cond-mat.mtrl-sci 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.

🔬 materials science

From Evaluation to Design: Using Potential Energy Surface Smoothness Metrics to Guide Machine Learning Interatomic Potential Architectures

This paper introduces the Bond Smoothness Characterization Test (BSCT), a computationally efficient metric that detects potential energy surface non-smoothness to both validate Machine Learning Interatomic Potentials and guide iterative architectural improvements, resulting in models that achieve low regression errors while ensuring stable molecular dynamics simulations.

Ryan Liu, Eric Qu, Tobias Kreiman, Samuel M. Blau, Aditi S. Krishnapriyan2026-06-02

🔬 applied physics

19 GHz Single-Ended-to-Balanced Modified Ladder-Lattice Filters Realized Using Periodically Polarized AlScN BAW Resonators

This paper presents the design and characterization of two 19 GHz single-ended-to-balanced modified ladder-lattice filters realized using periodically polarized AlScN BAW resonators, which eliminate the need for baluns while demonstrating competitive insertion loss, bandwidth, and out-of-band rejection for wireless communication applications.

Merrilyn M. A. Fiagbenu, Shun Yao, Siddhant Sahoo, Mojtaba Hodjat-Shamami, Daeho Kim, Craig Moe, Pinal Patel, Ramakrishn (…)2026-06-02

🔬 materials science

Beyond Text and Tables: Vision-Language Model Integration in ComProScanner for Extracting Materials Data from Scientific Figures with High Accuracy

This paper presents an enhanced version of the ComProScanner framework that integrates vision-language models to automatically extract composition-property data from scientific figures, achieving high accuracy and cost-effectiveness while establishing the first fully automated, multimodal pipeline for mining materials data from text, tables, and images.

Aritra Roy, Enrico Grisan, Chiara Gattinoni, John Buckeridge2026-06-02

🔬 materials science

Advances in electrical contacts to single crystals of emerging materials for transport measurements

This review highlights recent technological advancements in fabricating high-quality, lithographically defined multi-terminal electrical contacts on emerging single crystals, providing a practical guide to overcome challenges posed by their irregular geometries and structural characteristics for reliable transport measurements.

Huandong Chen, Abhay. N. Pasupathy, Jayakanth Ravichandran2026-06-02

🔬 materials science

Data-Driven Discovery of Unconventional Antiferromagnets

This paper presents a scalable, data-driven framework that screens a vast materials database to identify and classify 36 previously unreported altermagnets and 9 Luttinger-compensated ferrimagnets, establishing a high-throughput route for discovering unconventional antiferromagnets with promising spintronic applications.

Qirui Cui, Chenxu Liu, Anna Delin, Kaiyou Wang2026-06-02

🔬 materials science

Synthesis of single-layered fluorographdiyne nanosheets via selective on-surface 2D covalent polymerization

This paper reports the successful synthesis of single-layered fluorographdiyne nanosheets up to 60×60 nm² on an Au(111) surface via a selective on-surface 2D covalent polymerization method that combines cobalt catalysis and coronene templating to overcome previous challenges in achieving large, defect-free domains.

Chen-Hui Shu, Yi Zheng, Tao Lin, Li-Xia Kang, Zhang Qu, Zhi-Yu Wang, Ying Wang, Zheng-Yang Huang, Qian Liu, Hang Xu, Cho (…)2026-06-02

🔬 materials science

Impact of Disorder Dynamics and Multi-Domain Kinetics on the Sliding Ferroelectricity of CVD-Grown 3R-WSe2 Bilayers

This study investigates the ferroelectric switching characteristics of CVD-grown 3R-WSe2 bilayers using a graphene-based field-effect transistor, revealing that growth-induced structural disorder significantly impacts polarization switching while multi-domain kinetics govern the evolution of the ferroelectric response.

Sourav Paul, Prasenjit Ghosh, Krishna Prasad Maity, Vineet Pandey, Abhijith M. B., Premananda Chatterjee, Kenji Watanabe (…)2026-06-02

🔬 materials science

Manifold Diffusion for Structure Generation of Transition Metal Complexes

This paper introduces TMCgen, a manifold diffusion model that efficiently and accurately generates the three-dimensional geometries of diverse transition metal complexes by focusing on key degrees of freedom such as coordination angles and ligand torsions.

Luca Schaufelberger, Kjell Jorner2026-06-02

🔬 applied physics

Topological Edge States from Molecular Chirality: A General Framework for Dimerized Dipolar Arrays

This paper establishes a general theoretical framework demonstrating that molecular chirality in dimerized dipolar arrays induces tunable topological edge states with unique stereochemical labeling, offering a controllable platform for quasi-one-dimensional topological quantum matter.

Muhammad Arsalan Ali Akbar, Mohsin Raza, Sabre Kais2026-06-02

🔬 materials science

Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach

This paper proposes a novel multimodal learning approach to model the interfaces of stacked bilayer 2D materials and predict their emergent properties, addressing a gap in AI-driven materials discovery by demonstrating superior effectiveness and efficiency compared to baseline methods.

An Vuong, Minh-Hao Van, Chen Zhao, Xintao Wu2026-06-02

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