🔬 Category

cond-mat.mtrl-sci

4007 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

Amortized Posteriors for Estimation of Material Constitutive Parameters from Multimodal Measurements on Small Punch Tests

This paper presents an amortized, likelihood-free framework combining Gaussian process surrogates and Conditional Flow Matching to efficiently estimate material constitutive parameters from multimodal Small Punch Test data, demonstrating that integrating Digital Image Correlation fields with force-displacement curves significantly improves posterior precision compared to using global response data alone.

Mohammad Ali Seyed Mahmoud, Aditya Venkatraman, Raj Mahat, Samantha Mitra, Surya R. Kalidindi2026-07-28
🔬 materials science

A General Model of Interfacial Chemical Equilibrium in Phase-Field Method

This paper introduces a general phase-field model for interfacial chemical equilibrium that utilizes auxiliary non-conserved variables to describe composition differences, unifying the WBM and KKS models as limiting cases while enabling direct integration of thermodynamic databases to solve complex problems like interdiffusion between ordered phases with non-overlapping composition ranges.

Yanzhou Ji, Long-Qing Chen2026-07-28
🔬 materials science

Proximity-induced Rashba spin-orbit interaction in BaMnO3∣_\text{3}|KTaO3_\text{3} heterostructure for antiferromagnetic spintronics

This study proposes and validates via DFT calculations a BaMnO3_3|KTaO3_3 heterostructure that successfully induces a strong Rashba spin-orbit interaction in the antiferromagnetic BaMnO3_3 layer through proximity to KTaO3_3, offering a promising pathway for advancing antiferromagnetic spintronics.

Vivek Kumar, Nirmal Ganguli2026-07-27✓ Author reviewed ⓘ
🔬 materials science

Robust Orbital-Selective Flat Bands in Transition-Metal Oxychlorides

This study identifies and experimentally validates a robust, room-temperature orbital-selective flat-band mechanism in van der Waals transition-metal oxychlorides (NbOCl2 and TaOCl2), arising from specific orbital hybridization and Peierls dimerization, thereby establishing a new design principle for realizing exotic quantum phases.

Xiangyu Luo, Ludovica Zullo, Sahaj Patel, Dongjin Oh, Qian Song, Asish K. Kundu, Anil Rajapitamahuni, Elio Vescovo, Nata (…)2026-07-27
🔬 condensed matter

NanoBTE: Fast Iterative Solution of the Phonon Boltzmann Transport Equation for Nanoscale Heat Transport

This paper presents NanoBTE, a deterministic finite-volume solver that efficiently solves the non-gray phonon Boltzmann transport equation for complex nanoscale geometries by integrating advanced boundary conditions, band-resolved properties, and hybrid CPU-GPU parallelization with synthetic iterative schemes to accelerate convergence in multiscale heat transport simulations.

Hongjiang Chen, Hai-Xuan Lin, Xiaole Tian, Hongyu Chen, Juan Zhang, Shengyao Yan, Hezhu Shao, Yu Wu, Junjie Liu, Hao Zha (…)2026-07-27
🔬 materials science

Generative and multimodal AI for materials prediction and design: Progress, challenges, and perspectives

This paper proposes a materials property hierarchy and evidence-based framework to address the challenges of substantiating novelty in AI-driven materials discovery, arguing that current limitations in multimodal data integration and benchmarking must be overcome through community-wide standards to enable the design of experimentally realizable materials.

Xianyuan Liu, Charles Anjah, Benjamin E. Jolly, Jonathon F. S. Markanday, Joshua Berry, Haolin Wang, Nicola A. Morley, R (…)2026-07-27
🔬 materials science

Symmetry-Adapted Physical and Vibrational Properties of Ferroelectric Perovskite Oxides: Application to PbZrxTi1-xO3

This paper applies group theory and tensor analysis to systematically map the symmetry-dependent physical and vibrational properties of ferroelectric PbZrxTi1-xO3, revealing that its morphotropic phase transition involves a continuous redistribution of Raman spectral intensity rather than the emergence of new modes, while highlighting the role of local symmetry breaking in interpreting its functional behavior.

Sumit Ranjan Maity, Brajesh Tiwari2026-07-27
🔬 physics

Learning Lattice Parameters from Powder X-Ray Diffraction Data Using Invariants

This paper introduces a machine learning method that improves the accuracy of predicting unit cell parameters from powder X-ray diffraction data by using a novel, convention-independent invariant lattice bispectrum representation as the model target instead of directly predicting the parameters themselves.

Elyssa Hofgard, Kyucheol Min, Nofit Segal, David W. Mittan-Moreau, Aria Mansouri Tehrani, Vanessa Oklejas, Jigyasa Nigam (…)2026-07-27