Liquid Sb and Bi are two pnictogens whose structure factors show the Friedel shoulder characteristic of nonsimple liquid metals. We compute their shear viscosity with a static, pairwise pipeline, a Bretonnet–Silbert (BS) pseudopotential with Rice–Allnatt transport theory. The main result is component resolved: the soft-tail contribution accounts for 54%–59% of the viscosity yet supplies little of its measured temperature dependence. The calculation runs from each melting point to at least 500K above it, uses five local-field corrections and the Zahid parameters, and resolves the temperature gradient |dη/dT| into kinetic, hard-core, and soft-tail components. The calculated gradient is systematically too weak: η is underestimated at the melting point (−16% for Sb, −32% for Bi) and overestimated at high temperature. Because ηs is an integral over g(r), replacing the hard-sphere form gHS(r) with a modified hypernetted-chain (MHNC) one changes ηs by −2 to ＋21%, but does not recover the gradient; nor does varying the pseudopotential parameters across the BS physical window, so no single tested ingredient accounts for it. The local-field correction changes η by only 3%–4%, an order of magnitude less than the spread from the non-unique BS parameters; the ab initio molecular-dynamics data are too sparse to test the gradient. These results delimit the static, pairwise framework for Sb and Bi and identify the component that such dynamic, many-body, or screening extensions need to address.
Single wall carbon nanotubes (SWCNTs) are promising building blocks for nanoelectronic and optoelectronic devices, yet reliable and stable doping, particularly n type, remains challenging due to strong environmental sensitivity and competing extrinsic effects. Encapsulation of charge transfer molecules within the SWCNT cavity offers a promising route to stable doping while preserving the nanotubes outer surface for subsequent processing. Here, we systematically investigate the filling of arc discharge SWCNTs with the electron donor tetrathiafulvalene and electron acceptor tetracyanoquinodimethane, comparing different methods for filling, including melt filling, solution reflux, and vacuum phase sublimation. We follow the entire processing workflow from raw, unfilled powders to aqueous dispersions and employ density gradient ultracentrifugation to separate filled from empty nanotubes as well as metallic from semiconducting ones. Encapsulation efficiency and electronic modification are assessed using absorption spectroscopy, resonant Raman scattering, thermogravimetric analysis, X-ray photoelectron spectroscopy and electron paramagnetic resonance. Finally, we introduce a complementary vacuum-phase method that removes externally adsorbed molecules without extensive solvent washing, enabling cleaner encapsulated systems.
Hydrogenation offers a versatile route to tuning the physical properties of intermetallic compounds. In this study, we synthesized CoZr2Hx with different hydrogen contents and found that hydrogen is incorporated in two distinct concentration regimes separated by a wide composition gap: a low-concentration hydrogenated superconducting phase (x = 0−0.054) and a high-concentration hydrogenated ferromagnetic phase (x = 2.786). Hydrogen plays fundamentally different roles in the two concentration regimes. In the high hydrogen concentration phase, the Zr-H interactions substantially modify the metallic bands crossing the Fermi level, leading to the emergence of ferromagnetism. In contrast, in the low hydrogen concentration phase, hydrogen behaves as a nonmagnetic impurity without altering the electronic band structure. Despite the nearly identical Debye temperatures across the low-concentration series, the superconducting transition temperature (Tc) is progressively suppressed with increasing hydrogen content. The observed Tc suppression is consistent with the Abrikosov–Gor'kov pair-breaking theory, indicating that the superconducting state of CoZr2 deviates from the ideal Anderson-theorem limit of a single-band isotropic s-wave superconductor.
To accelerate the rational design of high-performance functional polymers, such as anion exchange membranes (AEMs), the establishment of chemically meaningful and actionable design guidelines is essential. Machine learning (ML) models, particularly artificial neural networks (ANNs), offer high predictive accuracy for such materials but suffer from limited interpretability due to their black-box nature. Although explainable artificial intelligence (XAI) methods such as SHapley Additive exPlanations (SHAP) provide a unified framework for model explanation, their application to ANN models is hindered by the expensive computation cost associated with the high dimensionality of molecular descriptors commonly used to represent polymer structures. In this study, a framework that combines statistical (minimum redundancy maximum relevance) and explainable ANN-based (permutation importance via ELI5) feature selection was developed, reducing the input space to 67 key descriptors. This dimensionality reduction enabled computationally feasible SHAP analysis while enhancing the predictive accuracy of the ANN by 40.87%. However, the resulting key descriptors were often difficult to interpret in physicochemical terms. To address this, large language models (LLMs) such as ChatGPT were employed to analyze descriptor source code and assist human experts in deriving chemically intuitive insights. By orchestrating XAI, LLM assistance, and expert knowledge, the framework successfully extracted design guidelines for AEMs. Based on these insights, two candidate AEM polymers with predicted anion conductivities >= 0.1 S cm-1 at 80 degrees C were proposed, exceeding typical commercialization thresholds. This study illustrates a generalizable, explainable, and efficient pathway for integrating ML, XAI, and LLMs in polymer informatics, with broad applicability across descriptor-based materials research.
The Upper Paleolithic archaeological record of the Tolbor Valley (northern Mongolia) documents a shift in emphasis from large-blade production to smaller-format bladelet production, characteristic of the Initial Upper Paleolithic (IUP) to Early Upper Paleolithic (EUP) transition in Central and Northeast Asia. This periodization is often associated with, respectively, early dispersal and permanent instalment of Homo sapiens populations in eastern Eurasia. In some regions of West Asia and Europe, an increase in lithic sharp-edge productivity has been described in the EUP, raising the hypothesis that for some groups intensified bladelet production represented a potential solution to constraints on sharp-edge availability. We test this using an allometric approach that controls for blank size, drawing on data excavated from three Upper Paleolithic sites in the Tolbor Valley dated between ca. 45 ka and < 28 ka. A diachronic increase in edge length ( 10 mm) is detected among small flakes (< 5 g) between the IUP and EUP samples, while laminar blanks (blades/bladelets) show no consistent increase. This suggests that the increased emphasis on bladelet production during the EUP at Tolbor was not primarily a response to constraints on sharp-edge availability. Instead, it coincided with more productive small flakes, whether as byproducts of bladelet manufacture or as a parallel/integrated blank production strategy. These results highlight the importance of accounting for blank size when evaluating diachronic trends in sharp-edge productivity.
