4962 papers
Condensed matter physics and materials science form a dynamic partnership, exploring how the collective behavior of atoms gives rise to the unique properties of solids and liquids. This field bridges the gap between fundamental quantum mechanics and the practical engineering of everything from flexible electronics to superconductors, turning abstract theories into tangible innovations that shape our daily lives.
At Gist.Science, we process every new preprint in this category directly from arXiv to make these complex discoveries accessible to everyone. Our team generates both plain-language overviews and detailed technical summaries for each paper, ensuring that researchers, students, and curious minds alike can grasp the latest breakthroughs without getting lost in dense jargon.
Below are the latest papers in condensed matter and materials science, organized by their most recent publication dates.
This paper demonstrates that gapped two-dimensional materials exhibiting the quantum anomalous Hall effect display universal optical transmission, reflection, and absorption coefficients at low temperatures that depend solely on the ratio of photonic to gap energy, featuring total reflection at energy equality and recovering graphene's fine-structure constant-dependent behavior in the vanishing gap limit.
This study demonstrates that hydrogen and deuterium tunneling in body-centered-cubic niobium is a fundamentally nonadiabatic, collective process mediated by anharmonic lattice couplings, which can only be accurately described by a five-dimensional lattice-renormalized framework that treats interstitial and transition-state lattice modes on equal quantum footing.
This study investigates relativistic spin-momentum locking in centrosymmetric CrSb and noncentrosymmetric MnTe, revealing that while -wave symmetry is preserved only under specific Néel vector and electric field alignments, ferroelectric altermagnets can exhibit mixed angular-momentum wave symmetries featuring both symmetry-protected nodal planes and accidental nodal surfaces.
This paper establishes that the non-normality of linearized update operators in neural network training, quantified by the condition number , serves as a robust early-warning indicator for transient instabilities and loss spikes that traditional spectral radius analysis fails to detect.
This study combines broadband ultrafast transient absorption spectroscopy with first-principles calculations to reveal that high-energy optical transitions in monolayer WSe exhibit significantly slower formation and relaxation dynamics than band-edge excitons due to the phonon-mediated formation of momentum-dark excitons.
This paper challenges the prevailing view that nonrelativistic effects in altermagnets are independent of spin-orbit coupling by predicting a giant, nonperturbative magnetic orbital Hall effect that is uniquely allowed in altermagnets, enabling field-free magnetization manipulation and strong room-temperature responses in materials like CrSb and FeSb2.
The paper introduces MetaDNS, a framework that integrates well-tempered metadynamics into discrete neural samplers to overcome mode collapse and enable efficient exploration of high-energy barriers for accurate free energy estimation in complex discrete distributions.
This first-principles study reveals that while Fe adsorption on biphenylene networks minimally affects in-plane mechanical properties, it dramatically enhances out-of-plane stiffness in bilayer structures and induces pronounced electrical conductivity anisotropy, highlighting its potential for tuning the material's functional properties.
This paper investigates an alternative path-finding approach utilizing the A* algorithm to compute the minimal-weight-matching centrosymmetry parameter, offering a potential solution to the flaws identified in existing molecular dynamics analysis methods.
This paper presents an automated deep learning framework utilizing an EfficientNetV1B0 Convolutional Neural Network to accurately classify nine distinct magnetic states, including complex antiferromagnetic textures, from RGB visualizations generated by atomistic spin dynamics simulations.