electrical
evolution of the films. In-situ infrared spectroscopy revealed non-monotonic behavior: an initial increase in aliphatic CH bonds was observed, followed by a decrease at higher hydrogen fluences. This was accompanied by a continuous decrease in the aromatic C=C signal. Atomic force microscopy showed a significant increase in the Young's modulus of the film for both sample types after hydrogenation. This mechanical change was correlated with an increase in the I(D)/I(G) ratio from Raman spectroscopy. Furthermore, both macroscopic current vs. voltage and local scanning tunneling spectroscopy measurements demonstrated a notable increase in electrical conductivity. For single just-formed soot particles, moreover, a hydrogen-induced transformation from a semiconductive to a semi-metallic nature was observed. The collective evidence points towards an H-induced CC cross-linking mechanism within the nanoparticle films. We propose that atomic hydrogen facilitates the formation of radical sites, which promotes covalent bond formation between adjacent particles or molecular units, creating a more interconnected and rigid network, with smaller interlayer distance. These findings provide crucial insights into the structural
evolution of carbonaceous materials in hydrogen-rich environments, with direct implications for understanding soot formation and for the tailored design of carbon-based materials.
Read the full abstract ▾
All authors Luca Basta, Francesca Picca, Pegah Darvehi, Vincenzo Pagliara, Alberto Aloisio, Mario Commodo, Patrizia Minutolo, Vito Mennella, Stefan Heun, Stefano Veronesi, Andrea D'Anna
Materials Science
Temperature dependent ferroelectricity in strained KTaO3 with machine learned force field
Yu Zhu, Luigi Ranalli, Taikang Chen et al. (+2 more)
Ferroelectric materials are a class of dielectrics that exhibit spontaneous polarization which can be reversed under an external electric field. The emergence of ferroelectric order in incipient ferroelectrics is a topic of considerable interest from both fundamental and applied perspectives. Among the various strategies explored, strain engineering has been proven to be a powerful method for tuning ferroelectric polarization in materials. In the case of KTaO3, first principles calculations have suggested that strain can drive a ferroelectric phase transition. In this study, we investigate the impact of in-plane uniaxial and biaxial strain, ranging from 0% to 1%, on pristine KTaO3 to explore its potential for ferroelectricity induction via inversion
symmetry breaking. By integrating density functional theory calculations with the
stochastic self-consistent harmonic approximation assisted by on the fly machine learned force field, we obtain accurate structural information and dynamical properties under varying strain conditions while incorporating higher-order anharmonic effects. Employing the Berry phase method, we obtained the ferroelectric polarization of the strained structures over the entire temperature range up to 300 K. Our findings provide valuable insights into the role of strain in stabilizing ferroelectricity in KTaO3, offering guidance for future experimental and theoretical studies on strain-engineered ferroelectric materials.
Read the full abstract ▾
All authors Yu Zhu, Luigi Ranalli, Taikang Chen, Wei Ren, Cesare Franchini
Materials Science
Stabilization of Metallic, Excitonic Insulator, and Superionic Phases in Helium-Rare Gas Compounds at Sub-Terapascal Pressures
Cong Liu, Jordi Boronat and Claudio Cazorla
Helium and rare gases (RG: Ne, Ar, Kr, Xe) are typically considered chemically inert, yet under the extreme pressures of planetary interiors they may form compounds with unexpected properties. Using
crystal structure prediction and first-principles calculations, we mapped the phase diagram of binary He-RG systems up to $1$ TPa. We identify several previously unknown stoichiometric compounds that are both thermodynamically and vibrationally stable at sub-terapascal pressures, within the reach of modern high-pressure experiments. In particular, AHe$_{2}$ and AHe (A: Ar, Kr, Xe) adopt previously unreported orthorhombic, hexagonal and cubic phases that remain stable over wide pressure ranges. We further find that He-Xe systems host metallic and excitonic
insulator phases at pressures nearly an order of magnitude lower than those required for pure helium, offering a pathway to realize these exotic
quantum states experimentally. Finite-temperature simulations also reveal superionic He-Xe phases, in which helium ions diffuse either anisotropically or isotropically depending on the host
lattice. These findings constitute the first prediction of helium-based systems that combine
metallicity and superionicity, with profound implications for energy transport and planetary dynamo processes. Overall, our results demonstrate that mixing helium with heavier rare gases provides an effective strategy to stabilize metallic, excitonic
insulator, and superionic phases at experimentally accessible pressures, opening new research directions for condensed matter physics and planetary science.
Read the full abstract ▾
Materials Science · Cross-listed from physics.app-ph
Tailored heat treatments to characterise the fracture resistance of critical weld regions in hydrogen transmission pipelines
D.R. Chalfoun, J. Parker, M. Gagliano et al. (+1 more)
A new protocol is presented to directly characterise the toughness of microstructural regions present within the weld heat-affected zone (HAZ), the most vulnerable location governing the structural integrity of hydrogen transport pipelines. Heat treatments are tailored to obtain bulk specimens that replicate predominantly ferritic-bainitic, bainitic, and martensitic microstructures present in the HAZ. These are applied to a range of pipeline steels to investigate the role of manufacturing era (vintage versus modern), chemical composition, and grade. The heat treatments successfully reproduce the hardness levels and microstructures observed in the HAZ of existing natural gas pipelines. Subsequently, fracture experiments are conducted in air and pure H2 at 100 bar, revealing a reduced fracture resistance and higher hydrogen embrittlement susceptibility of the HAZ microstructures, with initiation toughness values as low as 32 MPa$\sqrt{\text{m}}$. The findings emphasise the need to adequately consider the influence of microstructure and hard, brittle zones within the HAZ.
Read the full abstract ▾
All authors D.R. Chalfoun, J. Parker, M. Gagliano, E. Martínez-Pañeda
Materials Science · Cross-listed from quant-ph
Diamond quantum sensing at record high pressure up to 240 GPa
Qingtao Hao, Ze-Xu He, Na Zuo et al. (+10 more)
Quantum sensing utilizing nitrogen-vacancy (NV) centers in diamond has emerged as a transformative technology for probing
magnetic phase transition1-4, evidencing Meissner effect of
superconductors1,5-9, and visualizing stress distribution3,9 under extreme conditions. Recent development in NV configurations and hydrostatic environments have raised the operational pressures of NV centers to 140 GPa2,6,10,11, but substantial challenges remain in extending sensing capabilities into multi-megabar range, critical for research in hydrogen-rich
superconductors like La-Sc-H ($T_{\text{c}}$ of 271-298 K at 195-266 GPa)12 and
evolution of minerals near Earth's core13. Here we report the fabrication of shallow NV centers through ion implantation followed by high-pressure and high-temperature (HPHT) annealing, leading to increased density, improved coherence, and mitigated internal stresses, a pre-requisite for reducing their degradation under compression. This NV magnetometry enable breakthrough of pressure capabilities exceeding 240 GPa, constrained by structural integrity of the 50 um diamond anvils, suggesting that the untapped pressure limit may enable further advancements with smaller cutlets or more robust diamonds. We present compelling evidence of the Meissner effect and trapped flux at record-high pressure of 180 GPa for superconducting transition in elemental titanium (Ti) as
benchmark, establishing a solid foundation for high-pressure magnetometry in exploring complex
quantum phenomena at previously unreachable pressures.
Read the full abstract ▾
All authors Qingtao Hao, Ze-Xu He, Na Zuo, Yang Chen, Xiangzhuo Xing, Xiaoran Zhang, Xinyu Zhuang, Zhixiang Shi, Xin Chen, Jian-Gang Guo, Gang-Qin Liu, Xiaobing Liu, Yanming Ma
Materials Science · Cross-listed from cond-mat.str-el
Dynamical control of Coulomb interactions and Hubbard bands in monolayer 1T-TaS$_2$
Niklas Notter, Markus Aichhorn and Anna Galler
Monolayer 1T-TaS$_2$ hosts a
star-of-David charge-density wave (CDW) that stabilizes a low-temperature Mott-insulating state. Recent time-resolved spectroscopies indicate a coupling between the CDW amplitude mode and the electronic correlation strength, yet the role of the screened Coulomb interaction remains unclear. Using the constrained random-phase approximation, we show that the CDW amplitude modifies the bare and screened on-site interactions, leading to sizable variations in the effective Hubbard U. Our combined density functional and dynamical mean-field theory calculations reveal that the Hubbard bands shift in concert with the CDW amplitude, and that a reduced distortion drives a transition from a Mott
insulator to a correlated metal. These results demonstrate a direct link between
lattice distortions and Coulomb interactions in transition-metal dichalcogenides, providing a microscopic mechanism for light-induced control of correlated phases in two-dimensional
quantum materials.
Read the full abstract ▾
Materials Science
Strain Engineering of Altermagnetic Symmetry in Epitaxial RuO$_2$ Films
Johnathas D. S. Forte, Seung Gyo Jeong, Anand Santhosh et al. (+3 more)
The
magnetic ground state of RuO$_2$ has been under intense debate. Using first-principles calculations, we show that compressive strain along [001] direction stabilizes an altermagnetic phase in RuO$_2$ thin films grown on (100) and (110) TiO$_2$ substrates. We further identify that compressive strain enhances the density of states near the
Fermi level, resulting in a
Fermi surface instability and the emergence of altermagnetism. The magnitude of strain and the associated increase in the density of states can be tuned by varying the film thickness, as systematically confirmed by x-ray diffraction and photoemission spectroscopy measurements.
Symmetry analysis further reveals that (100) RuO$_2$ hosts an ideal altermagnetic order, whereas broken
symmetry in (110) films leads to an uncompensated ferrimagnetic state. Finally, we discuss the effects of Hubbard $U$ parameters and evaluate the realistic tunneling magnetoresistance of (100) RuO$_2$.
Read the full abstract ▾
All authors Johnathas D. S. Forte, Seung Gyo Jeong, Anand Santhosh, Seungjun Lee, Bharat Jalan, Tony Low
Materials Science
Tunable Colloidal Synthesis Enabling {\mu}-ARPES on Individual Two-dimensional Bismuth Nanocrystals
Fagui He, Yan Yan Grisan Qiu, Simone Mearini et al. (+4 more)
Two-dimensional bismuth (Bi) is a promising platform for
quantum and energy technologies due to strong
spin-orbit coupling, high thermoelectric efficiency, and magnetoresistance. However, scalable and flexible synthesis of high-quality Bi with fast research turnaround remains challenging. We report a controlled colloidal synthesis of Bi nanosheets with tunable lateral sizes (0.6 - 4.1 um), hexagonal shape, and a layered single-crystalline structure along the {00l} planes. The nanosheets exhibit excellent oxidation resistance and ambient stability. ARPES measurements on individual nanosheets reveal a band structure in excellent agreement with DFT calculations, confirming high
crystal quality and uniformity. Our findings enable fast production and characterization of two-dimensional Bi, paving the way for fundamental studies and integration into next-generation
quantum and energy devices.
Read the full abstract ▾
All authors Fagui He, Yan Yan Grisan Qiu, Simone Mearini, Vitaliy Feyer, Kevin Oldenburg, Rostyslav Lesyuk, Christian Klinke
Materials Science
Understanding the swelling behavior of P(DMAA-co-MABP) copolymer in paper-based actuators
Catarina C. Ribeiro, Nele Link, Jan-Lukas Schäfer et al. (+3 more)
As interest in sustainable materials grows, paper is being reimagined as a multifunctional substrate with significant potential for future technologies for innovative, environmentally friendly solutions. This study investigates the swelling behavior and environmental responsiveness of a copolymer, poly(N,N-dimethylacrylamide-co-4-methacryloyloxybenzophenone) (P(DMAA-co-MABP)), when applied to cellulosic paper for use in humidity-sensitive actuators. The copolymer's swelling behavior was characterized using dynamic vapor sorption (DVS) and in-situ atomic force microscopy (AFM). DVS measurements demonstrated that the
polymer coating significantly enhances the hygroscopic properties of the paper, while AFM revealed the
polymer's fast response to relative humidity (RH) changes, shown by immediate height adjustments, increased adhesion, and decreased stiffness at higher RH levels.Studies on
polymer-modified paper-based
bilayer actuators demonstrate that incorporating the hydrophilic P(DMAA-co-MABP) results in actuation in response to relative humidity variations between 10% and 90% RH. From these findings, two models were proposed to assess key mechanisms in the swelling behavior: the correlation between the heterogeneity in crosslinking and the
polymer swelling behavior, and the correlation between
polymer-paper interactions and the hygro-responsive bending behavior. Additionally, thermal analysis was performed by thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), providing a comprehensive profile of the copolymer's behavior.
Read the full abstract ▾
All authors Catarina C. Ribeiro, Nele Link, Jan-Lukas Schäfer, Carina Breuer, Markus Biesalski, Robert W. Stark
Materials Science
Magnetic Field-Controlled THz Modulation in Uniaxial Anisotropic Spin-Valves Emitters
Arseniy M. Buryakov, Anastasia V. Gorbatova, Pavel Y. Avdeev et al. (+6 more)
Uniaxial spintronic
heterostructures constitute compact THz emitters under femtosecond optical excitation, with emission amplitude and polarization governed by the applied
magnetic field is presented. We demonstrate here efficient magnetically tunable THz amplitude control in ultrathin, exchange-biased Co/Pt/Co/IrMn
spin valve. Terahertz spintronic magnetometry resolves reversible switching between parallel and antiparallel magnetization states and correlates the high- and low-emission regimes with constructive and destructive interference of charge transients generated by the inverse
spin Hall effect in the Pt spacer. A residual low-emission signal is traced to
spin-to-charge conversion in IrMn. Phase inversion under front- versus back-side excitation confirms the ISHE origin of the emission, while a macrospin Landau-Lifshitz-Gilbert model reproduces the field dependence of its amplitude and separates layer-specific contributions. Together, these results define a wafer-compatible
spin valve device architecture that enables efficient, low-field THz amplitude control.
Read the full abstract ▾
All authors Arseniy M. Buryakov, Anastasia V. Gorbatova, Pavel Y. Avdeev, Igor Yu. Pashen'kin, Maksim V. Sapozhnikov, Alexey A. Klimov, Elena D. Mishina, Alexandr S. Sigov, Vladimir L. Preobrazhensky
Materials Science · Cross-listed from physics.chem-ph
Atomistic Simulations of Oxide-Water Interfaces using Machine Learning Potentials
Jan Elsner, K Nikolas Lausch and Jörg Behler
Oxide-water interfaces govern a wide range of physical and chemical processes fundamental to many fields like catalysis, geochemistry, corrosion, electrochemistry, and sensor technology. Near solid
oxide surfaces, water behaves differently than in the bulk, exhibiting pronounced structuring and increased reactivity, typically requiring ab initio-level accuracy for reliable modeling. However, explicit ab initio calculations are often computationally prohibitive, especially if large system sizes and long simulation time scales are required. By learning the potential energy surface (PES) from data obtained from electronic structure calculations, machine learning potentials (MLPs) have emerged as transformative tools, enabling simulations with ab initio accuracy at dramatically reduced computational expense. Here, we provide an overview of recent progress in the application of MLPs to atomistic simulations of
oxide-water interfaces. Specifically, we review insights that have been gained into the reactivity of interfacial systems involving the dissociation and recombination of water molecules,
proton transfer processes between the solvent and the surface and the dynamic nature of aqueous
oxide surfaces. Moreover, we discuss open challenges and future possible research directions in this rapidly evolving but challenging field.
Read the full abstract ▾
Materials Science
Investigation of the intrinsic hidden spin texture and spin-state segregation in centrosymmetric monolayer dichalcogenide: effectiveness of the electric-field approach
Ameneh Deljouifar, Anita Yadav, Nataša Stojić et al. (+2 more)
The emergence of hidden
spin polarization in centrosymmetric nonmagnetic
crystals due to local
symmetry breaking has created new opportunities for potential spintronic applications and for enhancing our understanding of mechanisms to electrically manipulate
spin-related phenomena. In this work, we investigate within density functional theory the properties of the hidden
spin texture and
spin-layer segregation in a prototype centrosymmetric dichalcogenide-monolayer material using an electric-field-based method. This method is shown to yield a precise and robust alternative to traditional layer-projected
spin-polarization techniques for obtaining the intrinsic hidden
spin textures in such materials. Moreover, it gives access at the same time to the spatial distribution within the monolayer of the individual
spin-segregated states responsible for the hidden
spin textures, not provided by other techniques. With this approach we determine and study the hidden
spin textures of the upper valence bands of the PtTe2 monolayer together with the spatial behavior of the probability densities and
spin polarization densities of the corresponding maximally segregated
spin states. This combined study enabled by the electric-field method yields new insights into the mechanisms controlling the
spin-layer segregation and resulting hidden
spin texture in such systems. We also discuss the
symmetry rules governing the shape in the Brillouin zone of the hidden
spin texture, which can be straightforwardly predicted within the present framework.
Read the full abstract ▾
All authors Ameneh Deljouifar, Anita Yadav, Nataša Stojić, H. Rahimpour Soleimani, Nadia Binggeli
Materials Science · Cross-listed from cond-mat.soft
Large electrocaloric strength in ferroelectric nematic liquid crystals with a tuneable operational temperature range
Diana I. Nikolova, Rachel Tuffin, Mengfan Guo et al. (+5 more)
The electrocaloric (EC) effect offers a promising energy-efficient and clean cooling technology. We present the first direct measurements of EC temperature change in a new family of EC fluids, ferroelectric nematic
liquid crystals (FNLCs), demonstrating in two such materials temperature jumps of $|{\Delta}T_j|$ ~ 0.2 K for field changes as low as ${\Delta}E$ ~ 0.1 $V {\mu}m^{-1}$. Indirect measurements of adiabatic temperature change $|{\Delta}T|$ confirm that these direct measurements are an underestimate and that ${\Delta}E$ = 2 $V {\mu}m^{-1}$ can induce up to $|{\Delta}T|$ ~ 1.6 K, yielding EC strengths $|{\Delta}T/{\Delta}E|$ up to 100% higher than incumbent materials. For temperature spans of 5-10 K, we predict a coefficient of performance of ~21-40. We find $|{\Delta}T|$ ~ 1 K for >100 FNLCs that collectively span all temperatures between $0{^\circ}$C and $100{^\circ}$C. This, together with the new device concepts conceivable with fluid EC materials, offers huge potential for cooling applications.
Read the full abstract ▾
All authors Diana I. Nikolova, Rachel Tuffin, Mengfan Guo, Neil D. Mathur, Xavier Moya, Peter Tipping, Richard J. Mandle, Helen F. Gleeson
Materials Science · Cross-listed from physics.app-ph
Self-Assembled hBN Wrinkles as Planar Optofluidic Channels
Xiliang Yang, Tetsuo Martynowicz, Allard Katan et al. (+3 more)
Optically accessible, scalable planar nanofluidic channels are attractive for studying transport and localization under confinement. Two dimensional (2D) materials provide large area, atomically flat interfaces for generating such platforms, yet achieving long range one-dimensional (1D) confinement with top-down nanofabrication remains challenging because it requires reproducible nanoscale feature control over extended distances, high yield, and low nonspecific adsorption of analytes under aqueous conditions. Here we demonstrate that thermally induced wrinkling of exfoliated hexagonal boron nitride (hBN) produces self-assembled,
liquid-accessible, channel-like networks through a lithography-free process. By varying flake thickness and substrate choice, we quantify statistical trends in wrinkle density and morphology, thereby establishing a practical fabrication design space. Atomic force microscopy and electron microscopy reveal wrinkle-derived geometries with vertical confinement ranging from <2 nm to >100 nm depending on flake thickness and substrate. We further employ time-sequence optical imaging upon droplet-contact, which together with Raman mapping of the water OH-stretch band and capacitance-gradient mapping (dC/dz) by scanning dielectric microscopy (KPFM-based) measurements, demonstrates
liquid infiltration and long-term
liquid retention within the wrinkle network for more than 10 h. We finally show a proof-of-concept biomolecule confinement application in which we integrate a
graphene overlayer as a background suppression interface, enabling wide-field fluorescence localization of ATTO647N labeled DNA along hBN wrinkle-induced nanochannels. Overall, this work establishes self-assembled hBN wrinkles as a scalable, and optically addressable planar nanofluidic platform for confinement of fluids and biomolecules.
Read the full abstract ▾
All authors Xiliang Yang, Tetsuo Martynowicz, Allard Katan, Kenji Watanabe, Takashi Taniguchi, Sabina Caneva
Materials Science · Cross-listed from physics.class-ph
Momentum-Transfer Framework Unifies High-Velocity Impact and Failure Across Materials, Geometries, and Scales
Yasara Dharmadasa, Nicholas Jaegersberg, Ara Kim et al. (+2 more)
Materials that dissipate energy efficiently under high-speed impacts, from micrometeoroid strikes on spacecraft to ballistic penetration in protective systems, are essential for maintaining structural integrity in extreme environments. Yet, despite decades of study, predicting and comparing impact performance across materials, geometries, and length scales remains challenging because conventional projectile-impact models often rely on conservation-based or empirically partitioned descriptions that assume the projectile-target interaction is a closed system. Here, we relax this assumption and directly observe the momentum and energy transferred out of the projectile during impact. We find that the momentum transferred to the target consistently reaches its maximum at the ballistic-limit velocity, demonstrated through a coordinated suite of micro-projectile impact experiments spanning varied projectile diameters, target thicknesses, and impact velocities, and further supported by targeted macroscale tests. This behavior is reinforced across a broad range of independent studies encompassing metals,
polymers, composites, sandwich panels, and reinforced concrete, with thicknesses ranging from nanometers to hundreds of millimeters and projectiles of spherical, blunt, ogive, and conical shape, under both normal and oblique impacts. Together, these observations reveal a consistent impact behavior across all available data: maximum momentum transfer occurs at the ballistic limit. Extending this bound into the energy absorption landscape addresses an entrenched misconception in the field by revealing that specific energy absorption inherently inflates the performance of thinner targets due to
geometric normalization, rather than reflecting genuine material enhancement.
Read the full abstract ▾
All authors Yasara Dharmadasa, Nicholas Jaegersberg, Ara Kim, Jizhe Cai, Ramathasan Thevamaran
Materials Science
High-temperature plasma in Casimir physics
Suman Kumar Panja and Mathias Boström
We present a short review of an unusual but important application for a high-temperature charged
plasma. The unorthodox proposition was made by Ninham concerning a contribution from Casimir forces across high-temperature electron-positron
plasma in
nuclear interactions. The key message in the current work is how high temperatures ($\sim10^{11}$ \,K) pop out as essential. Clearly, classical, semi-classical, and
quantum considerations for the background media impact both the Casimir effect and the physics of
stars and the Universe.
Read the full abstract ▾
Materials Science · Cross-listed from quant-ph
Fermionic dynamics on a trapped-ion quantum computer beyond exact classical simulation
Faisal Alam, Jan Lukas Bosse, Ieva Čepaitė et al. (+37 more)
Simulation of the time-dynamics of fermionic many-body systems has long been predicted to be one of the key applications of
quantum computers. Such simulations – for which classical methods are often inaccurate – are critical to advancing our knowledge and understanding of
quantum chemistry and materials, underpinning a wide range of fields, from biochemistry to clean-energy technologies and chemical synthesis. However, the performance of all previous digital
quantum simulations of
fermions has been matched by classical methods, and it has thus far remained unclear whether near-term, intermediate-scale
quantum hardware could offer any computational advantage in this area. Here, we implement an efficient
quantum simulation
algorithm on Quantinuum's System Model H2 trapped-ion
quantum computer for the time dynamics of a 56-
qubit system that is too complex for exact classical simulation. We focus on the periodic spinful 2D
Fermi-Hubbard model and present evidence of
spin-charge separation, where the elementary electron's charge and
spin decouple. In the limited cases where ground truth is available through exact classical simulation, we find that it agrees with the results we obtain from the
quantum device. Employing long-range Wilson operators to study deconfinement of the effective gauge field between spinons and the effective potential between charge carriers, we find behaviour that differs from predictions made by classical tensor network methods. Our results herald the use of
quantum computing for simulating strongly correlated electronic systems beyond the capacity of classical computing.
Read the full abstract ▾
All authors Faisal Alam, Jan Lukas Bosse, Ieva Čepaitė, Adrian Chapman, Laura Clinton, Marcos Crichigno, Elizabeth Crosson, Toby Cubitt, Charles Derby, Oliver Dowinton, Norhan Eassa, Paul K. Faehrmann, Steve Flammia, Brian Flynn, Filippo Maria Gambetta, Raúl García-Patrón, Max Hunter-Gordon, Glenn Jones, Abhishek Khedkar, Joel Klassen, Michael Kreshchuk, Edward Harry McMullan, Lana Mineh, Ashley Montanaro, Caterina Mora, John J. L. Morton, Alberto Nocera, Dhrumil Patel, Pete Rolph, Raul A. Santos, James R. Seddon, Evan Sheridan, Wilfrid Somogyi, Marika Svensson, Niam Vaishnav, Sabrina Yue Wang, Gethin Wright, Eli Chertkov, Henrik Dreyer, Michael Foss-Feig
Materials Science
Impact of AlN buffer thickness on electrical and thermal characteristics of AlGaN/GaN/AlN HEMTs
Minho Kim, Dat Q. Tran, Plamen P. Paskov et al. (+3 more)
We investigate the influence of AlN buffer thickness on the structural, electrical, and thermal properties of AlGaN/GaN high-electron mobility transistors (HEMTs) grown on semi-insulating SiC substrates by metal-organic chemical vapor deposition. X-ray diffraction and atomic force microscopy reveal that while thin AlN layers (120 nm) exhibit compressive strain and smooth step-flow surfaces, thicker single-layer buffers (550 nm) develop tensile strain and increased surface roughness. Multi-layer buffer structures up to 2 {\mu}m alleviate strain and maintain surface integrity. Low-temperature
Hall measurements confirm that electron mobility decreases with increasing interface roughness, with the highest mobility observed in the structure with a thin AlN buffer. Transient thermoreflectance measurements show that thermal conductivity (ThC) of the AlN buffer increases with the thickness, reaching 188 W/m.K at 300 K for the 2 {\mu}m buffer layer, which is approximately 60% of the bulk AlN ThC value. These results highlight the importance of optimizing AlN buffer design to balance strain relaxation, thermal management, and carrier transport for high-performance GaN-based HEMTs.
Read the full abstract ▾
All authors Minho Kim, Dat Q. Tran, Plamen P. Paskov, U.Choi, O.Nam, Vanya Darakchieva
Materials Science
Stopping power of electron liquid for slow quantum projectiles
Vladimir U. Nazarov and E. K. U. Gross
We revisit the problem of deceleration of a charge moving in a medium. Going beyond the traditional approach, which relies on Ehrenfest dynamics, we treat the projectile fully
quantum mechanically, on the same footing as the electrons of the target. In order to separate the dynamics of the projectile from that of the electrons, we employ the Exact Factorization method. We illustrate the resulting theory by applying it to the problem of the stopping power (SP) of a jellium-model metal for slowly moving charges. The
quantum mechanical nature of particles manifests itself remarkably in the differences in the SP for projectiles of the same charge moving with the same velocity, but having different masses.
Read the full abstract ▾
Materials Science · Cross-listed from cond-mat.mes-hall
Exciton dynamics in equilibrium and nonequilibrium regimes
Pushpendra Yadav
The bound electron-hole pairs known as
excitons govern the optical properties of insulating solids. While their behavior in
equilibrium is well-understood theoretically, the nonequilibrium regime at high excitation densities-where phenomena like electron-hole
liquids emerge - is less explored. This thesis presents a first-principles study of
excitons in two-dimensional materials. We use the GW approximation and the Bethe-Salpeter equation to investigate their properties from
equilibrium to nonequilibrium conditions. We first demonstrate how increasing photo-excited carrier density leads to a
redshift-blueshift crossover of
excitons. We then show that electron-
phonon interactions critically modify optical spectra and
exciton lifetimes at finite temperatures. Finally, we unify these effects to demonstrate the formation of an electron-hole
liquid phase above a critical carrier density and below a critical temperature. Our work identifies how enhanced Coulomb interactions in two dimensions can stabilize this phase at significantly higher temperatures, proposing promising material candidates for observing these collective states.
Read the full abstract ▾
Materials Science
Applications of Machine Learning in Polymer Materials: Property Prediction, Material Design, and Systematic Processes
Hongtao Guo Shuai Li Shu Li
This paper systematically reviews the research progress and application prospects of machine learning technologies in the field of
polymer materials. Currently, machine learning methods are developing rapidly in
polymer material research; although they have significantly accelerated material prediction and design, their complexity has also caused difficulties in understanding and application for researchers in traditional fields. In response to the above issues, this paper first analyzes the inherent challenges in the research and development of
polymer materials, including structural complexity and the limitations of traditional trial-and-error methods. To address these problems, it focuses on introducing key basic technologies such as molecular descriptors and feature representation, data standardization and cleaning, and records a number of high-quality
polymer databases. Subsequently, it elaborates on the key role of machine learning in
polymer property prediction and material design, covering the specific applications of
algorithms such as traditional machine learning, deep learning, and transfer learning; further, it deeply expounds on data-driven design strategies, such as reverse design, high-throughput virtual screening, and multi-objective optimization. The paper also systematically introduces the complete process of constructing high-reliability machine learning models and summarizes effective experimental verification, model evaluation, and optimization methods. Finally, it summarizes the current technical challenges in research, such as data quality and model generalization ability, and looks forward to future development trends including multi-scale modeling, physics-informed machine learning, standardized data sharing, and interpretable machine learning.
Read the full abstract ▾