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DEM calibration insights on the role of particle shape for sub 2 mm particles
Abstract This study introduces a comprehensive calibration technique for discrete element method (DEM) simulations. Its focus is on particles smaller than 2 mm and this showcase shows comparison between spherical and polyhedral particle shape calibration. Very fine powders or particulate materials with small particles are usually calibrated with upscaling. Unfortunately, some applications are dependent heavily on a quite precise particle size range, such as abrasion, crushing, pneumatic conveying, feeding, and dosing. Traditional DEM simulations often rely on spherical or multi-spherical particle models, which lack the precision needed, particularly due to the surface waviness introduced in the latter case. This limitation impacts dynamic industrial applications like mixing, hopper discharge, and abrasion. To address this gap, we present a comparative calibration approach for spherical and polyhedral particles, using silica sand as the test material. The calibration combines static and dynamic parameters such as rolling resistance, particle-to-particle restitution, and wall friction, validated through experiments on a powder flow calibration stand. Results revealed significant differences in flow dynamics, highlighting the enhanced realism of polyhedral models despite increased computational demands. This work provides a comprehensive framework for DEM calibration of fine particulate materials, specifically validated for particle sizes between 400 and 1500 µm, improving simulation accuracy and extending applicability across various industrial processes.
Ensemble learning for biomedical signal classification: a high-accuracy framework using spectrograms from percussion and palpation
Oil removal from wastewater with biomass-derived hydrochars laboratory insights
Enhancing urban quality of life evaluation using spatial multi criteria analysis
Natural experiments from Earth Hour reveal urban night sky being drastically lit up by few decorative buildings
N-alkylated polydithiocarbamates derived from thiocarbonyl fluoride as macro-photoiniferters for living 3D printing
Quantum dynamics simulation of exciton-polariton transport
Abstract Strong coupling between excitons and confined modes of light presents a promising pathway to tunable and enhanced energy transport in organic materials. By forming hybrid light-matter quasiparticles, exciton-polaritons, electronic excitations can traverse long distances at high velocities through ballistic flow. However, transport behavior of exciton-polaritons varies strongly across experiments, spanning both diffusive and ballistic transport regimes. Which properties of the material and light-modes govern the transport behavior of polaritons remains an open question. Through full-quantum dynamical simulations we reveal a strong dependence of polariton transport on vibronic interactions and static disorder within molecules in both ideal and lossy cavities. Specifically, we show that intramolecular vibrations mediate relaxation processes that alter polariton composition, lifetime and velocity on ultrafast timescales. Analysis of the propagating wavepacket in position and momentum space provides mechanistic insight into the robustness of ballistic flow of exciton-polaritons found experimentally under cryogenic conditions.
Design, Synthesis, and Application of a Family of Chiral Non‐C <sub>2</sub> ‐Symmetric NHCs with a Fused Sidechain
Abstract Although a considerable number of chiral nitrogen heterocyclic carbenes (NHCs) have been developed yet it is highly necessary to develop new NHCs bearing multiple sites for facile modifications of both electronic nature and steric hindrance. Herein, we uncover a new family of chiral non‐C 2 ‐Symmetric NHCs with a fused sidechain, whose precursors are synthesized by a simple five‐step route. The synthesis includes Pd‐catalyzed cross‐coupling or nucleophilic addition/oxidation, chiral phosphoric acid‐catalyzed asymmetric reduction of 2‐aryl‐quinolines, bromination at C8, Buchwald–Hartwig amination, and cyclization with methyl orthoformate. Among nine prepared NHCs, YC‐NHC8 is the optimal ligand for Cu(I)‐catalyzed asymmetric S N 2′ silylation, YC‐NHC3 works as the best ligand for Cu(I)‐catalyzed enantioselective conjugate silylation of simple α,β‐unsaturated amides, and YC‐NHC9 serves as the most suitable ligand for copper(I)‐catalyzed asymmetric silylation of azadienes. Remarkably, these three reactions are successfully run under a catalyst loading of 0.1 mol%, indicating that YC‐NHCs may have the potential to be broadly used in efficient asymmetric transition metal catalysis.
Plasmonic Ion Diode Membrane (PIDM) for Enhanced Nanofluidic Ion Transport
Abstract Efficient applications of nanofluidic devices are often limited by the insufficient ion permselectivity and inherent ion concentration polarization (ICP) phenomenon. In this work, a bio‐inspired plasmonic ion diode membrane (PIDM) was designed and fabricated for enhanced ion transport and osmotic energy harvesting by integrating covalent organic frameworks (COFs) and three‐dimensional Au nanoparticles (3D AuNPs) into anode aluminum oxide (AAO). Under light irradiation, localized surface plasmon resonance (LSPR) excitation of 3D AuNPs can release huge plasmonic heat and produce abundant hot charge carriers (hot electrons and holes) simultaneously. The former heats the solution and generates a thermal gradient for boosting ion flux, while the latter transfers to the COFs layer, increasing charge density for promoting ion permselectivity. Importantly, it has been found that different COFs with varied pore sizes and charges have an obvious influence on energy harvesting efficiency. Under the optimum condition, a high output power density of 65.7 W m −2 in a 500‐fold concentration gradient could be achieved. This work provides a practical and efficient way to boost ion transport and enhance osmotic energy conversion by utilizing the synergistic effect of plasmonics and ion diode (ID) property.
The prognostic significance of the geriatric nutritional risk index in postoperative parotid gland carcinoma
Abstract The impact of the Geriatric Nutritional Risk Index (GNRI) on the prognosis of postoperative parotid gland carcinoma (PGC) remains unclear. This study investigates the role of GNRI in predicting disease-free survival (DFS) and overall survival (OS) in postoperative PGC patients and develops a predictive model. We conducted a retrospective analysis of 389 postoperative PGC patients treated from May 2008 to June 2019 at two regional medical centers in China. The independent prognostic factors were identified by univariate and multivariate Cox regression analyses. Then, two nomograms were established based on these independent prognostic factors and verified by a series of methods. The GNRI was identified as an independent prognostic factor in postoperative patients with PGC. A higher GNRI value indicated a worse prognosis for the patient. Based on the recognized independent prognostic factors—such as surgical margin, perineural invasion, extranodal extension (ENE), age-adjusted Charlson comorbidity index (ACCI), American Joint Committee on Cancer (AJCC) stage, and GNRI—two nomograms for overall survival (OS) and disease-free survival (DFS) were developed. The concordance index (C-index) for DFS was 0.712 and 0.730, while for OS it was 0.697 and 0.722 in the training and validation groups, respectively. These results demonstrate a significant improvement over the traditional AJCC staging system. Additionally, the area under the curve (AUC) values in both the training and validation sets were impressive, with all AUC scores exceeding 0.7. Decision curve analysis (DCA) also indicated substantial clinical benefits. The GNRI is an important predictive index in postoperative patients with PGC, which is not limited to the elderly. The newly developed nomograms provide a new tool of prognostic evaluations for postoperative patients with PGC.
Fecal microbiota transplantation improves Sansui duck growth performance by balancing the cecal microbiome
An analysis of sustainability and performance indicators in Eco-Conscious trainers’ brands
Abstract The fashion industry is known for its negative environmental and social impacts globally. Sustainability has become a priority for governmental agendas and concerned consumers. However, achieving sustainability remains a challenge for the industry due to its complex supply chains and systems. Specifically, the footwear industry accounts for 1.4% of global carbon emissions, with trainers being one of the most popular types of footwear among consumers. Recent studies have highlighted their ecological footprint, prompting companies to implement various actions to address this issue. Nevertheless, the environmental impact of this sector continues to pose significant challenges. This paper conducts a content analysis to examine and classify the actions taken by 13 Sustainable Trainers’ Brands according to five categories: Sustainable Materials, Sustainable Manufacturing, Sustainable Distribution, End-of-Life Recovery, and Eco-Design. Results show that Sustainable Materials is the most frequently adopted approach for sustainability, while Eco-Design is the least emphasised area. Additionally, the indicators used to assess sustainability in this sector primarily focus on the Environmental Sphere, with Sustainable Materials being the most prominently coded category. This study identifies Eco-Design as an area that requires further attention in future developments to address sustainability from a broader perspective.