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 presents an automated, cyclic framework that integrates neural network training with crystal structure prediction to generate diverse training data and develop reliable machine learning interatomic potentials with minimal human intervention.
This paper demonstrates that a modified non-orthogonal local submatrix method achieves over 1.1 EFLOP/s on 4,400 NVIDIA A100 GPUs, enabling ab-initio molecular dynamics simulations of SARS-CoV-2 spike proteins containing up to 83 million atoms.
This paper presents the CP2K atomistic simulation package, highlighting its second-generation Car-Parrinello molecular dynamics capabilities and detailing development strategies for massively parallel low-scaling solvers and approximate computing on low-precision hardware to prepare for the exascale era.
This paper establishes general recommendations for verifying the precision of density-functional-theory implementations by presenting a universal, reproducible workflow based on AiiDA that generates a comprehensive reference dataset of 960 equations of state across the periodic table to cross-check all-electron codes and improve pseudopotential-based approaches.
This paper proposes and experimentally demonstrates a mechanism using tunable magnetic anisotropy to stabilize and magnetically drive one-dimensional chains of topological bimerons within the helical ground state of D-symmetric magnets, offering a scalable route for low-dissipation spintronic applications.
This paper introduces a high-throughput database of thousands of theoretically twistable 2D semimetals and insulators derived from the Topological 2D Materials Database, providing a foundational resource for exploring moiré superlattices and strongly correlated physics.
This study utilizes low-temperature STM/STS to demonstrate that while polymer-free transfer preserves the structural integrity of 9-atom-wide armchair graphene nanoribbons on graphene substrates, it induces significant degradation in nanoribbons with modified edge topologies, thereby establishing a critical framework for assessing post-processing modifications essential for reliable nanoelectronic device integration.
This review provides a practical guide to the versatile CP2K software package, focusing on its application for simulating diverse atomistic systems using quantum-mechanical and classical methods, while prioritizing usage over theoretical depth.
This paper presents a computational framework that systematically identifies first-order saddle points to map the energy landscape and transition mechanisms of metastable magnetic textures in 2D chiral magnets, revealing a hierarchical network of nucleation, annihilation, and rearrangement processes that preserve or alter topological charge.
This study demonstrates through first-principles calculations that monolayer 1T-SnTe2 is a stable metallic 2D material exhibiting ultralow and anisotropic lattice thermal conductivity driven by heavy atomic mass, weak bonding, and flat acoustic phonon branches, thereby highlighting its significant potential for thermoelectric and optoelectronic applications.