Preferred Synthesis of Armchair Transition Metal Dichalcogenide Nanotubes

This study demonstrates a novel synthesis strategy for producing chirality-preferred armchair transition metal dichalcogenide nanotubes with up to 84% yield by utilizing boron nitride nanotube templates to guide the rolling-up of energetically stable zigzag nanoribbons, a mechanism confirmed through combined experimental imaging, theoretical calculations, and real-time in-situ observations.

Abid, Luneng Zhao, Ju Huang, Yongjia Zheng, Yuta Sato, Tianyu Wang, Dmitry Levshov, Lingfeng Wang, Qingyun Lin, Zhen Han, Chunxia Yang, Bill Herve Nduwarugira, Yicheng Ma, Yige Zheng, Hang Wang, Salman Ullah, Afzal Khan, Qi Zhang, Wenbin Li, Junfeng Gao, Bingfeng Ju, Feng Ding, Yan Li, Wouter Herrebout, Kazu Suenaga, Shigeo Maruyama, Huayong Yang, Rong XiangFri, 13 Ma🔬 physics.app-ph

The crystalline properties of silica biomorphs vary within and between morphologies

Using X-ray texture and diffraction tomography, this study reveals that silica-witherite biomorphs exhibit significant variations in crystalline properties both within and between different morphologies, leading to a unified growth scheme that highlights the critical role of silicate oligomerization in their formation.

Moritz P. K. Frewein, Britta Maier, Moritz L. Stammer, Isabella Silva-Barreto, Anastasiia Sadetskaia, Asma Medjahed, Remi Tucoulou, Julie Villanova, Manfred Burghammer, Henrik Birkedal, Tilman A. GrünewaldFri, 13 Ma🔬 cond-mat.mtrl-sci

Visible and Terahertz Nonlinear Responses in the Topological Noble Metal Dichalcogenide PdTe2

This study demonstrates that single-crystal PdTe2_2 exhibits strong second- and third-order nonlinear optical responses in both visible and terahertz regimes, driven by its topological surface states and radiative photocurrents, positioning it as a promising material for advanced sensing, frequency mixing, and beam focusing applications.

George J. de Coster, Lucas Lafeta, Stefan Heiserer, Cormac Ó Coileáin, Zdenek Sofer, Achim Hartschuh, Georg S. Duesberg, Paul SeifertFri, 13 Ma🔬 cond-mat.mtrl-sci

Sensor free, self regulating thermal switching via anomalous Ettingshausen effect and spin reorientation in DyCo5

This paper proposes a sensor-free, self-regulating thermal switch utilizing the anomalous Ettingshausen effect in DyCo5_5, where a temperature-driven spin reorientation transition induces a two-order-of-magnitude contrast in anomalous Nernst conductivity due to Berry curvature hot spots, enabling robust thermal control without external electronics.

Shibo Wang, Hiroki Tsuchiura, Nobuaki TerakadoFri, 13 Ma🔬 physics.app-ph

Matlantis-PFP v8: Universal Machine Learning Interatomic Potential with Better Experimental Agreements via r2SCAN Functional

The paper introduces Matlantis-PFP v8, a universal machine learning interatomic potential trained on the more accurate r2SCAN functional rather than PBE, which achieves systematically improved agreement with experimental data and high-accuracy references across diverse chemical domains without requiring domain-specific fine-tuning.

Chikashi Shinagawa, So Takamoto, Daiki Shintani, Yong-Bin Zhuang, Yuta Tsuboi, Katsuhiko Nishimra, Kohei Shinohara, Shigeru Iwase, Yuta Tanaka, Ju LiFri, 13 Ma🔬 physics

Micropatterning photopolymerizable hydrogels for diffusion studies using pillar arrays or photomasks

This paper presents two novel microfluidic platforms—one utilizing pillar arrays and the other employing a custom Pt-coated PMMA photomask—for the in situ micropatterning of PEGDA-PEG hydrogels to enable precise control and tracking of molecular diffusion for diverse applications ranging from biosensing to drug delivery.

Sevgi Onal, Edmondo Battista, Hilal Nasir, Fabio Formiggini, Valentina Mollo, Raffaele Vecchione, Paolo NettiFri, 13 Ma🔬 physics

From Phase Prediction to Phase Design: A ReAct Agent Framework for High-Entropy Alloy Discovery

This paper introduces a ReAct-based LLM agent framework that autonomously designs high-entropy alloy compositions by iteratively querying a calibrated XGBoost surrogate, demonstrating superior performance over Bayesian optimization and random search in discovering diverse, experimentally viable phases while aligning its reasoning with empirical phase distributions.

Iman Peivaste, Salim BelouettarFri, 13 Ma🔬 cond-mat.mtrl-sci

Moiré in Γ\Gamma-valley square lattice: Copper- and iron-based superconductor simulation in a single device

This paper proposes a universal theoretical framework using twisted homobilayers of Γ\Gamma-valley square-lattice systems, specifically identifying ZnF2_2 as a promising candidate to simulate the effective models of high-temperature superconductors like cuprates and iron-based materials by realizing single-orbital and multi-orbital Hubbard models within their moiré bands.

Toshikaze Kariyado, Yusuf Wicaksono, Ashvin Vishwanath, Pavel Volkov, Zhu-Xi LuoFri, 13 Ma🔬 cond-mat

Exceptional Optical Phonon Coherence in Enriched Cubic Boron Arsenide via Suppression of Three-Phonon Scattering

This study demonstrates that isotopically enriched cubic boron arsenide exhibits record-high optical phonon coherence below 100 K due to the near-elimination of three-phonon scattering, with high-resolution spectroscopy revealing that defect scattering is negligible compared to isotope scattering in determining phonon linewidths.

Tong Lin, Fengjiao Pan, Gaihua Ye, Sanjna Sukumaran, Cynthia Nnokwe, Ange Benise Niyikiza, William A. Smith, Stephen B. Bayne, Rui He, Zhifeng Ren, Hanyu ZhuFri, 13 Ma🔬 cond-mat.mtrl-sci

Switchable circular dichroism and ionic migration dominated charge transport in a chiral spin crossover polymer

This study demonstrates that a chiral spin crossover polymer exhibits thermally switchable circular dichroism linked to Fe 3d electronic reorganization and displays charge transport dominated by ionic migration rather than electronic carriers.

M Zaid Zaz, Sartaz Sakib, Wai Kiat Chin, Peace Adegbite, Gauthami Viswan, Alpha T Ndaiye, Andrew J Yost, Rebecca Y Lai, Peter A DowbenFri, 13 Ma🔬 cond-mat.mtrl-sci

Pseudo Point Nodal Superconducting Gap in Spin-Triplet UTe2_2

High-resolution thermal conductivity measurements on high-quality UTe2_2 single crystals reveal a fully gapped superconducting state with a pseudo point-nodal structure, where gap minima approach but do not reach zero, thereby resolving conflicting reports on the gap anisotropy and excluding non-unitary mixing of pairing symmetries.

S. Hosoi, K. Imamura, M. M. Bordelon, E. D. Bauer, S. M. Thomas, F. Ronning, P. F. S. Rosa, R. Movshovich, I. Vekhter, Y. MatsudaFri, 13 Ma🔬 cond-mat

Intrinsic Even-Odd Thickness-Driven Anomalous Hall in Epitaxial MnBi2Te4 Thin Films

Through precise molecular beam epitaxy synthesis of MnBi2Te4 thin films, researchers demonstrated that controlling layer thickness induces a striking even-odd dependence in the anomalous Hall effect, where odd layers exhibit robust non-compensated antiferromagnetism and even layers show minimal response, offering a pathway toward realizing the zero-field quantum anomalous Hall effect.

Debarghya Mallick, Simon Kim, An-Hsi Chen, Gabriel A. Vázquez-Lizardi, Alessandro R. Mazza, T. Zac Ward, Gyula Eres, Yue Cao, Debangshu Mukherjee, Hu Miao, Liang Wu, Christopher Nelson, Danielle Reifsnyder Hickey, Robert G. Moore, Matthew BrahlekFri, 13 Ma🔬 cond-mat.mtrl-sci

Electronic Coherence Evolution at the Nearly Commensurate Incommensurate CDW Boundary of 1T-TaS2

Using temperature-dependent angle-resolved photoemission spectroscopy, this study reveals that the nearly commensurate to incommensurate charge density wave transition in 1T-TaS2 is driven by a momentum-dependent loss of electronic coherence and spectral weight redistribution rather than a conventional metal-insulator transition, offering new microscopic insights into the material's room-temperature resistivity anomaly.

Turgut Yilmaz, Yi Sheng Ng, Menka Jain, Xiao Tong, Thipusa Wongpinij, Pat Photongkam, Anil Rajapitamahuni, Asish K. Kundu, Jin-Cheng Zheng, Elio VescovoFri, 13 Ma🔬 cond-mat

MaterialFigBENCH: benchmark dataset with figures for evaluating college-level materials science problem-solving abilities of multimodal large language models

The paper introduces MaterialFigBench, a benchmark dataset of 137 university-level materials science problems requiring figure interpretation, which reveals that despite improvements in multimodal large language models, they still struggle with genuine visual reasoning and quantitative analysis, often relying on memorized knowledge rather than accurately reading provided diagrams.

Michiko Yoshitake, Yuta Suzuki, Ryo Igarashi, Yoshitaka Ushiku, Keisuke NagatoFri, 13 Ma💬 cs.CL

Atomic-Scale Mechanisms of SiO2_2 Plasma-Enhanced Chemical Vapor Deposition Revealed by Molecular Dynamics with a Machine-Learning Interatomic Potential

This study employs molecular dynamics simulations with a machine-learning interatomic potential to reveal the atomic-scale mechanisms of SiO2_2 plasma-enhanced chemical vapor deposition, elucidating how oxidant-to-silane ratios govern network formation via Si-OH condensation and how high-energy plasma species influence film stoichiometry, density, and surface roughness.

Jaehoon Kim, Minseok Moon, Hyunsung Cho, Hyeon-Deuk Kim, Rokyeon Kim, Gyehyun Park, Seungwu Han, Youngho KangFri, 13 Ma🔬 cond-mat.mtrl-sci

Valley-dependent electron-phonon scattering in thermoelectric semimetal Ta2_2PdSe6_6

This study theoretically reveals that the strong electron-hole asymmetry in the carrier lifetime of the thermoelectric semimetal Ta2_2PdSe6_6 originates from valley-dependent electron-phonon scattering, where a soft phonon mode coupled to the valence band induces sharp scattering near the Fermi level for electrons but only moderate scattering for holes.

Masayuki Ochi, Hitoshi Mori, Akitoshi NakanoFri, 13 Ma🔬 cond-mat.mtrl-sci

Meta-generalized gradient approximation made in the Hartree gauge

This paper proposes a meta-generalized gradient approximation for the exchange energy constructed explicitly within the Hartree gauge, utilizing the hydrogen atom's exchange energy density to align gauges in core and asymptotic regions, thereby enabling the formulation of density functionals at the energy density level to expand machine learning datasets and improve nonlocal functional accuracy.

Yan Oueis, Akilan Ramasamy, James W. Furness, Jamin Kidd, Timo Lebeda, Jianwei SunFri, 13 Ma🔬 cond-mat.mtrl-sci