2898 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 presents a design strategy for achieving broadband optical gain beyond 2 μm in GaSb-based waveguide amplifiers by utilizing asymmetric GaInSb/AlGaAsSb quantum wells of varying thicknesses to create a flat gain spectrum with a simulated bandwidth exceeding 340 nm.
This paper demonstrates that boron-vacancy color centers in hexagonal boron nitride serve as high-resolution, quantitative strain sensors capable of precisely measuring lattice deformation and validating strain-induced Raman shifts in two-dimensional materials.
This paper theoretically investigates the tunable dynamical behaviors of antiferromagnetic domain walls under spin-polarized currents, revealing distinct regimes of precessional, propagating, and oscillatory motion depending on current polarization, characterizing their velocity and asymmetric profiles, and discussing the impact of Dzyaloshinskii-Moriya interaction and large induced magnetization for potential experimental detection.
This study proposes 4/Co (Rh, Pd, Ru) atomic bilayers on Re(0001) as a new platform for realizing thermally stable, zero-field isolated skyrmions with nanoscale radii, a prediction confirmed by first-principles calculations and atomistic spin simulations that incorporate higher-order exchange interactions.
This study reports the synthesis and magnetic characterization of quasi-1D magnesium lanthanide borates (Mg$Ln_5_{10}$), revealing distinct single-ion anisotropy behaviors across the lanthanide series and identifying MgGdBO as a promising candidate for solid-state refrigeration at liquid helium temperatures.
This paper reports the experimental synthesis of a two-dimensional nitrogen crystalline structure, termed nitrogene, on silver surfaces via ion-beam-assisted epitaxy, revealing a puckered honeycomb lattice with a predicted band gap of up to 7.5 eV suitable for ultraviolet optoelectronic and high-k dielectric applications.
This paper introduces an efficient, first-principles framework that computes photoelectron states as Kohn-Sham scattering solutions to enable accurate, transparent, and widely compatible simulations of angle-resolved photoemission spectroscopy (ARPES), as demonstrated by excellent agreement with experimental data for graphene and WSe.
This study proposes a new computational random graph algorithm that unifies low-temperature bosonic and high-temperature crystalline paradigms to analytically model solid amorphous inorganic structures, successfully explaining the boson peak phenomenon and validating its results against experimental neutronography data without requiring melting simulations.
This paper introduces SCALAR, a benchmark designed to evaluate how materials foundation models handle geometric scale generalization and structural reasoning across diverse nanoparticle structures, revealing that while explicit physics-grounded reasoning can reduce hallucinations and errors, it often compromises output consistency and validity.
This study employs density functional theory to elucidate how hydrogen uptake in brownmillerite perovskites induces localized electronic and magnetic changes, establishing design rules based on B-site d-electron counts and lattice flexibility while highlighting the need for careful computational treatment and machine-learning benchmarks to guide the development of hydrogen-responsive iono-electronic devices.