jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mohit Mittal | Kanchan Phutela
Source: Journal of Applied Research and Technology (article, 2023-12-15)
Field: Materials Science — Polymers and Plastics

Modeling and parameters optimization of biocomposite using box-Behnken response surface methodology The primary objective of this work includes modeling and optimization of the mechanical properties of natural fiber biocomposites using three-factor, three-level Box-Behnken design (BBD). In this context, the effect of three independent performance parameters; pineapple leaf fiber (PALF) length, fiber content, and polyethylene-grafted-maleic anhydride (MAPE) compatibilizer load have been investigated on the mechanical properties of PALF/HDPE/MAPE biocomposite. The sequential model sum of squares, lack of fit, and normal probability plots showed a good agreement in between the experimental results and those predicted by mathematical models (95% confidence level). The optimization results obtained in Design-Expert software revealed that the most optimal value of tensile strength, tensile modulus, flexural strength, flexural modulus, and impact strength as 32.35 MPa, 1475 MPa, 49.21 MPa, 1659.04 MPa, and 58.24 J/m respectively, at fiber length of 13.67 mm, PALF content of 16.84 wt.%, and MAPE load of 2.95 wt.%. In order to verify the mathematical models, the validation tests were also performed which showed that the response surface methodology (RSM) based BBD and ANOVA tools are adequate for analytically evaluating the performance of biocomposites. Box–Behnken design ; Response surface methodology ; Materials science ; Ultimate tensile strength ; Biocomposite ; Flexural strength ; Composite material ; Fiber ; Maleic anhydride ; Context (archaeology) ; Young's modulus ; High-density polyethylene ; Mathematics ; Polyethylene ; Polymer ; Composite number ; Statistics Natural Fiber Reinforced Composites ; Agricultural Engineering and Mechanization
Authors: Tom Dekker | Mathilde A. C. H. Janssen | Christina Sutherland | R. W. M. ABEN | Hans W. Scheeren | Daniel Blanco‐Ania | Floris P. J. T. Rutjes | Maikel Wijtmans | Iwan J. P. de Esch
Source: ACS Medicinal Chemistry Letters (article, 2023-05-02)
Field: Chemistry — Organic Chemistry

An Automated, Open-Source Workflow for the Generation of (3D) Fragment Libraries The recent success of fragment-based drug discovery (FBDD) is inextricably linked to adequate library design. To guide the design of our fragment libraries, we have constructed an automated workflow in the open-source KNIME software. The workflow considers chemical diversity and novelty of the fragments, and can also take into account the three-dimensional (3D) character. This design tool can be used to create large and diverse libraries but also to select a small number of representative compounds as a focused set of unique screening compounds to enrich existing fragment libraries. To illustrate the procedures, the design and synthesis of a 10-membered focused library is reported based on the cyclopropane scaffold, which is underrepresented in our existing fragment screening library. Analysis of the focused compound set indicates significant shape diversity and a favorable overall physicochemical profile. By virtue of its modular setup, the workflow can be readily adjusted to design libraries that focus on properties other than 3D shape. Workflow ; Fragment (logic) ; Computer science ; Modular design ; Set (abstract data type) ; Novelty ; Drug discovery ; Workflow technology ; Software engineering ; World Wide Web ; Data science ; Bioinformatics ; Programming language ; Database ; Biology Cyclopropane Reaction Mechanisms ; Microbial Natural Products and Biosynthesis ; Chemical Synthesis and Analysis
Authors: Massimo Serra | Davide Rubes | Sergio Schinelli | Mayra Paolillo
Source: Preprints.org (preprint, 2023-06-22)
Field: Chemistry — Organic Chemistry

Small Molecules against Metastatic Tumors: Concrete Perspectives and Shattered Dreams Metastasis is the main cause of anti-cancer therapies failure, leading to unfavorable prognosis for patients. The true challenge to increase cancer patient life expectancy by making cancer a chronic disease with periodic but manageable relapses, relies on the development of efficient therapeutic strategies specifically directed against key targets in the metastatic process. Traditional chemotherapy with classical alkylating agents, microtubule inhibitors and antimetabolites has demonstrated its limited efficacy against metastatic cells due to their capacity to select chemo-resistant cell populations that undergo epithelial to mesenchymal transition (ETM) thus promoting the colonization of distant sites that in turn sustain the initial metastatic process. This scenario has prompted efforts aimed at discovering a wide variety of small molecules as potential anti-metastatic drugs directed against more specific targets known to be involved in the various stages of metastasis. In this short reviews we will give an overview of the most recent advances related to three main large families of antimetastatic small molecules: intracellular tyrosine kinase inhibitors, integrin antagonists and small interfering (siRNAs). Although the majority of these small molecules are not yet approved and not available in the drug market, any information related to their stage of development could represent a precious and valuable tool to identify new targets in the endless fight against metastasis. Metastasis ; Cancer ; Small molecule ; Disease ; Medicine ; Small interfering RNA ; Tyrosine kinase ; Cancer research ; Bioinformatics ; Biology ; Internal medicine ; Cell culture Click Chemistry and Applications ; Chemical Reactions and Isotopes ; Cancer Treatment and Pharmacology
Authors: Dinesh Kumar | Satnam Singh | Surjit Angra
Source: Evergreen (article, 2023-03-01)
Field: Chemistry — Inorganic Chemistry

Morphology and Corrosion Behavior of Stir-Cast Al6061-CeO_2 Nanocomposite Immersed in NaCl and H_2So_4 Solutions Durability in terms of life is intended as a significant factor in developing advanced materials. The enrichment in corrosion resistance of the produced progressive material can be the solution. In the current study, a nanocomposite of aluminum 6061 and cerium oxide was prepared with a stir casting route reinforced in the range of 1-3 wt.%. The corrosion and microstructural behavior were observed under parametric conditions. The exposure time (36-180 hours), temperatures (room temperature, 45 ºC, and 75 ºC), and 2.5 wt.% of Sodium chloride (NaCl) and Sulphuric acid (H_2So_4) solutions were chosen as parameters for examining the corrosion rate using the immersion test method. The lower corrosion resistance was noticed in aluminum metal matrix nanocomposites (AlMMNCs) reinforced with 3 wt.% of CeO_2. The SEM analysis concluded voids, holes, clustering of particles, and debris kind of defects were observed in stir casting of AlMMNCs samples. The Pitting, fretting, and grain boundary corrosions were the primary degradation factors for corrosion behavior as evaluated from microstructural characteristics. The 0.116 has been observed as a significant corrosion rate in mm potential per year after 180 hours as exposure time at 75ºC in 2.5 wt.% NaCl solution. Morphology (biology) ; Materials science ; Nanocomposite ; Corrosion ; Composite material ; Chemical engineering ; Metallurgy ; Engineering ; Geology Pigment Synthesis and Properties ; Anodic Oxide Films and Nanostructures ; Aluminum Alloys Composites Properties
Authors: Allana Brunna Sucupira Duarte | Yunierkis Pérez‐Castillo | Danielle da Nóbrega Alves | Ricardo Dias de Castro | Rafael Limongi de Souza | Damião Pergentino de Sousa | Elquio Eleamen Oliveira
Source: Brazilian Journal of Microbiology (article, 2023-12-23)
Field: Materials Science — Biomaterials

Antifungal activity against Candida albicans of methyl 3,5-dinitrobenzoate loaded nanoemulsion Candida albicans ; Antifungal ; Minimum inhibitory concentration ; Dispersity ; Chemistry ; Corpus albicans ; Nitro ; Mechanism of action ; Fluconazole ; Microbiology ; Toxicity ; Biochemistry ; Biology ; In vitro ; Organic chemistry Nanocomposite Films for Food Packaging ; Microencapsulation and Drying Processes ; Antimicrobial agents and applications
Authors: Paul-Emmanuel Edeline | Mickaël Leclercq | Jérémy Le Luyer | Sébastien Chabrier | Arnaud Droit
Source: Scientific Reports (article, 2023-08-12)
Field: Materials Science — Biomaterials

Pearl shape classification using deep convolutional neural networks from Tahitian pearl rotation in Pinctada margaritifera Tahitian pearls, artificially cultivated from the black-lipped pearl oyster Pinctada margaritifera, are renowned for their unique color and large size, making the pearl industry vital for the French Polynesian economy. Understanding the mechanisms of pearl formation is essential for enabling quality and sustainable production. In this paper, we explore the process of pearl formation by studying pearl rotation. Here we show, using a deep convolutional neural network, a direct link between the rotation of the pearl during its formation in the oyster and its final shape. We propose a new method for non-invasive pearl monitoring and a model for predicting the final shape of the pearl from rotation data with 81.9% accuracy. These novel resources provide a fresh perspective to study and enhance our comprehension of the overall mechanism of pearl formation, with potential long-term applications for improving pearl production and quality control in the industry. Pearl ; Margaritifera ; Pearl oyster ; Convolutional neural network ; Fishery ; Computer science ; Artificial intelligence ; Geography ; Biology Calcium Carbonate Crystallization and Inhibition ; Cephalopods and Marine Biology ; Marine Bivalve and Aquaculture Studies
Authors: Wattanapong Kurdthongmee
Source: HighTech and Innovation Journal (article, 2023-09-01)
Field: Chemistry — Organic Chemistry

Comprehensive Evaluation of Deep Neural Network Architectures for Parawood Pith Estimation Accurate pith estimation is crucial for maintaining the quality of wood products. This study delves into deep learning techniques for precise Parawood pith estimation, employing popular convolutional neural networks (ResNet50, MobileNet, and Xception) with adapted regression heads. Through variations in regression functions, optimizers, and training epochs, the most effective models were pinpointed. Xception, coupled with Huber Loss regression, Nadam optimizer, and 200 epochs, showcased superior performance, achieving a 4.48 mm mean error (with a standard deviation of 3.69 mm) in Parawood. Notably, benchmarking on the Douglas Fir dataset yielded similar results (2.81 mm mean error, standard deviation: 1.57 mm). These findings underscore deep learning's potential for Parawood and Douglas Fir pith estimation, offering substantial benefits to wood industry quality control and production efficiency. By harnessing advanced machine learning techniques, this study advances wood industry processes, promoting the adoption of state-of-the-art technology in forestry and wood science. Doi: 10.28991/HIJ-2023-04-03-06 Full Text: PDF Pith ; Convolutional neural network ; Deep learning ; Benchmarking ; Artificial neural network ; Standard deviation ; Computer science ; Estimation ; Regression ; Artificial intelligence ; Regression analysis ; Relative standard deviation ; Douglas fir ; Machine learning ; Statistics ; Mathematics ; Engineering ; Forestry ; Botany ; Geography Wood and Agarwood Research ; Remote Sensing and LiDAR Applications ; Industrial Vision Systems and Defect Detection
Authors: Changshun Tian | Yunzhang Rao | Gang Su | Tao Huang
Source: International Journal of Chemical Engineering (article, 2023-06-28)
Field: Materials Science — Materials Chemistry

Effects of Pyrrhotite on the Combustion Behavior and the Kinetic Mechanism of Pyrite-Pyrrhotite Mixture Powders in the Air In this study, we performed a comparative analysis of the combustion behavior of pyrite, pyrrhotite, and pyrite-pyrrhotite mixture (mixed mineral) powders in an air atmosphere. To study the influence of the pyrrhotite content in mixed mineral powders on the combustion behavior in the air, thermogravimetric mass spectrometry, X-ray diffraction analysis, and scanning electron microscopy were employed. The results indicated that pyrrhotite lead to a weight gain in the mixed minerals during the combustion process. Pyrrhotite particles are more easily adsorbed on the surface of pyrite particles during mixed mineral combustion due to their strong ability to absorb oxygen, which accelerates pyrite combustion. The weight loss of mixed minerals decreased during the combustion process with increasing pyrrhotite content, resulting from pyrite encapsulation by agglomerated and sintered pyrrhotite during combustion. The calculated kinetic parameters and phase analysis results suggested that pyrite combustion is consistent with the shrinking core mechanism, and in the combustion process, the irregular pyrite particle shrank into a spherical particle; the combustion products of pyrrhotite grew in a layer-by-layer manner. Pyrrhotite combustion corresponded to the three-dimensional diffusion mechanism, and mixed mineral combustion was dominated by the shrinking core mechanism and supplemented by the three-dimensional diffusion mechanism. SO2, as the main combustion product, was continuously generated and volatilized in the reaction, signifying that the combustion reaction of pyrite is a two-phase reaction involving gas and solid. Pyrrhotite ; Pyrite ; Combustion ; Mineralogy ; Chemistry ; Chemical looping combustion ; Materials science ; Chemical engineering ; Organic chemistry Thermal and Kinetic Analysis ; Combustion and Detonation Processes ; Energetic Materials and Combustion
Authors: Talía Tene | Marco Guevara | Myrian Borja | María José Mendoza Salazar | María de Lourdes Palacios Robalino | Cristian Vacacela Gómez | Stefano Bellucci
Source: Frontiers in Physics (article, 2023-05-10)
Field: Materials Science — Materials Chemistry

Modeling semiconducting silicene nanostrips: electronics and THz plasmons Silicene nanostrips (SiNSs) have garnered significant attention due to their remarkable physical properties, making them an ideal candidate for numerous electronics and plasmonics applications. Their compatibility with current semiconductor technology further enhances their potential. This study aims to investigate the electronic and plasmonic properties of SiNSs with a minimum width of 100 nm using a semi-analytical model that utilizes the carrier velocity of silicene. The carrier velocity was calculated using density functional computations and refined through the GW approximation. Our results reveal that SiNSs with widths ranging from 100 to 500 nm exhibit small bandgaps within the range of a few meV, specifically ranging from 30 to 6 meV, respectively. Furthermore, all the nanostrips analyzed in this study exhibit a <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m1"><mml:mrow><mml:msqrt><mml:mi>q</mml:mi></mml:msqrt></mml:mrow></mml:math> -like plasmon dispersion within the THz regime ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m2"><mml:mrow><mml:mo>≤</mml:mo></mml:mrow></mml:math> 35 THz). By varying the experimental setup or the geometric factors of the nanostrips, the associated plasmon THz frequency can be manipulated, resulting in an increase or decrease in frequency or a shift to larger momentum values. Our study serves as a fundamental starting point and a source of inspiration for future experiments, providing a foundation for confirming the results presented in this study. Silicene ; Plasmon ; Terahertz radiation ; Semiconductor ; Materials science ; Optoelectronics ; Physics ; Graphene ; Nanotechnology Graphene research and applications ; Topological Materials and Phenomena ; Carbon Nanotubes in Composites
Authors: Chao‐Tun Cao | Chenzhong Cao
Source: ACS Omega (article, 2023-02-08)
Field: Chemistry — Organic Chemistry

New Method of NPOH Equation-Based to Estimate the Physicochemical Properties of Noncyclic Alkanes Changes in various physicochemical properties (<i>P</i> <sub>(<i>n</i>)</sub>) of noncyclic alkanes can be roughly classified as linear and nonlinear changes. In our previous study, the NPOH equation was proposed to express nonlinear changes in the properties of organic homologues. Until now, there has been no general equation to express nonlinear changes in the properties of noncyclic alkanes involving linear and branched alkane isomers. This work, on the basis of NPOH equation, proposes a general equation to express nonlinear changes in the physicochemical properties of noncyclic alkanes, including a total of 12 properties, boiling point, critical temperature, critical pressure, acentric factor, heat capacity, liquid viscosity, and flash point, named as the "NPNA equation", as follows: ln(<i>P</i> <sub>(<i>n</i>)</sub>) = <i>a</i> + <i>b</i>(<i>n</i> - 1) + <i>c</i>(<i>S</i> <sub>CNE</sub>) + <i>d</i> (ΔAOEI) + <i>f</i>(ΔAIMPI), where <i>a</i>, <i>b</i>, <i>c</i>, and <i>f</i> are coefficients, and <i>P</i> <sub>(<i>n</i>)</sub> represents the property of the alkane with <i>n</i> carbon atom number. <i>n</i>, <i>S</i> <sub>CNE</sub>, ΔAOEI, and ΔAIMPI are number of carbon atoms, sum of carbon number effects, average odd-even index difference, and average inner molecular polarizability index difference, respectively. The obtained results show that various nonlinear changes in the properties of noncyclic alkanes can be expressed by the NPNA equation. Nonlinear and linear change properties of noncyclic alkanes can be correlated with four parameters, <i>n</i>, <i>S</i> <sub>CNE</sub>, ΔAOEI, and ΔAIMPI. The NPNA equation has the advantages of uniform expression, usage of fewer parameters, and high estimation accuracy. Furthermore, using the above four parameters, a quantitative correlation equation can be established between any two properties of noncyclic alkanes. Employing the obtained equations as model equations, the property data of noncyclic alkanes, involving 142 critical temperatures, 142 critical pressures, 115 acentric factors, 116 flash points, 174 heat capacities, 142 critical volumes, and 155 gas enthalpies of formation, a total of 986 values, were predicted, which have not be experimentally measured. NPNA equation not only can provide a simple and convenient estimation or prediction method for the properties of noncyclic alkanes but also can provide new perspectives for studying quantitative structure-property relationships of branched organic compounds. Chemistry ; Chromatography Free Radicals and Antioxidants ; Various Chemistry Research Topics ; Chemical Thermodynamics and Molecular Structure
Authors: Rongrong Zhu | Tianhang Chen | Kai Wang | Hao Wu | Huan Lu
Source: Frontiers in Materials (article, 2023-10-03)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Metasurface-enabled electromagnetic illusion with generic algorithm Electromagnetic cloak or illusion, which can interfere with device detection and provide superior self-protection capabilities for animals or humans, has received much attention. The proposal of transformation optics provides a generalized strategy for realizing electromagnetic illusion. However, the complex parameter composition causes a substantial computational cost, which is not conducive to practical applications. To overcome these challenges, we report an intelligent illusory metasurface optimized by a genetic algorithm, which not only presents predefined illusory effects but also reduces the parameter space in physics. By designing a high-performance tunable metasurface, a high-fidelity inverse design is performed in simulation. Near-field and far field results show that the metasurface can generate virtual targets in different scenarios and realize electromagnetic illusion. This work is helpful in facilitating the practical application of electromagnetic illusion strategies. Illusion ; Computer science ; Fidelity ; Electromagnetic field ; High fidelity ; Transformation optics ; Transformation (genetics) ; Field (mathematics) ; Metamaterial ; Optical illusion ; Cloak ; Algorithm ; Physics ; Optics ; Telecommunications ; Acoustics ; Mathematics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Jiangui Zhao | Tingyu Zhu | Zhichao Qiu | Tao Li | Guo‐Liang Wang | Zhiwei Li | Huiling Du
Source: Journal of Agricultural Engineering (article, 2023-06-20)
Field: Chemistry — Analytical Chemistry

Hyperspectral prediction of pigment content in tomato leaves based on logistic-optimized sparrow search algorithm and back propagation neural network Leaf pigment content can reflect the nutrient elements content of the cultivation medium indirectly. To rapidly and accurately predict the pigment content of tomato leaves, chlorophyll a, chlorophyll b, chlorophyll and carotenoid were extracted from leaves of tomato seedlings cultured at different nitrogen concentrations. The visible/near-infrared(VIS/NIR) hyperspectral imaging (HSI) non-destructive measurement technology, 430-900 nm and 950-1650 nm, with total variables of 794, was used to obtain the reflection spectra of leaves. An improved strategy of the sparrow search algorithm (SSA) based on Logistic chaotic mapping was proposed and optimized the back propagation (BP) neural network to predict the pigment content of leaves. Different pretreatment methods were used to effectively improve the prediction accuracy of the model. The results showed that when the nitrogen concentration in the nutrient solution was 302.84 mg·L-1, the pigment content of leaves reached the maximum. Meanwhile, the inhibition effect of high concentration was much stronger than that of low concentration. To address the problem that the SSA is prone to get in premature convergence due to the reduction of population diversity at the end of the iteration, the initialization of the SSA population by Logistic chaotic mapping improves the initial solution quality, convergence speed and search capacity. The root mean squared error (RMSE), coefficient of determination (R2) and relative percent deviation (RPD) of chlorophyll a were 0.77, 0.77 and 2.08, respectively. The RMSE, R2 and RPD of chlorophyll b were 0.30, 0.66 and 1.71, respectively. The RMSE, R2 and RPD of chlorophyll were 0.88, 0.81 and 2.28, respectively. The RMSE, R2 and RPD of carotenoid were 0.14, 0.75 and 2.00, respectively. The HSI technology combined with machine learning algorithms can achieve rapid and accurate prediction of crop physiological information, providing data support for the precise management of fertilization in facility agriculture, which is conducive to improving the quality and output of tomatoes. Hyperspectral imaging ; Mean squared error ; Mathematics ; Chlorophyll ; Population ; Algorithm ; Coefficient of determination ; Backpropagation ; Content (measure theory) ; Botany ; Horticulture ; Biology ; Statistics ; Artificial neural network ; Artificial intelligence ; Computer science Spectroscopy and Chemometric Analyses ; Leaf Properties and Growth Measurement ; Water Quality Monitoring and Analysis