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 9
Universal Drift Correction for Multidimensional Scanning Microscopy
In scanning microscopy, drift causes the specimen to be sampled at positions displaced from the nominal probe positions.AtomWorld-Mem: Memory-Restored World States for Long-Horizon Atomistic Evolution
High-fidelity atomistic evolution over long timescales requires more than observing the current crystal configuration.Phase-accumulating hyperfine strain sensing with rare-earth-ion phase memories
Long-lived hyperfine coherences in rare-earth-ion crystals provide controlled phase evolution windows for metrology.Scaling Density Functional Theory with Gaussian Splatting
Density functional theory (DFT) strikes a practical balance between accuracy and computational cost in many problems of computational chemistry and materials science.Retrainable physics-integrated neural differentiable modeling of sintering across material systems
Sintering is widely used to manufacture ceramics, but coupled densification and grain growth, material-dependent kinetics, and sparse measurements complicate predictive modeling and process design.CP-Agent: A Harness-Engineered Agent for Crystal Plasticity Simulation Workflows
Crystal plasticity (CP) simulations predict the mechanical behavior of polycrystalline metals, yet their routine use is hindered by the manual effort of configuring heterogeneous tools…Knowledge-Driven XRD Phase Identification via Multi-View Retrieval and Explanation
X-ray diffraction (XRD) is a experimental technique for determining the phase composition and structure of crystalline materials.Growth-Inspired Graph Generation and Inverse Design of Mechanical Lattices via Dot Matrices Database Augmentation and GCNN
Natural load-bearing and transport networks are not assembled in a single step; they emerge through a temporally ordered process of growth, branching, reinforcement, and loop formation.From Processing to Functionality: Engineering Accessible Material States in Cu-Embedded SiO$_x$ Memristive Devices
Resistive switching in oxide-based devices is widely governed by stochastic defect processes, yet a predictive link between fabrication conditions and functional behavior remains elusive.Beyond Compression: Training Latent Representations for Stable Long-Horizon Rollout in Neural Surrogate Solvers
Latent neural surrogate solvers, or latent dynamics models, accelerate simulations of time-dependent physical systems by evolving a compressed latent space rather than resolving full-resolution…Stable solutions of the Allen--Cahn equation in dimension three are one-dimensional
We prove that every bounded stable solution of the Allen--Cahn equation in $\mathbb R^3$ is one-dimensional.X2SBench: an open benchmark for evaluating crystal structure determination from powder diffraction
Progress towards practical powder X-ray diffraction (PXRD) structure determination requires evaluation beyond small crystals and idealized patterns.SoLiD26: A First Principles Solid-Liquid Interface Dataset for Machine-learned Interatomic Potentials
Machine-learned interatomic potentials (MLIPs) for solid-liquid interfaces in advanced materials applications, e.g., electrochemistry, catalysis and corrosion, require training data that samples…Scalable simulation of non-Markovian quantum transport by stochastic-phase bath reduction
Accurate simulations of non-Markovian quantum transport remain limited to small systems, and a key bottleneck is that each system site requires an independent set of quantum bath orbitals.Leakage-Safe Machine Learning for Hydrogen Embrittlement Detection in 316L Stainless Steel: A Region-Held-Out Evaluation of Texture and Deep Features in SEM Micrographs
Scanning electron microscopy (SEM) is routinely used to characterize the microstructural changes caused by hydrogen embrittlement (HE) in structural steels.Large-Area SnS Crystals by Controlled Sn-S Chemical Vapor Deposition: Growth Optimization, Morphology, and Raman Characterization
Tin monosulfide (SnS) is a layered IV-VI semiconductor with strong in-plane anisotropy and promising properties for optoelectronic and ferroic applications.Real-Time Atomic-Resolution Electron Phase Imaging without Probe Calibration via Ptychography-Supervised Learning
Atomic-scale phase imaging is central to resolving defects, interfaces, and weakly scattering atoms that govern the behavior of nanoscale materials.Deep Generative Crystal Structure Prediction: A Benchmark Study and a Controlled Test of Prototype Dependence
Deep generative models are widely reported to enable de novo crystal structure prediction (CSP), but their capability has not been measured consistently against template-based methods.Topology-Stratified Materials Discovery with A Flow-Based Generative Model
Accurate generation of crystal structures is the foundation to the discovery of high-performance materials for extreme-environment applications, such as aerospace, additive manufacturing, and fusion…An open benchmark for machine learning-based polymer property prediction
Polymer property prediction lacks open, standardized benchmarks that enable rigorous comparison of machine-learning methods, with existing resources covering only a narrow fraction of polymer…