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.

🔬 materials science

Visualizing the Zhang-Rice singlet, molecular orbitals and pair formation in cuprate

Using scanning tunneling microscopy on hole-doped Ca2CuO2Cl2\mathrm{Ca_2CuO_2Cl_2}, this study visualizes the formation of localized Zhang-Rice singlets that evolve into delocalized molecular orbitals with stripe-like patterns, proposing that these states mediate Cooper pair formation through the antiferromagnetic spin background.

Shusen Ye, Jianfa Zhao, Zhiheng Yao, Sixuan Chen, Zehao Dong, Xintong Li, Luchuan Shi, Qingqing Liu, Changqing Jin, Yayu (…)2026-09-09
🔬 materials science

Irida-Graphene Phonon Thermal Transport via Non-equilibrium Molecular Dynamics Simulations

This study utilizes non-equilibrium molecular dynamics simulations to reveal that the newly proposed 2D carbon allotrope, Irida-Graphene, exhibits an intrinsic room-temperature thermal conductivity of approximately 215 W/mK—significantly lower than pristine graphene due to phonon scattering from its porous 3-6-8 ring structure and reduced group velocities—while maintaining isotropic thermal transport with notable size effects.

Isaac M. Felix, Raphael M. Tromer, Leonardo D. Machado, Douglas S. Galvão, Luiz A. Ribeiro, Marcelo L. Pereira2026-09-09
🔬 materials science

Lattice Thermal Conductivity of Sun-Graphyne from Reverse Nonequilibrium Molecular Dynamics Simulations

This study employs reverse non-equilibrium molecular dynamics simulations to demonstrate that Sun-Graphyne, a 2D carbon allotrope, possesses a significantly lower intrinsic thermal conductivity of approximately 24.6 W/mK compared to graphene due to enhanced phonon scattering caused by acetylenic bonds and acoustic-optical mode interactions, making it a promising material for applications requiring reduced thermal transport.

Isaac de Macêdo Felix, Raphael Matozo Tromer, Leonardo Dantas Machado, Douglas Soares Galvão, Luiz Antônio Ribeiro, Marc (…)2026-09-09
🔬 materials science

Exploring Novel 2D Analogues of Goldene: Electronic, Mechanical, and Optical Properties of Silverene and Copperene

This study utilizes density functional theory to demonstrate that silverene and copperene, the proposed monolayer analogues of goldene, are energetically and dynamically stable 2D materials with isotropic mechanical properties and unique metallic-optical characteristics suitable for optoelectronic applications.

Emanuel J. A. dos Santos, Rodrigo A. F. Alves, Alexandre C. Dias, Marcelo L. Pereira Junior, Douglas S. Galvão, Luiz A. (…)2026-09-09
🔬 materials science

Computational Characterization of the Recently Synthesized Pristine and Porous 12-Atom-Wide Armchair Graphene Nanoribbon

This study employs density functional theory and molecular dynamics simulations to demonstrate that introducing periodic porosity into 12-atom-wide armchair graphene nanoribbons effectively tunes their electronic, optical, and thermal properties while maintaining structural stability, thereby establishing porosity engineering as a viable strategy for advanced nanodevice applications.

Djardiel da S. Gomes, Isaac M. Felix, Willian F. Radel, Alexandre C. Dias, Luiz A. Ribeiro Junior, Marcelo L. Pereira Ju (…)2026-09-09
🔬 applied physics

Deep Learning to Automate Parameter Extraction and Model Fitting of Two-Dimensional Transistors

This paper presents a deep learning framework that automates the extraction of physical parameters and model fitting for two-dimensional transistors by leveraging a pre-trained neural network to approximate physics-based simulators, achieving high accuracy with significantly fewer training samples than previous methods.

Robert K. A. Bennett, Jan-Lucas Uslu, Harmon F. Gault, Asir Intisar Khan, Lauren Hoang, Tara Peña, Kathryn Neilson, Youn (…)2026-09-09
🔬 materials science

A Concise Review of Recently Synthesized 2D Carbon Allotropes: Amorphous Carbon, Graphynes, Biphenylene and Fullerene Networks

This paper provides a concise review of recently experimentally realized 2D carbon allotropes—including graphynes, biphenylene networks, fullerene networks, and amorphous carbon—by analyzing their structures, synthesis methods, and the interplay between theoretical predictions and experimental findings while highlighting gaps for future investigation.

Ricardo Paupitz, Alexandre F. Fonseca, Mizraim Bessa, Guilherme S. L. Fabris, William F. da Cunha, Leonardo D. Machado (…)2026-09-09