2756 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 proposes a minimal nonlinear ODE model demonstrating that a saddle-node bifurcation in interfacial morphology governs battery degradation, successfully mapping various anode configurations onto a stability spectrum where anode-free lithium sits near the critical threshold, thereby predicting universal instability and validating key experimental trends.
This paper demonstrates that thermally induced curvature in hexagonal boron nitride (hBN) flakes creates strain gradients that suppress phonon coupling, thereby significantly enhancing the room-temperature spectral purity and coherence of embedded single-photon emitters.
This paper introduces QT-Net, a rotationally augmented graph neural network evaluated via a principled out-of-distribution protocol based on SOAP descriptors, which demonstrates that inferring atomic properties like electron populations and multipoles improves downstream molecular property prediction and accurately recovers ground-truth dipole moments.
This study establishes the noncentrosymmetric rare-earth germanides RGaGe (R = Ce, Pr, Nd) as a tunable platform for exploring the evolution from d- to f-orbital dominated topology and demonstrates their giant intrinsic anomalous Hall effect driven by robust Weyl semimetallic states coupled with magnetic order.
This study employs machine learning enhanced by generative adversarial network-based data augmentation to successfully predict body-centered cubic phase stability in cobalt-free high-entropy alloys, identifying mixing enthalpy and atomic size difference as key descriptors with 84% accuracy.
This paper challenges the conventional use of single oxygen vacancy formation energy for screening perovskite thermochemical materials by demonstrating that accounting for finite vacancy concentrations and configurational entropy in doped CaMnO3 provides a more accurate, experimentally consistent framework for predicting equilibrium oxygen stoichiometry and guiding high-throughput material discovery.
Using first-principles calculations and Monte Carlo exploration, this study elucidates the atomic-scale structure of Eu in -SiAlON phosphors, confirming a planar Eu-N coordination model that explains the material's weak electron-phonon coupling, resolved vibronic peaks, and the red-shift of emission with increasing Al/O concentration.
This study resolves the long-standing puzzle of the sign reversal in the temperature dependence of the bandgap in CsPb(Br,Cl)3 nanocrystals by demonstrating that the inversion, occurring at chlorine concentrations above 40%, is driven solely by a unique electron-phonon coupling mechanism involving synchronous octahedral tilting and cesium rattling.
This paper demonstrates that spin dynamic mean-field theory (spinDMFT) is an efficient and accurate method for simulating spectral spin diffusion and zero-quantum line shapes in static disordered solids, successfully matching experimental data for test substances where exact brute-force calculations are infeasible.
By employing quasi-simultaneous synchrotron X-ray diffraction and tomography to analyze Al-Mn alloy solidification, this study elucidates the nucleation and co-growth dynamics of peritectic structures, revealing how Mn-rich diffusion layers govern phase transformations and how cooling rates can be tuned to control defect formation and morphology transitions.