Yucheng Ouyang、Xin Chen、Ying Liu 等 11 位作者2026-08-17arXiv (Cornell University)
Bulk materials, as opposed to nanomaterials, require molecular dynamics (MD) simulations on a large spatial scale (~10^9 atoms or more) to adequately capture their atomic-scale physical properties. Previously, the introduction of machine-learning interatomic potentials (MLIPs) has extended MD to this scale, but even s…
Machine Learning in Materials ScienceQuantum many-body systemsBlock Copolymer Self-Assembly
Cibrán López、David Rovira、Edgardo Saucedo 等 4 位作者2026-08-17arXiv (Cornell University)
Pnictogen chalcohalide (MChX; M=Bi,Sb; Ch=S,Se; X=I,Br) solid solutions combine earth-abundant constituents, tunable band gaps ($1.2$-$2.1$ eV), and strong optical absorption, making them attractive for solar energy conversion. Yet their vast compositional space has so far prevented a systematic assessment of how band…
Advanced Thermoelectric Materials and DevicesChalcogenide Semiconductor Thin FilmsMachine Learning in Materials Science
Javier Sivianes、Enrique Boquete-Someso、Daniel Hernangómez‐Pérez 等 4 位作者2026-08-17arXiv (Cornell University)
The optical response of magnetic materials is conventionally classified through magnetic space groups (MSGs), where spin and lattice are locked by the relativistic spin-orbit interaction. However, most optical observables are governed primarily by nonrelativistic physics, and thus a purely MSG-based description can ov…
Multiferroics and related materialsHeusler alloys: electronic and magnetic propertiesIron-based superconductors research
Shimaa Husien、Rana R. Haikal、Eman A. Khalil 等 6 位作者2026-08-17Figshare
Supplementary Material 1
Wound Healing and TreatmentsGraphene and Nanomaterials ApplicationsElectrospun Nanofibers in Biomedical Applications
Konstantinos Alexopoulos、Josselin Garnier2026-08-17arXiv (Cornell University)
We study resonance prediction in dispersive media, formulated as nonlinear spectral problems for volume integral operators. The main idea is to use asymptotic analysis not only as a baseline approximation, but also as a guide for constructing predictive correction models. We learn the residual between asymptotic and r…
Acoustic Wave Phenomena ResearchElectromagnetic Scattering and AnalysisMetamaterials and Metasurfaces Applications
Kazuma Ito2026-08-17arXiv (Cornell University)
Atomistic descriptions of hydrogen diffusion and trapping at defects are essential for understanding hydrogen embrittlement. As the lightest solute in metals, hydrogen exhibits nuclear quantum effects that alter these processes even at room temperature. Explicit treatment of such effects is computationally demanding,…
Nuclear Materials and PropertiesHydrogen embrittlement and corrosion behaviors in metalsHydrogen Storage and Materials
Eric Xie、Wenqian Ye、Aidong Zhang2026-08-17arXiv (Cornell University)
Large language models produce outputs presented as discoveries - new proofs, conjectures, or molecules. Whether such an output that appears creative is truly original and effective is hard to establish: open-ended outputs require subjective judgment, the output may replicate something seen in training, or the task may…
Machine Learning in Materials ScienceTopic ModelingScientific Computing and Data Management
Jonas Matuzas2026-08-17arXiv (Cornell University)
Let Phi be an irreducible reduced crystallographic root system of rank r at least 2, let N = |Phi^+| be the number of positive roots, and let h be its Coxeter number. For the normalized Witten zeta function xi_Phi, we determine the first distinct pole below the leading pole 2/h. It is located at q_2(Phi) = (r-1)/(N-1)…
Algebraic structures and combinatorial modelsAdvanced Combinatorial MathematicsQuasicrystal Structures and Properties
Retna Putri Fauzia、Azmi Aulia Rahmani、Zahra Afriani 等 11 位作者2026-08-17ChemistryOpen
Gadolinium nanoparticles (GdNPs) have been studied extensively due to their lower toxicity and better magnetic resonance imaging (MRI) detection capabilities than Gd‐chelates. Their surfaces are conveniently modified with several molecules to enhance their accumulation in the cancer of interest, thereby enabling more…
Nanoparticle-Based Drug DeliveryNanoplatforms for cancer theranosticsLanthanide and Transition Metal Complexes
Bruno Camino、C. Richard A. Catlow、John Buckeridge 等 16 位作者2026-08-17arXiv (Cornell University)
The predictive simulation of molecules and materials has had a broad and significant impact. It nevertheless remains constrained by the cost of accurately treating electronic correlation, excited states, and complex energy landscapes. Quantum computing offers a fundamentally different computational paradigm in which q…
Scientific Computing and Data ManagementMachine Learning in Materials ScienceQuantum Computing Algorithms and Architecture
Mengfei He、Mingyang Wang、Huihui Zhu 等 4 位作者2026-08-17InfoScience.
Abstract Carrier polarity is a fundamental parameter that defines the electronic functionality of semiconductors. In multielement chalcogenides grown far from equilibrium, the deposited phase can deviate substantially from the nominal source material, providing an alternative route for polarity selection beyond conven…
Advanced Thermoelectric Materials and DevicesChalcogenide Semiconductor Thin FilmsPhase-change materials and chalcogenides
Abderrahmane Benhadjira、C. Detlefs、V. Favre‐Nicolin 等 7 位作者2026-08-17arXiv (Cornell University)
Weak-beam imaging in dark-field X-ray microscopy (DFXM) can resolve individual dislocations in bulk crystals, but assigning Burgers vectors from the resulting contrast typically requires manual comparison with forward simulations. Here, we train a physics-informed convolutional neural network (CNN) on geometrical opti…
Advanced X-ray Imaging TechniquesMicrostructure and mechanical propertiesAdvanced Electron Microscopy Techniques and Applications
Kuo Zhan、Peilin Xin、Yingqi Zhao 等 10 位作者2026-08-17arXiv (Cornell University)
Single-molecule surface-enhanced Raman spectroscopy (SM-SERS) captures dynamic molecular behavior with ultrahigh sensitivity, but its biopolymer analysis is hindered by strong spectral heterogeneity, transient hotspot sampling, and background interference. Here, we develop a physics-aligned deep learning framework int…
Gold and Silver Nanoparticles Synthesis and ApplicationsPlasmonic and Surface Plasmon ResearchOrbital Angular Momentum in Optics
Marco Marino、Lasse Sternemann、Mirko Cinchetti 等 4 位作者2026-08-17arXiv (Cornell University)
Time- and angle-resolved photoemission spectroscopy provides direct access to pump-induced changes in the electronic structure of correlated materials, but its theoretical description generally requires computationally demanding two-time non-equilibrium calculations. We introduce an instantaneous approximation for pum…
2D Materials and ApplicationsOrganic and Molecular Conductors ResearchIron-based superconductors research
Sophie Gerits、Andrew Diggs、Nima Karimitari 等 6 位作者2026-08-17ChemRxiv
Free energy barriers for electrochemical reactions at solvated interfaces remain challenging to compute because they require extensive sampling of dynamic solvent and proton configurations beyond the reach of conventional ab initio molecular dynamics. Here, we show that a meta-GGA-trained, equivariant machine learned…
Machine Learning in Materials ScienceElectrocatalysts for Energy ConversionElectronic and Structural Properties of Oxides
Yifeng Xia、Guanghui Wang、Sining Wang 等 7 位作者2026-08-17arXiv (Cornell University)
Designing electrolyte molecules for lithium batteries requires balancing electronic stability with appropriate Li+ solvation, yet the structural basis remains unclear across chemically diverse molecules. High-throughput screening expands the searchable space, but ranked candidates alone do not reveal recurring motifs…
Advanced Battery Materials and TechnologiesMachine Learning in Materials ScienceCoordination Chemistry and Organometallics
Luman Shang、Shuming Zeng、Chenhan Liu 等 4 位作者2026-08-17arXiv (Cornell University)
Decoupling heat and charge transport is a key challenge in thermoelectrics. Here, we identify a route to spatially separate phonon and carrier transport in quasi-one-dimensional materials through high-throughput screening of the Materials Project database. Representative Sn$_2$S$_3$ and SbTeI exhibit a strong-intracha…
Machine Learning in Materials ScienceAdvanced Thermoelectric Materials and DevicesThermal properties of materials
Tadeáš Těhan、Jaromı́r Kopeček、Elizaveta Iaparova 等 5 位作者2026-08-17arXiv (Cornell University)
Mechanical properties and dynamical mechanical analysis were performed on compact Spark Plasma Sinter samples. It has been observed that the sample with less porosity reflects the behavior of superelasticity response. Other samples show failure during first cycles that may be due to porosity. Compaction of metallic po…
Powder Metallurgy Techniques and MaterialsShape Memory Alloy TransformationsMetallic Glasses and Amorphous Alloys
V. Mamitha、S. Lincy Mary Ponmani2026-08-17Molecular Crystals and Liquid Crystals
A novel organic single crystal of L-cysteine sodium formate (LCSF) was successfully grown by the solution growth technique. Single-crystal X-ray diffraction confirmed its triclinic crystal structure, while FTIR and EDAX analyses verified the functional groups and elemental composition. SEM images revealed well-develop…
Crystal Structures and PropertiesLuminescence and Fluorescent MaterialsNonlinear Optical Materials Research
Н. С. Морозов、V. Yu. Gubin、Vladimir A. Shulyak 等 12 位作者2026-08-17Applied Physics Letters
We report natural graphite-based multigraphene materials with thermal conductivity enhanced by 20% compared to our previously reported results. The influence of density on the thermal conductivity of these materials was examined. Increasing the density from 1.0 to 1.8 g cm−3 leads to a more than twofold enhancement in…
Fiber-reinforced polymer compositesThermal properties of materialsGraphene research and applications