jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Zainab Talib Kasim | Rafid K. Abbas
Source: Al-Qadisiyah Journal for Engineering Sciences (article, 2022-09-30)
Field: Chemistry — Analytical Chemistry

Using special additives for decreasing the asphaltene content of missan crude oil In crude oil, asphaltene is one of the fractions that may be dissolved in aromatics like benzene or toluene but cannot be dissolved in alkanes like n-heptane, n-pentane, or petroleum ether (a mixture of alkane compounds). A typical difficulty in oil recovery and refinery processes is asphaltene precipitation, which happens when the oil stream's pressure, composition, or temperature change. So, the stability of asphaltene in crude oil needs to be looked at to find out how likely it is to form asphaltene so that it can be stopped and high treatment costs can be reduced. In the present study, saturate, aromatic, resin and asphaltene (SARA) analysis of Missan heavy crude oil from the (Omar River Field) was performed. Three additives were used to show their effect on asphaltene at different concentrations and temperatures. The additives included nanoparticles (nano ferric oxide red, nano silica oxide, and a mixture of nano silica and ferric oxide red) and the polymer fiberglass. The concentrations of the additives of the nanoparticles were (200 ppm, 3533 ppm, a867 ppm), (1667 ppm, 6667 ppm, 10000 ppm, and 16667 ppm) and (24000 ppm, 40000 ppm, and 48000 ppm) of nano-silica, ferric oxide red, and a mixture of nano silica and ferric oxide red, respectively, while fofiberglassss, 3733 ppm, 7066 ppm, 10400 ppm, and 13733 ppm) and measured at temperatures (5, 25, and 45oC) The best read I got was when it was used. 4.249% from origin to 6.375% after treating the percentage of asphaltene with 48000 ppm of ferric oxide red and nanoo-silica. Asphaltene ; Chemistry ; Toluene ; Ferric ; Heptane ; Oxide ; Organic chemistry Petroleum Processing and Analysis ; Enhanced Oil Recovery Techniques ; Hydrocarbon exploration and reservoir analysis
Authors: Belgacem Fissah | Hadj Belghalem | Messaoud Djeddou | Belgacem Mamen
Source: JOURNAL OF MECHANICAL ENGINEERING AND SCIENCES (article, 2022-06-30)
Field: Materials Science — Materials Chemistry

Critical thermal shock temperature prediction of alumina using improved hybrid models based on artificial neural networks and Shannon entropy This study investigates the potential of a simple and Hybrid artificial neural network (ANN) to predict dense alumina's critical thermal shock temperature (ΔTc). The predictive models have been constructed using two ANNS models (M1, M2). In the first model (M1), elaboration, physical and mechanical parameters have been exploited to build three ANNs, namely generalized linear regression (M1-GLRNN), extreme learning machine (M1-ELM), and radial basis function (M1-RBFNN). The second model (M2) has been built by the three models mentioned above incorporated by the Shannon Entropy (SE) method. To compare the performance of all the developed models, coefficient of correlation (R), root mean square error (RMSE), mean absolute percentage error (MAPE), and Nash-Sutcliffe efficiency coefficient (NSE) have been considered. It is found that M2-RBFNN model with (RMSE = 4.3526, MAPE= 0.3406, NSE = 0.9921, and R= 0.9960) had superiority to the M1-RBFNN model (RMSE = 4.7030, MAPE= 0.3003, NSE = 0.9908, and R = 0.9954). More importantly, the contribution of the present work is that prediction of ΔTc has been performed through the developed hybrid model (M2-RBFNN), which reduces the number of inputs from six to only four inputs and offers high accuracy for all the studied variables. Mean squared error ; Mean absolute percentage error ; Correlation coefficient ; Artificial neural network ; Coefficient of determination ; Mathematics ; Entropy (arrow of time) ; Linear regression ; Algorithm ; Statistics ; Biological system ; Computer science ; Artificial intelligence ; Thermodynamics ; Physics Thermal properties of materials ; Machine Learning in Materials Science ; Nuclear Materials and Properties
Authors: Fanghua Wang | Xuejing Mao | Fuli Deng | Ruiguo Cui | Lilang Li | Siyu Liu | Bo Yang | Dongming Lan | Yonghua Wang
Source: International Journal of Molecular Sciences (article, 2022-10-01)
Field: Materials Science — Materials Chemistry

A New Phospholipase D from Moritella sp. JT01: Biochemical Characterization, Crystallization and Application in the Synthesis of Phosphatidic Acid A new phospholipase D from marine <i>Moritella</i> sp. JT01 (MsPLD) was recombinantly expressed and biochemically characterized. The optimal reaction temperature and pH of MsPLD were determined to be 35 °C and 8.0. MsPLD was stable at a temperature lower than 35 °C, and the t<sub>1/2</sub> at 4 °C was 41 days. The crystal structure of apo-MsPLD was resolved and the functions of a unique extra loop segment on the enzyme activity were characterized. The results indicated that a direct deletion or fastening of the extra loop segment by introducing disulfide bonds both resulted in a complete loss of its activity. The results of the maximum insertion pressure indicated that the deletion of the extra loop segment significantly decreased MsPLD's interfacial binding properties to phospholipid monolayers. Finally, MsPLD was applied to the synthesis of phosphatidic acid by using a biphasic reaction system. Under optimal reaction conditions, the conversion rate of phosphatidic acid reached 86%. The present research provides a foundation for revealing the structural-functional relationship of this enzyme. Phosphatidic acid ; Phospholipase D ; Crystallization ; Chemistry ; Biochemistry ; Characterization (materials science) ; PLD2 ; Enzyme ; Organic chemistry ; Materials science ; Nanotechnology ; Phospholipid Enzyme Structure and Function ; Biochemical and Molecular Research ; Enzyme function and inhibition
Authors: Mingchun Fu | Xishan Yu | Shichao Ying | M Egbo | A Gupta | I Fidan | S Hasanov | A Khadak | B Subeshan | R Asmatulu | J Pappas | A Thakur | M Leu | J Paul | B Santhosh | E Ananthapadmanabhan | C Hu | W Hau | W Chen | B Chang | J Gu | Z Long | K Moyer | N Boucherbil | M Zohair | S Huo | S Yang | J Wang | K Mori | N Matsumoto | M Yabe | H Yu | G Liu | M Wang | A Zhou | Z Yu | H Wei | C Ajinjeru | V Kishore | X Chen | M Aoki | A Shundo | S Yamamoto | M Mahmoudi | S Burlison | S Moreno | T Uddin | A Chakraborty | A Khusro
Source: International Journal of Mechatronics and Applied Mechanics (article, 2022-07-13)
Field: Materials Science — Materials Chemistry

MECHANICAL PROPERTIES TESTING OF CARBON FIBER REINFORCED COMPOSITES the current research in the field of materials focuses on the analysis of the properties of carbon fiber (CF). There are relatively few studies related to the structural design of CF composite reinforcements in practical applications. In order to improve the traditional laminate structure of aircraft engine blades, CF reinforced epoxy resin matrix composites are used as the research object. Its surface modification method, toughening method, and molding process ae studied. Then, the laminate structure of aircraft engine blades is studied and designed based on CF reinforced epoxy resin matrix composites combined with the concept of bionics. The root, middle, and tip parts of the engine blade are designed with layered structure and angle. Finally, the mechanical properties of the designed blades are tested through experiments. The results show that among the threelayered design structures of the blade root, the bionic synchronous double helix structure of the blade root has the highest tensile strength, which is 419.13MPa. The bending strength of the leaf root bionic variable angle double helix structure is the highest, which is 1349.45MPa. Among the three-layered design structures in the blade, the biomimetic nonlinear structure in the leaf has the highest tensile strength and bending strength values, which are 468.23MPa and 1222.44MPa, respectively. Among the three-layered design structures of the blade tip, the tensile strength and bending strength of the blade tip bionic variable-angle double helix structure are the highest, which are 457.78MPa and 1126.33MPa, respectively. These results provide research experience for further improving the performance of aircraft engines. Composite material ; Materials science ; Fiber Carbon Nanotubes in Composites ; Occupational Health and Performance ; Winter Sports Injuries and Performance
Authors: Navneet Chaudhry | Damini Verma | Amit K. Yadav | Jai Gopal Sharma | Pratima R. Solanki
Source: Research Square (preprint, 2022-07-06)
Field: Materials Science — Materials Chemistry

Determination of ciprofloxacin using the Ziziphus mauritania derived fluorescent carbon dots based optical sensor Abstract The rapid determination and sensitive monitoring of antibiotics residues are critical challenges and highly essential for the protection of human and environment. Hence, in the present work, facile green synthesis of fluorescent carbon quantum dots (CDs) has been done using one step hydrothermal treatment of fruit exact of Ziziphus mauritiana for the first time, acting as natural source of carbon for optical determination of ciprofloxacin (CIP). These prepared CDs was used to selectively detect CIP, exhibiting high quantum yield of 30% at excitation wavelength of 340 nm. After the optimal parameters, the sensor gave the linear detection range from 20 to 100 µM along with limit of detection of 9.20 µM. The current work depicts the potential to effectively and rapidly determine other forthcoming environmental pollutants. Fluorescence ; Detection limit ; Carbon fibers ; Quantum yield ; Ziziphus ; Hydrothermal circulation ; Quantum dot ; Linear range ; Materials science ; Optoelectronics ; Nanotechnology ; Chemistry ; Chromatography ; Chemical engineering ; Optics ; Physics ; Botany ; Biology Carbon and Quantum Dots Applications ; Electrochemical sensors and biosensors ; Dye analysis and toxicity
Authors: Abu Sayeed Chowdhury | Julia Thom Oxford
Source:  (article, 2022-12-01)
Field: Materials Science — Biomaterials

Collagen a1 (XI) structure prediction by Alphafold 2 Collagen α1(XI) is a minor fibrillar collagen involved in the critical regulation of collagen fibrils such as nucleation, assembly, and regulation of fibril diameter. The amino propeptide domain of the collagen α1(XI) is retained on the surface of the collagen fibril for an extended period of time and may play a crucial role in the interaction with extracellular matrix glycosaminoglycans and other proteins during the process of fibrillogenesis. Understanding the mechanism of action of this protein will ultimately help us understand the organization and assembly of the extracellular matrix that underlies the structural integrity of connective tissues. Computer science Collagen: Extraction and Characterization ; Proteoglycans and glycosaminoglycans research ; Cell Adhesion Molecules Research
Authors: Chang‐Dae Kim | Inho Lee | Gwanho Yoon
Source: Journal of Flexible and Printed Electronics (article, 2022-08-01)
Field: Materials Science — Surfaces, Coatings and Films

Studies on General Deep Neural Networks to Predict Optical Responses of Multilayered Thin Films Burgeoning demand on the analysis of multilayered optical thin films yields an advent of the simulation methods to calculate the optical response of structures. Machine learning ensures expedite calculation once a model has been trained. Here, we present a basic structure of deep neural network to demonstrate a validity of machine learning-based approach by showing how well the trained models approximate the target optical spectral responses. The numerical simulations with several tunable conditions show the overall inclination of performance of the models. This study paves the way for using machine learning-based approaches to predict the spectral responses of optical thin films. Artificial neural network ; Computer science ; Artificial intelligence ; Deep learning ; Deep neural networks ; Machine learning Optical Coatings and Gratings ; Photonic and Optical Devices ; Thin-Film Transistor Technologies
Authors: Gökmen Sığırcık | Ömer Selim Yıldırım | Tunç Tüken
Source: Acta Metallurgica Slovaca (article, 2022-09-24)
Field: Materials Science — Materials Chemistry

ATMOSPHERIC CORROSION BEHAVIOR OF HOT-DIP GALVANIZED AND CONTINUOUS GALVANIZED STEEL Five years of outdoor atmospheric corrosion tests of hot dip galvanized steel samples were performed, for products of continuous galvanizing and after fabrication batch galvanizing processes. For the purpose of comparison between corrosion performances of these two different galvanizing process products, an industrial coastal area (Gemlik-Bursa/TURKEY) was chosen for outdoor testing, which fits into C4 type corrosive atmosphere definition, according to ISO 9223. Samples were studied in laboratory with accelerated salt spray exposure test and electrochemical methods. Corrosion products formed on exposed samples and cross section of coatings are analyzed by SEM. Lead is observed to change the corrosion characteristics of the coatings with change in constituents of environments. In saline electrolytes, alloying of lead is found to accelerate corrosion rate. This metal deposits as cluster on top layer of the galvanized coatings and acts as strong cathodes with respect to the zinc and accelerates the corrosion rate. It was determined that differences in dip and continuous galvanization processes cause dramatic differences in the elemental composition, morphology and regional hardness values of coatings. In the comparison of corrosion resistance, lower performance of the dip galvanized coating, although it is much thicker, has been shown due to the differences mentioned above. Galvanization ; Corrosion ; Metallurgy ; Materials science ; Zinc ; Coating ; Layer (electronics) ; Composite material Corrosion Behavior and Inhibition ; Structural Integrity and Reliability Analysis ; Concrete Corrosion and Durability
Authors: Afsar Jahan | Brij Kishore | H Nar | K Werle | M Bauer | H Dollinger | B Jung | S Molet | C Belleguic | H Lena | N Germain | C | S Shapiro | J Planquois | P Delaval | V Lagente | R Hautamaki | D Kobayashi | R Senior | C Le Qument | I Gunon | J Gillon | S Valenca | V Cayron-Elizondo | E Boichot | L Coussens | B Fingleton | L Matrisian | M Liu | H Sun | X Wang | T Koike | H Mishima | K Ikeda | T Watanabe | N Ochiai | J Fan | J Johnson | M Markus | B Dwyer | S Wolfrom | J Li | W Li | K Malakian | J Wilhelm | D Tsao | R Morales | S Perrier | J Florent | J Beltra | S Dufour | I Mendez | P Manceau | A Tertre | F Moreau | D Compere | A Dublanchet | M gara | I Bertini | V Calderone | M Cosenza | M Fragai | Y Lee | C Luchinat | S Mangani | B Terni | P Turano | L Devel | V Rogakos | A David | A Makaritis | F Beau | P Cuniasse | A Yiotakis | V Dive | P Ducrot | C Andrianjara | D Compre | A Denis | S Blais | P Cluzeau | K Court | J Hamon | M Prunet | A Rossello | E Nuti | P Carelli | E Orlandini | M Macchia | S Nencetti | M Zandomeneghi | F Balzano | G Uccello
Source: Journal of Chemical Biological and Physical Sciences (article, 2022-01-31)
Field: Chemistry — Organic Chemistry

Quantitative Structure-Activity Relationship Study on Arylsulfones as Matrix Metalloproteinase-12 inhibitors QSAR study has been carried out on the MMP-12 inhibitory activity of arylsulfones in 0D-to 2D-Dragon descriptors. The derived QSAR models have revealed that the average molecular weight (descriptor AMW), number of rotatable bonds in a molecular structure (descriptor RBN), complimentary information content index of 3 rd order neighborhood symmetry (descriptor CIC3) and average valence connectivity index chi-3 (descriptor X3Av) in addition to sum of topological distance between N and O atoms (descriptor T(N..O)) played a pivotal role in rationalization of MMP-12 inhibition activity of titled compounds. 5 th order Galvez topological charge index (descriptor GGI5), atomic polarizability weighted descriptor GATS6p and presence of secondary aliphatic amide functionality are also predominant to explain MMP-12 inhibition actions of arylsulfones. PLS analysis has also corroborated the dominance of CP-MLR identified descriptors. Applicability domain analysis revealed that the suggested model matches the high quality parameters with good fitting power and the capability of assessing external data and all of the compounds was within the applicability domain of the proposed model and were evaluated correctly. Matrix metalloproteinase ; Matrix metalloproteinase inhibitor ; Metalloproteinase ; Chemistry ; Matrix (chemical analysis) ; Computational biology ; Pharmacology ; Medicine ; Biochemistry ; Biology ; Chromatography Synthesis and biological activity
Authors: Yu Lv | Fujia Dong | Jiarui Cui | Ruiming Luo | Songlei Wang | Argenis Rodas‐González | Jie Hao | Sijia Liu
Source: Research Square (preprint, 2022-08-11)
Field: Chemistry — Analytical Chemistry

Fusion of spectral and textural data of hyperspectral imaging for glycine content prediction in beef using SFCN algorithms Abstract Glycine, the simplest free amino acid, is one of the most important factors affecting the flavor of beef. In this paper, a fast and non-destructive method combining near-infrared hyperspectral (900–1700 nm) and textural data was first proposed to determine the content and distribution of glycine in beef. On the basis of spectral information pre-processing, spectral features were extracted by the interval Variable Iterative Space Shrinkage Approach, Competitive Adaptive Reweighting algorithm and Uninformative Variable Elimination (UVE). The glycine content prediction models were established by partial least squares regression, least squares support vector machine, and the optimized shallow full convolutional neural network (SFCN). Among them, the UVE-SFCN model obtained better results with prediction set determination coefficient (R P 2 ) of 0.8725). Further, textural features were extracted by the gray level co-occurrence matrix and fused with the spectral information of the best feature band to obtain an optimized UVE-FSCN-fusion model (R P 2 = 0.9005, root mean square error = 0.3075, residual predictive deviation = 0.2688). Compared with the full spectrum and characteristic wavelength spectrum models, R P 2 was improved by 6.41% and 3.10%. The best fusion model was visualized to visually represent the distribution of glycine in beef. The results showed that the prediction and visualization of glycine content in beef were feasible and effective, and provided a theoretical basis for the hyperspectral study of meat quality monitoring or the establishment of an online platform. Hyperspectral imaging ; Partial least squares regression ; Variable elimination ; Computer science ; Residual ; Convolutional neural network ; Support vector machine ; Pattern recognition (psychology) ; Algorithm ; Artificial intelligence ; Matrix (chemical analysis) ; Mathematics ; Chemistry ; Machine learning Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Advanced Chemical Sensor Technologies
Authors: Vitor Silva Liduino | Gabriel Batalha Leoni | Simone L.D.C. Brasil | João Payão-Filho | Eliana Flávia Camporese Sérvulo
Source: Research Square (preprint, 2022-07-14)
Field: Materials Science — Materials Chemistry

Corrosion of Weld Heat-affected Zones Submersed in Seawater With Indigenous Microorganisms Abstract The corrosion behaviors of different weld heat-affected zones (HAZs) were investigated, comprising an API 5L X65 steel immersed in seawater with an abundant native microbial community. Before tests, HAZ physical simulations were performed at the peak temperatures of 700°C, 860°C, 1000°C, and 1350°C. Throughout 14 days of immersion, various planktonic bacterial groups associated with microbiologically influenced corrosion were metabolically active in the seawater. Desulfovibrio members were present in a considerable number of OTUs. Scanning electron microscopy showed an intense microbial adhesion and corrosion product deposits in all HAZ sub-regions and the control base metal coupon (BM). The electrochemical tests revealed that the corrosion behavior of all HAZ sub-regions and BM were indistinguishable. However, topography analysis showed different behaviors of pitting corrosion. The results revealed that the pitting resistance of the microstructure composed of cementite grains (700°C HAZ) was superior to that of other HAZ sub-regions. On the other hand, the microstructure composed of martensite and austenite grains (860°C HAZ) exhibited the worst pitting resistance of the weld joint, leading to a maximum pit penetration of 2.3 times greater than that pit on the BM. The changes in the HAZ sub-region sensitivity to pitting corrosion were attributed to variations in the microstructural composition. Metallurgy ; Corrosion ; Materials science ; Microstructure ; Pitting corrosion ; Seawater ; Martensite ; Welding ; Heat-affected zone ; Cementite ; Austenite ; Tempering ; Electrochemical noise ; Electrochemistry ; Chemistry ; Geology Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Dental materials and restorations
Authors: Yufan Li | Dongmei Fu | Xuequn Cheng | Dawei Zhang | Yunxiang Chen | Wenkui Hao | Yun Chen | Bingkun Yang
Source: Frontiers in Materials (article, 2022-12-08)
Field: Materials Science — Materials Chemistry

Developing a regional environmental corrosion model for Q235 carbon steel using a data-driven construction method Studying the impact of the environment on metal corrosion is of considerable significance for the safety assessment of buildings and the life prediction of equipment. We developed a new regional environmental corrosion model (RECM) to predict the atmospheric corrosion of Q235 carbon steel based on measured environmental data and corrosion rates obtained from one-year-long static coupon tests. The corrosion of metals varies depending on the environment; therefore, the ability of the model to distinguish such differences is crucial for accurately predicting corrosion. Herein, the regions in which the test sites were located were divided based on the basic principles of atmospheric corrosion. Furthermore, random forest was used to assess the importance of various environmental factors in the corrosion process within each region, which established a close relationship between corrosion and environmental conditions. Our results showed that the accuracy of the RECM is higher than that of the dose-response function of the ISO9223-2012 standard. The method of model construction can be realized automatically using a computer. Corrosion ; Carbon steel ; Environmental science ; Materials science ; Process (computing) ; Metallurgy ; Computer science Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Smart Materials for Construction