Condensed Matter · Physics & Astronomy
Materials Science
The newest papers in Materials Science that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
269 papers, from 31 August 2026 to 5 November 2026: 195 arXiv preprints and 74 OpenAlex records.
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Newest papers, page 4
Deep Scientific Reasoning under Physical Constraints: Structure-Aware Spectrum Prediction
Structured scientific spectra encode rich physical information while obeying hard constraints, such as conservation laws and characteristic spectral geometry.TCSP3.0: Template-Based Crystal Structure Prediction with Coefficient-Preserving Element Substitution and Structural Diversity
Template-based crystal structure prediction (CSP) transfers a known crystal structure to a new composition by element substitution, so its accuracy depends on retrieving suitable templates, mapping…MatOS: An Agent Operating System for Materials Research
Materials research relies on scattered and growing data, knowledge, and simulation tools, and a single study often spans multi-day workflows across literature analysis, computation, and experiment.Real-Time Correlation of Relaxation, Dephasing, and Two-level System Dynamics in Transmon Qubits
Materials improvements in transmon qubits have yielded remarkable advances in qubit lifetimes (T1)and coherence times (T2).Hidden Fisher Information in Many-Body Quantum Sensors
Quantum Fisher information (QFI) determines the ultimate precision of a quantum sensor after optimization over all allowed measurements, but it does not quantify how difficult the optimal readout is…Material criteria for angular-momentum transfer from twisted photons to photoelectrons
We study the material requirements for transferring the total-angular-momentum (TAM) projection of a twisted photon to the orbital angular momentum (OAM) of a photoelectron emitted from an $n$-type…High-quality, deep formation and identification of oxygen-vacancy defects in silicon carbide
Optically addressable paramagnetic defects in silicon carbide (SiC) are attractive for scalable quantum technologies such as quantum sensing.Probing the limits of forward screening and inverse design of crystal materials
Crystal materials are designed either by screening known crystals for a target property or by generating new crystals with that property.Exploring Joint-Embedding Predictive Architectures for Self-Supervised Representation Learning of Powder X-ray Diffraction Patterns
Powder X-ray diffraction (XRD) is the primary high-throughput method for resolving crystal structures, a cornerstone of materials science.The often overlooked role of sound in liquid thermal transport
Formulated a hundred years ago, the Bridgman formula for thermal conductivity of liquids postulates a proportionality between sound velocity and thermal conductivity.Screening strongly correlated materials in solid oxide cells with quantum simulation
We develop an end-to-end framework for assessing a quantum-computing application in industrial materials science: the screening of strongly correlated oxygen-electrode materials for SOFCs and SOECs.Compositional neural networks for multimodal X-ray and neutron scattering inversion
X-ray and neutron scattering are indispensable for structural characterization across condensed-matter physics and materials science.Automated Materials Data and Knowledge Extraction using Machine Learning and Large Language Models
Over the past decade, substantial efforts have been devoted to developing machine learning (ML) methods for extracting materials data and, where possible, materials knowledge directly from the…Delta-Doped GeV$^-$ in diamond with isotope resolvable optical spectra
Group IV color centers in diamond -- silicon, germanium, tin, and lead-vacancy centers -- are a promising platform for quantum networking.Learning the Geometry of Materials Space with Trained Neural Tangent Kernels
Neural networks trained to predict materials properties learn representations whose physical content can be difficult to extract.CrystalAR: Autoregressive Modeling for Symmetric Crystal Generation
Deep generative modeling has achieved remarkable progress in crystal generation.Enhancement of Li and Na Storage in Janus HfSSe Monolayers by Co-Induced Electron-Deficient Chalcogen Sites: A First-Principles Study
The growing demand for high-capacity, fast-charging, and durable rechargeable batteries has intensified the search for advanced electrode materials, with two-dimensional materials offering large…GBClaw: An agentic AI framework for atomistic grain boundary research and mechanistic discovery
Agentic artificial intelligence (AI) systems hold immense potential for automating complex workflows in materials discovery and design, but extending them to domain-intensive mechanistic…Sidewall Metrology Protocol for Superconducting Qubit Devices
Sidewall morphology is a potentially important factor influencing superconducting qubit performance, yet its quantitative characterization remains challenging due to the absence of standardized…Ammonia-Hydrogen Phase Equilibria in Planetary Envelopes from First-Principles-Based Machine-Learning Molecular Dynamics
Ammonia and hydrogen are major constituents of planets within and beyond the solar system, yet how they interact in planetary envelopes is poorly known.