4173 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 benchmarks five foundational machine learned interatomic potentials against DFT-NEB calculations to evaluate their accuracy in predicting ionic migration barriers, revealing that models like MACE-MP-0 and Orb-v3 excel in barrier prediction and high-throughput screening despite a lack of correlation with local geometry accuracy.
This study utilizes a machine learning potential to demonstrate that uniaxial compressive stress significantly influences polarization switching and domain wall evolution in tetragonal BaTiO3, revealing a critical threshold of approximately 120 MPa for 90-degree switching, stress-induced reductions in remnant polarization and coercive field, and the emergence of double hysteresis loops at 80 MPa.
This study demonstrates that controlling sulfur stoichiometry and growth kinetics during molecular beam epitaxy on silicon substrates enables the creation of defect-engineered Mo/MoS heterostructures with residual metallic Mo and sulfur vacancies, which significantly enhance hydrogen evolution reaction performance by activating inert basal planes and improving charge transfer compared to stoichiometric films.
This paper presents a robust convolutional neural network trained on realistic micromagnetic simulations that accurately and reliably estimates interfacial Dzyaloshinskii-Moriya interaction strength from magnetic bubble domain textures, offering a fast and quantitative alternative to inconsistent experimental methods.
This study employs first-principles calculations to map the structural, electronic, and hyperfine properties of the NaRTiO Ruddlesden-Popper series, revealing how ionic radius dictates the competition between ground-state symmetries and establishing Electric Field Gradient signatures as a sensitive probe for resolving these structures via experimental techniques like NMR and PAC.
This paper introduces \texttt{SingingMaterials}, a modular Python package that sonifies phonon density-of-states data from the Materials Project using three distinct approaches, and validates through a user study that auditory representations can effectively help listeners distinguish differences in material properties.
This paper demonstrates that heteroepitaxial -AlO grown on TiN via pulsed laser deposition forms a high-quality, single-crystal dielectric with an intrinsically low two-level system loss of , establishing it as a promising materials platform for reducing dielectric losses in superconducting quantum circuits.
This study utilizes non-empirical hybrid functional calculations to validate the electronic properties and surface stability of lead-free CsMX vacancy-ordered double perovskites, revealing that CsX-terminated surfaces avoid detrimental in-gap trap states and identifying specific candidates with optimal energy level alignment for next-generation optoelectronic applications.
This study demonstrates that while a long-range MACELES model significantly improves the quantitative accuracy of predicting transition temperatures, elastic constants, and dielectric constants for BaTiO3 compared to a local-only model, both approaches successfully reproduce the material's key qualitative ferroelectric behaviors such as phase transitions and polarization switching.
This study employs first-principles calculations to systematically investigate two-dimensional transition-metal trihalide monolayers, identifying MnF3 and PdF3 as promising candidates for the quantum anomalous Hall effect due to their spin-orbit coupling-induced band gaps, nonzero Chern numbers, and chiral edge states.