jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tsenka Grancharova | Stanislava Simeonova | Bissera Pilicheva | Plamen Zagorchev
Source: Cureus (article, 2024-02-22)
Field: Materials Science — Materials Chemistry

Gold Nanoparticles in Parkinson’s Disease Therapy: A Focus on Plant-Based Green Synthesis Parkinson's disease (PD) is a progressive neurodegenerative disease that affects approximately 1% of people over the age of 60 and 5% of those over the age of 85. Current drugs for Parkinson's disease mainly affect the symptoms and cannot stop its progression. Nanotechnology provides a solution to address some challenges in therapy, such as overcoming the blood-brain barrier (BBB), adverse pharmacokinetics, and the limited bioavailability of therapeutics. The reformulation of drugs into nanoparticles (NPs) can improve their biodistribution, protect them from degradation, reduce the required dose, and ensure target accumulation. Furthermore, appropriately designed nanoparticles enable the combination of diagnosis and therapy with a single nanoagent. In recent years, gold nanoparticles (AuNPs) have been studied with increasing interest due to their intrinsic nanozyme activity. They can mimic the action of superoxide dismutase, catalase, and peroxidase. The use of 13-nm gold nanoparticles (CNM-Au8®) in bicarbonate solution is being studied as a potential treatment for Parkinson's disease and other neurological illnesses. CNM-Au8® improves remyelination and motor functions in experimental animals. Among the many techniques for nanoparticle synthesis, green synthesis is increasingly used due to its simplicity and therapeutic potential. Green synthesis relies on natural and environmentally friendly materials, such as plant extracts, to reduce metal ions and form nanoparticles. Moreover, the presence of bioactive plant compounds on their surface increases the therapeutic potential of these nanoparticles. The present article reviews the possibilities of nanoparticles obtained by green synthesis to combine the therapeutic effects of plant components with gold. Colloidal gold ; Parkinson's disease ; Nanoparticle ; Nanotechnology ; Pharmacology ; Biodistribution ; Bioavailability ; Chemistry ; Medicine ; Disease ; Materials science ; Biochemistry ; Internal medicine ; In vitro Nanoparticles: synthesis and applications ; Advanced Nanomaterials in Catalysis ; Medicinal Plants and Neuroprotection
Authors: Tingsong Zhang | Ziyuan Liu | Qing Ma | Dong Hu | Yujia Dai | Xinfeng Zhang | Zhu Zhou
Source: Foods (article, 2024-05-27)
Field: Chemistry — Analytical Chemistry

Identification of Dendrobium Using Laser-Induced Breakdown Spectroscopy in Combination with a Multivariate Algorithm Model Dendrobium, a highly effective traditional Chinese medicinal herb, exhibits significant variations in efficacy and price among different varieties. Therefore, achieving an efficient classification of Dendrobium is crucial. However, most of the existing identification methods for Dendrobium make it difficult to simultaneously achieve both non-destructiveness and high efficiency, making it challenging to truly meet the needs of industrial production. In this study, we combined Laser-Induced Breakdown Spectroscopy (LIBS) with multivariate models to classify 10 varieties of Dendrobium. LIBS spectral data for each Dendrobium variety were collected from three circular medicinal blocks. During the data analysis phase, multivariate models to classify different Dendrobium varieties first preprocess the LIBS spectral data using Gaussian filtering and stacked correlation coefficient feature selection. Subsequently, the constructed fusion model is utilized for classification. The results demonstrate that the classification accuracy of 10 Dendrobium varieties reached 100%. Compared to Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN), our method improved classification accuracy by 14%, 20%, and 20%, respectively. Additionally, it outperforms three models (SVM, RF, and KNN) with added Principal Component Analysis (PCA) by 10%, 10%, and 17%. This fully validates the excellent performance of our classification method. Finally, visualization analysis of the entire research process based on t-distributed Stochastic Neighbor Embedding (t-SNE) technology further enhances the interpretability of the model. This study, by combining LIBS and machine learning technologies, achieves efficient classification of Dendrobium, providing a feasible solution for the identification of Dendrobium and even traditional Chinese medicinal herbs. Dendrobium ; Support vector machine ; Random forest ; Artificial intelligence ; Principal component analysis ; Pattern recognition (psychology) ; Identification (biology) ; Computer science ; Feature selection ; Multivariate statistics ; Interpretability ; Dimensionality reduction ; Mathematics ; Data mining ; Machine learning ; Biology ; Botany Spectroscopy and Chemometric Analyses ; Laser-induced spectroscopy and plasma ; Identification and Quantification in Food
Authors: Mike Hardy | Hossein Kashani Zadeh | Angelis Tzouchas | Fartash Vasefi | Nicholas MacKinnon | Gregory H. Bearman | Yaroslav Sokolov | Simon A. Haughey | Christopher T. Elliott
Source: ACS Food Science & Technology (article, 2024-08-22)
Field: Chemistry — Analytical Chemistry

Freshness in Salmon by Hand-Held Devices: Methods in Feature Selection and Data Fusion for Spectroscopy Salmon fillet was analyzed via hand-held optical devices: fluorescence (@340 nm) and absorption spectroscopy across the visible and near-infrared (NIR) range (400-1900 nm). Spectroscopic measurements were benchmarked with nucleotide assays and potentiometry in an exploratory set of experiments over 11 days, with changes to spectral profiles noted. A second enlarged spectroscopic data set, over a 17 day period, was then acquired, and fillet freshness was classified ±1 day via four machine learning (ML) algorithms: linear discriminant analysis, Gaussian naïve, weighted <i>K</i>-nearest neighbors, and an ensemble bagged tree method. Dual-mode data fusion returned almost perfect accuracies (mean = 99.5 ± 0.51%), while single-mode ML analyses (fluorescence, visible absorbance, and NIR absorbance) returned lower mean accuracies at greater spread (77.1 ± 10.1%). Single-mode fluorescence accuracy was especially poor; however, via principal component analysis, we found that a truncated fluorescence data set of four variables (wavelengths) could predict "fresh" and "spoilt" salmon fillet based on a subtle peak redshift as the fillet aged, albeit marginally short of statistical significance (95% confidence ellipse). Thus, whether by feature selection of one spectral data set, or the combination of multiple data sets through different modes, this study lays the foundation for better determination of fish freshness within the context of rapid spectroscopic analyses. Fillet (mechanics) ; Principal component analysis ; Feature selection ; Fluorescence spectroscopy ; Linear discriminant analysis ; Absorbance ; Spectroscopy ; Biological system ; Pattern recognition (psychology) ; Analytical Chemistry (journal) ; Context (archaeology) ; Artificial intelligence ; Mathematics ; Chemistry ; Computer science ; Fluorescence ; Materials science ; Optics ; Chromatography ; Physics ; Biology Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Lindsay E. Chaney | Anton van Beek | Julia R. Downing | Jinrui Zhang | Hengrui Zhang | Janan Hui | Eva Sørensen | Maryam Khalaj | Jennifer B. Dunn | Wei Chen | Mark C. Hersam
Source: Small (article, 2024-03-26)
Field: Materials Science — Materials Chemistry

Bayesian Optimization of Environmentally Sustainable Graphene Inks Produced by Wet Jet Milling Abstract Liquid phase exfoliation (LPE) of graphene is a potentially scalable method to produce conductive graphene inks for printed electronic applications. Among LPE methods, wet jet milling (WJM) is an emerging approach that uses high‐speed, turbulent flow to exfoliate graphene nanoplatelets from graphite in a continuous flow manner. Unlike prior WJM work based on toxic, high‐boiling‐point solvents such as n‐methyl‐2‐pyrollidone (NMP), this study uses the environmentally friendly solvent ethanol and the polymer stabilizer ethyl cellulose (EC). Bayesian optimization and iterative batch sampling are employed to guide the exploration of the experimental phase space (namely, concentrations of graphite and EC in ethanol) in order to identify the Pareto frontier that simultaneously optimizes three performance criteria (graphene yield, conversion rate, and film conductivity). This data‐driven strategy identifies vastly different optimal WJM conditions compared to literature precedent, including an optimal loading of 15 wt% graphite in ethanol compared to 1 wt% graphite in NMP. These WJM conditions provide superlative graphene production rates of 3.2 g hr −1 with the resulting graphene nanoplatelets being suitable for screen‐printed micro‐supercapacitors. Finally, life cycle assessment reveals that ethanol‐based WJM graphene exfoliation presents distinct environmental sustainability advantages for greenhouse gas emissions, fossil fuel consumption, and toxicity. Graphene ; Materials science ; Graphite ; Exfoliation joint ; Nanotechnology ; Chemical engineering ; Process engineering ; Composite material Graphene research and applications ; Radiation Effects in Electronics ; Electrohydrodynamics and Fluid Dynamics
Authors: Amel Khalfaoui | Zakaria Laggoun | Kerroum Derbal | Abderrezzaq Benalia | Amira Fadia Ghomrani | A. Pizzi
Source: JOURNAL OF RENEWABLE MATERIALS (article, 2024-11-20)
Field: Chemistry — Analytical Chemistry

Experimental Study of Selective Batch Bio-Adsorption for the Removal of Dyes in Industrial Textile Effluents This research aims to study the bio-adsorption process of two dyes, Cibacron Green H3G (CG-H3G) and Terasil Red (TR), in a single system and to bring them closer to the industrial textile discharge by a binary mixture of two ... | Find, read and cite all the research you need on Tech Science Press Textile ; Effluent ; Adsorption ; Industrial effluent ; Pulp and paper industry ; Waste management ; Chemistry ; Environmental science ; Materials science ; Engineering ; Organic chemistry ; Composite material Dye analysis and toxicity ; Dyeing and Modifying Textile Fibers ; Enzyme-mediated dye degradation
Authors: Parsa Farzin | Mohammad Javad Hajiahmadi | Mohammad Soleimani
Source: Scientific Reports (article, 2024-05-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Multi-channel polarization manipulation based on graphene for encryption communication Wave-based cryptography, at the vanguard of advancing technologies in advanced information science, is essential for establishing a diverse array of secure cryptographic platforms. The realization of these platforms hinges on the intelligent application of multiplexing techniques, seamlessly combined with appropriate metasurface technology. Nevertheless, existing multi-channel encryption technologies based on metasurfaces face challenges related to information leakage during partial channel decoding processes. In this paper, we present a reprogrammable metasurface for polarization modulation. This metasurface not only allows for the arbitrary customization of linearly polarized reflected waves but also enables real-time amplitude modulation. Here, relying on polarization amplitude control, a fully secure communication protocol is developed precisely in the terahertz (THz) spectrum to achieve real-time information encryption based on polarization modulation metasurfaces where access to information is highly restricted. The proposed metasurface employs the double random phase encryption (DRPE) algorithm for information encryption. It transmits the encrypted data through different polarization channels using two graphene nanoribbons, exclusively controlled by external biasing conditions. Various encryption scenarios have been outlined to fortify information protection against potential eavesdroppers. The simulated results show that this unique technology for hiding images by manipulating the polarization of the reflected wave provides new opportunities for various applications, including encryption, THz communications, THz secure data storage, and imaging. Encryption ; Computer science ; Multiplexing ; Polarization (electrochemistry) ; Cryptography ; Electronic engineering ; Computer network ; Telecommunications ; Engineering ; Computer security Metamaterials and Metasurfaces Applications ; Antenna Design and Analysis ; Wireless Communication Security Techniques
Authors: Hüsnügül Yılmaz Atay | Valentyna Loboichenko | Jacek Łukasz Wilk-Jakubowski
Source: Cement Wapno Beton (article, 2024-07-27)
Field: Materials Science — Polymers and Plastics

Investigation of calcite and huntite/hydromagnesite mineral in co-presence regarding flame retardant and mechanical properties of wood composites This work examines the characteristics of mineral additives in wood composites that affect the fire retardant properties of the material, and at the same time are environmentally friendly. The paper analyzes the results of measurements for wood composites, which is the natural building material of many houses, as well as elements of their furnishings. Sawdust waste was applied as a matrix. In the paper, a co-presence effect of calcite and huntite/hydromagnesite mineral was investigated. The calcite mineral was used as auxiliary minerals in addition to the huntite/hydromagnesite mineral to obtain a better flame retardant according to the UL94 standard and mechanical properties in the wood composite, such as flexural strength and flexural modulus. The results obtained were measured and evaluated depending on the mineral content of the composites. The results indicated that sample 40S/ 50H/ 10C is the most optimal in terms of the ratio of the modulus of flexibility and fire retardant characteristics. Fire retardant materials can be used in the construction industry, as well as in the electrical engineering applications, such as for acoustic fire extinguishers [e.g. for waveguide construction]. Fire retardant ; Materials science ; Sawdust ; Calcite ; Flexural strength ; Composite material ; Flammability ; Environmentally friendly ; Mineral ; Mineralogy ; Pulp and paper industry ; Metallurgy ; Geology Flame retardant materials and properties ; Recycling and utilization of industrial and municipal waste in materials production ; Fire dynamics and safety research
Authors: Dorota Orzel | Henri Ravald | Amy Dillon | J.H. Rantala | Susanne Κ. Wiedmer | Giacomo Russo
Source: Journal of Chromatography A (article, 2024-08-18)
Field: Chemistry — Spectroscopy

Immobilised artificial membrane liquid chromatography vs liposome electrokinetic capillary chromatography: Suitability in drug/bio membrane partitioning studies and effectiveness in the assessment of the passage of drugs through the respiratory mucosa This study pioneers a comparison of the application of biomimetic techniques, immobilised artificial membrane liquid chromatography (IAM LC) and liposome electrokinetic capillary chromatography (LEKC), for the prediction of pulmonary drug permeability. The pulmonary absorption profiles of 26 structurally unrelated drug-like molecules were evaluated using their IAM hydrophobicity index (CHI IAM) measured in IAM LC, and the logarithm of distribution constants (log K<sub>LEKC</sub>) derived from the LEKC experiments. Lipophilicity (phospholipids) parameters obtained from IAM LC and most LEKC analyses were linearly related to the n-octanol/water partitioning coefficients of the neutral forms (i.e., log P<sub>o/w</sub> values) to a moderate extent. However, the relationship with distribution coefficients at the experimental pH (7.4) (i.e., log D<sub>7.4</sub>) were weaker overall for IAM LC data and sigmoidal for some liposome compositions (phosphatidyl choline (PC): phosphatidyl inositol (PI) 85:15 mol% and 90:10 mol%) and concentrations (4 mM) in LEKC. This suggests that phospholipid partitioning supports both hydrophobic and electrostatic interactions occurring between ionised drugs and charged phospholipid moieties. The latter interactions are original when compared to those taking place in the more established n-octanol/water partitioning systems. A stronger correlation (R<sup>2</sup> > 0.65) was identified between the LEKC retention parameters, and the experimental apparent lung permeability (i.e., log P<sub>app</sub> values) as opposed to the values obtained by IAM LC. Therefore, LEKC offers unprecedented advantages over IAM LC in simulating cell membrane partitioning processes in the pulmonary delivery of drugs. Although LEKC has the advantage of more effectively simulating the electrostatic and hydrophobic forces in drug/pulmonary membrane interactions in vitro, the technique is unsuitable for analysing highly hydrophilic neutral or anionic compounds at the experimental pH. Conversely, IAM LC is useful for analysing compounds spanning a wider range of lipophilicity. Its simpler and more robust implementation, and propensity for high-throughput automation make it a favourable choice for researchers in drug development and pharmacological studies. Chemistry ; Chromatography ; Micellar electrokinetic chromatography ; Liposome ; Capillary electrophoresis ; Membrane ; Drug ; Electrokinetic phenomena ; Pharmacology ; Biochemistry Analytical Chemistry and Chromatography ; Microfluidic and Capillary Electrophoresis Applications ; Lipid Membrane Structure and Behavior
Authors: Martin Rejhon | V. Dědič | Mykhailo Shestopalov | Jan Kunc | Elisa Riedo
Source: Nanoscale (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Impact of metastable graphene-diamond coatings on the fracture toughness of silicon carbide Silicon carbide has excellent mechanical properties such as high hardness and strength, but its applications for body armor and protective coating solutions are limited by its poor toughness. It has been demonstrated that epitaxial graphene-coated SiC can enhance SiC mechanical properties due to the pressure-activated phase transition into a sp<sup>3</sup> diamond structure. Here, we show that atomically thin graphene coatings increase the hardness of SiC even for indentation depths of ∼10 μm. Very importantly, the graphene coating also causes an increase of the fracture toughness by 11% compared to bare SiC, which is in contradiction with the general indirect variation of hardness and fracture toughness. This is explained in terms of the presence of a diamond phase under the indenter while the rest of the coating remains in the ultra-tough graphene phase. This study opens new venues for understanding hardness and toughness in metastable systems and for the applications of graphene-coatings. Materials science ; Diamond ; Indentation ; Fracture toughness ; Graphene ; Silicon carbide ; Composite material ; Metastability ; Toughness ; Coating ; Carbide ; Phase (matter) ; Nanotechnology Diamond and Carbon-based Materials Research ; Graphene research and applications ; Metal and Thin Film Mechanics
Authors: Yunfei Zuo | Ryan T. K. Kwok | Jianwei Sun | Jacky W. Y. Lam | Ben Zhong Tang
Source: Chemical Physics Reviews (article, 2024-02-27)
Field: Materials Science — Materials Chemistry

Aggregation-induced emission luminogens for super-resolution imaging Over the past three decades, humanity has successfully surpassed Abbe's diffraction limit through the development of super-resolution microscopy (SRM), which leads to an increasing demand for specialized fluorescent molecules. The concept of aggregation-induced emission (AIE) has emerged as a powerful tool in fluorescence imaging since its inception in 2001. While thousands of distinctive AIE-based fluorescent molecules have been extensively utilized, their application in SRM was not explored until 2013. Although fewer than one hundred works on AIE and SRM have been published so far, this field is experiencing rapid growth. This review provides a comprehensive summary of advancements made by these intersecting domains over the last decade. The recent research is outlined, and four future directions are highlighted to guide the design of high-quality AIE-based probes for SRM applications that can further advance and promote this exciting area of research. Aggregation-induced emission ; Resolution (logic) ; Physics ; Computer science ; Optics ; Artificial intelligence ; Fluorescence Luminescence and Fluorescent Materials ; Advanced Fluorescence Microscopy Techniques ; Photoreceptor and optogenetics research
Authors: Peifeng Xiong | Man Xiao | Zhonghua Yao | Hanxing Liu | Hua Hao
Source: Crystals (article, 2024-02-29)
Field: Materials Science — Materials Chemistry

Improving the Energy Storage Performance of Barium Titanate-Based Ceramics through the Addition of ZnO-Bi2O3-SiO2 Glass Lead-free ceramics with excellent energy storage performance are important for high-power energy storage devices. In this study, 0.9BaTiO3-0.1Bi(Mg2/3Nb1/3)O3 (BT-BMN) ceramics with x wt% ZnO-Bi2O3-SiO2 (ZBS) (x = 2, 4, 6, 8, 10) glass additives were fabricated using the solid-state reaction method. X-ray diffraction (XRD) analysis revealed that the ZBS glass-added ceramics exhibited a perovskite structure, with the maximum relative density achieved at x = 6. The average grain size reduced obviously as the glass additive wt% increased. Also, the dielectric constant decreased and the breakdown strength increased with increases in the glass additives. The optimal energy storage density of 1.39 J/cm3 with an energy storage efficiency of 78.3% was obtained at x = 6 due to high maximum polarization and enhanced breakdown strength. The results demonstrate that this material is a potential candidate for high-pulse-power energy storage devices. Materials science ; Barium titanate ; Ceramic ; Barium ; Energy storage ; Titanate ; Metallurgy ; Mineralogy ; Chemical engineering ; Chemistry ; Physics Ferroelectric and Piezoelectric Materials ; Advanced Battery Materials and Technologies ; Microwave Dielectric Ceramics Synthesis
Authors: Alfonso Ramírez-Pedraza | Sebastián Salazar-Colores | Juan Terven | Julio-Alejandro Romero-González | José‐Joel González‐Barbosa | Diana‐Margarita Córdova‐Esparza
Source: AgriEngineering (article, 2024-09-23)
Field: Chemistry — Analytical Chemistry

Nutritional Monitoring of Rhodena Lettuce via Neural Networks and Point Cloud Analysis In traditional farming, fertilizers are often used without precision, resulting in unnecessary expenses and potential damage to the environment. This study introduces a new method for accurately identifying macronutrient deficiencies in Rhodena lettuce crops. We have developed a four-stage process. First, we gathered two sets of data for lettuce seedlings: one is composed of color images and the other of point clouds. In the second stage, we employed the interactive closest point (ICP) method to align the point clouds and extract 3D morphology features for detecting nitrogen deficiencies using machine learning techniques. Next, we trained and compared multiple detection models to identify potassium deficiencies. Finally, we compared the outcomes with traditional lab tests and expert analysis. Our results show that the decision tree classifier achieved 90.87% accuracy in detecting nitrogen deficiencies, while YOLOv9c attained an mAP of 0.79 for identifying potassium deficiencies. This innovative approach has the potential to transform how we monitor and manage crop nutrition in agriculture. Artificial neural network ; Cloud computing ; Point cloud ; Computer science ; Environmental science ; Artificial intelligence ; Operating system Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Remote Sensing in Agriculture