3501 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 study demonstrates that localized femtosecond laser irradiation of silicon carbide substrates, particularly those with an epitaxial graphene layer, effectively generates silicon vacancy centers and divacancies with lowered photoluminescence thresholds, offering a scalable method for creating defined color centers relevant to quantum technologies.
This study demonstrates that controlling chemical short-range order (SRO) in GeSn alloys through growth method selection (MBE vs. CVD) serves as a new degree of freedom for band engineering, enabling significant bandgap reduction beyond what is achievable by composition alone.
This study utilizes Brillouin-Mandelstam and Raman spectroscopy to demonstrate that while Si doping in AlN thin films causes non-monotonic changes in optical phonon frequencies due to strain and dislocation variations, it results in a monotonic decrease in acoustic phonon velocities, a finding critical for optimizing high-power semiconductor devices.
This study introduces the Northeast Materials Database (NEMAD), a comprehensive resource of 67,573 magnetic materials entries generated via Large Language Models, and demonstrates its utility in training machine learning models that achieve high accuracy in classifying magnetic types and predicting transition temperatures to accelerate the discovery of high-performance magnetic materials.
This study utilizes nuclear magnetic resonance and density functional calculations to confirm that both CrNbS and MnNbS exhibit chiral helical magnetism, demonstrating that the Mn compound maintains this ground state despite a higher density of structural defects.
This paper proposes a minimal Hubbard model to explain the ferrimagnetic ground state of the metal-organic framework CrCl(pyz), demonstrating that delocalized electrons on pyrazine sites couple with localized chromium spins to yield a magnetic moment and exchange interactions consistent with experimental observations.
This study utilizes a calibrated Phase-Field Discrete Element Model to demonstrate that precipitation-induced slowdowns in pressure-solution creep are driven by chemical solute accumulation when precipitation is slow, but by mechanical stress reduction when precipitation is fast.
This study presents a Gaussian Process-based framework incorporating Error-in-Variables to construct high-fidelity, uncertainty-aware equation of state tables for gold across extreme temperatures and densities, effectively addressing uncertainties in both input parameters and output thermodynamic properties derived from first-principles DFT data.
This study utilizes a deep neural network trained on density functional theory data to reveal that while increasing pressure up to 1000 MPa enhances the static dielectric constant of liquid water due to higher density and collective dipole fluctuations, it simultaneously reduces the Kirkwood correlation factor by disrupting the ideal tetrahedral hydrogen-bonding network.
This paper introduces AIM, a user-friendly MATLAB-based GUI that streamlines fixed-bed adsorption modeling by integrating isotherm fitting, mixture prediction, isosteric heat estimation, and breakthrough simulations, which were validated against experimental data for a ternary gas mixture.