Materials Literature
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Quantum geometry, comprising of quantum metric and Berry curvature, plays a significant role in the electronic transport properties of solids. In this work, we theoretically investigate the quantum geometric properties of a Hopf-link semimetal, a distinct topological class that is charecterized by a nodal link-unlink…
We present an accelerated materials discovery framework that combines diffusion-based crystal structure generation with hierarchical screening to identify new rare-earth--transition-metal magnets simultaneously achieving high magnetization and thermodynamic stability. Using this workflow, we systematically explored ov…
We investigate the stability of elastic interfaces beyond the linear regime by considering penny-shaped crack fronts propagating through toughness heterogeneities. Using fracture mechanics simulations, we drive crack fronts through arrays of obstacles with tunable toughness contrast. At low contrast, the crack front s…
Abstract As open systems, arthropod joints and mechanical articulations face common challenges such as contamination and loss of lubricant. Recent studies suggest that insects manage these objectives of such open joints using a combination of cuticular microstructures and lubricating fluids. Here we provide an insight…
Abstract This study aims to find the impact of lattice-core geometry on the tensile and flexural properties of FDM-printed PETG-sandwich panels. Six core profiles (namely square, circular, elliptical, octagonal, pentagonal and hexagonal) were fabricated under controlled parameters of the FDM and tested based on ASTM D…
Physics-informed machine learning, digital twins, and additive manufacturing are a new direction for the creation of intelligent, adaptive, and high-performance engineering systems that are being integrated into a smart industrial framework. The strategy combines multimodal sensing, data fusion, physics-based modeling…
Large language models increasingly operate within systems that provide retrieved knowledge, policies, tool descriptions, workflow state, and other contextual signals. This work investigates Quantum Reservoir Assist, a pre-generation context-orchestration layer that uses a CUDA-Q-based quantum reservoir process to rank…
Abstract A new class of electrically tunable nanophotonic devices is presented combining atomically thin 2D materials and metasurfaces supporting quasi bound states in the continuum, with appealing potential applications.
Large language models increasingly operate within systems that provide retrieved knowledge, policies, tool descriptions, workflow state, and other contextual signals. This work investigates Quantum Reservoir Assist, a pre-generation context-orchestration layer that uses a CUDA-Q-based quantum reservoir process to rank…
This paper proposes a spectral-Galerkin method for the backward stochastic Allen-Cahn equation (BSACE), whose cubic nonlinearity is not globally Lipschitz. We construct spatially semi-discrete and space-time discrete schemes by combining spectral-Galerkin approximations in space with implicit Euler time stepping. Unde…
Abstract Luminescent benzochalcogenadiazole liquid crystals have attracted considerable interest owing to their combination of photophysical and mesomorphic properties. These compounds consist of central heterocycles containing oxygen, sulfur or selenium, linked to phenyl groups via triple bonds. These groups are then…
Abstract Electrochemical sensing of ascorbic acid (AA) and dopamine (DA) has attracted considerable attention owing to their important roles in biological systems; therefore, precise determination of these analytes is essential for biological and clinical analysis. In this work, an α-Fe2O3/CuO nanocomposite was synthe…
Natural fibers from different plants are widely used as reinforcing fillers in polymers because of ecological, economic and technical benefits with applications in all major industries. Since a typical drawback of incorporating natural fibers in polymers is the reduction of impact strength this work investigates ways…
The large-scale retirement of LiFePO4 (LFP) batteries is generating increasing amounts of Fe- and P-rich lithium-extraction slag, which is discarded as low-value solid waste. Herein, we report the direct upcycling of spent LFP (S-LFP)-derived slag into a reconstructed Fe-based electrocatalyst for the nitrate reduction…
In the context of intensified polymerization processes, solvent-free polymer synthesis has emerged as a promising route to reduce processing volumes and improve sustainability. However, the high viscosity during the reaction imposes mass‑ and heat transfer limitations, posing operational hurdles. To address these issu…
Global demand for electrochemical energy storage (EES) is rising, driven by integration of intermittent renewable energy sources like solar and wind, demand for electric vehicles with long ranges and quick charging times, and increasing ubiquity of portable electronics such as smartphones, laptops, power tools, and mo…
Hamiltonian structures for the passive dynamics of topological defects in nematic liquid crystals in two-dimensional systems are presented. Following the work by Miyoshi et al. (Miyoshi et al., 2024, Proc. R. Soc. A 480, 20240405), which demonstrated that the regularized Frank free energy associated with topological d…
We investigate degradation and surface protection of epitaxial 2H-MoTe2 films grown by molecular beam epitaxy on GaAs(111)B substrates. Using X-ray photoelectron spectroscopy (XPS), scanning tunneling microscopy, atomic force microscopy (AFM), Kelvin probe microscopy (KPM), Raman spectroscopy, and density functional t…
Amorphous materials are disordered solids without long-range structural order, making them useful systems for studying electron transport beyond the crystalline picture. This review discusses how structural disorder changes the spatial character of electron wavefunctions and how these changes govern carrier transport…
We present the first application of simulation-based inference to resonant inelastic X-ray scattering spectroscopy. Using truncated marginal neural ratio estimation to efficiently restrict the prior and conditional flow matching as the joint density estimator, we infer full posteriors with a modest simulation budget f…