4797 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 crystal symmetry can predict unconventional compensated magnetism in materials without prior knowledge of their magnetic ground states, enabling the identification of thousands of promising candidates where 68% of prioritized examples exhibit unconventional character.
This study reports the discovery of correlated electronic states in the conduction bands of near-AA-twisted bilayer MoS, revealing a twist-angle-dependent phase diagram where Pomeranchuk-like electronic localization persists above 100 K, distinguishing it from similar phenomena in graphene systems.
This paper presents an AI-guided, high-throughput closed-loop platform that successfully discovered and validated durable, iridium- and ruthenium-free palladium-oxide catalysts, specifically InMnPdOx and NiTaPdOx, which significantly outperform conventional designs in activity and stability for acidic oxygen evolution in proton-exchange-membrane water electrolysis.
This paper introduces projected amorphous topological insulators (PATIs), a new class of systems where a fraction of randomly selected disconnected sites from a parent crystal retains quantized global or fragile local topological invariants and boundary modes, exhibiting a tunable strong-to-fragile quantum phase transition characterized by a specific correlation length exponent.
This paper demonstrates that current-induced magnon creation and annihilation significantly distort spin-orbit torque estimates in various bilayer systems, leading to substantial overestimations if unaccounted for, and proposes a reliable method to quantify and correct these effects by combining nonlinear magnetoresistance measurements.
This study provides compelling experimental evidence for chiral fermion edge modes in -RuCl by demonstrating that geometrically constricted samples retain a significant thermal Hall signal at low temperatures where bulk crystals do not, thereby validating a theoretical method to distinguish topological heat carriers and identify chiral spin liquids.
This study reports that LaPbO undergoes a pressure-suppressible structural phase transition at 225 K driven by La-Pb dimerization rather than Fermi surface instability, which competes with pressure-induced superconductivity reaching a maximum critical temperature of 10 K.
This paper demonstrates that magnetically doped topological insulators serve as a versatile platform for realizing non-Hermitian dynamics, specifically exhibiting the non-Hermitian skin effect in the quantum anomalous Hall phase and asymmetric bidirectional coupling in the metallic phase through tunable chiral edge states.
This study demonstrates that a modified ligand-assisted reprecipitation (LARP) method, enhanced by amine-mediated size trimming and DDAB surface passivation, produces single CsPbBr3 perovskite quantum dots with state-of-the-art optical properties, including stable emission and high-purity single-photon generation, establishing it as a viable, milder alternative to traditional hot-injection synthesis.
This paper establishes that polyconvexity implies true-stress-true-strain monotonicity in incompressible isotropic hyperelasticity, a finding used to design and calibrate four physics-augmented neural network architectures that reveal significant differences in extrapolation performance despite satisfying identical constitutive constraints.