Hasil untuk "Chemical technology"

Hui Xu, Runfeng Chen, Qiang Sun et al.

The design and characterization of metal-organic complexes for optoelectronic applications is an active area of research. The metal-organic complex offers unique optical and electronic properties arising from the interplay between the inorganic metal and the organic ligand. The ability to modify chemical structure through control over metal-ligand interaction on a molecular level could directly impact the properties of the complex. When deposited in thin film form, this class of materials enable the fabrication of a wide variety of low-cost electronic and optoelectronic devices. These include light emitting diodes, solar cells, photodetectors, field-effect transistors as well as chemical and biological sensors. Here we present an overview of recent development in metal-organic complexes with controlled molecular structures and tunable properties. Advances in extending the control of molecular structures to solid materials for energy conversion and information technology applications will be highlighted.

V. Tung, Li‐Min Chen, M. Allen et al.

Geoffrey M. Geise, Hae-Seung Lee, Daniel J Miller et al.

J. Choi, Sang-Soo Han, Hak-Sung Kim

François Thevenot

C. Granqvist

R. Noyori

M. Kelland

M. Aider

A. Manz, D. J. Harrison, E. Verpoorte et al.

A. Goldman

M. Rubio, G. Martinez, L. Baena et al.

C. Doss, M. Morris

Lin Yu, Shanshan Wu, Xiaowen Hao et al.

1 Applied Biology Laboratory, Shenyang University of Chemical Technology, 110142, Shenyang, China 2 Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, Hubei, China 3 SciLifeLab, Department of Microbiology, Tumor and Cell Biology. Karolinska Institute, Solna 171 65, Sweden. 4 College of Life Science, HeNan Normal University, 453007 Xinxiang, Henan, China 5 Pluri Biotech Co.Ltd, Xuzhou, 221001, China 6 Shenyang Center for Disease Control And Prevention, 110031, Shenyang, Liaoning, China 7 Liaoning Center for Disease Control And Prevention, 110005, Shenyang, Liaoning, China 8 Biotech & Biomedicine Science (Shenyang)Co. Ltd, Shenyang, 110000, China 9 Nanog Biotech Co.Ltd, Shanghai, 200000,China 10 Biotech & Biomedicine Science (Jiangxi)Co. Ltd, Ganzhou, 341000, China

R. Curl, F. Capasso, C. Gmachl et al.

YaoKun Lei, Yi Isaac Yang

Chemical reaction sampling critically depends on collective variables (CVs) that capture the slow degrees of freedom governing reactive transformations. However, existing reaction CVs are often defined in geometric space or learned in a system-specific manner, which limits their transferability and leaves open the more fundamental question of how reaction progress should be represented. From a physical perspective, chemical reactions are defined by electron redistribution. Here, we introduce a charge-space electronic collective variable that describes the electronic component of reaction progress in a common linear form based on atomic charges. To enable its use in enhanced sampling, atomic charges and the corresponding CV gradients are provided by a neural-network model trained on QM/MM data within an iterative sampling-training workflow. Across multiple reactions in aqueous and enzymatic environments, we show that this electronic CV can be constructed in a common charge-space form, with the corresponding coefficients assigned in a simple manner from charge differences between relevant states. Our simulations further show that reaction progress generally involves coupled electronic and conformational components, and that the same framework can also be extended to restrain side reactions. These findings support charge-based electronic CVs as a physically motivated framework for describing the electronic component of chemical reaction progress with reduced reliance on handcrafted geometric descriptors.

Yun-Wen Mao, Roman V. Krems

Efficient optimization of molecules with targeted properties remains a significant challenge due to the vast size and discrete nature of chemical compound space. Conventional machine-learning-based optimization approaches typically require large datasets to construct accurate surrogate models, limiting their applicability in data-scarce settings. In this study, we present a Bayesian optimization (BO) framework that identifies optimal molecular structures with high precision using fewer than 2,000 training data points within a chemical subspace containing more than 133,000 molecules. The framework employs a low-dimensional and physics-informed molecular descriptor vector that facilitates data-efficient surrogate modelling and optimization. A key innovation of the proposed framework is a reliable inverse mapping scheme that translates optimized points in the descriptor space back into chemically valid molecular structures, thereby bridging continuous optimization and discrete molecular design. We demonstrate the effectiveness of our approach on the QM9 benchmark dataset, where the framework successfully identifies organic molecules with the target entropy and zero-point vibrational energy (ZPVE) values.For entropy optimization, our approach achieves a 100% success rate while requiring fewer than 1,000 molecular evaluations in more than 80% of test cases. For ZPVE, the success rate exceeds 80% for molecules containing more than two heavy atoms. These results highlight the critical role of low-dimensional, interpretable descriptors in enabling data-efficient optimization and robust inverse molecular design, and establish Bayesian optimization as a practical tool for molecular discovery in small-data regimes.

The Truyen Tran, Thu Minh Tran, Xuan Tung Nguyen et al.

This study aims to present the results of anticipation of lightweight concrete durability when exposed to a chloride environment under pre-compressive load. The research employs Keramzit aggregate as the coarse aggregate for lightweight concrete. Following a 28-day curing period in water, the concrete specimens undergo varying levels of pre-compressive stress. Rapid Chloride Permeability Testing is then conducted to ascertain the chloride diffusion coefficient. The study posits a correlation between the chloride diffusion coefficient and precompressive stress levels, drawing from the experimental findings. Furthermore, Monte-Carlo simulation is employed to assess the influence of stochastic variables on the corrosion likelihood of concrete structures using lightweight aggregates. These stochastic variables encompass the chloride diffusion coefficient, surface chloride concentration, critical chloride concentration, concrete protection layer thickness, and a coefficient contingent on environmental conditions, to appraise the operational lifespan of lightweight concrete structures.

Elaina M. Kenyon, Michael J. Devito, Grace Patlewicz et al.

PFASs are widely present and persistent in the environment, and exposure can occur via multiple pathways. Human and animal PFAS exposures have been associated with alterations in thyroid hormones, hepatotoxicity, and other adverse effects. This study evaluated the subchronic toxicities of four specific PFASs in 90-day oral rat studies. Studies were conducted in male and female Sprague–Dawley rats exposed to PFASs in corn oil via oral gavage. The PFASs studied were 1H,1H,9H-perfluorononyl acrylate (PFNAC), 1H,1H,2H,2H-perfluorohexyl iodide (PFHI), methyl heptafluoropropyl ketone (MHFPK), and 2-chloro-2,3,3,3-tetrafluoropropanoic acid (CTFPA). High doses were 10 mg/kg-day (male) and 30 mg/kg-day (female) for PFNAC, 200 mg/kg-day for PFHI, 300 mg/kg-day for MHFPK, and 30 (male) and 100 mg/kg-day (female) for CTFPA. The four lower doses for each PFAS were spaced at two- or threefold dose increments. The most consistent effect was dose-dependent increases in the relative and absolute liver weights for PFNAC, PFHI, and CTFPA but not for MHFPK. Increased liver weights were correlated with findings of hepatocellular hypertrophy. Increased kidney weights for PFNAC and PFHI were correlated with increased incidence of minimal tubule epithelial hypertrophy (PFNAC) or increased incidence and severity of chronic progressive nephropathy and hyaline droplet accumulation (PFHI). There were no compound-related effects on morbidity and mortality or overt signs of toxicity.

Flávio Rodrigues, Mariana Fernandes, Filipe Samuel Silva et al.

In the pursuit of addressing the persistent challenge of bacterial adhesion and biofilm formation in dental care, this study investigates the efficacy of electric current as an alternative strategy, specifically focusing on its application in dental contexts. Polyether ether ketone (PEEK), known for its excellent biocompatibility and resistance to bacterial plaque, was enhanced with conductive properties by incorporating silver (Ag), a well-known antibacterial material. Through systematic in vitro experiments, the effectiveness of alternating current (AC) and direct current (DC) in reducing bacterial proliferation was evaluated. The tests were conducted using two bacterial strains: the Gram-positive <i>Staphylococcus aureus</i> and the Gram-negative <i>Pseudomonas aeruginosa</i>. Various configurations, current parameters, and two different electrode configurations were assessed to determine their impact on bacterial reduction. A notable finding from this study is that alternating current (AC) demonstrates superior efficacy compared to direct current (DC). The more significant decrease in CFUs/mL for <i>P. aeruginosa</i> with AC was recorded at the current levels of 5 mA and 500 nA. In opposition, <i>S. aureus</i> exhibited the greatest reduction at 5 mA and 1 mA. This study highlights the potential of using electric current within specific intensity ranges as an alternative strategy to effectively mitigate bacterial challenges in dental care.