jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: A. V. Pashkevich | Ludmila A. Bliznyuk | А.К. Fedotov | Vladimir Khovaylo | A. A. Kharchanka | В. В. Федотова
Source: Journal of the Belarusian State University Physics (article, 2022-10-10)
Field: Materials Science — Materials Chemistry

Thermal and thermoelectric properties of ceramics based on zinc oxide alloyed with iron In this work, we study the effect of adding iron oxides FeO and Fe2O3 in a ratio of 1 : 9 on the thermal and thermoelectric characteristics of ceramics based on zinc oxide ZnO. The samples themselves were made in two stages based on the ceramic technology of sintering powder mixtures in an open atmosphere. Thermal conductivity studies point to the dominant contribution of lattice thermal conductivity at room temperature. The decrease in thermal conductivity as a result of alloying is due to an increase in phonon scattering at point defects introduced into the ZnO lattice (due to the replacement of zinc ions by iron ions) and at grain boundaries (due to microstructure refinement), as well as an increase in porosity (a decrease in density) and the formation of particles of an additional ZnFe2O4 ferrite phase. Alloying wit iron and the accompanying change in the structure of ceramics (decrease in grain size, increase in porosity, precipitation of the ferrite phase) leads to an increase in the thermoelectric figure of merit ZT by 2 times (due to a decrease in electricalresistivity and thermal conductivity with a relatively small decrease in the thermoelectric coefficient). The results obtained can be used to fabricate ZnO-based ceramics with optimal thermoelectric characteristics. Materials science ; Thermoelectric effect ; Thermal conductivity ; Ceramic ; Sintering ; Thermoelectric materials ; Microstructure ; Metallurgy ; Phonon scattering ; Zinc ferrite ; Grain boundary ; Grain growth ; Grain size ; Composite material ; Zinc ; Thermodynamics Advanced Thermoelectric Materials and Devices ; Phase Change Materials Research ; Gas Sensing Nanomaterials and Sensors
Authors: Veronika Bronskaya | G V Manuyko | Г. А. Аминова | Olga Kharitonova | D S Balzamov | Alsu A. Lubnina
Source: Polymers (article, 2022-11-28)
Field: Chemistry — Physical and Theoretical Chemistry

Temperature Dependence of the Kinetic Parameters of the Titanium–Magnesium Catalyzed Propylene Polymerization This paper provides a study of the liquid-phase polypropylene polymerization on a heterogeneous titanium-magnesium Ziegler-Natta-type catalyst. A kinetic model was developed that included the activation of potential active centers, chain growth, transferring the chains to hydrogen and monomer, and the deactivation of active centers. The model was created to predict the polymerization rate, polymer yield, and average molecular weights of polymer chains where the polymerization temperature changes from 40 to 90 °C. In developing polycentric kinetic models, there is a difficulty associated with evaluating the kinetic constants of the rates of elementary reactions/stages in polymerization. Each heterogeneous titanium-magnesium catalyst (TMC), including a co-catalyst, as well as an internal and an external electron donor, has its own set of kinetic parameters. Therefore, its kinetic parameters must be defined for each new catalyst. The presented algorithm for identifying the kinetic constants of rates starts with a kinetic model that considers one type of active centers. At the second stage, a deconvolutional analysis is used for the molecular weight distribution (MWD) of the gel permeation chromatography (GPC) data of the polypropylene samples and the most probable distribution of Flory chain lengths is found for each type of active centers. At the third stage, the single-center model is transformed into a polycentric kinetic model. For the catalyst system, five types of active centers were identified, together with a mass fraction and a number-average molecular weight for each active center type of the catalyst, which is consistent with the published results for similar Ti-based Ziegler-Natta catalysts. Magnesium ; Titanium ; Catalysis ; Polymerization ; Kinetic energy ; Materials science ; Chemistry ; Organic chemistry ; Polymer ; Composite material ; Metallurgy ; Physics Advanced Physical and Chemical Molecular Interactions ; Thermal and Kinetic Analysis ; Inorganic and Organometallic Chemistry
Authors: Christian Frabitore | Jérome Lépeule | Tom Livinghouse
Source: Molecules (article, 2022-07-17)
Field: Chemistry — Organic Chemistry

Copper(I)-Catalyzed Cross-Coupling of 1-Bromoalkynes with N-Heterocyclic Organozinc Reagents Nitrogen-containing heterocycles represent the majority of FDA-approved small-molecule pharmaceuticals. Herein, we describe a synthetic method to produce saturated N-heterocyclic drug scaffolds with an internal alkyne for elaboration. The treatment of N,N-dimethylhydrazinoalkenes with Et<sub>2</sub>Zn, followed by a Cu(I)-catalyzed cross-coupling with 1-bromoalkynes, results in piperidines and pyrrolidines with a good yield. Five examples are reported and a proposed mechanism for the Cu(I)-catalyzed cross-coupling is presented. Alkyne ; Yield (engineering) ; Catalysis ; Reagent ; Combinatorial chemistry ; Chemistry ; Coupling reaction ; Coupling (piping) ; Copper ; Molecule ; Medicinal chemistry ; Organic chemistry ; Materials science Catalytic C–H Functionalization Methods ; Catalytic Alkyne Reactions ; Catalytic Cross-Coupling Reactions
Authors: Srinivas Doddapaneni | Sathyashankara Sharma | G Gowrishankar | Rajesh Nayak | Nitesh Kumar | Manjunath Shettar
Source: Istrazivanja i projektovanja za privredu (article, 2022-01-01)
Field: Materials Science — Ceramics and Composites

Optimization and prediction of the hardness behaviour of LM4 + Si3N4 composites using RSM and ANN: A comparative study In the present work, LM4 + Si3N4 (1, 2, and 3 wt.%) composites were fabricated using the two-stage stir casting method. Precipitation hardening treatment was carried out on the cast composites and hardness results were compared with as-cast specimens. Microstructural analysis was performed using Scanning Electron Microscope (SEM) images to validate the existence and homogenous distribution of reinforcement in the matrix. LM4 + 3 wt.% Si3N4 composite with multistage solution heat treatment (MSHT) and aging at 100°C showed higher hardness viz., 124% improvement when compared to as-cast LM4 due to the uniform distribution of Si3N4 and precipitation of metastable phases during the heat treatment process. The microhardness values of the fabricated composites was investigated using Artificial Neural Network (ANN) and Response Surface Methodology (RSM). Both RSM and ANN models predicted hardness values close to experimental values with minimum error, and the prominence of aging temperature in the improvement of hardness was observed. The data obtained illustrate that the proposed regression model can accurately predict hardness values within the constraints of the factors under consideration. Based on the error values it can be concluded that the ANN model can deliver results with higher accuracy than the RSM model. Materials science ; Response surface methodology ; Indentation hardness ; Composite material ; Precipitation hardening ; Hardening (computing) ; Composite number ; Hardness ; Central composite design ; Scanning electron microscope ; Work hardening ; Precipitation ; Microstructure ; Machine learning ; Computer science ; Layer (electronics) Advanced ceramic materials synthesis ; Aluminum Alloys Composites Properties ; Advanced materials and composites
Authors: Yu Chen | Miao Liu
Source: Frontiers in Materials (article, 2022-06-28)
Field: Materials Science — Materials Chemistry

Evaluation of Cytotoxicity of Pb2+ Ion-Adsorbed Amino-Functionalized Magnetic Mesoporous Silica Nanoparticles: An In Vitro Study Application of amino-functionalized mesoporous silica-coated core-shell magnetic nanoparticles (Fe 3 O 4 @mSiO 2 -NH 2 NPs) for adsorbing heavy metal ions has attracted intensive interest in recent years. Despite the cytotoxicity triggered by the co-exposure of nanoparticles (NPs) and metal ions in relatively high dosages being reported, the effect of the adsorbed heavy metal ions on the cytotoxicity to human cells remains unexplored. Herein, we demonstrated the effect of amino-functionalized Fe 3 O 4 @mSiO 2 core-shell magnetic nanoparticles before and after adsorbing Pb 2+ ions on the cytotoxicity of human kidney cells (HEK293). The surface morphology, viability, and oxidative stress (OS) induction of HEK293 cells incubated with Fe 3 O 4 @mSiO 2 -NH 2 NPs and Pb 2+ ion-adsorbed Fe 3 O 4 @mSiO 2 -NH 2 NPs were assessed, respectively. Transmission electron microscopic (TEM) images of cell sections depicted that Fe 3 O 4 @mSiO 2 -NH 2 NPs were internalized by HEK293 cells and gathered mainly in the cytoplasm. Cell viability (MTT) assays revealed the Fe 3 O 4 @mSiO 2 -NH 2 NPs could enhance the cell viability to 119.9% and 108.2% compared to the control group, respectively. On contrast, the Pb 2+ ion-adsorbed Fe 3 O 4 @mSiO 2 -NH 2 NPs were toxic to the cell because when the Pb 2+ ion contents were 5.0 and 7.5 μg mL −1 , the viabilities of the samples decreased to 97.1% and 84.7%, respectively. Oxidative stress data proved that OS was negatively affected by both dissociative Pb 2+ ions and the Pb 2+ ion-adsorbed Fe 3 O 4 @mSiO 2 -NH 2 NPs. Cytotoxicity may be attributed to the OS induced by Pb 2+ ions leaked from the adsorbent. Under the same Pb 2+ ion concentration, the cytotoxicity of the adsorbed Pb 2+ ions was lower than that of the dissociative Pb 2+ ions, indicating that the adsorption by NPs inhibited the cytotoxicity of Pb 2+ ions. This work will provide new references for assessing the cytotoxicity of Pb 2+ -adsorbed nanoparticles. Viability assay ; Cytotoxicity ; Nuclear chemistry ; Adsorption ; Nanoparticle ; Mesoporous silica ; MTT assay ; Chemistry ; Mesoporous material ; Metal ions in aqueous solution ; HEK 293 cells ; Metal ; Materials science ; Nanotechnology ; In vitro ; Organic chemistry ; Biochemistry ; Catalysis Nanoparticles: synthesis and applications ; Graphene and Nanomaterials Applications ; Nanoparticle-Based Drug Delivery
Authors: Ely Setiawan | Mudasir Mudasir
Source: Journal of Applied Pharmaceutical Science (article, 2022-07-01)
Field: Chemistry — Organic Chemistry

Quantitative structure–activity relationship study to predict the antibacterial activity of gemini quaternary ammonium surfactants against Escherichia coli Gemini quaternary ammonium surfactants (GQAS) have a unique structure built of two conventional surfactants connected by a spacer group. In previous studies, it has been found that GQAS have potency as antimicrobial agents. Thus, we developed a quantitative structure-activity relationship (QSAR) model to predict the antibacterial activity of GQAS. A dataset containing 57 GQAS with antibacterial activity against Escherichia coli was chosen from the literature. After optimizing all structures of these compounds using the ab initio 6-311G basis sets at the Hartree-Fock level theory, the molecular descriptors were calculated using the Mordred program. The genetic algorithm (GA) and multiple linear regressions (MLR) were used for generating two QSAR models with different splitting techniques. The predictive powers of the obtained models were discussed using the leave-one-out (LOO) cross-validation and external test set. The best GA-MLR models were obtained with reliable value of R 2 = 0.891, Q 2 LOO = 0.851, lack-of-fit = 0.116, root mean square error (RMSE train ) = 0.267, R 2 test = 0.834, and RMSE test = 0.269. The GA-MLR methods were used to develop models that possess good predictive ability based on both internal and external validation parameters. The design of new molecules was done, and the antibacterial activity could be predicted using the resulting model with 16 compounds that showed potential as antibacterial agents. Quaternary ; Ammonium ; Escherichia coli ; Antibacterial activity ; Protein quaternary structure ; Chemistry ; Microbiology ; Bacteria ; Biochemistry ; Biology ; Organic chemistry ; Genetics ; Paleontology Antimicrobial agents and applications ; Spectroscopy and Chemometric Analyses ; Medicinal Plant Research
Authors: Zecheng Zhuang | Zhen Li | Xuehai Qian | Jianping Tan | Lei Zeng | Yang Zhao | Yong Xiang
Source: Materials (article, 2022-12-14)
Field: Materials Science — Materials Chemistry

A Study on the Acquirement Method of Mechanical Property Parameters in the Different Base Materials Composite Region of Clad Rebar Clad rebar is one of the key structures of marine and construction services. Therefore, it is of great importance to acknowledge the mechanical property parameters of the composite region in the structural integrity evaluation of clad rebar. The different base materials of clad rebar (20MnSiV/316L steel, 35#/316L steel, 45#/316L steel, and 55#/316L steel) are researched in this study. The composite area is further refined, and simultaneously, a refinement model of the composite region of clad rebar is established. In view of the fact that a surface hardness experiment is quite easy to conduct, a proposed method consists of obtaining the mechanical property parameters of materials using the surface hardness test. The mechanical property parameters are acquired; moreover, the relationship between yield stress and surface hardness of the stainless steel clad rebar is set up. We used this method to acquire the mechanical parameters of a composite surface uneven area of clad rebar, and we established a mechanical parameters mathematics model of clad rebar, it is a significant basis for a structural integrity evaluation of cladding materials. Rebar ; Materials science ; Cladding (metalworking) ; Composite number ; Composite material ; Structural engineering ; Indentation hardness ; Microstructure ; Engineering Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Concrete Corrosion and Durability
Authors: Jaehyeon Kim | Seung Hyeon Kim | Nam Jung Heo | Benjamin P. Hay | Sung Kuk Kim
Source: International Journal of Molecular Sciences (article, 2022-12-22)
Field: Chemistry — Spectroscopy

Molecular Pincers Using a Combination of N-H and C-H Donors for Anion Binding A naphthalene imide (<b>1</b>) and a naphthalene (<b>2</b>) bearing two pyrrole units have been synthesized, respectively, as anion receptors. It was revealed by <sup>1</sup>H NMR spectral studies carried out in CD<sub>3</sub>CN that receptors <b>1</b> and <b>2</b> bind various anions via hydrogen bonds using both C-H and N-H donors. Compared with receptor <b>2</b>, receptor <b>1</b> shows higher affinity for the test anions because of the enhanced acidity of its pyrrole NH and naphthalene CH hydrogens by the electron-withdrawing imide substituent. Molecular mechanics computations demonstrate that the receptors contact the halide anions via only one of the two respective available N-H and C-H donors whereas they use all four donors for binding of the oxyanions such as dihydrogen phosphate and hydrogen pyrophosphate. Receptor <b>1</b>, a push-pull conjugated system, displays a strong fluorescence centered at 625 nm, while receptor <b>2</b> exhibits an emission with a maximum peak at 408 nm. In contrast, upon exposure of receptors <b>1</b> and <b>2</b> to the anions in question, their fluorescence was noticeably quenched particularly with relatively basic anions including F<sup>-</sup>, H<sub>2</sub>PO<sub>4</sub><sup>-</sup>, HP<sub>2</sub>O<sub>7</sub><sup>3-</sup>, and HCO<sub>3</sub><sup>-</sup>. Chemistry ; Hydrogen bond ; Imide ; Receptor ; Pyrophosphate ; Substituent ; Fluorescence ; Proton NMR ; Stereochemistry ; Ion ; Medicinal chemistry ; Crystallography ; Molecule ; Organic chemistry ; Enzyme Molecular Sensors and Ion Detection ; Luminescence and Fluorescent Materials ; Supramolecular Chemistry and Complexes
Authors: Αθανάσιος Κοτρώτσος | George Michailidis | Άννα Γείτονα | Filippos Tourlomousis | Vassilis Kostopoulos
Source: International Journal of Molecular Sciences (article, 2022-03-27)
Field: Materials Science — Polymers and Plastics

Toughening and Healing of CFRPs by Diels–Alder-Based Nano-Modified Resin through Melt Electro-Writing Process Technique In the current study, a novel approach in terms of the incorporation of self-healing agent (SHA) into unidirectional (UD) carbon fiber reinforced plastics (CFRPs) has been demonstrated. More precisely, Diels-Alder (DA) mechanism-based resin (Bis-maleimide type) containing or not four layered graphene nanoplatelets (GNPs) at the amount of 1 wt% was integrated locally in the mid-thickness area of CFRPs by melt electro-writing process (MEP). Based on that, CFRPs containing or not SHA were fabricated and further tested under Mode I interlaminar fracture toughness experiments. According to experimental results, modified CFRPs exhibited a considerable enhancement in the interlaminar fracture toughness properties (peak load (P<sub>max</sub>) and fracture toughness energy I (G<sub>IC</sub>) values). After Mode I interlaminar fracture toughness testing, the damaged samples followed the healing process and then were tested again under identical experimental conditions. The repeating of the tests revealed moderate healing efficiency (H.E.) since part of the interlaminar fracture toughness properties were restored. Furthermore, three-point bending (3PB) experiments were conducted, with the aim of assessing the effect of the incorporated SHA on the in-plane mechanical properties of the final CFRPs. Finally, optical microscopy (OM) examinations were performed to investigate the activated/involved damage mechanisms. Materials science ; Fracture toughness ; Composite material ; Toughening ; Toughness ; Graphene ; Bending ; Flexural strength ; Three point flexural test ; Optical microscope ; Scanning electron microscope ; Nanotechnology Polymer composites and self-healing ; Electrospun Nanofibers in Biomedical Applications ; Advanced Sensor and Energy Harvesting Materials
Authors: Rishikesh Ranade | Haiyang He | Jay Pathak | Norman Chang | Akhilesh Kumar | Wen Jimin
Source: arXiv (Cornell University) (preprint, 2022-09-10)
Field: Materials Science — Materials Chemistry

A Thermal Machine Learning Solver For Chip Simulation Thermal analysis provides deeper insights into electronic chips behavior under different temperature scenarios and enables faster design exploration. However, obtaining detailed and accurate thermal profile on chip is very time-consuming using FEM or CFD. Therefore, there is an urgent need for speeding up the on-chip thermal solution to address various system scenarios. In this paper, we propose a thermal machine-learning (ML) solver to speed-up thermal simulations of chips. The thermal ML-Solver is an extension of the recent novel approach, CoAEMLSim (Composable Autoencoder Machine Learning Simulator) with modifications to the solution algorithm to handle constant and distributed HTC. The proposed method is validated against commercial solvers, such as Ansys MAPDL, as well as a latest ML baseline, UNet, under different scenarios to demonstrate its enhanced accuracy, scalability, and generalizability. Solver ; Scalability ; Autoencoder ; Computer science ; Chip ; Thermal ; Generalizability theory ; Finite element method ; Constant (computer programming) ; Computational science ; Simulation ; Computer engineering ; Artificial intelligence ; Deep learning ; Engineering Thermal properties of materials ; Advancements in Semiconductor Devices and Circuit Design ; Machine Learning in Materials Science
Authors: Hossam F. Nassar | Alzahraa Shaban | Amal Zaher | Taha Abdelmonein | Esaraa Salama | yasser gaber | Nabila Shehata | Reda M. Abdelhameed | Rehab Mahmoud
Source: Egyptian Journal of Chemistry (article, 2022-11-09)
Field: Chemistry — Inorganic Chemistry

Iron-trimesic metal organic frameworks as nano-adsorbents for tetracycline and Ceftriaxone contaminated wastewater effluents Antibiotics release has been identified as a series concern with adverse effects on the ecosystem. Nano-adsorbents are promising materials to remove antibiotics from wastewater effluents. In this work, iron-trimesic metal organic frameworks (Fe-BTC MOF) was synthesized and characterized by XRD, FTIR, SEM and TEM. Fe-BTC was then investigated as nano-adsorbent for tetracycline (TC) and Ceftriaxone sodium (CFTR) antibiotics. TC and CFTR are common antibiotics, which are extensively used by industrial activities and thereby are released to wastewater effluents. Fe-BTC MOF showed high adsorption capacity of 713 and 1284.6 mg/g for TC and CFTR respectively. This study aim to compares the uptake efficiencies for two drug residues. Single antibiotic residues adsorption tests showed that Fe-BTC MOF effectively takes up TC more than CFTR. The influence of pH, dose, concentration and time on the adsorption process was estimated. Such adsorption capacity of Fe-BTC will make it favorable for further environmental applications. Adsorption ; Effluent ; Wastewater ; Trimesic acid ; Ceftriaxone ; Chemistry ; Nuclear chemistry ; Metal-organic framework ; Antibiotics ; Environmental chemistry ; Organic chemistry ; Waste management ; Biochemistry Metal-Organic Frameworks: Synthesis and Applications ; Adsorption and biosorption for pollutant removal ; Nanomaterials for catalytic reactions
Authors: Walid Kamal Abdelbasset | Gopal Nambi | Safaa M. Elkholi | Marwa M. Eid | Saud M. Alrawaili | Mustafa Z. Mahmoud
Source: Food Science and Technology (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Application of neural networks in predicting the qualitative characteristics of fruits In this research, the quality properties of persimmon were predicted using artificial intellect techniques. The persimmon samples were transferred to a computer vision lab, room temperature of 24 °C and 22% RH. The samples were divided into three groups for temperature treatment. They were kept at three temperature levels of 5 °C, 15 °C, and 24°C (control group) for 72 hours. The sample was then placed at room temperature and was imaged every second day for a 14 day period. After imaging, each sample underwent destructive tests to determine their quality attributes, including sugar content, firmness, and pH. The results indicate that the neural network's predicted values of acidity, firmness, and sugar of persimmon were not statistically significant differences from their actual values. In predicting the acidity of persimmon, the sugar RMSE is more than the two factors of firmness and acidity. For this reason, the accuracy of firmness and acidity is higher than sugar. MAPE is 10.11, 20.81, and 6.03 for acidity, firmness, and sugar, respectively. The model for sugar indicates a high difference between the actual values and the predicted values. Sugar ; Chemistry ; Significant difference ; Control sample ; Food science ; Mathematics ; Horticulture ; Statistics ; Biology Spectroscopy and Chemometric Analyses ; Postharvest Quality and Shelf Life Management ; Water Quality Monitoring and Analysis