4239 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 maps the phase diagram of compressively strained thin films, revealing a superconducting dome characterized by an electron-hole crossover and an anomalous Hall coefficient sign change that suggests Fermi surface reconstruction.
Using an X-ray free-electron laser, researchers observed that electronically heated palladium nanocrystals undergo a transient period of heterogeneous structural strain before achieving uniform thermal expansion.
This paper presents a multi-fidelity high-throughput screening protocol that utilizes foundational MACE machine-learning force fields and DFT calculations to efficiently identify and validate novel intercalation cathode materials for next-generation Na-, K-, Mg-, and Ca-ion batteries.
This first-principles DFT study investigates the thermodynamic, kinetic, optical, and mechanical properties of () hydrides, identifying as the most promising candidate for hydrogen storage due to its superior storage capacity.
This paper presents a second-order accurate, fixed-grid sharp-interface numerical method to solve the three-phase Stefan problem in spherical coordinates, demonstrating that kinetic energy terms significantly influence the phase change behavior of nanoparticles compared to larger particles.
BRAIN (Boltzmann Reinforcement for Analog Ising Networks) is a variational reinforcement learning framework that overcomes measurement noise in analog Ising machines by learning the Boltzmann distribution through aggregated information, significantly outperforming traditional MCMC methods in both accuracy and speed across various combinatorial topologies.
This paper proposes a new framework for non-Hermitian hyperuniformity and stealthiness, extending the concepts of correlated disorder and PT-symmetry to open systems to reveal unique scattering properties, such as unidirectional phases, that are impossible in Hermitian materials.
This paper demonstrates that the moiré potentials in heterobilayers originate from a combination of lattice reconstruction (inducing local strain and piezopotentials) and interlayer charge transfer (inducing built-in electric fields), which together determine the localization of charge carriers in both R-type and H-type moiré patterns.
The paper proposes the "Chiralometer," a novel mechanical detection method that uses temperature gradients or electric fields to induce uncompensated angular momentum in chiral crystals, generating a measurable macroscopic torque that serves as a direct probe for crystal chirality.
The paper proposes using the single-layer multiferroic interacting with surface phonon polaritons from a substrate as a platform to demonstrate cavity-mediated control of magnetic order by tuning the spiral wavelength and inducing a transition to ferromagnetism.