3226 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 treating oxygen vacancies statistically, rather than using traditional models, is essential for accurately predicting their formation in high-entropy perovskite oxides, revealing that A-site cation size variance significantly influences vacancy thermodynamics and reduces temperature sensitivity.
By integrating electrical and photoelectrical characterization techniques with advanced numerical simulations, this study deciphers the defect landscape of wide-bandgap perovskite thin films, distinguishing between mobile ionic defects and recombination-active electronic states to reveal their specific energy distributions, concentrations, and mobilities.
This paper demonstrates that elliptically or circularly polarized light can dynamically switch zero-net-magnetization odd-parity magnets (such as -wave and -wave states) into finite spin-polarized states with controllable Chern numbers, offering a promising optical route for spintronics and quantum information applications.
This paper presents a parameter-free *ab initio* framework that overcomes the limitations of periodic boundary conditions in photoemission calculations by constructing open scattering states for semi-infinite crystal-vacuum interfaces, enabling accurate predictions of absolute quantum efficiency and vectorial photoemission for materials like Ag(111).
This paper demonstrates that cavity vacuum fluctuations can induce macroscopic polarization and magnetization in materials lacking these properties in free space by leveraging symmetry principles to enable quantum electrodynamical control of material responses.
This paper proposes "Nitrospinics," a new framework leveraging the unique properties of nitride materials, exemplified by the 2D MXene Cr2N, to enable energy-efficient orbital-torque spintronic devices and artificial intelligence hardware.
This study presents a novel Si-doped Li6.6Si0.6Sb0.4S5I iodide argyrodite electrolyte that achieves high room-temperature ionic conductivity (9.9 mS cm⁻¹) and enables stable, wide-temperature all-solid-state batteries with a LiNbO3-coated cathode, overcoming key interfacial and thermal challenges for next-generation energy storage.
This paper presents an efficient, two-stage analytical framework based on a solvable modified Kratzer model to retrieve fundamental material parameters of monolayer transition-metal dichalcogenides directly from optical and magneto-optical exciton spectra, enabling the accurate prediction of excitonic properties without the need for numerical fitting or matrix diagonalization.
This paper establishes a symmetry-based framework linking the structural stacking and twist angles of MoS2 bilayers to their second-order nonlinear optical response, demonstrating how specific symmetry breaking induces a frequency-independent rotation of second-harmonic generation patterns that enables precise, wavelength-independent determination of twist angles and the engineering of tailored optical functionalities.
This study demonstrates that MgO-based magnetic tunnel junctions can simultaneously exhibit linear, non-hysteretic magnetoresistance suitable for field sensing and non-volatile, quasi-analogue memristive behavior, with doping-induced power reduction and reversible switching capabilities that enable the co-integration of spintronic and memristive functionalities for advanced reprogrammable circuits and neuromorphic computing.