2692 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 mechanical resonance measurements offer a rapid, non-destructive, and high-accuracy experimental method to guide the discovery of optimal compositions in complex high-entropy alloy design spaces by providing essential data to benchmark computational models.
This paper demonstrates that unsupervised nonlinear dimensionality reduction applied to the Inorganic Crystal Structure Database reveals a hidden low-dimensional geometric manifold that organizes crystalline materials, successfully segregating superconductors and enabling accurate prediction of critical temperatures without knowledge of the underlying pairing mechanism.
By combining fast differential scanning calorimetry with correlative STEM across a wide range of heating rates, this study reveals that interdiffusion in nanoscale Ni/Al multilayers proceeds hierarchically, transitioning from grain boundary-dominated transport at low temperatures to lattice diffusion at higher temperatures, thereby establishing grain boundaries as the primary control on reaction onset and microstructural design.
This paper demonstrates that compositional gradient engineering in ultrathin AlScN films mitigates leakage and breakdown by distributing structural discontinuities, thereby enabling robust ferroelectric switching in stacks as thin as 5 nm with significantly enhanced resistivity and polarization compared to homogeneous counterparts.
This paper evaluates seven fine-tuning strategies for machine-learned interatomic potential (MLIP) foundation models across diverse chemical benchmarks, revealing that while prerequisites like foundation model quality and correct energy initialization are paramount, naive fine-tuning is optimal for single-system accuracy whereas multihead replay uniquely preserves out-of-distribution robustness for broader deployment.
This paper proposes a unified framework linking electronic structure to intrinsic ductility by identifying shear amorphization as a lower-energy fracture criterion than dislocation nucleation, thereby enabling accurate predictions of ductility and ductile-to-brittle transitions for both pure metals and multi-principal-element alloys.
This paper warns that machine-learning interatomic potentials trained on PBE-based DFT data incorrectly predict the ground-state structure of HfO due to the functional's tendency to over-stabilize low-density phases, a flaw that can be mitigated by using alternative functionals like PBEsol or LDA.
This study reveals that introducing magnesium into lithium metal anodes induces a conditional spinodal decomposition between ordered B2 and Li-rich -BCC phases, creating a continuous interconnected microstructure that facilitates rapid lithium diffusion and suppresses dendrite formation at high current densities.
This study employs a novel approach combining photoluminescence imaging, drift-diffusion simulations, and Bayesian inference to map the spatially non-uniform degradation of perovskite solar cells, successfully distinguishing between bulk and interface defects and demonstrating that amino-silane passivation effectively suppresses interfacial degradation.
Using cryo-confocal microscopy and particle image velocimetry, this study reveals that volumetric expansion, rather than Marangoni flows, dominates fluid motion around bubbles during directional solidification, challenging existing theoretical models and offering new insights for controlling bubble distribution in solidified materials.